Thesis submitted to the Department of Civil Engineering of the. University of ....
Great Britain, for example, there were over 1,000 deaths a year even before the ...
ROAD ACCIDENTS IN DEVELOPING COUNTRIES
Thesis submitted to the Departmentof Civil Engineering of the University of Surrey in fulfilment of the requirement for the award of a Ph.D degree.
G. D. JACOBS L. R.I. C. M-Inst. H.E.
I,.
ABSTRACT
The aim of the work described in this
thesis was to obtain a greater
understanding of the problem of road accidents in developing countries.
The social
importance of road accidents in developing countries by comparing deaths from road accidents with deaths
was identified
from diseases thought to be of concern in the Third World. importance was assessed by reviewing cost-estimates of Asian and African
and casualty rates over various ten-year periods
were determined and countries for these abnormalities
levels
derived in a number
countries.
Trends in fatality
those countries
The economic
showing abnormalities
were investigated
concerned.
identified.
Reasons
data from disaggregated using
be found to related were rates
Fatality
to
of vehicle ownership, the higher the vehicle ownership the lower
the fatality
rate.
Regression equations derived were compared with
those for developed countries.
A detailed study was madeof road accidents in Kenyaand comparisons madewith results from Europe. The high incidence of fatal accidents, single-vehicle
accidents andthose involving injury to occupants of
commercial vehitles were noted.
Regression equations were derived which related rural accidents to geometric design features of the road.
Comparisonswith results from
developed countries indicated the high accident rates pertaining in the developing countries studied.
The pattern of road accidents in selected
urban areas was examined, areas of high risk identified
I
and relationships
established
between accident rates and levels of vehicle and pedestrian
flows.
Factors that might be contributory
to the high accident rates in
developing countries were studied - the road surfacdf, vehicle condition and road-user behaviour.
From these studies,
recommendations are put forward for dealing
with road accidents on a cost-effective relatively efficiently
basis, ensuring that what
small sums of money are available
in these countries
be spent in dealing with the problem.
ii
can most
ACKNOWLEDGMENTS
The work described in this
thesis was carried out in the Overseas Unit,
Transport and Road Research Laboratory and I would like
to thank the
Laboratory for giving me the opportunity
to undertake this project,
the Dire-ctor,
and Dr ED Tingle,
particularly
Mr A'S Silverleaf
head of
the Overseas Unit.
I would like
I.-o express my gratitude
to Mr P Gardiner,
Senior
and to Dr J Howe, formerly of the University,
Lecturer,
Surrey University,
for their
sustained and constructive
guidance, given throughout this
investigation.
I would also like
and in particular during the project
to thank my colleagues,
Mr P Fouracre, Mr I Sayer
Mrs M Bardsley for their cooperation and assistance and Mrs B Wilson who typed the thesis.
Finally I would like to thank the manypeople, throughcut the developing world, for their cooperation, without which the project would not have been possible.
4
III
CONTENTS Paqe
ABSTRACT
ACKNOWILEDGEMENTS
1 INTRODUCTION CHAPTER
CHAPTER 2 LITERATURE REVIEW
7
2.1
Introduction
2.2
Road fatalities
2.3
Accident rates in developing countries
10
2.4
Comparative accident costs in developing countries
13
2.5
Data collection
16
2.6
Accident rates in rural
2.7
Accidents in urban areas
22
2.8
Factors involved in road accidents
25
and other causes of death
and analysis
8
20
areas
CHAPTER AS A CAUSE 3 ROAD ACCIDENTS OF DEATHIN DEVELOPING COUNTRIES
30
3.1
Introduction
30
3.2
Sources of data
31
3.2.1 Definitions
32
3.3
Selection
3.4
Comparison of deaths from road accidents and from diseases
35
Trends in fatality rates from road accidents and from diseases, over time
38
3.5 3.6
and classification
of diseases
A study of medical records in Nairobi,
IV
Kenya
33
39
CONTENTS Page
3.7
3.6.1 A comparison of the number of patients receiving treatment for road accidents and various illnesses
48
3.5.2 The utilisation of medical and financial resources by road accident patients
49
3.6.3 The age distribution
50
of in-patients
Conclusions and discussion
52
4A STUDYOF ROADACCIDENTRATESIN DEVELOPING CHAPTER COUNTRIES
54
4.1
Introduction
54
4.2
Data sources
56
4.2.1 Definitions
56
4.3
Trends in vehicle ownership, fatality and injury rates
4.4
Fatality
4.5
Injury
4.6
Severity
rates
4.8
72
rates
76
index
4.6.1 Severity 4.7
63
index and medical facilities
Factors affecting
79 82
accident rates
4.7.1 Changes in fatality rates and motorcycle ownership
83
4.7.2 Pedestrian fatalities
84
4.7.3 Changes in the average number of casualties per accident
87
4.7.4 Accidents during daylight
89
Conclusions and discussion
V
and darkness
91
t
CONTENTS CHAPTER 5 COMPARATIVE ACCIDENTCOSTSIN DEVELOPING COUNTRIES
Page 95
5.1
Introduction
95
5.2
Accident cost results
96
5.2.1 The studies surveyed
96
5.2.2 Study results
96
5.2.3-Interpretation results
5.3
103
Somepoints of methodology
105
5.3.1 Base data
105 of accident statistics
6.4
114
114
Introduction
6.2 The need for accident records in road safety work 6.3
107 III
Conclusions
CHAPTER 6 ROADACCIDENTDATACOLLECTION AND ANALYSISIN DEVELOPING COUNTRIES
6.1
101
5.2.4 Comparison of road accident costs with gross domestic product (GDP)
5.3.2 Valuation 5.4
of the comparative
114
Types of document used for the reportin and analysis of road accidents .g
118
6.3.1 Accident reporting
118
6.3.2 Accident analysis
119
6.3.3 The UK system of accident reporting and analysis
119
Survey of existing data collection and analysis methods in developing countries
120
6.4.1 Examination of police forms or booklets
125
report
6.4.2 Examination of the accident analysis forms
vi
129
CONTENTS
6.5
6.6
The design of a data collection system for developing countries
Page
and analysis
131
6.5.1 Recommended police accident report booklet
132
6.5.2 Recommended accident analysis
135
form
6.5.. 3 Data processing
137
Discussion
138
7 AN ANALYSISOF ROADACCIDENTSIN KENYA CHAPTER
146
7.1
Introduction
146
7.2
Data cdllection
147
7.3
Data analysis
147
7.4
Results
150
7.4.1 The location of road accidents and casualties in Kenya
150
7.4.2 Road casualties
154
in Kenya
7.4.3 Road accidents in Kenya 7.4.4 The vehicles in Kenya 7.5
involved
in road accidents
165 169 171
Conclusions
CHAPTER OF ACCIDENT 8A STUDY RATESONRURALROADS IN COUNTRIES DEVELOPING
175
8.1
Introduction
175
8.2
Data collection-
176
8.2.1 Kenya data
176
8.2.2 Jamaica data
181
Analysis procedure
185
8.3
vii
CONTENTS 8.4
Results
187
between accident rate 8.4.1 The relationship flow vehicle and
188
8.4.2 The results 8.4.3 Multiple
8.5
Paqe
of the simple regression analysis
192
analysis
regression
190
8.4.4 Comparison of the Kenya and Jamaica results with those from other countries
196
Conclusions
199
203
IN URBANAREAS 9 ROADACCIDENTS CHAPTER
9.1
Introduction
203
9.2
Data collection
204
9.3
Accident rates in cities
9.4
The distribution
9.5
An analysis of the type of accident taking place in tile various cities
214
9.5.1 Casualties by class of road user
214
World Third the of
211
of accidents
involved
9.5.2 Types of vehicles accidents
in urban
9.6 A study of relationships between accident rates and vehicle and pedestrian flows 9.7
205
Conclusions and discussion
CHAPTER'10 INVOLVED THEFACTORS IN ROAD ACCIDENTS
219
222 234
237
237
10.1 Introduction 10.2 Accident investigation
on a regional basis
10-2.1 National studies
I
AII
239 240
CONTENTS
Page
10.2.1.1
Objectives
240
10.2.1.2
International
241
10.2.1.3
Road accidents in Kcnya
243
studies
244
Rural studies
244
10.2.2.2 Urban studies
248
10.2.2 District 10.2.2.1
comparisons
10.2.3 Local studies
255
10.3
The road surface as a factor
10.4
Vehicle factors
in road accidents
10.4.1 Vehicle testing 10.4.2 Tyre condition
10.5
in accidents
266
in developing countries
267 275
in Nairobi
10.4.3 The importance of seat belts
276
The human element as a factor
280
in road accidents
10-5.1 Alcohol and road accidents 10.5.2 Driver behaviour at traffic 10.5.2.1
282 signals
Non observance of red signal
10.5.2.2 Stopping behaviour on appearance of amber signal
10.6
258
284 284 293
10.5.3 Driver behaviour at zebra crossings
296
10.5.4 Pedestrian usage of
301
zebra crossings
302
Conclusions
CHAPTER 11 CONCLUSIONS
305
CHAPTER 12 RECOMMENDATIONS
308
REFERENCES
314
APPENDICES70CHAPTERS 3,4
and 9 ix
1.
Surprising
though it
Great Britain,
INTRODUCTION
may seem, road safety is a very old problem.
In
for example, there were over 1,000 deaths a year even
before the advent of the motor car. with over a third
of a million
By 1970 this figure
had reached 7,500,
people being injured.
i
In 1974, in those countries
of Europe makingreturns
accidents to the United Nations, injured
by motor vehicles.
55,000 were killed. and injuries
of road
90,000-persons were killed
and 1,800,000
In the same year in the United States over
Despite the enormity of these figures,
seem to have very little
road deaths
impact on the general public.
For some time comfort was taken, in most European countries, that the accident rate per vehicle-kilometre and it was conveniently
forgotten
travelled
in the fact
had been decreasing
that the absolute numbers of accidents
and the economic cost to the community were rising
steadily.
As late as
1968, Professor John Cohen expressed the view that a's a country we had the ability, that this disaster
but not the will, attitude
to solve, the road accident problem and
arose because we were not sufficiently
moved by
on the road.
'The pubZic conscience is more outraged by the discovery of a child
in death to stabbed a wood than by a count of 8,000 corpses on
the road in a period of twelve months.
A fatality
is the road on
Prosaic and unpleasant to think about, the less said about it Further,
the effects
on the public
road deaths do not affect
imagination
the better.
are not cumulative;
8,000
us twice as much as 4,000 road deaths'
During the last decade there has been a growing awareness in Western Europe and North America that the problem to be dealt with has
reached epidemic proportions comparable with any. earlier I
mass epidemics
For example, the United States military
or even war. 10,000 lives
forces lost
in the Vietnam war, understandably arousing national
because of the tragic persons were killed
nature of these losses.
Yet a similar
concern
number of
on the roads of the United States in just
over two
months in 1966.
Throughout Europe and North America we find a new resolve to come to grips with this
problem and to bring all
continuing
knowledge to bear upon it.
It is particularly
our scientific
interesting
to note that
many of the safety measures suggested in 1968 by Professor Cohen (to save lives)
have now been introduced
In comparison with the countries
in this country.
of Western Europe and North
America, the study of road accidents in developing countries
has been
Although much research has been carried
almost non-existent.
out on
the transport
problems of the Third World, mainly under the auspices i lending agencies, little of international emphasis has been placed on the problem of road accidents.
There may be a numberof reasons to explain why such an attitude prevail.
Firstly,
should
road accidents may be thought to be insignificant
comparedwith the (supposedly) more important problems of poverty, sickness and malnutrition.
Secondly, the road accident rate may be
considered low in developing countries and although it is likely in the future it is (hopefully)
insignificant
road accidents may be thought to have little
at present.
to rise
Thirdly,
in cost at present
developing countries. The object of much of the work described in this directed
towards disproving
the above points.
2
thesis
has been
In other words to show
that road accidents already constitute
a serious social problem, that
rates are high (and in many countries
are increasing)
costs are by no means insignificant.
Indeed, the loss to the developing
and that accident
country in economic terms from a road accident may be greater than at first
involved is not a representative
appears, since the population Many of the fatalities
cross-section. from the minority
occur to vehicle-users
people, such as doctors,
of qualified
businessmen, whose loss to the country is particularly
Earlier,,
figures were quoted which outlined
in Europe and the United States.
situation
who come
teachers, and serious.
the general accident
In comparison, the author made
a crude estimate that in the Third World there were over 100,000 people in road accidents in 1974 and over 1,200,000 injured
killed
figures -
that cannot, by any standard, be regarded as insignificant.
It
is useful
at this
such as 'developing
point
country'.
understand what is implied to provide
a clear-cut
or 'Third
definition.
although it
America.
Not all
is of little
in these regions
is quite
difficult of the
of South and
are 'poor'
and
of where they are to be found.
of the world is provided
lending agencies such as the World Bank, the
Asian Development Bank etc.
These organisations
tend to group countries
together according to the average level of gross national capita (G. N. P. /capita).
to
a definition.
Much of the aid to the poor countries through international
it
South East Asia and parts
an indication
value in providing
terms,
is-easy
Most of the poor countries
countries
geography provides
Whereas it
World'.
by such evocative
world are to be found in Africa, Central
by terms is what meant
to consider
Thus the poorest countries
3
product per
of the world 'are
often grouped as those with a G.N. P./capita The British
Ministry
'developing'
if
less than $100 per annum.
of Overseas Development (ODM)regards countries
the average G.N. P. /capita
is less than $600 per annum.
Such values are perhaps the best way of defining is part of the Third World or not, but it whether $600 should be the criterion chosen figure.
arbitrarily
is still
or whether it
Furthermore, even if
levels
of interest
to decide
should be some other a country has a G.N. P. / receive aid from
The World Bank provides loans at various
that depend on the relative
Thus another criterion
whether a country
difficult
capita greater than, say, $600 per annum it may still donor agencies or countries.
as
wealth of the country.
thdt could be used would be the level of interest
charged by the World Bank.
During the early work described in this
thesis,
the author took
the level of vehicle ownership to be the most appropriate criterion
and a
developing country was taken to be one with a vehicle ownership level of less than one vehicle per 10 persons. Later in the work the ODMcriterion G.N.P./capita less than $600 per annum- was used. Whatever definition is used, the really poor countries of the world will always be included and it is only countries such as Cypruss Singapore etc that will
appear
borderline.
In 1971,, during the early stages of this research work, the author soon discovered that there was a lack of reliable available
in developing countries.
and analysis However, total
A detailed
road accident data
survey of data-collection
procedures adopted by developing countries accident statistics
numberof fatalities,
were available;
confirmed this.
that is,
the total,
casualties and accidents taking place each year.
%I_r
4
-
These data have been used to calculate developing ccuntries
in trends accident rates and
so that the magnitude of the problem could be
identified.
In order to study accidents investigate
in urban and rural
road-user behaviour in cities
areas or to
of the Third World, visits
Kenya, Malawi, Thailand, to by the author were made Ghana and Malaysia during the period 1972-1976. from data obtained other countries, were channels, Finally,
items as accident costs. 50 developing countries
questionnaires
Indonesia, Turkey,
Through official particularly
were sent to over
to obtain basic road statistics,
statistics
information and
collection
and vehicle-inspection
The cycle of attitudes
on subjects
on such
accident
data such as road accident
methods used in developing countries.
to the road accident problem gone through
by the countries of Western Europe are now repeating themselves in the Ihird. World. Perhaps twenty years ago the problem hardly existed, a decade ago it was not knownto
exist.
Five years ago there was an
awakeningto the growing problem, whilst today there is gcnuine concern and, with their experience built
up over years of dealing with the
subject, the advice of the developed countries is being actively
sought.
Detailed research, similar to that carried out by the author in Kenya, is needed so that more information can be obtained of where accidents occur, to what class of road user and what kind of accident. The thesis describes how areas of high risk in urban and rural areas were identified
in Kenya,,Jamaica and Indonesia and relationships
which need to be tested and verified
5
in other parts of the world.
derived
As is shown in the thesis, problems virtually
cuur.tries
unknown in Europe and road safety features used for
example in Great Britain
are relatively
Much more work is needed on the subject, countries
themselves.
step, hopefully
of the Third World face
ineffective particularly
in these countries. in the developing
The work described here is no more than a first
in the right
direction.
6
2.
LITERATURE REVIEW 2.1
INTRODUCTION
The object of the research described in this thesis was to obtain a greater understanding of the problem of road accidents in developing countries.
By studying accident rates and trends, comparing deaths
from road accidents with other causes of death and analysing the cost of road accidents in these countries, perspective.
the problem could be put into
By studying accident statistics
in detail,
a clearer
understanding could be obtained of what type of accident is happening involved.
to what class of road user, and the type of vehicle such as the condition
Factors
of the road, the vehicle and also road-user
behaviour needed to be studied so that the major contributory
factors
in accidents taking place in the Third World could be identified.
Over the period 1971-1976, the author found that very little
work
had been carried out on the subject of road accidents in developing countries.
Indeed, when comparedwith the amountof research carried
out on subjects such as vehicle operating cosis, project appraisal etc. it appeared that road safety was a muchneglected subject.
Consequently.
almost all the work described in this thesis on road accidents in developing countries, was carried out by the author.
It was essential,
however, that relationships
derived in the
developing world, be comparedwith similar relationships
obtained in
Europe and North America so that they ca'n be put into perspective. For example, a rate of 40 injury-accidents
per kilometre of road per
annumon a busy shopping street in Indonesia, is only seen as an extremely high rate when comparedwith shopping streets in Great Britain,
7
where, for a similar
level of vehicle
flow,
Most of the references given in this out in developed countries
work carried
the equivalent
value is 15.
thesis therefore, (mainly Great Britain
are to and the
United States) and have been used to make these comparisons.
2.2
ROADACCIDENTFATALITIESANDOTHERCAUSES OF DEATH
One of the most comprehensive studies oý the health problems of the 5 developing world was carried out by Bryant in 1968 - 69 In this study, Bryant reviews the general health situation and uses the results 4 of World Health Organisation (WHO)surveys to identify the diseases which are of particular America.
concern throughout Asia, Africa
There was found to be some variation
parts of the world but in general,
tuberculosis,
and South
between the different smallpox, dysentery
etc. created serious health problems in most of the developing world.
Having identified
JChemost important causes of death, the author
then made comparisons between the number of deaths in selected countries from these diseases and from road accidents.
Information on the numberof deaths from the different
diseases
2 was obtained from the United Nations DemographicYearbooks 1963 - 1972 These publications gave (for a selection of countries throughout the world) the total numberof deaths taking place in a given year and details of cuases of deaths, such as the numberof people dying from various diseases or in certain types of accidents.
Using these data,
information was obtained on the numberof deaths from diseases causing particular
concern in the Third World in about eleven developing countries.
8
Information
deaths from the of road accidents were on number Road Federation (IRF) publication
obtained from the International 'World Road Statistics".
- In Bryant's he classified
study of the health problems of developing countries,
various diseases into groups and in Hong Kong, for examples
studied the change in the number of deaths from these groups of diseases over time.
The groups of diseases were infect -ious, intestinal circulatory
neoplasmics respiratory,
and diseases of the nervous system.
He showed, for example, that over the period 1950 - 1965s that deaths from infectious, whilst
intestinal
and respiratory
those from circulatory
diseases were decreasing,
and neoplasmic diseases was increasing.
The author was able to make similar
studies in four developing countriess
comparing changes in death rates from the above groups of diseases with deaths from read accidents.
After of patients
reviewing Bryant's receiving
work, the author made detailed
in-patient
hospital
analyses
treatment from diseases and
also from road accidents in Nairobi by studying unpublished medical records of the three major hospitals in the city.
Havard6madea comparison of deaths from road accidents and other causes of death in Europeancountries, illustrating
in particular,
the fact that road accidents are the major cause of death for young males in the 16 - 24 years age group. Results obtained by Havard in Europeancountries were comparedwith those from developing countriesq obtained by the author.
9
2.3
COUNTRIES ACCIDENTRATESIN DEVELOPING
13 In 1948, Smeed studied the relationships fatality
rates (per licensed vehicle)
of population)
between road accident
and vehicle ownership (per head
in 20 developed countries,
1938data for the year using
An equation was derived as follows: (VF
where
0.0003 (V/p)-0.67
F=
fatalities
V=
number of vehicles
P=
population
from road accidents in use
33,119 14, Further research by Smeed showed that the above relationshipq derived using data for the year 1938, was still for data from many countries
fit a remarkably good
as late as 1968.
Smeedused this relationship
to show that the future numberof
road deaths in a country can be predicted from a knowledgeof the future numberof people and vehicles in that country.
F=0.0003
Thus:-
(VP2)0.33
WhereF. Vj P are as defined above. I
In 1972, the author8 derived an equation similar to that obtained by Smeedby taking fatality
and vehicle ownership levels in 32 different
developing countries for the year 1968. It was not the author's intention to use the equation to predict future numberof deaths but to use it as a basis for comparison of accident fatality
10
rates in developed
The equation derived by the author: -
and developing countries..
F=0.0007 v showed that fatality similar
(V/p)-0.4
levels of vehicle
ownership.
of road accident fatalities
Smeed" also found that definitions varied in some countries
from that recommendedby the United Nations
Economic Commission for Europe (ECE). for fatalities
adjustment factors ECEdefinition.
for
in developing countries were greater rates
Furthermore, he calculated
for those countries
the
not'using
by the author. used were subsequently
These factors
Jeffcoatel5 madea detailed analysis of fatality ownership rates in Great Britain
and vehicle
1938. 1909 the period over -
in the
Similarlyý Dondanville16 madea study of similar relationships United States over the period 1912 - 1967 and comparedresulting equations with fatality different
in many and vehicle ownership rates existing
countries throughout the world in the year 1967. Dondanville
showedthat the relationship
between fatality
rate and vehicle
different for 1967 derived 1912 in USA the to that was similar ownership countries for 1967. The author used these studies to comparerelationin those derived in Britain States Great United the ships with and developing countries. 13, derived by Smeed31
Reasons for the existance of the relationship 17. Someexplanation is required were put forward by Garwood that as a country,
or group of countries,
experience increasing
ownership, there is a decrease in the fatality suggests, more vehicles vehicle
conflict
should me-ana greater
and hence the likelihood 11
of the fact
rate.
vehicle
As Garwood
possibility
of vehicle-
of more accidents.
17 Garwood suggested that the reasons for the fal*l in the total per vehicle mile in Great Britain
number of casualties
(1)
the decreasing proportion
(2)
pedal cyclist
of two-wheeled motor traffic; is not included in
and pedestrian travel
the assessment of vehic-le miles but their not increasing
were: -
are
casualties
at as fast a rate as in the total
of
other casualties; (3)
the number of pedestrian casualties mile for the different
per motor vehicle
classes of vehicle
is falling.
18 by Garwoodand Johnson
These and other points were investigated 11,14 'who confirmed the validity and Smeed of the above points made by Garwood. Unpublished data from different
developing countries
were
used by the author to see whether the above points also applied to countries
of the Third World.
Smeedmade a study" (per licensed vehicle head of population)
of the changes in fatality
and casualty rates
and per person), and vehicle
(per ownership rates
9-year a over p,.,riod in 15 mainly developed countries. this over and casualty rates
He found that percentage changes in fatality period were not related that in all vehicle
to changes in vehicle
but one of the countries,
fell
whilst
in all
ownership.
the fatality
the countries
vehicle
He also found
licensed rate per ownership rose.
The
analysis was repeated by the author8 for a number of developing countries and countries
showi,ng abnormal trends in fatality
The severity
indlex, ie the proportion
, fatal was studied in detail
in Great Britain
12
of all
identified. were rates
casualties
that are
in the publication
10 Yearbooks
84
'Research on Road Safety . Using the United'Nations' 1, and the IRF yearbooks were obtained by the similar relationships 8 In this analysis, further author in a number of developing countries. insight
into the reasons for high indices in developing countries
obtained by using information
on the medical facilfties
These data were extracted 2. Demographic Yearbooks these countries.
were in
available
from the United Nations'
In a detailed
trafiic review of'rural census procedures used by 9 developing countries, Howe found that few countries carried out comprehensive national
and trend censuses.
was not able to convert numbers of fatalities
million
Consequently the author into fatality
rates per
vehicle kilometres travelled.
2.4
COMPARATIVE ACCIDENTCOSTSIN DEVELOPING COUNTRIES
The very problem of valuing road accident costs is a contentious 20 economic issue. Mishan19and Adams have argued that the techniques commonlyused have little is the inability
validity
from a theoretical
It
standpoint.
to ask a person what value he places on his life
that forms the basis of Mishan's criticism. between costing a certain
There is clearly a difference
number of accidents that will
probably take
place tomorrow, and asking people how muchthey would pay not to be 21 killed in a road accident. -On the valuation of humanlife, Goodwin argues that objections clearly
specified
society would find
be may avoided, if
if only not overcome,
that the monetary value arrived it worthwhile
it
at is a minimum that
spending in order to avoid a fatal
accident.
13
Whatever difficulties
there may be in costing road accidents,
attempts have been made in Great Britain
to derive the overall
annual
since before the war. The first estimate at 36 in down based TRRLwas derived by Reynolds set and was on procedures cost of road accidents
in 1947 to the Minister
a report
of Transport.
This could be defined
income approach and the costs which were included could
as a national
be divided into two groups: those that cause a diversion resources, and the losses of future Amongthe former are, repairing
output because of death or injury.
damageto the vehicle
medical treatment and the adminis tration
property,
of current
and other
of insurance,
police
and the law.
23 In 1967 Dawson produced a comprehensive report on road accident 36 Britain, costs in Grea-'%, using the methodology outlined by Reynolds In this
report Dawsonsuggested that loss of output should be estimated
using the 'net' loss of future difference injured,
In this method, the measure required of the
output is its
between the future
net present day value, which is the loss of output of those killed
assuming an otherwise normal expectation
the future of life,
approach.
consumption of those killed,
and
life, of working
and
assuming a normal expectation
both having been discounted to give present day values.
24 A further report by Dawsonin 1971 showedtwo significant differences from that produced earlier. 'net'
In the later report, the
approach described above was changed to a 'gross'
in the case of a road death,, future from future approaches. differentiate
loss of output.
method wheres
consumption was not subtracted
Arguments have been put forward for both
Also, in the second analysis,
no attempt was made to
between various age and sex groups.
14
I
in the later cost of suffering relatives
24 work by Dawson , an attempt is made to assess the and bereavement experienced by the friends
Such assessments can only be made
of road accident casualties.
on a subjective
and
basis.
In an attempt to determine how various developlng countries road accidents, this
the author reviewed the studies thdt had been made on
subject in a number of countries.
different
cost
definitions
Within the limitations
employed, the different
the dates of the studies,
factors
of the
taken into account,
the methods of measuring costs and the
currency of measurement, the various studies were compared and general conclusions reached.
26 (apart from those for Ivory Coast and South
Most of the studies
Africa30 ) wereconcerned with establishing
injuries
associated with road traffic
he number of deaths and 4%-.
accidents, valuing the resulting
loss in output and vehicle damage, and summingthe valuation and damageto give a total
Injuries 26 employed a slightly study
accident cost.
The Ivory Coast
. data format which meant that
different
total accident costs could not be derived. derived unit costs of injuries
of all
30 The South African study
and vehicle damageas well as total
accident costs; the method of deriving the costs was by sampling the insurance paymentsmadeto the accident claimants.
The Kenyan study information.
25
incorporated
both accident and casualty
This was useful since it
provided a means of specifying
the probable number of persons with different
types of injury
be involved in different
In this way, the costs
of different
types of accidents.
types of injuries
and accidents can be assessed.
15
who will
In the
Turkish studies,
33,34
are documented, the number of serious and slight on assumptions about the severity
Adler
22
based were
injuries
index.
has suggested that for less developed countries,
valuation
of life
is likely
to be of minor significance
road investment in rural
the
in fatalities
is not necessary because the reduction
be derived from transport
compared with other benefits
investment.
to
This approach may be true of
areas but is hardly true in urban areas where
managementschemes are designed specifically
traffic
and injured
numbers of killed
although the total
to obviate
32 accident black spots. The above studies together with those from Ghana 9 28 Thailand27 and S. Rhodesia in 1963-64 have all showed that accident costs in developing countries
2.5
are a significant
cost item.
DATACOLLECTION ANDANALYSIS
have been given of the method used in Great 84 Britain to collect and analyse road accident data In a Paper on 73 Sabey describes the main uses of accident analyses in Britain,
Numerousdescriptions
national
data and the role played by the various organisations
Thus, information a booklet,
on accidents
transferred
is collected
on to a standardised
by the police by means of form, the Ministry
Transport STATS19 'Report on a road accident resulting injury',
involved.
of
in personal
and then on to punched cards or data tape for analysis
by
computer.
Data retrieval
is- aided by special
main forms of analysis
required,
accidents with specific
details
programs developed for the listing
which are tabulations, and plotting
of locations
Such programs include RATTLE'Road Accident Tabulation
16
of
in map form. 37 Language' 9
38, developed at the TRRL and SPSS developed at the Edinb*urgh Regional Computing Centre.
73 According to Sabey the uses of national ,
(1)
-
to provide a means of assessing the need for and effect of national
(2)
data are fourfold:
legislation,
to provide an overall
picture
of the accident situations
'turn in gives a guide to where effort which
should be
directed
(3)
to identify
trends and to enable forecasts
to be made
to provide a basis for ccrriparison in regional and local studies
The above reasons are also valid
and in
in developing countries,
if developing by find countries to systems, any, are used out what order to collect and analyse road accident data, a survey was carried out of the methods used by 34 countries.
The results of the survey enabled. the author to makean assessment of the quality of data collection
by the and analysis procedures adopted
developing countries7.
Those countries responding to the questionnaire have not been referred
to separately
but replies
were received from: -
17
&
Bahamas
Kenya
Barbados
Ku wait
Belize
Malagasy
Botswana
Malaysia
Cyprus
Malawi
Dominica
Mauritius
Ethiopia
Montserrat
Fiji
Morocco
Ghana
Nigeria
Gibralter
St Helena
Guyana
St Lucia
Hong Kong
Sarawak
India
Seychelles
Indonesia
Singapore
Iran
Sri Lanka
Jamaica
Swaziland
Jordan
Zambia
From this survey, it was found that whereas data collection
by the
data developing the few is thorough, countries analyse police usually 7 collected in any detail and very few do so by meansof a computer
Someidea of the detail that can be extracted from a complete year's accident data can be obtained by an examination of the British Ministry of Transport annual publication In this publication, place in Great Britain
'Road Accidents in Great Britain
an analysis of the personal injury accidents taking each year are presented in considerable detail.
In this way a clear understanding is obtained of the types of accidents taking place, where, when and how they occur and to what class of road
user. 18
44
A similar
analysis
out by the author on the personal
was carried
accidents taking place in Keriya in 1972.
injury
Data collected
by the
author were supplemented by those obtained from urban transport studies 41 42 Using'traffic data from these carried out in Nairobi and Mombasa studies,
it was possible
to convert numbers of accidents in these urban
areas into rates per million
kilometres
vehicle
travelled.
Similarlys
accidents in rural
areas were converted into rates by using the results 40 censuses set up by Howe during the period 1967-1970
of rural traffic
The analysis
procedure used was that devised by Harris
TRRL. In this method, data are transferred
card; details
of the persons injured
involved are on a third
being punched for each vehicle
In order to identify
such
are on a second set of cardso the finally
details
of
set of cards, again with one card
involved.
unusual accident patterns in Kenyaqcomparisons
were madewith results from other countries. accident statistics
Thus details
of the accident are given on one
number, depending on the number of persons involved; the vehicles
at the
on to punched cards and each
accident has three sets of cards associated with it. as the date, time, place and location
37
Information on basic
in a number of European countries
from obtained was
the 1972 report on trends in road accidents from the Conference of Ministers of Transport. in Great Britain
Comparisonswere madewith accident patterns 44 using the annual report described above
During a visit to Ghana in 1972* the. author obtained an unpublished 46 report by Okyere on road accident problems in Ghana. In this report
Okyere analysed both accident rates and the distribution
of road
accidents taking place in Ghanain 1972. Unfortunately Okyere was not, able to obtain theAotal number"of injury accidents taking place 19
(only about 20 percent) were a representative
and it sample.
is doubtful
whether those collected
However the results
of this
survey were
in between accidents comparisons
used by the author to make tentative Ghana and Kenya.
2.6
Much work has been carried
ACCIDENTRATESIN RURALAREAS
out in Great Britain
to show that accident
roads can be related to the road geometry. As early as 47 1937, Bennett fatal accidents in Oxfordshire over a four studying .
rates on rural
showed that a large proportion
year period, related
in some way to the design
of the accidents were
of the road.
49,50 In 1946-47 Coburn studied the effect in rural
Buckinghamshire, particularly
curvature.
,
the effects
of horizontal
Coburn showed that as the radius of curvature of bends
decreased, the injury increased.
of road layout on accidents
accidents
An extensive
per million
investigat4on
vehicle
of rural
miles travelled,
in the accident rates
United States by Raff64 showedthat the accident rate was related to radius of curvature, as above and also to the width of the shoulders. Raff also found evidence that accident rates increase with increasing vehicle flow. per million traffic
Thus, on four-lane undivided roads, the numberof accidents
vehicle miles increased by about 50 percent as the meandaily
increased from the range 5,000
Even on roads built shown to exist
Hillier
10,000 to 10,000 - 15,000.
to a high standard, relationships
between accident rates and gradient
and Wardrop5l studied personal-injury
have been
and curvature.
accident rates on sections
of the MI, London to Birminghammotorway in 1963.. Where the gradient was upsthe-accident rate was slightly
20
less than on flat
sections; where
it was down, the rate was twice as high as flat'sections. influencing
A major factor
accident rate was found to be that of speed, affected
in turn
by the gradient.
A comprehensive analysis of the factors affecting rural accident 55 in 1972-73. Silyanov combined results rates was made by Silyanov obtained by numerous researches in different composite equations.
countries
For example, the first
per kilometre of road per annum to vehicle 56 57 583,59 in Russia Sweden and Australia ,
equation relating flow,
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It can be seen that,
as might be. expectedi in all
was an increase in the number of vehicles
countries
there
per person over the 10-year
period.
The number of fatalities countries injuries Britain
except in Cyprus where it per head of population
fell
except in
indicated
coefficients
Thus Uganda and Zambia had similar
vehicle ownership (28 and 29 percent respectively)
an increase in Uganda of only 29 percent.
values of
increases in
yet fatalities
Zambia increased by 239 percent over the 10-year period whilst
the changes in injury
and
rel'ated to changes in vehicle owner-
of rank correlation
approximately zero).
countries
The number of
The percentage changes in fatalities
do not appear to be closely
(Calculations
increased in all
by six percent.
also rose in all
where there was no change.
injuries ship.
per head of population
Similarly,,
in there was
in these countries
rates per Derson were 209 percent in Zambia and
8 percent in Uganda.
Table 4.1 also shows changes in fatalities vehicle.
This is a more useful indication
and injuries
per licensed
of the accident situation
in
any country over a period of time since it introduces an effect of 'exposure' to the vehicle population.
It can be seen that there is a
tendency for both rates to do-creasewith time. studied 15 sho%-., ed a decrease in fatalities in injuries
per vehicle.
Out of the 19 countries
per vehicle and 14 a decrease
Similar analysis by SwRed" showeddecreases in
15 out of 16 countries studied (only three countries were the sameas those studied here).
If there is a tendency for fatality
and injury rates per
licensed vehicle to decrease with time, those countries not showing this tendency may be experiencing unusual conditions. Kenya in particular
Zambia, Jamaica and
had considerable increases in the numberof fatalities
per 1i censed vehi cl e, and in these countri es it might wel 1 be that someof 60
the many features driver
training.,
necessary to reduce accident rates, enforcement of regulations,
for example,
improvement of vehicle
safety standards and of road design, are not being introduced, at the same time vehicle
ownership is increasing
rapidly.
whilst
Thus, by
examining trends over a period of time it may be possible to identify countries where the road accident situation
is not improving.
The analysis was repeated in 1975 using data over the period 1961-71.
Changes in vehicle
ownership, fatality
and casualty rates are
given in Table 4.2, and the basic data used given in Appendix Table 4.2.
It can be seen that there is again a tendency for bot-h fatality injury
rates (per vehicle)
on developing countries
to decrease with time,
The earlier
trend and in these countries
rates per licensed vehicle
increased over the 10-year period.
these countries
It is interesting
work
showed that Kenya, Jamaica and Zambia were-
notable exceptions to this
analysis
and
again exhibit
this
the fatality In this
trend as does Nigeria.
to note that in Kenya and Jamaica the fatality
rate per vehicle has, in fact increased at a much greater rate than the increase in vehicle
ownership.
An -analysis of road accidents taking
place in Kenya12in 1972 (see Chapter 7) showedthat over 80 percent of all accidents involved a single vehicle, a pedestrian or a cycle and thus under 20 percent involved two or more vehicles. therefore, it might be assumedthat fatality
rates might increase in -
direct proportion to the increase in vehicles. increase in fatalities
As an approximation
In Kenya, however, the
per vehicle was over two and a half times the
increase in vehicle ownership. Later in this attempt to identify
chapter a study is made of disaggregated data in an why the fatality
rate p*er vehicle
ing in these countries.
61
should be increas-
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4.4
Fatality
rates
The previous section examined the changes over time in the number of vehicles, it
and injuries
fatalities
is worth-while
in different
countries.
However
examining the absolute values of these quantities.
Using data for road fatalities,
vehicles and population for the 13 year 1938 from 20 developed countries Smeed derived the relationship
2/3 (V/P)0.0003 =
(F/V)
where F=
fatalities
from road accidents
V=
number of vehicles
P=
population
in use
Thus according to this equation,
in a group of countries,
the level of vehicle ownership, the lower the fatality
rate.
the greater The equation
for data collected by Smeedfor 16 developed countries 11 rangifig over the period 1957 -'66 and also for 68 different countries
was also a good fit
over the period 1960 - 6714.. In order to determine whether the fatality rate per vehicle
in developing countries
level of vehicle ownership, an analysis in 1971 on 32 developing countriess order to derive a linear fatality
is similarly was carried
related
to the
out by the author
using data for the year 1968. the logarithmic
values of the
rates were regressed against the logarithmic
values of the
vehicle-ownership
relationship
rates and the following
(F/V) The data and line
8
In
equation derived:
2/5 = 0.00077, (V/P)-
are given in Figure 4.1, and the basic data used
in Appendix Table 4.3 63
0 0 0 cli
0 0 0
CY
0
0
CY
\>
CCP C93 C"
CY
V; !!J. . od
c UD 0 c 0 #A
0 0 0
IAJ U. LA-
/071 0 u
9r
0
0
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14
4) V
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E
1
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0
Lai
010
CY CY LL.
00 cli
u00000
0 U)
IT
OOOOL iod sailgoloj
64
cri
It can be seen that the equation derived for developing counti-ies differs
With a doubling of vehicles
somewhat from the Smeedequation.
per person the Smeedequation implies vehicle of 37 percent whilst
Thus the Smeedequation predicts
per vehicle
The 90% confidence limits
per
for developing countries
the relationship
implies a decrease of 24 percent. larger decrease in fatalities
a decrease in fatalities
a
ownership rises.
as vehicle
for the regression
were calculated
equation derived for the developing countries,
see Fig. 4.1 (90 percent
of the points would be expected to fall
these limits.
points lie
below the lower limit,
low rates.
(It
within
suggesting that they have unusually
outside the 90% confidence limits,
care should be taken in drawing conclusions
were similar
from these points. )
per 10,000 persons and fatalities During this
period vehicle
from 33'vehicles
and the relationship
data for the developing countries It can be seen that all and are fairly
Fatalities plotted
for 1968, wi'th vehicle
per 10,000 vehicles
on the same graph as the
(see Appendix, Table 4.4 and Fig. 4.2)-ý lie
the points
close to the line.
within
the 90% confidence limits
This implies
experienced in the developing countries those experienced by'Britain
in Britain.
per 10,000 persons in 1909 to 670
vehicles per 10,000 persons in 1938. were calculated
per 10,000 vehicles
ownership levels
to those of the developing countries
ownership rising
and
15 for the years 1909 - 38
Data were then obtained for Britain
were calculated.
Some
should be noted however,, that on average one or two
points would be expected to lie
and the vehicles
)
that the fatality
in 1968 are not dissimilar
in her, early
rates to
stages of road transport
development.
(A similar
16 found that the'relationanalysis by Dondanville
ship between fatalities
per vehicle
and vehicles
per person in the US
65 I
1
(0
C%j
V) '1
t()
t) 4-
(0
c0 =U Lo c"
2
CA LAJ
vi 0 4) CO ca
C2
0 , Im 0 Ob
8
In
CL 0
e -Z: 0 In 00
Co 00 00
0 to C'V
0
CY
0
0N
Co
0 ,30im 0 Cj 0
CYI
8 CL 040 C" 3 C: 8 C" 0 L CL ca 0 o C3 Z:
cn LLLS
!a 00
0
CD C3 NC
0, 0
Ch.
od LIJ
0
1
(1
0 IN
CY
C2 Lai
.j LLJ
-L----L
n
uU V-DID1140A OOOOL Jad S211110103
66
for 1912 - 67 was comparable with that for various countries
of the
world for 1967).
Care must be taken in drawing conclusions since differences
in the distribution
developing countries
from these relationships,
could be an importanIt. factor,
annual vehicle distance travelled
in Britain
of population
or vehicles
and the
as could average
per kilometre
of road, for
example. In the earlier
work, developing
defined according to the level
of vehicle
now repeated for a group of countries Development definition
coUntries
were,, as stated
ownership.
The analysis was
using the Ministry
of Overseas-
(ie that of income level)
given earlier
using data for 1968 (see Appendix Table 4.5).
above,
again
The equation derived
was:(F/V)
0.43 = 0.00074 (V/P)-
As can be seen, this is very similar derived earlier,
little
indeed to the equation
the exclusion of the richer countries having relatively
effect.
In order to see whether the relationship
changeswith time, the
analysis was repeated for the samegroup of. countries, using data for the year 1971. (See Appendix Table 4.6).
The relationship
derived
wasas follows: (F/V) '=
0..000914 (V/p)-0.43
The two regression equations (together, with the values for 1968 and 1971) are given in Figure 4.3.
d
It can be seen that the slope of
67
m (a w
i2
ci 3: 0
0
CN v-
q-
i LU
0
13 000
0 0 c
0
/0
4
0
a, Lo
0
1-. C) C) CD
0/
/0 /0
ö
0.
C02 U), rýNi 4
(I
0),
, 0
Co (0 C» 1-
W
to (D
.2 0w
*>
0,
CP 00
0,
dy
00
/
LO
LL.
/0 Je
'cl,
.0
LO
C4 S013140A ()0()
C4
0L
68
1
1wcý LA.
the line has remained exactly line
itself
fatality
the same, whilst
has moved upwards.
at the same time, tile
In other words, the equation gives higher
rates in 1971,, than in 1968, for the same level
ownership.
By comparing the two regression
coefficients
of vehicle for 1968 and
1971, it
can be seen that there has been an average 24 percent increase in
fatality
rates for the same level
of vehicle
ownership.
Thus, over the short period 1968 to 1971, the situation in the developing countries, in over two-thirds
with the fatality
of the countries
worsened
rates actually
increasing
studied.
In order to determine whether the Smeedequation has changed with time, almost exactly
the same group of countries
were taken and relationships
used by Smeedin 1938
derived for the years 1950,1960 and 1970.
The equations were found to be as follows: -
1950
(F/V)
= 0.00034 (V/p)-0.58
1960
(F/V)
= 0.00034 (V/p)-0.60
1970
(F/V)
=
0.0003'9 (V/p)-0.56
The actual values for the different
countries,
(see Appendix
Tables 4.7.4.8
and 4.9) and the regression equations are illustrated
in Figure 4.4.
It can be seen that there was little
equations over the 20 year period. regression lines
calculated
variation
in the
Figure 4.5 shows the three
for developed countries,
for the years 19509
1960 and 1970, together with that derived by Smeed using 1938 data. Again, it can be seen that there is little variation between the four equations,
the Smeedequation fitting
the year 1970.
69
very closely
indeed, data for
) )
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j
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sal3! qOA 000 Ol/Salljlele:
70
i
of T-
0.
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elf 0
CJ
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00 (0 cn
c31
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71
Sall! lele: j
rate in a country can be
It is not suggested that the fatality
'eXpIdir.ed' simply by the level of vehicle ownershipor that the equation is a completely satisfactory predictor of changesin fatality
rates over
time, since so few parametersare involved. For examplethe equation makesno allowancesfor changesin vehicle composition, the distribution of traffic
on an urban/rural basis or for changesin social behaviour.
In the above analysis
it
has been used simply to show that the relation-
ship derived for developing countries that for developed countries
(see Figure 4.5).
important,, in developing countries, short 3-year period,
with fatality
1971 than in 1968 (for developed countries
Perhaps even more
the relationship
changed over the
rates per vehicle
being greater in
the same levels
the relationship
from
would appear to be different
of vehicle
ownership)s whereas in
between the fatality
rate and
vehicle ownership has hardly changed in over 30 years.
4.5 - INJURYRATES
For each of the 32 developing countries the number of injuries was calculated,
(serious
selected
per 10,000 vehicles
and slight)
see Appendix Table 4.10.
in the initial
The logarithms
obtained were regressed. against the logarithms, of vehicles persons in each country but in this
relationship
case no statistically
was obtained, even at. the 10 percent level.
rates were found, to be. significantly
ownership levels,
the injury-rates
were'not
Values of injuries
related
in 1968
of the values per 10,000 significant
the points using logarithmic *scales is given in Fig. 4.6. fatality
analysis)
The scatter of Thus although
to the vehicle
so related.
per, 10,000 vehicles and vehicles per 10,000 persons were obtained for Great Britain for the period 1909-1938, see Appendix Table 4.11. The logarithmic values of these data were found to be significantly related at the 5 percent level. Thus, although no 72-.
significant
relationship
countries,
a significant
Britain
different found for 32 the was was found to exist
relationship
and injuries
density,
per kilometre road. (at
obtained
and (log)
were examined for the developing countries
per 10,000 vehicles
population
were regressed
of paved road and finally The only
statistically
vehicles
(log)
for
per 10 kilometres'of
relationship injuries
road.
therefore that the injury1rates
physical and social
vehicles
per kilometre
vehicles
significant
level)
the 5 percent
against
in urban areas,
of population
percentage
in turn
of was
per 10,000 vehicles
is
This relationship
shown in Fig. 4.7 and the data in Appendix Table 4.12.
likely
for Great
over a number of years.
Further relationships
total
developing
It is quite
in each country depend on other
which ar,_1not easy to measure, and was obtained between injury rate and
characteristics
for this reason no relationship
vehicle ownership for the different
countries, whilst such a relation-
ship was found to exist for one country, namely Great-Britain,
over a
numberof years.
Furthermore whilst fatal accidents are fairly accuracy and reliability
of recording falls
severity of the accident. serious accidents and slight correlation
well recorded, the
drastically
with the
Therefore if it had been possible to analyse accidents separately, a significant
might have been found between serious accidents and vehicle
ownership for the different
' countries. Unfortunately serious and slight
I accidents were grouped together in all the data sources and this analysis
was not possible.
73
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4.6
The severity
SEVERITYINDEX
index is a measure of the proportion
that are fatal.
(fatal,
serious and slight),
country with a high severity These results
regression
level
and expressed as a percentage. index has a high proportion The severity
per 10,000 persons using logarithmic
of fatal
injuries.
index was plotted scales and the
It can be seen that as vehicle ownership rises the
index falls.
and all
Thus a
level, 0.1 the percent at
line was found to be significant
see Fig. 4.8. severity
divided by the number of casualties
ý. in Table 4. are given
against vehicles
casualties
for each developing country for
It was calculated
1968, as the number of fatalities
of all
Confidence limits
but two countries
were within
for Iraq lies
above the upper limit,
high severity
index for its
high proportion
vehicle
of road injuries
has an unusually low severity
The severity
these limits.
ownership levels
of injuries
index even if
it
below the lower limit.
It is unlikely
however as it
that are fatal.
is
A country
has a large number of fatalitiess
has a high number of casualties.
should not therefore
that iss a very
On the other hand Cameroon
are fatal.
index must not be misinterpreted
may have a low severity
The point
has it that an abnormally suggesting
index and lies
only a measure of the proportion
simply because it
were calculated
90% the at
The severity
index
be studied in isolation.
that the severity index is causally related directlY
to vehicle ownership, but more likely
that it
is related to other
factors which also change as vehicle ownership increases.
76
TABLE4.3 1968 SEVERITYINDEXFORDIFFERENTDEVELOPING COUNTRIES
Country
Total casualties
Fatalities
Severity index
Vehicles/ 1D$000 persons
1.
Botswana
20
229
8.73
77
2.
Ca-meroon
90
2,247
4.01
99
3.
Ceylon
589
8,337
7.17
118
4.
Chile
ls448
25,485
5.68
303
5.
Cyprus
117
3,148
3.72
IS090
6.
Dahomey
102
18.41
68'
7.
Ethiopia
583
3,598
16.20
22
8.
Gambia, The
27
317
8.52
95
9.
Guyana
125
2,080
6.01
452
554.
10.
India*
9,734
61,111
15.93
23
11.
Indonesia
2,328
13,338
17.45
54
12.
Iraq
827
2,407
34.36
157
13.
Ivory Coast
362
4,688
7.72
204
14.
Jordan
197
2,267
8.69
123
15.
Kenya
670
5,599
11.97
100
16.
Kuwait
206
2,829
7.29
1,917
17.
Madagascar
148
2,778
5.33
ill
18.
Malawi
152
1,699
8.95
40
19.
Malaysia (W)
719
8$553
8.41
591
20.
Mauritius
80
1$928
4.15
257
21.
Morocco
ls305
21,775
5.99
187
22.
Niger
79
516
15.31
16
23.
Pakistan
1,650
6,779
24.34
18
24.
Portugal
13,183
24,716
4.79
830
25.
Rhodesia
480
6,133
7.83
603
26.
Singapore
312
9,576
3.26
1,241
27.
South Africa
5,810
60,321
9.63
1,006
28.
Swaziland
72
548
13.14
263
29.
Syria
337
2,002
16.83
93
30.
Tunisia
214
3$687
5.80
212
31.
Yugoslavia
2,703
41,427
6.52
443
32.
Zambia
617
5,660
10.90
'178
*
Figures for 1967
77
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II-
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AIIJOAiaS_
78
Severity
index and medical facilities
A comparison was made between the severity medical facilities
significant
index was plotted
the population
against the total
It can be seen that the severity
per available
index rises as
bed increasess i. e., as medical
hospital
level 90% the were at
becomeworse.
calculated
(see Fig. 4.9) and four points were found to lie The points
limit,
their
indices
population
The results
facilities
limits.
For
beds in each country and a regression
at the 0.1 percent level was obtained.
are shown in Fig. 4.9.
index.
thus lowering the severity
divided by the number of hospital line,
have been fatal-
which would previously
may now only be injuries,
each country the severity
As medical
(see Appendix, Table 4.13).
improve, casualties
facilities ities
available
I%--.
index and the level of
Tolerance limits
for Iraq and Niger lie being high for their
the outside
tolerance the upper above levels
of population
per
hospital bed.
Another measure of medical facilities, was compared with the severity points were plotted
significant,
population
per physicians
index (see Appendix, Table 4.13).
(see Fig. 4,10) and the correlation
this time at the 5 percent level..
Tile
found to be
There is again a general
increase in the severity index as the population per physician becomes larger,
i. e. as medical facilities
becomepoorer.
Tolerance levels at
the 90%level were added and here the point for Pakistan lies just outside the upper limit is likely
while the point for Iraq lies well outside.
that manyother factors govern the overall
index of severity
of road accidents in any country, the degree of medical facilities provided being important but only one of many factors.
79
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81 t
-9
RATES FACTORS AFFECTING ACCIDENT
4.7
It might, at first, vehicles
appear reasonable to assume that as the number of
increases in a country,
also increase,
analysis
conflicts
rates will
implies that vehicle-vehicle,
since more vehicles
even vehicle-pedestrian
and injury
the fatality
become more likely.
or
However$ the
in Section 4.4 shows that there is a tendency for the number
of fatalities
and injuries
to fall
per vehicle
with increasing
ownership. Reasons for this tendency were put forward by Garwood and 17 Munden in 1968. They showed that in Great Britain, whereas the total
number of casualties
for drivers
the rate per vehicle-mile vehicks,
per vehicle-mile
motorcyclists
travelled
fell
over times
of cars, other four-wheeled
and pedal cyclists
actually
rose.
The reasons
suggested for this were:
the have two-wheeled much riders and passengers of vehicles highest casualty rates per mile travelled,
but over time
they becomea decreasing proportion of the total traffic.
2.
pedal cyclist
and pedestrian travel are not included in the
assessmentof motor vehicle miles, but their casualties are not increasing at as fast a rate as is the total of other casualties.
3.
the number of pedestrian for the different
casualties
classes of vehicle
Thus, the decrease in fatality
per motor vehicle-mile is falling.
rates per vehicle over time in most
countries could mainly be due to the fact that vehicles with the highest accident rates are decreasing in numbers., and*that pedestrian accident 8,2
rates per vehicle of pedestrianisation pedestrian-crossing countries,
because decreasing kinds possibly are also of various better, to shopping areas, and also
of central
Using data from a number of developed
facilities.
Professor Smeed"wasable to confirm that the above points
suggested by Ganiood do have a significant
effect
fatality in on changes
and casualty rates over time.
As was seen earlier,
Kenya, Jamaica, Zambia and Nigeria
showed an
the to time, opposed as over
upward trend in fatality
rates per vehicle
downward trend exhibited
by most other developed and developing countries.
Applying the reasons suggested by Garwood above, to these countries, is possible
for example, that the increases in fatality
rapid increases in motorcycle ownership, or possibly pedestrian
fatality
due to are rates to the fact that
in is the most countries. case as
rates are not falling
In order to investigate
it
these and other factors,
a limited
amount of
disaggregated road accident data were obtained from the above countries, mainly in the form of annual statistical
4.7.1
Changes in fatality
abstracts.
rates and motorcycle ownership
Table 4.2 gave the changes in fatality
rates per licensed vehicle
over the 10-year period, 1961-71. An attempt was madeto determine the changes in the proportion of two-wheeled motor vehicles over this period. This proved somewhatdifficult,
because in early years, somecountries
listed only the numberof motorcycles (as opposed to total motor vehicles), later date.
but then listed
two-wheeled
all two-wheeled motor vehicles at a
However, comparable data were obtained for 16 countries
over the period 1962 - 1971. 0
Out of the 16 countries for which comparable data were available, the numberof two-wheeled vehicles expressed as a percentage of the 83
total
venicle
population
Those showing the greatest
nine.
in decreased and
increased in seven countries
increase were those where the fatality
rate had increased over time, namely Kenya, Jamaica,, Zambia and Malawi: Changes for these countries
A rank correlation
analysis
in fatality out on changes
was carried
moped and motor scooter ownership over timeq and
rates and motorcycle,
the two were found to be significanýly There would appear, therefore, fatality
in Figure 4.11.
are illustrated
rates per vehicle
related
(at the 5 percent level).
to be a relationship
between increasing
in these ownership motorcycle
and increasing
count!ries.
4.7.2
Pedestrian fatalities
In order to investigate ties and casualties injuries
changes in the proportion
that are pedestrian
to different
plus pedal cyclist,
fatali-
deaths and
classes of road user need to be recorded
Of the countries
separately.
of total
with increasing
fatality
rates per vehicle,
such a breakdown was obtained from Jamaica, Zambia and Malawi: but not for Kenya.
Over varying periods of time, ranging from six to nine yearss
it was found that the ratio
remained constant for Jamaicas decreased for
Zambia and increased considerably
for Malawi.
obtained by comparing peedestrian fatalities
A. similar
with the total
result
was
(ie excluding
pedal cycle casualties).
In a similar
analysis,
plus pedal cycle to total
Smeed" found that the ratio fatalities
and casualties
teen out of eighteen developed countries, this period, countries
the total
but one.
fatality
decreased in seven-
over- a 10-year period.
rate per licensed
It would seem, therefore,
84
of pedestrian
'that
vehicle
fell
During
. in all
the second reason
120
160 80
60
I,-
4C
2C
111111
0'
54 1955 56
57
71 1970 69 67_ 68 6_6 58 59 1960 61 62' 63 64,1965 Year
72
I
12
c 4ý :3 06 0 CL
10
8 0 0) C" 41 m CL to
OA
tu
4
u 0 41 0 2
541955 56
57
58
59 1960 61
62
63 64,1965,66 Year
67
68 69 1970 71
72 .
Fig.4.11 FATALITIES /10000 POPULATION AND MOTOR CYCLES AS A PERCENTAGE OF TOTAL VEHICLE POPULATION FOR KENYA,JAMAICA. ZAMBIA AND MALAWI 1954-1972
85
put forward by Garwood and Munden.,for the decrease in fatality per licensed vehicle, conversely,
applied to a large number of countries
rates but
did not decrease
in Jamaica and Malawi., where the ratio
rate per licensed vehicle showed an increase.
over time, the fatality
Garwood and Munden also pointed out that although the overall fatality
rate decreased over time in Great Britain
the risk
to a number of individual was increasing.
travelled
European countries,
categories
of road user per mile
Smeedalso noted this
were not decreasing,
decreased considerably6
rates for all
discrepancy apparent travelled
the rate for pedestrian
The overall
casualties
divided by the motor vehicle was for the total
effect
fatality
the fall
due to improved pedestrian areas, and possibly
in pedestrian
facilities,
to an overall
casualty
kilometres
and casualty
In Great Britain
classes of road-user combined, to fall,
and other countries,
for motor
(The rates for pedestrians were not true risks
but were the number of casualties travelled).
trend in a number of
and one of the reasons for this
is that although most rates per vehicle-kilometre traffic
between 1957 and 19669
rates is probably
pedestrianisation
decrease in pedestrian
of main shopping movement.
In Jamaica, Zambia and Malawi, road fatalities were categorised . by type, and it was possible to comparechanges in pedestrian and nonpedestrian fatalities
per licensed vehicle over the 10-year period.
In
Jamaica, the pedestrian rate increased over the 10-year periods and did so at the samerate as the non-pedestrian fatalities. In Zambias the pedestrian fatality
rate increased, but not as rapidly as the non-
pedestrian rate, whilst in Malawi, the pedestrian rate increased at a greater rate than the non-pedestrian fatalities.
86
Thus, another important fatality
rates in these countries
increase in
(as be that opposed to most might is increasing,
rate for pedestrians
the fatality
other ccuntries),
in the overall
factor
and
not decreasing.
4.7.3
Changes in the average number of casualties
All
per accident
the work described so far has examined numbers of people killed
and injured,
and not the actual
some of the countries
listed
number of accidents
in Appendix Table 4.2 the personal-injury
accidents taking place in 1961 and 1971 were obtained, licensed vehicle
accidents involving
and the rates per
(Most developing countries
calculated.
accidents i. e. including
For
taking place.
listed
total
damage-only, and did no-t give the number of
personal-injury),
For all the countries, except Kenya, the percentage change in accident rate over the ten-year period altered in the samemanneras the fatality
and injury rates.
Thus, in most countries,
injury and accident rates per licensed vehicle fell, period, whilst
the fatalityq over the ten-year
in Jamaica, Malawi and Zambia, the rates all increased.
As was seen earlier,
the fatality
and injury rates per licensed vehicle
increased in Kenya; it was found, however, that over the sameperiod of time, the accident rate decreased.
If the injury
and fatality
accident rate is decreasing, be increasing and injured casualties calculated,
over time.
rates are increasing, the number of casualties
whilst
the
per accident must
In other words, more people are being killed
per accident in 1971 than in. 1961.,, The number of per accident for the years 1960 to 1972,, in Kenya,, were and the results
are given in F_igure 4.12.
87
For comparison,
1.70
Kenya
1.60
1.50
1.40 Co
G.B.
CL
22 m
... . 0.
loo
1.30 Jamaica
i. 2C
1.1c
1.00 59 1960
61
62
63
64
1965
66
67
68
69
1970
72
Year' Fig.4.12 THE NUMBER OF CASUALTIES PER ACCIDENT OCCURRING IN KENYA, GREAT BRITAIN, AND JAMAICA, 1960-1972
88
73
from Jamaica and Great Britain
results
are also illustrated.
It can be seen that the rate increased almost 60 percent in Kenyaq remaining fairly
whilst
in fatality
and injury
rates per licensed
in Kenya, from 1961
vehicle
to a higher vehicle occupancy rate in
to 1971, might be due, in part, 1971, than existed
Thus, the increase
constant in other countries.
in 1961, or possibly
to a certain
type of accident
becoming more prevalent. injury
accidents
For example, an analysis of all personal. taking place in, Kenyai, in 1972,, (see Chapter 7) showed
that the number of casualties
who were occupants of commercial vehicles
expressed as a percentage of the total European countries,
the equivalent
value is of the order of 5 percent.
This hi'gh rate to users of commercial vehicles to the use of open-sided lorries their
places of work.
increasing
to transport
When such a vehicle
large numbers of casualties
In
was almost 17 percent.
frequently
is probably due workers to and from
is invulved
in an accident,
It is possible,
result.
urban development in Kenya, that this
with
type of accident has
increased in recent years.
4.7.4
Accidents during daylight
and darkness
The road accident data in Kenya provided information on the number of casualties occurring during daylight and darkness.
From 1960 to 1972,
the percentage of casualties injured during darkness increased from 24 percent, to 33 percent (see Figure 4.13).
This increase is almost
certainly
due to a corresponding trend in the proportion of night-time
traffic.
As the accident rate is higher at night,
to the overall accident rate-increasing Little
this could contribute
over this period.
information was available from other 'countries
proportion of accidents occurring during daylight 89
on the
and darknesss but
40
4A 401
35
4m c
m
31 0 4).
2
58
59
1960
61
62
63
64
1965- 66
67
68
69
197o
Year, Fig.4.13 THE PROPORTION OF CASUALTIES DURING THE HOURS OF DARKNESS IN KENYA AND GREAT BRITAIN
90
71
72-
18 from 1958 to 1969 .
data were obtained for Great Britain
It can be seen that the proportion
also shown on Figure 4.13. casualties 1966.
This is
in dark hours also increased in Great Britain,
The proportion
of fatal
from 1958 to
in the dark fell
and serious casualties
in 1967, and again in 1968, possibly due to the introduction breath tests
and injury
of tile
(Road Safety Act, 1967) in October 1967.
4.8
This analysis
of
CONCLUSIONS ANDDISCUSSION
shows that there was a continuing
rates per licensed vehicle,
1961 to 1971 in the majority
downward trend in fatality
over the periods 1958 -to 1968 and
of the countries
but that Kenya,,
studied,
Jamaica, Zambia and Malawi were notable exceptions to this.
Detailed research in these countries is needed to obtain a full understanding of the accident patterns that exist, have been used to illustrate
but disaggregated data
leading be to factors that the someof may
increasing, as opposed to decreasing, fatality
and injury rates.
In the countries studied, there was found to be close correlation between changes in the proportion of two-wheeled motor vehicles on the road, and the changes in fatality ing the greatest largest
increases in fatality
type of vehicle
kilometre risks
Thus, countries show-
rates per vehicle
also had the
increases in the ownership of two-wheeled motor vehicles.
Research in Great Britain this
and injury rates.
travelled),
and other European countries
has a very high accident rate, (per vehicleand every effort
should be made to ensure that the
to users of two-wheeled motor vehicles
suggested that if
has shown that
it does not already exist,
on the use of safety helmets.
If legislation
should be made to enforce the regulations.
91
are minimised. legislation
It is
be introduced
already existss
efforts
In most countries, for the fatality
over recent years, there had been a tendency
and injury
rates to pedestrians
to show a considerable
decrease.
Zambia, Jamaica and Mala-wridid not show this decrease, and
pedestrian
rates increased often at a greater rate than that to other With increasing
road users. is particularly
pedestrians
and if
vulnerable,
is not possible,
precincts
road traffic
segregation by the use of pedestrian should bemade for
then adequate provision
to cross the road safely.
World use uncontrolled
in urban areas, the pedestrian
pedestrian
Most countries
crossings;
of the Third
studies in Kenya and
Thailand showed poor road user behaviour at these crossings. work, detailed
in Chapter 10, could be a major influence
This
on casualty
rates.
An analysis
of road accidents and casualties
showed that the average number of casualties place has increased by sixty
percent,
Users of commercial vehicles and the transportation
rate,
in open lorries
per injury-accident
ovey- the last
should be made to ensure that the over-loading place.
in Kenya (see Chapter 7)
ten years.
of'vehicles
taking Efforts
does not take
in Kenya seem to have a high risk
of workers to and from their
place of work
should perhaps be regulated.
In Kenya, the percentage of casualties occurring during darkness increased considerably between 1960 and 1972. This is almost certainly due to an increase in night traffic.
Accident and casualty rates are
higher during the hours of darkness so a change in the proportion of traffic
at night will
rates.
The work on road-user behaviour in urban areas, referred to above,
have an effect on the overall accident or casualty
92
has shown that very few pedal-cyclists at night (either
front
or rear).
in particular
The author concludes that efforts
should be made to ensure that vehicles time journeys,
and if
lights any show
are properly equipped for nightit,
the community can afford
that main roads have
adequate street-lighting. Fatality be significantly
found 'k. developed developing 0 were and countries rates -for correlated
with vehicle
ownership, the higher the level
of vehicle ownership, the lower the fatality-rate. by Professor Smeed, using data from different
developed countries,
the year 1938, was found to be a very good predictor for the years 1950,1960 and 1970. is clearly
different
The equation derived
of fatality
for rates
The equation for developing countries
from that derived by Smeed, the regression
line
having a lower slope.
The regression
line
calculated
for develcping countries
for the
year 1971 was above that calculated for 1968, the slopes of the two lines being almost exactly the same. In other words, the fatality
rates were
greater in 1971, than in 19689 for all levels of vehicle ownership. This implies that over the short period, 1968 to 1971, the situation worsened in developing countries.
has
Apart from the reasons put forward
above, such as changes in vehicle composition, or increases in night-time driving,
it is possible that the manyfactors neededto reduce accident
rates, such as improved junction design, vehicle maintenance and inspection, education and enforce'ment are not keeping abreast with the larger
increases in vehicle
ownership.
The severity indices in 32 developing countries for the year 1968 were found to be correlated with the vehicle ownership level, the vehicle ownership, the greater the severity index.
the lower
As has already
been pointed out, the quality of accident reporting varies greatly from
93
country to country with the quality of the accident.
severity
of reporting
The severity
up to 20 times higher than in Great Britain without
with the
indices in developing countries
may not be as high as they at first
therefore
falling
appear.
Since they are
for example, they are,
doubt high by European standards even when quality
of reporting
is taken into account.
Severity available hospital treatment,
indices were found to be related
in these countries. facilities
to the medical facilities
As might be expected, the better
the
or the number of doctors able to provide immediate
the less were the chances of a serious injury
fatality.
94
becoming a
ACCIDENTCOSTSIN DEVELOPING COMPARATIVE COUNTRIES
5.
5.1
INTRODUCTION
The purpose of this work was to collate infor-mation as exists
in comparative form such in developing countries,
on accident cost analysis
the methodologies employed and to indicate
to discuss briefly
some of
as regards data sources and definitions,
the problems, particularly
There is clearly
which have been identified.
no definitive
is the intention
for assessing accident costs but it
show what techniques might be usefully
methodology
of this work to
adopted to indicate
the level
of
accident costs in developing countries.
Accident cost analysis investment appraisal.
possible,
A transport
is clearly
reduces accidents if
is a well-established
part of road project
investment which, among other effects,
providing
an economic benefit
which should,
be measured.
The problems of measuring the benefits provide a contentious economic 20 have 19 argued that the techniques commonly issue. Mishan and Adams little have used
validity
is presented in the full
from a theoretical
standpoint.
knowledge that limitations
investment projects road comparing of purposes
This analysis
exist;
but for th e
or safety equipment and
data provides a useful cost measuring the accident of use procedures, tool life,
injury. On the destruction death, and valuation of for analysing 21 (if be "objections that may avoided not answered) Goodwin argues
only if
it
is clearly
specified
that the money value arrived
it find worthwhile that would society minimum a fatal
accident".
the content of this
It is this
at is a
spending in order to avoid
argument which has been adopted to justify
chapter.
95
There is a further
that for less developed countries because the reduction
raised by Adler
observation
the valuation
in fatalities
compared to the other benefits
is likely
22;
he has suggested
of life
is not necessary
to be of minor significance
to be derived from transport
investments.
While this argument may be true of road investments (new construction, realignment and resurfacing)
it
cannot be levelled
managementschemes designed specifically It is also evident, developing countries
as this
5.2.1
to obviate accident black spots.
work shows, that accident costs in
are a significant
5.2
against traffic
cost item.
ACCIDENTCOSTRESULTS
The studies surveyed
Information from seven studies in developing countries has been 23'24 have been included collated by the author. Data for Great Britain to give a comparative order of magnitude and also because the methodology employed in the British other studies.
(To all
studies provides a good base for discussing the 24 intents and purposes the study by Dawson
being used by the Department of the 25 Environment in Britain). The eight countries surveyed'are Kenya (1965)9 26 27 28 Ivory Coast (1970), Thailand (1963 and 1964), S Rhodesia (1961)1, (1971). 31 29,30 32ý 33,34 S Africa (1963), Israel (1967),. Ghana (1970) and Turkey
provides the methodology currently
5.2.2
Study results
Within the limitations different
of the, different, definitions
employed, the
factors taken into account, the-dates of the studies, the
methodsof measuring costs and the currency of measurement,Tables 5.1 and 5.2 set out the main results that, each.study has produced. 96
Table 5.1 describes the costs associated with each type of injury and the average material
damage costs incurred
Blanks in the Table indicate
in a road accident.
that the study concerned has either
costs or has included them under another
considered these particular
In no instance is any cost included for the grief
cost heading.
not
and
(Estimates have been made for suffering caused through a fatality. " 3,24 Britain" but are not included in the figures given here).
Distinction livelihood,
is made between the value of life
the valuation
The value of livelihood,
and the value of
of the former being a possibly therefore,
isoluble
presents only a partial
problem.
and minimum
sum that a person would forago in the event of his being fatally
injured.
to ask a person what value he places on his life 19 that forms the basis of Mishan's criticism of the techniques described (It
is this
inability
here).
Table 5.2 indicates
the average cost of different
types of road
accident and estimated total
accident costs for the country concerned.
Blanks in the table indicate
that results
form because the base data did not exist
cannot be presented in that in the study report which would
permit the necessary analysis.
Table 5.3 gives the percentage total
costs by major category, viz.
loss in output, medical costs and vehicle damages. The Ivory Coast and S African
data cannot be presented in this
form.
It should be noted that the Kenyan study employed *cost data at 1961 prices and accident data in 1965. Britian
Similarly
(1970) is based on 1968 accident
regards the Israel
the cost estimate for
figures'
and 1970 prices.
study only the aggregatq figures
and 5.3 have been obtained. 97.
As
shown in Tables 5.2
4
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5.2.3
Interpretation
of the comparative results
comparison of the absolute values given in Tables 5.1 and
Direct
5.2 would be misleading for the reasons to which reference has already been made. For example, even some of the British 1970 are not directly difference.
of a net loss in output (future
(12880) was measured on the basis
income less future
consumption) while
(E9960) was measured on the basis of a gross loss in
the 1970 figure output (future
income) of the fatally
and Turkish studies have similarly
injured
The Ivory Coast
person.
used gross loss valuation
while the
have adopted the net loss valuation.
apart from S Africa,
other studies,
study is based on insurance payments paid out to cover
loss of income, medical expenses, legal costs, etc on third
for 1963 and
comparable, and not simply because of the time
The 1963 cost of fatality
The S African
figures
party policy
damagecosts,,
vehicle
claims.
Apart from differences in the measurementof the losses there are also differences
in actual definitions
Thailand a serious injury short period in hospital
involves
of what is being measured.
either
permanent disablement or a
followed by convalescence and complete recovery.
The Kenyan and S Rhodesian studies do not include definitions different
categories.
For
The Ivory Coast data do not distinguish
slight and serious injuries,
although it may be inferred
results are based on hospital information)
of the between
(because the
that the figures quoted
concern mainly serious accidents.
in date of study and currency measurements are self23 Dawson noted that some comparison can be made using official
Differences evident.
exchangerates to convert local -currencies to sterling rates are frequently
not appropriate.
101 t
but that these
in study output,
Cespite such great disparities
and
valuation
definit Acn, some general conclusions have been drawn from the figures The average personal injury
given.
developing countries
tends to be high compared with Britain.
probably due to the high severity injuries
accident cost (Table 5.2) for
on the roads)
indices
(ratio
latter
distortion
will
bias were removed, it developing countries likely
of fatalities
found in developing countries
recording of minor accidents as mentioned earlier bias the severity is still
likely
to total
and probable under-
in this Thesis.
index upwards.
that the severity
Even if indices
The the
for
would be high compared with the UK index.
that one of the major reasons is the differences
facilities
This is
It is
in the medical
available.
Material damageunit costs (Table 5.1) show a fair
consistency in
order of magnitude from country to country apart from Thailand. scurce for the Thailand figures
are insurance payments made against
damageclaims and represent the cost per vehicle
per typical accident.
The
rather
than the cost
It might'b*e expected'that in developing countries
material damagewould be a significant
cost item; spare parts will
be
expensive, if only because they have to be imported, and the skilled labour necessary to effect repairs will 'be'at a' premium. Some supplementary information on vehicle damageunit costs for Kenya and S Afri ca is presented in Table 5.4. The former -were' col I ected by the author in Kenya in 1974 with the cooperation CompanyLtd.
102
of'the
Guardian Assurance
TABLE5.4 AVERAGE VEHICLEREPAIRCOSTSFORS AFRICAANDKENYA (Sources: National Institute for Road Research, S Africa Guardian Assurance Co (Kenya)) Slight damage
Heavy damage
Write off
Motor car Lorry
E120
1430
1550
E 38
E334
E705
Bus
1 14
E 83
E565
Vehicle type
S. AFRICA (1963)
KENYA(1970)
All
Both sets of figures
vehicles
1185-
the high cost of vehicle
underline
this respect the damage unit costs reported for lhailand Despite such lcw unit costs,
In
repair.
low. seem very
however, reference to Table 5.3 shows that
vehicle damagetotal costs represent a high proportion of total accident costs in Thailand. from Israel
This is true of all those countries analysed, apart
where only 17 percent of total
for by vehicle
damageand administration.
accident costs is accounted Thus, in general,
damagecosts are small in comparison to loss-in-output former are going to be very important
5.2.4
while unit
unit costs,
in assessing total
the
accident costs.
Comparison of road accident costs wAh gross domestic product
In Table 5.5 the aggregate figure the GDP(at market prices)
for accident
of the respe'ctive
cou'ntries.
There is no reason to suppose any direct GDPand total
accident costs;
are many other factors
in determining
of traffic.
can only be. used as an initial
causal relationship
a high GDPý, niay imply heavy traffic
involved
numbers besides the level
costs is compared with
th6 accident
"''Any'conclusions
guideline 103
between but there
rate and
drawn from Table 5.5
in view of the previously
noted
2 C:)
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123
TABLE6.2 The use of accident
Countries which supplied examples
report
documents by the police
Countries which have no system of reporting accidents
Botswana
Indonesia
Gibraltar
Nigeria
Countries which use a document for recording accidents but have not supplied examples
Countries which have not clearly stated whether any document is used or not
Ethiopia
Mauritius
Countries which nave not replied Gambia, The
Malaysia
Hong Kong
Iran
Ivory Coast
Swaziland
Kuwait
Sierre
Zambia
Dominica
Tunisia
Guyana
Jordan
Syria
Sarawak
Barbados
Niger
Bahamas
Madagascar
Pakistan
Belize
Seychelles
Malta
Sri Lanka
Morocco
Leone
Cyprus Fiji Montserrat St Helena St Lucia Malawi India Kenya Jamaica Singapore Ghana
B) Accident analysis forms
Countries which have supplied examplesof a form equivalent to the UKStats. 19 Sri Lanka Cyprus HongKong Morocco Singapore
Countries which do not use an analysis form
Countries which do not use an analysis form but have supplied an accident summarysheet
Ccuntries which have not stated clearly whether or not they use an analysis form
Bahamas Belize Guyana Indonesia
Fiji India Jordan Swaziland
Barbados Ethiopia
Montserrat Nigeria Sarawak Seychelles St Helena Za.-bia
Kenya
Gibraltar Iran Jamaica Kuwait Malaysia Malawi Mauritius Botswana St Lucia Dominica Madagascar
124
6.4.1
Examination of police
forms or booklets
report
In order to make a comprehensive examination of examples of documents supplied by developing countries,
accident reporting complete list
divided be that asked was possible questions might
of all
(corresponding
into 5 sections
the
accident would, in reality, "Administrative
roughly to the sections in which an
be reported). details
These were: -
and records of immediate action"
2)
"details
3)
"drivers,
4)
"space allowed for-statements"
5)
"site
of persons injured" vehicles
and passengers"
and statistical
and
information.
As can be seen from Table 6.3. of the samples of police documents provided,
report
8 are in booklet form, 13 are forms or file
and 4 have an additional
document for"damage-onlyl
covers If the
accidents.
numbers of items covered (see Table 6.4) are examined with regard to the type of document used, it
or file
can be seen that of the 13 examples of forms
covers, only 3 include more than half the items included in the
U. K. booklet.
On the other hand'all
except two of the police
report
booklets'include
60 or more items -_ nearly two thirds of the numberof items included in the U.K. booklet. TABLE6.3 TYPEOF ACCIDENTREPORT DOCUMENT'USED BY THE POLICE
Police report booklet used Cyprus Gibraltar Guyana Jamaica Malawi Montserrat Swaziland Zambia
Form or file cover used-, Bahamas Belize Sri Lanka.. Fiji *Hong Kong x,.3 India Sarawak Singapore St Helena, ýSt Lucia _ . Botswana Kenya Ghana
Extra form used for 'damage-only', accidents Cyprus, Gibraltar Hong,Kong* Singapore
The Hong Kong. Police use 4 file covers one each for fatal, serious injury accidents and one for' I damage only' accidents. and slight 125
have documents which are almost as comprehensive as
Somecountries the U. K. booklet, detail
in their
whilst
barest include the minimum of only others
reporting
documents.
There are a number of items that are consistently documents supplied.
For instance,
site of an accident to be stated,
excluded from the do ask for the
although many countries very few ask-for
a map reference or Thus many
indeed define any positive
method of describing
documents are quite likely
to state that an accident occurred on a given
road which may be several miles long. sive documents cover details required very little refer
to skidding,
of injured
information driver's
on'that
a site.
While most of the more comprehenpersons fairly subject.
adequately,
some
Very'few countries
manoeuvres or excessive speed of a vehicle
involved in an accident.
Table 6.5 showsa comparison of the average numberof questions ýand files). booklets forms by those and using using covered countries higher,
It can be seen that the numberof items covered is consistently
whena booklet is used. This Table-also shows the average numberof in the the as a percentage of covered number expressed questions covered numbercovered in the U.K. police booklet.
Itýappears that even the
booklets used in developing countries are'particularly
deficient
in
the numberof questions asked about-the site of the-accident and other statistical
information such as weather conditions, 'day of week etc.
Although this information is relatively
un,important-as-far
as prosecu-
tions and other action that might be taken by the police are concerned,
126 91
TABLE6.4 WITH TO BE COVER[DCOMPARED Colelpt, RISO, j OF ALL POSSICLEQUESTIONS
ACTUALLY COLLECTED INFORMATION Section I Administrative details and records of imiediate action
Section 2 Details of persons injured
Section 4 Drivers vehicles and passengers
31
58
76
5
18
Great Britain
20
19
36
5
14
Bahamas
10
10
Is
25
42
Celize
14
14
14
3
'49
Cyprus
22
34
23
6
1
0
Gibraltar
9
14
21
42
50
Guyana
16
14
25
46
65
Hong Kong
11
4
20
4
4
7
9
06
26
11
21
26
46
68
7
7
26
5
14
is
26
45
ýO
"0
105
Number of possible questions
Section 5 Space for statements
Section 6 Site and statistical information
Total
188
Questions actually covered by 94
Barbados 5
.4 10
104
0
11
18
Ethiopia Fiji Ghana
India
1.0
49
Indonesia Iran Ivory Coast Jamaica Jordan Kenya Kuwait Malaysi a Malawi
11
56
Mauritius Montserrat
64
Morocco Niýcria Sarawak
4
Seychelles Singapore
12
18
37
41
Sri Lanka
10
0
07
20
St Helena
4
00
11
24
55
55
61
55
63
-7 '22 27
St Lucia
13
14
Swaziland
10
14
Zambia
12
14
Botswana
4
0
-27 3
Ghana
8
9
17
127
007 1
11
46
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128
as 4-) A
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41) a 4J 4-r- C
it
to determine the contributory
is important when trying
factors
concerned in the accident.
A police booklet has been designed for use in developing countries. Although this has been kept as concise as possible,
the number of
U. K. in is the the the accident almost as as on site of many questions police booklet.
Examination of the accident analysis
6.4.2
As explained earlier, analysis
form similar
only five
forms
countries - appear to use an accident
to the U. K. Stats.
police booklet or form for reporting.
19, whereas twenty-one used a
In addition,
the analysis forms
were muchless comprehensivethan the accident-reporting although data collection coding and analysis
is carried
documents. So
out in a reasonable manner, data
is poor.
From Table 6.6 it can be seen that there was considerable
variation
between the analysis forms used by the various countries.
In Table 6.6, the data provided by the forms has been examined under I the following categories as used in the U.K. Stats. 19.
casualties involved(ii)
vehicles involved
(iii)
drivers and riders attendant
circumstances.,
129
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130
As can be seen there was considerable
In the U. K. "Casualty"
used by the various countries. using 36 alternative
variation
between the forms
the developing countries
classifications,
of "vehicles
Details
between 7 and 21 classifications.
is described by using
involved"
are
described by as few as 3 and as many as 112 on the report sheets used by the developing countries,
6.5
the U. K. using 42 items.
ANDANALYSISSYSTEM THE DESIGNOF A DATACOLLECTION COUNTRIES FORDEVELOPING
there is considerable
As can be seen from the previous analysis variation to collect
in the design of the documents used by the various countries data. and analyse road accident
be criticised could used
Whilst some of the forms too simple in design or too
for being either
least have these that be at it countries remembered should complicated document to road accident attempted
information.
balance be there a, must system,
In designing an accident reporting between the collection and a simplified
of a considerable
K. U. in data the as amount of
data basic the are collected. most system where only
If over-complication
better be the avoided, system stands a much can
in developing, implemented being country. a of chance essential
it then asked are questions
questions will
be answered thoroughly
If, fewer, but
is reasonable to assume'that these and accurately.
if manyquestions are demandedthere will
Alternatively,
-
be less readiness to complete
the document.
It was decided that a system based on the method used in the U.K. but considerably simplified those organisations
would best, meet the needs of police forces and
requiring,
statistical
131
information
and analysis,
in-,
an accident,
use of policemen reporting data can be coded.
relevant
are illustrated
of a booklet for the
This system would consist
developing countries.
form on which
and an analysis
forms so designed
The booklet and analysis
in Figs. 6.2 and 6.3.
Recommended Police accident report booklet
6.5.1
The U. K. Accident report booklet. oq which the recommendedbooklet is based, consists of a booklet small enough to fit covered with fairly it
is easily
stiff
carried
card.
The front
accident.
This was copsidered to be ideal because
around and presents few difficulties
at the site of an accident. injury
into, a pocket and
One bookletAs
in
when filled
completed for each personal-
cover deals with identification,
accident by time, place, date and class (ie fatal,
of the
serious, or slight),
details. the the and. with, of,. the po*licb accident person with reporting station and division concerned. The recommended booklet for developing_cýountries follows the same but information concerning medical aid that may contains extra pattern have been called.
Whereverpossible, for ease of completion the informa-
tion required can be entered with a tick or simply entered in a box (ie time at which accident was reported).
(See.Fig. 6.2), _
The inside cover and following five pages deal with persons involved. These cover details details
of drivers
for 3 persons and vehicles
Apart from personal details,
details, weather.
details'
and details
injury
of pedestrians
most of the information
with a mark in the appropriate page for 'site
personal details,
box or a 'yes'
of road surface,
and passengers.
can' be filled
or 'no answer.
which include road classification
type and condition
details,
speed limits,
There is a
and junction visibility
There is also a section for damage to other property 132
in
and
or animals.
for a sketch map of the site and the remaining
A blank page is available
parts of the booklet are for state. T4nts, police
officer's
comments and details
cautions given and various legal and administrative
report,
as required by the police
force of the country concerned. I
This booklet appears to conform -with'the It
is simple to complete and information
The type of information
requirements stated earlier.
can easily
be found when needed.
required to be entered includes administrative
to be used in analysis by statistical f tions and the legal points which need to be entered. I
details,
details
likely
organisa-
Table 6.4 gives the number of questions asked in the police booklets used by the U. K. and developing countries
and Table 6.5 shows
the average number of questions asked by the various countries as a percentage of those in the U. K. booklet.
report
expressed
Table 6.7 compares these
for in developing designed booklet the suggested use countries. newly with
It can be seen that there are almost as manyquestions in the ý in booklet U. K. the there are one, apart from the section as suggested on details
of vehicles
and passengers where 17 questions are asked.
Apart from simply the number of questions asked, the proposed booklet I
has been designed in such a way as to make,completion particularly in most cases simply a matter of ticking
the appropriate
Also the U. K. booklet is so arranged that it personal details several times.
(ie Nameand address etc) are frequently
his personal details
'driver'. under
box.
is likely
Thus if a casualty were also the driver
easy,
that entered
of a vehicle,
be entered once under 'casualty' would
and again
The reconnendedbooklet has been designed to avoid
this repetition. 133
W0 >
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134
r.
The main disadvantage of the use of a booklet is the limited available
for large numbers of persons and vehicles
in one accident.
space
which may be involved
This problem could be overcome either
by using an
extra booklet or by having a sheet of paper which could be attached to the booklet.
6.5.2
Recommended accident analysis
fom
The form which has been designed for the analysis (see Fig. 6.3) is effectively There is no information
a simplified
on the analysis
sections on persons involved, of the accident.
version of the U. K. Stats.
vehicles,
19.
form that cannot be found in the
As with the booklet,
completed report booklet.
of accident
site
it
is divided
details
into the
and identification
There is space for coded information
on 6 pedestrians,
6 passengers and 4 vehicles.
Table 6.6 showed the total
number of coded alternatives
U. K. and the developing countries. uses about 34 alternatives Stats. 'drivers 'Vehicles
'persons involvedIt
to cover 'casualties'
form
the U. K.
and 24 to cover
The design of the new form thus being more concise.
and riders'. involved'
The newly designed analysis
to describe
19 uses 36 alternatives
used by the
and 'attendant
covered by 19 and 40 alternatives
circumstances-and
respectively
site
details'
are
in the recommended
analysis form which is a sensible balance between the extremes used in developing countries.
It is hoped that the form would be simple enough for the person
responsible to complete without taking too much time.
This in turn
would meanconsiderable saving in manpoweras the completed forms could then be sent monthly,
or even weekly, to a central office where
machine analysis could immediately be carried out. 135
It would also mean
that records required for police transcription
could be kept to a minimum. With this
of information
delays would not be incurred in extracting
system. working efficiently,
from the machine analysis
useful statistics quickly
contained a detailed
various countries
form and which definitions
account of how to complete the
that police, and any other organisations
receive adequate training
in the completion of the booklet
form.
The form has been designed sc that coded information directly
transferred
numbers from Ihas a '1' injury
sent to
to apply to the various terms.
It is of course essential
and analysis
and these could be used
Following this work, the information
and efficiently.
involved,
use need not be sent away and that
onto a punch card system.
48.
can be
On the form itself
For example 'degree of injury
are
for pedestrians'.
located above the space provided to describe the degree of
to the pedestrian.
This refers
to the fact that on transfer
of data to a punch card, the appropriate. code is punched in column one on the card.
In total
48 columns on the card would be used to code
the data contained on the form, the 48th column containing information on the visibility
pertaining.
The U.K. Stats. 19 uses 63 columns of the punch card. suggested for use by developing countries and is therefore
Thus if
uses 48, as explained above
more concise than that used in the U. K.
card for use on a Hollerith
sorter
The system
The 'standard'
or computer has 80 columns available.
any country wished to include additional
ample space available.
136
data there would be
6.5.3
Data Processing
In order to make full
use of the data collected,
that an adequate data-processing to the questionnaire
detailed
data analysis was carried
cards so that it
is essential
system be used. None of the countries
used such a system and consequently little
replying
The data collected
it
out.
should be transferred
to a system of punch
can be processed manually, mechanically or by computer,
depending on facilities
available
in the particular
country.
The most simple device in commonuse is a system of cards where the edges are clipped or punched with holes according to a given code. Rods can then be inserted
clipped edges will lifted
into the holes and lifted.
The cards with
remain and the ones with complete holes will
be
,
out.
A more advanced system is the Hollerith
card sorter,
whereby punched
cards are inserted into a machine which automatically sorts the coded alternatives
on any particular
column. This is an efficient
system as long as complicated analyses are not required
comprehensivetabulation can be built
but reasonably
up using a card sorter and an
automatic tabulator.
If computer facilities
are available,
data can be transferred
to
punch cards or data tape and stored in the computer. These data can then be analysed using an appropriate been carried
program.
Considerable work has
out at the Laboratory on the designs of such programs.
137
37 "RATTLE (Road Accident Tabulation .
for System 4 computers and is designed for use by people with
suitable little
Language) is a program
computer experience.
It will
in tabular
requested and present the results statistical
select and tabulate
It will
form.
not perform
of basic tables and relationships
but for provision
tests,
records as
it
is an extremely useful program. "SPSS", (Statical Package for 38 Social Sciences) is a more sophisticated computer package and will carry out sub-programs eg frequency distribution,
coefficientss
correlation
regression analyses etc, as required.
As explained in Section 6.2, number of different
accident records are needed by a I The police collect information in
organisations.
order to enforce the law whilst
other organisations
so that decisions
can be made on legislation
schemes etcaimed
at reducing road accidents.
need statistics
and road improvement be,
It would therefore
reasonable that a governmentdepartment other than the police should be responsible for the detailed analysis of road accident data. logically
It follows
that this work should be carried out by the department
responsible for the analysis of other national statistics.
A comprehen-
sive report produced annually could then be published and circulated
to
the various governmentdepartments concerned.
6.6
Few accidents have a single
DISCUSSION
39 cause and considerable
before remedial measures can be formulated. analysis
described in this
report
collect
is needed
As was seen from the
very few developing countries
an adequate road accident data collection number of countries
detail
and analysis
system.
accident data reasonably efficiently
few analyse the data so collected.
Thus only five
138
operate A but
developing countries
were found to use an analysis 'report
form equivalent
in a personal injury'.
of a road accident resulting
forms provided by these countries over complicated. questionnaire
Finally,
mechanical sorting
collection
none of the countries
and tabulation
In order to assist
19
The analysis
inadequate or
replying
to the
that to so cards on punch
could be carried
developing countries
out.
data set up a sound
system, both a police booklet and analysis
and analysis
have been designed.
tended to be either
data collected
transferred
to the U. K. Stats.
form
Both are based on the system used in the U. K. but
emphasis has been placed on simplicity
and ease of completion.
Guidance has also been given on the methods that can be used to tabulate It is hoped that the system so described will
the data so collected.
be adopted so that much more information location
can be obtained on the type,
and persons involved in read accidents in developing countries.
Only with this
information
can effective
-1
1
139
be introduced. remedial measures
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156
U C)
The ag.- distribution
In Kenya,accidents are
of casuallLies:
to adults or to persons under 15 years of age.
recorded as occurring
Table 7.7 shows the accident severity
for these two age groups.
TABLE7.7 SEVERITYBY AGE Adult
Juvenile
Unknown
No
%
No
%
Fatal
1013
13.9
174
19.2
Serious
2100
28.8
249
Slight
4188
57.4
485
Unknown TOTAL
7301
%
11
2.6
1198
14.0
27.4
64
15.0
2413
28.0
53.4
132
30.8
4805
55.5
51.6
221
2.5
-
-
100
908
100
428
I
I
I
percentage of juvenile
11 percent of the total;
I18 percent.
No
-
II The overall
%
No
221
-
TOTAL
the equivalent
100 I
casualties figure
8637 I
100 II
was found to be almost
for Great Britain
being
An unpublished analysis of road accidents in Ghanagives
the percentage of child casualties as 23 percent of the total studied. The percentage of child low.
particularly
in Kenya would thus appear to be
casualties
It is possible
to children are less likely
however that the less severe accidents
to be reported.
It can be seen that over 19 percent of all juvenile casualties were fatal whilst the equivalent adult value was almost 14 percent (the difference being statistically In Great Britain
significant
at the 5 percent level).
the reverse is found to occur with 2-3
percent of
adult casualties being fatal and 1.4 percent of juvenile casualties (under 15 years of age) being fatal. proportion
Britain
of all
casualties
but the fatality
be particularly
Thus in Kenya not only is the
that are fatal
greater than in Great
rate for juvenile casualties would appear to
high.
157
The casualty distribution percent of all
casualties
during daylight
percentage seriously
during daylight
occurring
during darkness the equivalent
12 Over darkness: and were fatal,,
whilst
figure was 17 percent (see Table 7.8).
The
and darkness.
injured was the same during daylight TABLE7.8 SEVERITYBY DAYLIGHTANDDARKNESS Darkness
Daylight
Unknown
No
%
No
%
840
12.4
322
17.0
Serious
1815
27.7
533
Slight
3700
57.0
131
2.0
Fatal
Unknown TOTAL
6486 (75.1%)
Seventy-five
100
No
%
1198
13.9
27.7
-36 65
16.1 29.2
2413
27.9
990
51.4
115
51.6
4805
55.6
83
4.3
7
3.1
221
2.6
1928 (22.3%)
percent of all
100
casualties
100
8637 100 (100%)
were injured
during daylight
223 (2.6%)
and 22.3 percent during darkness. In Great Britainta N
TOTAL % No
greater percentage
of all casualties occur during darkness (36 percent), a difference that might be attributed
to proportionately
darkness in Great Britain
The distribution
more driving
being done during
than in Kenya.
of casualties bZ hour, day and month: As can be
seen from Table 7.9 and Figure 7.3, the incidence of road accident
casualties in Kenya rises sharply between 6amand 7amand continues to rise throughout the day, reaching a peak at 5pm. The casualty rate then decreases sharply until
The casualties
the following
in Great Britain
morning.
also reach a peak at 5pm (see
Figure 7.3) but differences between'the two countries clearly exist. Thus in the UK there is clear evidence of a peak occurring
158
at midnight.
10 9 8 7 6 cm 5 4 3 2 1 011.
0
IIIII-IIII
L---L
J---i-l ---
IIIII
2400 2200 2000 1800 1600 1400 0800 1000 0200 0400 0600 1200
Hour
Kenya
9 3 7
M c CL
Fig.7.3 THE DISTRUBUTION OF ROAD ACCIDENT CASUALTIES THROUGHOUT THE DAY IN KENYA AND GREAT BRITAIN
159
TABLE7.9 CASUALTIES BY TIME OF DAY Hourly period commencing
Kenya %
Great Britain % No
129
1.5
9 353
2.60
92
1.1
7 240
2.01
79
0.9
4 748
1.32
105
1.2
0.59
43
0.5
2 143 1 417
63
0.7
1 618
0.45
109
1.3
3 010
0.83
342
4.0
11 209
3.12
375
4.3
19 149
5.33
355
4.1
12 251
3.41
404
4.7
13 072
3.64
11 am 12 noon
404
4.7
16 2-33
4.52
377
4.4
19 985
5.56
1 pm 2 pm
450
5.2
19 076
5.31
482
5.6
20 478
5.70
3 pm 4 pm
515
6.0
23 866
6.64
544
6.3
30 796
8.57
788
9.1
30 467
8.48
625
7.2
21 002
5.85
7 pm 8 pm
716
8.3
18 181
5.06
536
6.2
14 260
3.97
9 pm 10 pm
375
4.3
13 614
3.79
312
3.6
19 339
5.38
11 pm Unknown
194
2.2
26 493
7.37
223
2.5
-
No
12 midnight 1 am 2 am 3 am 4 am 5 am 6 am 7 am 8 am 9 am 10 am
5 Pm 6 pm
TOTAL
.
8 637
100
160
,,
359 000
0.39
100
.
This might be due to a greater proportion
of travel
greater incidence of drinking
in Great Britain
and driving
at night or to a than in
Kenya. TABLE7.10 CASUALTIES BY DAYOF WEEK Great Britain
Kenya Day of week
%
No
%
Sunday
1 466
17.0
49 658
13.8
Monday
1 144
13.2
46 678
13.0
Tuesday
1 077
12.5
45 339
12.6
Wednesday
1 075
12.5
44 554
12.4
Thursday
1 052
12.2
47 728
130.3
Friday
1 170
13.5
60 885
17.0
Saturday
1 562
18.1
64 158
17.9
Unknovin
91
1.0
8 637
TOTAL
The distributions and Great Britain
No
-
100
-
359 000
100
of casualties in each day of the week in Kenya
are shown in Table 7.10 and Figure 7.4.
highest number of casualties
In Kenya the
occurred on Saturdays and Sundays whereas
in Great Britain
the highest numbers occurred on Fridays and Saturdays
(the differences
being statistically
Social patterns
significant
at the 5 percený level). for example in
obviously account for these differences;
Kenya Saturday mornings are working periods for most of the population and Sundays are days of increased leisure
Casualties
activity.
by month for Kenya and Great Britain
Table 7.11 and Figure 7.5. occurred in March, April
In Kenya the greatest
are shown in
number of casualties
and September: in Great Britain
numbers of
casualties were highest in Novemberand December,a pattern also shown by Sweden, Germany, Yugoslavia etc.
In Great Britain
161
these periods when
20 18 16 14 12 10 0-
8 6 4 2 0 Sun
Mon
Tues
Wed
Thurs
Fri
Sat
Kenya
18 16 14 12 21
10
6 4 2 0 Sun
Fiq.7.4
Mon
Tues
Wed Great Britain
Thurs
Fri
ROAD ACCIDENT CASUALTIES BY DAY OF VJEEK IN KENYA AND GREAT BRITAIN
162
Sat
high traffic do high with a not coincide number of casualties occurred 44, hours daylight flows factors, extreme and as short of other such ý' weather conditions
having greater effect. TABLE7.11
-- . t.
CASUALTIES BY MONTH'IN KENYAANDGREATBRITAIN Great Britain
Kenya Month
623
7.3
29 388
8.2
February
657
7.6
26 279
7.3
March
793
9.2
28 805
8.0
April
772
8.9
27 259
7.6
May
703
8.1
30 828
8.6
June
710
8.2
29 687
8.2
July
738
8.5
31 324
8.7
August
674
7.8
29 286
8.1
September
774
9.0
27 719
7.7
October
727
8.4
30 911
8.6
November
672
7.8
33 661
9.4
December
683
7.9
34 532
9.6
Unknown
111
1.3
-
8 637
Howe9,, found no evidence
greatest
of a regular
in the month containing
in March or April
figures
100
359 679
pattern
100
of, seasonal
variation
flow in Kenya; and the author found no evidence that traffic
Kenya the climate follows
The first
%
No
January
TOTAL
in traffic
%
No
the highest number of casualties.
flows were In
a strong seasonal pattern with high rainfall
and a secondary less severe rainy period in November.
of these periods coincides with the months when,casualty are highest.
However casualties
secondary less severe rainy season.
163
do not seem high during the
10 9 8 7 6 cr 5 CL.
4 3 2 1 0 Feb
Jan
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
Kenya
10 9 8 7
Q)
6
4
3
Jan
Feb Mar Apr
May Jun
Jul
Aug
Sep Oct Nov
Great Britain
Fig.7.5 ROAD ACCIDENT CASUALTIES BY MONTH IN KENYA AND GREAT BrZITAIN
164
Dec
7.4.3
Road accidents in Kenya
Note.
The accidents referred
involved a personal injury
Accident types:
to in this
chapter are those which
and do not include damage-only accidents.
according to the
Accidents were categorised
are given in Table 7.12.
vehicles or persons involved and results TABLE7.12
ACCIDENTTYPESIN KENYA Type of injury accident Single vehicle Vehicle - vehicle
Number
Percent
1490
27.4
989
18.2
195
3.4
631
11.6
2133
39.2
5
0.1
Vehicle - motorcycle Vehicle - cycle Vehicle - pedestrian Unknown
100
5443
TOTAL
Vehicle-pedestrian accidents in Kenyawere the most frequent, being over 39 percent of the total; 29 percent.
in Great Britain
the equivalent figure is
The most commonaccident in Great Britain
vehicle type, being over 45 percent of the total, 18.2 percent of accidents were of this type. I
Table 7.12, single-vehicle 'the equivalent
figure
but in Kenya only
As can be seen from
accidents in Kenyawere27.4 percent of the total,
in Great Britain
between the two countries
is the vehicle-
being 19.5 percent.
are statistically
significant
Differences
at the 5 percent
level. Accidents in urban and rural types was carried
areas: A further
analysis
of accident
out and as can be seen from Table 7.13 most accidents
165
involving
in occurred cycle or motorcycle
a vehicle and a pedestrian,
;ýccidents divided almost equally
urban areas, with vehicle-vehiclc between urban and rural
areas. TABLE7.13
TYPEOF ACCIDENTIN URBANANDRURALAREAS Urban
Type of injury accident
No
Single vehicle Vehicle - vehicle Vehicle - motorcycle Vehicle - cycle Vehicle - pedestrian
is 42 percent.
single-vehicle
% 1.3
1490 100
475) 48.0
505 51.1
9
0.9
989 100
161 82.6
30 15.4
4
2.0
195 100
405 64.2
217 34.4
9
1.4
631 100
1363 63.9
728 34.1
42
2.0
2133 100
2 40.0
1 20.0
2769 50.9
2589 47.6
single-vehicle
With the relatively
2 40.0 85
1.5
5
100
5443 100
accidents were found to the equivalent
figure
low vehicle flows existing on rural
are less likely
to collide
with one another and
accidents might be expected to predominate.
Kenya where rural
%
No
19
areas in Kenya; in Great Britain
roads in Kenya, vehicles
No
1108 74.4
Almost 75 percent of all occur in rural
%
140
363 24.4
Unknown TOTAL
%
TOTAL
Unknown
Rural
Thus in
horizontal roads are narrowers with greater extremes of
and vertical curvature and where light vehicles travel at greater speeds .V on average45 than in Great Britain, the single vehicle accident would appear to be a particularly
serious problem.
The severity of the various types of accident: As might be expected vehicle-pedestrian fatal
(see Table 7.14).
higher fatality first
accidents were those with the highest proportion The fact
that single-vehicle
rate than vehicle-cycle
seem surprising.
being
accidents had a
or vehicle-motorcycle
might at
However, as was seen in Table 7.13, almost
three-quarters of these accidents occurred in: rural areas, where vehicle speeds are greater and where medical aid might be less readily available. 166
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168
r:
c:c
c:
CD
Accident types on various road surfaces: classified
as 'surfaced'
(those with a bituminous surface),
(those with ail engineered gravel surface) surface).
In Kenya, roads are 'murram'
(with 'unmade' an earth and
Tdble 7.15 shows the number of accidents occurring
on these
types of roads.
On surfaced roads, vehicle-pedestrian whereas on murram and unmaderoads single common. Over 77 percent of all and 18 percent on murram roads. the total roads.
vehicle
kilometres
accidents were most common vehicle
accidents were most
accidents occurred on surfaced roads It was estimated that about 5 percent of in Kenya took place on murram
travelled
The accident rate per vehicle-kilometre
is thus much higher on
these roads than on surfaced roads.
7.4.4
The vehicles
involved in road accidents in Kenya
TABLE7.16 Vehicle type
Number
Percent
3917
54.8
Motorcycle
394
5.5
Cycle
690
9.7
Commercial
1342
18.8
Land Rover
366
5.1
Bus
336
4.7
Tractor
82
1.1
Other
17
0.2
Car
TOTAL
7144-.
100
As can be seen from Table 7.16, cars and Land Rovers were involved -
in 60 percent of all injury accidents reported in Kenya. An estimate was obtained of the total annual vehicle-kiloriletres
travelled
by cars,
buses and commerci. al vehicles in Kenya' thus enabling the accident rates for these types of vehicles to be estimated. (see Table 7.17). 169
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r_
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VC
Mutorcycles were found to have the high-ast accident rates with cownercial vehicles having the lowest rates, in most European countries.
a pattern
In Great Britain,
commonly found
however, public
vehicles have a higher accident rate than private
service
cars (probably due
to the fact that most psv journeys are made in heavy traffic
with'high
occupancy rates).
7.5
CONCLUSIONS ANDDISCUSSION
This analysis has shown that although the greatest and casualties million
number of accidents
occurred in Nairobi Province, the accident rates per
vehicle kilometres
travelled
in lowest this were
Nairobi Province also had the lowest ratio Fourteen percent of all
casualties
compared with countries
in Western Europe.
of casualties
in Kenya were fatal,
per accident. which is high
(As stated earlier
part may be due to the fact that serious and slight be as well reported as fatal
prcvince.
this
in,
accidents may not
accidents).
There were proportionately
fewer casualties to users of two-wheeled
vehicles in Kenyathan in Europeancountries, which reflects
the low
usage of these vehicles in Kenya. The proportion of all casualties that were occupants of commercial vehicles was,very muchhigher in Kenya than in Europe. This might well be due to the fact, that commercial vehicles are used in Kenya to transport workersIto and from building sites and other work places and it is commonto see open lorries up to thirty and 7.6b.
menbeing carried.
with
Examplesof this are shown in Figs. 7.6a
Whensuch vehicles are involved in accidents there are likely
to be manycasualties. Social reflected
patterns which differ
in the distribution
from those in Great Britain
of road. casua*lties.
171
were
Thus in Kenya the
number of casualties
being (Saturday Saturdays morning were greatest on
leisure increased day) Sundayss a period of a normal working and In Kenya the proportion
of casualties
lower than in Great Britain
activity.
darkness during was occurring
which may reflect
proportionately
less travel
at night.
Forty percent of all thirty
accidents involved a pedestrian and almost
percent involved a single-vehicle
vehicle accidents was particularly three-quarters
of this
The incidence of single
only.
high in rural
areas where almost
type of accident took place.
Eighteen per cent of all
accidents occurred on murram roads which
were estimated to carry only five percent of the vehicle-kilometres dust in Kenya. The lower geometric standards, of effect -the 7.7 Fig. deterioration their in on visibility and also wet weather see travelled
probably account for the high accident rate on these roads.
As stated earlier, analysis of their
very few developing countries
road accidents.
However it
is'only
detailed a make by carrying
analysis such as that described here that the real situation apparent.
Thus although the Kenya Government realise
increasing accident problem, it was never fully example, single-vehicle
out an
is made
that they have an
appreciated
that,
for
accidents or accidents to occupants. of commercial
vehicles were so prevalent.
172
(b)
Fig. 7.6 COMMERCIAL
VEHICLES BEING USED TO TRANSPORT MEN TO PLACES OF WORK
173
NX,
"", f ,ý,
(a) Poor visibility
(b) Surface deterioration
caused by dust
caused by heavy rainfali
Fig.7.7 PROBLEMS ON MURRAM
174
ROADS IN KENYA
I
8.
A STUDYOF ACCIDENTRATESON RURALROADSIN DEVELOPING COUNTRIES
8.1
INTRODUCTION
12
The analYsis of road accidents in Kenya, together with studies in 46 indicated that accident rates tehd to be other developing countries particularly single-vehicle
high on rural
roads.
As was noted in the previous chapter,
accidents were particularly
prevalent
Kenya, being almost 50 percent of the total In this
situation
a significant construction
it
number of accidents occurring.
is probable that design features Even in Great Britain
factor.
roads in
on rural
of the road are
where the standard of road
is high compared with most developing countries,
layout,, SUrface or furniture
was found to be a contributory
the road factor
almost 30 percent of all
on mainly rural
within
out in Oxfordshire47
accidents occurring 39. Work carried a defined study area
1937 (when vehicle developing countries
in
roads in,
flows were probably of the order of those in some at present) concluded that 75 percent of the accidents
would not have occurred had the road conformed to the (then) current Ministry
of Transport Memorandum575 on the Layout and Construction
of
Roads.
In order to study the relationships
between personal injury accident
rates and*geometric design of the road, data have been collected from Kenyaand Jamaica. The primary objective of the investigation attempt to correlate the numberof accidents per million
was to
vehicle-
kilometres on a length of road with the design characteristics
of the
road in order to obtain information which would be of use in formulaiing for the design of safer*roads in developing countries. -,, However, relationships d.erived in this,, investigation need to be verified
principles
by studies on roads in other countries. 175
In particular I
itAs
hoped that
the relationships be incorporated
derived here and in other countries
could eventually 48 into the Road Transport Investment Model developed by
the Overseas Unit.
This Model attempts to winimise the total by devising
cost of a given project
transport
the optimum standard of road
construction and design. 8.2
In order to correlate
DATACOLLECTION
accident rates with road design it
to have, for each section of road, the precise location injury
is necessary of each personal
accident taking place. over a given period of time, an accurate flow throughout the year and measurement of
measurement of traffic factors
such as road width,
irregularity
etc.
horizontal
and vertical
curvature,
There were very few developing countries
surface
where such
data were available but it proved possibles by using data from various I research studies, to obtain the required information for Kenya and Jamaica.
3.2.1
Kenyadata
During 1973 a visit information
on all
was madeto Kenya by the author to collect
personal injury
accidents taking place in 1972.
In
1975, following meetings with the KenyaMinistry of Works, details of all injury accidents taking place in 1973 on the Nairobi-MombasaRoad (see Figure 8.1) were obtained by the author. accident data and with accurate traffic decided to use this
road for detailed
With this extra road
flow data available,
it was
study.
48 The Road Transport Investment Model designed by the Overseas Unit , to minimise total transportation costs on a given road project, was based on data, collected
in Kenya over the period 1969-1974.
176
Test
on the Nairobil-
sections were set up throughout Kenya, particularly MombasaRoad, and the traffic
flow and geometric design data collected
during that period have been used for this accident rates.
investigation
of road
The road in question was divided into various sec-aions
(see Figure 8.1) with the following
information
available
for each
road length:
1)
personal injury
2)
the length of each section
3)
the average annual daily
4)
the average road width (metres)
5)
the number of junctions
6)
the average horizontal
7)
the average vertical
curvature
8)
surface irregularity
(millimetres
in 1972 and 1973
accidents occurring
traffic
flow
(per kilometre) curvature
From 1) and 2) personal injury
(degrees per km) (metres per km) per km).
accidents per 1(ilometre tier annum
1), 2) from and and 3) accidents per million were obtained,
vehicle-
kilometres were obtained. Geometric design parameters
The road width was the width of the surfaced section of the road excluding the gravel shoulders. The vertical
curvature of a road can be described most easily
its 'average gradient' or its total vertical measure is fully of measuring it
satisfactory
'rise
but rise and fall
from a specially
and fall'.
was preferred.
by
Neither A method
designed and instrumented moving
vehicle was developed for the study in Kenya.
The development of this
technique allowed a high degree of accuracy to be obtained even on roads with irregular
surfaces.
177
Horizontal
curvature
is simply the 'bendiness'
in metres or by the degree of curvature, between the straight
definition
different
is the most suitable
it
defined as the angle in degrees
sections of road which are joined by the curve.
Although the latter radii,
carried
between bends of
does not differentiate
for evaluating
of a series of bends on accident rates because it to measure.
In developed countries
where similar
radius of curvature.
occur and where high levels
the overall
is additive
effect
and easier
studies have been
out49,50,51 the accident rate has frequently
the existing
A
by the radius of curvature measured
bend can be defined either
particular
of a road.
been correlated
with
On busy roads where numerous accidents flow exist,
of vehicle
this
is probably the
dimension to use. convenient most
Surface irregularity
is sometimes called
the 'riding
quality'
of the
from.. developed irregularity A was road. method of measuring surface 52 in which the vertical movements the principles of the 'bump integrator' of the axle of a single-wheel by an integrating
clutch.
trailer
are summedover a test section
Though necessarily
the system
-arbitrary, that was developed provided an index of the irregularity for comparing the surface conditions
of the test
which was useful
sections.
The parameters obtained for the sections of road used in this analysis are given in Table 8.1.
178
Vfllvý%Ios Lu u
cc a
03
c 0 '4Z
cc
0 S
'0
>-
w -0
c
E 0 2 1
:3 -lu co 0 cu
>
.0
co
I v
Z
0 >. C
ca
z
m -0
U)
4
H
E LLU
0
Z w
'0
ca
ui
0 :3 22
-0
z
*Z -0
/
m c31
/1
ý
CD
CD U')
C:) LO
CD-
0a a ,0
r 179
Co
TABLE8.1 DATAFORSECTIONSONNAIROBI-MOMBASA ROAD,KENYA
Section Number
Personal 1njury Accidents/ Million Veh-km/ annum
Average Road Width (metres)
Vertical Curvature (m/km)
Horizontal Curvature (deg/km)
1
2.93
6.1
10.02
19.42
2300
0.66
2
2.17
6.1
1.36
4.59
2300
3
2.32
6.1
0
0.73
3030
0.39 1.43
4
2.62
6.1
5.40
12.54
3264
0.67
5
3.54
6.1
5.40
35.53.
3086
0.43
6
1.67
6.1
14.6
40.72
3086
0.56
7
2.83
6.1
14.6
4j. 74
3308
0.32
8
2.67
6.1
14.6
16.98
3308
0.35
9
1.08
6.1
15.0
2.08
3308
0.12
10
2.11
6.1
15.0
3308
0.43
11
2.42
6.1
1.41
1.19
3308
0.32
12
1.88
7.0
2.62
5.07
3308
0.17
13
4.60
7.0
8.88
53.79
3308
1.94
14
1.96
7.0
5.59
12.73
1633
0.14
15
1.33
7.0
4.45
4.78
1633
0.12
16
1.54
7.0
5.04
7.22
16313
0.26
17
1.91
7.0
13.02
38.90
1633
0.21
18
1.67
7.0
1.91
10.42
1633
0.31
19
2.29
7.5
11.12
30.44
1488
0.56
1
180
31.5
I
Surface irreg (mm/km)
Junctions/ km
8.2.2
Jamaica data
In 1962 a team was sent by the Laboratory to carry out urban and research work in Jamaica. During this period an unpublished 53 'black details and report was produced which gave of accident rates
rural
'A' and V
spots' on rural (per million
roads on the island.
vehicle-miles)
were calculated
after
for almost the entire
'A'
(see Figure 8.2) and have been used in this
road network on the island present report
The accident rates
the rates into metric units.
converting
A detailed
investigation
was also carried out on the deficiences of the rural 54 network in Jamaica , with detailed inventories being made of the existing
rural
following
road system.
For each section of rural
'A' road the
I
parameters were obtained:
1)
(feet) average width
2)
profile
3)
average vertical
4)
averag3 horizontal curvature (degrees/mile)
5)
average surface irregularity
6)
average sijht'distance
7)
the numberof junctions
'Geometric
and gradients (percent) curvature (ft/mile)
(in/mile)
(ft)
(per mile)
design parameters
Average road width was obtained by taking five intervals
road
measurements at equal
every mile.
The vertical
curvature was obtained by measuring the elevation
at
every crest and hollow and accurately measuring the distances in between. Thus, as in Kenya, the 'rise
and faIll 181
per unit length of road was
1ý
obtained.
The gradient was obtained by using an Abney level mounted in
a survey car and modified to read grade directly.
As in Kenya, the horizontal degree of curvature
curvature was measured in terms of
or 'bendiness'
per unit length of road, but in this
case was obtained by taking measurements from 1: valuation
12,500 scale land
maps.
The average surface irregularity
(see above) for each section of
road was obtained by using a towed bump integrator above, the vertical
movementof a wheel relative
measured, thus providing
where, as described to its mountings was
a measure of the unevenness of the road surface.
The average sight distance of each section was obtained by
measuring how far ahead a driver could see an obstruction on the roal. I Measurementswere madeby putting downmarkers at 100ft intervals along the road and, at each marker, counting how many markers could be seen on the road ahead.
Twelve-inch high rubber cones were used as markers.
This method has the advantage of-simplicity
and speed. The average
sight distance was calculated from the total of the numbersof cones counted in the section and the numberof observations madewithin the
section.
The parameters obtained for the sections of road used in this analysis
are given in Table 8.2.,
182
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c13
c
tu
-0
02 > m CM 2
41 0 c c
0
0
-
-0
k- LO -
Z Co
(n
LD -
2 -ro
(D m CY)
:r
C, 4 (0
m
2 c .! cu o ý
1c 0 +ý
c4 Co
J2 r
w
0
92 . -C3 h-
r1.03
m m
m
q-
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cu > m
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U. 0 cu
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> 0 to -i
w
cu cu T
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c (9 > (1)
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M
m c
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0 E
m
183 ""
TABLE8.2 DATAFORSECTIONS OF RURALA ROADS,JAMAICA Total Injury Accidents per million . veh-km
Average width (metres)
Vertical Curvature (metres/ km)
2.16
7.32
2.43
25.40
2a
3.05
2b
1.96
6.92 6.10
3.27 12.41
3a
3.70
6.13
3b
3.71
4a
Horizontal Curvature (deg/km)
Sight Distance (metres)
Junctions per kilometre
2822.8
237.29
4* 80
47.70 134.41
3879.4 4904.5
209.54 126.58
6.64 6.81
9.29
102.86
4809.9
146.40
7.73
5.89
35.93
274.16
5109.5
96.38
8.32
2.47
6.25
51.36
322.42
4557.5
106.75
4.84
4b
1.37
6.68
19.10
130.62
4368.3
139.69
5.88
5a
1.04
6.34
8.93
111.12
3122.5
168.67
2.51
5b
3.01
5.64
7.56
124.66
4604.8
133.29
3.18
6
6.17
5.43
8.09
184.66
4967.6
127.80
8.19
8
2.78
6.22
11.23
199.63
4257.9
122.00
5.40
9
1.61
6.41
1.77
97.95
3800.6
163.79
3.76
10a
1.95
6.50
14.73
148.32
4872.9
134.81
3.12
10b
2.25
6.59
6.08
106.71
3311.7
169.58
4.61
Ila
1.85
5.86
11.31
133.04
4683.7
131.76
4.49
llb
3.37
5.22
20.94.
249.63
4967.6
110.41
7.17
12
1.52
5.09
12.79
273.04
6103.0
110.41
3.27
13a-
1.88
5.37
11.50
243.48
5850.7
105.84
6.50
13b
4.06
5.09
15.68
339.57
6039.9
95.47
4.53
14a
3.02
4.97
18.89
250.75
4731.0
92.11
5.75
14b
3.19
5.34
13.36
180.62
4857.2
118.34
15a
4.24 .
5.00
5.43
15.58
138.32
5456.4
135.73
4.42
15b
3.31
5.76
17.21
219.13
6087.2
111.63
6.37
16
2.25
5.55
29.79
368.32
4936.0
80.52
8.01
17a
1.73
6.65
8.87
161.18
4321.0
117.73
2.83
17c
0.95
7.59
22.31
38.32
2192.0
149.45
4.35
17d
1.17
5.98
39.56
423.60
6087.2
68.63
1.17
We
3.40
5.43
29.62
346.34
6986
71.98
3.88
18
2.61
5.40
40.87
232.42
5945.3
96.99
2.61
Section l 1
184
-
Surface irreg. (mm/km)
8.3
Regression analysis
was used by the author to establish
between one dependent variable
relationships
(The first
variables.
ANALYSISPROCEDURE
variable,
known as the dependent variable
and quantify
and one or more independent
which is the quantity
under study$ is
and the others are defined as the
independent variables).
In this
investigation
four dependent variables
were studied
separately.
1)
personal injury
accidents per kilometre
per annum - Kenya
2)
personal injury
accidents per kilometre
per annum - Jamaica
3)
personal injury
4)
personal injury
accidents per million accidents per million
The choice of independent variables
related to the dependent variable.
vehicle-kilometres
Kenya -
vehicle-kilometres
Jamaica. -
implied thatthey
'sensibly' were
In this study, a further condition
in choosing independent variables was that they should be simple to define and, for an engineer working in the field,
reasonably easy to
measure. They should, of course, be measuring different
elements of the
road geometry. As a preliminary investigation
of which variables were most closely
correlated with accident rate, simple regressions of accident rate on each of the road features
individually,
were of the form:
y=a+
blxi
185
were performed.
Equations derived
where independent vaýiable
y= x,
dependent variable =
a=
regression
b,
= regression
constant coefficient
However because many of the road design features are inter4elated simple regression relationships
analysis
may give a misleading
impression of the Multiple
that they have with accident rate.
in which the accident rate is expressed as a function 'independent'
variables
simultaneously,
regression,
of several
to be a better
is likely
guide.
Equations derived were then Gf the form:
y=a+
blxl
+ b2X2 +b.......... 3X3
bx nn
where b13, b2s, bn Xn X29 Y, X1, 9
were as above.
For these estimates to be acceptable it was necessary to test the hypothesis that the value computedfor each regression coefficient by To have to check this, chance. arisen unlikely
was
the standard error
of each regression coefficient
was computedand tested for significance;
variables with non-significant
coefficients
were eliminated from the
analysis.
The comput, programme used was part of a statistical -lr had an automatic procedure for eliminating non-significant for testing
such variables
package and variables
with other combinations and replacing
where necessary. This technique is knownas 'stepwisel
186
and
them
regression analysis.
Data obtained on rural
roads in Kenya and -Jamaica were analysed
separately.
8.4
From the analysis, kilometre
equations were derived which related
per annum to vehicle
kilometres
RESULTS
accidents per
flow and accidents per million
These equations should only be
to the geometric parameters.
used in other developing countries
vehicle-
wher6 the data are similar
and magnitude to those found in Kenya and Jamaica.
in range
Table 8.3 gives the
maximum,minimum and means of the parameters obtained on the rural studied.
The standard deviation,
roads
which measures the variance about the
mean, is also given. TABLE8.3 VARIATIONIN PARAMETER VALUES Parameter
Maximum Minimum
Mean
Standard Deviation
KENYA Average width (metres) Vertical curvature (m/km) Horizontal
curvature Surface irregularity
(deg/km) (mm/km)
6.10
6.50
0.500
15.00
0
7.91
5.41
53.80
0.73
7.50
3308
Junctions/km
20.0
1488
2625
17.33 770.5
1.94
0.12
0.49
0.460
7.6
4.97
6.00
0.68
51.35
1.77
17.26
12.33
JAMAICA (metres) width ýAverage Vertical curvature (m/km) Horizontal
curvature Surface irregularity
(deg/km)
423.6
25.4
193.4
(mm/km),
6991.1
2193.0
4783.0
Junctions/km Average sight distance (metres)
8.32 237.3 1
187
1.17
5.01
68.6 -
126.9 -
102.86 1081.7 1.89 37.60
8.4.11 The r6lationships
between accident rate and vehicle
per kilometre
The number of injury-accidents on rural
occurring
the vehicle
of road per annum
roads in Kenya and Jamaica were regressed separately
be found to related was rate significant
against
on each test section of road
flow per hour occurring
In both cases the accident
(averagad over a 12-hour 7am - 7pm period).
statistically
flow
flow (with results
to the vehicle
being
The equations
level). 5 the percent at
derived were as follows:
For Kenya
y=0.116
+ 0.009lx
For Jamaica
y=0.158
+ 0.0126x
where
y=
personal
injury
accidents
x=
average vehicle
flow/hour.
per km per annum
I
It
Figure 8.3 illustrates increases with increasing
how the accident rate in both countries flow.
(Figure 8.3 also shows a relationship
derived for a number of developed countries; It can be seen from Figure 8.3 that,
this
for a. similar
is discussed later). rate of vehicle
flows
Jamaica has a higher accident. rate than Kenya.
In order to investigate relationships
between geometric design and
kilometre the of road per annum accidentý per number of accident rates, to flow by divided the road, per annum section of vehicle on each were obtain the number of personal-injury kilometres.
accidents
In this way the relationship
into is taken account. ' accident rate
188
per million
between vehicle
vehicleflow and the
CN
cc 0
U. 0 2 20
0
0
'a (U CL
00
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co
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C)
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Mw
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Oo 0 C14
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r
m
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Ci
N
N
wnuue/wl/sl. uapjo:)L,Ainjul Jo jaqwnN
189 ,
co C3
0
8.4.2
The results 8.4.
of the simple regression
The results
of the simple regression
standard error
The tables indicate
that the relationship the many factors
(Note: 5 percent is the level
analysis,
in this
The correlation
Y
coefficient
independent variable.
49 percent of the variation variation
per kilometre
in y that
of variability
Thus, for
x value.
was found to be the most
The r2, value of 0.49 indicates
in accident rate is 'explained'
in the number of junctions
The
is also given.
in the appropriate
is accounted for by variability
significant
found signif-
be considered could study
value r2 provides a measure cf the proportion
example in Kenya, junctions
Bearing in mind
accident rates,, a relationship
icant at the 10 percent level
usually
ie there is only a5 percent probability
could have occurred by chance.
affecting
was
be found to significant were which
the relationships
accepted in statistical
to the
coefficient
to have occurred by chance).
(ie were unlikely
level. 5 10 the percent at or
satisfactory).
are given in Table
and was used to test whether the relationship significant
statistically
analysis
of the regression
value is the ratio
The 't'
andlysi
per kilometre
In both countries the most significant
that
by
alone.
parameter of those considered The
in this study was found to be the numberof junctions per kilometre. correlation
between the junctions and the accident rate was greater on
the Nairobi-Mombasaroad, Kenya, than in JamaiCdbut as can be seen from Figure 8.4. the ranges were quite different
in the two countries.
In
Kenyawhere there were never more than two junctions per kilometre an addition of one junction per kilometre was associated withan in the accident rate of over one accident per million
increase
vehicle-kilometres.
In Jamaica,,where there were often as many as eight junctions per
190
TARE SA ANALYSIS RESULTSOF SIMPLERFCRESSION a)
Kenya Level of Statistical Significance
Regression Constant a
Regression Coefficient b
Correlation Coefficient r
3.9166
- 0.2482
0.1507
0.6237
not sig at 10'.
Vertical curvature (m/km)
2.2846
, 0.00 22
0.0145
0.0601
not sig at 10%
Horizontal curvature (deg/km)
1.7674
0.0268
0.5645
2.6201
sig at 5%
Surface irregularity (m/ km)
1.1837
0.0004
0.3984
1.7907
sig at 10%
Junctions per kilometre
1.685S
1.2476
0.6968
4.0061
sig at 5%
Independent Variable Av width (m)
b)
t value
JamaicA Level of Statistical Significanceý
Ind'ependent Variable
Regression Constant a
Regression Coefficient b
Correlation Coefficient r
Av width (m)
7.6658
- 0.8418
0.4802
2.8445. -
Sig at 5%
Vertical curvature (m/km)
2.6969 2.
- 0.0033
0.0346
- 0.1798
not Sig at 10%
Horizontal curvature (deg/km)
2.3654
0.0014
0.1224
0.6407
not Sig at'10%
Surface irregularity (mm/km)
0.7750
0.00039
0.3643
2.10
Sig at 5%
Av sight distance (metres)
3.1711
0.0042
0.1324
0.6941
not Sig at 10%
2.8797
sig at Son
Junctions per kil ometre
t valu3
I 1.1082
0.3054
0.4847
191 1
increase kilometre would per
junctions increase three of an
kilometre,
the accident rate by one accident per million
On the Jamaican Wroads,
vehicle-kilometres.
road width was also a very significant
8.5). (see Figure lower the the the the wider accident rate road
factor,
On the Nairobi-Mombasaroad, there was very little
(see Table 8.3) has not provided
width and the small amountof variation a significant
with accident rate.
relationship
the surface irregularity
In both countries
in the road
variation
was related
to the
higher the number of accidents the the the road rougher accident rate: I Jamaica In the was relationship per million vehicle-kilometres. statistically
significant
at the 5 percent level whilst
at the 10 percent
was significant was greater
in both countries;
similar
metres per kilometre
to the accident rate,
irregularity
a reduction
the range was yery
vehicle-kilometres I
in the accident per annum.
be to significantly was1found curvature a decrease of 35 degrees per kilometre
the accident rate by one accident per million
kilometres.
vehicle-
In Jamaica neither horizontal curvature nor sight distance
was found to be a significant result
of surface
was associated-with
In Kenya the horizontal
reducting
in Jamaica,
an improvement in roughness of 2000 milli-
rate of 0.8 accidents per million
related
(Again,
level.
The effect
than in Kenya).
in Kenya it
factor.
since the range of horizontal
This is,, a somewhatsurprising curvature
is much greater
in Jamaica
than in Kenya.
8.4.3
Multiple
regression'analysis
........
The results obtained in, the previous section show how various features of the road considered separately* were related 192
to the accident
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in is 80 behaviour Such taking unknown seconds. over pedestrians taken time the takes the a crossing pedestrian on once
Great Britain;
to cross the road without being interrupted.
Since this was about
7 secondsin Bangkokit is clear that pedestrians experienceconsiderfor this Reasons delays the further on crossing. whilst actually able can be seen from the last columnin Table 10.19. Of those vehicles given a completely free choice to stop or not stop for a pedestrian on the crossing only 17 percent did so. In somebusy periods only 3 percent of all drivers whocould have-stoppeddid so. In Great Britain
studies'
17
showed that over 75 percent of drivers
at zebra crossings. larly
Somepedestrians
stop willingly
in Bangkok experienced particu-
hazardous journeys across the road with up to 30 vehicles
driving
either
side of them as they were attempting
The author was left
to cross the road.
with the clear impression that trying
to cross
This seems N who now recruit groups of
the road in Bangkokwas an extremelyAangerous business. to have been recognised by the-authorities students armed with flags and whistles allowing
10.5.4
pedestrians
to force vehicles
to cross the road.
to stoPs thus
'
Pedestrian useage of zebra crossings
Work carried out in Great Britain117 showedthat pedestrian useage of zebra crossings is extremely good,ýwith about 80 percent of all pedestrians actually
crossing on and within
using the crossing itself.
50 yards of a zebra crossing, '
Surveys were made of pedestrian
useage of crossings
results were as follows:
301
in Nairobi and
TABLE10.20 OF ZEBRACROSSINGS, USEAGE NAIROBI
Flow on zebra crossing
Site
Flow 50 yards either side of crossing
percent using crossing
River Road
8,043
8,711
48
River Road
2,034
2,078
49
Government Road
2,660
2,450
52
Haile Selassie Ave.
2,236
1,828
55
Kimathe Street
2,576
5,776
31
Kimathe Street
6,212
6,603
48
Ronald Ngala St.
8,481
3,794
69
Tom 11boya
2,850
4,018
41
35,092
35,258
50
TOTAL
Average useage of crossings for those people crossing on and Within 50 yards either
side was found to be 50 percent ie proportionately
less people using the crossings', than in-Great Britain. 80982 country showed that within'50 yards of a crossing dangerous place for pedestrians
to cross the road.
was found to be up to six times greater'than
risk-by
is a particularly
Relative
risk
here
on the crossing itself.
If the sameis true for Nairobi',, then, proportionately pu ting t emselves at greater
Work in this
more people are
not, -,using the crossings.
10.6, CONCLUSIONS: ', ,I,, In this chapter, the'author has, to,, show that road accident --attempted, investigation
can be carried
out, at three different,
means of nationals, regionaland
local
levels,
studies.
By the use of national data (as covered in detail problems were identified developing countries
broadly.
namely by
in Chapter 4)
It was showns. for example, that
as a whole have high fatality 302
rates and severity
indices and that a lack of medical facilities,
the proportion
motorcycles on the road, the misuse of vehicles proportion
driving
of night-time
could all
of
in increase the or an
be contributing
to these
high rates.
Analysis of Kenya national proportion
accident statistics
involving
of accidents
incidence of single-vehicle
showed the high
commercial vehicles,
accidents,
the high
and the high accident rate on
murramroads.
The detailed
studies of rural
roads (Chapter 8) and urban areas
(Chapter 9) were used to show the value of regional studies.
Although it was not possible, to'carry,
accident investigations,,
out detailed
on-the-spot
selected, studies were madeto show the
importance of the road (and, environment), the vehicle and the roaduser as factors
in road accidents.
Rainfall and accident datawere,, obtained in three developing Measurementstaken ýith the portable skidmeter in these
countries.
countries showedthat where accident-rates did, not increase during wet weather, the skid resistance of, the road surface was adequates whereas in the country where accidents increased significantly wet weather the skid resistance countries usually
was frequently
during
found to be low.
In
of the Third World where the number of rainy days are less than in Western Europe and where ice and snow are almost
unknown, it
is likely
that the effect
than in Europes especially
if
of climate
the skid-resistance
on accidents
of. the road surface
is adequate.
303
is less
1
if
A survey conducted to find
showed that the majority-of
roadworthiness of vehicles
to supervise the condition
efforts
of, vehicles
countries
make
commercial
particularly
service vehicles.
and public
A survey of the condition
of vehicle
tyres in Nairobi showed
less tread depth than those in Great
that cars have significantly
Further surveys in the developing world are necessary before
Britain. positive
check on the
developing countries
statements can be made of the condition
countries
and the likelihood
of vehicle
of vehicles
in these
defects being a major factor
in road accidents.
Road-user behaviour was found to be particularly of developing countries.
poor in a number
Large percentages of motorists
drive through
has-been, showing for 20 seconds or ipore. It Stopping behaviour on appearance of-the amberýsignal atAifferent
red signals evert when the, signal
distances from the crossing wasialso found to'be poor in comparison with Great Britain. for pedestrians
Using a-zebra crossing was particularly
in Nairobi and Bangkok with many drivers, failing
stop for people actually a major factor
to
is ',, behaviour If: the. using crossing. road-user
in road accidents
so in developing countries frequently
hazardous
iniGreat, Britain
where driver
dangerous.
304
it must be even more
behaviour was not, only poor but
ll.
Since very little
work has been done on road accidents in
developing countries, to identify
' CONCLUSIONS-
the object of much of the research was simply
the basic problem, to gain an understanding of the factors
involved and to put road-accidents and in urban and rural
in the Third World (both nationally
areas) into-perspective
from Europe and North-America.
with results
ih6; ends-,of each of the chapters in
Conclusions have been given'at this
it
thesis and whilst
here, it
by making comparisons
is'not
pýoposed, to repeat them in detail
is well worth emphasising'some of, the main points arising.
a6dde'nt fatalities From the comparison of- ,roadýý
'and the number
of deaths from diseases considered by developing countries to be of particular
concern, road accidents must already be regarded as a
serious social
problem.
Further,
whilst'deathsfrom-these-diseases
are decreasing, those from road accidents-are rapidly increasing.
2.
The study of accident rates in developing'countries
fatality
rates (per licensed
North America and, unlike opposed to decreasing.
vehicl6), were higher''than
Severity
3.
countries
were increasing
I were 'clearlý"'related"to'
as
the lack
available,. "",
A review of accident cost studies
showed that,
in''Europe and
indices were'hi-gh, (ie the proportion
of all accidents that areIatal)-and, of medical facilities
countries
the'd6eloped
showed that
as in Great Britain.,
approximately
carried
acciden road
out in specific
st developing
one'percent, of their"toial"gr6ssdomestic
305
countries
product each year. costing
India and Nigeria 1200 million
These figures
4.
Thus for example road accidents may already be and over 140 million
each year.
cannot by any means be regarded as insignificant.
Accident rdtes were shownto be high in both urban and rural
areas of the Third World. Rural accident rates were related to road design and the equations derived comparedwith similar relationships obtained in developed countries.
Rates were always greater in the
rural roads in developing countries for-similar
levels of vehicle flow
and for similar levels of geometrlic design. In addition, were greater on busy shopping streets in cities than in Great Britain, pedestrian flows.
accident rates
of the Third World
again for similar levels of vehicle and
Other factors such as poorly maintained vehicles or
poor road-user behaviour are. obviously --ý contributing
to these high
rates.
5.
Surveys showedthat accident data collection
cedures varied greatly in the different operated, a fairly
effective
and analysis proMost of them
countries.
accident collection
system which
is perhaps not surprising because the information collected by the police is used mainly for legal purposes. Few countries analysed the road accident data in any great detail,
failing
therefore to obtain a
clear understanding of the road accident situation.
Thus few were
able to say where accidents happened, to what class of road user and in what type of accident. introduce effective
6.
Without such information it is difficult
remedial measures.
A detailed study by the author of road accidents in Kenya, showedthe high incidence of single-vehicle
306
* accidents, the
to
high proportion
of accidents involving
occupants of commercial vehicles
and the high accident rates on murram (ie gravel) information
7.
would not have been available
In order to identify
without
the road surface on accidents,
the condition
road-user behaviour at'pedestrian
was found to be particularly
poor. '
307
analysis.
in road accidents,
of weather and condition
road-user behaviour in developing countries. Britain,
a detailed
what may be the major factors
selected studies were made of the effects
Such
surfaced roads.
of vehicles
of
and finally
In comparison with Great crossings and traffic
signals
12.
Having done much to identify factors
basic problems and some of the major
is inevitable
it
involved,
RECOWENDATIONS
the question of introducing
that some thought must be given to remedial measures for dealing
effective
with the accident problem.
In Chapters 8 and 9, accident rates were derived for the various urban and rural
must be-recognised that merely
roads studied'but'it
being in possession of such rates does not immediately enable the engineer to know to which roads remedial measures should be applied first.
This difficulty
is-illustrated
with the-hypothetical
data given in
Table 12.1.
FromTable 12.1 it can be seen that neither the casualty nor accident rates indicate which is the more dangerousýroad nor which should be treated first.
Perhaps road A with over twice, the numberof accidents
as road B offers the greatest potential
for accident reduction.
But
if road A is a dual carriageway with its scattered, along, -accidents, length it may require greater expenditure of funds'ýthan road B to achieve a similar reduction.
Thus more information is: required about, the type
of road and type of accident taking place and'it
should be borne in mind
that an accident rate derived for oneýpurposemay not beýsuitable for another. 118 As stated by Chapman:
'What matters in selecting
locations
present rate of accidents per unit rate of acridents
of vehicle
distance
nor the present
per year (both of which may vary widely) ýbut. the
saving in accidents per'year within
for treatment is not the
that'could
budget", given a 308 1
be'achieved: by available
methods
TABLE 12.1 ACCIDENTDATAON TWOROADS Road A
Details
5
Length (Km)
103,000
Averd9a annual daily traffic in 3 1.11umber years of accidents Numberof casualties in 3 years (fatal and serious) Average number of accidents/Km/PA Rate 1.
Casualties/millionVeh.,
Rate 2.
Accidents/million
In developing countries scarce, it
is essential
Kms.
Veh.
Road B -6 4,000
30
14
38
18
2.0
0.78
0.69
0.68
0.55
0.53
IKms..
I ,a- Ii al -rI I I esourc-es are particul arly whereýfin nc
that the saýings in'accident
costs are maximised.
This could be achieved as follows 0 It
At a numberof locations,
the numberof accidents that could be
prevented following an appropriate remedial measurecould be estimated together with the cost of applying such measures. If the average cost of an accident in a particular
country is known (see Chapter 5), the
' location'. be By a'ssessedat each savings in accident costs can dividing savings by costs, a cost-effective'ratio these can then be listed until
can be obtained;
from the'highestýto-the'lowest
and implemented
the budget is expended. In this method'it is neither the accidents
per unit vehicle-distance nor the numberof accidents per year that is in *per but the saving accident costs unit spent that is expected used, used as an index for site selection.
The problem of having to estimate a reduction, in the number of accidents following a given road improvementremains. been done on this
Muchwork has
subject in the developed. world but there is no
309
guarantee that similar
results it
In Britain
countries.
reduced at busy junctions
could be obtained in developing
has been estimated that accidents can be by 60 percent by installing
a roundabout,.
or that on a busy
installing 40 by percent or
traffic
shopping street,
accidents can be-reduced by-50 percent
by introducing
pcdestrian
a zebra crossing.
signals:
It was seen in Chapter 10 that
light-controlled is behaviour at poor road-user
signals
it in developing unlikely countries crossings -is. -and. reductions
that percentage
in accidents as large as these could be achieved in the
developing world without extremely useful if carefully
and at zebra
improving road user behaviour.
changes in accidents at junctions
monitored as signals
effectiveness
etc were installed
It would be etc could be
so tnat their
from a road safety point of view could be assessed.
Someidea of where the expenditur eue wo Id b the be by of results some obtained can examining
like ly to take place obtained'earlier.
Rural accident rates in Jamaica and Kenya were of the order of 3.0 per million
vehicle
Kms. Urban accident rates in Nairobi were of the
order of 20 per million of accidents,, vehicle
vehicle
Kms. Hypothetical
values of number
flows and road lengths leading to such values
might be as follows: -
310 F
TABLE 12.2 URBANANDRURALACCIDENTRATES HYPOTHETICAL Area _Urban
Value Injury P.A.
Rural
accidents
146
22
Road length (Km)
10
Average annual daily traffic
20,000
Total veh. Kms P. A (million) Accidents per million vehicle
2,000
7.3
7.3
-
20.0
Kms
3.0
It can be seen that the total numberof vehicleýkilcmetres The accident rates,
7.3 is the the two million. same, on roads million
vehicle
kilometres
travelled)
roads in developing countries
(per*
-rural urban and
are týpical-of
ie 20,,and 3 respectively
of accidents ara, very much differents'146
travelled
but the numbers
on one kilometre
of urban road
and 22 on ten kilometres of rural road.
The methodsby which accidents might be 'reduced on'these roads is obviously different.
From relationships
derived"in'Cha'pter'8
it can
be seen that major improvementsto the geometry and design of the rural road would have to be effected at considerable'cost of accidents by 30 percent.
(Thus saving on this
to reduce etc number example, a total
of
about 7 accidents).
The methodsmentioned above that can be used to reduce accidents in urban areas can also be applied in cities as already stated,
they are likely
-the Thi rd'14orl d but of
to"be less effective.
311
If the
is only half that found in Great. Britain,
effectiveness
in the number of accidents is nevertheless
still
ber of urban accidents the nu:-,.
to reduce by 20 - 25
by installing
In this example 30
and zebra crossings.
traffic
to be greater for improvements introduced rural
directed.
is likely
in towns and cities
is perhaps in this area that effort
Methods could of course be refined,
expected lives
In other
road.
of accident cost savings to expenditure
roads, and it
signals
40 accidents might be-ýre-
vented at a much lower cost than redesiQ-ning a rural words, the ratio
In the
considerable.
example given in Table 11.2 it might be possible percent,
the reduction
than on
should be where the
especially
by discounted the the vary, use of costs measures of
and benefits.
The problem still
remains of knowing what safety measures to adopt
and in consequence how to allocate example should efforts
ba- diracted
or should money and effort
scarce financial
resources.
For
at improving infrastructure
solely
be spent on education,
research,
propaganda
73 by Sabey As enforcement? or stated
'one important facet of interacting illustrated
in relation
to remedial action.
largest part in contributing it that recognise
factors
to accidents.
can already be
Humanfactors
play the
Yet is is important
be easier and cheaper to effect may
environmental remedies to counter human failing
engineering
to or
than to influence
humanbehaviourl.
Whilst this is withoutdoubt true in Great Britain
where road-
user behaviour must be regarded as of a generally high standard, it may not be so in developing countries. 312
As was shown in Chapter 10,
traffic
lose a great deal of their
signals and zebra crossings
iveness because of extremely poor user-behaviour little
point in spending considerable
facilities.
In the author's
opinion,
stringent will
and there may be
sums of money in improving these strenuous efforts
to improve road-user behaviour by better driving
effect-
should be made
safety education,
test and by improved enforcement.
a more
Only by so doing,
the road accident problem in the developing world be brought to
manageable proportions.
313
-,
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an analysis of the
LISTER RD and BM MILSOM. Car seat belts: injuries
sustained by car occupants.
1963,191t
Practitioner,
332-40.
108.
NEILSONI D.
109.
FARRB N.
Autocar. 1972, (June).
The Way forward for car safety.
Seat belts
the proportion Ministry
occupants using them.
of cars fitted
of Transport,
and of
RRL Report LR 342.
Crowthorne, 1970 (Road Research Laboratory).
110.
F A. WHITLOCK
Death on the road: a study in social Ltd. 1971.
Tavistock Publications
RA and AL MOSELEY. Humanfactors McFARLAND safety,
Harvard School of Public Health,
112. McFARLAND R A.
violence.
in highway -transport
1954.
p. 50.
Current research in road safety in the United
States of America. Prepared for publication
in Practitioner,
1962, p. 4.
113. TILLMAN WA and GE HOBBS, Accident-prone automobile driver: study of psychiatric
and social background. Amer. J. Psychiat.
1949,1069 pp. 321-31.
114.
DREWG C.
The study of accidents.
Bull.
Brit.
Psychol.
Soc.
1963,163, pp. 1-10.
115. BEAUMONT K and RF NEWBY.Traf fic Law and road -safety research in the United Kingdom. British
countermeasures. National Road
Safety Symposium,March,1972s Canberra.
327
116.
MACKIEMA and GD JACOBS. Comparison of road-user behaviour light and zebra at panda, Control, 1965,6,
117.
crossings.
Traff.
Engn., &
(12), 714-718,732.
JACOBSG D, SJ OLDERand DG WILSON. .11% comparison of x-way and Report RRL Ministry Transport, of crossings. other pedestrian LR 145.
118.
controlled
Crowthorne, 1968 (Road Research Laboratory).
CHAPMAN R A.
The use and abuse of accident rates.
16 August 1974, pp. 26-29*
f
328
The Surveyor,
APPENDICES'TO'CHAPTERS33,4 and 9.
329
APPENDIX3.1 FROMUNITEDNATIONS' DEMOGRAPHIC YEARBOOKS DATAON DISEASESCOLLECTED
From the 1969 edition into two parts,
onwards, the table showing causes of death is divided
A&B.
Part A shows deaths, and, death rates classified
according to the "Abbreviated
list
recommendedby the International International revision)
Lists
of 50 causes for tabulation
of mortality",
Conference, for the Seventh revision
of Diseases and Causes of Death.
is kncwn or assumed to have, been used by all
of the
The 1955 (Seventh the countries
or
areas for whomdata have been included in part A'and in Demographic Yearbooks previous to 1969.
Part B includes data classified
according to the "Abbreviated
50 causes for tabulation of mortality", Conference for the Eight revision
list
by the International recommended
of the International
Lists
of Diseas'es
and Causes of Death, adopted by the 19th World Health Assembly.
COLLECTED FROM DISEASES FORWHICHDATAWERE UNITEDNATIONS' YEARBOOKS DEMOGRAPHIC
Group into which disease was classified 1:
Infectious
Disease
diseases
Cholera Typhoid fever Plague Diphtheria Whooping Cough Meningococcal infection Poliomyelitis (Acute) Smallpox -Measles Typhus and other ricksetial diseases Malaria Syphilis and its sequelae All other diseases classified as infectious and parasitic Rheumatic fever Influenza
330
of
Diseases for which data was collected Yearbooh
from United Nations'
(Continued)
Group into which disease was classified 2:
T.ntest-*:nal diseases
Disease -
3:
Demographic
Diseases of the respiratory system
Dysentery, all forms Enteritis and other diarrhoeal diseases Ulcers of stomach and duodenum Appendicitis Cirrhosis of liver __Tubercullosis,of the respiratory system Bronchitis'
4:
Neoplasmic diseases
Malignant neoplasms Benign neoplasms and neoplasms ý'ofunspe_cifjed nature
331 ,
AkNDIX F&Ulity
Country
veer
Fatalities
and injury
rates over a 10-year peri od (1958 - 68) I Populat ion (000's)
Vehicles
Injuries
TABLE4.1
2.526.692 4.463,000
Fatalities
per person
per 10.000 person
per 10.000 person
0.266 0.367 '
2.26 2.78
S7.05 67.53
8.50 7.58
214.48 184.20
98
0.100.
0.92
, 28.41
9.21
283.58
165
0.132
9.64
413.99
9.500 12,173
Australia
19se 1968
2.147 3.382
54.193 82,210
BahamasThe
1957
9
277
9 768
1967
21
902
21:798
Barbados
1958 1968
29 39
950 1.056
236 252
British Honduras
19S7 1967
7 16
266 365
9,087 1a 500 . 1,311 3.5&0
Cyprus
1958 1963
1. 719 3: 031
1
112 k 117
great Sri taim 19sa 196a
S.970 6,310
1958 1968
6S 125
i9se 1968
170 347
jam i C&
l9ss 1965
78 279
JAP4R
1958 1963
8.243 3.038
Guyana Kong 1
,,
,
Injuries
Fatalities
Injuries
'Vehicles
per 10,000 vehicles
per 10,000 vehicles
1. 27
64.67
0.039 0.073
1.23 '1.55
40.25 41.90
31.91 21.08
1045.45 570.81
as 112
0.015 0.032
0.82 1.43
31.20 32.59
$3.40 45.20
2030.00 1031.01
36,950 67.789
558 622
0.066 0.109'
2.00
.. 31.31 48.72
30.31 17.20
465.22 447.10
7 902 313 3 3.797 14:445:000 342.398 342* 0398 13.8" 1.218 32,49S 1.955, 1 955 . 37.777 7.000 109.736 11.596
SO.500 55,283
0.156 0.261,
1.18 1.23
62.14 1 61.94
7.55 4.71
39?.10 237.02
540 719
0.026 0.045
1.20 1.72
22.56 27.19
47.00 38.47
$80.76 601.63
2.806 3.925
0 013 0: 028
'0.61 0.88
24.95
45.00 31.62
1852.98 1056.72
29,024 65.300
1.554 1.791
0.019 '0.036
O.SO 1.56
19.54 28.89
26.87 42.73
1047.06 792.50
185.390 1.317.000 828.071, 12.870.000
92,000 100.510
0.014 0.128
20.15 82.39
62.59 12.46
1413.03 643.41
3.73 4.82
38.44 65.70
388.89 483.30
3.039 S.175
J
1958 1968
282 670
2 SS31 4: 9Z9
73.358 101.972
7.652' 10.209
0.009 0.010
0.90 1 60 . 0.37 0.65
Malawi
1958 1968
92 1b,2
8561,10.100 17.005 1,54?
2,800 4.286
0.004 0.004
0.34 0.35
3.13 3.71
90 34 89:40
840.48 909.73
Mauritius
19S7 19671 19581 1963
ss 97
1,693 2.270
11.300 21.921
597 782
0.019 0.028
0.92 1.11
28.30 29.00
48 60 0: 02
1500.21 1040.10
379 SZ2
11.480 17.698
610.000 1.100,000
2.282 2,776
0 267 0: 396
1.66 1.88
49.99 63.75
6.21 4.76
187 02. 160:89
1958 1968
193 312
3.817 9.264
82.594 246.798
I'sis 1,988
0.054 0.124
1.27 1.57
25.19 46.60
23.36 12.64
462 70 375:40
1956 1966
93 143
2.890 4.213
30.206 S9.951
743 995
0.041 0.060
1.2s 1.44
38.92 42.34
30.79 23.85
956.76 703.74
1956 11966 1 l9sa 1968
310 $14
3.846 4.536
30.312 $1.000
6,046 8.000
0.005 O.DD6
0.51 0.66
6.36 5.67
102.27 100.80
1268 889:41
37,000 $5.200
68.298,000 2,000.WO 08.ODO. 000
174,882 201.152
0.391 0.537
2.12 2.74
99.43
5.42 5.11
18S.19
1958 1963
131 Gil
3.000 4.144
0.014 0.018
0.44 1.49
4.11 12.69
30.95 83.30
291.S2 681.49
Kenya
NewZealand Sift"Porm Trinidad a Tobago Uganda USA Zambia
,
1 234 5: 043
-
42.330 74,ODO
332
APPENDIXTABLE4.2 rATALITY AND INJURYRATESOVERA 10-year PERIM (1961 - 71) Country
Year
Fatalities
Injuries
I
Vehicles'
population 000 s)
Australia
1961 1971
2. S24 3.590
60.749 91.036
3.001.903 5.006,446
10 I'll 12: 730
Botswana
1961 1911
14 44
133 336
2,983 7.798
British Honduras
MI 1971
7 is
220 393
Ceylon
1961 1971
434 688
9.62S 8.416
Cyprus great Britain
Kong
1961 1971 1961 1971
Vehicles per person 1
Fatalities Injuries Injuries Fatalities per 10, 000 per 10, 000 per 10, 000 per 10 , 000 person person vehicles vehicles
0.286 0.394
2.40 2.82
57.81 71.51
8.41 7.17
202.37 181.84
332 618
0.009 0.013
0.42 0.71
4.01 5.44
48.56 56.42
461.33 430.88
1.835 7.440
93 123
0.020 0.061
0.7S 1.46
23.66 31.14
38.15 24.19
1198.91 514.78
102,886 180.249
10.168 12,849
0.011 0.015
0.43 0.54
9.47 6.55
'8 42. i7 38.
935.50 466.91
0.077-
1.81
32.70
23.69
0.157
2.11
66.98
. 13.44
428.74
0.189 0.267
1.31 1.38
65.09 61.60
6.97 5.16
346.10 230.98
1.900 44.316 IOS 100.4 135 1 4.287 342.959 9.906.300 6.908 7,696 344.390 14.910.000
581
1 1
S2.676 55.910 ,
426.66
1961 1971
81 184
19200 2.666
189027 44.111
561 732
0.033 0.061
1.44 2.51
21.39 36.42
44.93 41.71
665.67 604.38
1961 1971
209 383
7.801 14.580
53967S 164.710
3.130 4,04S
0.018 0.041
0.67 0.95
24.92 36.04
38.94 23.25
1453.38 885.19
0.046 0.258
1.37 1.56
32 82 90:74
30.04 6.04
720.83 352.47
1 12 96S 1 308. 697 4.282.S42 94 050 16:27 949.689 26.944.000 104:660
Japan
1961 1971
Jammics
1%1 1971
177 401
49300 4.180
561OS7 $1200
1,635 1.900
0.034 0.043
1.08 2.11
26.30 22.00
31.60 49.00
767.85 $09.63
u"A
1961 1971
329 1104S
3.701 7.509
94,540 1509697
8.300 11.800
0.010 0.013
1 40 0: 89
4.46 6.36
38.92 69.41
437.78 498.28
PAIM
1961 1971
Ica IM
1,218 1.834
12.700 17.800
3, S80 4.550
0.0035 0.0039
0.30 0.41
3.40 4.14
a5:03 IC1393
959.06 1058.43
PAIAYA
1961 1971
w 1.543
6.671 14.344
211 am 739.165
7.137 11.160
0.030 0.067
0.82 1.39
9.35 12.85
27 71 20:94
314.92 194.06
NewZealand
1959, 1968'
379 SZ2
11.480 17.698
610.0" 1.100.000
2,282 2,776
0.267 C.396
1.66 1.88
49.99 63.75
Nigeria
1961 1971
1.313 3.206
10,614 14.S92
95.S62 183.100
36.'POC 56,510
0.003 0.004
0.36 0.57
2.93 2.58
137.40 175.10
1110 69 796:94
Singapore
1%1 1971
194 341
6.804 9.536
117.907 314.190
1.687 2.110
0.070 0.149
1.15 1.62
40.33 46.62
16.45
577.06 313.06
1
1
6 21 4: 75ý
187.02 160.89,
Sabah
1961 1971
14 40
170 554
10.159 43,342
475 680
0.022 0.060
0.29 0.59
3.58, 8.15
-10.85 13.78 9.92
St. tude
1961 1971
6 20
136 134
1,347 4.692
91 114
0.015 0.042
0.66 1.75
14.95 11.75
44.54 42.63
1009.65 285.59
Tanzania
1959, 1969M
277 $21
2.90S S.095
38.527 74.979
9.076 12,926
0.004 0.006
0.31 0.41
3.20 3.94
71 90 70:42
754 02 679:52
1.822 3.679
10 327 19:849
142.119 400.000
726 64 . 4ii. 23
300 17 . 461.36
1
Turity
1961 1971
28,602 36.160
0.005 0.012
0.64 1.02
3.61 5.21
U.S.A.
195-1m 37.OUO 68.298.000 174.882 2.000.000 108.0009000 201.152 I" SS.200
0.391 0.537
2.12 2.74
99.43
123 20 91:98 , 5.42 5.11
0 017 0: 025
0.83 1.87
4.95 11.28
MIS 76.41
Zambia
19611 1911
273 794
1.634 4.794
54:94361 103 IQ 0
3:2300 4 50
* 1961- 1971 fioures not available
333
167.34 137.33
185.19
APPENDIXTAELE 4-.3 1968 COUNTRIES A%DFATALITY RATESFOR DIFFERENTDEVELOPING VEHICLEOWNERSHIP (as used in initial analysis) Fata ýi ties per 601000 vehi; -Ies 43
Population (000's)
Fatalities
4,685
610
20
77
53,547
5,414
90
99
17
Vehicles
Country
Vehicles per 10,000 persons
1.
Botswana
2.
Cameroon
3.
Ceylon
142.260
11,964
598
118
42
4.
Chile
283,240
9,351
1,448
303
51
S.
Cyprus
67.789
622
117
1,090
17
6.
Dahomey
16,626
2.574
102
68
58
7.
Ethiopia
53,200
24,200
583
22
110
8.
Cambia, The
3.326
350
27
95
81
9.
Cuyara
125ý
452
38
10.
India*
23
84
11.
54
37
1
32,495 1.153,586
-719 501.760
Indonesia
623,174
114,640
ý9,734 2.328,
12.
Iraq
138,406
8,766
827
157
60
13.
Ivory Coast
83,462
4,100
362
44
14.
Jordan
26,290
2,133
197
j. 04 123
15.
Kenya
101,972
10,209
670,
100
66
16.
Kuwait
134,188
17.
Madagascar
79,960
ý700 7,199
18.
Malawl
17,005
41286
152
40
89
19.
Malaysia (W)
526,485
8*914
719
591
14
20.
Mauritius
20,40S
257
39
21.
Morocco
277,360
'795 14,580
80 1,305
187
47
22.
Niger
5,852
3,640
79
16
135
23.
Pakistan
203,165
113,000
18
81
24.
Portugal
738,229
8.894
1,650 _, 1,183
830
16
25.
Rhodesia
151.16
4,860
480
32
26.
Singapore
246,798
1,988
312
603 '1,241
27.
South Africa
1,929,000
19,167
30
28.
Swaziland
10.395
395
72
-1,006 263
29.
Syria
50,747
5,460
337
93
66
30.
Tunisia
101.826
4,807
214
212
21
20,154
2.703
443
30
173
83
31. 32.
Yugoslavia Zambia
893,555
,
74, OOC
,
617 ýý I, ",
334,
ý
15 19
148
49144
Figures for 1967
1,917
206
75
7
13 69
APPENDIXTABLE4.4 VEHICLEOWNERSHIP ANDFATALITY RATESFORBRITAIN 1909 - 1938
Year
Vehicles (000, S),
Population (000, S)
Fatalities
Veh. per 10,000 Popn.
Fatal i ties per 10-000 9 Vehs.
1909 1910
133 155
40,133
11101
33
82.6
40,529
1,277
38
82.3
1911
204
40,831
1,490
50
73.0
1912
257
41,068
1,712
63,
66.7
1913
318
41,302
2,018
77
63.4'
1914
402
41,714
2,284
56.8
1915
419
40,155
2,931
ý96 104
1916
441
39, U7
2,755
112
62.5
1917
354
39,007
2,361
1918 1919
242
38,836
2J54
62
89.0
343
40,247
2,559
85
74.6
1920
663
42,111
2,782
157
42.0
1921
860
42,769
2,755
201
32.0
1922
966
43,103
29847
224
29.5
1923
19119
43,337
39064
258
27.4
1924
1,314
43,657
301
28.4
1925
1,523
43,802
348
26.8'
1926
1,729
43,978
393
28.3
1927
11900
44,133-
430
28.0,
1928
2,053
44,330
463
29.9
1929
2,196
44,433
6,138 6,696
494
30.5,
1930
2,287
44,629'
7,305
512'-'-"*
31.9
1931
2,214
44,831
6,691
494
30.2
1932
2,240
45,084
6,6 67
497
29.8
1933
2,297
45,262
7s2O2
507
31.4
1934
2,417
45,401
7,343
532
30.4
1935
2,581
45,598
6,502
566
25.2
1936
2,769_
45,805
6,561
605
23.7,
1937
2,938
46,008,
6,633
639
22.6
1938
3,094
46,208
6,648
670
21.5
ý3,735 4,085 ý4,886, 5,329
335
70.0 66.7
APPINIDIXTABLE4.5 1968 V,ý!,ERSHIPK%DFATALITY r,,,,TES FOP DIFrERE,'%TDEVELOPING COU14TRIES VE111CLE (Using OD,4 criterion for daveloping countries) I Country
Vehicles (000-S)
Population (OUO's)
Fatalities
Vehicles per 10,000 persons
Fatalities per 10,000 vehicles
4.68S
610
20
77
43
Ceylon
142,260
11,964
598
118
42
3.
Chile
233,240
9,351
1,448
303
51
4.
Cyprus
67.789
622
117
1.090
17
S.
17.626'
2,574
102
68
58
6.
Dahom.y Ethiopia
53.200
2i. 200
583
22
110
7.
Gambia. The
3,326
350
27
95
81
8.
Guyana
32.495
719
125
452
38
9.
India
1.153,586
501,760
10,654
23
92
2,328
54
37
1.
Botswana
2.
10.
Indonesia
623.174
114,640
11.
Iraq
138,406
8.766
827
157
60
12.
Ivory Coast
83,462
4,100
362
204
43
13.
Jordan
26,290
2.133
197
123
75
14.
Kenya
101,972
10.209
66
15.
Malagasy
79,960
7,199
'670 148
100 111
18
16.
Malawi
17,005
4,286
152
40
89
17.
526.45
8,914
27
20,405
795
1.438 ý80
591
18.
M31ays;a (W) Mauritius
257
39
19.
Morocco
277.360
1,305
187
47
20.
Niger
5,852
14,580 ý, 640
79
16
135
21.
Pakistan
203,165
113,000
1,650
18
81
22.
Singapore
246,798
1,988
312
1,241
'13
23.
Swaziland
10,395
72
263
69
24.
Syria
50,747
337
93
66
25.
Thailand
535,331
33,552
1,765
160
33
26.
Tunisia
101,826
4,807
214
212
21
27.
Turkey
311,000
33,539
3,747
93
120
28.
Zarbia
74,090
4,144
617
178
83
395 5,460
1
I
APPENDIXTAKE 4.6 1971 %1: COUNTRIES 'ERSHIP AND FATALITY RATEs mi DWERENT DEVELOPING 111CLEVWN (Using ONI criterion for developing countries)
Country
1.
Botswana
2.
Vehicles (000's)
Pop-ilation 1000, S)
-Fatalities
Vehicles per 10,000 persons'
Fatalities per 10,000 vehicles
7.793
668
44
117
56
Ceylon
180,249
12,762
688
141
38
3.
Chile
323.100
8.992
1 871
359
58
4.
Cyprus
100,479
639
135
1,572
13
S.
Dahonty
17.626
--ý2,574
6.
Ethiopia
7.
Garbia, The
-42.063 3.326
s25,248 350
8.
Guyana
44,111
736
194
9.
India
1,426,0(A
550.374
12,638
26_
102 -871 2i
68,
58
17,
207,
95
ý
81
-
599
42
10.
Indonesia
925,240
124,994
3,364
74
36
11.
Iraq
123,892
9,750
768
127
62
12.
Ivory Coast
98.500
4.420
380
223
39
13.
Je)rd3n
25.814
2,383
259
108
100
14.
Kenya
135,210
11.694
1.046
116
77
IS.
Malagasy
91.394
7,400
257
124
28
16.
Malawi
23,205
4,549
164
51
71
17.
Malaysia (W)
739.165
8,979
1,548
823
21
18.
Mauritius
25,317
822
110
308
43
19.
Morocco
221.690
1,833
20.
Niger
9,904
-15,234 4,126
82
24
21.
Pakistan
220,000
113.500
19780
20
314,190
2,110
341
1,489
11
100
259
92
229 Singapore
146
83, ,,
83 80,
23.
Swaziland
10,893
421
24.
Syria
60,900
-6,451
'824
"94
137
25.
Thailand
831,800
35,335
2,404
235
29
26.
Tunisia
118.000
45
Turkey
400,000
28.
Zanbia
103,910
--528 3,679 794
225
27.
5,240 --36,110 4,275 --
337 4
-
111
92
243
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APPENDIXTABLE4.10 1968 COUNTRIES VEHICLECWNIRSHIPAND INJURYRATESFORDIFFERE14T UEVELOPING
Country
Vehicles
Injuries (serious and slight)
Injuries per 10,000 vehicles
Vehicles per 10,000 persons
1.
Botswana
4.685
209
446
77
2.
Cameroon
53,547
2.157
403
99
3.
Ceylon
142,260
7,739
544
118
4.
Chile
283,240
24,037
849
303
5.
Cyprus
67,789
3,031
447
1,090
6.
Dahomey
17,626
452
68
7.
Ethiopia
53,200
3,015
256 567
22
8.
Gambia, The
3.326
290
872
95
9.
Guyana
32,495
1,955
602
452
1.153,586
51,377
445
23
10.
India*
I].
Indonesia
623,174
11,010
177
54
12.
Iraq
138.406
1,580
114
157
13.
Ivory Coast
83,462
4,326
518
204
14.
Jordan
26,290
2,070
787
123
15.
Kenya
101,972
4,929
483
100
16.
Kurwait
134,188
2,623
195
1,917
17.
Madagascar
79,960
2,630
329
111
18.
Malawi
17,005
1,547
910
40
19.
Malaysia (W)
526,485
7,834
149
591
20.
Mauritius
20,405
1,848
906
257
21.
Morocco
277,360
20,470
738
187
22.
Niger
5,852
437
747
16
23.
Pakistan
203,165
5,129
252
18
24.
Portugal
738,229
23,533
319
830
25.
Rhodesia
151.153
5,653
374
603
26.
Singapore
246,798
9,264
375
1.241
27.
South Africa
1,929,000
54,511
283
1,006
28.
SwaziI and
10,395
476
458
263
29.
Syria
50,747
1,665
328
93
30.
Tunisia
101.826
3,473
341
212
31.
Yugoslavia
893,555
38,724
433
443
32.
Zambia
74,000
5,043
681
178
*
Figures for 1967
341
APPENDIXTABLE4.11 AND INJURY RATESFORBRITAIN 1909-1933 VEHICLEOWNERSHIP
Year
I nj uri es (serious and slight)
,
I nj uri es, per 10,000 vehicles
Vehicles per 10,000 persons
1909
30,573
2,265
33
1910
33,924
2,189
38
1911
38,293
1,877
50
1912
41,881
1,630
63
1913
48,384
1,522
77
1914
67,526
1,680
96
1915
68,500
1,635
104
1916
58,567
1,328
112
1917
48,933
1,382
91
1918
40,534
1,675
62
1919
55,382
1,615
85
1920
62,966
950
157
1921
70,241
817
201
1922
79,013
818
224
1923
93,887
839
258
1924
110,833
843
301
1925
130,658
858
348
1926
133,888
774
393
1927
148,575
782
430
1928
164,838
803
463
1929
170,917
778
494
1930
177,895
778
512
1931
202,119
913
494
1932
206,450
922
497
1933
226,328
985
507
1934
231,603"
958
532
1935
221,726
859
566
1936
227,813
823
605
1937
226,402
771
639
1938
226,711
733
670
342
APPENDIXTABLE4.12 VEHICLESFORlOkm OF ROADAND INJURYRATESFORDIFFERENT DEVELOPING COUNTRIES
Country
Vehicles
Km total road
Vehicles/lOkm of road
I
Injuries per 10,000 vehicles
1.
Botswana
4,685
7,780
6.0
446
2.
Cameroon
13,755
38.9
403
3.
Ceylon
53,547 142,260
39,292
36.2
544
4.
Chile
283,240
54,400
52.1
849
5.
Cyprus
67,789
76.5
447
6.
Dahomey
17,626
8,862 ' 6,500
27.1
256
7.
Ethiopia
53,200
23,000
23.0
567
8.
Gambia, The
3,326,
1,175
28.3
872
1,153,586
000
14.1
445
10.
India
11.
Indonesia
623,174
80,000
78.0
177
12.
Iraq
138,406
20,800
66.5
114
13.
Ivory Coast
83,462'
3511149
23.7
518
14.
Jordan
26,290
5,600
47.0
787
15.
Kenya
101,972
42,294
24.1
483
16.
KiAiai t
134,188
1,523
881.0
195
17.
Madagascar
79,960
8,363
95.6
329
18.
Malawi
17,005
10,140
15.8
910
19.
Malaysia (W)
15,425
341.0
149
20.
Mauritius
5269,485 1 20,405
1: 897
107.0
906
21.
Morocco
277$360
51,800
53.5
738
22.
Niger
7,450
7.8
747
23.
Pakistan
203,165
2501,373
8.1
252
24.
Portugal
738
414.7
319
25.
Rhodesia
0229 1519153
17,800 78,428
37.4
374
26.
Singapore
2469798
1,912
1,292.0
375
27.
South Africa
58.0
283
28.
Swaziland
109395
2ý670
38.9
458
29.
Syria
509747
109500
48.3
328
30.
Tunisia
101,826
16,728
60.9
341
31.
Yugoslavia
893,555
78,750
113.5
433
32.
Zambia
74,000
333500
22.1
681'
5,852
19929,000
3321,813
343
APPE14DIX TABLE4.13 AND MEDICAL FACILITIES THESEVERITYINDE FORDIFFERENT -7X DEVELOPING COUNTRIES
Country
Severity index
Population per availableIhospital bed
Population per physician
1.
Botswana
8*73
400
21,960
2.
Cameroon
4.01
480
26,050
3.
Ceylon
7.17
320
4,060
4.
Chile
5.68
250
2,320
5.
Cyprus
3.72
210
1,360
6.
Dahomey
18.41
930
31,300
7.
Ethiopia
16.20
2,490
65,380
8.
Gambia, The
8.52
690
18,670
Guyana
6.01
210
4,450
10.
India
15.93
1,670
4,830
U.
Indonesia
17.45,
1,470
27,560
12.
Iraq
34.36
540,
3,830
13.
Ivory Coast
7.72
5110
17,980
14.
Jordan
8.69
580
3,880
15.
Kenya
11.97
730
10,240
16.
Kuwait
7.28
150
9,640
17.
Madagascar
5.33
360
9,640
18.
Malawi
8.95
800
45,110
19.
Malaysia (W)
8.41
250
4,750
20.
Mauritius
4.15
250
4,120
21.
Morocco
5.99
660
12,930
22.
Niger
15.31
140
569140
23.
Pakistan
24.34
24.
Portugal
4.79
170
1,200
25.
Rhodesia
7.83
300
53,280
26.
Singapore
3.26
280
1,780
27.
South Africa
9.63
1190
19500
28.
Swaziland
13.14
290
71,280
29.
Syria
16.83
900
3,970
5.80
390
83,320
6.52 * 10.9 0
170
1,130
380
169100
30*. Tunisia 31.
Yugoslavia
32.
Zambia
33,560
344
91890
APPENDIXTABLE9.1 KINGSTON JAMAICA1962
No.
CENTRAL AREASTREETS
Road
Total Ini. Acc. / KM/P.A.
Av. Veh. flow/hr
52
1100
29
684
24
790
30
900
17
773
1.
Parade
2.
W Queen St.,
Spanish Town Rd.
3.
E Queen St.
Victoria
4.
Elletson
5.
Orange St.,
6.
King St.
30
549
7.
South CampRd.
27
643
8.
Orange St.
37
750
9.
North St.
43
1070
9
Av., Windward Rd.
Rd., Mountain View Rd. Slipe Rd., Half Way Tree Rd.
345
APPENDIXTABLE9.2 KINGSTON JAMAICA1962
No.
Road
'A' AND 'B' ROADS
Total Ini. Acc. / KM/P.A.
Av. Veh. fIDw/hr
1.
Retirement/Rosseau
15
264
2.
Brentford/Lyndhurst
9
457
3.
East Street
21
789
4.
South CampRd.
10
714
5.
Merrion Rd.
7
477
6.
Mountain View Av.
4
187
7.
Shortwood Rd.
5
230
8.
Waltham Park Rd.
17
335
9.
Molynes Rd.
5
282
10.
Dunrobin Av.
7
344
11.
Hagley Park Rd.
18
468'
12.
Old Hope Rd.
11
657
13.
Hope Rd.
9
663
14.
Mona Rd.
2
486
15.
Lady Musgrave Rd.
3
326
16.
Trafalgar
5
498
17.
Wellington
4
340
18.
Red Hills
4
136
19.
Mannings Hill
1
66
Rd. Drive Rd. Rd.
346
APPENDIXTABLE9.3 MOMBASA KENYA1972/73
No. *
Road
CENTRAL AREASTREET
Total Inj. Acc. / KM/P.A.
Av. Veh. flow/hr
1.
Kilindini
Rd.
20.5
1011
2.
Jomo Kenyatta
28.0
1122
3.
Tom Mboya
3.14
357
4.
Digo Rd.
9.11
900
5.
Nkrumah
5.0
714
6.
Haile Selassie
10.5
625
7.
Mbaraki
4.8
536
347
APPENDIXTABLE9.4 NAIROBI KENYA1972
No.
CENTRAL AREASTREETS
Road
Total Inj. Acc. / KM/P.A.
Av. Veh. flow/hr
I.
Ronald Ngala
52
1040
2.
Government Road
19
1157
3.
Haile Selassie Avenue
50
2064
4.
HarambeeAvenue
6
1214
5.
Kenyatta Avenue
64
2310
6.
Kimathi Street
9
973
7.
Koinange Street
7
799
8.
Muindi Mbingo Street
9
755
9.
New PumwaniRoad
69
163'7
7
1174
10.
MamaNgina
11.
Racecourse Road
86
1610
12.
River Road
23
603
13.
Tom Mboya Street
20
1206
14.
Kaunda Street
10
326
348
APPENDIXTABLE9.5 NAIROBI KENYA1972.73
No.
AREASTREETS CENTRAL
Pedestrian relative risk rate (2 yr. ped. acc. ) (ped. flow/hr.
Road
Av. Veh. flow/hr
Ronald Ngala
0.0036
967
2.
Government Road
0.0037
1110
3.
Haile Selassie Avenue
0.025
1973
4.
Harambee
0.0009
1082
5.
Kenyatta Avenue
0.0069
2148
6.
Kimathi Street
0.0005
875
7.
Koinange Street
0.0008
637
8.
Muindi Mbingo Street
0.0011
364
9.
New PumwaniRoad-
0.0090
1522
10.
MamaNgina
0.0007
960
11.
Racecourse Road
0.0108
1489
12.
River Road
0.0058
585
13.
Tom Mboya Street
0.0025
1223
14.
Uhuru Highway
0.0249
2917
15.
Kaunda Street
0.0014
297
r
349
APPENDIXTABLE9.6 NAIROBI KENYAAVENUEFORYEARS1969,70,72
No.
Total Inj. Acc. / KM/P.A.
Road
1.
Sclaters
2.
'A' AND 'B' ROADS
Road
Av. Veh. flow/hr
4.90
773
Fort Hall Road
7.79
779
3.
Ngong Road(-Dagoretti)
8.00
619
4.
Naivasha Road
3.60
206
5.
Valley Road
7.00
1100
6.
Haile Selassie Avenue
10.80
1306
7.
Lower Kabete Road
2.10
550
8.
MombasaRoad
1.50
435
9.
Marlborough Road
1.10
206
10.
Limuru Road
5.25
825
11.
Forest Road
3.45
619
12.
Ngara Road
8.80
688
13.
Ainsworth Hill
14.
Road
.,
8.25
894
Park Road
11.60
619
15.
Jogoo Road
13. 10 W
1123
16.
Outer Ring Road
4.70
206
17.
Liverpool
7.25
550
18.
St. Austins Road
1.75
413
19.
Juja Road
16.50
619
20.
Landhies Road
15.00
1581
21.
Argwings Kodhek Road
5.50
619
22.
Kiambu Road
1.50
275
23.
Racecourse Road
28.00
1100
24.
Watkins Street
13.60
481
25.
Ring Road Ngara
8.10
894
26.
Ngong Road (After
1.90
172
Road
Dagoretti)
350
APPENDIXTABLE9.7 SURBAYA INDONESIA1974
No.
Total Inj. Acc KM/P.A.,
Road
Av. Veh. flow/hr
1.
Ambengan
97.6
1621
2.
Bubutan
36.8
1509
3.
Panglima Sudirman
161.6
2674
4.
Pemuda
65.6
2485
5.
Tunjungan
155.2
2405
6.
Pasar Besar Wetan
19.2
1175
7.
Undaan Wetan
22.4
523
8.
Praban
80.0
1644
9.
Blauran
113.6'
10.
1
CENTRAL AREASTREETS
Kedungdoro
43.2
-
11.
Genteng Kali
67.2
'1291 1889
12.
EmbongMalang
49.6
90
1
1
351
1
APPENDEX TABLE9.8
No.
Road
Pedestrian relative risk rate (2 yr. ped. acc. ) (ped. flo-4/hr.
Av. Veh. flow/hr.
1.
Ambengan
0.01776
1621
2.
Bubutan
0.00672
1509
3.
Panglima Sudirman
0.02960
2674
4.
Pemuda
0.01200
2485
5.
Tunjungan
0.02832
2405
6.
Pasar Besar Wetan
0.00352
1172
7.
Undaan Wetan
0.00400
523
S.
Praban
0.01456
1644
9.
Blauran
0.02080
1379
'10.
Kedungdoro
0.00784
1291
11.
Genteng Kau
0.01216
1889
12.
EmbongMalang
0.00896,
983
352
APPE, '%'D: X TOLE 9.9 GREATBRITAIN
No.
L_
CENTRALAREASTREETS
Total Ini. Acc. /
Area
Pedestrian relative risk rate (2 r. ped. acc. ) (pf%d.- f low/hr.
Av. Veh. -flow/hr.
1.
Hammersmith Rd.
1,961
31
0.0090
2050
2.
Goldhawk Rd.
1961
17
0.0037
1519
3.
Uxbridge Rd.
1961
28
0.0070
1289
4.
Kensington High St.
1961
53
0.0034
2202
5.
Ladbroke Grove
1961
6
0.0025
718
6.
Kings Rd.
Chelsea
1961
22
0.0057
1202
7.
Kensington High St.
1967
64
0.0054
2366
8.
Kensington Rd.
1967
36
0.0059
2549
9.
Brompton Rd.
1967
66
0.0025
2468
10.
Uxbridge Rd.
1964-66
30
0.0049
990*
11.
Green Lanes Harringay
1964-66
23
0.0070
1170
12.
Slough High St.
1967
25
0.0020
1180
13.
Kensington High St.
1968
68
0.0072
2628
14.
Kensington Rd.
1968
26
0.0100
2604
15.
1969-70
98
0.0084
3070
16.
Kensington High St. London Rd/High St Cheltenham
1965
6
0.0023
729
17.
Lawford/Clifton
1965
4
O.OG13
572
18.
Southgate/London Rd.
1965
10
0.0069
1160
19.
Hammersmith Rd.
1949
27
0.0040
1242
20.
Goldhawk Rd.
1949
12
0.0038
'6'96
21.
Uxbridge Rd.
1949
22
0.0046
1476
22.
King St.
1949
23
0.0024
870
23
Kings Rd.
1949
is
0.0023
894
24.
Christchurch
1960
22
0.0020
1290
Hammersmith
Ealing
Rds Rugby Bath
Hammersmith
Hammersmith Chelsea Rd.
Boscombe
I
_I
353
II
