A study of an Asian anthropometric pedestrian in vehicle-pedestrian ...

ICrash 2006, Athens Greece, 4th-7th July 2006

A study of an Asian anthropometric pedestrian in vehicle-pedestrian accidents using real world accident data Rong Guo1, Quan Yuan2, C.E.N. Sturgess1 A.M. Hassan1 Yibing Li2 Yuanzhi Hu1 (1. Birmingham Automotive Safety Centre, University of Birmingham, Edgbaston, B15 2TT,UK 2. State Key Laboratory of Automobile Safety and Energy, Tsinghua University, Beijing 100084, China;) Contact Information: G47C, Birmingham Automotive Safety Centre Department of Mechanical and Manufacturing Engineering University of Birmingham Edgbaston, Birmingham, B15 2TT, UK Tel: +44 121 414 4212 Fax::+44 121 414 4180 Email: [email protected]

Abstract: Real-world road accident data involving pedestrians was obtained from police records in Beijing. In total, 158 vehicle-pedestrian accidents were included in this study, from which the accident characteristics were identified. The data was analysed and the overall epidemiology established, in addition representative cases were studied in-depth using MADYMO reconstructions. In order to carry out this study accurately a MADYMO pedestrian model based on Chinese anthropometric values has been developed. A comparable European size MADYMO model has also been used to demonstrate the differences between the two anthropometric types. Using the Chinese pedestrian model, a complete accident event is reconstructed, in terms of pre-impact behaviour, causation, injury characteristics, and post-impact kinematics.

Keywords: Road Safety, Accident Reconstruction, Pedestrian Accident Introduction Vehicle to pedestrian accidents are a common type of road traffic accident in motorized countries, and considerable research into pedestrian protection, has been conducted at both the passive and active level. In Europe, the number of pedestrians killed or seriously injured in road accidents has been on a downward trend in the past 10 years [1]. However, in fast developing countries like China where the motor vehicle has become a

tool in the daily life of ordinary people, the number of pedestrians killed or seriously injured on the roads is still very high and is showing an upward trend [2]. The contrast between the fast growing vehicle numbers, slow improvements to the road platform, and poor traffic safety education is mostly blamed for this upward trend [2], the vehicle development at the micro level can also play an important role. Nowadays, even in major international cities, such as Beijing and Shanghai, ageing vehicle


models from western countries can still be seen. Among such vehicles, very little or no pedestrian protection features have been taken into consideration when it was initially designed. In addition, due to the difference in anthropometry within the human body, even a EuroNCAP tested vehicle, which is considered to be pedestrian friendly in Europe, might be unsuitable for pedestrian protection in China. Table 1 gives a overview of the body parameter differences among 50% males in the UK, USA, and China. [4,5,8] 50% Male Anthropometric parameters UK

USA

China

Weight (kg)

79.75

82.1

60

Stature (mm)

1755.1

1781

1690.5

Head Length (mm)

200.2

200.9

189.5

Shoulder Height (mm)

1455.3

1459.7

1388.6

Hip Height (mm)

931.5

934.3

860.4

Thigh Depth (mm)

166.8

171.3

137.9

Knee Height (mm)

467.3

468.7

413

Table 1 In recent years, a number of new Chinese vehicle safety standards have been proposed and applied. Chinese standard frontal impact and rear impact regulation has been in place since 2002, a new side impact legislation will also come in force. Due to the high accident volume, There has always been a demand for a pedestrian accident study in China, in order to reduce the number of pedestrians/cyclists killed on the road, as well as proposing

Chinese pedestrian regulatory standards. This study has been focused on the creation of a pedestrian accident database, and the simulation of selected cases to demonstrate the use of a MADYMO model based on Chinese anthropometric values.

Chinese pedestrian accident database For this database, pedestrian accident data has been collected by the Accident Reconstruction Group in Tsinghua University. 158 fatal/serious vehicle-pedestrian cases from years 2001-2003 are investigated, recorded, and studied at an in-depth level. Figure 1 shows that in this study, most of cases included are fatal cases; 64.4% of cases in this database involving one pedestrian being killed, and another 21.5% cases involving one pedestrian serious injured. Figure 2 shows, that although there is still small number of vehicle-pedestrian impact cases which occurred in the rural areas, most of vehicle pedestrian impact are recorded in the busy urban or sub-urban areas. Figure 3 analyzed the type of vehicle involved in the vehicle-pedestrian accidents. Cars account for 51.3 % of the total vehicles to pedestrian accidents. Light Goods Vehicle accounts for another 8.9 % and Heavy Goods Vehicles account for 7% of the total accidents. Clearly, most of vehicles involved in the pedestrian accidents are passenger cars. Figure 4 represents the general weather condition when the accidents occurred. 77.8% pedestrian accidents occurred when the weather was clear and dry; 8.2% of accidents took place when it was cloudy, and 4.4% accidents occurred when it was raining. Figure 5 shows the hour of the day when the


accidents occurred,. It can be seen that the morning and afternoon rush hours are important times, and that 38.6% of accidents occurred between 1800 to 2100 hours. Figure 6 represents the road condition a at the vehicle-pedestrian accident scenes. The analysis shows that 47% of vehicle pedestrian accidents occur on the roads in good condition, 33% of accidents occur on roads in average condition, and about 8% of accidents occur on roads in poor condition. Figure 7 and Figure 8 shows the driver information. As shown in the figure, the majority of drivers involved in the pedestrian accidents are male, and the 35-40 age groups are the represented age group. Figure 9 shows the pedestrian age group analysis. Unlike in Europe or USA, where most of the recorded vehicle-pedestrian accident victims are children or elderly people [2], the most common age group found in pedestrian accidents in China is the middle age group. Figure 10 shows the gender analysis of the pedestrians in the database. Due to data protection of the fatalities, there are a large number of cases with unknown gender in this analysis. However, the analysis based on the available information shows nearly equal numbers of males and females involved in fatal pedestrian accidents. Figure 11 represents a common way to classify vehicle types in China. 44% of the vehicles involved in the pedestrian accidents have extended long bonnets, and 36% of the vehicles involved have no bonnet. Figure 12 shows the pedestrian movement period prior to the impact, 78% of cases happened when the pedestrian tried to cross the road. Figure 13 shows the location of the impact, most of accidents take place in the middle of road (72%), and this can be regarded as pedestrian trying to cross the road

without using signal controlled or pedestrian crossing facilities. Figure 14 shows the vehicle damage profile after the main impact with the pedestrian. 34.2% of cases involve damage to the vehicle bumper, bonnet, and windscreen. 15.8% of cases involve damage to both bumper and bonnet. 10.1% of cases involve damage to bumper only, and 6.3% of cases involved damage to bonnet and windscreen. Figure 15 shows the vehicle speed analysis, most vehicle-pedestrian accident occurred when the vehicle was traveling at 35-50 km/h region. 10.8% of vehicles are recorded traveling at 45-50km/h region. 8.2% of vehicles are recorded traveling at 40-45 km/h region and another 8.2% of vehicles are recorded traveling at 35-40km/h region. Further analysis has been carried out, mainly concentrated on the passenger cars. 49.4% of damage caused by the pedestrian to the cars involved damage to the bumper/bonnet/windscreen and 13.6% of damage to the cars involved damage to the bumper/bonnet only, and 12.3% of damage on the car body shell involves damage to the bonnet/windscreen. In 8.8% of cases, the pedestrian are killed or seriously when hit by vehicles at 35-40km/h, and in another 9% of cases, pedestrians are killed/injured when hit by vehicle traveling at 40-45km/h. In total, 67% of the pedestrians killed are hit by vehicles traveling at a speed over 40km/h. There are 102 cases involving single pedestrians being killed by the striking vehicle, in those cases. 32 cases or 31.4% involve damage to the vehicle bumper, bonnet and windscreen. 12 cases or 11.7% involved


damage to the bumper and bonnet, and 10 cases or 10% involve damage to bumper only. In the 34 accidents involving serious injuries, there are 41.2% of cases involving damage to the bumper, bonnet and windscreen; 17.6% of cases involved damage to bumper and bonnet, and 14.7% of cases involve damage to bumper only.

Pedestrian Accident Case Selection Information included in the Chinese pedestrian accident database has been pre-analyzed; therefore, this database provides a useful source in identifying accidents contain chosen particular characteristics. Cases involving pedestrian in 50% Chinese anthropometric value are selected for further reviews. After analyzing the database, some accidents supported by urban CCTV camera are found. Those CCTV footages are initially kept by the police for prosecution purpose. However, in order to study the Chinese anthropometry pedestrian at a micro level, those footages are studied, among them; a well document case has been selected. The whole event of this accident was accidentally captured by a overhead CCTV, by study the relevant footage frame by frame provide graphical evidence. The accident concerned took place in a narrow street on the east side of the old town in Beijing. The driver was under the influence of alcohol; therefore, very little avoiding action or braking was made by the driver. In this accident, two pedestrians have been hit by the vehicle, one of them sustained fatal injuries. The vehicle involved in the accident was a 2003 model Volkswagen Passat, which has been tested by EuroNCAP in Europe. The pedestrian who received the fatal injury was a middle aged Chinese male, his stature is

1.69m and his weight is 62kg, which is considered a close match to the 50% Chinese anthropometry shown in Table 1. The location of the accident was on a narrow one-way street. The vehicle was traveling towards the east at high speed, estimated at 50km/h by analysis of the roadside reference objects from the CCTV recording. The pedestrians were walking in the same direction as the vehicle was traveling, unaware of the approaching vehicle from behind, as shown in the Figure 16-Frame 1. In the period before the impact, the pedestrian was turning to his right, and therefore positioned himself for a direct side impact by the vehicle. He did not have enough response time to perform any act of self-protection against the oncoming vehicle, as shown in the Figure 16-Frame 2. The vehicle hit the pedestrian without applying its brakes; the pedestrian was thrown into the air. Eventually, he landed some 22.5 meters from the point of impact and landed on his head, with his head pointing west and his feet pointing east, as shown in the Figure 16-Frame 3 and Figure 16-Frame 4. From the impact marks on the vehicle body shell, and from analyzing the video, it was determined that the contact points are on the offside of the bumper, along the offside bonnet leading edge, and the head strike point was around the bottom left of the windscreen, as shown in the Figure 17 and Figure 18. The victim received a fatal brain injury, dislocated shoulder, abrasions on his elbow, wrist, and knee, and he also received a hematoma on his left upper leg. As marked in the Figure 19

Accident Simulation MADYMO environment

in

the

The selected pedestrian case has been reconstructed in the MADYMO environment.


The TNO human body model has been widely used in the pedestrian safety application [3], it consists of 52 rigid bodies, the outer surface is described by 64 ellipsoids and 2 planes on the feet. The anthropometry data of the TNO human body model was based on the database of the RAMSIS software package (RAMSIS 1997), in this database, the Western European population aged 18-70 years of age in 1984 was used. In order to use the TNO model to represent pedestrians of different sizes, the common practice in adjusting the size of the human body model is to use MadyScale. However, scaling can only adjust the model’s main parameters to a certain percentage. Even the fashion industry has agreed that it is not advisable to simply scale their European/USA specification to meet the needs of the Asian market [6]. Therefore, in terms of anthropometric accuracy, this model cannot be made to represent the Chinese 50% standard pedestrian very well. Therefore, a Madymo pedestrian model based on Chinese anthropometric parameters has been developed. The pedestrian model was initially designed using 18 ellipsoids, one ellipsoid represented the head, two ellipsoids represent neck segments, single ellipsoids are used to represent the chest, waist, hip, upper arms, lower arms, hands, upper legs, lower legs and feet, as shown in Figure 20. The anthropometry data of this pedestrian model is obtained from a number of sources. It is mainly based on the Chinese Anthropometry Value Handbook published by People’s Health Publishing after extensive studies into this subject for over 10 years by a special committee on the subject. The anthropometry data used for this model are also supported by other data sources, such as the People’s Size 1998 published by DTI, the GB10000-88 set out by the Chinese Standardization committee.

The total weight of the pedestrian model is 60kg as suggested in the People’s Size 1998. The weight percentage of each body segments has been selected based on many different factors. The first factor considered was the percentage of the skin area, this is the method used in China to determine the seriousness of the injury sustained following an accident, as suggest in the GB18667-2002 set out by the Chinese Standardization committee. TNO models have also been used as a reference, in which the RAMSIS software package is used to determine the weight of each body segments. The model’s neck is modeled by 2 kinematics joints, one free joint at the lower neck location and another free joint at the upper neck location respectively. The free joints in the neck allow elongation, and the stiffness in the each direction is modeled by using Six-DOF restraints at the joint locations. The values of the stiffness’ used are scaled based on the values obtained from the TNO facet occupant model. Its Z-direction stiffness is obtained from the TNO facet occupant model, and the stiffness’ in the X and Y directions are higher than in the Z-direction, in order to prevent lateral translation. A damping coefficient is used in the Z-direction, which is also based on the facet occupant model from TNO. It is very difficult to construct a model to accurately represent each actual section of the human body, such as chest, ribs, shoulder, abdomen, pelvis, and breasts for the female. Initially, the pedestrian was modeled used 3 ellipsoids and 3 kinematics joints. Six-DOF restrains were also used to determine the stiffness of the torso, as shown in Figure 19. Contact characteristics have been obtained from Eurosid biofidelity requirements (Roberts et al 1991, ISO-N455 1996)


The hip joints were modeled by spherical joints. The stiffness curves for these joints were obtained from the validated pedestrian model by Yang & Lovsund (1997). These joint stiffness curves are also used in the TNO pedestrian model. The joint stiffness curves were found to agree with a range of motion in the RAMSIS human model (Speyer and Seidl, 1998). The leg and knee joint are the most complex part of the model. In the TNO human body model, spherical joints are used, and it is said to represent the fracture and bend under external loading. In this Chinese pedestrian model, only two free joints at the knee location are used and modeled by Linear lateral bending stiffness agreeing with the dynamic data of Kaizer et al, (1997) was selected, this data is considered comparable to the EEVC requirements (EEVC 1994). The knee flexion and extension stiffness had been implemented using reported volunteer data (Engin. 1979 Ma et al 1995). For the knee lateral shear force, an injury tolerance level of 4 KN in force and 6 mm in displacement has been used, which is as the EEVC 1996 standard. This results in a linear stiffness of 6.7E5 N/m, which has been applied in this pedestrian model, as well as in the TNO model. Forward and backward shear force is considered of less importance in the pedestrian applications, therefore the stiffness selected for lateral shear force in those two directions was selected as the same value. In the ankle joint, the rotational stiffness for ankle dorsiflexion was obtained from the volunteer tests with extended knees, the rotational stiffness for inversion/eversion was also obtained from volunteer test data (Craandall et al.,1996)

In order to show the difference between the European size pedestrian and Chinese anthropometrical pedestrian, a simple vehicle pedestrian test has been carried out to demonstrate the similarities and differences. Figure 21 shows, two pedestrian models built on the two different anthropometry datasets have totally different responses to vehicle impact within a 200ms period, which simulates the initial impact with the vehicle front profile. When the vehicle is traveling at 13.33 m/s, the Chinese pedestrian model tends to dive faster and earlier than the taller European counterpart, due to the shorter length of its upper leg, and shorter width of its hip. The hip tends to hit the bonnet first, the head then strikes the windscreen, where for the European size pedestrian, the shoulder strikes the windscreen first. The impact location for the Chinese anthropometry model is at the bottom of the windscreen, where it is considered to be very stiff and extremely harmful for the pedestrian. It is found from the animation that the kinematics response of the pedestrian model matches the basic trajectory in the selected real world pedestrian accident. The primary impact has produced a head resultant acceleration value of 900 m/s2 over a 10ms period, which translates to a HIC value of 1134. Such a HIC value can be considered as serious, the value of fatality probability from this impact is 53.294%, however, the ground impact has been much more severe than the initial impact with the windscreen. A HIC value as high as 4,000 can be seen from this impact, which would be clearly fatal From the head acceleration-time graph, it is also to see the difference between the throw distance for the two models. The throw distance of the Chinese anthropometry pedestrian model is 24.96 meters, which compared to the actual throw distance, estimated from the video


record , it is around 11% less. The first model shows that there is a significant difference between the pedestrian models of different anthropometry. Nevertheless, there were a number of disadvantages in this model. Therefore, a second model has been developed based on the first concept. In the first model, three ellipsoids were used to represent the torso. By using such a method, the pedestrian contact with vehicle part, such as bonnet leading edge, was somewhat unrealistic. It is very difficult to show all the contact points and correct contact path with the vehicle, as there will only be 3 contact points on each side of the torso. This may lead to chances of multiple contacts with the same vehicle part, and as a result, lead to extremely high resultant stiffness. Therefore, a modified torso shown in Figure 22 has been used, and there is only one dynamic joint, its stiffness is modeled using Six-DOF. The pedestrian shoulder is also considered as a very complex system, in the first model, the shoulder has been considered as an integrated part of the chest. In the new model, the shoulder has been separately modeled. The elbow and the knee model has also been re-modeled, a ball joint has been added, this is used to help simulate the fracture and dislocation of the joints. In addition the contact between the elbow and the vehicle components can be more accurately expressed. An extra 2 kg weight has been add to the torso, as in the selected case, the pedestrian’s actual weight was 62kg. The vehicle model has also been improved. Its geometry has been modified to match the actual vehicle involved in the selected accident, namely the Volkswagen Passat. Three ellipsoids have

been used on each vehicle frontal components. As shown in Figure 23, for the vehicle bumper, 3 rigid bodies have been given same stiffness. However, on the bumper leading edge, bonnet, and windscreen, higher stiffness has been given to the ellipsoids at the sides to represent the higher stiffness of the vehicle body frames. The simulation duration has been set to be 2 seconds in order to reconstruct the whole event, Figure 24 shows the kinematics of the reconstructed the event. It is shown in the animation that the kinematics movement matches the CCTV footage better than the first model. The head impact point is around the lower middle section on the offside part of the windscreen. The pedestrian model throw distance is 23.76 meters as shown in the figure 25, which is very close to the real world event. The model eventually landed on his head toward the west and feet toward east. Figure 26 shows that the HIC value in the initial impact is around 1007, the HIC obtained from the ground impact is still much higher than the primary impact, it is recorded as being 4328. This is inline with the pedestrian injury documentation, as well as the video footage.

Discussion and Conclusion Using CCTV footage to support computerized simulation of a pedestrian impact is a new method. This can support the simulation with a precise view of the real world kinematics. However, due to the limitations within the model, there are still substantial differences between the model and the actual real world event. For example, the model’s in-the-air movement is quite different from the real pedestrian. It is also difficult to obtain an accurate value for the ground coefficient of friction; hence, the throw distance in the simulation is often different from the actual one. The model’s shoulder is a critical part, as


Chinese pedestrian is generally shorter, the shoulder would normally strike the bonnet first, and therefore, the structure and the stiffness of the shoulder model can be very important. In the reconstructed case, it is shown that the initial impact with the windscreen, which result to a HIC value of 1007, would be serious and maybe fatal, but it could also be non-fatal, the value of fatality probability is 47.702%.. The ground impact, which resulted in a HIC value of over 4000, would definitely be fatal. This value is based on assumption that the ground stiffness is 3000N/m2, which is the default TNO value, but the actual ground stiffness might be different to this. Clearly, as shown in the first simulation, there are significant differences between the pedestrian of the Chinese anthropometry and that of the European anthropometry. Generally speaking less consideration has been given to Asian anthropometric pedestrian protection in the vehicle designed for or sold in the Chinese market. With the increasing concern in road safety development in China, such differences should be taken into account. In order to obtain a more realistic and accurate result, parameters other than anthropometric values for Chinese human body, such as joint stiffness and injury tolerance values need to be used. In some trial simulation runs, stiffness values within a 20% range have been tested, and can result to considerable kinematics difference as well as great difference in HIC value. For example, due to the thickness difference, the damp coefficient in the shoulders of Chinese anthropometric pedestrian has been reduced to 1.9, which is 20% less than the default value. This results HIC value of 1127.2 from the head impact with the windscreen, which results to a probability of fatalities value of 53.003%.

The database used for this study will be subject to ongoing review, a similar database for cyclist accidents is also been developed for further study and analysis. These two databases will be later interlinked and analyzed.

Acknowledgements This database collection and study discussed in this paper is sponsored by the Chinese National Natural Science Foundation Committee (NSFC) Grant No. 50422284.


Figures Weather Condition Clear and dry

70

Rain Cloudy not rain Snow

60

Frog Unknown

Percent

50

40

30

20

10

0 1 Pedestrian 1 Pedestrian 2 Pedestrian Killed Seriously Killed Injured

4.00

12.00

999.00

Injury

Figure 4

Figure 1

50

20

40

Count

30

10

20 5

10

0

.00 4.00 6.00 8.00 10.00 12.00 14.00 16.00 18.00 20.00 22.00 3.00 5.00 7.00 9.00 11.00 13.00 15.00 17.00 19.00 21.00 23.00

0 city

Outer City

Rural Area

Hour

Accident Region

Figure 5

Figure 2

60 50

50 40

Percent

40

Percent

Percent

15

30

20

30

20

10 10

0

h Ve

D

s Bu

4W

g Ar

V

V

G M

Figure 3

G H

V LG ar C g h in ac ur co To er ng n va er ng e ss Pa

e cl hi Ve

e ss Pa

i in M

ar C

Vehicle Type

0 Good

Average

Poor

Road Condition

Figure 6

999.00


Figure 9 Pedesrain Sex

25

Male Female Unknown

Percent

20

15

10

5

0 15

25

35

20

45

30

40

Unknown 50

Drive Age Group

Figure 7 Figure 10 Driver Sex Male Female

50

Unknown

Percent

40

30

20

10

0 Long Bonnet

No Bonnet

999.00

Vehicle Frontal Profile

Figure 11

Figure 8

80

40

60

Percent

Percent

30

20

40

20

10

0 Crossing Road

0

10

20 15

30 25

40 35

50 45

Ped Age Group

60 55

65

70 Unknown

Walking by road

Standing

Pedestrian Movement

Figure 12

999.00


60

50

Percent

40

30

20

10

0 Mid of road

Junction

Pedestrian Crossing

Controlled Crossing

999.00

Contact Position

Figure 13

40

Percent

30

20

10

0 e o ds nn +R in Bo en +W cre r+ et pe ds nn m in Bo Bu +W r+ et pe nn m n Bo Bu ee r+ cr pe ds m in Bu +W w et no nn nk n Bo U ee r+ cr pe ds m n i Bu +W et de nn Si n Bo r+ ee pe cr m ds m in W Bu r+ et pe nn m Bo Bu r+ pe m Bu

de n Si ee cr ds in W et nn Bo r pe m Bu

Damage location

Figure 14

25

20

Percent

Figure 16 15

10

5

0 20

25

30

35

40

45

50

55

60

65

70

75

75+

NA

Vehicle Speed Group

Figure 15 Figure 17


Figure 18

Figure 21

Figure 19

Figure 22

Figure 20

Figure 23


Figure 24

Figure 25

Figure 26


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