Final formatted paper Driving Performance of Drivers ...

IRJSSE / Volume : 2 / Issue: 11 / Nov.. 2014

ISSN: 2347-6176 2347

International Research Journal Of Sustainable Science & Engineering. Engineering A Monthly Peer-Reviewed Journal

Driving Performance of Drivers and Psychomotor Characteristics at Extreme Weather Conditions Neelima Chakrabarty1; Kamini Gupta2 ;Ravindra Kumar3; Geetanjali Singh4 1 Sr. Principal Scientist, CRRI, Mathura Road, New Delhi, India [email protected] 2

STO, CRRI, Mathura Road, New Delhi, India [email protected] 3 Principal Scientist. CRRI, Mathura Road, New Delhi, India [email protected] 4 Research Intern, CRRI, Mathura Road, New Delhi, India [email protected] Abstract - Extreme weather conditions and temperature fluctuations are the major causes of an elevated risk of traffic accidents and compromised traffic flow in India. In India where hard winters and impaired road conditions are not unusual enough to stop daily routines, people are not free to make safe travel decisions, despite their safe intentions. The effect of o such conditions on driver behaviour has been a matter of concern for many years and the subject of past research.

Objective :The The objective of this research study was to analyze the visual traits and psychomotor behaviour of the drivers along with their choice of speed, reaction time and driving behaviour during adverse weather under simulated ted and realistic environment conditions. Methodology : Main focus of the present study was to understand how an individual driver responds to certain stimuli according to his/her individual characteristics during various driving conditions. The data acquisition of this study was done under two different settings settings a) laboratory setting and b) field setting to achieve overall data set of the driver’s response patterns at different weather conditions (clear, cloudy, rainy, foggy) in India. a)

In laboratory setting different psychophysical tests such as visual acuity test, glare test and night vision test were conducted under controlled lab conditions. Driving simulation tests were administered with driving simulator installed at CSIR-CRRI CSIR CRRI to analyze driver’s crash characteristics, risk taking practices and average reaction action time under adverse weather conditions. b) In field setting, during the various driving situations ,driver’s characteristic and other driving behaviours were measured which included driver’s reaction time, facial movements and some road related stimuli with the help of three cameras of V-box. V box. Different driving cycles were also recorded during the data acquisition. The Findings : The findings highlight drivers’ state and pattern of crashes during rain and foggy conditions during simulated adverse weatherr conditions. Different driving cycles were analyzed after the data processing. Recommendations : Based on these findings this has been recommended that frequency and severity of accident like situations and other related incidents can be reduced by providing providing drivers with enough information about the roadway and traffic conditions as well as through better traffic management during adverse weather conditions. However, due to paucity of time in this study sample size was small, this study may be further initiated tiated by increasing large sample size for doing sensitivity analysis. Researches on the area of developing advanced motorist warning systems which notify drivers about weather-related weather related conditions such as fog, flooding, or slippery pavement can be done for better understanding of driver’s responses during adverse weather conditions. This information is particularly helpful in light of the growing deployment of ITS technologies. Page 1

IRJSSE / Volume : 2 / Issue: 11 / Nov. 2014

ISSN: 2347-6176

1. INTRODUCTION Driving largely is a visual task; a poor visibility condition during adverse weather creates several additional demands on the driver and drastically reduces their ability to collect necessary visual information. The driving task also involves a number of activities e.g. guiding the vehicle within the road, detecting other vehicles, non motorized users, judging their speed, position, their possible behaviour and reacting accordingly. The review of related literature highlights that over the past couple of decades, international groups such as the Intergovernmental Panel on Climate Change (IPCC), and the Climate Change Science Program (CCSP) and Transportation Research Board (TRB) have done several studies that describe the details of climatic changes and their potential societal impacts, including those on the transportation sector. Adverse weather is one of the environmental factors that is known to affect the performance of moving vehicles, especially when the road friction is reduced, visibility is poor (Debus et al 2005; Kelker R.R. 2000). Studies Conducted in India Adverse weather such as heavy rain and fog poses significant challenge in safe driving in India. Due to low visibility and high traffic sometimes fog related road traffic accidents involve multiple vehicles resulting in vehicle pile ups. These accidents are in general fatal or severe due to the fact that multiple vehicles are involved which makes escaping very hard. A study conducted by Singh and Shrivastava (2013) tried to quantify the impact of rainfall, temperature, visibility and wind speed on traffic flow in India for two year period. Traffic and weather data were collected from Highway Traffic Management System installed at Jaipur Plaza in India on NH8 which connects Delhi to Mumbai. Research weather parameters were categorized on the basis of daily variation and they investigated their impact on traffic flow. The study highlight that during rain of more than 10 mm/hr with visibility less than 1 km and temperature (less than 10oc and more than 40oc) showed traffic volume reductions of 14%-18%, 5%-10% and 2%-5% respectively. Further weather adjustment factor was computed as the ratio of the traffic volume under existing weather condition relative to the base key parameter. Finally they developed models for weather adjustment factor for traffic flow corresponding to variation in rainfall, temperature and visibility. The findings indicated that the impact of rain is more significant than currently reported in the Highway Capacity Manual and therefore it indicated the need to carefully examine freeway operation strategies during adverse weather events. In addition to the loss of lives these accidents result in huge property damages. In India, fog remains a major problem in winter time. Among major cities, fog is a serious problem in Delhi and each year there are multiple vehicle accidents involving rear-end and head-on collisions two most common types of crashes occur in poor visibility. These accidents not only disrupt safety but also cause traffic closure and major congestion and often such crashes occur in high demand roadways with poor visibility. In many cases the visibility is so poor that the impact speed is very high resulting in serious and fatal injury crashes. However, the nature and characteristics of these crashes occurred in fog or other reduced visibility are still not fully explored. Conditions such as wet pavement, impaired visibility, heavy precipitation, frozen precipitation, flooding, high winds, and extremes of temperature can act in various ways to increase risks to drivers and their vehicles, as well as the infrastructure. The vulnerability of the national highway system, drivers to weather conditions and climate change arises from potential exposure to both unforeseen and anticipated changes in weather or climate patterns and from potential increases in the intensity and frequency of extreme weather events. A study done by Ashish Verma et al 2011 highlights that driver behaviour through better driver education, driver training and licensing procedures along with good on-road enforcement can be improved. A study conducted by Robin Burgess et al 2011 highlights that adverse weather conditions in India appear to lead to significantly deaths. Mortality increases steeply due to the rise of temperature 30◦-32◦C (∼ 86◦-90◦F) range at adverse weather. One single additional day with a mean temperature above 36◦C, relative to a mean temperature in the 22◦-24◦C range, increases the annual mortality rate by roughly 0.75 %. Delhi, capital of India is a monsoon-influenced humid subtropical with high variation between summer and winter temperatures. The monsoon starts in late June and lasts until mid-September and the post-monsoon season continues till late October, winter starts in November and peaks in January. Last year, according to the weather telecast, the cloudiest month was recorded August, with 90% of days were more cloudy than clear. This has been observed that during rainy season majority of the roads become choked with overflowing rainy water with loose potholes, wires, debris. The gamut of these researches helped to create the background of the present study under different Indian weather conditions and it was felt by CSIR-CRRI scientists to study the psychophysical and behavioural traits of drivers for all weather conditions in Delhi, India. However, no study has explored the effect of weather on different vehicle operating condition and its impact on speed in urban condition of Delhi city. 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IRJSSE / Volume : 2 / Issue: 11 / Nov. 2014

ISSN: 2347-6176

2. OBJECTIVES The main objectives of this research work were i) To study the visual traits and psychomotor behaviour of the drivers along with their choice of speed, reaction time and lane driving behaviour under simulated and realistic field conditions during adverse weather conditions in Delhi, India. ii) To analyze the effect of adverse weather conditions (in the form of different weather condition such as clear day, rainy, cloudy day, foggy day) on the operating speed and vehicle operating conditions. 3. METHODOLOGY Main focus of the present study was to understand how an individual driver responds to certain stimuli according to his/her individual characteristics during various adverse driving conditions. The data acquisition of this study was done under two different settings i.e. a) Laboratory Setting and b) Field Setting to achieve overall experience about the driver’s response pattern under adverse weather condition in India. a) Under laboratory setting different psychophysical tests were conducted under controlled settings the tests were visual acuity test, Glare tolerance test, night vision test. With the driving simulator driving simulation tests were conducted to analyze the crash characteristics and risk taking practices, average reaction time of the driver under adverse weather conditions. b) Under field setting driver’s characteristic were measured. In which driver’s reaction time, facial movements and road assets were measured with the help of three cameras of V-box during the various driving situations. Different driving cycles were also processed during the data acquisition. Sample Size and Characteristics: Twenty one commercial vehicle drivers pertaining to the age group between twenty to forty years with minimum two years to fifteen years driving experience of commercial vehicles were randomly selected for the present study. All the drivers were male and from same economic status. 4. LABORATORY STUDY During laboratory setting the test battery consisting of visual and other sensorimotor behavioural traits was conducted in Laboratory setting under controlled conditions. In the present study different computerized and semi computerized tools were selected to measure driving behaviour and crash characteristics at simulated adverse driving condition and realistic settings. Before conducting tests driver’s individual records or demographic characteristics (e.g. number of accident records , drug or alcohol addiction records , smoking addiction records, wearing spectacles or not , driving experience and mileage covered, type of vehicle ) were documented before conducting different psycho physical or skill tests . After providing comfort to the drivers, different vision related tests were conducted with the help of Porto Clinic and Porto Glare equipments (Pic 1&2).

Pic1&2: Porto Clinic & Glare Equipments Findings of Laboratory Study Visual Acuity Test (Both Eyes): The observance of the data analysis has shown that for the both eyes 27% drivers needed retesting and 11% performed poorly. Visual Acuity Test (Right Eye): For the right eye 29% needed retesting and 16% performed poorly. Visual Acuity Test (Left Eye): For the left eye 21% needed retesting and 12% have performed poorly. Glare Test: 28% drivers performed satisfactory, 5% below average & 3% poor for glare recovery time. Page 3

IRJSSE / Volume : 2 / Issue: 11 / Nov. 2014

ISSN: 2347-6176

Night Vision Test: In night vision 22% drivers performed satisfactory, 4% below average and 2% performed poorly.

5. SIMULATION TEST (TESTING WITH DRIVING SIMULATOR) The simulator was used to measure driving skills and crashing behaviour during clear, rainy and foggy weather conditions. Total three sessions for each drivers, 30 minutes for each session, were conducted for evaluating driver behaviour during clear, rainy and foggy weather simultaneously. The selected test battery was related to the highway driving and city driving conditions. Following driving related errors were measured under a fixed time period a) b) c) d)

Number of crashing Wrong side overtaking Lane discipline Signal obedience

Before conducting the tests the drivers were divided according to their driving experiences i.e. upto two year, two to five years and more than five years. The driver performances during the whole test period were continuously monitored and evaluated (pic. 3).

Picture3: Testing with Driving Simulator at CSIR-CRRI Findings of Simulation Study Following major types of risk taking practices and traffic rule violations were recorded under simulation study (Table-1). Table1: Percentage Errors Committed By the Commercial Drivers in Simulated Traffic Environment Driving Experience Percent Errors

committed

Crashing (Av. Frequency) Speeding (Km/hr.)

Improper Merging (Av. Freq.) Signal Violations (Av. Freq.)

Weather

Upto 2 Yrs.

2 to 5 Yrs.

5 Yrs. & ab.

Clear Weather Rainy Foggy Clear Weather Rainy

13.64 15.91 14.29 23.08 10

10.81 13.51 9.51 22.35 17.35

0 5.5 9.43 40 25

Foggy

7.59

17.99

12.5

Clear Weather Rainy Foggy Clear Weather Rainy Foggy

33.33 33.33 35.71 18.75 31.25 16.67

20 40 18.75 17.95 20.51 15.38

0 12.5 14.89 20 40 34.78

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IRJSSE / Volume : 2 / Issue: 11 / Nov. 2014

ISSN: 2347-6176

Overall crash frequency under simulated conditions: Overall crash frequency among drivers up to 2years driving experience was having 13.64% in clear, 15.91% in rainy and 14.29% in the foggy weather conditions. Observed driving pattern under simulated conditions: During foggy weather high experienced driver’s crash frequency was higher. Speeding behaviour under simulated conditions: Experienced drivers drove the simulated vehicle at higher speed. Improper merging in the roundabouts under simulated conditions: Highest of improper merging behaviour was noted among drivers experienced up to two years. The Speed Limit Violation and Violation of Road Signals: Highest of improper merging behaviour was noted among experienced drivers. 6. FIELD STUDY For the present study twenty two kilometres road stretch from Central Road Research Institute (CRRI) to Institute of Driving & Training Research (IDTR) under Maruti Suzuki situated at Loni Road near Yojana Vihar, Delhi was selected. This stretch was selected in the view point of its single to multilane structure and its manifold variations of road infrastructures (e.g. different road width, median width, and accessibility facilities) (picture – 4). The road width and the median width were measured with the measuring wheel.

Pic.4: Represents the Study Area Map Effect of Adverse Weather Conditions on Vehicle Speed Data collected at different weather conditions on same road section to study the effect of weather condition on speed of the vehicle. After analyzing the average speed on flyover Standard deviation, mean of speed & mean square values for Speed at flyover were calculated which are for ascending 0.808 kmph, 50.467 kmph & 0.980 kmph and for descending 1.097 kmph, 54.033 kmph & 1.805 kmph. Result shows that average speed values on 2 lanes, 3 lanes and 4 lanes were 34.1kmph, 47.7kmph and 63.25 km/hr respectively. 2 lane road shows significant variation in speed due to changes in weather with standard deviation of 2.5 kmph whereas as for 3 lanes and 4 lane roads showed no significant variation in speed due to changes in weather condition. Average speed on plains at different lanes is 48.35kmph with standard deviation of 4.987. Overall, the average speed was observed increasing with the increase in number of lanes (table-2). ANOVA analysis confirmed the level of significance .05 levels (table-3). Table2- Average Speed (Km/hr): CRRI to IDTR (Up) and CRRI (Down) Weather Condition Clear Rainy Cloudy Foggy

2 Lane Up 32.58 33.73 36.15 25.1

Down 38.5 36.12 42.825 31.9

Up 42.09 50.83 50.19 38.7

3 Lane Down 57.34 53.75 52.75 26.4

Up 70 56.73 63.02 30.5

4 Lane Down 57.705 65.86 63.7 31.5

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IRJSSE / Volume : 2 / Issue: 11 / Nov. 2014

ISSN: 2347-6176

Table3- Analysis Of Variance of Average Speed (Km/hr): Up: From CRRI to IDTR and Back Source of Variation df Among mean 5 Within Conditions 12 Total 17 *F (5, 12) =2.16, p