Survival analysis: Pedestrian risk exposure at signalized intersections |
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| Institution: | 1. Smart Cities Transport Group, Department of Infrastructure Engineering, Melbourne School of Engineering, The University of Melbourne, Victoria 3010, Australia;2. Department of Civil and Environmental Engineering, Kharazmi University, P.O. Box 15614, Tehran, Iran;1. National Technical University of Athens, Department of Transportation Planning and Engineering, Greece;2. IFSTTAR – Institut français des sciences et technologies des transports, de l’aménagement et des réseaux, France;1. Center for Studies of Hong Kong, Macao and Pearl River Delta, Collaborative Innovation Center for the Cooperation and Development of Hong Kong, Macao and Mainland China, Sun Yat-Sen University, Xingang Xi Road, Guangzhou, China;2. Department of Civil Engineering, National Chi Nan University, No. 1, University Rd, Puli, Nantou County 54561, Taiwan;1. The Academy of Criminalistic and Police Studies, Cara Dusana 196, Zemun, Serbia;2. Faculty of Transport and Traffic Engineering, Vojvode Stepe 305, Belgrade, Serbia;3. Faculty of Transport and Traffic Engineering, Vojvode Misica 52, Doboj, Bosnia and Herzegovina;1. University of Alaska Anchorage, 2900 Spirit Drive, Anchorage, AK 99508, United States;2. Department of Civil Engineering, Institute of Technology Kanpur, Kanpur 208016, India;3. Department of Civil Engineering, Indian Institute of Technology Kanpur, Kanpur 208016, India;1. Istanbul Technical University, Faculty of Civil Engineering, Department of Civil Engineering, Maslak, Istanbul, Turkey;2. Işık University, Faculty of Engineering, Department of Civil Engineering, Şile, Istanbul, Turkey |
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| Abstract: | Pedestrian behaviour was observed at seven selected intersections in Delhi, India. Data collection occurred at these intersections by placing a video camera at each zebra crossing. Pedestrian crossing behaviour was then obtained from careful review of the videotapes. Pedestrian crossing behaviour was analyzed using survival analysis statistical methodology. The analyses produce Kaplan–Meier survival curves for waiting time prior to crossing unsafely, separately for males and females, and for each intersection. Mean observed waiting time and model-based waiting time of 90% of pedestrians were then studied. Mean waiting time of females are 27% more than for males, while the waiting time of 90% of female pedestrians are 44% more than the corresponding number for males. The probability for a pedestrian to cross the road, when it is unsafe, i.e. motor vehicles still have green or yellow, varies with waiting time. People do not want to wait too long to cross streets. As signal waiting time increases, pedestrians get impatient and violate the traffic signal. This violation places them at increased risk of being struck by a motor vehicle. Thus, reducing the waiting time for pedestrians are likely to decrease the probability of pedestrian crossers being hit by a motor vehicle. |
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