Evaluating the Factors Affecting Severity of Pedestrian Accidents in Urban Streets and Providing a Model for Predicting These Accidents (Case Study: Qazvin City)
Document Type : Original Article
Authors
1 Assistant Professor, Department of Civil Engineering, Savadkooh Branch, Islamic Azad University, Savadkooh, Iran.
2 Ph.D. Student, Department of Civil Engineering, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran.
Abstract
Recently, with the increase in the production of vehicles on the one hand and the increase in the population of cities and villages on the other hand, sufficient attention to the issue of pedestrians, especially in terms of safety, is very important and noteworthy. In recent years, the rate and growth of pedestrian casualties in major cities of the country compared to developing countries is high. The purpose of this study was to investigate the effect of pedestrian characteristics and behavior, environmental characteristics and time of pedestrian accidents on the probability of pedestrian injuries and to provide a model to determine the probability of any severe or minor injuries. The independent variables defined in the model are for vehicle accidents with pedestrians on Jomhuri Eslami Boulevard in Qazvin. Therefore, using the data obtained from the provincial forensic medicine organization and the traffic police, which are related to traffic accidents from 1397 to 1399, these factors have been modeled using the logistic regression model. The results show that pedestrian education, time of accident, speed of vehicle and color of pedestrian clothing are the most influential factors in the probability of injury.
Keywords
-Abdel-Aty, M.A. and Radwan. E.A., (2000), “Modelling traffic accident occurrence and involvement”, Accident Analysis and Prevention, Vol.32, No.5, pp.633-642.
-Afshari, A., Ayati, E. and Barakchi, M., (2021), “Evaluating the effects of external factors on pedestrian violations at signalized intersections (a case study of Mashhad, Iran)”, IATSS research, Vol.45, No.2, pp.234-240.
-Aziz, H.M.A., Ukkusuri, S.V. and Hasan, S., (2013), “Exploring the determinants of pedestrian–vehicle crash severity in New York City”, Accident Analysis and Prevention, 50, pp.1298-1309.
-Clifton, K.J., Burnier, C.V. and Akar, G., (2009), “Severity of injury resulting from pedestrian–vehicle crashes: What can we learn from examining the built environment?”, Transportation Research Part D: Transport and Environment, Vol.14, No.6, pp.425-436.
-Dai, D., (2012), “Identifying clusters and risk factors of injuries in pedestrian–vehicle crashes in a GIS environment”, Journal of Transport Geography, 24, pp.206-214.
-Delen, D., Sharda, R. and Bessonov, M., (2006), “Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks”, Accident Analysis and Prevention, Vol.38, No.3, pp. 434- 444.
-Diependaele, K., (2019), “Non-compliance with pedestrian traffic lights in Belgian cities”, Transp. Res. P. F: Traffic Psychol. Behav., 67, pp.230-241.
-Dissanayake, S. and Lu, J., (2002), “Analysis of severity of young driver crashes: sequential binary logistic regression modeling”, Tranportation research record, Vol.1784, No.1, pp.108-114.
-Eluru, N., Bhat, C. R. and Hensher, D. A., (2008), “A mixed generalized ordered response model for examining pedestrian and bicyclist injury severity level in traffic crashes”, Accident Analysis and Prevention, Vol.40, No.3, pp. 1033-1054.
-Gray, R.C. and Quddus, M.A., (2008), “Injury severity analysis of accidents involving young male drivers in Great Britain”, Journal of Safety Research, Vol.39, No.5, pp.483- 495.
-Guo, Y., Liu, P., Liang, Q. and Wang, W., (2016), “Effects of parallelogram-shaped pavement markings on vehicle speed and safety of pedestrian crosswalks on urban roads in China”, Accident Analysis & Prevention, Vol.95, Part B, pp.438-447.
-Hauer, E., Council, F.M. and Mohammedshah, Y., (2004), “Safety models for urban four-lane undivided road segments”, Transportation research record, Vol.1897, No.1, pp.96-105.
-Kim, J.K., Ulfarsson, G.F., Shankar, V.N. and Kim, S., (2008), “Age and pedestrian injury severity in motor-vehicle crashes: A heteroskedastic logit analysis”, Accident Analysis & Prevention, Vol.40, No.5, pp.1695-1702.
-Kniuman, M.W., Council, F.M. and Reinfurt, D.W., (1993), “Association of median width and highway accident rate”, Transportation Research Record, 1401, pp.70-82.
-Lange, F., Haiduk, M., Boos, M., Tinschert, P., Schwarze, A. and Eggert, F., (2016), “Road crossing behavior under traffic light conflict: Modulating effects of green light duration and signal congruency”, Accident Analysis & Prevention, Vol.95, pp.292-298.
-Montana, G., (2005), “Simulation tool for generating haplotype data with pre-specified allele frequencies and LD coefficients”, Bioinformatics, Vol.21, No.23, pp.4309–4311.
-Moudon, A.V., Lin, L., Jiao, J., Hurvitz, P. and Reeves, P., (2011), “The risk of pedestrian injury and fatality in collisions with motor vehicles, a social ecological study of state routes and city streets in King County, Washington”, Accident Analysis & Prevention, Vol.43, No.1, pp.11-24.
-Onelcin, P. and Alver, Y., (2017), “Why cross on red? A questionnaire survey study in Izmir, Turkey”, Transportation research procedia, Vol.25, pp.1964-1971.
-Otte, D., Jänsch, M. and Haasper, C., (2012), “Injury protection and accident causation parameters for vulnerable road users based on German In-Depth Accident Study GIDAS”, Accident Analysis & Prevention, Vol.44, No.1, pp.149-153.
-Niebuhr, T., Junge, M. and Rosen, E., (2016), “Pedestrian injury risk and the effect of age”, Accident Analysis & Prevention, Vol.86, No.1, pp.121-128.
-Rankavat, S. and Tiwari, G., (2016), “Pedestrians risk perception of traffic crash and built environment features–Delhi, India”, Safety science, Vol.87, pp.1-7.
-Retting, R., (2017), “Pedestrian traffic fatalities by state”, Governors Highway Safety Association: Washington, DC, USA.
-Rifaat, S.M. Tay, R. and De Barros, A., (2011), “Effect of street pattern on the severity of crashes involving vulnerable road users”, Accident Analysis & Prevention, Vol.43, No.1, pp.276-283.
-Rosenbloom, T. Sapir-Lavid, Y. and Perlman, A., (2016), “Risk factors in road crossing among elderly pedestrians and readiness to adopt safe behavior in socio-economic comparison”, Accident Analysis & Prevention, Vol.93, No.1, pp.23-31.
-Sze, N.N. and Wong, S.C., (2007), “Diagnostic analysis of the logistic model for pedestrian injury severity in traffic crashes”, Accident Analysis & Prevention, Vol.39, No.6, pp.1267-1278.
-Whittemore, A.S. and Halpern, J., (2003), “Logistic regression of family data from retrospective study designs”, Genetic Epidemiology: The Official Publication of the International Genetic Epidemiology Society 25, No.3, pp.177-189.
-Yang, Y. and Sun, J., (2013), “Study on pedestrian red-time crossing behavior: integrated field observation and questionnaire data”, Transportation research record, Vol.2393, No.1, pp.117-124.
-Zhang, G., Yau, K.K. and Zhang, X., (2014), “Analyzing fault and severity in pedestrian–motor vehicle accidents in China”, Accident Analysis & Prevention, Vol.73, pp.141-150.
-Zhang, G., Tan, Y. and Jou, R.C., (2016), “Factors influencing traffic signal violations by car drivers, cyclists, and pedestrians: A case study from Guangdong, China”, Transportation research part F: traffic psychology and behaviour, Vol.42, pp.205-216.
-Zhang, W., Wang, K., Wang, L., Feng, Z. and Du, Y., (2016), “Exploring factors affecting pedestrians’ red-light running behaviors at intersections in China”, Accident Analysis & Prevention, Vol.96, pp.71-78.
-Zhou, H., Romero, S.B. and Qin, X., (2016), “An extension of the theory of planned behavior to predict pedestrians’ violating crossing behavior using structural equation modeling”, Accident Analysis & Prevention, Vol.95, pp.417-424.
-Zhuang, X., Wu, C. and Ma, S., (2018), “Cross or wait? Pedestrian decision making during clearance phase at signalized intersections”, Accident Analysis & Prevention, Vol.111, pp.115-124.