A Model for Predicting Schoolchildren Accidents in the Vicinity of Rural Roads based on Geometric Design and Traffic Conditions


1 Ph.D student, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran

2 Professor, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran

3 MSc graduate, Department of Civil and Environmental Engineering, Tarbiat Modares University, Tehran, Iran


awareness they gain from their surroundings. Recent statistics indicate that about 40 percent of road accident fatalities are pedestrians, 30 percent of which are under 18 years old. Based on the fact that almost two million Iranian students study in the vicinity of rural roads, this paper aims to develop a model for predicting the risk of students’ accidents near the aforementioned schools. Therefore, by gathering data from schools located in rural areas, schools are divided in three categories which are: no risk (no accidents/year), medium risk (one accident/year), and high risk (two or more accidents/year). A multinomial logit (MNL) model has been chosen and the utility function was considered as a combination of variables such as road width, functional speed, presence of school guardian, number of students and the ratio of average daily traffic to the distance of schools from roads. Results indicate that the proposed model can predict the risk of accident occurrence with the accuracy of more than 70 percent. Meanwhile, school guardian is known as an important variable in the prediction model. Also, results show the important role of the road width and proposed ADT/Dis variables.


- Ben-Akiva, M. and Lerman, S.R. (1993) “Discrete Choice Analysis; Theory and Application to Travel Demand”. 5th printing, the MIT Press
- Christie, N. (1995) “The high-risk child pedestrian: socio-economic and environmental factors in their accidents”, TRL Research Report PR117
- Duperrex, O., Roberts, I. and Bunn, F. )2002( Safety Education of Pedestrians for Injury Prevention. Cochrane, Rev 2.
- Geedipally, S. and Turner, A. (2011) “An analysis of motorcycle crashes in Texas using a multinomial logit model”. The 90th Annual Meeting of the Transportation Research Board, USA
- Graham, D., Glaister, S. and Anderson, R. (2002) “Child pedestrian casualties in england: the effect of area deprivation”, Centre for Transport Studies, London
- Iranian Legal Medicine organization (2007) “Descriptive Analysis of Traffic Accident Victims”, Tehran, Iran
- Joly, M.F., Foggin, P.M. and Pless, I.B. (1991) “Geographical and socio-ecological variations of traffic accidents among children”, Journal of Social Science and Medicine, Vol. 33
- Jones S.J., Lyons R.A., John A. and Palmer S.R. (2005) “Traffic calming policy can reduce inequalities in child pedestrian injuries.” Database Study Injury Prevention
- KanafanI, A. (1983) “Transportation demand analysis”, McGraw-Hill book company, New York, USA
- McDonald, N.C. (2008) ”Children’s mode choice for the school trip: the role of distance and school location in walking to school”, Journal of Transportation: Planning, Policy, Research, Practice, Volume 35, No. 1, Springer Science and Business Media Publishing
- Meyer, M.D. and Miller, E.J. (2001) “Urban transportation planning, a decision-oriented approach”, 2nd ed. McGraw-Hill book company, New York, USA 
- Navidi, W. (2010) “Principles of statistics for engineers and scientists”, 1st ed. McGraw-Hill book company, New York, USA
- NHTSA )2003) “Traffic safety facts, pedestrians”, Department of Transportation National Highway Traffic Safety Administration (DOT HS) 809 769, Washington DC, USA
- Ortuzar, J. D. and Willumsen, L.G. (2011) “Modelling transport”. 4th ed. John Wiley and sons, New York, USA
- Parisi Associates Transporting Consulting (2003) “Transportation tools to improve children's health and mobility
- Recorded Accidents in Iran (2006-2008), Islamic Republic of Iran Traffic Police
- Savolainen, P. and Mannering, F. (2007) “Probabilistic models of motorcyclists’ injury severities in single and multi-vehicle crashes”, Journal of Accident Analysis and Prevention, Vol. 39, pp.955–963
- Savolainen, P., Mannering, F., Lord, D., Quddus, M. (2011) “The statistical analysis of highway crash-injury severities: A review and assessment of methodological alternatives”, Journal of Accident Analysis and Prevention, Vol. 43, pp. 1666-1676
- Scottish Executive Social Research (2003( “Children Attitudes to Sustainable Transport. Derek Halden Consultancy”, Scotland. 
- Trimothy, J., Tapan, K. and Savolainen, P. (2009) “Evaluation of a pedestrian safety educational program for elementary and middle school children”, Department of Civil and Environmental Engineering, Wayne State University, Transportation Research Board
- Wang C., Quddus A. and Ison G. (2011) “Predicting accident frequency at their severity levels and its application in site ranking using a two-stage mixed multivariate model”. The 90th Annual Meeting of the Transportation Research Board, USA
- Washington, S., KArlaftis, M. and Mannering, F. (2011) “Statistical and econometric methods for transportation data analysis”. 2nd ed. Chapman and Hall/ CRC, Boca Raton, FL, USA
- Wedagama, D.M.P. (2006) “The relationship between urban land use and non-motorised transport accidents and casualties”, PhD Thesis, Newcastle University, UK
- Wedagama, D.M.P., Bird, R.N. and Metcalfe, A.V. (2006) “The influence of urban land-use on non-motorised transport Casualties”, Journal of Accident Analysis and Prevention, Vol. 38
- World Health Organization (WHO) (2003) “World Report on Road Traffic Injury Prevention”.
- Yamamoto, T., Shankar, V. (2004) “Bivariate ordered response probit model of driver’s and passenger’s injury severities in collisions with fixed object”, Journal of Accident Analysis and Prevention, Vol. 36 (5), pp.869–876