An analysis of influential factors associated with rural crashes in a developing country: A case study of Iran


  • Abbas Sheykhfard Department of Civil Engineering, Babol Noshirvani University of Technology, Babol Author
  • Farshidreza Haghighi Department of Civil Engineering, Babol Noshirvani University of Technology, Babol Author
  • Reza Abbasalipoor Department of Civil Engineering, Babol Noshirvani University of Technology, Babol Author



rural roads, severity of crashes, crashes, injury-fatal crashes, logit model, crash data collected


Road traffic deaths continue to rise, reaching 1.35 million in recent years. Road traffic injuries are the eighth leading cause of death for people of all ages. Note that there is a wide difference in the crash rate between developed and developing countries and that developed countries report much lower crash rates than developing and underdeveloped countries. World Health Organization reports that over 80% of fatal road crashes occur in developing countries, while developed countries account for about 7% of the total. The rate of road crashes in developing countries is higher than the global average, despite some measures reducing deaths over the last decade. Numerous studies have been carried out on the safety of urban roads. However, comprehensive research evaluating influential factors associated with rural crashes in developing countries is still neglected. Therefore, it is crucial to understand how factors influence the severity of rural road crashes. In the present study, rural roads in Mazandaran province were considered a case study. The Crash data collected from the Iranian Legal Medicine Organization covers 2018 to 2021, including 2047 rural crashes. Dependent variables were classified as damage crashes and injury-fatal crashes. Besides, independent variables such as driver specifications, crash specifications, environment specifications, traffic specifications, and geometrical road specifications were considered parameters. The logit model data indicate that factors associated with driver and crash specifications influence rural crashes. The type of crashes is the most critical factor influencing the severity of crashes, on which the fatal rate depends. The findings suggested that implementing solutions that minimize the effect of the factors associated with injury and death on rural roads can reduce the severity of crashes on rural roads that share the same safety issues as the case study. Further studies can also be conducted on the safety and mechanics of the vehicle by focusing the research on the types of vehicles and the sources of the damage.


Abounoas, Z., Raphael, W., Badr, Y., Faddoul, R., Guillaume, A. (2020). Crash data reporting systems in fourteen Arab countries: Challenges and improvement. Archives of Transport, 56(4), 73-88. DOI: 10.5604/01. 3001.0014.5628.

Al-Bdairi, N. S. S., Behnood, A. (2021). Assessment of temporal stability in risk factors of crashes at horizontal curves on rural two-lane undivided highways. Journal of Safety Research, 76, 205-217. DOI: 10.1016/j.jsr.2020 .12.003.

Alhomaidat, F., Abushattal, M., Morgan Kwayu, K., Kwigizile, V. (2022). Investigating the interaction between age and liability for crashes at stop-sign-controlled intersections. Transportation Research Interdisciplinary Perspectives, 14, 100612. DOI: 10.1016/j.trip. 2022.100612.

Agbelie, B. R. D. K. (2016). Random-parameters analysis of highway characteristics on crash frequency and injury severity. Journal of Traffic and Transportation Engineering (English Edition), 3(3), 236-242. DOI: 10.1016/j.jtte.2015.09.006.

Ambros, J., Elgner, J., Turek, R., Valentova, V. (2020). Where and when do drivers speed? A feasibility study of using probe vehicle data for speeding analysis. Archives of Transport, Vol. 53, iss. 1. DOI: 10.5604/01.3001.0014. 1747.

Ayazi, E., Khorsand, R., Sheikholeslami, A. (2020). Investigating the effectiveness of geometric and human factors on the severity of urban crashes. IOP Conference Series: Materials Science and Engineering, 3rd International Conference on Engineering Sciences . 671, pp. 1-8. Kerbala, Iraq: IOP. DOI: 10.1088/1757-899X/671/1/012102.

Bandyopadhyaya, R., Mitra, S. (2013). Modelling Severity Level in Multivehicle Crashes on Indian Highways. Procedia - Social and Behavioral Sciences, 104, 1011-1019. DOI: 10.1016/j.sbspro.2013.11.196.

Chen, C., Zhang, G., Huang, H., Wang, J. A., Tarefder, R. (2016, November). Examining driver injury severity outcomes in rural non-interstate roadway crashes using a hierarchical ordered logit model. Crash Analysis and Prevention, 96, 79-87. DOI: 10.1016/j.aap.2016.06.015.

Dingus, T. A., Guo, F., Lee, S., Antin, J. F., Pe-rez, M., Buchanan-King, M., Hankey, J. (2016). Driver crash risk factors and prevalence evaluation using naturalistic driving data. Proceedings of the National Academy of Sciences, 113(10), 2636-2641. DOI: 10.1073/pnas. 1513271113.

Ditcharoen, A., Chhour, B., Traikunwaranon, T., Aphivongpanya, N., Maneerat, K., Ammarapala, V. (2018, 2018 5th International Conference on Business and Industrial Re-search (ICBIR)). Road traffic crashes severity factors: A review paper. 5th International Conference on Business and Industrial Research (ICBIR) (pp. 339-343). Bangkok, Thailand: IEEE. DOI: 10.1109/ICBIR.2018.8391218.

Echaveguren, T., Díaz, Á., Vargas-Tejeda, S. (2015). Operating speed models for horizontal reverse curves. Proceedings of the Institution of Civil Engineers - Transport, 168(6), 510-522. DOI: 10.1680/jtran.13.00016.

Elvik, R. (2013). International transferability of crash modification functions for horizontal curves. Crash Analysis and Prevention, 59, 487-496. DOI: 10.1016/j.aap.2013.07.010.

Ersan, Ö., Üzümcüoğlu, Y., Azık, D., Fındık, G., Kaçan, B., Solmazer, G., Özkan, T., Lajunen, T., Öz, B., Pashkevich, A., Pashkevich, M., Danelli-Mylona, V., Georgogianni, D., Krasniqi, E. B., Krasniqi, M., Makris, E., Shubenkova, K., Xheladini, G. (2019). The relationship between self and other in aggressive driving and driver behaviors across countries. Transportation Research Part F: Traffic Psychology and Behaviour, 66, 122-138. DOI: 10.1016/j.trf.2019.08.020.

Ghasemlou, K., Aydi, M. M., Yildirim, M. S. (2015). Prediction of pedal cyclists and pedestrian fatalities from total monthly crashes and registered private car numbers. Archives of Transport, 34(2). DOI: 10.5604/08669546. 1169209.

Haleem, K., Gan, A. (2013). Effect of driver’s age and side of impact on crash severity along urban freeways: A mixed logit approach. Journal of Safety Research, 46, 67-76. DOI: 10.1016/j.jsr.2013.04.002.

He, L., Lin, X. (2018). An improved mathematical model for vehicle crashagainst highway guardrails. Archives of Transport, Vol. 48, iss. 4. DOI: 10.5604/01.3001.0012.8364.

Iranian Legal Medicine Organization. (2018). Iranian Legal Medicine Organization.

Jahandideh, Z., Mirbaha, B., Rassafi, A. A. (2017). Identifying factors affecting pedestrians’ crossing decisions at intersections in Iran. Proceedings of the Institution of Civil Engineers - Municipal Engineer, 172(1), 26-36. DOI: 10.1680/jmuen.17.00005.

K.W.Yau, K. (2004, May). Risk factors affect-ing the severity of single vehicle traffic crashes in Hong Kong. Crash Analysis and Prevention, 36(3), 333-340. DOI: 10.1016/S0001-4575(03)00012-5.

Kaiser, S., Furian, G., Schlembach, C. (2016). Aggressive Behaviour in Road Traffic – Findings from Austria. Transportation Research Procedia, 14, 4384-4392. DOI: 10.1016/j.trpro.2016.05.360.

Lee, C., Li, X. (2014). Analysis of injury severity of drivers involved in single- and two-vehicle crashes on highways in Ontario. Crash Analysis and Prevention, 71, 286-295. DOI: 10.1016/j.aap.2014.06.008.

Leonardi, S., Distefano, N., Pulvirenti, G. (2020). Identification of road safety measures for elderly pedestrians based on K-means clustering and hierarchical cluster analysis. Archives of Transport, 56(4), 107-118. DOI: 10.5604/01.3001.0014.5630.

Ma, M., Yan, X., Huang, H., Abdel-Aty, M. (2010). Safety of public transportation occupational drivers risk perception, attitudes, and driving behavior. World Transit Research.

Manner, H., Wünsch-Ziegler, L. (2013). Ana-lyzing the severity of crashes on the German Autobahn. Crash Analysis and Prevention, 57, 40-48. DOI: 10.1016/j.aap.2013.03.022.

Marzoug, R., Lakouari, N., Ez-Zahraouy, H., Castillo Téllez, B., Castillo Téllez, M., Cisneros Villalobos, L. (2022). Modeling and simulation of car crashes at a signalized intersection using cellular automata. Physica A: Statistical Mechanics and Its Applications, 589, 126599. DOI: 10.1016/j.physa.2021.126599.

Mekonnen, T. H., Abere, G., Olkeba, S. W. (2019). Risk Factors Associated with Upper Extremity Musculoskeletal Disorders among Barbers in Gondar Town, Northwest Ethiopia, 2018: A Cross-Sectional Study. Pain Research and Management, 2019, e6984719. DOI: 10.1155/2019/6984719.

Michalaki, P., A.Quddus, M., Pitfield, D., Huetson, A. (2015, December). Exploring the factors affecting motorway crash severity in England using the generalised ordered logistic regression model. Journal of Safety Research, 55, 89-97. DOI: 10.1016/j.jsr.2015.09.004.

Mohamed, M., Bromfield, N. F. (2017). Attitudes, driving behavior, and crash involvement among young male drivers in Saudi Arabia. Transportation Research Part F: Traffic Psychology and Behaviour, 47, 59-71. DOI: 10.1016/j.trf.2017.04.009.

Nguyen, D. V. M., Vu, A. T., Polders, E., Ross, V., Brijs, T., Wets, G., Brijs, K. (2021). Modeling the injury severity of small-displacement motorcycle crashes in Hanoi City, Vietnam. Safety Science, 142, 105371. DOI: 10.1016/j.ssci.2021.105371.

NHTSA. (n.d.). Motor Vehicle Traffic Crashes As a Leading Cause of Death in the United States.

OECD iLibrary | Road Safety Annual Report 2017. (n.d.). Retrieved December 22, 2019, from road-safety-annual-report-2017_irtad-2017-en.

Oikawa, S., Matsui, Y. (2017). Features of se-rious pedestrian injuries in vehicle-to-pedes-trian crashes in Japan. International Journal of Crashworthiness, 22(2), 202–213. DOI: 10.1080/13588265.2016.1244230.

Pahukula, J., Hernandez, S., Unnikrishnan, A. (2015). A time of day analysis of crashes involving large trucks in urban areas. Crash Analysis and Prevention, 75, 155-163. DOI: 10.1016/j.aap.2014.11.021.

Phan, V. L., Evdorides, H., Bradford, J., Mumford, J. (2016). Motorcycle crash risk models for urban roads. Proceedings of the Institution of Civil Engineers - Transport, 169(6), 397-407. DOI: 10.1680/jtran.15.00075.

Ratanavaraha, V., Suangka, S. (2014, March). Impacts of crash severity factors and loss values of crashes on expressways in Thailand. IATSS Research, 37(2), 130-136. DOI: 10.1016/j.iatssr.2013.07.001.

Rolison, J. J., Regev, S., Moutari, S., Feeney, A. (2018). What are the factors that contribute to road crashes? An assessment of law enforcement views, ordinary drivers’ opinions, and road crash records. Crash Analysis and Prevention, 115, 11-24. DOI: 10.1016/j.aap.2018.02.025.

Sheykhfard, A., Haghighi, F. (2018). Behavioral analysis of vehicle-pedestrian interactions in Iran. Scientia Iranica, 25(4), 1968-1976. DOI: 10.24200/sci.2017.4201.

Sheykhfard, A., Haghighi, F. (2019). Performance analysis of urban drivers encountering pedestrian. Transportation Research Part F: Traffic Psychology and Behaviour, 62, 160-174. DOI: 10.1016/j.trf.2018.12.019.

Sheykhfard, A., Haghighi, F. (2020). Assessment pedestrian crossing safety using vehicle-pedestrian interaction data through two different approaches: Fixed videography (FV) vs In-Motion Videography (IMV). Crash Analysis and Prevention, 144, 105661. DOI: 10.1016/j.aap. 2020.105661.

Sheykhfard, A., Haghighi, F., Nordfjærn, T., Soltaninejad, M. (2021). Structural equation modelling of potential risk factors for pedestrian crashes in rural and urban roads. International Journal of Injury Control and Safety Promotion, 28(1), 46-57. DOI: 10.1080/1745 7300.2020.1835991.

Sheykhfard, A., Haghighi, F. R., Soltaninejad, M., Karji, A. (2020). Analyzing Drivers’ Mental Patterns Using Q-Methodology. Journal of Transportation Technologies, 10(02), 169. DOI: 10.4236/jtts.2020.102011.

Shrestha, P., Shrestha, K. (2017, February). Factors associated with crash severities in built-up areas along rural highways of Nevada: A case study of 11 towns. Journal of Traffic and Transportation Engineering (English Edition), 4(1), 96-102. DOI: 10.1016/j.jtte.2016.08.003.

Spyropoulou, I., Sermpis, D. (2009). Performance of junctions with a high motorcycle proportion. Proceedings of the Institution of Civil Engineers - Transport, 162(2), 63-69. DOI: 10.1680/tran.2009.162.2.63.

Sun, J., Zhou, S., Li, K., Ni, Y. (2012). Evaluation of safety factors at Chinese intersections. Proceedings of the Institution of Civil Engineers - Transport, 165(3), 195-204. DOI: 10.1680/tran.10.00021.

Thakur, S., Biswas, S. (2019). Assessment of Pedestrian-Vehicle Interaction on Urban Roads: A Critical Review. Archives of Transport, 51(3). baztech/element/bwmeta1.element.baztech-dff368a3-229a-4797-b322-ea03f68ec7c3.

Theofilatos, A., Yannis, G., Vlahogianni, E. I., Golias, J. C. (2017). Modeling the effect of traffic regimes on safety of urban arterials: The case study of Athens. Journal of Traffic and Transportation Engineering (English Edition), 4(3), 240-251. DOI: 10.1016/j.jtte.2017.05.003.

Thomas, M., Williams, T., Jones, J. (2020). The epidemiology of pedestrian fatalities and substance use in Georgia, United States, 2007-2016. Crash Analysis and Prevention, 134, 105329. DOI: 10.1016/j.aap.2019.105329.

Wali, B., Ahmad, N., Khattak, A. J. (2022). To-ward better measurement of traffic injuries – Comparison of anatomical injury measures in predicting the clinical outcomes in motorcycle crashes. Journal of Safety Research, 80, 175-189. DOI: 10.1016/j.jsr.2021.11.013.

Wang, L., Li, R., Wang, C., Liu, Z. (2021). Driver injury severity analysis of crashes in a western China’s rural mountainous county: Taking crash compatibility difference into consideration. Journal of Traffic and Transportation Engineering (English Edition), 8(5), 703-714. DOI: 10.1016/j.jtte.2020.12.002.

Wang, X., Cheng, Y. (2019). Lane departure avoidance by man-machine cooperative control based on EPS and ESP systems. Journal of Mechanical Science and Technology, 33(6), 2929-2940. DOI: 10.1007/s12206-019-0540-6.

WHO | Global status report on road safety 2018. (n.d.-a). WHO. Retrieved December 19, 2019, from

WHO | Global status report on road safety 2018. (n.d.-b). Retrieved December 22, 2019.

Wu, Q., Chen, F., Zhang, G., Liu, X. C., Wang, H., Bogus, S. M. (2014). Mixed logit model-based driver injury severity investigations in single- and multi-vehicle crashes on rural two-lane highways. Crash Analysis and Prevention, 72, 105-115. DOI: 10.1016/j.aap.2014.06.014.

Wu, Q., Zhang, G., Zhu, X., Cathy Liu, X., Tarefder, R. (2016, September). Analysis of driver injury severity in single-vehicle crashes on rural and urban roadways. Crash Analysis and Prevention, 94, 35-45. DOI: 10.1016/j.aap. 2016.03.026.

Zhao, Y., Yamamoto, T., Kanamori, R. (2020). Study of older male drivers’ driving stress compared with that of young male drivers. Journal of Traffic and Transportation Engineering (English Edition), 7(4), 467-481. DOI: 10.1016/j.jtte.2018.10.011.

Zhang, G., K.W.Yau, K., Chen, G. (2013, October). Risk factors associated with traffic violations and crash severity in China. Crash Analysis and Prevention, 59, 18-25. DOI: 10.1016/j.aap.2013.05.004.

Zhou, M., Chor Chin, H. (2019, March). Factors affecting the injury severity of out-of-control single-vehicle crashes in Singapore. Crash Analysis and Prevention, 124, 104-112. DOI: 10.1016/j.aap.2019.01.009.






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How to Cite

Sheykhfard, A., Haghighi, F., & Abbasalipoor, R. (2022). An analysis of influential factors associated with rural crashes in a developing country: A case study of Iran. Archives of Transport, 63(3), 53-65.


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