Abstract
Safety and accident issues are considered as important problems in the world. Road accident issues would have a more conspicuous countenance in Malaysia. Since 4% of fatal accidents increase annually, prevention of this accidents issues needs to be controlled. This study focused only on the Seremban area to identify the characteristics of road fatalities and to investigate the probable factors that contribute to the fatal accident. It was conducted on 381 road users where 224 were fatally injured in road accidents in Seremban during 2015. The risk of involvement in fatal rather than nonfatal accidents for gender was higher among males than among females. The middle age group (31–40 years old) is the most vulnerable to fatal accidents. In accidents that occurred during the night, the risk of death was higher than during the day. The risk of death for vehicle types was higher in other vehicles (bus, pedestrians, bulldozer and other uncategorized vehicles) compared to motorcycle, car and lorry/truck. Major accident causes in road user fatalities were over speed. The risk for fatal injury in a road traffic accident was estimated using logistic regression adjusting for gender, age, time of day of accident, vehicle types and accident cases. Among the variables obtained, two independent variables were found significantly associated with fatal accidents; namely vehicle types (lorry/truck and others) and accident cases (over speed and sudden change signal). The findings show meaningful interpretations that can be used for future safety improvement in Seremban.
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References
Oyedepo, O.J., Makinde, O.O.: Accident prediction models for Akure—Ondo carriageway, Ondo state southwest Nigeria; using multiple linear regressions. Afr. Res. Rev. 4(2), 30–49 (2010)
Dabbour, E.: Using logistic regression to identify risk factors causing rollover collisions. Int. J. Traffic Transp. Eng. 2(4), 372–379 (2012). https://doi.org/10.7708/ijte.2012.2(4).07
National Highway Traffic Safety Administration: Traffic Safety Facts. Motor Vehicle Crash Data from FARS and GES (2012)
Royal Malaysian Police: http://www.rmp.gov.my/ (2015)
Wedagama, D.M.P., Dissanayake, D.: The influence of accident related factors on road fatalities considering Bali province in indonesia as a case study. J. East. Asia Soc. Transp. Stud. 8 (2009)
Yan, X., Radwan, E., Abdel-Aty, M.: Characteristics of rear-end accidents at signalized intersections using multiple logistic regression model. Accid. Anal. Prev. 37(6), 983–995 (2005)
Haadi, A.-R.: Identification of factors that cause severity of road accidents in ghana: a case study of the northern region. Int. J. Appl. Sci. Technol. 4(3) (2014)
Shankar, V., Mannering, F., Barfield, W.: Statistical analysis of accident severity on rural freeways. Accid. Anal. Prev. 28(3), 391–401 (1996)
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Malek, I.A., Salim, N.N.M., Alias, S.N., Zaki, N.A.M., Malek, H.A. (2019). Road Fatalities Using Logistic Regression. In: Kor, LK., Ahmad, AR., Idrus, Z., Mansor, K. (eds) Proceedings of the Third International Conference on Computing, Mathematics and Statistics (iCMS2017). Springer, Singapore. https://doi.org/10.1007/978-981-13-7279-7_50
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DOI: https://doi.org/10.1007/978-981-13-7279-7_50
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