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Road Fatalities Using Logistic Regression

  • Isnewati Ab MalekEmail author
  • Nurul Najihah Mohd Salim
  • Siti Naffsikah Alias
  • Nurul Akilah Mohd Zaki
  • Haslinda Ab Malek
Conference paper

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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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Isnewati Ab Malek
    • 1
    Email author
  • Nurul Najihah Mohd Salim
    • 1
  • Siti Naffsikah Alias
    • 1
  • Nurul Akilah Mohd Zaki
    • 1
  • Haslinda Ab Malek
    • 1
  1. 1.Faculty of Computer and Mathematical SciencesUniversiti Teknologi MARAShah AlamMalaysia

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