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Drivers’ Behavior and Traffic Accident Analysis Using Decision Tree Method

Author

Listed:
  • Pires Abdullah

    (Department of Transport Technology and Economics, BME Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, 1111 Budapest, Hungary
    Department of Spatial Planning, College of Spatial Planning, University of Duhok, Kurdistan Region, Duhok 42001, Iraq)

  • Tibor Sipos

    (Department of Transport Technology and Economics, BME Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics, 1111 Budapest, Hungary
    KTI—Institute for Transport Sciences, Directorate for Strategic Research and Development, 1119 Budapest, Hungary)

Abstract

This study was carried out to examine the severity level of crashes by analyzing traffic accidents. The study’s goal is to identify the major contributing factors to traffic accidents in connection to driver behavior and socioeconomic characteristics. In order to find the most probable causes in accordance with the major target variable, which is the level of severity of the crash, the study set out to identify the main attributes induced by the decision tree method (DT). The local people received a semi-structured questionnaire interview with closed-ended questions. The survey asked questions about drivers’ attitude and behavior, as well as other contributing factors such as time of accidents and road type. The attributes were analyzed using the machine-learning method using DT with Python programming language. This method was able to determine the relationship between severe and non-severe crashes and other significant influencing elements. The Duhok city people participated in the survey, which was conducted in the Kurdistan area of northern Iraq. The results of the study demonstrate that the number of lanes, time of the accident, and human attitudes, represented by their adherence to the speed limit, are the primary causes of accidents with victims.

Suggested Citation

  • Pires Abdullah & Tibor Sipos, 2022. "Drivers’ Behavior and Traffic Accident Analysis Using Decision Tree Method," Sustainability, MDPI, vol. 14(18), pages 1-11, September.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11339-:d:911304
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    References listed on IDEAS

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    1. Bertoli, Paola & Grembi, Veronica, 2021. "The political cycle of road traffic accidents," Journal of Health Economics, Elsevier, vol. 76(C).
    2. Mohammad Maghrour Zefreh & Adam Torok, 2021. "Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Environmental External Costs," Sustainability, MDPI, vol. 13(6), pages 1-22, March.
    3. Michael Naor & Alex Coman & Anat Wiznizer, 2021. "Vertically Integrated Supply Chain of Batteries, Electric Vehicles, and Charging Infrastructure: A Review of Three Milestone Projects from Theory of Constraints Perspective," Sustainability, MDPI, vol. 13(7), pages 1-21, March.
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    Cited by:

    1. Jianjun Wang & Chicheng Ma & Sai Wang & Xiaojuan Lu & Dongyi Li, 2022. "Risk Assessment Model and Sensitivity Analysis of Ordinary Arterial Highways Based on RSR–CRITIC–LVSSM–EFAST," Sustainability, MDPI, vol. 14(23), pages 1-19, December.

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