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International Journal of Civil Engineering

, Volume 15, Issue 4, pp 653–662 | Cite as

Identifying the Most Important Factors in the At-Fault Probability of Motorcyclists by Data Mining, Based on Classification Tree Models

  • Mohammad Bagher Anvari
  • Ali Tavakoli Kashani
  • Rahim Rabieyan
Research Paper

Abstract

The motorcycle is considered one of the most applicable transportation modes for various trips in Iran. According to a 2011 report by Iran’s Police Department, motorcyclists and their passengers accounted for almost 25% of all crash fatalities. The objective of this study is to identify the most important factors that contribute to the fault of motorcyclists involved in crashes. The classification and regression trees model is used in this research to differentiate between at-fault and not-at-fault cases. The results show collision type to be the most determining factor for at-fault probability of motorcyclists. According to this fact, the probability of rear-end collision is the highest, while the probability of side collisions is the lowest. Other factors involved vary according to the collision type. Factors affecting rear-end collisions the most are passenger characteristics and the rider’s age. However, side collisions are mainly due to lighting conditions and area types (urban and rural roads). Finally, this paper suggests that training riders and installing warning systems that warn drivers when they are too close to motorcycles can reduce rear-end and side collisions to a great extent.

Keywords

Motorcycle Being at-fault Classification and regression trees Passengers 

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Copyright information

© Iran University of Science and Technology 2017

Authors and Affiliations

  • Mohammad Bagher Anvari
    • 1
  • Ali Tavakoli Kashani
    • 1
  • Rahim Rabieyan
    • 1
  1. 1.School of Civil EngineeringIran University of Science and TechnologyTehranIran

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