Association rule analysis of factors contributing to extraordinarily severe traffic crashes in China

Chengcheng Xu; Jie Bao; Chen Wang; Pan Liu

doi:10.1016/j.jsr.2018.09.013

Association rule analysis of factors contributing to extraordinarily severe traffic crashes in China

J Safety Res. 2018 Dec:67:65-75. doi: 10.1016/j.jsr.2018.09.013. Epub 2018 Oct 5.

Authors

Chengcheng Xu¹, Jie Bao², Chen Wang³, Pan Liu⁴

Affiliations

¹ Jiangsu Key Laboratory of Urban ITS, Southeast University, Si Pai Lou #2, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Si Pai Lou #2, Nanjing 210096, China; School of Transportation, Southeast University, Si Pai Lou #2, Nanjing 210096, China. Electronic address: xuchengcheng@seu.edu.cn.
² Jiangsu Key Laboratory of Urban ITS, Southeast University, Si Pai Lou #2, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Si Pai Lou #2, Nanjing 210096, China; School of Transportation, Southeast University, Si Pai Lou #2, Nanjing 210096, China. Electronic address: baojie@seu.edu.cn.
³ Jiangsu Key Laboratory of Urban ITS, Southeast University, Si Pai Lou #2, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Si Pai Lou #2, Nanjing 210096, China; School of Transportation, Southeast University, Si Pai Lou #2, Nanjing 210096, China. Electronic address: wkobec@hotmail.com.
⁴ Jiangsu Key Laboratory of Urban ITS, Southeast University, Si Pai Lou #2, Nanjing 210096, China; Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Si Pai Lou #2, Nanjing 210096, China; School of Transportation, Southeast University, Si Pai Lou #2, Nanjing 210096, China. Electronic address: liupan@seu.edu.cn.

PMID: 30553431
DOI: 10.1016/j.jsr.2018.09.013

Abstract

Introduction: This study aimed to investigate the contributing factors to serious casualty traffic crashes and their interdependency in China. Serious casualty crashes are defined as crashes that lead to more than 10 deaths.

Method: The data of serious casualty crashes between 2009 and 2013 were obtained from the Annual Report for Road Traffic Accidents published by the Ministry of Public Security of China (MPSC). Descriptive statistics were used to illustrate the characteristics of serious casualty crashes in terms of road user behavior, vehicle conditions, geometric characteristics, and environmental conditions. The association rule mining technique was further applied to identify sets of crash contributory factors that often occur together in serious casualty crashes.

Results: The results showed that serious casualty crashes are a result of complex interactions between road user behavior, vehicle factors, road geometric characteristics, and environmental factors. Association rule analysis revealed the reasons for the occurrence of serious casualty crashes in different circumstances, based on which potential policy implications for preventing serious casualty crashes were identified.

Practical applications: The results of this study can provide transportation agencies with useful insights for understanding why serious casualty crashes occur and developing effective policy initiatives and engineering countermeasures to reduce the fatalities and injuries of serious casualty crashes.

Keywords: Association rules; Crash characteristics; Crash contributing factors; Serious casualty crashes; Traffic safety policy.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Accidents, Traffic / mortality
Accidents, Traffic / prevention & control*
Accidents, Traffic / statistics & numerical data
Automobile Driving
Cause of Death* / trends
China / epidemiology
Engineering
Environment Design
Humans
Motor Vehicles
Policy
Transportation