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Risk Factors Affecting Traffic Accidents at Urban Weaving Sections: Evidence from China

Author

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  • Xinhua Mao

    (School of Economics and Management, Chang’an University, Xi’an 710064, China
    Department of Civil and Environmental Engineering, University of Waterloo, Waterloo, ON N2L 3G1, Canada)

  • Changwei Yuan

    (School of Economics and Management, Chang’an University, Xi’an 710064, China)

  • Jiahua Gan

    (Transport Planning and Research Institute, Ministry of Transport, Beijing 100028, China)

  • Shiqing Zhang

    (School of Management Engineering, Zhengzhou University of Aeronautics, Zhengzhou 450046, China)

Abstract

As a critical configuration of interchanges, the weaving section is inclined to be involved in more traffic accidents, which may bring about severe casualties. To identify the factors associated with traffic accidents at the weaving section, we employed the multinomial logistic regression approach to identify the correlation between six categories of risk factors (drivers’ attributes, weather conditions, traffic characteristics, driving behavior, vehicle types and temporal-spatial distribution) and four types of traffic accidents (rear-end, side wipe, collision with fixtures and rollover) based on 768 accident samples of an observed weaving section from 2016 to 2018. The modeling results show that drivers’ gender and age, weather condition, traffic density, weaving ratio, vehicle speed, lane change behavior, private cars, season, time period, day of week and accident location are important factors affecting traffic accidents at the weaving section, but they have different contributions to the four traffic accident types. The results also show that traffic density of ≥31 vehicle/100 m has the highest risk of causing rear-end accidents, weaving ration of ≥41% has the highest possibility to bring about a side wipe incident, collision with fixtures is the most likely to happen in snowy weather, and rollover is the most likely incident to occur in rainy weather.

Suggested Citation

  • Xinhua Mao & Changwei Yuan & Jiahua Gan & Shiqing Zhang, 2019. "Risk Factors Affecting Traffic Accidents at Urban Weaving Sections: Evidence from China," IJERPH, MDPI, vol. 16(9), pages 1-17, May.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:9:p:1542-:d:227505
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    References listed on IDEAS

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    Cited by:

    1. Lijing Du & Fasheng Huang & Hua Lu & Sijing Chen & Qianwen Guo, 2024. "An Association Rule Mining-Based Modeling Framework for Characterizing Urban Road Traffic Accidents," Sustainability, MDPI, vol. 16(23), pages 1-30, December.
    2. Yaqi Liu & Xiaoyuan Wang, 2020. "Differences in Driving Intention Transitions Caused by Driver’s Emotion Evolutions," IJERPH, MDPI, vol. 17(19), pages 1-22, September.
    3. Jinhua Tan & Li Gong & Xuqian Qin, 2019. "Effect of Imitation Phenomenon on Two-Lane Traffic Safety in Fog Weather," IJERPH, MDPI, vol. 16(19), pages 1-15, October.
    4. Fanyu Wang & Junyou Zhang & Shufeng Wang & Sixian Li & Wenlan Hou, 2020. "Analysis of Driving Behavior Based on Dynamic Changes of Personality States," IJERPH, MDPI, vol. 17(2), pages 1-17, January.
    5. Jinliang Xu & Tian Xin & Chao Gao & Zhenhua Sun, 2022. "Study on the Maximum Safe Instantaneous Input of the Steering Wheel against Rollover for Trucks on Horizontal Curves," IJERPH, MDPI, vol. 19(4), pages 1-23, February.
    6. Zhanji Zheng & Qiaojun Xiang & Xin Gu & Yongfeng Ma & Kangkang Zheng, 2020. "The Influence of Individual Differences on Diverging Behavior at the Weaving Sections of an Urban Expressway," IJERPH, MDPI, vol. 18(1), pages 1-17, December.
    7. Yuquan Zhou & Yingzhi Wang & Feng Zhang & Hongye Zhou & Keran Sun & Yuhan Yu, 2023. "GATR: A Road Network Traffic Violation Prediction Method Based on Graph Attention Network," IJERPH, MDPI, vol. 20(4), pages 1-18, February.

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