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Unsafe Behaviors Analysis of Sideswipe Collision on Urban Expressways Based on Bayesian Network

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  • Huajing Ning

    (College of Civil Engineering, Lanzhou Jiaotong University, West Anning Road #88, Lanzhou 730000, China
    School of Urban Construction and Transportation, Hefei University, Hefei Jinxiu Road #99, Hefei 230000, China)

  • Yunyan Yu

    (College of Civil Engineering, Lanzhou Jiaotong University, West Anning Road #88, Lanzhou 730000, China)

  • Lu Bai

    (Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Si Pai Lou #2, Nanjing 210000, China
    Department of Civil Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong 999077, China)

Abstract

The causes of crashes on urban expressways are mostly related to the unsafe behaviors of drivers before the crash. This study focuses on sideswipe collisions on urban expressways. Through real and visual crash data, 17 unsafe behaviors were identified for the analysis of sideswipe collisions on an urban expressway. The chains of high-risk and unsafe behaviors were then revealed to investigate the relationship between drivers’ unsafe behaviors and sideswipe collisions. A Bayesian network diagram of unsafe behaviors was used to obtain the correlation between unsafe behaviors and their influence. A topology diagram of unsafe behaviors was then constructed, and relational reasoning of typical behavioral chains was conducted. Finally, the unsafe behaviors and behavior chains that were likely to cause sideswipe collisions on the urban expressway were determined. The possibility of each behavior chain was quantified through the reasoning of variable structures constructed by the Bayesian network. The result shows that the significant influential single unsafe behavior leading to sideswipe collision on urban expressways was lane change without checking the rearview mirror or not scanning the road around and queue-jumping; moreover, based on unsafe behavior chains analysis, the most influential chains leading to sideswipe collision were: improper driving behavior in an emergency—failure to turn on signal when changing lanes—distracted and inattentive driving. Some safety precautions and countermeasures aimed at unsafe behaviors could be taken before the crash. The results of the study can be used to reduce the number of sideswipe collisions, thereby improving traffic safety on urban expressways.

Suggested Citation

  • Huajing Ning & Yunyan Yu & Lu Bai, 2022. "Unsafe Behaviors Analysis of Sideswipe Collision on Urban Expressways Based on Bayesian Network," Sustainability, MDPI, vol. 14(13), pages 1-15, July.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:13:p:8142-:d:855208
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    References listed on IDEAS

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    1. Fang Zong & Hongguo Xu & Huiyong Zhang, 2013. "Prediction for Traffic Accident Severity: Comparing the Bayesian Network and Regression Models," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-9, October.
    2. Iranitalab, Amirfarrokh & Khattak, Aemal, 2020. "Probabilistic classification of hazardous materials release events in train incidents and cargo tank truck crashes," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    3. van Lint, J.W.C. & Calvert, S.C., 2018. "A generic multi-level framework for microscopic traffic simulation—Theory and an example case in modelling driver distraction," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 63-86.
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    Cited by:

    1. Tong Liu & Chang Wang & Rui Fu & Yong Ma & Zhuofan Liu & Tangzhi Liu, 2022. "Lane-Change Risk When the Subject Vehicle Is Faster Than the Following Vehicle: A Case Study on the Lane-Changing Warning Model Considering Different Driving Styles," Sustainability, MDPI, vol. 14(16), pages 1-20, August.

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