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Influence of Risky Driving Behavior and Road Section Type on Urban Expressway Driving Safety

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  • Huacai Xian

    (Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China
    Shandong Key Laboratory of Smart Transportation (Preparation), Jinan 250357, China)

  • Yujia Hou

    (Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China)

  • Yu Wang

    (Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China)

  • Shunzhong Dong

    (Traffic Administration of Shandong Public Security Department, Jinan 250031, China)

  • Junying Kou

    (Traffic Administration of Shandong Public Security Department, Jinan 250031, China)

  • Zewen Li

    (Transportation and Logistics Engineering College, Shandong Jiaotong University, Jinan 250357, China)

Abstract

The causes of traffic crashes are complex and uncertain, among which the risky driving behaviors of drivers and the types of road sections in high-crash areas are all critical influencing factors. We used ArcGIS software to draw traffic heat maps under different thresholds to prevent the occurrence of traffic crashes accurately and effectively according to the vehicle GPS data of urban expressways in Jinan City, Shandong Province. This paper studied the relationship between risky driving behaviors (rapid acceleration, rapid deceleration, and overspeed) and road types with traffic crashes. The traffic safety evaluation model of urban expressways based on ordered logistic was established to predict the safety level of the urban expressway. The model’s accuracy was 85.71%, and the applicability was good. The research results showed that rapid deceleration was the most significant influencing factor of crashes on urban expressways. When the vehicle deceleration was less than or equal to −4 m/s 2 , the probability of a crash was 22.737 times greater than when the vehicle deceleration was at −2 to −2.5 m/s 2 ; when the vehicle acceleration was greater than or equal to 3 m/s 2 , the probability of a crash was 19.453 times greater than when the vehicle acceleration was at 1 to 1.5 m/s 2 . The likelihood of a crash at a road section with a ramp opening was 8.723 times greater than that of a crash at a non-ramp opening; the crash probability of a speeding vehicle was 7.925 times greater than that of a non-speeding vehicle; the likelihood of a crash on a curve was 6.147 times greater than that on a straight. The research results can provide adequate technical support for identifying high-risk sections of expressways and active early warning of traffic crashes.

Suggested Citation

  • Huacai Xian & Yujia Hou & Yu Wang & Shunzhong Dong & Junying Kou & Zewen Li, 2022. "Influence of Risky Driving Behavior and Road Section Type on Urban Expressway Driving Safety," Sustainability, MDPI, vol. 15(1), pages 1-15, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:398-:d:1015822
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    References listed on IDEAS

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    1. Shengdi Chen & Qingwen Xue & Xiaochen Zhao & Yingying Xing & Jian John Lu, 2021. "Risky Driving Behavior Recognition Based on Vehicle Trajectory," IJERPH, MDPI, vol. 18(23), pages 1-14, November.
    2. Longhai Yang & Xiqiao Zhang & Xiaoyan Zhu & Yule Luo & Yi Luo, 2019. "Research on Risky Driving Behavior of Novice Drivers," Sustainability, MDPI, vol. 11(20), pages 1-20, October.
    3. Natalia Casado-Sanz & Begoña Guirao & Maria Attard, 2020. "Analysis of the Risk Factors Affecting the Severity of Traffic Accidents on Spanish Crosstown Roads: The Driver’s Perspective," Sustainability, MDPI, vol. 12(6), pages 1-26, March.
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    Cited by:

    1. Huiqin Chen & Hao Liu & Hailong Chen & Jing Huang, 2023. "Towards Sustainable Safe Driving: A Multimodal Fusion Method for Risk Level Recognition in Distracted Driving Status," Sustainability, MDPI, vol. 15(12), pages 1-22, June.

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