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An extended dynamic probabilistic risk approach based on a surrogate safety measure for rear-end collisions on two-lane roads

Author

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  • Torkashvand, Mojtaba Bahrami
  • Aghayan, Iman
  • Qin, Xiao
  • Hadadi, Farhad

Abstract

The rear-end collisions have significantly increased on two-lane roads because of drivers’ overtaking behaviors, and the time to collision (TTC) plays an effective role in these collisions. To prevent this type of collision, investigating the effect of overtaking behaviors on the TTC and predicting the risk probability of collisions are essential issues in road safety. To this end, the present study evaluated overtaking behaviors to find the effect of these behaviors on the TTC to determine a TTC threshold as a surrogate safety measure. Moreover, a dynamic probabilistic risk approach was developed based on binomial logistic regression and higher-order ordinary differential equations to examine the risk probability of the TTC threshold, which is then numerically solved by relying on Euler’s method. Accordingly, the importance weights of overtaking variables on the TTC were studied by multilayer perceptron to determine the importance weights in the risk value. The obtained data indicated that the TTC threshold was 2.4 s under the influence of overtaking behavior. Further, the results from dynamic risk probabilistic models revealed that space headway, time headway, and overtaking speed could raise the probability risk of the TTC threshold by 97, 95, and 93%, respectively. Finally, data related to the risk of the TTC for the proposed models indicated that the highest and lowest risks belong to space headway (1.3 times higher than other variables) and decision time (0.6 times less than other variables), respectively.

Suggested Citation

  • Torkashvand, Mojtaba Bahrami & Aghayan, Iman & Qin, Xiao & Hadadi, Farhad, 2022. "An extended dynamic probabilistic risk approach based on a surrogate safety measure for rear-end collisions on two-lane roads," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    • Handle: RePEc:eee:phsmap:v:603:y:2022:i:c:s0378437122005490
    DOI: 10.1016/j.physa.2022.127845
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    References listed on IDEAS

    as
    1. Rezaei, Danial & Aghayan, Iman & Hadadi, Farhad, 2021. "Studying perturbations and wave propagations by lane closures on traffic characteristics based on a dynamic approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    2. Jiao, Shuaiyang & Zhang, Shengrui & Zhou, Bei & Zhang, Lei & Xue, Liyuan, 2021. "Dynamic performance and safety analysis of car-following models considering collision sensitivity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    3. Behram Wali & Asad Khattak & Thomas Karnowski, 2020. "The relationship between driving volatility in time to collision and crash injury severity in a naturalistic driving environment," Papers 2010.04719, arXiv.org.
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    Cited by:

    1. Hossein Samadi & Iman Aghayan & Khaled Shaaban & Farhad Hadadi, 2023. "Development of Performance Measurement Models for Two-Lane Roads under Vehicular Platooning Using Conjugate Bayesian Analysis," Sustainability, MDPI, vol. 15(5), pages 1-26, February.

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