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Influential Factors Associated with Consecutive Crash Severity: A Two-Level Logistic Modeling Approach

Author

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  • Fanyu Meng

    (Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen 518000, China
    Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen 518000, China)

  • Pengpeng Xu

    (Department of Civil Engineering, The University of Hong Kong, Hong Kong 999077, China)

  • Cancan Song

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

  • Kun Gao

    (Department of Architecture and Civil Engineering, Chalmers University of Technology, 41296 Göteborg, Sweden)

  • Zichu Zhou

    (Key Laboratory of Road and Traffic Engineering of the Ministry of Education, Tongji University, Shanghai 201804, China)

  • Lili Yang

    (Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen 518000, China)

Abstract

A consecutive crash series is composed by a primary crash and one or more subsequent secondary crashes that occur immediately within a certain distance. The crash mechanism of a consecutive crash series is distinctive, as it is different from common primary and secondary crashes mainly caused by queuing effects and chain-reaction crashes that involve multiple collisions in one crash. It commonly affects a large area of road space and possibly causes congestions and significant delays in evacuation and clearance. This study identified the influential factors determining the severity of primary and secondary crashes in a consecutive crash series. Basic, random-effects, random-parameters, and two-level binary logistic regression models were established based on crash data collected on the freeway network of Guizhou Province, China in 2018, of which 349 were identified as consecutive crashes. According to the model performance metrics, the two-level logistic model outperformed the other three models. On the crash level, double-vehicle primary crash had a negative association with the severity of secondary consecutive crashes, and the involvement of trucks in the secondary consecutive crash had a positive contribution to its crash severity. On a road segment level, speed limit, traffic volume, tunnel, and extreme weather conditions such as rainy and cloudy days had positive effects on consecutive crash severity, while the number of lanes was negatively associated with consecutive crash severity. Policy suggestions are made to alleviate the severity of consecutive crashes by reminding the drivers with real-time potential hazards of severe consecutive crashes and providing educative programs to specific groups of drivers.

Suggested Citation

  • Fanyu Meng & Pengpeng Xu & Cancan Song & Kun Gao & Zichu Zhou & Lili Yang, 2020. "Influential Factors Associated with Consecutive Crash Severity: A Two-Level Logistic Modeling Approach," IJERPH, MDPI, vol. 17(15), pages 1-16, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:15:p:5623-:d:394515
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    References listed on IDEAS

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    1. Nagatani, Takashi, 2015. "Chain-reaction crash in traffic flow controlled by taillights," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 1-6.
    2. Xiaojun Shao & Xiaoxiang Ma & Feng Chen & Mingtao Song & Xiaodong Pan & Kesi You, 2020. "A Random Parameters Ordered Probit Analysis of Injury Severity in Truck Involved Rear-End Collisions," IJERPH, MDPI, vol. 17(2), pages 1-18, January.
    3. Yingying Xing & Shengdi Chen & Shengxue Zhu & Yi Zhang & Jian Lu, 2020. "Exploring Risk Factors Contributing to the Severity of Hazardous Material Transportation Accidents in China," IJERPH, MDPI, vol. 17(4), pages 1-19, February.
    4. Feng Chen & Mingtao Song & Xiaoxiang Ma, 2019. "Investigation on the Injury Severity of Drivers in Rear-End Collisions Between Cars Using a Random Parameters Bivariate Ordered Probit Model," IJERPH, MDPI, vol. 16(14), pages 1-12, July.
    5. Fangrong Chang & Maosheng Li & Pengpeng Xu & Hanchu Zhou & Md. Mazharul Haque & Helai Huang, 2016. "Injury Severity of Motorcycle Riders Involved in Traffic Crashes in Hunan, China: A Mixed Ordered Logit Approach," IJERPH, MDPI, vol. 13(7), pages 1-15, July.
    6. Kairan Zhang & Mohamed Hassan, 2019. "Crash severity analysis of nighttime and daytime highway work zone crashes," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-17, August.
    7. Changxi Ma & Jibiao Zhou & Dong Yang, 2020. "Causation Analysis of Hazardous Material Road Transportation Accidents Based on the Ordered Logit Regression Model," IJERPH, MDPI, vol. 17(4), pages 1-25, February.
    8. Xiong, Yingge & Tobias, Justin L. & Mannering, Fred L., 2014. "The analysis of vehicle crash injury-severity data: A Markov switching approach with road-segment heterogeneity," Transportation Research Part B: Methodological, Elsevier, vol. 67(C), pages 109-128.
    9. Jingjing Xu & Behram Wali & Xiaobing Li & Jiaqi Yang, 2019. "Injury Severity and Contributing Driver Actions in Passenger Vehicle–Truck Collisions," IJERPH, MDPI, vol. 16(19), pages 1-16, September.
    10. Nagatani, Takashi & Yonekura, Shoichi, 2014. "Multiple-vehicle collision induced by lane changing in traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 404(C), pages 171-179.
    11. En-Zhong Zhao & Li-Li Dong & Yang Chen & Qi Lou & Wen-Hai Xu, 2020. "The Impact of LED Color Rendering on the Dark Adaptation of Human Eyes at Tunnel Entrances," IJERPH, MDPI, vol. 17(5), pages 1-20, February.
    12. Rachel Aldred & Susana García-Herrero & Esther Anaya & Sixto Herrera & Miguel Ángel Mariscal, 2019. "Cyclist Injury Severity in Spain: A Bayesian Analysis of Police Road Injury Data Focusing on Involved Vehicles and Route Environment," IJERPH, MDPI, vol. 17(1), pages 1-16, December.
    13. Sugiyama, Naoki & Nagatani, Takashi, 2013. "Multiple-vehicle collision in traffic flow by a sudden slowdown," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(8), pages 1848-1857.
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    Cited by:

    1. Arshad Jamal & Waleed Umer, 2020. "Exploring the Injury Severity Risk Factors in Fatal Crashes with Neural Network," IJERPH, MDPI, vol. 17(20), pages 1-22, October.
    2. Xiuguang Song & Rendong Pi & Yu Zhang & Jianqing Wu & Yuhuan Dong & Han Zhang & Xinyuan Zhu, 2021. "Determinants and Prediction of Injury Severities in Multi-Vehicle-Involved Crashes," IJERPH, MDPI, vol. 18(10), pages 1-16, May.

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