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Quantitative risk assessment of freeway crash casualty using high-resolution traffic data

Author

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  • Xu, Chengcheng
  • Wang, Yong
  • Liu, Pan
  • Wang, Wei
  • Bao, Jie

Abstract

This study aimed to investigate the impacts of traffic flow conditions on crash casualty of different collision types using high-resolution traffic data. The principle components analysis was conducted to deal with a large number of correlated lane-specific traffic variables. A four-stage random-parameters sequential logistic regression model was then developed to link the probability of crash casualty of each collision type with real-time traffic flow, weather, and geometric conditions. The results showed that the risks of injuries in sideswipe crashes increase with an increase in the speed difference between adjacent lanes, volume on right lane, and standard deviation of volume on inner lanes. The congested traffic conditions and its interaction with adverse weather decrease the risks of injuries in sideswipe crashes. For rear-end crashes, the congested traffic conditions at diverge area, and large difference in speed on right lane between upstream and downstream station in adverse weather contribute to crash casualty. Moreover, high volume on inner lanes reduce the risks of injuries in rear-end crashes. The validation results showed that the prediction accuracy at each severity level by collision types is satisfactory.

Suggested Citation

  • Xu, Chengcheng & Wang, Yong & Liu, Pan & Wang, Wei & Bao, Jie, 2018. "Quantitative risk assessment of freeway crash casualty using high-resolution traffic data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 299-311.
    • Handle: RePEc:eee:reensy:v:169:y:2018:i:c:p:299-311
    DOI: 10.1016/j.ress.2017.09.005
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    References listed on IDEAS

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    1. Wang, Chao & Quddus, Mohammed & Ison, Stephen, 2009. "The effects of area-wide road speed and curvature on traffic casualties in England," Journal of Transport Geography, Elsevier, vol. 17(5), pages 385-395.
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    Cited by:

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    4. Bo Yang & Yao Wu & Weihua Zhang & Jie Bao, 2020. "Modeling Collision Probability on Freeway: Accounting for Different Types and Severities in Various LOS," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    5. Feng, Yingzi & Zhao, Jiandong & Sun, Huijun & Wu, Jianjun & Gao, Ziyou, 2022. "Choices of intercity multimodal passenger travel modes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    6. Chen, Tianyi & Wong, Yiik Diew & Shi, Xiupeng & Wang, Xueqin, 2022. "Optimized structure learning of Bayesian Network for investigating causation of vehicles’ on-road crashes," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    7. Xu, Chengcheng & Xu, Shuoyan & Wang, Chen & Li, Jing, 2019. "Investigating the factors affecting secondary crash frequency caused by one primary crash using zero-inflated ordered probit regression," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 524(C), pages 121-129.
    8. Jiajun Shen & Guangchuan Yang, 2020. "Crash Risk Assessment for Heterogeneity Traffic and Different Vehicle-Following Patterns Using Microscopic Traffic Flow Data," Sustainability, MDPI, vol. 12(23), pages 1-18, November.
    9. Gu, Yu & Fu, Xiao & Liu, Zhiyuan & Xu, Xiangdong & Chen, Anthony, 2020. "Performance of transportation network under perturbations: Reliability, vulnerability, and resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 133(C).
    10. Yongfeng Ma & Wenbo Zhang & Xin Gu & Jiguang Zhao, 2019. "Impacts of experimental advisory exit speed sign on traffic speeds for freeway exit ramp," PLOS ONE, Public Library of Science, vol. 14(11), pages 1-17, November.
    11. Liping Liu & Qing Wu & Shuxia Li & Ying Li & Tijun Fan, 2021. "Risk Assessment of Hazmat Road Transportation Considering Environmental Risk under Time-Varying Conditions," IJERPH, MDPI, vol. 18(18), pages 1-19, September.

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