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Exploring Influential Factors Affecting the Severity of Urban Expressway Collisions: A Study Based on Collision Data

Author

Listed:
  • Kun Wang

    (School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
    Beihang Hangzhou Innovation Institute Yuhang, Hangzhou 310023, China)

  • Xiaoyuan Feng

    (School of Transportation Science and Engineering, Beihang University, Beijing 102206, China)

  • Hongbo Li

    (School of Transportation Science and Engineering, Beihang University, Beijing 102206, China)

  • Yilong Ren

    (School of Transportation Science and Engineering, Beihang University, Beijing 102206, China
    Beihang Hangzhou Innovation Institute Yuhang, Hangzhou 310023, China)

Abstract

When traffic collisions occur on urban expressways, the consequences, including injuries, the loss of lives, and damage to properties, are more serious. However, the existing research on the severity of expressway traffic collisions has not been deeply explored. The purpose of this research was to investigate how various factors affect the severity of urban expressway collisions. The severity of urban expressway collisions was set as the dependent variable, which could be divided into three categories: slight collisions, severe collisions, and fatal collisions. Ten variables, including individual characteristics, collision characteristics, and road environment conditions, were selected as independent factors. Based on 975 valid urban expressway collisions, an ordered logistic regression model was established to evaluate the impacts of influence factors on the severity of these crashes. The results show that gender, collision modality, road pavement conditions, road surface conditions, and visibility are significant factors that affect the severity of urban expressway collisions. Females were more likely to be involved in more severe urban expressway collisions than males. For collisions involving pedestrians and non-motorized vehicles, the risk of more severe injury was 7.508 times higher than that associated with vehicle–vehicle collisions. The probability of more severe collisions on urban expressways with poor pavement conditions and wet surface conditions is greater than that on urban expressways with good pavement conditions and dry surface conditions. In addition, as visibility increases, the probability of more severe collisions on urban expressways gradually decreases. These results provide more effective strategies to reduce casualties as a result of urban expressway collisions.

Suggested Citation

  • Kun Wang & Xiaoyuan Feng & Hongbo Li & Yilong Ren, 2022. "Exploring Influential Factors Affecting the Severity of Urban Expressway Collisions: A Study Based on Collision Data," IJERPH, MDPI, vol. 19(14), pages 1-11, July.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:14:p:8362-:d:858516
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    References listed on IDEAS

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    1. Yuta Sekiguchi & Masayoshi Tanishita & Daisuke Sunaga, 2022. "Characteristics of Cyclist Crashes Using Polytomous Latent Class Analysis and Bias-Reduced Logistic Regression," Sustainability, MDPI, vol. 14(9), pages 1-15, May.
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    Cited by:

    1. Hao Dong & Yang Zhang & Tianqing Chen & Juan Li, 2023. "Acceptance Intention and Behavioral Response to Soil-Testing Formula Fertilization Technology: An Empirical Study of Agricultural Land in Shaanxi Province," IJERPH, MDPI, vol. 20(2), pages 1-13, January.
    2. Ying Cheng & Zhen Liu & Li Gao & Yanan Zhao & Tingting Gao, 2022. "Traffic Risk Environment Impact Analysis and Complexity Assessment of Autonomous Vehicles Based on the Potential Field Method," IJERPH, MDPI, vol. 19(16), pages 1-14, August.
    3. Yingcui Du & Feng Sun & Fangtong Jiao & Benxing Liu & Xiaoqing Wang & Pengsheng Zhao, 2023. "The Identification of Intersection Entrance Accidents Based on Autoencoder," Sustainability, MDPI, vol. 15(11), pages 1-17, May.

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