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Study on the Impact of Road Traffic Accident Duration Based on Statistical Analysis and Spatial Distribution Characteristics: An Empirical Analysis of Houston

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Listed:
  • Xu Sun

    (School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
    Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China)

  • Hanxiao Hu

    (Institute of Highway, Chang’an University, Xi’an 710129, China)

  • Shuo Ma

    (School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Kun Lin

    (Fuzhou Planning and Design Research institute Group Co., Ltd., Fuzhou 350108, China)

  • Jianyu Wang

    (School of Civil and Transportation Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
    Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China)

  • Huapu Lu

    (Institute of Transportation Engineering, Tsinghua University, Beijing 100084, China)

Abstract

In this study, factors affecting crash duration and geostatistical analysis were examined using traffic crash data from Houston, USA. Significant factors affecting road crash duration included 14 independent factors related to time, roadway, and environment. Delays caused by traffic crashes were used as an indicator to assess the impact of traffic crashes of different severity on the roadway network. In addition, the spatial distribution characteristics of the different values corresponding to each key impact factor under different scenarios in the region were studied using ArcGIS kernel density analysis techniques. This is because the combination of these two methods is more operational and understandable. The results show that accidents are more likely to occur at night and on holidays, that accidents last longer after they occur in residential areas, and that accident duration varies near different road facilities. This study may provide a reference for targeted management and improvement measures for road safety.

Suggested Citation

  • Xu Sun & Hanxiao Hu & Shuo Ma & Kun Lin & Jianyu Wang & Huapu Lu, 2022. "Study on the Impact of Road Traffic Accident Duration Based on Statistical Analysis and Spatial Distribution Characteristics: An Empirical Analysis of Houston," Sustainability, MDPI, vol. 14(22), pages 1-14, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:14982-:d:971167
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    References listed on IDEAS

    as
    1. Nam, Doohee & Mannering, Fred, 2000. "An exploratory hazard-based analysis of highway incident duration," Transportation Research Part A: Policy and Practice, Elsevier, vol. 34(2), pages 85-102, February.
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    3. Ping Zhang & Chenzhu Wang & Fei Chen & Suping Cui & Jianchuan Cheng & Wu Bo, 2022. "A Random-Parameter Negative Binomial Model for Assessing Freeway Crash Frequency by Injury Severity: Daytime versus Nighttime," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    4. Bardal, Kjersti Granås & Jørgensen, Finn, 2017. "Valuing the risk and social costs of road traffic accidents – Seasonal variation and the significance of delay costs," Transport Policy, Elsevier, vol. 57(C), pages 10-19.
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    Cited by:

    1. Minxue Zheng & Xintong Xie & Yutao Jiang & Qiu Shen & Xiaolei Geng & Luyao Zhao & Feng Jia, 2024. "Optimizing Kernel Density Estimation Bandwidth for Road Traffic Accident Hazard Identification: A Case Study of the City of London," Sustainability, MDPI, vol. 16(16), pages 1-17, August.
    2. Junfeng Yao & Longhao Yan & Zhuohang Xu & Ping Wang & Xiangmo Zhao, 2023. "Collaborative Decision-Making Method of Emergency Response for Highway Incidents," Sustainability, MDPI, vol. 15(3), pages 1-23, January.

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