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Analysis of Risk Factors Affecting Urban Truck Traffic Accident Severity in Korea

Author

Listed:
  • Maowei Chen

    (Graduate School of Logistics, Incheon National University, Incheon 22012, Korea)

  • Lele Zhou

    (Graduate School of Logistics, Incheon National University, Incheon 22012, Korea)

  • Sangho Choo

    (Department of Urban Design & Planning, Hongik University, Seoul 04066, Korea)

  • Hyangsook Lee

    (Graduate School of Logistics, Incheon National University, Incheon 22012, Korea)

Abstract

Due to increases in truck traffic, truck traffic safety has become an unavoidable societal issue in Korea. Truck traffic accidents were responsible for 24% of all traffic deaths in 2019, and the fatality rate was significantly higher than that of other forms of traffic. This study analyzes not only the driver and environmental factors, but also the traffic condition factors which are considered to contribute to the severity of truck traffic accidents, and presents practical truck safety solutions based on the findings. This study examines the fatal and serious injury truck traffic accidents in Incheon, which has large logistics facilities and the highest fatality rate (3.3) in Korea’s capital area. According to the regression analysis results, ‘Nighttime’, ‘Vehicle-single’, ‘Vehicle to Pedestrian’, ‘Lane violation’, and ‘Signal violation’ contribute to the severity of truck traffic accidents. Furthermore, truck traffic accidents in the logistics influencing area are more likely to be serious than in the non-influencing area. In terms of the traffic condition factors, the number of lanes, the maximum speed, and the number of road property-changing nodes were significant. The results of this study will provide useful data for establishing traffic safety policies in urban areas.

Suggested Citation

  • Maowei Chen & Lele Zhou & Sangho Choo & Hyangsook Lee, 2022. "Analysis of Risk Factors Affecting Urban Truck Traffic Accident Severity in Korea," Sustainability, MDPI, vol. 14(5), pages 1-14, March.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:5:p:2901-:d:762365
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    Citations

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    Cited by:

    1. Qing Ye & Yi Li & Wenzhe Shen & Zhaoze Xuan, 2023. "Division and Analysis of Accident-Prone Areas near Highway Ramps Based on Spatial Autocorrelation," Sustainability, MDPI, vol. 15(10), pages 1-20, May.
    2. Tongqiang Ding & Lianxin Zhang & Jianfeng Xi & Yingjuan Li & Lili Zheng & Kexin Zhang, 2023. "Bus Fleet Accident Prediction Based on Violation Data: Considering the Binding Nature of Safety Violations and Service Violations," Sustainability, MDPI, vol. 15(4), pages 1-22, February.
    3. Suzana Tajnik & Blaž Luin, 2022. "Impact of Driver, Vehicle, and Environment on Rural Road Crash Rate," Sustainability, MDPI, vol. 14(23), pages 1-18, November.

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