IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i7p3054-d1371016.html
   My bibliography  Save this article

Accident Severity Analysis of Traffic Accident Hot Spot Areas in Changsha City Considering Built Environment

Author

Listed:
  • Ruizhe Yan

    (School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China)

  • Lin Hu

    (School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China)

  • Juanjuan Li

    (School of Design, Changsha University of Science and Technology, Changsha 410114, China)

  • Nanting Lin

    (School of Automotive and Mechanical Engineering, Changsha University of Science and Technology, Changsha 410114, China)

Abstract

Examining the impacts of accident characteristics and differentiated built environment factors on accident severity at inherent accident hotspots within cities can help managers to adjust traffic control measures through urban planning and design, thereby reducing accident casualties. In this study, time series clustering was used to identify traffic accident hotspots in Changsha City. Based on the hotspot identification results, Kruskal–Wallis tests were used to select differentiated built environment factors among different accident areas within the city. A severity analysis model for road crashes in Changsha’s hotspots, taking into account the built environment, was constructed using a Light gradient boosting machine (LightGBM). In addition, Shapley additive explanations (SHAP) were used to reveal the influences of accident characteristics and built environment factors on accident severity. The results showed that different accident characteristics and built environment factors affect accident severity in different urban accident areas. Factors such as type of accident, visibility, period of time, land use mixing degree, population density, density of commercial places, and density of industrial places showed varying degrees of importance in influencing accident severity, while the overall impact trends remained consistent. On the other hand, transportation accessibility, road network density, landform, and accident location showed significant differences in their impacts on accident severity between different accident areas within the city.

Suggested Citation

  • Ruizhe Yan & Lin Hu & Juanjuan Li & Nanting Lin, 2024. "Accident Severity Analysis of Traffic Accident Hot Spot Areas in Changsha City Considering Built Environment," Sustainability, MDPI, vol. 16(7), pages 1-15, April.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:3054-:d:1371016
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/7/3054/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/16/7/3054/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Junwei Zeng & Yongsheng Qian & Fan Yin & Leipeng Zhu & Dejie Xu, 2022. "A multi-value cellular automata model for multi-lane traffic flow under lagrange coordinate," Computational and Mathematical Organization Theory, Springer, vol. 28(2), pages 178-192, June.
    2. Jianyu Wang & Lanxin Ji & Shuo Ma & Xu Sun & Mingxin Wang, 2023. "Analysis of Factors Influencing the Severity of Vehicle-to-Vehicle Accidents Considering the Built Environment: An Interpretable Machine Learning Model," Sustainability, MDPI, vol. 15(17), pages 1-17, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Liang Zou & Suiying Hu & Lingxiang Zhu, 2023. "Based on AFC Data Calculation of Walking Time in Metro Stations Considering the Impact of Passenger Flows," Sustainability, MDPI, vol. 15(8), pages 1-14, April.
    2. Tian, Tian & Liu, Gang & Hu, Xiaoxi & Bian, Dingding, 2024. "Traffic behavior analysis of the urban expressway ramp based on continuous cellular automata," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 633(C).
    3. Junwei Zhou & Xizhong Qin & Yuanfeng Ding & Haodong Ma, 2023. "Spatial–Temporal Dynamic Graph Differential Equation Network for Traffic Flow Forecasting," Mathematics, MDPI, vol. 11(13), pages 1-17, June.
    4. Lu, Hao & Fan, Yiwei & Jiao, Liudan & Wu, Ya, 2024. "Assessment and spatial effect of urban agglomeration business environments: A case study of two urban agglomerations in China," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
    5. Pan, Yuchen & Wu, Yu & Xu, Lu & Xia, Chengyi & Olson, David L., 2024. "The impacts of connected autonomous vehicles on mixed traffic flow: A comprehensive review," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    6. Chaolun Wang & Wang Xiang & Guiqiu Xu & Xiaomeng Li, 2023. "Effects of Object-Oriented Advance Guidance Signage on Lane-Changing Behaviors at the Mainline Toll Stations of Expressways," Sustainability, MDPI, vol. 15(2), pages 1-16, January.
    7. Pengying Ouyang & Bo Yang, 2024. "Evaluation of Spatiotemporal Characteristics of Lane-Changing at the Freeway Weaving Area from Trajectory Data," Sustainability, MDPI, vol. 16(4), pages 1-21, February.
    8. Zhang, Quan & Li, Xuan & Yan, Tao & Lu, Lili & Shi, Yang, 2022. "Last train timetabling optimization for minimizing passenger transfer failures in urban rail transit networks: A time period based approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 605(C).
    9. Zhuang, Xinfa & Zhang, Jing & Tian, Junfang & Cui, Fengying & Wang, Tao, 2024. "Variable time headway spacing strategy for connected vehicles platoon based on sliding mode control," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    10. Zhang, Xiangzhou & Shi, Zhongke & Yu, Shaowei & Ma, Lijing, 2023. "A new car-following model considering driver’s desired visual angle on sharp curves," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    11. Amani Abdallah Assolie & Rana Imam & Ibrahim Khliefat & Ala Alobeidyeen, 2024. "Modeling of Applying Road Pricing to Airport Highway Using VISUM Software in Jordan," Sustainability, MDPI, vol. 16(18), pages 1-49, September.
    12. Peng, Guanghan & Luo, Chunli & Zhao, Hongzhuan & Tan, Huili, 2023. "Jamming transition in two-lane lattice model integrating the deception attacks on influx during the lane-changing process under vehicle to everything environment," Chaos, Solitons & Fractals, Elsevier, vol. 176(C).
    13. Zhesong Hao & Ying Peng, 2022. "Comparing Nonlinear and Threshold Effects of Bus Stop Proximity on Transit Use and Carbon Emissions in Developing Cities," Land, MDPI, vol. 12(1), pages 1-21, December.
    14. Pei, Yulong & Pan, Sheng & Wen, Yuhang, 2024. "Analysis of roadway capacity for heterogeneous traffic flows considering the degree of trust of drivers of HVs in CAVs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    15. Zakaria A. Mani & Krzysztof Goniewicz, 2023. "Transportation Disaster Trends and Impacts in Western Asia: A Comprehensive Analysis from 2003 to 2023," Sustainability, MDPI, vol. 15(18), pages 1-14, September.
    16. Ning, Jia & Xing, Xinjie & Wang, Yadong & Yao, Yu & Kang, Liujiang & Peng, Qiyuan, 2024. "Coordinating last-train timetabling with app-based ride-hailing service under uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
    17. Nattawut Pumpugsri & Wanchai Rattanawong & Varin Vongmanee, 2023. "Development of a Safety Heavy-Duty Vehicle Model Considering Unsafe Acts, Unsafe Conditions and Near-Miss Events Using Structural Equation Model," Sustainability, MDPI, vol. 15(16), pages 1-20, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:7:p:3054-:d:1371016. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.