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Spatiotemporal Heterogeneity Analysis of Provincial Road Traffic Accidents and Its Influencing Factors in China

Author

Listed:
  • Keke Zhang

    (School of Automobile and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China)

  • Shaohua Wang

    (School of Automobile and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China)

  • Chengcheng Song

    (China Waterborne Transport Research Institute, Beijing 100088, China)

  • Sinan Zhang

    (School of Automobile and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China)

  • Xia Liu

    (School of Automobile and Transportation, Tianjin University of Technology and Education, Tianjin 300222, China)

Abstract

To objectively evaluate the road traffic safety levels across different provinces in China, this study investigated the spatiotemporal heterogeneity characteristics of macro factors influencing road traffic accidents. Panel data from 31 provinces in China from 2009 to 2021 were collected, and after data preprocessing, traffic accident data were selected as the dependent variables. Population size, economic level, motorization level, highway mileage, unemployment rate, and passenger volume were selected as explanatory variables. Based on the spatiotemporal non-stationarity testing of traffic accident data, three models, namely, ordinary least squares (OLS), geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR), were constructed for empirical research. The results showed that the spatiotemporal heterogeneity characterizing the macro factors of traffic accidents could not be ignored. In terms of impact effects, highway mileage, population size, motorization level and passenger volume had positive promoting effects on road traffic accidents, while economic level and unemployment rate mainly exhibited negative inhibitory effects. In terms of impact magnitude, highway mileage had the greatest impact on traffic accidents, followed by population size, motorization level, and passenger volume. Comparatively, the impact magnitude of economic level and unemployment rate was relatively small. The conclusions were aimed at contributing to the objective evaluation of road traffic safety levels in different provinces and providing a basis for the formulation of reasonable macro traffic safety planning and management decisions. The findings offer valuable insights that can be used to optimize regional traffic safety policies and strategies, thereby enhancing road safety.

Suggested Citation

  • Keke Zhang & Shaohua Wang & Chengcheng Song & Sinan Zhang & Xia Liu, 2024. "Spatiotemporal Heterogeneity Analysis of Provincial Road Traffic Accidents and Its Influencing Factors in China," Sustainability, MDPI, vol. 16(17), pages 1-17, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:17:p:7348-:d:1464508
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    References listed on IDEAS

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    1. Matteo Picchio & Michele Ubaldi, 2024. "Unemployment and health: A meta‐analysis," Journal of Economic Surveys, Wiley Blackwell, vol. 38(4), pages 1437-1472, September.
    2. Taruwere Yakubu, Ahmed & Aremu Muhammed, Ismail, 2021. "Economic Condition And Road Transport Crashes In Nigeria: Evidence From State Level Data," Ilorin Journal of Economic Policy, Department of Economics, University of Ilorin, vol. 8(2), pages 36-44, June.
    3. Huang, Yuan & Wang, Xiaoguang & Patton, David, 2018. "Examining spatial relationships between crashes and the built environment: A geographically weighted regression approach," Journal of Transport Geography, Elsevier, vol. 69(C), pages 221-233.
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