The urban built environment is closely related to the occurrence of traffic accidents. Accurately identifying the spatial heterogeneity characteristics of factors affecting traffic accidents is of great significance for accurate traffic safety management and control. In this study, 2,114 Traffic Analysis Zones (TAZ) in Tianjin, China were used as the research units, 25,869 road traffic accident data were collected as the dependent variable, and 12 built environment density data such as roads and Point of Interest (POI) were extracted as independent variables. After confirming the spatial dependence of the data based on the spatial autocorrelation test, three spatial econometric models of Ordinary Least Squares (OLS), Geographically Weighted Regression (GWR), and Multiscale Geographically Weighted Regression (MGWR) are constructed for optimization analysis. The research results show that MGWR is the optimal model to describe the spatial heterogeneity of traffic accidents in different built environment factors. There is a negative correlation between recreational density and intersection density with traffic accidents, while other influencing factors show a positive correlation. The regression coefficient for retail industry density is significantly higher than other influencing factors, while the regression coefficient for leisure and entertainment density is significantly lower than other influencing factors.


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    Titel :

    The Influence of Urban Built Environment on the Spatial Heterogeneity of Road Traffic Accidents


    Untertitel :

    ——Taking Tianjin, China as an example


    Weitere Titelangaben:

    Advances in Engineering res


    Beteiligte:
    Chen, Gongfa (Herausgeber:in) / Guo, Baohua (Herausgeber:in) / Chen, Yan (Herausgeber:in) / Guo, Jingwei (Herausgeber:in) / Zhang, Keke (Autor:in) / Kong, Chao (Autor:in) / Qin, Wenhui (Autor:in) / Yan, Hubin (Autor:in) / Wang, Shaohua (Autor:in)

    Kongress:

    International Conference on Rail Transit and Transportation ; 2024 ; Jiaozuo, China October 10, 2024 - October 12, 2024



    Erscheinungsdatum :

    15.12.2024


    Format / Umfang :

    9 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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