The urban expressway system plays an important role in the metropolitan transportation system. However, frequent crash occurrences have significantly influence the traffic operation and travel reliability. It is vital to understand the crash occurrence mechanisms and further improve traffic safety. Statistical models such as logistic models have been conducted to unveil the crash contributing factors. However, crash occurrence is concluded to be a result of complex interactions between various contributing factors, with the only correlation effects are not sufficient to explain crash occurrence mechanisms. Thus, in this study, we aim at analyzing the confounding impacts of the multi-crash contributing factors and their causal relationships with crash occurrence through a Structure Equation Model (SEM). Potential crash contributing factors were firstly extracted from the Shanghai urban expressway system data. Then, two Confirmatory Factor Analysis (CFA) models were performed and two latent variables were obtained through well fitted CFA analyses: Geometry complexity latent variable and traffic flow complexity latent variable. Finally, different structures of SEM were established and the best model structure was identified. The model contains two latent variables derived from CFAs, two observed variables including average speed and standard deviation of speed, and one crash occurrence indicator. The modelling results indicate that the geometry complexity negatively and traffic flow complexity positively influences the standard deviation of speed; Standard deviation of speed negatively affects the average speed; both average speed and traffic flow complexity have the positive effects on the crash occurrence. Furthermore, analyses of crash occurrence mechanism based on the modelling results were proposed at the end of this paper.


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    Title :

    Utilizing Structure Equation Model to Analyze Multi-Crash Contributing Factors for Shanghai Urban Expressway System


    Contributors:
    Yu, Rongjie (author) / Wang, Yiyun (author) / Zheng, Yin (author)


    Publication date :

    2019-07-01


    Size :

    302278 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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