HighlightsThis study aimed to investigate the effects of jobs-housing balance on traffic safety.S-GWR links crash frequency at traffic analysis zone (TAZ) with jobs-housing ratio and other factors.S-GWR provides better fitness than the generalized linear model.Jobs-housing ratio affects traffic safety at TAZ when other contributing factors are controlled.Interactive effects exist between jobs-housing ratio and other contributing factors.

    AbstractThis study aimed to investigate the effects of jobs-housing balance on traffic safety. The crash, demographic characteristics, employment, road network, household characteristics and traffic data were collected from the Los Angeles in 2010. One-way ANOVA tests indicated that the jobs-housing ratio significantly affects traffic safety in terms of crash frequency at traffic analysis zone (TAZ). To quantify the safety impacts of jobs-housing balance, the semi-parametric geographically weighted Poisson regression (S-GWPR) was further used to link crash frequency at TAZ with jobs-housing ratio and other contributing factors. The S-GWPR provides better fitness to the data than do the generalized linear regression, as the S-GWPR accounts for the spatial heterogeneity. The S-GWPR results showed that the jobs-housing relationship has a significant association with crash frequency at TAZ when the factors of traffic, network, and household characteristics are controlled. Crash frequency at TAZ level increases with an increase in the jobs-housing ratio. To further investigate the interactive effects between jobs-housing ratio and other factors, a comparative analysis was conducted to compare the variable elasticities under different jobs-housing ratios. The results indicate considerable interactive effects that traffic conditions and road network characteristics have different effects on crash frequency under various jobs-housing ratios.


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    Titel :

    Investigating the relationship between jobs-housing balance and traffic safety


    Beteiligte:
    Xu, Chengcheng (Autor:in) / Li, Haojie (Autor:in) / Zhao, Jingya (Autor:in) / Chen, Jun (Autor:in) / Wang, Wei (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2017-08-07


    Format / Umfang :

    11 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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