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A new zone system to analyze the spatial relationships between the built environment and traffic safety

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  • Obelheiro, Marta Rodrigues
  • da Silva, Alan Ricardo
  • Nodari, Christine Tessele
  • Cybis, Helena Beatriz Bettella
  • Lindau, Luis Antonio

Abstract

This study aims to investigate the impacts of the built environment on traffic safety at a zonal level using a newly developed crash-related zone system. Traffic analysis zones (TAZs) have been widely employed to analyze traffic safety at a macroscopic level. However, this zone system use may present problems. Unlike previous studies, in which new zoning systems were created from aggregating TAZs, in this study the new zone system, formed by traffic safety analysis zones (TSAZs), is created from the smallest available census units. Geographically Weighted Negative Binomial Regression (GWNBR) models are used and a comparative analysis between non-spatial global crash prediction models and spatial local GWPR (Geographically Weighted Poisson Regression) and GWNBR models using the two zonal systems is presented. We find that TSAZs based models performed better than TAZs based models, especially when combined to the GWNBR technique. Our results show that several features of the built environment are significant crash predictors, and that the relationships among these features and traffic safety vary across space. By combining a crash-related zonal system with spatial GWNBR models to understand the built environment effects on traffic safety, the results of the analysis can help urban planners to consider traffic safety proactively when planning or retrofitting urban areas.

Suggested Citation

  • Obelheiro, Marta Rodrigues & da Silva, Alan Ricardo & Nodari, Christine Tessele & Cybis, Helena Beatriz Bettella & Lindau, Luis Antonio, 2020. "A new zone system to analyze the spatial relationships between the built environment and traffic safety," Journal of Transport Geography, Elsevier, vol. 84(C).
    • Handle: RePEc:eee:jotrge:v:84:y:2020:i:c:s096669231930225x
    DOI: 10.1016/j.jtrangeo.2020.102699
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    References listed on IDEAS

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    1. Chandra, Aitichya & Sharath, M.N. & Pani, Agnivesh & Sahu, Prasanta K., 2021. "A multi-objective genetic algorithm approach to design optimal zoning systems for freight transportation planning," Journal of Transport Geography, Elsevier, vol. 92(C).

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