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Abstract
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Introduction
It is important to understand the relationship between the built environment and pedestrian safety to promote walking. Nevertheless, current literature insufficiently studied the impact of the built environment on pedestrian safety. There is few research considering spatial autocorrelation effects. This study aims to expand the investigation of conventional built environment correlates of pedestrian safety using the D variables from the walkability literature to further the discussions of the association of the built environment with both safety and walkability.
Methods
Data on pedestrian involved injuries were collected from the New York State Department of Transportation from 2012-2016. The results from the global Poisson regression (PR) models and the geographically weighted Poisson regression (GWPR) models were compared to show the spatially varying effects of built environment characteristics on pedestrian involved injuries. Data were analyzed in 2019.
Results
The results from the GWPR models were more pronounced than the global PR models. The findings confirmed the association of pedestrian safety with the D variables. The number of intersections, Walk Score, and population density showed conflicting impacts on safety and walkability. The statistically significant association of Walk Score with pedestrian safety in the study enriches current research on the relationship between built environment and pedestrian safety.
Conclusions
This study expanded the traditional built environment variables used in pedestrian safety research with the D variables in walkability research to help understand the role of built environment characteristics for building walkable and safe neighborhoods. The findings also shed light on the significance of distance in environmental modification for safe and walkable communities.
Language: en |