Modeling Road Safety in Car-Dependent Cities: Case of Jeddah City, Saudi Arabia

Abstract

Investigating the connections between pedestrian crashes and various urban variables is critical to ameliorate the prediction of pedestrian fatalities, formulate advisories for the stakeholders, and provide an evidence base for policy change to mitigate the occurrence and intensity of pedestrian fatalities. In this paper, we aim to explore the geographically varying association between the pedestrian fatalities and other associated factors of an urban environment in Jeddah city, which is a car-dependent city in Saudi Arabia. At first, Global Moran’s I and Local Indicators of Spatial Association (LISA) were applied to visualize the clustering of pedestrian fatalities in the various districts of Jeddah. Subsequently, we developed Poisson regression models based on their geographically weighted indicators. Both the global and geographically weighted regression models attempt to assess the association between the pedestrian fatalities and the geographically relevant land use and transport infrastructure factors. The results indicate that geographically weighted Poisson regression (GWPR) performed better than the global Poisson counterparts. It is also revealed that the existing transportation infrastructure in Jeddah was significantly associated with the higher pedestrian fatalities. The results have shown that the proposed model in this study can inform transport policies in Jeddah in prioritizing more safety measures for the pedestrians, including expanding pedestrians’ infrastructure, and cautious monitoring of pedestrian footpaths. It can facilitate the analysis and improvement of road safety for pedestrians in car-dependent cities.

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