A zonal level safety investigation of pedestrian crashes in Riyadh, Saudi Arabia

Abstract

In the recent decade, walking has been encouraged as an active mode of transportation, which could reduce congestion and air pollution and also improve community health. However, pedestrians are more vulnerable to traffic crashes compared with other road users, especially in developing countries such as Saudi Arabia. This paper examines the association among traffic volume, land-use, socio-demographic and roadway characteristics factors, and the frequency of pedestrian crashes based on macro-level safety analysis using data from Riyadh, the Capital of Saudi Arabia. Two Bayesian spatial Poisson-lognormal models for total and severe pedestrian crashes are developed in this study. The results show that the factors that affect total pedestrian crash occurrence are different from those affecting severe pedestrian crash. Several implications for pedestrian safety policies in Riyadh are suggested based on the results.

Keywords:

• Bayesian models
• CAR
• conditional autoregressive
• developing countries
• GIS
• macro-level analysis
• pedestrian safety
• Poisson lognormal

Acknowledgments

The authors wish to thank the High Commission for the Development of Riyadh (HCDR) for providing the data.