Cost of travel delays caused by traffic crashes

Abstract

This study proposes a method for measuring travel delays caused by traffic crashes based on taxi GPS data and other open-source spatial data. Travel delays caused by traffic crashes are quantified according to the difference between the post-crash and typical travel speeds on affected road segments. Based on multiple sources of data in Hong Kong, we also develop a generalized linear model with explanatory variables including crash characteristics, temporal attributes, road network features, traffic indicators, and built environment features, to unveil the relationship between travel delays and these factors. The findings show that crash characteristics alone inadequately explain variations in delays. The model performance improves after factors about the built environment and the dynamic road conditions are incorporated. This underscores the importance of urban factors in traffic delay analysis. Furthermore, we estimate the total travel delays caused by traffic crashes in the city. It is estimated that Hong Kong has suffered from a total delay of 713,877 vehicle-hours in 2021. The associated economic loss amounts to US$11.02 million. This study contributes to methodological advances in estimating crash-induced travel delays. The explanatory model considers factors which help policy makers and planners to identify risky factors and hot spots for devising more targeted and effective strategies of shortening crash-induced traffic congestion in the future. In addition, the findings highlight the significance and magnitude of another negative externality of traffic crashes – traffic delays – in a complex urban road network.

Keywords

• Travel delays
• Road crashes
• Road safety
• GPS data