Day-of-the-week variations and temporal instability of factors influencing pedestrian injury severity in pedestrian-vehicle crashes: A random parameters logit approach with heterogeneity in means and variances

Abstract

Using pedestrian-vehicle crash data in North Carolina from 2007 to 2018, this study explores the potential variation in the influence of factors affecting pedestrian injury severity in different time periods (weekday/weekend and three-year period). To capture unobserved heterogeneity, random parameters logit models with heterogeneity in means and variances are employed. In developing the model, several categories of factors are considered, including characteristics of the pedestrian, driver, crash, locality and roadway, time and environment, traffic control, and work zone. Transferability tests are conducted to examine the possible temporal instability of the estimation results between different time periods. According to the results, factors such as “ambulance rescue” and “curved roadway” produce temporally stable effects on pedestrian injury severity. However, strong temporal instabilities in effects on pedestrian injury severity are found for most factors across the three-year period and the weekday/weekend. In regard to structure, the model offers more insights by accounting for possible heterogeneity in the means and variances of the random parameters. Detailed policy-related recommendations are provided based on the analysis results. The findings of this work should be helpful to policymakers in future planning on safety improvements for pedestrians within the transportation system.