Factors influencing pedestrian injury severity in Chile : A hierarchical probit ordered model approach

Abstract

Introduction: Traffic crashes remain a leading cause of fatalities worldwide, with higher fatality and injury rates in non-developed countries. Understanding the relationship among variables influencing traffic crashes and its outcome, measured as crash severity, is crucial for developing effective and targeted countermeasures to mitigate this problem. Method: In this study, we analyze traffic crashes involving pedestrians in Chile from 2022 to 2023. This allowed us to consider the entire country rather than a specific urban area, which is the first of its kind for a Latin American country. A Hierarchical Ordered Probit (HOPIT) model was estimated to model both risk propensity and severity of pedestrian and vehicle crashes while maintaining an ordered threshold structure. Findings reveal that pedestrian and driver characteristics significantly influence crash severity. Results: Male drivers have a higher probability of being involved in more severe crashes. Meanwhile, older pedestrians present a higher risk of severe and fatal injuries. Crash severity is significantly influenced by variables related to vehicle type and environmental factors. Pedestrians hit by heavy-duty vehicles have a 60% and 30% higher chance of suffering fatal or severe injuries, respectively. Highways exhibit a 421% higher chance of fatal injuries, followed by crashes at night and crashes in rural areas with 380% and 267%, respectively. Practical Applications: This research indicates the need for targeted safety measures addressing pedestrian and driver demographics and behavior, vehicle types, and environmental factors to effectively reduce pedestrian injury severity.