Heterogeneous impacts of road characteristics on the severity of taxi-involved crashes: Practical insights for safety improvement

Taxi traffic safety arises from the complex interplay among road infrastructure, driver behavior, vehicle characteristics, and environmental conditions. However, driver, vehicle, and environmental factors are typically challenging to regulate directly through policy or design, whereas road characteristics can be systematically adjusted through infrastructure planning and traffic management strategies. Therefore, understanding how specific road features contribute to crash risk offers a more practical and sustainable pathway for enhancing taxi travel safety. This study aims at investigating how road characteristics heterogeneously influence the severity of taxi-involved crashes. To accomplish this, a latent class clustering method is first leveraged to classify crashes with similar contextual features. Subsequently, a partial proportional odds model is applied to quantify the class-specific impacts of road characteristics on taxi-involved crash severity. The taxi crash data reported by the London police from January 2019 to June 2024 are utilized to achieve this study. The results demonstrate substantial heterogeneity in how road characteristics affect taxi-involved crash outcomes across different crash classes. Among the examined factors on taxi-involved crashes, speed limits and junction controls exert the most pronounced influences. Higher speed limits (≥40 mph) substantially elevate the probabilities of serious injuries (+14.76%) and fatalities (+0.93%). In contrast, moderate speed limits (31-40 mph) are associated with notably lower marginal effects on serious injuries (+8.27%) and fatalities (+0.46%). The installation of traffic signals at junctions decreases the likelihood of serious injuries (-11.68%) and fatalities (-0.50%). These findings indicate that uniform safety policies may be insufficient for mitigating class-specific taxi risks. This study contributes empirical evidence and practical insights for road safety management. By identifying the heterogeneous influence patterns of road characteristics, the findings support targeted infrastructure design, speed management, and signal control strategies to effectively reduce both the frequency and severity of taxi-related crashes.