Truck-involved crash severity in Thailand: a multilevel perspective on driver behavior and contextual influences

Abstract

Truck-involved crashes in Thailand frequently lead to severe consequences due to the vehicles’ large size, heavy loads, and high-speed operations. Despite growing concerns, most previous studies have used single-level models that overlook the hierarchical structure of crash data and fail to account for spatial and contextual variations across regions. This study applies a Multilevel Ordered Logit Model to examine factors influencing truck crash severity by integrating individual-level variables (e.g., driver behavior, vehicle condition, environmental factors) with province-level contextual factors (e.g., population size, AADT, Highway length). The model captures both direct effects and cross-level interactions to assess how regional characteristics shape the relationship between individual risk factors and crash severity. The results reveal substantial provincial variation and demonstrate that contextual factors significantly moderate the impact of driver behavior on crash outcomes. These findings emphasize the importance of adopting multilevel analytical frameworks in road safety research, especially in developing countries. The study contributes to a more comprehensive understanding of truck-related crash mechanisms and provides practical insights for designing targeted, context-sensitive safety policies that align with the unique characteristics of each province.