Scholar: Mahyar Madarshahian
When: December 12th, 2025, 9:00 AM – 10:30 AM
ZOOM: https://unl.zoom.us/j/97206892522
Title: A Comprehensive Study of Crash Severity and Its Contributing Factors
Abstract: This dissertation presents a comprehensive analysis of factors influencing crash injury severity across diverse road and work zone environments. Using advanced statistical modeling techniques, it examines crash outcomes in four critical contexts: general road crashes, work zone crashes, truck-involved crashes, and high-speed rear-end collisions. A mixed logit modeling framework with random parameters, incorporating heterogeneity in parameter means and variances, is employed to capture unobserved heterogeneity in crash data. The analyses are further refined through targeted segmentation by speed regime, work zone type, and crash type to identify context-specific risk factors. In addition, a fuzzy cluster analysis is utilized to discern complex patterns in truck crash severity between urban and rural roads.
The integrated findings identify key risk factors that consistently exacerbate injury severity, while also revealing how their impacts differ across environments. For example, certain factors exert heightened effects in work zones or high-speed rear-end scenarios but are less pronounced in general road crashes. By comparing these varied scenarios, the research highlights that crash severity determinants are context-dependent, underscoring the importance of tailored safety strategies. The research also evaluates a specific intervention, increased law enforcement presence in work zones, and finds that enhanced enforcement significantly reduces vehicle speeds and improves driver compliance, supporting its role as an effective countermeasure.
Major contributions of this dissertation include a deeper understanding of critical crash severity determinants, evidence of differential effects of these factors across road conditions, and an assessment of an enforcement intervention’s benefits. These insights carry important practical implications: they can directly inform the design and management of safer work zones, guide the implementation of targeted enforcement strategies such as dedicated patrols or improved speed control in high-risk areas, and shape data-driven highway safety policies aimed at reducing the incidence of severe crashes.