Modeling of motorcyclist injury severities: A comparison between crashes on main-, frontage-, and standard-lane of roadway

Abstract

This study aims to examine the differentiated impacts of frontage-lane, main-lane, and standard-lane motorcycle collisions on rider injury severity in Thailand. Using comprehensive crash data from 2016 to 2019, a random parameters model accommodating heterogeneity in means and variances is applied. Predictive comparisons between out-of-sample and within-sample predictions uncover differences between collision location sub-models. For frontage-lane collisions, severe or fatal injuries are positively associated with male riders, truck involvement, and speeding. In main-lane collisions, increased severe/fatal injury risk is associated with nighttime, holidays, weekends, single-motorcycle crashes, and collisions with trucks or pickups. In standard-lane collisions, positive severe/fatal injury associations include male riders, nighttime, non-peak hours, speeding, truck/pickup involvement, and pillion presence. Predictive comparisons show reorienting crashes to the frontage lane could reduce fatal injury probability by 0.1199 and 0.2233 versus the main and standard lanes respectively, preventing many fatalities. This research underscores accounting for unobserved heterogeneity and predictive simulation insights. The findings inform effective countermeasures and aid safety professionals, instructors, policymakers, law enforcement, and designers in motorcycle safety efforts.

Keywords

• Motorcycle safety
• Roadway types
• Injury severity
• Random parameters
• Means and variance heterogeneity
• Out-of-sample prediction