Exploring differences in injury severity between occupant groups
involved in fatal rear-end crashes: A correlated random parameter logit model
with mean heterogeneity
Rear-end crashes are one of the most common crash types. Passenger cars
involved in rear-end crashes frequently produce severe outcomes. However, no
study investigated the differences in the injury severity of occupant groups
when cars are involved as following and leading vehicles in rear-end crashes.
Therefore, the focus of this investigation is to compare the key factors
affecting the injury severity between the front- and rear-car occupant groups
in rear-end crashes. First, data is extracted from the Fatality Analysis
Reporting System (FARS) for two types of rear-end crashes from 2017 to 2019,
including passenger cars as rear-end and rear-ended vehicles. Significant
injury severity difference between front- and rear-car occupant groups is found
by conducting likelihood ratio test. Moreover, the front- and rear-car occupant
groups are modelled by the correlated random parameter logit model with
heterogeneity in means (CRPLHM) and the random parameter logit model with
heterogeneity in means (RPLHM), respectively. From the modeling, the
significant factors are occupant positions, driver age, overturn, vehicle type,
etc. For instance, the driving and front-right positions significantly increase
the probability of severe injury when struck by another vehicle. Large
truck-strike-car tends to cause severe outcomes compared to car-strike-large
truck. This study provides an insightful knowledge of mechanism of occupant
injury severity in rear-end crashes, and propose some effective countermeasures
to mitigate the crash severity, such as implementing stricter seat belt laws,
improving the coverage of the streetlights, strengthening car driver's
emergency response ability