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Rear-end crashes are one of the most common crash types. Passenger carsinvolved in rear-end crashes frequently produce severe outcomes. However, nostudy investigated the differences in the injury severity of occupant groupswhen cars are involved as following and leading vehicles in rear-end crashes.Therefore, the focus of this investigation is to compare the key factorsaffecting the injury severity between the front- and rear-car occupant groupsin rear-end crashes. First, data is extracted from the Fatality AnalysisReporting System (FARS) for two types of rear-end crashes from 2017 to 2019,including passenger cars as rear-end and rear-ended vehicles. Significantinjury severity difference between front- and rear-car occupant groups is foundby conducting likelihood ratio test. Moreover, the front- and rear-car occupantgroups are modelled by the correlated random parameter logit model withheterogeneity in means (CRPLHM) and the random parameter logit model withheterogeneity in means (RPLHM), respectively. From the modeling, thesignificant factors are occupant positions, driver age, overturn, vehicle type,etc. For instance, the driving and front-right positions significantly increasethe probability of severe injury when struck by another vehicle. Largetruck-strike-car tends to cause severe outcomes compared to car-strike-largetruck. This study provides an insightful knowledge of mechanism of occupantinjury severity in rear-end crashes, and propose some effective countermeasuresto mitigate the crash severity, such as implementing stricter seat belt laws,improving the coverage of the streetlights, strengthening car driver'semergency response ability.

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Exploring differences in injury severity between occupant groups  involved in fatal rear-end crashes: A correlated random parameter logit model  with mean heterogeneity