A bivariate ordered-response probit model of driver's and most severely injured passenger's severity (IS) in collisions with fixed objects is developed in this study. Exact passenger's IS is not necessarily observed, especially when only most severe injury of the accident and driver's injury are recorded in the police reports. To accommodate passenger IS as well, we explicitly develop a partial observability model of passenger IS in multi-occupant vehicle (HOV). The model has consistent coefficients for the driver IS between single-occupant vehicle (SOV) and multiple-occupant vehicle accidents, and provides more efficient coefficient estimates by taking into account the common unobserved factors between driver and passenger IS. The results of the empirical analysis using 4-year statewide accident data in Washington State reveal the effects of driver's characteristics, vehicle attributes, types of objects, and environmental conditions on both driver and passenger IS, and that their IS have different elasticities to some of the risk factors.
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Contributory fault and level of personal injury to drivers involved in head-on collisions: Application of copula-based bivariate ordinal models.
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Department of Civil & Environmental Engineering, The University of Tennessee, United States; School of Transportation, Wuhan University of Technology, China. Electronic address:
The main objective of this study is to simultaneously investigate the degree of injury severity sustained by drivers involved in head-on collisions with respect to fault status designation. This is complicated to answer due to many issues, one of which is the potential presence of correlation between injury outcomes of drivers involved in the same head-on collision. To address this concern, we present seemingly unrelated bivariate ordered response models by analyzing the joint injury severity probability distribution of at-fault and not-at-fault drivers.
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Department of Civil Engineering, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8603, Japan.
A bivariate ordered-response probit model of driver's and most severely injured passenger's severity (IS) in collisions with fixed objects is developed in this study. Exact passenger's IS is not necessarily observed, especially when only most severe injury of the accident and driver's injury are recorded in the police reports. To accommodate passenger IS as well, we explicitly develop a partial observability model of passenger IS in multi-occupant vehicle (HOV).
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