Bivariate ordered-response probit model of driver’s and passenger’s injury severities in collisions with fixed objects
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 rec...
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| Veröffentlicht in: | Accident analysis and prevention 2004-09, Vol.36 (5), p.869-876 |
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| creator | Yamamoto, Toshiyuki Shankar, Venkataraman N. |
| description | 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. |
| doi_str_mv | 10.1016/j.aap.2003.09.002 |
| format | Article |
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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. 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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. 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| identifier | ISSN: 0001-4575 |
| ispartof | Accident analysis and prevention, 2004-09, Vol.36 (5), p.869-876 |
| issn | 0001-4575 1879-2057 |
| language | eng |
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| source | MEDLINE; Elsevier ScienceDirect Journals |
| subjects | Accidents, Traffic - statistics & numerical data Bivariate ordered-response probit model Fixed object Humans Injury severity Models, Statistical Risk Factors Single-vehicle accident Washington Wounds and Injuries - epidemiology |
| title | Bivariate ordered-response probit model of driver’s and passenger’s injury severities in collisions with fixed objects |
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