Browsing by Subject "injury severity modeling"
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Item The Joint Analysis of Injury Severity of Drivers in Two-Vehicle Crashes Accommodating Seat Belt Use Endogeneity(Elsevier, 2013) Abay, Kibrom A.; Paleti, Rajesh; Bhat, Chandra R.The current study contributes to the existing injury severity modeling literature by developing a multivariate probit model of injury severity and seat belt use decisions of both drivers involved in two-vehicle crashes. The modeling approach enables the joint modeling of the injury severity of multiple individuals involved in a crash, while also recognizing the endogeneity of seat belt use in predicting injury severity levels as well as accommodating unobserved heterogeneity in the effects of variables. The proposed model is applied to analyze the injury severity of drivers involved in two-vehicle road crashes in Denmark. The empirical analysis provides strong support for the notion that people offset the restraint benefits of seat belt use by driving more aggressively. Also, men and those individuals driving heavy vehicles have a lower injury risk than women and those driving lighter vehicles, respectively. At the same time, men and individuals driving heavy vehicles pose more of a danger to other drivers on the roadway when involved in a crash. Other important determinants of injury severity include speed limit on roadways where crash occurs, the presence (or absence) of center dividers (median barriers), and whether the crash involves a head-on collision. These and other results are discussed, along with implications for countermeasures to reduce injury severities in crashes. The analysis also underscores the importance of considering injury severity at a crash level, while accommodating seat belt endogeneity effects and unobserved heterogeneity effects.Item Modeling Injury Severity of Multiple Occupants of Vehicles: Copula-Based Multivariate Approach(National Academy of Sciences, 2010) Eluru, Naveen; Paleti, Rajesh; Pendyala, Ram M.; Bhat, Chandra R.Previous research in crash injury severity analysis has largely focused on level of injury severity sustained by the driver of the vehicle or the most severely injured occupant of the vehicle. While such studies are undoubtedly useful, they do not provide a comprehensive picture of the injury profile of all vehicular occupants in crash-involved vehicles. This limits the ability to devise safety measures that enhance the safety and reduce the injury severity associated with all vehicular occupants. Moreover, such studies ignore the possible presence of correlated unobserved factors that may simultaneously influence and impact the injury severity levels of multiple occupants in the vehicle.This paper aims to fill this gap by presenting a simultaneous model of injury severity that can be applied to crashes involving any number of occupants. A copula-based methodology, that can be effectively used to estimate such complex model systems, is presented and applied to a data set of crashes drawn from the 2007 GeneralEstimates System (GES) in the United States.The model estimation results provide strong evidence of the presence of correlated unobserved factors that affect injury severity levels among vehicle occupants. The correlation exhibits heterogeneity across vehicle types with greater level of inter-occupant dependency in heavier sport utility vehicles and pickup trucks.The study also sheds light on how numerous exogenous factors including occupant characteristics, vehicle characteristics, environmental factors, roadway attributes, and crash characteristics affect injury severity levels of occupants in different seat positions. The findings confirm that rear seat passengers are less vulnerable to severe injuries than front row passengers pointing to the need to enhance vehicular design features that promote front row occupant safety.