An analysis of injury severities of large-truck crashes.

详细信息   

• 作者：Zhu ; Xiaoyu.
• 学历：Doctor
• 年：2011
• 导师：Srinivasan, Sivaramakrishnan,eadvisor
• 毕业院校：University of Florida
• ISBN：9781124796116
• CBH：3467659
• Country：USA
• 语种：English
• FileSize：4128909
• Pages：142

文摘

Traffic crashes have become one of the largest public health problems in the world and will be one of the most concerned transportation issues in the future. The importance of trucking to freight logistics and, consequently, its impact on the economic well being of a nation is well acknowledged. There is a need for studying crashes towards improving the safety of the transportation system, educating driver behavior, enhancing carrier operation and incident cost reduction. Data from the Large Truck Crash Causation Study LTCCS) is used in the empirical analysis. The goal to develop econometric models of injury-severity in large-truck crashes is accomplished in a three-step procedure. The first step of this dissertation contributes towards that end by undertaking the relationship between injury severity and a vast number of inter-dependent explanatory factors using a crash level sample. The injury severity is modeled using both police-reported and researcher-determined scales. The results indicate the strong impacts of several Crash-, Truck, and Car-level variables on the severity of the crashes. Then we proceed to the occupant level study in the second step because the highest injury severity cannot fully represent the severity of the whole crash. The methodology of incorporating the effects of common unobserved factors error correlations) affecting the injury-severity of all persons involved in the same vehicle and crash is developed. Both the intra-crash and intra-vehicle correlations are confirmed to be important in the second step. A more advanced and flexible structure of methodology is explored in the last step. This approach is attractive as it recognizes the ordered nature of the choice alternatives and, at the same time, it is not constrained by the "proportional odds" or "parallel line" restrictions of the ordered probit. The results indicate that the variables which are not significant in ordered probit model may have impact on the injury severity. For different roles truck occupant, car driver and car passenger), the significant driver behavior variables are also different. In summary, the advanced and flexible methodologies for occupant level injury severity study are developed and compared in this dissertation. The results and implications are useful from the standpoints of traveler, transportation engineer and policy maker.