Analysis of injury severity of large truck crashes in work zones |
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| Affiliation: | 1. Department of Civil Engineering, University of Memphis, 3815 Central Avenue, Memphis, TN, 38152, United States;2. Department of Civil & Environmental Engineering, Old Dominion University, 135 Kaufman Hall, Norfolk, VA, 23529, United States;3. Intermodal Freight Transportation Institute, University of Memphis, Memphis, TN, 38152, United States;1. College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China;2. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China;3. Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, Southeast University, Nanjing 210096, China;1. Department of Civil Engineering, University of South Alabama, 150 Jaguar Drive, Shelby Hall, Suite 3142, Mobile, AL 36688, United States;2. Department of Civil, Construction & Environmental Engineering, University of Alabama, Box 870205, Tuscaloosa, AL 35487, United States;1. College of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China;2. MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China;3. Chongqing Key Lab of Traffic System & Safety in Mountain Cities, Chongqing Jiaotong University, Chongqing 400074, China;4. Australian Institute of Psychology, Level 2,140 Brunswick Street, Fortitude Valley, Queensland 4006, Australia;5. Griffith School of Engineering, Griffith University, Gold Coast, 4222 Queensland, Australia |
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| Abstract: | Work zones are critical parts of the transportation infrastructure renewal process consisting of rehabilitation of roadways, maintenance, and utility work. Given the specific nature of a work zone (complex arrangements of traffic control devices and signs, narrow lanes, duration) a number of crashes occur with varying severities involving different vehicle sizes. In this paper we attempt to investigate the causal factors contributing to injury severity of large truck crashes in work zones. Considering the discrete nature of injury severity categories, a number of comparable econometric models were developed including multinomial logit (MNL), nested logit (NL), ordered logit (ORL), and generalized ordered logit (GORL) models. The MNL and NL models belong to the class of unordered discrete choice models and do not recognize the intrinsic ordinal nature of the injury severity data. The ORL and GORL models, on the other hand, belong to the ordered response framework that was specifically developed for handling ordinal dependent variables. Past literature did not find conclusive evidence in support of either framework. This study compared these alternate modeling frameworks for analyzing injury severity of crashes involving large trucks in work zones. The model estimation was undertaken by compiling a database of crashes that (1) involved large trucks and (2) occurred in work zones in the past 10 years in Minnesota. Empirical findings indicate that the GORL model provided superior data fit as compared to all the other models. Also, elasticity analysis was undertaken to quantify the magnitude of impact of different factors on work zone safety and the results of this analysis suggest the factors that increase the risk propensity of sustaining severe crashes in a work zone include crashes in the daytime, no control of access, higher speed limits, and crashes occurring on rural principal arterials. |
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| Keywords: | Large truck Work zones Injury severity Multinomial logit Ordered logit Generalized ordered logit |
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