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contributor authorRong Zou
contributor authorHao Yu
contributor authorHanyi Yang
contributor authorCong Chen
contributor authorGuohui Zhang
date accessioned2024-04-27T22:32:02Z
date available2024-04-27T22:32:02Z
date issued2024/02/01
identifier other10.1061-JTEPBS.TEENG-7708.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4296877
description abstractThis study employs the mixed logit model to examine the statistically significant risk factors in influencing driver injury severity in four crash configurations in two-vehicle rear-end crashes on urban state roads based on seven-year data from the Washington State Department of Transportation. The data set only includes collisions with passenger cars and pickup trucks involved, as these two vehicle types are the most common in these crashes, and these two types typically have different masses and kinetic features. Four crash configurations are examined concerning the type of vehicles and their relative positions in a crash. Four models for these configurations and one model for the overall data set are estimated. The result shows discrepancies and similarities in risk factors for injury and fatality in different crash configurations, and each model has its unique parameters with heterogeneity of different distributions. Contributing factors to driver fatality include (1) alcohol-impaired drivers and older drivers when a passenger car strikes another passenger car, (2) curved and not level roads, and the vehicle in front when a passenger car is stricken by a pickup truck, (3) male drivers and being in winter season when a pickup truck is stricken by a passenger car, and (4) seatbelts not being in use for all configurations. Research findings in this work help understand the risk factors for driver injury severity in each configuration and develop injury and fatality prevention strategies for two-vehicle rear-end crashes involving passenger cars and pickup trucks.
publisherASCE
titleSeverity Analyses of Urban Two-Vehicle-Involved Rear-End Crashes Characterized by Different Configurations Using Mixed Logit Models
typeJournal Article
journal volume150
journal issue2
journal titleJournal of Transportation Engineering, Part A: Systems
identifier doi10.1061/JTEPBS.TEENG-7708
journal fristpage04023141-1
journal lastpage04023141-11
page11
treeJournal of Transportation Engineering, Part A: Systems:;2024:;Volume ( 150 ):;issue: 002
contenttypeFulltext


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