Analyzing the Injury Severity in Overturn Crashes Involving Sport Utility Vehicles: Latent Class Clustering and Random Parameter Logit Model
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 149, Issue 3
Abstract
The fatal or incapacitating injury caused by overturn crashes involving sport utility vehicles (SUVs) is irreparable. The purpose of this study is to identify potential factors that affect the injury severity of overturn crashes involving SUVs and develop adequate preventive strategies. Given the unobserved heterogeneity existing in the data set, crash data in North Carolina from Highway Safety Information System (HSIS) is analyzed and separated by Latent Class Clustering into six relatively homogeneous groups. To further explore the heterogeneity, random parameter logit models are developed for each cluster, and the impacts of significant factors are estimated with marginal effects. The results reveal the heterogeneity across the clusters and the homogeneity within the same cluster. Variables (including females, people over fifty years old, improper or aggressive behavior, rural areas, high-speed limit, curved roadway, rolling and mountainous terrain, adverse weather, and poor light conditions) are associated with the injury severity of the overturn crashes involving SUVs. The findings of this study can further provide decision makers with insightful countermeasures to improve transportation safety and mitigate the injuries of overturn crashes involving SUVs.
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Data Availability Statement
Some or all data, models, or code used during the study were provided by a third party. Direct requests for these materials may be made to the provider as indicated in the Acknowledgments.
Acknowledgments
The authors want to express their deepest gratitude to the financial support by the United States Department of Transportation, University Transportation Center through the Center for Advanced Multimodal Mobility Solutions and Education at The University of North Carolina at Charlotte (Grant No. 69A3551747133). The authors would also like to thank US Department of Transportation, Federal Highway Administration, and Highway Safety Information System for providing the data used in this research study.
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Published In
Journal of Transportation Engineering, Part A: Systems
Volume 149 • Issue 3 • March 2023
Copyright
© 2022 Published by American Society of Civil Engineers.
History
Received: Mar 3, 2022
Accepted: Oct 31, 2022
Published online: Dec 19, 2022
Published in print: Mar 1, 2023
Discussion open until: May 19, 2023
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