Investigating Occupant Injury Severity of Truck-Involved Crashes Based on Vehicle Types on a Mountainous Freeway: A Hierarchical Bayesian Random Intercept Approach

Earlier research on injury severity of truck-involved crashes focused primarily on single-truck and multi-vehicle crashes with truck involvement, or investigated truck-involved injury severity based on rural and urban locations, time of day variations, lighting conditions, roadway classification, and weather conditions. However, the impact of different vehicle-truck collisions on corresponding occupant injury severity is lacking. Therefore, this paper advances the current research by undertaking an extensive assessment of the occupant injury severity in truck-involved crashes based on vehicle types (i.e., single-truck, truck-car, truck-SUV/pickup, and truck-truck), and identifies the major occupant-, crash-, and geometric-related contributing factors. A series of log-likelihood ratio tests were conducted to justify that separate model by vehicle and occupant types are warranted. Injury severity models were developed using 10 years of crash data (2007–2016) on I-80 in Wyoming through binary logistic modeling with a Bayesian inference approach. The modeling results indicated that there were significant differences between the influences of a variety of variables on the injury severities when the truck-involved crashes are broken down by vehicle types and separated by occupant types. The age and gender of occupants, truck driver occupation, driver residency, sideswipes, presence of junctions, downgrades, curves, and weather conditions were found to have significantly different impacts on the occupant injury severity in different vehicle-truck crashes. Finally, with the incorporation of the random intercept in the modeling procedure, the presence of intra-crash and intra-vehicle correlations (effects of the common crash- and vehicle-specific unobserved factors) in injury severities were identified among persons within the same crash and same vehicle.

• Record URL:
  https://doi.org/10.1016/j.aap.2020.105654
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S0001457520306709
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00014575
• Supplemental Notes:
  • © 2020 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Haq, Muhammad Tahmidul
  • Zlatkovic, Milan
  • Ksaibati, Khaled
• Publication Date: 2020-9

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Serial:
  • Accident Analysis & Prevention
  • Volume: 144
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0001-4575
  • Serial URL: http://www.sciencedirect.com/science/journal/00014575

Subject/Index Terms

• TRT Terms: Crash characteristics; Crash injuries; Crash severity; Injury severity; Mountain roads; Pickup trucks; Sport utility vehicles; Truck crashes
• Geographic Terms: Wyoming
• Subject Areas: Freight Transportation; Highways; Safety and Human Factors; Vehicles and Equipment;

Filing Info

• Accession Number: 01747984
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 17 2020 9:38AM