How Do Motorists' Pre-Crash Behaviors Contribute to the Injury Severity of Police Officers? Using Interpretable Machine Learning to Untangle the Behavioral Pathways in Crashes Involving Police Vehicles

Details

• Journal Article:
  Journal of Safety Research
• Personal Author:
  Xu, Ningzhe ; Liu, Jun ; Zhang, Zihe ; Jones, Steven
• Description:
  Introduction: Police officers are integral to enforcing traffic laws and providing assistance to motorists. While performing their duties on the road or roadside, they encounter significant hazards, many of which arise from the negligent or inappropriate behaviors of drivers. Despite the prevalence of these risks, there is a paucity of research specifically examining the outcomes of traffic crashes involving police officers or police vehicles, particularly in relation to the injury severity sustained by police officers in such incidents. The objective of this study is to explore the roles of motorist behaviors in police-involved crashes. Method: Specifically, using police-involved crashes data from 2017 to 2021 in Alabama, this study employs a path analysis framework integrated with interpretable machine learning to examine the behavioral pathways from contributing factors to motorists' pre-crash behaviors, ultimately leading to the injury severity of police officers. The path analysis allows the identification of various factors that directly contribute to injury severity and those that indirectly contribute to injury severity through their relationships with motorists' pre-crash behaviors. Results: The results indicate that several factors are directly associated with policy injury severities, including motorists' pre-crash behaviors (such as failure to yield, driving under the influence (DUI), and traffic signal violations) that are significantly correlated with increased injury severity for police officers involved in crashes. Further, these pre-crash behaviors are associated with contributing factors including vehicle speeds, lighting conditions, seatbelt usage, and weather conditions. Thus, these contributing factors serve as significant predictors of motorists' pre-crash behaviors, indirectly impacting police injury severity through their influence on unsafe driving practices. Practical Applications: This study provides valuable insights into the behavioral pathway leading to police injury severities. By understanding the direct and indirect contributors to police injury severity, policymakers can develop targeted interventions to address these key risk factors and improve overall road safety for police officers.
• Subjects:
  Law Enforcement Motor Vehicles Occupational Health Safety
• Keywords:
  Author Keywords: Police Officers; Injury Severity; Traffic Crash; Pre-crash Behavior Police Officers; Motor Vehicles; Drivers; Behavior; Machine Learning; Injuries; Vehicle Safety; Safety Research;
• Source:
  J Safety Res 2025 Sep; 94:193-215
• ISSN:
  0022-4375
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  Alabama ; Birmingham Region [OSHA]
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  23 pdf pages
• Volume:
  94
• NIOSHTIC Number:
  nn:20071350
• Contact Point Address:
  Ningzhe Xu, Department of Civil, Construction and Environmental Engineering, The University of Alabama, Tuscaloosa, AL 35487, United States
• Email:
  nxu3@crimson.ua.edu
• Federal Fiscal Year:
  2025
• Performing Organization:
  University of Alabama in Tuscaloosa
• Peer Reviewed:
  True
• Start Date:
  20240930
• End Date:
  20280929
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:4346e5c4a9ddc543298289d35eb6534a7b9995313c5ae5f83ca0e2ca6603841c2d12238eca3b619b1c4f41f10480d00e440b76692fe99a90b1054ab9f32e9b20
• Download URL:
  https://stacks.cdc.gov/view/cdc/258825/cdc_258825_DS1.pdf
• File Type:
  [PDF - 2.60 MB ]