Advanced Driver Assistance Systems in Law Enforcement Vehicles

Wooten, Thomas; Fisher, Donald L.; Berg, Ian

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Advanced Driver Assistance Systems in Law Enforcement Vehicles

2026-08-10
By Wooten, Thomas ; Fisher, Donald L. ; Berg, Ian

File Language:

English

Details

Creators:

Wooten, Thomas ; Fisher, Donald L. ; Berg, Ian
Corporate Creators:

John A. Volpe National Transportation Systems Center (U.S.)
Corporate Contributors:

United States. Department of Transportation. Highly Automated Systems Safety Center of Excellence ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:

Advanced Driver Information Systems Emergency Medical Technicians Fire Fighting Human Factors Law Enforcement Training
Publication/ Report Number:

DOT-VNTSC-OST-26-01
Resource Type:

Tech Report
Geographical Coverage:

United States
Edition:

Final Report
Corporate Publisher:

John A. Volpe National Transportation Systems Center (U.S.)
Abstract:

Motor vehicle crashes are one of the leading causes of on-duty death for law enforcement (LE) officers, firefighters, and emergency medical service (EMS) personnel. This manuscript examines the potential benefits, limitations, and human factors considerations when implementing advanced driver assistance systems (ADAS) in LE fleets, with additional considerations when incorporating ADAS features in ambulances and fire trucks. We found that ADAS, specifically collision avoidance systems focused on longitudinal control and lateral control, are likely to significantly reduce crash risk in LE vehicles during normal driving scenarios. Conversely, collision avoidance systems may interfere with emergency driving and tactical driving maneuvers when active. Driver-vehicle interfaces for ADAS-equipped emergency vehicles should ideally have adaptive and flexible ADAS features that allow for their selective activation and deactivation based on situational needs. ADAS training for first responders should be multifaceted, including both general and specialized components to encourage accurate mental models.
Format:

PDF
Collection(s):

Volpe Center
Main Document Checksum:

urn:sha-512:7300a7aacf138d8753c5c1183b8250118ac3e43ea8286a981fd2ec605cc0a4fb516224ff5d177809ec0c5325c1d2b651281bfcdd7d20c8fd501cc0c1d8dbd75b
Download URL:

https://rosap.ntl.bts.gov/view/dot/92934/dot_92934_DS1.pdf
File Type:

[PDF - 1.43 MB ]

File Language:

English

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