Autonomous Road Vehicles and Law Enforcement

Identifying High-Priority Needs for Law Enforcement Interactions With Autonomous Vehicles Within the Next Five Years

Sean E. Goodison, Jeremy D. Barnum, Michael J. D. Vermeer, Dulani Woods, Tatiana Lloyd-Dotta, Brian A. Jackson

ResearchPublished Jul 16, 2020

Autonomous vehicles (AVs) promise many benefits, but questions remain about how law enforcement (LE) officers will interact with them. Officers likely will encounter new challenges related to technology, procedures, and constitutional authorities. To better understand the potential challenges of LE interaction with AVs, the RAND Corporation and the Police Executive Research Forum, on behalf of the National Institute of Justice, convened a workshop of practitioners and researchers to identify the highest-priority problems and associated needs related to AVs within the next five years. The purpose of the workshop was to explore specific scenarios involving AVs that have occurred or will occur and generate needs and potential technical options for addressing such situations. Workshop participants identified 33 needs that revolved around three broad themes: (1) designing a means of communicating with AVs that also maintains cybersecurity; (2) improving stakeholder communication and collaboration; and (3) developing standard procedures, guidelines, and training needs for LE interacting with AVs. The consensus was that many of the short-term needs identified in this report require a response and that LE should begin proactive preparations to address longer-term challenges before being forced into reactive changes.

Key Findings

Law enforcement must be able to communicate securely with AVs and their owners

  • Participants noted that methods are needed to determine whether and when an AV is operating without human control. From a legal standpoint, this is critical, because how a vehicle is operating could factor into officers' reasonable suspicion and probable cause determinations.

Participants agreed that communication and collaboration between stakeholders is important

  • AV manufacturers need an understanding of common problems officers face in the field so that AVs can be programmed in a way that allows for officers to manage routine interactions.
  • At the same time, LE needs to be informed of the capabilities and limitations of current AV systems to avoid misconceptions that might result in unrealistic ideas about what can and should be expected of AVs during LE interactions.

Standard protocols and procedures need to be established for LE interactions with AVs

  • Workshop participants expressed the need to ensure that all AVs are programmed to behave in the same way in each interaction with first responders so that procedures do not have to change based on the make and model of the car.
  • It is critical for LE and developers to work together to determine how interactions should occur and what behaviors can be expected of AVs. Standardization is critical, especially for vehicles that feature higher levels of autonomy.

Recommendations

  • Identify the costs and benefits of options to identify AV capabilities and authorization to run in automated mode.
  • Conduct an assessment of AVs and design tools to detect cyberattacks and facilitate investigation for law enforcement.
  • Conduct research to examine the costs and benefits of various options of communicating with AVs running in automated mode.
  • Develop a system that allows LE to communicate their intentions to AVs.
  • Develop the equivalent of license and documentation that allows LE to check the authorization to operate an AV.
  • Conduct research to identify the most-promising technological solutions that could be used in situations in which verbal communications are used.
  • Conduct workshops and ride-alongs for LE and other agency staff (as well as for AV system developers) to raise knowledge levels.
  • Conduct information-gathering exercises to develop ideal approaches for conveying information to first responders.
  • Conduct a survey of LE and crash reconstruction experts to identify information that would be most useful in crashes.
  • Develop web portals that could inform original equipment manufacturers about the kinds of information from which LE would benefit.
  • Identify best practices for cities and other entities that have information about upcoming closures.
  • Develop model training and guides for LE for identifying and interacting with AVs running in automated mode.
  • Develop guides and tools for potential LE responses to AV hacking.
  • Develop a guide containing likely scenarios in which AVs are used illegally, along with potential solutions.
  • Develop a description of the kinds of behaviors that LE will expect AVs to be able to perform that is representative across the United States.

Topics

Document Details

Citation

RAND Style Manual
Goodison, Sean E., Jeremy D. Barnum, Michael J. D. Vermeer, Dulani Woods, Tatiana Lloyd-Dotta, and Brian A. Jackson, Autonomous Road Vehicles and Law Enforcement: Identifying High-Priority Needs for Law Enforcement Interactions With Autonomous Vehicles Within the Next Five Years, RAND Corporation, RR-A108-4, 2020. As of September 9, 2024: https://www.rand.org/pubs/research_reports/RRA108-4.html
Chicago Manual of Style
Goodison, Sean E., Jeremy D. Barnum, Michael J. D. Vermeer, Dulani Woods, Tatiana Lloyd-Dotta, and Brian A. Jackson, Autonomous Road Vehicles and Law Enforcement: Identifying High-Priority Needs for Law Enforcement Interactions With Autonomous Vehicles Within the Next Five Years. Santa Monica, CA: RAND Corporation, 2020. https://www.rand.org/pubs/research_reports/RRA108-4.html.
BibTeX RIS

Research conducted by

The research described in this report was prepared for the National Institute of Justice (NIJ) and conducted by the Justice Policy Program within RAND Social and Economic Well-Being.

This publication is part of the RAND research report series. Research reports present research findings and objective analysis that address the challenges facing the public and private sectors. All RAND research reports undergo rigorous peer review to ensure high standards for research quality and objectivity.

This document and trademark(s) contained herein are protected by law. This representation of RAND intellectual property is provided for noncommercial use only. Unauthorized posting of this publication online is prohibited; linking directly to this product page is encouraged. Permission is required from RAND to reproduce, or reuse in another form, any of its research documents for commercial purposes. For information on reprint and reuse permissions, please visit www.rand.org/pubs/permissions.

RAND is a nonprofit institution that helps improve policy and decisionmaking through research and analysis. RAND's publications do not necessarily reflect the opinions of its research clients and sponsors.