As part of an ongoing series of reports on workshops sponsored by the National Institute of Justice (NIJ) under its Priority Criminal Justice Needs Initiative, this report presents the conclusions of a workshop convened to better understand the problems and opportunities, both technical and legal, that autonomous vehicles (AVs) may pose for law enforcement.
The workshop, which was intended to inform NIJ's science and technology innovation agenda, met on July 24-25, 2019. Workshop participants were invited based on consultation with those who had produced relevant research literature, federal partners, and law enforcement agencies in jurisdictions where AV pilot projects are currently operating. The workshop explored public safety scenarios that involved autonomous road vehicles that have been or will be encountered by law enforcement agencies within 5 years. Workshop discussions focused on four categories of law enforcement interaction, i.e., traffic stops, collisions, emergencies (e.g., detours, and evacuations), and tangential interactions (e.g., AVs as a source of evidence during an investigation and exclusion zones). Participants were led through the scenarios in semi-structured discussions. Following the discussions, experts participated in a ranking exercise to identify the most important needs, i.e., a problem or opportunity and accompanying solution. A total of 17 of the identified needs were categorized as high priority. The three general categories of need are 1) cybersecurity and means of communicating with AVs, their owners, or remote operators; 2) stakeholder communication and collaboration; and 3) standard procedures, guidelines, and training needs for law enforcement. The workshop recommended the following research areas for cybersecurity and AV communication: 1) identification of the costs and benefits of various options for identifying the capabilities and authorization to operate a vehicle in automated mode; and 2) the examination of the costs and benefits of various options for communicating with vehicles operating in automated mode. 6 figures, 4 tables, and 36 references
- The Probabilistic Genotyping Software STRmix: Utility and Evidence for its Validity
- Determining the Number of Contributors to DNA Mixtures in the Low-Template Regime Exploring the impacts of Sampling and Detection Effects
- Estimating School Climate Traits Across Multiple Informants: An Illustration of a Multitrait-Multimethod Validation Through Latent Variable Modeling