A Multi-Site Evaluation of Automated License Plate Readers

Existing research suggests that LPRs can improve public safety, but the technology’s impact depends on its implementation.

Project Overview

The goal of this project is to conduct a multisite, quasi-experimental assessment of fixed-location license plate readers (LPRs) on public safety outcomes. Existing research suggests that LPRs can be an effective for increasing the recovery of stolen vehicles and arrests for auto thefts (Koper et al., 2013, 2019, 2021; Ohio State Highway Patrol, 2005; Ozer, 2010; Taylor et al., 2012) and, under certain conditions, may improve clearance rates for auto theft and robbery (Koper & Lum, 2019).

However, several studies exploring the crime prevention value of LPRs have found effectiveness varied based on several factors. These included volume and concentration of LPR deployment, the type of LPR deployed (fixed vs. mobile, general patrol versus specialized unit), location of use, the types of databases connected to LPR and how often they are updated, how officers use LPRs in the field, and agency pursuit and response policies for officers informed about suspects by LPR technology.

Modern LPR cameras now uses machine learning to capture a variety of additional information about the vehicle that could not be captured previously. This additional information may have implications for both how LPRs are used and their effects on public safety. Considering recent improvements in LPR technology, the current study seeks to expand understanding of the public safety benefits of LPRs through a multi-site data collection and analysis, focused on fixed-location LPR systems in several large law enforcement agencies across the United States.

Methodology

The study evaluates the implementation of fixed-location LPR systems across multiple large jurisdictions using a quasi-experimental design. Longitudinal data from the treatment and control sites will be collected across jurisdictions to examine the following questions. Does the implementation of fixed LPR systems…

  1. … increase arrest for (a) vehicle related offenses?
  2. … improve the (a) quality, (b) speed, and (c) and close rate of investigation?
  3. … affect reported rates of certain types of crime, including vehicle-related offenses?
  4. … create a pathway for transparency, accountability, and engagement with the community?

Additional questions about system use will be explored, including: (a) How is the system being used? (b) What data were captured? (c) What searches were being performed? (d) How were the data used?

Project Resources

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Project Publications

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Service Area(s)

Staff Contact(s)

Travis Taniguchi

Travis Taniguchi, PhD

Director of Research

Hannah Wu

Hannah Xiaoyun Wu, PhD

Senior Research Associate

Media Contact

Media inquiries should be directed to our Communications team at:

media@policinginstitute.org
202-833-1460

More Information

Project Status: Active

Project Period:  April 2022 -

Research Design: Quasi-experiment

Research Method(s): Longitudinal study, Secondary data analysis

Service Area(s)

Staff Contact(s)

Travis Taniguchi

Travis Taniguchi, PhD

Director of Research

Hannah Wu

Hannah Xiaoyun Wu, PhD

Senior Research Associate

Media Contact

 

Media inquiries should be directed to our Communications team at:

media@policinginstitute.org
202-833-1460