AAMVA released the License Plate Reader Program Best Practices Guide Edition 2 in August. This Q&A covers the history of the technology, highlights what’s new in the guide and provides tips for how to best use its information.

What is the history of license plate readers (LPRs)?

LPRs were developed in the 1970s in the United Kingdom, primarily to combat terrorism. The technology spread, including to the United States in the 1980s, when jurisdictions first began using them for roadway safety and law enforcement.

About 65% of large agencies employ LPRs today, but only about 1% of all patrol cars in the U.S. are equipped with an LPR. That 1% does not account for LPRs that are used at fixed sites, which exist in greater numbers.

What are the greatest challenges with LPRs?

The challenges are primarily threefold. The biggest is the cost. The equipment and network capacity are expensive to acquire, implement and maintain. LPR programs also require staffing resources.

Another challenge in using the equipment is the presence of obstructions, whether from weather, lighting conditions, plate obstructions or plates that are not aligned with the AAMVA license plate standard, often resulting in misreads.

The Big Brother public perception is another major concern. The collection of vehicle data raises privacy questions and concerns about surveillance, data storage and retention. Sound policies are needed to ensure transparency and appropriate LPR system use.

What should people know about the efforts to combat these concerns?

AAMVA’s LPR Program Best Practices document, if followed, will help member law enforcement agencies address these concerns. It’s a continuous balancing act of what is best for public safety versus what constitutes government overreach. Privacy concerns have to be considered.

How did AAMVA arrive at the changes for this new guide? What should readers know?

Because of the rapid rate of change, particularly when it comes to technology, it is critical that agencies continuously review their policies, procedures and practices to make sure they stay in line with current best practices.

AAMVA’s Law Enforcement Committee periodically reviews all of its published best practices. Even though it’s only been about three years since AAMVA published the original document, so much had changed that it needed to be updated.

How did the working group operate?

AAMVA had representatives from eight state police agencies and a group of technical advisors representing several LPR manufacturers. The entire group contributed significantly. In particular, Sergeant Jonathan Zarkauskas of the Virginia State Police chaired the working group and deserves special mention.

AAMVA conducted two in-person meetings and several virtual meetings to complete the work over a several-month period. Because of the dedicated effort of the working group members, AAMVA published several months ahead of the original target of November 2025.

What are the differences between the two editions?

In addition to generally updating the entire document, AAMVA added two chapters that did not exist in the first edition. The first new chapter addresses LPR equipment acquisition.

The second new chapter covers the ethical use of artificial intelligence in LPR operations. In the early days of LPRs, artificial intelligence and machine learning didn’t exist. Over time, AI and machine learning have crept into LPR capabilities, sometimes in conflict with individual state privacy laws. The use of AI and machine learning certainly can make LPR operations more effective, but if they are allowed at all, they must be used within the laws and policies of the jurisdiction.

How should people use these best practices?

As with other guides, AAMVA recommends that members use this best practice document in two ways. For an agency without a current LPR program, this guide serves as a blueprint for establishing a program and building it from the ground up.

For agencies with existing LPR programs, the document should be used to benchmark current practices against the recommended best practices in the AAMVA document. This exercise allows agencies to identify performance gaps and opportunities for program improvement.