Embracing Artificial Intelligence to Mitigate Police Vehicle Crashes

The nation's roadways have become more treacherous for all who travel, including police officers. Understandably, there is significant attention to preventing the deaths of police officers feloniously killed by gunfire. However, motor vehicle crashes are considered a leading cause of death for police officers, and opportunities to prevent police-involved motor vehicle crashes are often overlooked. The impact of motor vehicle crashes on today's law enforcement officers extends far beyond death due to the long-term effects of injuries, litigation, career loss, and more.

Artificial Intelligence (AI) is a critical tool that is often underutilized in preventing police-involved motor vehicle crashes. As AI has flourished in the last year or so, many people believe AI is new, and some may think it predominantly consists of programs involving large language models that aid with writing. However, AI vehicle technology has been preventing crashes for decades, and these technologies can assist in building a pathway to more efficient, innovative, and, most importantly, safer police driving.

Many police agencies effectively utilize vehicle telematics systems, which include GPS capabilities, maintenance tracking, data collection, and other features. Telematics can also be essential for monitoring and improving officers' driving behavior, ensuring compliance with agency policies, assessing individual training requirements, and identifying necessary adjustments to agency policies or training programs. When utilized appropriately, telematics can often assist during litigation by reinforcing the officer's credibility of driving within the parameters of agency policies. However, suppose agencies have telematics systems but do not use them for speed monitoring, driver coaching, determining training needs, and policy compliance and development. In that case, it may indicate that improper driving behavior is being ignored or even encouraged.

AI vehicle technologies now go far beyond telematics. Like many civilian vehicles, police vehicles are equipped with Advanced Driver Assisted Systems (ADAS) and Collision Avoidance Systems (CAS). These systems typically offer lane departure warnings, blind spot detection, cross-traffic alerts, and emergency braking for vehicles. Furthermore, AI vehicle technologies are rapidly advancing to include Vehicle-to-Vehicle (V2V), Responder-to-Vehicle (R2V), and Responder-to-Responder (R2R) capabilities, which warn civilian motorists and other emergency vehicles of emergency vehicle activity.

However, as with telematics, such technological advancements are only valuable when utilized effectively as an overall agency strategy to keep officers and the community safe. Local government leaders and Chiefs of Police are encouraged to review the considerations below and embrace the AI technologies of today and tomorrow to help mitigate crashes, deaths, injuries, and claims.

AI Police Vehicle Crash Mitigation Considerations:

• Review the agency fleet to determine what ADAS and CAS systems exist on each vehicle by year, make, and model, and ensure that all agency vehicle operators are aware of the technology.
• Develop strong agency policy guidance that governs the appropriate settings for these crash prevention systems. Officers accustomed to specific alerts might be more prone to crash when another driver purposely or inadvertently deactivates the system settings.
• Integrate comprehensive training on crash prevention systems into the agency's vehicle deployment program and new officer field training program, ensuring detailed familiarization with these systems and adherence to policy requirements governing their settings.
• When preparing budget requests, evaluate available vehicle options, including ADAS and CAS systems, to help prevent crashes.
• Ensure an agency-specific policy is developed governing telematics. The policy should include guidelines concerning access to data, including random access, live data, stored data, and third-party data sharing. The individuals designated to review specified trigger alerts and stored data should be codified in the agency policy.
• Research the growing availability of V2V and related technologies that warn motorists of emergency vehicles at or approaching intersections and other locations.