Enhancing Fleet Safety with MV/AI VEDR

Whereas traditional VEDR systems relied on g-force triggers to reactively capture events—with unsafe behavior identified only after a sudden impact or movement—MV/AI (Machine Vision/Artificial Intelligence) VEDR systems now use real-time video analysis to proactively detect and address unsafe driving behaviors as they occur. 

MV/AI VEDR leverages advanced video analytics and machine learning algorithms to continuously monitor driver behavior, identify potential safety risks, and deliver real-time alerts to both drivers and management when an unsafe event is detected—enabling earlier intervention and improved safety outcomes. 

How AI VEDR Enables Proactive Safety 

MV/AI VEDR is a significant step forward in proactive safety management. Real-time driver coaching, through audible in-cab alerts, helps drivers stay focused and keeps safe driving practices top of mind. At the same time, fleet managers can monitor events and trends, allowing them to identify key areas for improvement. 

As more events occur, machine learning and data analytics will further enhance the system’s accuracy and effectiveness, allowing for even earlier detection of high-risk behaviors and better predictive insights to enhance your fleet safety efforts. 

Best Practices to Follow Up on Events 

MV/AI VEDR improves event recognition, but it is not a substitute for a safety program – it should be used to inform how your organization approaches safety overall. In addition to monitoring VEDR events, it is recommended fleet managers:

• • • Conduct immediate coaching sessions with drivers after incidents to reinforce safe practices and clarify policy expectations.
       
    • Implement regular ride-alongs and targeted coaching for drivers frequently involved in specific violations, like close following or incomplete stops.
       
    • Conduct periodic spot checks at terminals to reinforce compliance with seatbelt and camera maintenance requirements. 

Common VEDR Concerns 

• • • Data Sharing: Only pass/fail outcomes for each Key Indicator are shared. No specific information on events or drivers. 

• • • Contracted vs. Posted Speed: There is a crucial difference between the contracted speed limit of 65 mph and higher posted or governed speeds. It’s important that drivers be aware of these requirements as there can be steep penalties, including contract termination risks associated with speeding incidents exceeding 70 mph. 

• • • Event Disputes: Most events are able to be disputed if there are concerns about their validity. It’s best that disputes are submitted within 24 hours of the event being received.  

Conclusion 

MV/AI VEDR is helping service providers create safer roadways and build out the culture of safety within their teams. It helps to improve driver safety in two key ways: 

• • • • In-cab alerts to notify the driver of unsafe driving practices and reduce the risk of accidents in real time.  

• • • • Actionable insights to inform management of key areas for improvement, and where to allocate safety resources. 

By leveraging the event recognition and data from VEDR as part of a robust safety program, contractors can significantly enhance driver safety and reduce their compliance risks, while enhancing operations overall.