AASHTO reports on a public-private advanced traffic management pilot-project in Las Vegas, Nevada.
The Nevada DOT, in partnership with the Nevada Highway Patrol and the Regional Transportation Commission (RTC) used artificial intelligence (AI) software to alleviate traffic crashes at dangerous intersections with higher than average crash rates in Southern Nevada. The software was developed by a private contractor. The system used connected vehicle data, existing cameras, roadside sensors, and other traffic-related data to develop predictive analytics that could be used to recognize traffic patterns associated with crash-related congestion. These detected traffic patterns then enabled traffic management professionals to implement countermeasures to improve safety such as increasing police presence in areas with speeding vehicles and improving response times for emergency vehicles by detecting incidents sooner.
Performance of the system was evaluated during a one-year pilot project where before and after safety data were evaluated in 2017.
Results indicated that AI and deep learning strategies, when deployed in collaboration with traffic management and enforcement agencies, can improve safety on congested freeways. Traffic safety data collected during the one-year pilot program indicated the system contributed to a 17 percent reduction in primary crashes along a key corridor of Interstate 15 in Las Vegas, and emergency response times improved for first responders as incidents were able to be detected an average of 12 minutes sooner.