In Pittsburgh the pilot program has been developed that uses intelligent technology to optimize timings for traffic signals. This helps reduce vehicle stop-and idle times and travel times. The system was designed by an Carnegie Mellon professor in robotics and combines existing signals with sensors and artificial intelligence to improve the routing of urban roads.

Sensors are utilized by adaptive traffic signal control systems (ATSC) to monitor and adjust the timing and the phasing of signals at intersections. They can be built on a variety of hardware, including radar, computer vision, and inductive loops that are installed on the pavement. They can also gather data from connected vehicles in C-V2X and DSRC formats. Data is processed on the edge device, or sent to a cloud for analysis.

Smart traffic lights can adjust the idle time and RLR at busy intersections to allow vehicles to move without slowing down. They can also alert drivers to dangers, such as the violation of lane markings or crossing lanes, helping to reduce injuries and accidents on city roads.

Smarter controls can also help to tackle new challenges like the growth of e-bikes, escooters, and other micromobility options that have become more popular since the pandemic. These systems can track these vehicles’ movement and apply AI to better manage their movements at intersections that are not appropriate for their small size.