In Pittsburgh, a pilot program has been developed that uses intelligent technology to optimize timings for traffic signals. This reduces vehicle stop-and idle times and travel times. The system was developed by a Carnegie Mellon professor of robotics the system integrates existing signal systems with sensors and artificial intelligence to improve the routing within urban road networks.

Sensors are used by adaptive traffic signal control systems (ATSC) to monitor and adjust the timing and the phasing of signals at intersections. They may be based on a variety hardware, including radar, computer vision, and inductive loops embedded within the pavement. They can also capture vehicle data from connected cars in C-V2X and DSRC formats with data processed at the edge device or transferred to a cloud location for further analysis.

Smart traffic lights can adjust the idling time and RLR at busy intersections to ensure that vehicles are moving without sloweding them down. They can also alert drivers to safety issues such as the violation of lane markings or crossing lanes, assisting to prevent injuries and accidents on city roads.

Smarter controls can also be used to address new challenges, such as the rise of ebikes Escooters, and other micromobility devices which have increased during the epidemic. These systems can track the movements of these vehicles and employ AI to improve their movements at intersections with traffic lights, which aren’t ideal for their small size or maneuverability.

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