In Pittsburgh, a pilot program utilizes smart technology to optimize timings of traffic signals. This reduces vehicle stop-and idle time as well as travel times. Created by a Carnegie Mellon professor of robotics the system blends existing signal systems with sensors and artificial intelligence to improve the routing in urban road networks.
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 based on a variety of hardware, including radar computer vision, radar, and inductive loops incorporated into the pavement. They can also gather data from connected vehicles in C-V2X and DSRC formats. The data is processed at the edge device, or sent to a cloud location to be analyzed.
Smart traffic lights can regulate the idling speed and RLR at busy intersections so that vehicles can move without slowing down. They can also detect and notify drivers of dangers, such as lane marking violations or crossing lanes, helping to reduce accidents and injuries on city roads.
Smarter controls can also help to overcome new challenges like the growth of e-bikes and e-scooters and other micromobility options that have become more popular during the outbreak. These systems are able to monitor the movement of these vehicles, and utilize AI to control their movements at traffic light intersections which aren’t ideal for their small size or maneuverability.