In Pittsburgh the pilot program uses intelligent technology to optimize traffic signal timings. This decreases the stop-and-go idle time and travel times. The system was developed by a Carnegie Mellon professor in robotics and combines existing signals with sensors and artificial intelligence to improve the efficiency of urban roads.
Sensors are used 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, as well as inductive loops incorporated into the pavement. They can also collect vehicle data from connected vehicles in C-V2X and DSRC formats and then process the data at the edge device or sent to a cloud server to be further analyzed.
Smart traffic lights can regulate the time of idle and RLR at busy intersections so that vehicles can move without slowing down. They can also detect safety issues such as violations of lane markings or crossing lanes and notify drivers, helping to prevent accidents on city roads.
Smarter controls are also a way to meet new challenges, such as the rise of ebikes escooters and other micromobility solutions which have increased during the epidemic. These systems can track the movements of these vehicles, and utilize AI https://technologytraffic.com/2022/08/12/best-data-rooms-providers-for-international-companies to help control their movements at traffic light intersections, which aren’t ideal to their small size or maneuverability.