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In Pittsburgh, a pilot program has been developed that uses smart technology to optimize traffic signal timings. This reduces vehicle stop-and idle time and travel times. It was designed by a Carnegie Mellon professor of robotics The system combines 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 various types of hardware, including radar, computer vision, and inductive loops that are installed on the pavement. They can also capture vehicle data from connected cars in C-V2X or DSRC formats and have the data processed on the edge device or sent to a cloud storage location to be further analyzed.
Smart traffic lights can alter the time of idle and RLR at busy intersections to keep vehicles moving without slowed down. They can also identify and warn drivers of dangers, such as traffic violations, lane markings, or crossing lanes, assisting to reduce accidents and injuries on city roads.
Smarter controls are also able in tackling new challenges, like the growth of e-bikes, e-scooters, and other micromobility options that have become increasingly popular during the outbreak. Such systems can monitor the movement of these vehicles and use AI to better control their movements at traffic light intersections which aren’t ideal to their small size or maneuverability.