In Pittsburgh the pilot program is using smart technology to optimize timings of traffic signals. This can reduce the amount of time that vehicles stop and idle time as well as travel times. The system was designed by an Carnegie Mellon professor in robotics and integrates 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 based on various types of hardware, including radar computer vision, radar, as well as inductive loops that are installed on the pavement. They can also record vehicle data from connected cars in C-V2X and DSRC formats with data processed on the edge device or dispatched to a cloud location to be further analyzed.
Smart traffic lights can adjust the idle time and RLR at busy intersections to keep vehicles moving without slowing down. They also can alert drivers to dangers, such as the violation of lane markings or crossing lanes. They can also help to reduce injuries and accidents on city roads.
Smarter controls are also a way to overcome new challenges like the growing popularity of ebikes scooters, and other micromobility solutions that have grown in popularity during the epidemic. These systems can track the movement of these vehicles and apply AI to help control their movements at intersections with traffic lights, which aren’t well-suited due to their small size and mobility.