In Pittsburgh the pilot program utilizes intelligent technology to optimize traffic signal timings. This can reduce the amount of time that vehicles stop and 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 road networks.
Adaptive traffic signal control (ATSC) systems depend on sensors to monitor the condition of intersections in real time and adjust signal timing and phasing. They may be based on different types of hardware, such as radar, computer vision or inductive loops embedded within 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 alter the idling time and RLR at busy intersections so technologytraffic.com/2020/05/21/the-benefits-of-using-modern-traffic-technologies-by-data-room that vehicles can move without slowing them down. They can also identify and warn drivers of safety issues, like lane marking violations or crossing lanes. They can also help to prevent injuries and accidents on city roads.
Smarter controls can also assist to overcome new challenges like the growth of e-bikes, escooters, and other micromobility options that have become increasingly popular during the pandemic. These systems are able to monitor the movement of these vehicles and use AI to help control their movements at intersections with traffic lights, which aren’t well-suited to their small size or mobility.