In Pittsburgh, a pilot program uses smart technology to optimize traffic signal timings. This can reduce the amount of time that vehicles stop and idle time as well as travel times. The system was created by a Carnegie Mellon professor in robotics and combines signals from the past with sensors and artificial intelligence to improve routing on urban roads.
Sensors are used by adaptive traffic signal control systems (ATSC) to monitor and adjust the timing and timing of signals at intersections. They can be based on various types of hardware, including radar computer technologytraffic.com vision, radar, as well as inductive loops that are installed on 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 server for analysis.
By capturing and processing real-time data about road conditions traffic, accidents, congestion and weather conditions, smart traffic lights can automatically adjust idling times, RLR at busy intersections and speed limits recommended by the authorities to keep vehicles moving freely without slowing them down. They can also detect and notify drivers of safety issues such as lane marking violations or crossing lanes, helping to minimize injuries and accidents on city roads.
Smarter controls also can help to address new challenges like the growth of e-bikes, escooters, and other micromobility options that have become more popular during the pandemic. These systems can track these vehicles’ movement and apply AI to better manage their movements at intersections that aren’t well-suited for their small size.