Smart Technologies for Traffic Signals

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In Pittsburgh the pilot program utilizes intelligent technology to optimize timings for traffic signals. This reduces vehicle stop-and idle time and travel times. Designed by an Carnegie Mellon professor of robotics The system combines signals from the past with sensors and artificial intelligence to improve routing in urban road networks.

Sensors are used by adaptive traffic signal control systems (ATSC) to monitor and adjust the timing and the phasing of signals in intersections. They can be built on various types of hardware, including radar, computer vision, and inductive loops that are embedded in the pavement. They can also collect vehicle data from connected cars in C-V2X or DSRC formats with data processed at the edge device or sent to a cloud server to be further analyzed.

By recording and processing real-time data regarding road conditions such as accidents, congestion, and weather, smart traffic lights can automatically adjust idling time, RLR at busy intersections and speed limits recommended by the authorities to allow vehicles to move freely without causing a slowdown. They can also detect and alert drivers of safety issues such as traffic violations, lane markings, or crossing lanes, assisting to minimize injuries and accidents on city roads.

Smarter controls can also be used to tackle new challenges, such as the popularity of ebikes, escooters and other micromobility solutions which have increased during the epidemic. These systems can monitor the movements of these vehicles and use AI to control their movements at traffic light intersections which aren’t suited due to their small size and maneuverability.

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