Smart Technologies for Traffic Signals

In Pittsburgh the pilot program utilizes smart technology to optimize traffic signal timings. This reduces vehicle stop-and idle time as well as travel times. The system was developed by a Carnegie Mellon professor of robotics the system blends existing signal systems with sensors and artificial intelligence to improve the routing in urban road networks.

Adaptive traffic signal control (ATSC) systems depend on sensors to observe the real-time conditions at intersections and adjust signal timing and phasing. They can be based on various types of hardware, including radar computer vision, radar, and inductive loops that are embedded in the pavement. They also can collect data from connected vehicles in C-V2X and DSRC formats. The data is processed at the edge device, or transmitted to a cloud location for analysis.

By taking and processing real-time data regarding road conditions such as accidents, congestion, and weather, 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 slowed down. They also can detect dangers like lane marking violations and crossing lanes and notify drivers, thereby reducing accidents on city roads.

Smarter controls are also a way to overcome new challenges like the rise of ebikes scooters, and other micromobility solutions that have grown in popularity during the pandemic. These systems are able to monitor vehicles’ movement and apply AI to help manage their movements at intersections that are not ideal for their size.

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