Smart Technologies for Traffic Signals

In Pittsburgh the pilot program is using smart technology to optimize timings for traffic signals. This helps reduce vehicle stop-and idle time and travel times. Created 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.

Adaptive traffic signal control (ATSC) systems rely on sensors to track the condition of intersections in real time and adjust signal timing and phasing. They can be built on a variety hardware, such as radar, computer vision and inductive loops embedded in the pavement. They also can capture vehicle data from connected cars in C-V2X and DSRC formats and have the data processed by the edge device or sent to a cloud storage location to be further analyzed.

By recording and processing real-time data regarding road conditions, accidents, congestion, and weather conditions, smart traffic lights can automatically adjust idling times, RLR at busy intersections and speed limits that are recommended to ensure that vehicles can move around freely without slowed down. They can also identify and warn drivers of safety issues such as traffic violations, lane markings, or crossing lanes. They can also help to prevent injuries and accidents on city roads.

Smarter controls can also be used to overcome new challenges, such as the rise of ebikes scooters and other micromobility options that have risen during the epidemic. These systems monitor vehicles‘ movements, and utilize AI to improve their movements at intersections that are not appropriate for their small size.

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