Smart Technologies for Traffic Signals

A pilot in Pittsburgh uses smart technology to improve traffic signals, thereby reducing vehicle stop-and-idling time and overall travel times. Created by a Carnegie Mellon professor of robotics, the system combines existing signal systems with sensors and artificial intelligence to improve the routing in urban road networks.

Adaptive traffic signal control (ATSC) systems rely on sensors to monitor real-time conditions at intersections and adjust signal timing and phasing. They can be based on various types of hardware, such as radar, computer vision, and inductive loops embedded in pavement. They also can capture vehicle data from connected vehicles in C-V2X and DSRC formats and have the data processed by the edge device or sent to a cloud server for further analysis.

Smart traffic lights can regulate the idling speed and RLR at busy intersections to ensure that vehicles are moving without slowing them down. They also can alert drivers to safety issues such as violations of lane markings, or crossing lanes. They can also help to minimize injuries and accidents on city roads.

Smarter controls also can help to address new challenges such as the rise of e-bikes, escooters, and other micromobility options that have become more popular during the pandemic. These systems monitor vehicles’ movements and employ AI to better manage their movements at intersections that are not appropriate for their small size.

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