Smart Technologies for Traffic Signals

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

Adaptive traffic signal control (ATSC) systems depend on sensors to monitor the condition of intersections in real time and adjust the timing of signals and phasing. They can be built on different types of hardware, including radar, computer vision or inductive loops embedded in pavement. They can also record vehicle data from connected vehicles in C-V2X or DSRC formats and have the data processed at the edge device or dispatched to a cloud location for further analysis.

By collecting and processing real-time information about road conditions traffic, accidents, congestion and weather conditions, smart traffic signals can automatically adjust idle time, RLR at busy intersections and speed limits that are recommended to keep vehicles moving freely without causing a slowdown. They can also detect and alert drivers of dangers, such as violations of lane markings, or crossing lanes. They can also help to prevent injuries and accidents on city roads.

Smarter controls are also able to overcome new challenges such as the rise of e-bikes, escooters, and other micromobility options that have become more popular during the outbreak. These systems monitor vehicles’ movements and employ AI to improve their movements at intersections that aren’t ideal for their size.

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