Smart Technologies for Traffic Signals

A pilot in Pittsburgh is using smart technology to optimize traffic signals, which is reducing the amount of time spent on stopping and idling vehicles and overall travel time. Designed by an Carnegie Mellon professor of robotics the system blends existing signal systems with sensors and artificial intelligence to improve the routing in urban road networks.

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

Smart traffic lights can regulate the idle time and RLR at busy intersections to keep vehicles moving without slowed down. They can also spot dangers like crossing lanes and alert drivers, helping to reduce accidents on city roads.

Smarter controls can also help to overcome new challenges such as the rise technologytraffic.com/2020/05/21/the-benefits-of-using-modern-traffic-technologies-by-data-room of e-bikes and e-scooters and other micromobility options that have become more popular since the pandemic. These systems are able to monitor the movement of these vehicles and employ AI to control their movements at traffic light intersections which aren’t ideal to their small size or maneuverability.


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