Smart Technologies for Traffic Signals

A pilot in Pittsburgh is using technology that is smart to optimize traffic signals, thus reducing vehicle stop-and-idling time and overall travel times. The system was developed by an Carnegie Mellon professor of robotics, the system combines 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 on a variety of hardware, including radar, computer vision, and inductive loops incorporated into the pavement. They also can capture vehicle data from connected vehicles in C-V2X or DSRC formats, with data pre-processed on the edge device or dispatched to a cloud location to be further analyzed.

By collecting and processing real-time information about road conditions, accidents, congestion, and weather conditions, smart traffic lights will automatically adjust the idling time, RLR at busy intersections and recommended speed limits so that vehicles can continue to move without causing a slowdown. They can also spot safety issues like violations of lane markings or crossing lanes, and alert drivers, thereby reducing accidents on city roads.

Smarter controls also technologytraffic.com/2021/07/08/generated-post-2/ can help to tackle new challenges such as the rise of e-bikes, escooters, and other micromobility options that have become increasingly well-known during the pandemic. Such systems can monitor the movements of these vehicles and employ AI to control their movements at intersections for traffic lights, which are not well suited for their small size or maneuverability.