Smart Technologies for Traffic Signals

In Pittsburgh, a pilot program uses intelligent technology to optimize traffic signal timings. This decreases the stop-and-go idle time as well as travel times. Designed by a Carnegie Mellon professor of robotics The system combines signals from the past with sensors and artificial intelligence to improve the routing within urban road networks.

Adaptive traffic signal control (ATSC) systems depend on sensors to monitor the conditions at intersections in real-time and adjust the timing and phasing of signals. They may be based on different types of hardware, including radar, computer vision and inductive loops embedded in pavement. They can also gather data from connected vehicles in C-V2X and DSRC formats. The data is processed at the edge device, or sent to a cloud server for analysis.

By taking and processing real-time data about road conditions, accidents, congestion, and weather conditions, smart traffic lights can automatically adjust idling time, RLR at busy intersections and speed limits recommended by the authorities to keep vehicles moving freely without causing a slowdown. They can also alert drivers to safety concerns, such as lane marking violations or crossing lanes, helping to reduce injuries and accidents on city roads.

Smarter controls are also a way to overcome new challenges, such as the growing popularity of ebikes Escooters, and other micromobility devices which have increased during technologytraffic.com/2021/07/08/generated-post-2 the epidemic. Such systems can monitor the movements of these vehicles and apply AI to control their movements at traffic light intersections which aren’t well-suited for their small size or maneuverability.