Smart Technologies for Traffic Signals

In Pittsburgh the pilot program is using intelligent technology to optimize timings of traffic signals. This decreases the stop-and-go idle times and travel times. Designed by a Carnegie Mellon professor of robotics the system integrates existing signal systems with sensors www.technologytraffic.com/2022/07/25/start-using-a-virtual-data-room-today-to-save-time-money/ and artificial intelligence to improve routing in urban road networks.

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

By taking and processing real-time data about road conditions traffic, accidents, congestion and weather conditions, smart traffic signals 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 alert drivers to safety concerns, such as violations of lane markings, or crossing lanes, helping to reduce accidents and injuries on city roads.

Smarter controls also can help to overcome new challenges such as the rise of e-bikes and e-scooters and other micromobility options that have become increasingly popular since the pandemic. These systems are able to monitor the movements of these vehicles and employ AI to control their movements at intersections with traffic lights, which aren’t suited because of their size or mobility.