Smart Technologies for Traffic Signals

A pilot in Pittsburgh is using technology that is smart to optimize traffic signals, reducing the time it takes for vehicles to stop and idle as well as overall travel time. Created by a Carnegie Mellon professor of robotics, the system combines existing signal systems with sensors and artificial intelligence to improve www.technologytraffic.com/2022/07/25/start-using-a-virtual-data-room-today-to-save-time-money/ the routing in urban road networks.

Adaptive traffic signal control (ATSC) systems depend on sensors to monitor the real-time conditions at intersections and adjust the timing and phasing of signals. They can be based upon various hardware like radar, computer vision and inductive loops embedded in the pavement. They can also collect vehicle data from connected cars in C-V2X and DSRC formats and then process the data on the edge device, or transferred to a cloud location to be further analyzed.

By recording and processing real-time data about road conditions traffic, accidents, congestion and weather, smart traffic lights will automatically adjust the idling time, RLR at busy intersections, and recommended speed limits to ensure that vehicles can move around freely without slowing them down. They also can detect dangers such as violations of lane markings or crossing lanes and notify drivers, helping to prevent accidents on city roads.

Smarter controls are also a way to overcome new challenges like the popularity of ebikes, scooters, and other micromobility solutions that have risen during the pandemic. These systems are able to monitor the movements of these vehicles and employ AI to help control their movements at traffic light intersections which aren’t suited because of their size or maneuverability.