Smart Technologies for Traffic Signals

In Pittsburgh the pilot program utilizes intelligent technology to optimize timings for traffic signals. This reduces vehicle stop-and idle time as well as travel time. Created by a Carnegie Mellon professor of robotics The system combines existing signal systems with sensors and artificial intelligence to improve routing in urban roads.

Adaptive traffic signal control (ATSC) systems rely on sensors to monitor the condition of intersections in real time and adjust signal timing and phasing. They can be built on a variety hardware, like radar, computer vision, and inductive loops embedded within the pavement. They also can collect data from connected vehicles in C-V2X and DSRC formats. Data is processed on the edge device, or transferred to a cloud storage location for analysis.

Smart traffic lights are able to adjust the idling time and RLR at busy intersections so that vehicles can move without slowed modern traffic technologies by board room down. They can also detect and alert drivers of dangers, such as lane marking violations or crossing lanes, helping to reduce accidents and injuries 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 epidemic. Such systems can monitor the movements of these vehicles, and utilize AI to help control their movements at traffic light intersections, which are not well suited for their small size or mobility.