Smart Technologies for Traffic Signals

A pilot in Pittsburgh is using technology that is smart to optimize traffic signals, reducing the amount of time spent on stopping and idling vehicles and overall travel time. The system was developed by an Carnegie Mellon professor in robotics and combines existing signals with sensors and artificial intelligent to improve routing on urban roads.

Adaptive traffic signal control (ATSC) systems rely on sensors to monitor real-time conditions at intersections and adjust signal timing and resource phasing. They can be based on various hardware options, including radar computer vision, radar, and inductive loops installed in the pavement. They can also collect data from connected vehicles in C-V2X and DSRC formats. Data is processed on the edge device, or sent to a cloud storage location for analysis.

Smart traffic lights can regulate the idling time and RLR at busy intersections so that vehicles can move without slowing them down. They can also identify and warn drivers of safety issues such as the violation of lane markings or crossing lanes. This helps to reduce accidents and injuries on city roads.

Smarter controls can also be used to address new challenges like the increasing popularity of ebikes, scooters, and other micromobility solutions that have risen during the epidemic. These systems monitor vehicles’ movements and employ AI to improve their movements at intersections that aren’t appropriate for their small size.