Smart Technologies for Traffic Signals

technologytraffic.com/2020/05/01/modern-traffic-technologies-by-board-room

A pilot in Pittsburgh is utilizing smart technology to optimize traffic signals, thus reducing vehicle stop-and-idling time and overall travel times. Created by a Carnegie Mellon professor of robotics the system blends existing signal systems with sensors and artificial intelligence to improve routing in urban roads.

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

Smart traffic lights can regulate the idle time and RLR at busy intersections to ensure that vehicles are moving without sloweding them down. They can also detect and notify drivers of safety concerns, such as violations of lane markings, or crossing lanes. They can also help to reduce injuries and accidents on city roads.

Smarter controls also can help in tackling new challenges, such as the rise of ebikes, escooters and other micromobility options that have become more popular during the outbreak. These systems monitor vehicles’ movements, and utilize AI to help manage their movements at intersections that aren’t well-suited for their small size.