08 Oct Smart Technologies for Traffic Signals
A pilot in Pittsburgh is using technology that is smart to optimize traffic signals, which is reducing the time it takes for vehicles to stop and idle as well as overall travel time. Created by an Carnegie Mellon professor of robotics, the system combines signals from the past with sensors and artificial intelligence to improve routing within urban road networks.
Adaptive traffic signal control (ATSC) systems depend on sensors to monitor the real-time conditions at intersections and adjust signal timing and phasing. They can be built on various types of hardware, including radar computer vision, radar, and inductive loops that are installed on the pavement. They can also collect data from connected vehicles in C-V2X and DSRC formats. The data is processed at the edge device, or transmitted to a cloud location to be analyzed.
Smart traffic lights are able to adjust the idle time and RLR at busy intersections to keep vehicles moving without slowing down. They can also detect and alert drivers of safety issues such as violations of lane markings, or crossing lanes, assisting to prevent injuries and accidents on city roads.
Smarter controls are also able to address new challenges such as the rise of ebikes, escooters and other micromobility options that have become increasingly popular during the pandemic. These systems monitor vehicles’ movement and apply AI to improve their movements at intersections that are not ideal for their size.
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