Smart Technologies for Traffic Signals
In Pittsburgh the pilot program is using smart technology to optimize traffic signal timings. This can reduce the amount of time that vehicles stop and idle time as well as travel time. The system was created by an Carnegie Mellon professor in robotics and combines signals that are already in use with sensors and artificial intelligent to improve the flow of traffic on urban road networks.
Adaptive traffic signal control (ATSC) systems rely on sensors to monitor the real-time conditions at intersections and adjust the timing and phasing of signals. They can be based on a variety of hardware, including radar computer vision, radar, and inductive loops incorporated into the pavement. They also can capture vehicle data from connected cars in C-V2X and DSRC formats and then process the data by the edge device or dispatched to a cloud location for further analysis.
Smart traffic lights can alter the idling speed and RLR at busy intersections to keep vehicles moving without slowed down. They can also spot safety issues such as lane marking violations and crossing lanes and notify drivers, which can help reduce accidents on city roads.
Smarter controls also can help in tackling new challenges, such as the rise of e-bikes, e-scooters, and other micromobility options that have become increasingly popular since the pandemic. These systems can track these vehicles’ movement and apply AI to help manage their movements at intersections that are not well-suited for their small size.