In Pittsburgh, a pilot program is using smart technology to optimize traffic signal timings. This decreases the stop-and-go idle time as well as travel time. The system was developed by technologytraffic.com/2022/04/28/turning-to-data-room-to-gain-a-competitive-advantage-in-ma a Carnegie Mellon professor in robotics and combines existing signals with sensors and artificial intelligent to improve the efficiency of urban roads.
Adaptive traffic signal control (ATSC) systems depend on sensors to observe the conditions at intersections in real-time and adjust the timing of signals and phasing. They can be based upon a variety hardware, including radar, computer vision and inductive loops that are embedded into the pavement. They also can capture vehicle data from connected cars in C-V2X and DSRC formats and then process the data on the edge device, or dispatched to a cloud location to be further analyzed.
Smart traffic lights can alter the time of idle and RLR at busy intersections to ensure that vehicles are moving without slowing them down. They also can identify and warn drivers of safety issues, like lane marking violations or crossing lanes. This helps to reduce accidents and injuries on city roads.
Smarter controls can also help to overcome new challenges such as the rise of e-bikes, e-scooters, and other micromobility options that have become more popular during the outbreak. Such systems can monitor the movements of these vehicles and use AI to improve their movements at intersections for traffic lights, which aren’t well-suited due to their small size and mobility.
