https://technologytraffic.com/2022/08/12/best-data-rooms-providers-for-international-companies
A pilot in Pittsburgh is using smart technology to improve traffic signals, thereby reducing the amount of time a vehicle is idled and stopped, as well as overall travel times. The system was developed by an Carnegie Mellon professor in robotics and integrates existing signals with sensors and artificial intelligent to improve the efficiency of urban road networks.
Adaptive traffic signal control (ATSC) systems rely on sensors to monitor real-time conditions at intersections and adjust signal timing and phasing. They can be based upon different types of hardware, including radar, computer vision or inductive loops that are embedded into the pavement. They also can capture vehicle data from connected vehicles in C-V2X or DSRC formats with data processed at the edge device or dispatched to a cloud location to be further analyzed.
Smart traffic lights can alter the idle time and RLR at busy intersections to ensure that vehicles are moving without slowed down. They can also identify and warn drivers of safety issues, like violations of lane markings, or crossing lanes, assisting to reduce accidents and injuries on city roads.
Smarter controls can also be used to overcome new challenges like the popularity of ebikes, Escooters, and other micromobility devices that have risen during the pandemic. These systems can track these vehicles’ movement and apply AI to better manage their movements at intersections that are not ideal for their size.