AI-TOMS

AI-TOMS ensures a safer and more efficient future for transportation networks. Predict traffic volumes, swiftly detect incidents, and automatically implement measures to streamline Transportation Management Center (TMC) operations. AI-TOMS seamlessly integrates with existing infrastructure systems, connected vehicles, and autonomous vehicles, operating in harmony to optimize data ingestion, analysis, and the utilization of TMC data.

This system detects and tracks vehicles coming to a high-speed signalized intersection and determines whether they will be trapped in the Dilemma Zone (DZ)—the area before the stop-bar where drivers have difficulty deciding whether to proceed or stop when the traffic signal turns Yellow. Green signal is extended for these vehicles. When green phase is maxed out, flash beacons turn on ahead of the yellow phase, so drivers have more time to slow down and stop before the stop-bar. Live Signal Phase and Timing (SPaT) data and cloud-based vehicle to everything (V2X) technology is also offered as an in-vehicle warning solution.

Our MV cameras work on an edge computing hub which provides local machine learning capability to process video/images from up to four cameras and generate the traffic metadata. Vehicle count, classification and speed estimation can be done locally and forwarded to a remote server. A user interface software is provided to view the video stream, set up the detection zones and automatically reboot the system during power outages or other unplanned events.