Visible Light Communication at Urban Intersections to Improve Traffic Signaling and Cooperative Trajectories

Visible Light Communication (VLC) is proposed as an integrated approach to optimize traffic signals and vehicle trajectory at urban intersections. It utilizes light communication between connected vehicles (CVs) and infrastructure to coordinate traffic interaction. Light is used to transmit information between CVs and the infrastructure using streetlamps, intersection signals, and headlights. The system is flexible and adaptive, incorporating different traffic movements during multiple signal phases. The simulation process involves using the SUMO urban mobility simulator to create scenarios and generate traffic flows. VLC mechanisms and relative pose concepts are employed for queue/request/response interactions. A deep reinforcement learning algorithm is used to dynamically control traffic flows, minimizing bottlenecks during rush hour through Vehicle-To-Vehicle (V2V) and Vehicle-To-Infrastructure (V2I) communications. Comparisons with trajectory and signal optimization highlight the benefits in terms of throughput, delay, and vehicle stops, revealing optimal patterns for signals and trajectory.