Cooperative optimization method for connected vehicles and traffic signals via C-V2X

To address the inefficiency of intersections from independent control of vehicles and traffic signals in traditional transportation, a cooperative optimization method for connected vehicles and traffic signals via C-V2X (cellular vehicle-to-everything) was proposed. A closed-loop architecture integrating perception, communication, decision-making, and control was designed, leveraging edge intelligence to empower real-time traffic decision-making. A cooperative optimization algorithm, comprising a traffic pressure-based signal phase adjustment strategy and a state machine-based vehicle speed guidance strategy, was developed to achieve the collaborative optimization of signal phases and vehicle speeds. Hardware experiments and traffic flow simulation results demonstrate that the proposed method meets the requirements for hardware deployment and real-time response, effectively reducing vehicle travel time at intersections and improving traffic efficiency.