Distributed edge signal control for cooperating pre-planned connected automated vehicle path and signal timing at edge computing-enabled intersections

The emerging technologies in both wireless communication and automation driving that have enabled vehicles to communicate with infrastructure, and with each other, are collectively known as connected vehicle and automated vehicle (CAV) technology. In existing connected automated vehicle-based and traditional traffic control systems, urban arterials with signalized intersections still face issues, including local demand uncertainty and automation level compatibility. Here, a distributed signal control system that integrates automated vehicle path planning information is adapted to address these issues. The proposed method includes planning-based local demand estimation and demand-aware max pressure control in an edge computing environment. A bivariable automation model is developed to represent the various, i.e., L1-L5, automatic driving levels. A real district with typical scenarios is implemented to verify the proposed method. The simulation results show that the proposed demand-aware edge control provides better control results than benchmarks for almost all different performance indices and network demands. The proposed control reduces the waiting time by up to 30%, and the time loss decreased by up to 20%. Moreover, better performances are always obtained at different automation levels, so there is a good compatibility of the automation driving for the adaptation of the CAV flows, especially at the L3L5 levels.