Vehicle Trajectory Control and Signal Timing Optimization of Isolated Intersection under V2X Environment

This study proposes a two-level optimization model system for vehicle control and signal timing at isolated intersections under the mixed traffic flow environment composed of intelligent connected autonomous vehicles (CAVs) human-driven (CHVs), to minimize energy consumption delay intersections. The proposed two-layer is trajectory fuzzy model. includes signal-oriented car-following oriented former calculates expected acceleration speed commands each time step according coming information, help pass closest intersection without stopping during green light interval; latter uses variable headway (VTH) strategy follow preceding by maintaining safe distance. A microscopic simulator based on SUMO developed test performance algorithm. In simulation experiment, with driving characteristics CHV drivers considered, results show that our performs well CAV penetration rate 30%–60% small or moderate levels flow. average waiting reduced about 25% compared uncontrolled scheme. Under condition 60%, in 17.56% lower than addition, reduces 21.94% scheme only controlling vehicles. When low medium level, are nearly 35%