Trajectory optimisation method for CAVs considering energy–efficiency balance

With the development of vehicle-to-everything (V2X) technology, connected automated vehicles (CAVs) will be an important part of urban road transportation. However, frequent acceleration, deceleration and rapid stopping at intersections lead to increased energy (fuel) consumption, reduced driving efficiency and balanced benefits. Here, an optimal control model (OCM) for vehicle trajectories is proposed that considers energy–efficiency balance (EEB) based on the characteristics of V2X technology. First, a vehicle trajectory control model was developed based on the intelligent driver model by accounting for the features of V2X technology. The idea of balanced optimisation considering EEB was then introduced and a vehicle trajectory OCM was devised. The proposed model was solved using design algorithms based on the non-dominated sorting genetic algorithm-II. The experimental results showed that the vehicle trajectory OCM could increase the balanced driving efficiency of vehicles within intersections, which is conducive to improving the robustness of the vehicle’s trajectory state, thus proving the effectiveness of the proposed method. The method also provides an important technical basis for the vehicle trajectory optimisation experiments under real V2X environments in the future.