Multiple Vehicles Merging Control via Sequence and Trajectory Optimization

In multi-lane traffic scenarios, accidents, construction, and other conditions will reduce the number of lanes, and vehicles need to decelerate, merge and pass. Therefore, vehicles merging is a hot topic in multi-vehicle cooperative driving. The existing primary methods focus on merging trajectory optimization based on the known sequence of merging and mainly consider the longitudinal model. Simulated annealing algorithm combined with Sequential Quadratic Programming is used to optimize the merging sequence and the corresponding trajectories. Numerical simulation verifies the stability and feasibility of the algorithm. Finally, the micro intelligent vehicles based simulation platform is introduced to carry out the merging experiment which proves the effectiveness of the proposed algorithm.