Motion Coordination of Multiple Autonomous Vehicles in Dynamic and Strictly Constrained Environments

With the increasing applications of fully autonomous vehicles, efficient motion coordination of multi-autonomous vehicles becomes a very important problem as it significantly affects the productivity. This problem is even harder to solve with the increases of the number of autonomous vehicles employed in a dynamic changing environment and constraints to vehicle movement. This paper presents a simultaneous path and motion planning (SiPaMoP) approach to coordinate motions of multi-autonomous vehicles in dynamic and strictly constrained environments. This approach integrates the path planning, collision avoidance and motion planning into a comprehensive model, which has so far not attracted a lot of attention in the academic literature, and optimizes vehicles' path and speed to minimize the completion time of a set of tasks. Simulation results demonstrated that this approach can effectively coordinate the motion of a team of vehicles, and solve the problems of traffic congestion and collision under various traffic conditions