Prioritized Anytime Dynamic A* Path Planning for Multi-Agent Vehicles in Heterogeneous Traffic

Abstract

For a centralized path planning in the multi-agent path finding (MAPF), especially for road vehicles using traffic rules, a prioritized planning algorithm is one of the key methods that deal with real-time problems. The time used for planning is limited, especially when a number of agents are present, and a suboptimal solution has to be found. If possible, the previous solution should be reused for the replanning. Anytime Dynamic A* (AD*) can both replan the path when the environment is changed dynamically and is able to return a safe, but potentially suboptimal solution in case where a maximum cycle time is exceeded. A prioritized order selection is based on the path length to the goal. To model heterogeneous traffics with vehicles and pedestrians, a combination of the bicycle and pedestrian obstacle reciprocal collision avoidance algorithms (B-ORCA and PORCA) is used to realize a naturalistic interaction among the multi-agent system and the dynamic environment. The number of agents and of dynamic obstacles is randomly generated and the time used for planning is analyzed in view of the limited time available in the simulations. In this work, the path planning of up to three agents can be executed in real-time in MATLAB.