  Multi-agent path finding (MAPF) is the problem of moving agents to the goal
vertex without collision. In the online MAPF problem, new agents may be added
to the environment at any time, and the current agents have no information
about future agents. The inability of existing online methods to reuse previous
planning contexts results in redundant computation and reduces algorithm
efficiency. Hence, we propose a three-level approach to solve online MAPF
utilizing sustainable information, which can decrease its redundant
calculations. The high-level solver, the Sustainable Replan algorithm (SR),
manages the planning context and simulates the environment. The middle-level
solver, the Sustainable Conflict-Based Search algorithm (SCBS), builds a
conflict tree and maintains the planning context. The low-level solver, the
Sustainable Reverse Safe Interval Path Planning algorithm (SRSIPP), is an
efficient single-agent solver that uses previous planning context to reduce
duplicate calculations. Experiments show that our proposed method has
significant improvement in terms of computational efficiency. In one of the
test scenarios, our algorithm can be 1.48 times faster than SOTA on average
under different agent number settings.
