Guidance_Environment_Code_and_Data_v3.1

This file contains the code and data (with guidance and environment files ) of the paper: HMLPA*: A Hierarchical Multi-target LPA* Pathfinding Algorithm Designed for Dynamic Indoor Road Network.Abstract: The Lifelong Planning A* (LPA*) algorithm demonstrates unique advantages in dynamic pathfinding by employing incremental update techniques, efficiently reusing previously computed search results to enable rapid path replanning in dynamic road network environments. However, when changes occur near the starting point or specific positions such as key intersections, bottlenecks, or locations with high connectivity within the road network, even small-scale changes can trigger large-scale adjustments, significantly increasing the re-routing search space and the computational costs of LPA*. To address this limitation, this paper proposes a Hierarchical Multi-target LPA* (HMLPA*) algorithm. HMLPA* partitions the indoor road network into multiple subgraphs using the METIS graph partitioning algorithm and constructs an abstract trunk graph based on the key nodes of these subgraphs, forming a hierarchical indoor road network. By leveraging this hierarchical structure, HMLPA* employs its sub-algorithm, Multi-target LPA* (MLPA*), for initial pathfinding and confines re-routing to affected subgraphs and the abstract trunk graph when road network changes. This localized re-routing approach effectively limits the search scope, significantly reducing computational overhead. Experimental results demonstrate that HMLPA* substantially outperforms LPA* in re-routing efficiency, effectively mitigating the high computational costs associated with dynamic road network environments.