Pathfinding on large maps is time-consuming. Classical search algorithms such as Dijkstra's and A* algorithms may solve difficult problems in polynomial time. However, in real-world pathfinding examples where the search space increases dramatically, these algorithms are not appropriate. Hierarchical pathfinding algorithms that provide abstract plans of future routing, such as HPA* and PRA*, have been explored by previous researchers based on classical ones. Although the two hierarchical algorithms show improvement in efficiency, they only obtain near optimal solutions. In this paper, we introduce the Hierarchical Shortest Path algorithm (HSP) and a hybrid of the HSP and A* (HSPA*) algorithms, which find optimal solutions in logarithmic time for numerous examples. Our empirical study shows that HSP and HSPA* are superior to the classical algorithms on realistic examples, and our experimental results illustrate the efficiency of the two algorithms. We also demonstrate their applicability by providing an overview of our Route Planner project that applies the two algorithms proposed in this paper.
['Suling Yang', 'Alan K. Mackworth']
Hierarchical Shortest Pathfinding Applied to Route-Planning for Wheelchair Users