An Extension of Pathfinding Algorithms for Randomly Determined Speeds

Pathfinding is the search of an optimal path between two points on a graph. This paper investigates the performance of pathfinding algorithms in 3D voxel environments, focusing on optimizing paths for both time and distance. Utilizing computer simulations in Unreal Engine 5, four algorithms—A*, Dijkstra’s algorithm, Dijkstra’s algorithm with speed consideration, and a novel adaptation referred to as Time*—are tested across various environment sizes. Results indicate that while Time* exhibits a longer execution time than A*, it significantly outperforms all other algorithms in traversal time optimization. Despite slightly longer path lengths, Time* can compute more efficient paths. Statistical analysis of the results suggests consistent performance of Time* across trials. Implications highlight the significance of speed-based pathfinding algorithms in practical applications and suggest further research into optimizing algorithms for variable speed environments.