An Extension of Pathfinding Algorithms for Randomly Determined Speeds
Document Type
Conference Proceeding
Publication Date
1-1-2024
Abstract
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.
Identifier
85217670990 (Scopus)
ISBN
[9798350367942]
Publication Title
Conference Proceedings of the IEEE International Performance, Computing, and Communications Conference
External Full Text Location
https://doi.org/10.1109/IPCCC59868.2024.10850316
ISSN
10972641
Fund Ref
New Jersey Institute of Technology
Recommended Citation
Rajesh, Visvam and Wu, Chase Q., "An Extension of Pathfinding Algorithms for Randomly Determined Speeds" (2024). Faculty Publications. 723.
https://digitalcommons.njit.edu/fac_pubs/723