Construction of dynamic trafficability map for unmanned vehicles considering multiple environmental factors and path planning

• Published in: Scientific reports Vol. 15; no. 1; pp. 9957 - 16
• Main Authors: Liu, Qingyun, You, Xiong, Zhang, Xin, Zuo, Jiwei
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22.03.2025; Nature Publishing Group; Nature Portfolio
• Subjects: 704/172/4081; 704/2151/213; 704/2151/215; Algorithms; Environmental factors; Humanities and Social Sciences; Improved A algorithm; Multi-element; multidisciplinary; Off-road environment; Path planning; Planning; Science; Science (multidisciplinary); Trafficability map; Vehicles; Path planning; Improved A algorithm; Trafficability map; Off-road environment; Multi-element
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-025-94377-4

Comprehensively considering the off-road trafficability of multiple environmental factors and carrying out optimal path planning is very important for assisting commanders to formulate battlefield maneuvering plans. Previous studies have had issues such as insufficient consideration of environmental factors that affect vehicle trafficability, failure to take into account the impact of meteorological factors on off-road trafficability, failure to consider spatiotemporal dynamic changes in influencing factors, and inaccurate construction of trafficability maps. Therefore, this article constructs a dynamic trafficability map of unmanned vehicles that integrates multiple environmental factors, considers the impact of meteorological factors on vehicle trafficability, takes into account the spatiotemporal dynamic changes of vehicle influencing factors, and conducts research on unmanned vehicle path planning based on the constructed trafficability map and improved A* algorithm. The results indicate that the constructed vehicle dynamic trafficability map can reflect the trafficability of different vehicles at different times. The paths planned by the traditional A* algorithm and the improved A* algorithm are different, and the improved A* algorithm is superior to the paths planned by the traditional A* algorithm. The relevant research provides theoretical and technical guidance for evaluating the trafficability of different vehicles at different times within a region.