Multi-Race Ant Colony Parallel Chaos Search Method for Path Planning on 3-D Terrain Considering Energy Consumption and Travel Distance
Jinlei Wang, Xiaofang Yuan, Guoming Huang, Weihua Tan, Yaonan Wang · IEEE Transactions on Vehicular Technology · 2024
For vehicle navigating on 3-D terrain, it is necessary to consider both energy consumption and travel distance. However, the complex 3-D terrain can lead to low efficiency and local optima in path planning. To address these challenges, a multi-race ant colony parallel chaos search method (MACPCS) is presented in this paper. To precisely evaluate the cost of energy consumption and travel distance, a shortsighted evaluation model is designed, the evaluation model accounts for slope changes in 3-D terrain and mitigates the impact of the terrain beyond the search domain. A multi-race ant colony strategy is proposed in the MACPCS, and three types of ants are deployed in this strategy to search for paths in parallel, ensuring that energy consumption and travel distance are appropriately considered. The optimal path is achieved through a parallel chaos search strategy (with five tracks), and this strategy allows each ant to have different parameters and conduct global search, thus preventing local optima and ensuring high efficiency in 3-D terrain path planning. Simulation results confirm the effectiveness of the MACPCS in finding optimal path and reducing energy consumption for vehicle on 3-D terrain.