A Multi-Vehicle Formation Path Planning Method in Urban Environments Based on Multi-Objective Optimization

This paper addresses the ground path navigation problem for army combat forces in urban environments and proposes an improved NSGA-II algorithm based on multiobjective optimization to solve the path planning of multiple vehicles with different weights and formations in complex road networks. The proposed method considers various constraints, including road segment load limits, height restrictions, turning radius, and traffic flow. By optimizing path length, travel time, and solution feasibility, it achieves a balance among multiple objectives. Compared with traditional NSGA-II, genetic algorithm, simulated annealing algorithm, and <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathrm{A}^{*}$</tex> algorithm, the improved NSGA-II algorithm demonstrates significant advantages in terms of path quality and solution diversity. Simulation experiments validate the algorithm's effectiveness in practical applications, and the results show that the improved NSGA-II algorithm can provide high-quality path solutions under multi-objective and multi-constraint conditions, meeting the operational needs of complex urban environments.