Research on global path planning of intelligent vehicles based on improved ant colony algorithm

Abstract

According to the needs of intelligent vehicles, this paper proposes a global path planning algorithm based on improved ant colony algorithm to address the problems of slow convergence speed and multiple path bends in ant colony algorithm. By redefining the heuristic function of ant colony algorithm, adopting fallback and fill mechanisms, setting safe distances, modifying pheromone concentration update rules, and limiting the range of pheromone concentration, the ant colony algorithm is improved. And by deleting redundant points on the path, selecting key turning points and cubic B-spline curves for path smoothing, the planned path is shortest and smooth, which can meet the needs of path following. Through simulation, the improved ant colony algorithm has the advantages of fast convergence and smooth path.