Path planning based on a new genetic algorithm

Starting from the disadvantage and two research results of the convergence of the previous genetic algorithm, three operations are added to the standard genetic algorithm to make the algorithm converge to a global optimum without the change of the search randomicity. A path planning method is proposed using the fitness of the roadside constraint, dynamic obstacle avoidance and the shortest distance based on the new genetic algorithm. The simulation results showed that the proposed method is effective, correct and highly real-time. Furthermore, compared with the path planning method based on the previous modified genetic algorithm from experiments, the proposed one has much better performance in the less time required and the shorter distance travelled.