Research On 3D Path Planning Method For Vehicle Of Weighing Energy Consumption And Distance

The appearance of vehicle has promoted the development of the world economy,and has a great impact on our life,making our life more convenient.However,with the continuous increase of vehicle ownership,many environmental problems appear,the emission and energy consumption of vehicles need to be solved by enterprises all over the world.Therefore,many enterprises began to promote the transformation of traditional vehicle industry,combined with electronic information technology,put forward the "new four modernizations" of the vehicle industry,which makes the vehicle industry develop towards the electric,network,intelligent and sharing.Based on this development background,different from the traditional research on improving vehicle endurance(reducing energy consumption)from the perspective of control strategy and energy management,this paper proposes a solution from the perspective of path planning.Vehicle path planning is an inevitable trend of "new four modernizations" in the vehicle industry,and has broad research value and significance in the fields of industry,military and transportation.Based on the traditional 2D path planning method,this paper extends the map to3 D,and adds energy consumption target,designs the vehicle three-dimensional path planning method,which enables the vehicle to weigh the energy consumption and distance objectives for path planning in 3D topographic map and road network map.The specific research contents of this paper include:Firstly,the grid method is used to establish 3D topographic map and road network map,and the basic principles of traditional path planning methods are introduced(A*algorithm and ant colony algorithm).Then,according to the characteristics of 3D map,the appropriate calculation model of energy consumption and distance value is established;Finally,the principle of multi-objective optimization algorithm is introduced,which provides a theoretical basis for the 3D path planning for vehicles of weighing energy consumption and distance in the following chapters.Secondly,aiming at the problem that the traditional ant colony algorithm is inefficient in 3D map search and prone to local optimization,the path search guidance strategy and pheromone updating factor are designed,and parallel search is introduced to improve the ant colony algorithm process.In order to make ant colony algorithm be able to balance energy consumption and distance for path planning,a new heuristic function is designed to evaluate the energy consumption and distance The energy consumption pheromone and distance pheromone are introduced to replace the traditional single pheromone.The multi-objective optimization algorithm is designed to optimize the path of ant colony algorithm,compromise the path of energy consumption and distance value,and compare it with the traditional ant colony algorithm in the random terrain map.The results verify the superiority of the method in the application of 3D path planning,and provide an effective solution for the design of 3D path planning method.Thirdly,A* algorithm is designed to balance the energy consumption value and distance value to solve the problems of low efficiency and unreasonable search path in traditional three-dimensional A* algorithm;the chaos multi-objective algorithm is designed to adjust the parameters in the heuristic function of A* algorithm for the two targets of energy consumption value and distance value.The optimization results show that the method can find the path of the compromise between energy consumption value and distance value;in the case of traditional A* algorithm,the search efficiency is low and the search path is unreasonable;the optimization results show that the method can find the path of the compromise between energy consumption value and distance value;in different 3D topographic maps,the method is compared with the traditional A*algorithm.The experimental results verify the advantages of the method in the application of 3D path planning;finally,the A* algorithm is tested on the road network map and compared with the traditional A* algorithm.The results show that the method can reduce the energy consumption value of the vehicle in the condition of increasing a small distance value,and thus can reduce the energy consumption value for the vehicle to drive the vehicle and provide an effective solution.