Vehicle path planning method adopting hybrid potential field ant colony algorithm

Abstract

The invention discloses a vehicle path planning method adopting a hybrid potential field-ant colony algorithm. The method comprises the steps that 1, vehicle information and environment information are acquired; 2, through analysis of the vehicle information and the environment information, a virtual potential field force currently borne by a vehicle is obtained, and an improved vehicle virtual potential field force model is established; 3, relevant parameters of the ant colony algorithm are initialized; 4, at an initial stage of path planning, an improved virtual potential field resultant force is introduced into the ant colony algorithm to serve as a heuristic information function, a weight coefficient is introduced, and a transition probability function of the ant colony algorithm is improved; 5, along with deepening of obstacle avoidance path planning, pheromone concentration and distance inspiration jointly play a role, the action of improving the potential field resultant force is lowered gradually, and the improved ant colony algorithm is used for performing path planning; and 6, an electronic control unit controls vehicle speed and a turning angle of a steering wheel according to a path planned in the steps 4 and 5. Through the method, stagnation of a path search process is effectively avoided, and path search efficiency is improved.

Description

technical field [0001] The invention relates to an integrated algorithm of path planning and executive mechanism control decision-making under complex dynamic working conditions, and belongs to the technical field of path planning. Background technique [0002] With the continuous development of science and technology, the environment faced by path planning technology will become more complex and changeable. This requires the path planning algorithm to have the ability to quickly respond to complex environmental changes. The ant colony algorithm adopts parallel operation and positive feedback mechanism, which has strong search ability and good robustness. It is a relatively mature path planning algorithm, but it has the disadvantages of randomness, blindness and easy stagnation in the search at the initial stage of operation. The present invention proposes a mixed potential field - Ant colony algorithm, based on the ant colony algorithm, the heuristic information function o...

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Problems solved by technology

The ant colony algorithm adopts parallel operation and positive feedback mechanism, which has strong search ability and good robustness. It is a relatively mature path planning algorithm, but it has the disadvantages of randomness, blindness and easy stagnation in the search at the initial stage of operation. The present invention proposes a mixed potential field - Ant colony algorithm, based on the ant colony algorithm, the heuristic information function of the virtual potential field is introduced, and the influence of the road surface adhesion coefficient and vehicle speed on the path planning is fully considered when the ant colony algorithm is used in the path planning process, and the advantages of the two algorithms are brought into play , to effectively avoid the randomness, blindness and stagnation of the search

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