A vehicle obstacle avoidance trajectory planning and tracking control method

Abstract

The invention belongs to the technical field of vehicle obstacle avoidance control methods, and discloses a vehicle obstacle avoidance trajectory planning and tracking control method, which decomposes the obstacle avoidance process into two parts: trajectory planning based on optimization and trajectory tracking control based on model predictive control. Based on the three-segment sinusoidal curve of acceleration, a trajectory optimization problem with time optimization and multiple constraints is established, and the optimal trajectory for obstacle avoidance is obtained through optimization; a two-degree-of-freedom vehicle control model is established, and the path Tracking performance and optimal steering angle are used as cost functions, and an optimal trajectory tracking controller based on the idea of ​​model predictive control is designed to achieve effective obstacle avoidance.

Description

technical field [0001] The invention belongs to the technical field of vehicle obstacle avoidance control methods, in particular to a vehicle obstacle avoidance trajectory planning and tracking control method. Background technique [0002] At present, automobile intelligence has become a research hotspot in the field of automobile industry and vehicle engineering, and vehicle obstacle avoidance control technology has received the focus and extensive research of the academic circles. In the existing vehicle obstacle avoidance control technology research, the control method of obstacle avoidance path planning and tracking is usually adopted, which is also the most effective control scheme for vehicle obstacle avoidance at present. For the planning of obstacle avoidance paths, it usually includes artificial potential field method, intelligent optimization algorithm, etc. Among them, the artificial potential field method is a kind of virtual force method, which regards the movem...

AI Technical Summary

Problems solved by technology

For the planning of obstacle avoidance paths, it usually includes artificial potential field method, intelligent optimization algorithm, etc. Among them, the artificial potential field method is a kind of virtual force method, which regards the movement of the vehicle in the surrounding environment as the vehicle in the artificially established virtual force field. The path planned by the artificial potential field method is generally smooth and safe, the algorithm is simple, and the real-time performance is good, but the smart car is easy to fall into the local optimum; and for the intelligent optimization algorithm, the fuzzy logic algorithm is often used, which is based on According to human experience, a fuzzy control rule base is designed, the information obtained by the sensor is used as input, and the required output of the vehicle is obtained through fuzzy reasoning. However, fuzzy rules are often preset by people through experience, so the flexibility is poor and cannot be learned.

[0003] For the tracking control of the obstacle avoidance path, the LQR method is usually used, but this method does not consider the target path in front of the preview, which is prone to the problem of large tracking error

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