Real-time trajectory planning method for autonomous vehicle

Abstract

The invention discloses a real-time trajectory planning method for an autonomous vehicle. The real-time trajectory planning method comprises the steps of: S1, acquiring relevant information of the autonomous vehicle in real time; S2, generating a reference trajectory, a feasible trajectory cluster determined by means of the reference trajectory and a speed corresponding to each feasible trajectoryin the feasible trajectory cluster based on the relevant information of the autonomous vehicle; S3, calculating an action of each feasible trajectory according to the feasible trajectories and the corresponding speeds thereof by utilizing a target optimization function taking safety and efficiency as targets, and selecting the feasible trajectory with the least action as the expected optimal trajectory, and carrying out optimization to obtain an expected optimal velocity corresponding to the expected optimal trajectory, wherein the target optimization function is obtained according to the principle of least action and an equivalent force method. The real-time trajectory planning method can enable the autonomous vehicle to imitate driving features of a driver in an unknown environmental condition, and can plan a trajectory that best meets the driver's driving expectation by taking the safety and efficiency as the driving targets according to the surrounding vehicles and environmental information in real time.

Description

technical field [0001] The invention relates to the field of automatic driving, in particular to a real-time trajectory planning method for an automatic driving vehicle. Background technique [0002] Intelligent vehicles refer to vehicles that install sensors, controllers, and actuators on the basis of traditional vehicles, and realize the ability to transport people and goods through technologies such as environmental perception, artificial intelligence, and automatic control. Intelligent driving technology helps to improve the safety and comfort of vehicle driving, and has received extensive attention from academia and industry. Trajectory planning is one of the core technologies in the field of unmanned driving. Vehicle trajectory planning refers to knowing the initial state of the vehicle, the target state, and the distribution of obstacles in the environment, and planning a possible path that does not collide with obstacles and satisfies the kinematic constraints, envi...

AI Technical Summary

Problems solved by technology

The biggest advantage of this method is that the real-time performance is very good, but the design of fuzzy membership functions and the formulation of fuzzy control rules mainly rely on human experience. How to obtain the optimal membership functions and control rules is the biggest problem of this method.

In recent years, some scholars have introduced neural network technology and proposed a method of fuzzy neural network control, which has good effect but is too complicated.

Images