Decision-making method, device and equipment for automatic driving equipment and readable storage medium

Abstract

The invention relates to the technical field of automatic driving, and discloses a decision-making method and device for automatic driving equipment, the equipment and a readable storage medium. The method comprises the following steps: acquiring local environment state information corresponding to each piece of automatic driving equipment, driving actions of each piece of automatic driving equipment, return parameter values for executing the driving actions and local update environment state information; determining a learning action value of a vehicle group corresponding to each automatic driving device based on the local environment state information and the driving action corresponding to each automatic driving device; determining a target action value of the vehicle group based on the return parameter value and the local update environment state information after each automatic driving device executes the driving action; and updating a driving decision strategy of the vehicle group based on the learning action value and the target action value. According to the invention, the updating of the vehicle group driving decision strategy is realized, the explosion problem of the training dimension is avoided, and the safety and the high efficiency of the driving decision strategy are improved.

Description

technical field [0001] The present invention relates to the technical field of automatic driving, in particular to a decision-making method, device, device and readable storage medium of automatic driving equipment. Background technique [0002] With the rapid development of artificial intelligence technology, deep learning has been widely used in task scenarios such as environment perception, feature extraction, obstacle recognition, path planning and intelligent decision-making of self-driving cars, and has been used in simulation simulators and simple real traffic scenarios. Better to achieve. Among them, in the technical route represented by deep reinforcement learning, self-driving vehicles, as agents, do not need the massive environmental state-driving action data provided by human drivers to train driving strategies, but use the Markov decision-making process to continuously interact with the traffic environment , to explore and improve autonomous driving policies fr...

AI Technical Summary

Problems solved by technology

[0003] In view of this, the embodiments of the present invention provide a decision-making method, device, device and readable storage medium for automatic driving equipment, so as to solve the problem that it is difficult to balance the safety of automatic driving vehicle group decision-making and the cost of driving strategy training at the same time

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