Generation method and device for decision network model of vehicle automatic driving

Abstract

The invention is applicable to the field of computer technology and provides a generation method and device for a decision network model of vehicle automatic driving. The method comprises the steps that a sample triad corresponding to each test moment is generated according to vehicle state information collected at each test moment, a preset vehicle movement set and a preset return function, all the sample triads are stored as sample data in a pre-established experience database, and all the sample data is subjected to clustering analysis; training samples are uniformly collected from each cluster obtained after clustering analysis of the experience database according to a preset sampling scale value, and a return accumulated value of each training sample is calculated; and according to all the training samples, the return accumulated value of each training sample and a preset deep learning algorithm, training is performed to obtain the decision network model of vehicle automatic driving. Therefore, the training efficiency of the decision network model and the generalization ability of the decision network model are effectively improved.

Description

technical field [0001] The invention belongs to the technical field of computers, and in particular relates to a method and device for generating a decision network model for automatic driving of vehicles. Background technique [0002] With the development of the economy and the advancement of urbanization, the global car ownership and road mileage are gradually increasing, resulting in a series of problems that cannot be properly solved by traditional cars, such as traffic congestion, accidents, pollution, and shortage of land resources. Self-driving car technology is seen as an effective solution to these problems, and its development has attracted much attention. [0003] Driverless cars, that is, driving on the road through their own assisted driving system without a driver, have the ability to perceive the environment. At present, the control method of the assisted driving system is mainly rule-based control decision-making, that is, according to the known driving expe...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a method and device for generating a decision-making network model for automatic driving of vehicles, aiming at solving the problem that the training efficiency of the decision-making model for automatic driving of vehicles is low, and the learning ability of the vehicle decision-making model is relatively weak and cannot be improved. Adapt to different routes and scenarios

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