Method and device for determining driving strategy based on reinforcement learning and rule

A driving strategy and reinforcement learning technology, applied in neural learning methods, character and pattern recognition, instruments, etc., can solve the problems of high model training time cost, inability to apply automatic driving, and high time cost of reinforcement learning model training, and achieve reasonable improvement. Effects of Sex and Stability

Active Publication Date: 2018-05-08
UISEE TECH BEIJING LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In the existing vehicle driving process, the vehicle control of the vehicle, especially the automatic driving vehicle, is mainly realized through the following methods: Rule-based automatic driving technology, that is, the vehicle control is realized by using the rule algorithm. According to the logic formula, the state input The output control value is directly obtained from the output control value. This type of algorithm is simple to implement, does not require training, and the output result of the control algorithm is predictable and relatively stable. However, the algorithm is not intelligent, and it is easy to be robbed of the right of way in the complex scene of real driving. , so the a

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  • Method and device for determining driving strategy based on reinforcement learning and rule
  • Method and device for determining driving strategy based on reinforcement learning and rule
  • Method and device for determining driving strategy based on reinforcement learning and rule

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Embodiment Construction

[0029] The application will be described in further detail below in conjunction with the accompanying drawings.

[0030] In a typical configuration of the present application, a terminal, a device serving a network, and a computing device include one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0031] Memory may include non-permanent storage in computer readable media, in the form of random access memory (RAM) and / or nonvolatile memory such as read only memory (ROM) or flash RAM. Memory is an example of computer readable media.

[0032] Computer-readable media, including both permanent and non-permanent, removable and non-removable media, can be implemented by any method or technology for storage of information. Information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memo...

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Abstract

The purpose of the present application is to provide a method or a device for determining a driving strategy based on reinforcement learning and rule fusion. The method comprises: based on the drivingparameter information of a vehicle, determining first driving strategy information of the vehicle through a reinforcement learning algorithm; based on the driving parameter information and the driving rule information of the vehicle, performing rationality detection on the first driving strategy information; and determining target driving strategy information of the vehicle based on the detectionresult of the rationality detection. Compared with the prior art, according to the technical scheme of the present application, the first driving strategy information calculated and determined by thereinforcement learning algorithm is constrained by the rule, so that the method for determining the driving strategy provided by the present application is more intelligent than the existing method for implementing vehicle control by using the rule algorithm, or the method for implementing vehicle control by using the reinforcement learning algorithm, and the rationality and stability of the finally determined driving strategy are improved.

Description

technical field [0001] This application relates to the field of automatic driving, in particular to a technology for determining driving strategies based on reinforcement learning and rules. Background technique [0002] In the existing vehicle driving process, the vehicle control of the vehicle, especially the automatic driving vehicle, is mainly realized through the following methods: Rule-based automatic driving technology, that is, the vehicle control is realized by using the rule algorithm. According to the logic formula, the state input The output control value is directly obtained from the output control value. This type of algorithm is simple to implement, does not require training, and the output result of the control algorithm is predictable and relatively stable. However, the algorithm is not intelligent, and it is easy to be robbed of the right of way in the complex scene of real driving. , so the algorithm cannot effectively cope with the complex scene of real d...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06N3/08
CPCG06N3/08G06F18/214G06F18/25
Inventor 许稼轩周小成
Owner UISEE TECH BEIJING LTD
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