Automatic driving system and method based on relative-entropy deep and inverse reinforcement learning

Abstract

The invention relates to an automatic driving system based on relative-entropy deep and inverse reinforcement learning. The system comprises a client, a driving basic data collection sub-system and astorage module, wherein the client displays a driving strategy; the driving basic data collection sub-system collects road information; the storage module is connected with the client and the drivingbasic data collection sub-system and stores the road information collected by the driving basic data collection sub-system. The driving basic data collection sub-system collects the road information and transmits the road information to the client and the storage module; the storage module receives the road information, stores a piece of continuous road information into a historical route, conducts analysis and calculation according to the historical route so as to simulate the driving strategy, and transmits the driving strategy to the client so that a user can select the driving strategy; the client receives the road information and implements automatic driving according to the selection of the user. In the automatic driving system, the relative-entropy deep and inverse reinforcement learning algorithm is adopted, so that automatic driving under the model-free condition is achieved.

Description

technical field [0001] The invention relates to an automatic driving system and method based on relative entropy deep inverse reinforcement learning, belonging to the technical field of automatic driving. Background technique [0002] With the increase of the number of cars in our country, road traffic congestion is becoming more and more serious, and the annual traffic accidents are also rising. In order to better solve this problem, it is necessary to research and develop auto-driving systems. And with the improvement of people's pursuit of quality of life, people hope to be liberated from tiring driving activities, and automatic driving technology has emerged as the times require. [0003] An existing auto-driving system for a vehicle uses a camera installed in the driver's cab and an image recognition system to identify the driving environment, and then the vehicle's main control computer, GPS positioning system, and path planning software provide information on the vehi...

AI Technical Summary

Problems solved by technology

[0004] In the above autopilot system, since the road map is pre-stored in the vehicle, the update of its data depends on the manual operation of the driver, and the update frequency cannot be guaranteed. There is no latest information about roads in the resources, so the final data cannot reflect the current road conditions, which eventually leads to unreasonable driving routes and low navigation accuracy, which brings inconvenience to driving

Moreover, most of the autopilot systems currently in the field of autopilot technology still require manual intervention, and cannot achieve complete autopilot.

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