Title:
AUTOMATIC DRIVING SYSTEM AND METHOD BASED ON RELATIVE-ENTROPY DEEP INVERSE REINFORCEMENT LEARNING
Document Type and Number:
WIPO Patent Application WO/2019/071909
Kind Code:
A1
Abstract:
An automatic driving system based on relative-entropy deep inverse reinforcement learning, comprising: (1) a client configured to display a driving strategy; (2) a basic driving data collection sub-system configured to collect road information; and (3) a storage module connected to the client and the basic driving data collection sub-system and configured to store the road information collected by the basic driving data collection sub-system, wherein the basic driving 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 as a historical route, conducts analytical calculation according to the historical route to simulate the driving strategy, and transmits the driving strategy to the client for user selection; and the client receives the road information and implements automatic driving according to the selection of the user. The system adopts the relative-entropy deep inverse reinforcement learning algorithm to achieve automatic driving under a model-free condition.
More Like This:
JP3702738 | BAGGAGE CARRYING FACILITY |
JP2022013388 | MOVING BODY |
JPH06187032 | MARKER FOR MOBILE ROBOT AND INFORMATION DETECTOR AND TRAVELING CONTROLLER |
Inventors:
LIN JIAHAO (CN)
ZHANG ZONGZHANG (CN)
ZHANG ZONGZHANG (CN)
Application Number:
PCT/CN2018/078740
Publication Date:
April 18, 2019
Filing Date:
March 12, 2018
Export Citation:
Assignee:
ZHANGJIAGANG INST IND TECH SOOCHOW UNIV (CN)
International Classes:
G05D1/02
Foreign References:
CN107544516A | 2018-01-05 | |||
CN105718750A | 2016-06-29 | |||
CN103699717A | 2014-04-02 |
Other References:
LU CHENJIE: "The Research of Apprenticeship Learning Algorithm Applied in thr Unmanned Car High-Speed Driving in the Simulated Environnment", ELECTRONIC TECHNOLOGY & INFORMATION SCIENCE, CHINA MASTER'S THESE FULL-TEXT DATABASE, 15 June 2013 (2013-06-15), pages 19-21 - 32-45, ISSN: 1674-0246
Attorney, Agent or Firm:
SUZHOU JINHE INTELLECTUAL PROPERTY AGENCY(SPECIAL GENERAL PARTNERSHIP) (CN)
Download PDF: