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기록

INTEGRATION-ORIENTED INTELLIGENT SPEED TRAJECTORY OPTIMIZATION METHOD AND SYSTEM FOR AUTONOMOUS TRAIN

발명심사 중
1조회수
9청구항 · 2 독립항
§ Ⅰ

개요

발명자

Hairong DONG; Min ZHOU; Haifeng SONG; Ling LIU; Xiaoyong WANG; Xuan LIU

IPC 분류

B61L 99/G6N 3/92

CPC 분류

B61L99/2G6N3/92B61L2210/2

The present invention relates to an integration-oriented intelligent speed trajectory optimization method and system for an autonomous train. The method includes: constructing an autonomous train speed trajectory optimization model under virtual coupling based on a discrete distance; converting the autonomous train speed trajectory optimization model into a Markov decision process; using a deep reinforcement learning algorithm TD3 to train a neural network and an agent in the Markov decision process, to obtain a trained neural network and agent; and deploying the trained neural network and agent to an autonomous train, to perform an autonomous train speed trajectory optimization decision, so that safe, efficient, and comfortable train autonomous operations can be implemented.

원문 (중국어)

The present invention relates to an integration-oriented intelligent speed trajectory optimization method and system for an autonomous train. The method includes: constructing an autonomous train speed trajectory optimization model under virtual coupling based on a discrete distance; converting the autonomous train speed trajectory optimization model into a Markov decision process; using a deep reinforcement learning algorithm TD3 to train a neural network and an agent in the Markov decision process, to obtain a trained neural network and agent; and deploying the trained neural network and agent to an autonomous train, to perform an autonomous train speed trajectory optimization decision, so that safe, efficient, and comfortable train autonomous operations can be implemented.