A Learning Based Intelligent Train Regulation Method With Dynamic Prediction for the Metro Passenger Flow-Reference-Cited by-同舟云学术

A Learning Based Intelligent Train Regulation Method With Dynamic Prediction for the Metro Passenger Flow

Published:2023-04 Issue:4 Volume:24 Page:3935-3948
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Zhu Li¹^ORCID,Shen Chunzi¹^ORCID,Wang Xi²^ORCID,Liang Hao¹^ORCID,Wang Hongwei³^ORCID,Tang Tao¹^ORCID

Affiliation:

1. State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing, China

2. School of Electronics and Information Engineering and the National Engineering Research Center of Rail Transportation Operation and Control System, Beijing Jiaotong University, Beijing, China

3. National Research Center of Railway Safety Assessment, Beijing Jiaotong University, Beijing, China

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Beijing Natural Science Foundation

Beijing Laboratory and the Beijing Jiaotong University Project

State Key Laboratory of Rail Traffic Control and Safety through Beijing Jiaotong University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Science Applications,Mechanical Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/6979/10086684/10004201.pdf?arnumber=10004201

Reference37 articles.

1. Joint optimal train regulation and passenger flow control strategy for high-frequency metro lines

2. Efficient Bilevel Approach for Urban Rail Transit Operation With Stop-Skipping

3. Real-Time Train Scheduling and Control Based on Model Predictive Control

4. Joint Security and Train Control Design in Blockchain Empowered CBTC System

5. Distributed Optimal Train Adjustment and Waiting Passengers Control for Metro Lines Based on ADMM Algorithm

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