A hybrid framework for synchronized passenger and train traffic simulation in an urban rail transit network-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A hybrid framework for synchronized passenger and train traffic simulation in an urban rail transit network

Published:2022-08-12 Issue: Volume: Page:1-30
ISSN:2324-8378
Container-title:International Journal of Rail Transportation
language:en
Short-container-title:International Journal of Rail Transportation

Author:

Zhang Hongxiang¹²³^ORCID,Lu Gongyuan¹²³^ORCID,Lei Yuanzheng¹²³,Zhang Guangyuan¹²³,Niyitanga Irene¹

Affiliation:

1. School of Transportation and Logistics, Southwest Jiaotong University, Chengdu, China

2. Comprehensive Transportation Key Laboratory of Sichuan Province, Chengdu, China

3. National United Engineering Laboratory of Integrated and Intelligent Transportation, Chengdu, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Informa UK Limited

Subject

Mechanics of Materials,Transportation,Automotive Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/23248378.2022.2109522

Reference48 articles.

1. Modeling and Simulation for Urban Rail Traffic Problem Based on Cellular Automata

2. Urban rail transit planning using a two-stage simulation-based optimization approach

3. Real-time automatic rescheduling strategy for an urban rail line by integrating the information of fault handling

4. Q-learning approach to coordinated optimization of passenger inflow control with train skip-stopping on a urban rail transit line

5. Investigating Bayesian Optimization for rail network optimization

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A hybrid machine learning approach for train trajectory reconstruction under interruptions considering passenger demand;International Journal of Rail Transportation;2024-04-02

2. A multi-agent simulation based train platforming research for facilitating passenger transfer in a high-speed railway station;Simulation Modelling Practice and Theory;2024-01

3. A new approach on passenger flow assignment with multi-connected agents;Physica A: Statistical Mechanics and its Applications;2023-10

4. Railcar Itinerary Optimization in Railway Marshalling Yards: A Graph Neural Network Based Deep Reinforcement Learning Method;2023

5. Railcar Itinerary Optimization in Railway Marshalling Yards: A Graph Neural Network Based Deep Reinforcement Learning Method;2023

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3