@inproceedings{0c55128f10164dea8db2329b78ca981d,
title = "Timetable Rescheduling for High-Speed Railways Considering Dynamical Train Groups in Case of Disturbances",
abstract = "High-speed railways are susceptible to emergencies that may cause trains to deviate from their original timetable. How to restore the disrupted timetable to normal conditions as soon as possible in case of disturbances is an important concern. This paper studies the dynamic rescheduling method of train groups in virtual coupling mode by considering a strategy for adjacent trains to depart the station. The mixed-integer linear programming (MILP) timetable rescheduling model is formulated taking into account the dynamical train groups. Five stations of the Beijing-Shanghai high-speed railway are used to verify the proposed method. The experiment results show that the timetable rescheduling method considering dynamical train groups under virtual coupling mode can reduce the average delay time and the number of delayed trains while reducing the impact caused by disturbances.",
keywords = "Disturbances, Dynamical train groups, High-speed railways, Timetable rescheduling, Virtual coupling",
author = "Min Zhou and Xuan Liu and Xingtang Wu and Haifeng Song and Hairong Dong",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 5th Chinese Conference on Swarm Intelligence and Cooperative Control, CCSICC 2021 ; Conference date: 19-01-2022 Through 22-01-2022",
year = "2023",
doi = "10.1007/978-981-19-3998-3\_168",
language = "英语",
isbn = "9789811939976",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "1808--1819",
editor = "Zhang Ren and Yongzhao Hua and Mengyi Wang",
booktitle = "Proceedings of 2021 5th Chinese Conference on Swarm Intelligence and Cooperative Control",
address = "德国",
}