Rescheduling models for railway traffic management in large-scale networks

被引:58
|
作者
Kecman P. [1 ]
Corman F. [2 ]
D'Ariano A. [3 ]
Goverde R.M.P. [1 ]
机构
[1] Department of Transport and Planning, Delft University of Technology, Delft
[2] Center for Industrial Management, Catholic University Leuven, Leuven
[3] Dipartimento di Informatica e Automazione, Università degli Studi Roma Tre, Rome
关键词
Alternative graph; Delay propagation; Macroscopic modeling; Railway traffic management; Timed event graph;
D O I
10.1007/s12469-013-0063-y
中图分类号
学科分类号
摘要
In the last decades of railway operations research, microscopic models have been intensively studied to support traffic operators in managing their dispatching areas. However, those models result in long computation times for large and highly utilized networks. The problem of controlling country-wide traffic is still open since the coordination of local areas is hard to tackle in short time and there are multiple interdependencies between trains across the whole network. This work is dedicated to the development of new macroscopic models that are able to incorporate traffic management decisions. Objective of this paper is to investigate how different levels of detail and number of operational constraints may affect the applicability of models for network-wide rescheduling in terms of quality of solutions and computation time. We present four different macroscopic models and test them on the Dutch national timetable. The macroscopic models are compared with a state-of-the-art microscopic model. Trade-off between computation time and solution quality is discussed on various disturbed traffic conditions. © 2013 Springer-Verlag Berlin Heidelberg.
引用
收藏
页码:95 / 123
页数:28
相关论文
共 50 条
  • [1] Train rescheduling for large-scale disruptions in a large-scale railway network
    Zhang, Chuntian
    Gao, Yuan
    Cacchiani, Valentina
    Yang, Lixing
    Gao, Ziyou
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2023, 174
  • [2] A delay propagation algorithm for large-scale railway traffic networks
    Goverde, Rob M. P.
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2010, 18 (03) : 269 - 287
  • [3] An MPC-Based Rescheduling Algorithm for Disruptions and Disturbances in Large-Scale Railway Networks
    Cavone, Graziana
    van den Boom, Ton
    Blenkers, Lex
    Dotoli, Mariagrazia
    Seatzu, Carla
    De Schutter, Bart
    IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, 2022, 19 (01) : 99 - 112
  • [4] Decomposition and distributed optimization of real-time traffic management for large-scale railway networks
    Luan, Xiaojie
    De Schutter, Bart
    Meng, Lingyun
    Corman, Francesco
    TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2020, 141 (141) : 72 - 97
  • [5] A Railway Timetable Rescheduling Approach for Handling Large-Scale Disruptions
    Veelenturf, Lucas P.
    Kidd, Martin P.
    Cacchiani, Valentina
    Kroon, Leo G.
    Toth, Paolo
    TRANSPORTATION SCIENCE, 2016, 50 (03) : 841 - 862
  • [6] Hybrid deep learning models for traffic prediction in large-scale road networks
    Zheng, Ge
    Chai, Wei Koong
    Duanmu, Jing-Lin
    Katos, Vasilis
    INFORMATION FUSION, 2023, 92 : 93 - 114
  • [7] Risk management in large-scale railway infrastructure projects
    Gardin, D.
    2001, International Railway Congress Association (32):
  • [8] EQUILIBRIUM TRAFFIC ASSIGNMENT FOR LARGE-SCALE TRANSIT NETWORKS
    NGUYEN, S
    PALLOTTINO, S
    EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1988, 37 (02) : 176 - 186
  • [9] Parallel Simulation of Large-scale Microscopic Traffic Networks
    Dai, Wei
    Zhang, Jiachen
    Zhang, Dongliang
    2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 3, 2010, : 22 - 28
  • [10] Lagrangian Models for Controlling Large-Scale Heterogeneous Traffic
    Molnar, Tamas G.
    Upadhyay, Devesh
    Hopka, Michael
    Van Nieuwstadt, Michiel
    Orosz, Gabor
    2019 IEEE 58TH CONFERENCE ON DECISION AND CONTROL (CDC), 2019, : 3152 - 3157