93
Views
1
CrossRef citations to date
0
Altmetric
Articles

Modeling and dynamic analysis for a kind of transportation system

, , &
Pages 803-810 | Received 25 Jul 2016, Accepted 26 Jun 2017, Published online: 16 Jan 2018
 

Abstract

Current urban rail transit system must be drastically improved to accommodate the predicted traffic growth. The urban rail transit network of signalized intersections can be suitably modeled as a discrete event system (DES), in which the train flow behavior is described by means of a time-driven model and the traffic dynamics are represented by a discrete event model. In this paper, we propose a max-plus general modeling framework adapted to the optimal control of traffic flow. The open-loop and closed-loop control models of train flow were established firstly. The max-plus model of such a network is used to state and solve the problem of coordinating several traffic flows with the aim of improving the performance of urban rail transit system. Starting from the state evolution of the urban rail transit system, the system stability and periodic steady-state analysis were presented. The main focus is to obtain key features of urban rail transit system and extend the framework by introducing new analysis techniques.

Acknowledgements

The authors are grateful to the anonymous reviewer for the comments and suggestions which have helped to improve the quality of the paper.

Notes

Please note this paper has been re-typeset by Taylor & Francis from the manuscript originally provided to the previous publisher.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 277.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.