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Formal Modelling of the Multiple Trains Following Operation in Uncertain Environments

  • Xia Wang
  • , Yang Xu
  • , Jun Liu
  • , Guanfeng Wu
  • , Shuwei Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Ensuring the safety of the following operation under moving block signal is very important for safe operation. Now that the Train Control system under Moving Block Signal (TC-MBS) is a distributed, complex, dynamic, and highly interactive system, the proposed method uses the Multi-Agent System (MAS) technique to design, model, and analyse the TC-MBS system. This paper describes implementing formal methods for modelling the TC-MBS system that operates in an uncertain environment and its safety verification based on model checking techniques. First, the multi-mode following operation in an uncertain environment is analysed using the decision table technique. Second, we introduce a creative modelling approach for MAS called UML-MAS to build the semi-formal model of the TC-MBS system. UML-MAS acts as a standard interface for the system designers and infrastructure managers to increase their requirement comprehension, analysis, system design, and scheme planning at the conceptual level. Thirdly, a set of rules is suggested to convert UML-MAS model into Vector-based Interpreted Systems Programming Language (VISPL) model, which serves as the input for the model checker MCMAS- T. In order to demonstrate the practicality and effectiveness of the suggested approach, some case studies on modelling the TC-MBS systems while considering various scenarios in an uncertain environment and their verification employing MCMAS- Tare presented.
Original languageEnglish
Title of host publicationISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering
PublisherIEEE
Pages450-457
Number of pages8
ISBN (Electronic)9798350318401
ISBN (Print)979-8-3503-1841-8
DOIs
Publication statusPublished (in print/issue) - 8 Apr 2024
Event18th International Conference on Intelligent Systems and Knowledge Engineering - Fuzhou, China
Duration: 17 Nov 202319 Nov 2023
Conference number: 18
http://www.iske2023.com

Publication series

NameISKE 2023 - 18th International Conference on Intelligent Systems and Knowledge Engineering

Conference

Conference18th International Conference on Intelligent Systems and Knowledge Engineering
Abbreviated titleISKE 2023
Country/TerritoryChina
CityFuzhou
Period17/11/2319/11/23
Internet address

Bibliographical note

Publisher Copyright:
© 2023 IEEE.

Funding

This work was supported by the National Natural Science Foundation of China (No.61976130, 62366017), the Chengdu International Science Cooperation Project under Grant 2020-GH02-00064-HZ.

FundersFunder number
National Natural Science Foundation of China61976130, 62366017
2020-GH02-00064-HZ

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 9 - Industry, Innovation, and Infrastructure
      SDG 9 Industry, Innovation, and Infrastructure
    2. SDG 11 - Sustainable Cities and Communities
      SDG 11 Sustainable Cities and Communities

    Keywords

    • Knowledge engineering
    • Interactive systems
    • Unified modeling language
    • Model checking
    • Control systems
    • Safety
    • Planning
    • train control system
    • uncertain environment
    • formal models
    • model checking
    • multi-agent systems
    • multi-agent system

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