A Refinement-based Formal Development of Cyber-physical Railway Signalling Systems

Author:

Aït-Ameur Yamine1ORCID,Bogomolov Sergiy2ORCID,Dupont Guillaume1ORCID,Iliasov Alexei3ORCID,Romanovsky Alexander2ORCID,Stankaitis Paulius4ORCID

Affiliation:

1. INPT–ENSEEIHT, Toulouse, France

2. Newcastle University, Newcastle upon Tyne, United Kingdom

3. The Formal Route Limited, United Kingdom

4. Newcastle University, United Kingdom

Abstract

For years, formal methods have been successfully applied in the railway domain to formally demonstrate safety of railway systems. Despite that, little has been done in the field of formal methods to address the cyber-physical nature of modern railway signalling systems. In this article, we present an approach for a formal development of cyber-physical railway signalling systems that is based on a refinement-based modelling and proof-based verification. Our approach utilises the Event-B formal specification language together with a hybrid system and communication modelling patterns to developing a generic hybrid railway signalling system model that can be further refined to capture a specific railway signalling system. The main technical contribution of this article is the refinement of the hybrid train Event-B model with other railway signalling sub-systems. The complete model of the cyber-physical railway signalling system was formally proved to ensure a safe rolling stock separation and prevent their derailment. Furthermore, the article demonstrates the advantage of the refinement-based development approach of cyber-physical systems, which enables a problem decomposition and in turn reduction in the verification and modelling effort.

Funder

EPSRC STRATA platform

Air Force Office of Scientific Research

DISCONT Project of the French National Research Agency

Publisher

Association for Computing Machinery (ACM)

Subject

Theoretical Computer Science,Software

Cited by 2 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 Formal Approach for a Railway Level Crossing Using the Event-B Method;Communications in Computer and Information Science;2024

2. Learning domain-heterogeneous speaker recognition systems with personalized continual federated learning;EURASIP Journal on Audio, Speech, and Music Processing;2023-09-05

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