Ten Diverse Formal Models for a CBTC Automatic Train Supervision System
Communications-based Train Control (CBTC) systems are metro signalling platforms, which coordinate and protect the movements of trains within the tracks of a station, and between different stations. In CBTC platforms, a prominent role is played by the Automatic Train Supervision (ATS) system, which...
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2018-03-01
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Online Access: | http://arxiv.org/pdf/1803.10324v1 |
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doaj-239a7043df644bd0a5ebd3683d5f6f5e2020-11-25T01:48:42ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802018-03-01268Proc. MARS/VPT 201810414910.4204/EPTCS.268.4:5Ten Diverse Formal Models for a CBTC Automatic Train Supervision SystemFranco Mazzanti0Alessio Ferrari1 ISTI-CNR ISTI-CNR Communications-based Train Control (CBTC) systems are metro signalling platforms, which coordinate and protect the movements of trains within the tracks of a station, and between different stations. In CBTC platforms, a prominent role is played by the Automatic Train Supervision (ATS) system, which automatically dispatches and routes trains within the metro network. Among the various functions, an ATS needs to avoid deadlock situations, i.e., cases in which a group of trains block each other. In the context of a technology transfer study, we designed an algorithm for deadlock avoidance in train scheduling. In this paper, we present a case study in which the algorithm has been applied. The case study has been encoded using ten different formal verification environments, namely UMC, SPIN, NuSMV/nuXmv, mCRL2, CPN Tools, FDR4, CADP, TLA+, UPPAAL and ProB. Based on our experience, we observe commonalities and differences among the modelling languages considered, and we highlight the impact of the specific characteristics of each language on the presented models.http://arxiv.org/pdf/1803.10324v1 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Franco Mazzanti Alessio Ferrari |
spellingShingle |
Franco Mazzanti Alessio Ferrari Ten Diverse Formal Models for a CBTC Automatic Train Supervision System Electronic Proceedings in Theoretical Computer Science |
author_facet |
Franco Mazzanti Alessio Ferrari |
author_sort |
Franco Mazzanti |
title |
Ten Diverse Formal Models for a CBTC Automatic Train Supervision System |
title_short |
Ten Diverse Formal Models for a CBTC Automatic Train Supervision System |
title_full |
Ten Diverse Formal Models for a CBTC Automatic Train Supervision System |
title_fullStr |
Ten Diverse Formal Models for a CBTC Automatic Train Supervision System |
title_full_unstemmed |
Ten Diverse Formal Models for a CBTC Automatic Train Supervision System |
title_sort |
ten diverse formal models for a cbtc automatic train supervision system |
publisher |
Open Publishing Association |
series |
Electronic Proceedings in Theoretical Computer Science |
issn |
2075-2180 |
publishDate |
2018-03-01 |
description |
Communications-based Train Control (CBTC) systems are metro signalling platforms, which coordinate and protect the movements of trains within the tracks of a station, and between different stations. In CBTC platforms, a prominent role is played by the Automatic Train Supervision (ATS) system, which automatically dispatches and routes trains within the metro network. Among the various functions, an ATS needs to avoid deadlock situations, i.e., cases in which a group of trains block each other. In the context of a technology transfer study, we designed an algorithm for deadlock avoidance in train scheduling. In this paper, we present a case study in which the algorithm has been applied. The case study has been encoded using ten different formal verification environments, namely UMC, SPIN, NuSMV/nuXmv, mCRL2, CPN Tools, FDR4, CADP, TLA+, UPPAAL and ProB. Based on our experience, we observe commonalities and differences among the modelling languages considered, and we highlight the impact of the specific characteristics of each language on the presented models. |
url |
http://arxiv.org/pdf/1803.10324v1 |
work_keys_str_mv |
AT francomazzanti tendiverseformalmodelsforacbtcautomatictrainsupervisionsystem AT alessioferrari tendiverseformalmodelsforacbtcautomatictrainsupervisionsystem |
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1725010630775144448 |