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Towards a Digital Highway Code using Formal Modelling and Verification of Timed Automata

Alves, Gleifer Vaz; Schwammberger, Maike ORCID iD icon; Luckcuck, Matt [Hrsg.]; Farrell, Marie [Hrsg.]

Abstract:

One of the challenges in designing safe, reliable and trustworthy Autonomous Vehicles (AVs) is to ensure that the AVs abide by traffic rules. For this, the AVs need to be able to understand and reason about traffic rules. In previous work, we introduce the spatial traffic logic USL-TR to allow for the unambiguous, machine-readable, formalisation of traffic rules. This is only the first step towards autonomous traffic agents that verifiably follow traffic rules. In this research preview, we focus on two further steps: a) retrieving behaviour diagrams directly from traffic rules and b) converting the behaviour diagrams into timed automata that are using formulae of USL-TR in guards and invariants. With this, we have a formal representation for traffic rules and can move towards the establishment of a Digital Highway Code. We briefly envision further steps which include adding environment and agent models to the timed automata to finally implement and verify these traffic rule models using a selection of formal verification tools.


Verlagsausgabe §
DOI: 10.5445/IR/1000169853
Veröffentlicht am 11.04.2024
Originalveröffentlichung
DOI: 10.4204/EPTCS.371.6
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Zitationen: 1
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Informationssicherheit und Verlässlichkeit (KASTEL)
Publikationstyp Proceedingsbeitrag
Publikationsjahr 2022
Sprache Englisch
Identifikator ISSN: 2075-2180
KITopen-ID: 1000169853
Erschienen in Proceedings of 4th International Workshop on Formal Methods for Autonomous Systems, FMAS@SEFM, Ed.: M. Luckcuck
Veranstaltung 4th International Workshop on Formal Methods for Autonomous Systems (FMAS 2022), Berlin, Deutschland, 26.09.2022 – 27.09.2022
Verlag Open Publishing Association
Seiten 77–85
Serie Electronic proceedings in theoretical computer science ; 371
Vorab online veröffentlicht am 28.09.2022
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