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Safe design of flow management systems using rebeca
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Mälardalens högskola , Vasteras, Sweden.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems. Mälardalens högskola , Vasteras, Sweden.
Volvo , Gothenburg, Sweden.
Reykjavik University , 101 Reykjavík, Iceland.
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2020 (English)In: Journal of Information Processing, ISSN 0387-5806, Vol. 28, p. 588-598Article in journal (Refereed) Published
Abstract [en]

Track-based flow management systems like transportation systems and traffic control systems play a crucial role in our daily life. Safety and performance are among the most important quality requirements for these systems. This paper presents AdaptiveFlow as a framework for modeling, safety checking and performance analysis of track-based flow management systems. AdaptiveFlow is based on the Hewitt actors computation model. In particular, tracks are modeled as actors and moving objects as messages. Timed Rebeca is used for modeling, and the model checking tool Afra is used for safety verification and performance evaluation in AdaptiveFlow. To react to dynamic changes in the environment, AdaptiveFlow provides support for three adaptive policies, which can be examined and compared in different scenarios. To demonstrate the applicability of AdaptiveFlow, we consider the Electric Site Research Project of Volvo Construction Equipment as a case study. In this project, a fleet of autonomous haulers is utilized to transport materials in a quarry site. Furthermore, to show the reusability of the framework for other flow management scenarios, an experiment on an urban garbage collection system is presented. © 2020 Information Processing Society of Japan.

Place, publisher, year, edition, pages
Information Processing Society of Japan , 2020. Vol. 28, p. 588-598
Keywords [en]
Actor model, Model checking, Performance evaluation, Safety verification, Track-based flow management
National Category
Computer Systems
Identifiers
URN: urn:nbn:se:mdh:diva-50993DOI: 10.2197/ipsjjip.28.588Scopus ID: 2-s2.0-85091393475OAI: oai:DiVA.org:mdh-50993DiVA, id: diva2:1472387
Available from: 2020-10-01 Created: 2020-10-01 Last updated: 2021-01-04Bibliographically approved

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Forcina, GiorgioSedaghatbaf, AliSirjani, Marjan

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