mdh.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Lightweight preprocessing for agent-based simulation of smart mobility initiatives
Division of Computer Science, Smart Mobility Lab, University of Camerino, Via Madonna delle Carceri 9, Camerino, MC, Italy.
Division of Computer Science, Smart Mobility Lab, University of Camerino, Via Madonna delle Carceri 9, Camerino, MC, Italy.
Division of Computer Science, Smart Mobility Lab, University of Camerino, Via Madonna delle Carceri 9, Camerino, MC, Italy.
School of Computer Science, Reykjavik University, Menntavegur 1, Reykjavik, Iceland.
Show others and affiliations
2018 (English)In: Lect. Notes Comput. Sci., Springer Verlag , 2018, p. 541-557Conference paper, Published paper (Refereed)
Abstract [en]

Understanding the impacts of a mobility initiative prior to deployment is a complex task for both urban planners and transport companies. To support this task, Tangramob offers an agent-based simulation framework for assessing the evolution of urban traffic after the introduction of new mobility services. However, Tangramob simulations are computationally expensive due to their iterative nature. Thus, we simplified the Tangramob model into a Timed Rebeca (TRebeca) model and we designed a tool-chain that generates instances of this model starting from the same Tangramob’s inputs. Running TRebeca models allows users to get an idea of how mobility initiatives affect the system performance, in a short time, without resorting to the simulator. To validate this approach, we compared the output of both the simulator and the TRebeca model on a collection of mobility initiatives. Results show a correlation between them, thus demonstrating the usefulness of using TRebeca models for unconventional contexts of application.

Place, publisher, year, edition, pages
Springer Verlag , 2018. p. 541-557
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 10729 LNCS
Keywords [en]
Actor-based modeling languages, Agent-based simulations, Formal methods, Iterative methods, Modeling languages, Systems analysis, Urban transportation, Actor-based modeling, Agent based simulation, Complex task, Mobility service, Transport companies, Urban planners, Urban traffic, Software engineering
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-38795DOI: 10.1007/978-3-319-74781-1_36ISI: 000432620300036Scopus ID: 2-s2.0-85042067249ISBN: 9783319747804 OAI: oai:DiVA.org:mdh-38795DiVA, id: diva2:1186864
Conference
15th International Conference on Software Engineering and Formal Methods (SEFM),Fondazione Bruno Kessler, Trento, ITALY, EP 04-05, 2017
Available from: 2018-03-01 Created: 2018-03-01 Last updated: 2018-06-07Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records BETA

Sirjani, Marjan

Search in DiVA

By author/editor
Sirjani, Marjan
By organisation
Embedded Systems
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 67 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf