Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/34107
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dc.contributor.authorZIEMKE, Dominik-
dc.contributor.authorKNAPEN, Luk-
dc.contributor.authorNagel, Kai-
dc.contributor.editorShakshuki, E-
dc.contributor.editorYasar, A-
dc.date.accessioned2021-05-27T14:05:48Z-
dc.date.available2021-05-27T14:05:48Z-
dc.date.issued2021-
dc.date.submitted2021-05-20T22:08:50Z-
dc.identifier.citationShakshuki, E ; Yasar, A (Ed.). 12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS-volume 184, ELSEVIER SCIENCE BV, p. 753 -760-
dc.identifier.issn1877-0509-
dc.identifier.urihttp://hdl.handle.net/1942/34107-
dc.description.abstractMATSim is an agent-based transport simulation model. In contrast to a pure dynamic traffic assignment (DTA) model, MATSim is more an agent-based transport than simulation model. which In contrast to a pure dynamic assignment model, can react to choice dimensions route choice, is the only choice treated traffic by a typical DTA. (DTA) Simulating the MATSim mobility can to more choice dimensions than during route choice, which the only choice treated by a represent typical DTA. the mobility and react activity participation of individuals the whole day, is MATSim can additionally mode Simulating choice, departure time and activity participation individuals during the whole day, in MATSim can additionally represent This mode choice, time choice, and other decisions of and is, therefore, policy-sensitive terms of these choice dimensions. allows for departure the analysis of choice, and other decisions and is, therefore, policy-sensitive in terms of these choice dimensions. This allows for the analysis of a wide scope of policies. MATSim can, however, not model the choice of the sequence of activity participation nor the choice of a activity wide scope of policies. MATSim can, however, not model choice part of the of activity participation nor of participation as such. Also, choices of locations are not the typically of sequence the modeling scope. Interventions into the the choice transport activity participation such. Also, choices of locations typically part changes of the modeling scope. Interventions into the transport and land-use systems as may, however, be substantial such are that not they can effect in behavior in terms of these choices. To allow and land-use systems may, however, be substantial such that they can effect changes in behavior in terms of these choices. allow for the assessment of such reactions, the FEATHERS activity-based demand model is coupled with MATSim. This paper To explores for the assessment such reactions, the FEATHERS activity-based demand model is of coupled with MATSim. This paper explores different options of of integration and describes the development steps of the integration FEATHERS and MATSim. different options of integration and describes the development steps of the integration of FEATHERS and MATSim.-
dc.language.isoen-
dc.publisherELSEVIER SCIENCE BV-
dc.rightsUnder a Creative Commons license-
dc.subject.otheragent-based simulation-
dc.subject.othertransport modeling-
dc.subject.othertransport demand modeling-
dc.subject.otherpolicy analysis-
dc.subject.othermodel integration-
dc.titleExpanding the analysis scope of a MATSim transport simulation by integrating the FEATHERS activity-based demand model-
dc.typeProceedings Paper-
local.bibliographicCitation.conferencedate2021, March 23 - 26-
local.bibliographicCitation.conferencenameThe 10th International Workshop on Agent-based Mobility, Traffic and Transportation Models, Methodologies and Applications (ABMTRANS 2021)-
local.bibliographicCitation.conferenceplaceWarsaw, Poland-
dc.identifier.epage760-
dc.identifier.spage753-
dc.identifier.volume184-
local.format.pages8-
local.bibliographicCitation.jcatC1-
local.publisher.placeSARA BURGERHARTSTRAAT 25, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS-
dc.relation.references[1] Arentze, T., Timmermans, H., 2004. A learning-based transportation oriented simulation system. Transportation Research Part B 38, 613–633. [2] Bellemans, T., Kochan, B., Janssens, D., Wets, G., Arentze, T., Timmermans, H., 2010. Implementation framework and development trajectory of FEATHERS activity-based simulation platform. Transportation Research Record 2175, 111–119. [3] Bhat, C., Guo, J., Srinivasan, S., Sivakumar, A., 2004. A comprehensive econometric microsimulator for daily activity-travel patterns. Trans- portation Research Record 1894, 57–66. doi:10.3141/1894-07. [4] Bischoff, J., Maciejewski, M., 2014. Agent-based simulation of electric taxicab fleets. Transportation Research Procedia 4, 191–198. doi:10. 1016/j.trpro.2014.11.015. [5] Hilgert, T., Heilig, M., Kagerbauer, M., Vortisch, P., 2017. Modeling week activity schedules for travel demand models. Transportation Research Record 2666, 69–77. doi:10.3141/2666-08. [6] Horni, A., Nagel, K., Axhausen, K.W., 2012. High-Resolution Destination Choice in Agent-Based Models. Annual Meeting Preprint 12-1988. Transportation Research Board. Washington, D.C. Also VSP WP 11-17, see http://www.vsp.tu-berlin.de/publications. [7] Horni, A., Nagel, K., Axhausen, K.W. (Eds.), 2016. The Multi-Agent Transport Simulation MATSim. Ubiquity, London. doi:10.5334/baw. [8] Kaddoura, I., 2015. Marginal congestion cost pricing in a multi-agent simulation: Investigation of the greater Berlin area. Journal of Transport Economics and Policy 49, 560–578. [9] Kaddoura, I., Laudan, J., Ziemke, D., Nagel, K., 2020. Verkehrsmodellierung für das ruhrgebiet: Simulationsbasierte szenariountersuchung und wirkungsanalyse einer verbesserten regionalen fahrradinfrastruktur, in: Proff, H. (Ed.), 11. Wissenschaftsforum Mobilität: Neue Di- mensionen der Mobilität: Technische und betriebswirtschaftliche Aspekte, Springer Gabler, Wiesbaden. pp. 361–386. doi:10.1007/ 978-3-658-29746-6. [10] Knapen, L., Adnan, M., Kochan, B., Bellemans, T., van der Tuin, M., Han, Z., Snelder, M., 2021. An Activity Based integrated approach to model impacts of parking, hubs and new mobility concepts, in: Procedia Computer Science, Elsevier, Warsaw, Poland. [11] Miller, E., Roorda, M., 2003. A prototype model of household activity/travel scheduling. Transportation Research Record 1831, 114–121. [12] Qiong, B., Kochan, B., Bellemans, T., Janssens, D., Wets, G., 2015. Investigating micro-simulation error in activity-based travel demand forecasting: a case study of the FEATHERS framework. Transportation planning and technology 38, 425–441. doi:10.1080/03081060. 2015.1026102. [13] Rasouli, S., Timmermans, H., 2013. Uncertainty in Predicted Measurement and Analysis, in: Transportation Research Board of the National Academies, TRB (Transportation Research Board), Washington, D.C. [14] de Romph, E., Kochan, B., Clerx, W., 2018. Een Activity Based Model voor Rotterdam, het ABMR, in: Colloquium Vervoersplanologisch Speurwerk, Colloquium Vervoersplanologisch Speurwerk. [15] Wallendorf, J., 2016. Agent-based simulation and traffic impact analysis of a new commercial park in Belgium. Master’s thesis. Technische Universität Berlin. [16] Ziemke, D., Charlton, B., Hörl, S., Nagel, K., 2021. An efficient approach to create agent-based transport simulation scenarios based on ubiquitous Big Data and a new, aspatial activity-scheduling model. Transportation Research Procedia 52, 613–620. URL: https://svn. vsp.tu-berlin.de/repos/public-svn/publications/vspwp/2020/20-11/. [17] Ziemke, D., Joubert, J.W., Nagel, K., 2017. Accessibility in a post-apartheid city: Comparison of two approaches for accessibility computations. Networks and Spatial Economics 18, 241–271. doi:10.1007/s11067-017-9360-3. [18] Ziemke, D., Kuehnel, N., Nagel, K., Moeckel, R., 2020. FABILUT: The Flexible, Agent-based Integrated Land-Use Transport Model. VSP Working Paper 20-01. TU Berlin, Transport Systems Planning and Transport Telematics. URL http://www.vsp.tu-berlin.de/ publications.-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.identifier.doi10.1016/j.procs.2021.04.022-
dc.identifier.isi000672800000097-
dc.identifier.eissn-
local.provider.typeCrossRef-
local.bibliographicCitation.btitle12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS-
local.uhasselt.uhpubyes-
local.uhasselt.internationalyes-
item.fulltextWith Fulltext-
item.accessRightsOpen Access-
item.validationecoom 2022-
item.contributorZIEMKE, Dominik-
item.contributorKNAPEN, Luk-
item.contributorNagel, Kai-
item.contributorShakshuki, E-
item.contributorYasar, A-
item.fullcitationZIEMKE, Dominik; KNAPEN, Luk & Nagel, Kai (2021) Expanding the analysis scope of a MATSim transport simulation by integrating the FEATHERS activity-based demand model. In: Shakshuki, E ; Yasar, A (Ed.). 12TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT) / THE 4TH INTERNATIONAL CONFERENCE ON EMERGING DATA AND INDUSTRY 4.0 (EDI40) / AFFILIATED WORKSHOPS-volume 184, ELSEVIER SCIENCE BV, p. 753 -760.-
crisitem.journal.issn1877-0509-
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