<div class="csl-bib-body">
<div class="csl-entry">Zhao, B., Tang, Y., Soga, K., Zhou, X., Wang, B., & Huang, J. (2023, January). <i>An integrated data-driven agent-based simulation (AAAM) for dynamic operations and individual behavior in urban rail transit systems</i> [Poster Presentation]. Transportation Research Board (TRB) 102nd Annual Meeting, Waschington, DC, United States of America (the). http://hdl.handle.net/20.500.12708/152693</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/152693
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dc.description.abstract
This study developed an integrated agent-based simulation by leveraging the computational approaches and data-driven optimization to analyze the dynamic operations and behaviors in urban rail transit systems. In the proposed simulation framework, network and infrastructure environments are generated to establish the transit network characteristics including the topologies, link connectivity, and vehicle capacities. Giving the dynamic transit schedule, passengers’ travel behaviors are then simulated considering individual route choice and activities under the constraints of network, infrastructure, and operation conditions. A benchmark case study is conducted incorporating smartcard data and operational records to present the simulated dynamic conditions of the transit systems including travel patterns, in-vehicle crowdedness, operational capacity, and on-platform queuing. Validation and scalability methods of the AAAM are proposed to verify and validate the functionality of the AAAM and the reliability of the simulated results which indicate the majority of the differences between simulated value and data records are within 3 minutes. We further developed optimization scenarios through the AAAM to calibrate the true values of the real-time operational characteristics such as peak hour train occupancy. Results indicate the precision and practicality of the integrated agent-based simulation to capture behavioral and operational dynamics at robust, reliable, and scalable levels.
en
dc.language.iso
en
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dc.subject
agent-based simulation
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dc.subject
passenger behavior
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dc.subject
urban rail transit
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dc.subject
smartcard data
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dc.subject
queuing and crowding
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dc.title
An integrated data-driven agent-based simulation (AAAM) for dynamic operations and individual behavior in urban rail transit systems
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dc.type
Presentation
en
dc.type
Vortrag
de
dc.contributor.affiliation
University of Regina, Canada
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dc.contributor.affiliation
University of California, Berkeley, United States of America (the)
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dc.contributor.affiliation
Arizona State University, United States of America (the)
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dc.contributor.affiliation
Beijing Rail Talent Development Co.,Ltd., China
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dc.contributor.affiliation
Beijing Transportation Research Center, China
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dc.type.category
Poster Presentation
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tuw.researchTopic.id
E1
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tuw.researchTopic.id
E2
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tuw.researchTopic.name
Energy Active Buildings, Settlements and Spatial Infrastructures
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tuw.researchTopic.name
Sustainable and Low Emission Mobility
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tuw.researchTopic.value
30
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tuw.researchTopic.value
70
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tuw.publication.orgunit
E230-01 - Forschungsbereich Verkehrsplanung und Verkehrstechnik
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tuw.author.orcid
0000-0002-2369-7731
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tuw.event.name
Transportation Research Board (TRB) 102nd Annual Meeting
