Please use this identifier to cite or link to this item:
http://hdl.handle.net/1942/33635
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | ZIEMKE, Dominik | - |
dc.contributor.author | Charlton, Billy | - |
dc.contributor.author | Hörl, Sebastian | - |
dc.contributor.author | Nagel, Kai | - |
dc.date.accessioned | 2021-03-12T10:29:05Z | - |
dc.date.available | 2021-03-12T10:29:05Z | - |
dc.date.issued | 2021 | - |
dc.date.submitted | 2021-03-05T10:27:48Z | - |
dc.identifier.citation | Transportation research procedia (Online), 52 , p. 613 -620 | - |
dc.identifier.issn | 2352-1457 | - |
dc.identifier.uri | http://hdl.handle.net/1942/33635 | - |
dc.description.abstract | Agent-based transport simulation models are a particularly useful tool to analyze demand-oriented transport policies and new mobility services, which have both gained significant attention lately. Since travel diaries, a traditional source to create the transport demand in agent-based transport models, are often hard to procure and not policy-sensitive, alternative approaches to creating travel demand representations for simulation scenarios are sought. In this study, a particularly efficient approach based on Big Data and a new, aspatial activity-based demand model with comparatively low input data requirements is established. Home, work, and education locations are informed based on mobile-phone-based origin-destination matrices. Other activity locations are modeled within the scope of the coevolutionary algorithm of the agent-based transport model, which is also responsible for finding suitable travel options of the modeled individuals. As a result, a comparatively lightweight process chain to create an agent-based transport simulation scenario is established, which is transferable to other regions. A basic quality evaluation of the created tool chain is carried out against a well-validated transport simulation model of the same region. c 2020 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 23rd EURO Working Group on Transportation Meeting. | - |
dc.description.sponsorship | The authors thank Tim Hilgert for discussions on the actiTopp model. DZ thanks Luk Knapen, Tom Bellemans, and Bruno Kochan for discussion on the interaction of activity scheduling and transport simulations models during repeated research stays at IMOB. The authors acknowledge funding by the National Research Programme Big Data (NRP 75) of the Swiss National Science Foundation and thank Swisscom for providing mobile-phone-based OD matrices as well as the Swiss Bundesamt f¨ur Statsitik for granting access to the STATPOP census dataset. | - |
dc.language.iso | en | - |
dc.publisher | Elsevier | - |
dc.rights | 2020 The Authors. Published by ELSEVIER B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of the 23rd Euro Working Group on Transportation Meeting | - |
dc.subject.other | Agent-based transport simulation | - |
dc.subject.other | activity-based demand models | - |
dc.subject.other | cell-phone data | - |
dc.subject.other | big data | - |
dc.subject.other | transport model | - |
dc.title | An efficient approach to create agent-based transport simulation scenarios based on ubiquitous Big Data and a new, aspatial scenarios based on ubiquitous Big Data and a new, aspatial activity-scheduling model. | - |
dc.type | Journal Contribution | - |
local.bibliographicCitation.conferencedate | 16-18 September 2020 | - |
local.bibliographicCitation.conferencename | 23rd EURO Working Group on Transportation Meeting, EWGT 2020 | - |
local.bibliographicCitation.conferenceplace | Paphos, Cyprus | - |
dc.identifier.epage | 620 | - |
dc.identifier.spage | 613 | - |
dc.identifier.volume | 52 | - |
local.format.pages | 8 | - |
local.bibliographicCitation.jcat | A1 | - |
local.type.refereed | Refereed | - |
local.type.specified | Article | - |
dc.identifier.doi | 10.1016/j.trpro.2021.01.073 | - |
dc.identifier.eissn | - | |
local.provider.type | - | |
local.uhasselt.uhpub | yes | - |
local.uhasselt.international | yes | - |
item.fullcitation | ZIEMKE, Dominik; Charlton, Billy; Hörl, Sebastian & Nagel, Kai (2021) An efficient approach to create agent-based transport simulation scenarios based on ubiquitous Big Data and a new, aspatial scenarios based on ubiquitous Big Data and a new, aspatial activity-scheduling model.. In: Transportation research procedia (Online), 52 , p. 613 -620. | - |
item.fulltext | With Fulltext | - |
item.validation | vabb 2023 | - |
item.contributor | ZIEMKE, Dominik | - |
item.contributor | Charlton, Billy | - |
item.contributor | Hörl, Sebastian | - |
item.contributor | Nagel, Kai | - |
item.accessRights | Open Access | - |
crisitem.journal.issn | 2352-1465 | - |
Appears in Collections: | Research publications |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
ZiemkeEtAl2021-2.pdf | Published version | 690.64 kB | Adobe PDF | View/Open |
Page view(s)
24
checked on Jun 29, 2022
Download(s)
8
checked on Jun 29, 2022
Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.