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dc.contributor.authorGong, Shuhui
dc.contributor.authorDong, Xiangrui
dc.contributor.authorWang, Kaiqi
dc.contributor.authorLei, Bingli
dc.contributor.authorJia, Zizhao
dc.contributor.authorQin, Jiaxin
dc.contributor.authorRoadknight, Christopher
dc.contributor.authorLiu , Yu
dc.contributor.authorCao, Rui
dc.date.accessioned2023-09-26T12:30:02Z
dc.date.available2023-09-26T12:30:02Z
dc.date.issued2023-08-31
dc.identifier.citationGong , S , Dong , X , Wang , K , Lei , B , Jia , Z , Qin , J , Roadknight , C , Liu , Y & Cao , R 2023 , ' Agent-based modelling with geographically weighted calibration for intra-urban activities simulation using taxi GPS trajectories ' , The International Journal of Applied Earth Observation and Geoinformation , vol. 122 , 103368 . https://doi.org/10.1016/j.jag.2023.103368
dc.identifier.issn1569-8432
dc.identifier.otherORCID: /0000-0001-7938-7671/work/143285388
dc.identifier.urihttp://hdl.handle.net/2299/26742
dc.description© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/bync-nd/4.0/)
dc.description.abstractHuman motivations are an important factor in influencing human movement. However, most existing studies on passenger travel demand prediction focus on external characteristics of movement, but neglect the influence of activities and the motivations behind them, on the citizen’s trip decisions. In this study, we proposed an agent-based model, to predict passengers’ travel behaviour over a period of time, particularly when the urban structure changes. The model includes passenger characteristics, transitions in travel demands between activities over time, and their movement in space and time. In addition, we innovatively calibrated the agent based model locally using Geographically Weighted Regression (GWR) to account for geographical variations in the parameters of destination attractiveness and travel cost in the agent-based model. We conducted a case study in Ningbo, China, using trip diaries, census data, and over 1.5 million taxi trip records. Our agent-based model showed superior performance in predicting citizens’ movements and activities after a new shopping area in Ningbo was built, compared with a model without local calibration. The results also revealed the geographic sensitivity to destinations and the effects of a passenger’s motivations that underpin human movement.en
dc.format.extent14
dc.format.extent4798794
dc.language.isoeng
dc.relation.ispartofThe International Journal of Applied Earth Observation and Geoinformation
dc.subjectActivity-based analysis
dc.subjectAgent-based modelling (ABM)
dc.subjectGeographically weighted regression (GWR)
dc.subjectHuff model
dc.subjectTaxi GPS trajectories
dc.subjectComputers in Earth Sciences
dc.subjectEarth-Surface Processes
dc.subjectManagement, Monitoring, Policy and Law
dc.subjectGlobal and Planetary Change
dc.titleAgent-based modelling with geographically weighted calibration for intra-urban activities simulation using taxi GPS trajectoriesen
dc.contributor.institutionBiocomputation Research Group
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.description.statusPeer reviewed
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85163865263&partnerID=8YFLogxK
rioxxterms.versionofrecord10.1016/j.jag.2023.103368
rioxxterms.typeJournal Article/Review
herts.preservation.rarelyaccessedtrue


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