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dc.contributor.authorMakinde, O.*
dc.contributor.authorNeagu, Daniel*
dc.contributor.authorGheorghe, Marian*
dc.date.accessioned2019-01-22T15:32:54Z
dc.date.available2019-01-22T15:32:54Z
dc.date.issued2019
dc.identifier.citationMakinde O, Neagu D and Gheorghe M (2019) Agent based micro-simulation of a passenger rail system using customer survey data and an activity based approach. In: Lofti A, Bouchachia H, Gegov A et al (eds) Advances in Computational Intelligence Systems. UK Workshop on Computer Intelligence, 2018. Advances in Intelligent Systems and Computing. Springer: Cham. 840: 123-137.en_US
dc.identifier.urihttp://hdl.handle.net/10454/16761
dc.descriptionNoen_US
dc.description.abstractPassenger rail overcrowding is fast becoming a problem in major cities worldwide. This problem therefore calls for efficient, cheap and prompt solutions and policies, which would in turn require accurate modelling tools to effectively forecast the impact of transit demand management policies. To do this, we developed an agent-based model of a particular passenger rail system using an activity based simulation approach to predict the impact of public transport demand management pricing strategies. Our agent population was created using a customer/passenger mobility survey dataset. We modelled the temporal flexibility of passengers, based on patterns observed in the departure and arrival behavior of real travelers. Our model was validated using real life passenger count data from the passenger rail transit company, after which we evaluated the use of peak demand management instruments such as ticketing fares strategies, to influence peak demand of a passenger rail transport system. Our results suggest that agent-based simulation is effective in predicting passenger behavior for a transportation system, and can be used in predicting the impact of demand management policies.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1007/978-3-319-97982-3_10en_US
dc.rights© Springer Nature Switzerland AG 2019. Reproduced in accordance with the publisher's self-archiving policy. The final publication is available at Springer via https://doi.org/10.1007/978-3-319-97982-3_10.en_US
dc.subjectAgent based simulationen_US
dc.subjectCustomer survey dataen_US
dc.subjectPassenger rail systemen_US
dc.titleAgent based micro-simulation of a passenger rail system using customer survey data and an activity based approachen_US
dc.status.refereedYesen_US
dc.date.Accepted2018
dc.date.application2018-08-11
dc.typeConference paperen_US
dc.type.versionNo full-text in the repositoryen_US
refterms.dateFOA2019-01-22T15:32:54Z


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