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    Agent based micro-simulation of a passenger rail system using customer survey data and an activity based approach

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    Publication date
    2019
    Author
    Makinde, O.
    Neagu, Daniel
    Gheorghe, Marian
    Keyword
    Agent based simulation
    Customer survey data
    Passenger rail system
    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.
    Peer-Reviewed
    Yes
    
    Metadata
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    Abstract
    Passenger 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.
    URI
    http://hdl.handle.net/10454/16761
    Version
    No full-text in the repository
    Citation
    Makinde 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.
    Link to publisher’s version
    https://doi.org/10.1007/978-3-319-97982-3_10
    Type
    Conference paper
    Collections
    Engineering and Informatics Publications

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