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Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior

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Listed:
  • Linda Nijland

    ()

  • Theo Arentze

    ()

  • Harry Timmermans

    ()

Abstract

Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of individuals indicate the importance of incorporating those pre-planned activities in the new generation of dynamic travel demand models. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that takes into account possible influences of pre-planned activities and events. This paper describes the theory and shows the results of simulations of the extension. The simulation was conducted for six different activities, and the parameter values used were consistent with an earlier estimation study. The results show that the model works well and that the influences of the parameters are consistent, logical, and have clear interpretations. These findings offer further evidence of face and construct validity to the suggested modeling approach. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Linda Nijland & Theo Arentze & Harry Timmermans, 2014. "Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior," Journal of Geographical Systems, Springer, vol. 16(1), pages 71-87, January.
  • Handle: RePEc:kap:jgeosy:v:16:y:2014:i:1:p:71-87
    DOI: 10.1007/s10109-013-0187-2
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    References listed on IDEAS

    as
    1. Kay Axhausen & Andrea Zimmermann & Stefan Schönfelder & Guido Rindsfüser & Thomas Haupt, 2002. "Observing the rhythms of daily life: A six-week travel diary," Transportation, Springer, vol. 29(2), pages 95-124, May.
    2. Tommy Gärling & Robert Gillholm & William Montgomery, 1999. "The role of anticipated time pressure in activity scheduling," Transportation, Springer, vol. 26(2), pages 173-191, May.
    3. Sean Doherty, 2006. "Should we abandon activity type analysis? Redefining activities by their salient attributes," Transportation, Springer, vol. 33(6), pages 517-536, November.
    4. Peter T.L. Popkowski Leszczyc & Harry Timmermans, 2002. "Unconditional and conditional competing risk models of activity duration and activity sequencing decisions: An empirical comparison," Journal of Geographical Systems, Springer, vol. 4(2), pages 157-170, June.
    5. Khandker Habib & Eric Miller, 2008. "Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour," Transportation, Springer, vol. 35(4), pages 467-484, July.
    6. Sean Doherty & Eric Miller, 2000. "A computerized household activity scheduling survey," Transportation, Springer, vol. 27(1), pages 75-97, February.
    7. Mohammadian, Abolfazl & Doherty, Sean T., 2006. "Modeling activity scheduling time horizon: Duration of time between planning and execution of pre-planned activities," Transportation Research Part A: Policy and Practice, Elsevier, vol. 40(6), pages 475-490, July.
    8. Linda Nijland & Theo Arentze & Harry Timmermans, 2012. "Incorporating planned activities and events in a dynamic multi-day activity agenda generator," Transportation, Springer, vol. 39(4), pages 791-806, July.
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    More about this item

    Keywords

    Activity-based modeling; Multi-day activity planning; Dynamic activity scheduling; Needs; Planned activities; Events; R41; C53; C63; C51;

    JEL classification:

    • R41 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - Transportation Economics - - - Transportation: Demand, Supply, and Congestion; Travel Time; Safety and Accidents; Transportation Noise
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation

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