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Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model

  • Auld, Joshua
  • Mohammadian, Abolfazl(Kouros)
Registered author(s):

    This paper describes the representation of the activity planning process utilized in a new activity-based microsimulation model called the ADAPTS (Agent-based Dynamic Activity Planning and Travel Scheduling) model, which dynamically simulates activity and travel planning and scheduling. The model utilizes a dynamic activity planning framework within the larger overall microsimulation system, which is a computational process model that attempts to replicate the decisions which comprise time-dependent activity scheduling. The model presents a step forward in which the usual concepts of activity generation and activity scheduling are significantly enhanced by adding an additional component referred to as activity planning in which the various attributes which describe the activity are determined. The model framework, therefore, separates activity planning from activity generation and treats all three components, generation, planning and scheduling, as separate discrete but dynamic events within the overall microsimulation. The development of the planning order model, which determines when and in what order each activity planning decision is made is the specific focus of this paper. The models comprising the planning order framework are developed using recent survey data from a GPS-based prompted recall survey. The model development, estimation, validation, and its use within the overall ADAPTS system are discussed. A significant finding of the study is the verification of the apparent transferability of the activity planning order model.

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    Article provided by Elsevier in its journal Transportation Research Part A: Policy and Practice.

    Volume (Year): 46 (2012)
    Issue (Month): 8 ()
    Pages: 1386-1403

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    Handle: RePEc:eee:transa:v:46:y:2012:i:8:p:1386-1403
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    1. 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.
    2. Golledge, Reginald G. & Kwan, Mei-Po & Garling, Tommy, 1994. "Computational-Process Modelling of Household Travel Decisions Using a Geographical Information System," University of California Transportation Center, Working Papers qt4kk8w93s, University of California Transportation Center.
    3. Luis Miranda-Moreno & Martin Lee-Gosselin, 2008. "A week in the life of baby boomers: how do they see the spatial–temporal organization of their activities and travel?," Transportation, Springer, vol. 35(5), pages 629-653, August.
    4. Auld, Joshua & Mohammadian, Abolfazl (Kouros) & Doherty, Sean T., 2009. "Modeling activity conflict resolution strategies using scheduling process data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 43(4), pages 386-400, May.
    5. Ming Lee & Michael McNally, 2006. "An empirical investigation on the dynamic processes of activity scheduling and trip chaining," Transportation, Springer, vol. 33(6), pages 553-565, November.
    6. Tsu-Tan Fu & Lung-An Li & Yih-Ming Lin & Kamhon Kan, 2000. "A limited information estimator for the multivariate ordinal probit model," Applied Economics, Taylor & Francis Journals, vol. 32(14), pages 1841-1851.
    7. Tomás Ruiz & Harry Timmermans, 2006. "Changing the timing of activities in resolving Scheduling Conflicts," Transportation, Springer, vol. 33(5), pages 429-445, 09.
    8. Lee, Ming-Sheng, 2001. "Experiments With A Computerized Self-Administrative Activity Survey," University of California Transportation Center, Working Papers qt55h7r7x0, University of California Transportation Center.
    9. Li, Yonghai & Schafer, Daniel W., 2008. "Likelihood analysis of the multivariate ordinal probit regression model for repeated ordinal responses," Computational Statistics & Data Analysis, Elsevier, vol. 52(7), pages 3474-3492, March.
    10. Zhou, Jianyu (Jack) & Golledge, Reginald, 2007. "Real-time tracking of activity scheduling/schedule execution within a unified data collection framework," Transportation Research Part A: Policy and Practice, Elsevier, vol. 41(5), pages 444-463, June.
    11. Choo, Sangho & Mokhtarian, Patricia L, 2008. "How do people respond to congestion mitigation policies? A multivariate probit model of the individual consideration of three travel-related strategy bundles," University of California Transportation Center, Working Papers qt53s553tn, University of California Transportation Center.
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