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

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  • Auld, Joshua
  • Mohammadian, Abolfazl(Kouros)

Abstract

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.

Suggested Citation

  • Auld, Joshua & Mohammadian, Abolfazl(Kouros), 2012. "Activity planning processes in the Agent-based Dynamic Activity Planning and Travel Scheduling (ADAPTS) model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 46(8), pages 1386-1403.
  • Handle: RePEc:eee:transa:v:46:y:2012:i:8:p:1386-1403
    DOI: 10.1016/j.tra.2012.05.017
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    References listed on IDEAS

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    Cited by:

    1. Manoj, M. & Verma, Ashish, 2015. "Activity–travel behaviour of non-workers from Bangalore City in India," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 400-424.
    2. Sheila Ferrer & Tomás Ruiz, 2017. "Comparison on travel scheduling between driving and walking trips by habitual car users," Transportation, Springer, vol. 44(1), pages 27-48, January.
    3. Yasmin, Farhana & Morency, Catherine & Roorda, Matthew J., 2015. "Assessment of spatial transferability of an activity-based model, TASHA," Transportation Research Part A: Policy and Practice, Elsevier, vol. 78(C), pages 200-213.
    4. Yoon, Seo Youn & Ravulaparthy, Srinath K. & Goulias, Konstadinos G., 2014. "Dynamic diurnal social taxonomy of urban environments using data from a geocoded time use activity-travel diary and point-based business establishment inventory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 68(C), pages 3-17.
    5. Mahmoud Javanmardi & Mehran Fasihozaman Langerudi & Ramin Shabanpour & Abolfazl Mohammadian, 2016. "An optimization approach to resolve activity scheduling conflicts in ADAPTS activity-based model," Transportation, Springer, vol. 43(6), pages 1023-1039, November.

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