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

Joshua Auld and Mohammadian, Abolfazl(Kouros)

Transportation Research Part A: Policy and Practice, 2012, vol. 46, issue 8, 1386-1403

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.

Keywords: Activity based modeling; Activity planning; Behavioral models; Activity scheduling behavior (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (17)

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DOI: 10.1016/j.tra.2012.05.017

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