Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour |
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Authors: | Khandker M. N. Habib Eric J. Miller |
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Affiliation: | (1) Department of Civil & Environmental Engineering, University of Alberta, , 3-004 Markin/CNRL Natural Resources Engineering Facility, Edmonton, AB, Canada, T6G 2W2;(2) Department of Civil Engineering, University of Toronto, 35 St. George Street, Toronto, ON, Canada, M4S 1A4 |
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Abstract: | This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto. |
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Keywords: | Activity generation Day-to-day dynamics Within-day dynamics Travel behaviour Activity utility |
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