01629520

Component

https://doi.org/10.3141/2664-05

Most existing activity-based travel demand models are typically implemented on a tour-based microsimulation framework. Two approaches are available to describe people’s daily decision-making processes on activity and travel in the activity-based model framework: rubber banding and growing scheduling. The growing-scheduling approach requires a series of linked dynamic discrete choices of activity episodes, locations, and travel modes to build incrementally an entire day’s activity-travel patterns for individuals in households. To incorporate explicitly time dependencies into activity episode choice and duration, a hazard-based duration model in a discrete-time framework is introduced; this framework is essentially the same as a discrete choice model with temporal dummies as the simplest form of dynamic discrete choice models. In the application of the discrete–time duration model to activity duration analysis, complex situations of activity-travel data are considered; these include multiple states of origin activity, competing risks of destination activity, and a multilevel structure for recurrent activity episodes within individuals. In addition, a circular, or periodic, variable is introduced as a combination of sine and cosine to model time-of-day effects.

01656344

17-05618

English

pp 42–50

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309442077

Digital/other

Figures (1) ; References (15) ; Tables (5)

Activity choices; Decision making; Origin and destination; Periods of the day; Time duration; Travel demand

Planning and Forecasting; Transportation (General)

TRIS, TRB, ATRI

Dec 8 2016 12:14PM

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