01626197

Component

https://doi.org/10.3141/2666-08

Activity schedules are an important input for travel demand models. This paper presents a model to generate activity schedules for one week. The approach, called actiTopp, is based on the concept of utility-based regression models and stepwise modeling. In contrast to most of the existing models, actiTopp covers the time period of one week. Few models have covered one week; thus, the activity generation approach of this simulation period is rare. Analysis of weekly activity behavior shows stability between different days (e.g., working durations). Hence, the model explicitly takes these aspects into account, for example, by defining time budgets to spread durations within the week. For model estimation, the study used data from the German Mobility Panel (MOP). This annual survey collects representative data on the travel behavior of the German population. The data from 2004–2013 provide more than 17,500 activity schedules for one week, with more than 450,000 activities. Selected results are shown for the model application to 2014 MOP data, which the study used for validation purposes. The mean value of activities per person and week show a difference of 0.3 activity. To evaluate the model, the study used Kolmogorov-Smirnov tests with a significance level of α = 0.001. For the activity type distribution of the 2014 sample, the analysis could not reject the null hypothesis of equality of the distribution of the model and the survey data at this significance level.

01648400

17-00682

English

pp 69–77

2017

Transportation Research Record: Journal of the Transportation Research Board

9780309441926

Digital/other

Figures (5) ; References (25) ; Tables (4)

Activity choices; Regression analysis; Time periods; Travel demand; Weeks

German Mobility Panel

Planning and Forecasting; Transportation (General)

TRIS, TRB, ATRI

Dec 8 2016 10:08AM

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