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Multi-day activity-travel pattern sampling based on single-day data

delete2018-04-01
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A
Anpeng Zhang
J
Jee Eun Kang *
K
Kay W. Axhausen
C
Changhyun Kwon
DOI:10.1016/j.trc.2018.01.024delete
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Abstract

Abstract

En 中文
Although it is important to consider multi-day activities in transportation planning, multi-day activity-travel data are expensive to acquire and therefore rarely available. In this study, we propose to generate multi-day activity-travel data through sampling from readily available single-day household travel survey data. A key observation we make is that the distribution of interpersonal variability in single-day travel activity datasets is similar to the distribution of intrapersonal variability in multi-day. Thus, interpersonal variability observed in cross-sectional single-day data of a group of people can be used to generate the day-to-day intrapersonal variability. The proposed sampling method is based on activity-travel pattern type clustering, travel distance and variability distribution to extract such information from single-day data. Validation and stability tests of the proposed sampling methods are presented.
Keywords:
Activity-travel patterns
Day-to-day variability
Interpersonal variability
Sampling multiday activity-travel patterns
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Journal

Transportation Research Part C-Emerging Technologies cover
Transportation Research Part C-Emerging Technologies
IF:
7.9
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4.7K
Citations:
3.2W

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state university of new york (suny) system
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university at buffalo, suny
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swiss federal institutes of technology domain
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