Abstract
Sequence analysis is used in this paper to measure fragmentation in activity participation and travel. Fragmentation here is defined as the sequencing of many short and long activities and trips that happen in a personal daily schedule. Studying sequences of daily episodes (each activity at a place and each trip) is preferable over other techniques of studying activity– travel behavior because sequences include the entire trajectory of a person’s activity during a day while jointly considering the number of activities and trips, their ordering, and their durations. We first identify places visited and duration at each place on a minute-by-minute basis, then we derive representative daily behavior patterns using hierarchical clustering. Our study shows there are at least nine distinct daily patterns with different sequencing of activities and travel as well as travel time ratios and modal split. These patterns include typical commute to work or school, staying at home all day, or traveling extensively. As expected, day of the week plays a major role in the type of daily activity–travel patterns. Travel time ratios are also examined for each daily pattern and we find differences in the role played within each pattern between central city, suburban, exurban, and rural dwellers. In a comparison of couples, we find systematically higher fragmentation in households that have children and their parents are employed, with women showing higher fragmentation in the activity–travel patterns.
Original language | English |
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Title of host publication | Transportation Research Record |
Publisher | SAGE Publications Ltd |
Pages | 38-51 |
Number of pages | 14 |
Volume | 2674 |
Edition | 12 |
DOIs | |
State | Published - 2020 |
Externally published | Yes |
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Funding for this research was provided by the Pacific Southwest Region 9 University Transportation Center and the GeoTrans Laboratory at the Department of Geography, University of California Santa Barbara. The data is available at the Transportation Secure Data Center of NREL. Three anonymous reviewers provided invaluable comments that the authors appreciate.
Funders | Funder number |
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Pacific Southwest Region 9 University Transportation Center | |
University of California, Santa Barbara |