Unveiling Taxonomy of Daily Travel and Time Use Patterns Using Human Mobility Motifs and Sequence Analysis

Keywords: human mobility, motif, sequence analysis, travel survey, telecommuting, senior
Session Type: Virtual Paper
Day: Thursday
Session Start / End Time: 4/8/2021 09:35 AM (Pacific Time (US & Canada)) - 4/8/2021 10:50 AM (Pacific Time (US & Canada))
Room: Virtual 33

Abstract

We propose a new joint pattern recognition method that combines network motifs with activity sequence-based analysis. Motifs are networks of distinct locations visited in a day and the directional movements between them. Sequence-based analysis uses minute-by-minute data on time allocation to activities and travel to identify distinct daily schedules of people and classify them in clusters. In the first application using the entire California component of the 2017 National Household Travel Survey workday samples, we find that 16 unique motifs can capture 83.05% of the total respondents. Motifs are grouped into categories based on the number of distinct locations a person visits in a day and their correlation with time use and travel is explored. The within motif group clusters of activity-based sequences show typical commuting, going to school, and resting patterns. In the second application focusing on differences and commonalities in travel behavior between telecommuters and usual commuters, we find that telecommuters do not only perform work tasks from home; instead, during a day a high percentage travel to a variety of locations to either visit customers and/or use their spatiotemporal schedule flexibility to perform work tasks from locations other than home. In the third application, we focus on senior respondents and correlate the daily mobility motif patterns with socio-demographic characteristics as well as built environment factors. We find that seniors are more likely to have simple motifs with three or fewer distinct locations on non-workdays, while they present more complex motifs during workdays.