Application of Sequence Alignment Methods in Clustering and Analysis of Routine Weekly Activity Schedules.

Author(s)
Saneinejad, S. & Roorda, M.J.
Year
Abstract

Extension of the 24-hour activity models to weeklong models and generating better routine activity skeletons, which are later filled in with non-routine activity episodes are identified as two areas of improvement in current activity-based modeling techniques. This paper utilizes multidimensional sequence alignment methods to measure similarities between routine weekly activity sequences of 282 surveyed individuals, as reported in a specialized survey of routine weekly schedules conducted in Toronto, Canada. Similar activity patterns are classified into a number of clusters. General behavioral patterns of the resulting clusters are described and analyzed based on socioeconomic activities of members of each cluster. Significant differences are found in a variety of socioeconomic variables that describe individual membership in each cluster, including age, income, gender, employment status, student status, marital status, drivers license, cell phoneusage and education level.

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Publication

Library number
C 45281 (In: C 43862 CD-ROM) /73 / ITRD E843811
Source

In: Compendium of papers CD-ROM 87th Annual Meeting of the Transportation Research Board TRB, Washington, D.C., January 13-17, 2008, 20 p.

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