Identifying Skeletal Information of Activity Patterns by Multidimensional Sequence Alignment

Abstract

String-alignment techniques, which were introduced in biology to measure similarity between DNA strings or protein sequences, find increasing application in travel behavior research to analyze activity-travel patterns. This paper explores a method to identify common elements, referred to as skeletons, in multidimensional activity patterns by using a multidimensional string-alignment technique that the authors developed. The method identifies the skeletal information of the multidimensional activity patterns of a group and describes the results of an application to an activity diary set. The analysis reveals structural patterns in the activity patterns and well-interpretable differences in patterns between males and females. The method offers a promising approach to activity analysis.

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