Identifying skeletal information of activity patterns of a group

String-alignment techniques, which were originally introduced in biology to measure similarity between DNA strings or protein sequences, find increasing application in travel behavior research to analyze activity/travel patterns. In this paper, we explore a method to identify common elements, referred to as skeletons, in multi-dimensional activity patterns by using a multi-dimensional string alignment technique the authors previously developed. We show how the new method identifies the skeletal information of the multi-dimensional activity patterns of a group and describe 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. We conclude that the new method offers a promising approach to activity analysis.