Sequence Alignment Analysis of Variability in Activity Travel Patterns through 8 Weeks of Diary Data

Abstract

Variability of activity travel patterns has long been an important issue in transportation research. Such variability has been typically explained in relation to covariance with a set of sociodemographic characteristics of travelers. However, variability also stems from differences in knowledge about the environment, which changes over time. To improve understanding of the contribution of different sources to variability in observed activity travel patterns, this paper applies sequence alignment to investigate different sources of variability in longitudinal patterns. The data on activity travel patterns were collected in 2010 for 3 months from newcomers to the city of Eindhoven, Netherlands. GPS technology was used to obtain traces that were processed with TraceAnnotator to impute activities and trips. A set of activity travel sequences for 8 weeks for 27 respondents was used in the analysis. The results show that (a) interpersonal variability is significantly higher than intra personal variability, although intrapersonal variability is yet substantial and should not be ignored; (b) intrapersonal variability reflecting different speeds of learning the new environment substantially changes over time; and (c) both interpersonal and intrapersonal variability are affected by socio-demographic characteristics such as gender and country of origin. The paper also discusses the implications of these findings for future research.