Longest common subsequences: Identifying the stability of individuals’ travel patterns

There is a strong consensus in the travel behaviour research community that the one day travel diary collection is insufficient to understand the finer aspects of behaviour that transcend attributes such as average trip length, duration, travel modes, etc. While a large body research was done on exploring the spatial, temporal and spatio-temporal travel behavioural patterns, the sequential aspect of behaviour is seldom studied. The consensus of the few papers that have studied travel behaviour variability from a sequential perspective has been to use edit distance and compute the costs of transforming one day of travel activities into another. While useful, this approach generates difficult to understand metrics since it does not directly extract (sub)sequences but computes penalties. This paper provides an alternative for investigating the sequential aspect of travel behaviour that makes use of longest common subsequences to extract the activities that are common to multiple days and / or users. The proposed methodology provides indexes for measuring the inter- and intra-personal stability of a given user base and its usefulness is proved in a case study on travel diaries collected from 51 users for a period of 7 days.QC 20180508