Abstract:Most travel demand models assume that individuals’ daily travel patterns are stable or follow a fixed routine. This hypothesis is being questioned by more and more researchers. In this study, longitudinal mobile phone data were used to study the stability of individual daily travel patterns from three aspects, including activity space, activity points, and daily trip-chain patterns. The activity space was represented by the number of nonhome activity points, the radius of nonhome activity points, and the distance from home. The visitation pattern of activity points was analyzed by entropy and predictability measures. The stability of trip-chain patterns was described by the number of distinct trip chains, the typical trip chain, and the typical trip-chain ratio. Analysis of 21 days of mobile phone data from three communities in Shanghai, China, revealed that individuals’ daily travel patterns showed considerable variation. Although individuals’ visitation patterns to activity points were very regular, the day-to-day variations of individual trip-chain patterns were quite significant. On average, an individual exhibited about eight types of daily trip chains during the 21-day period. The daily travel patterns of residents in the outskirts were more stable than those of residents in the city center. Individuals’ travel patterns on weekdays were more complex than those on weekends. As individuals’ activity spaces increased, the stability of their travel patterns decreased.