Analysis of Public Transport Commuters’ Travel Characteristics Based on Smart Card Data

The travel patterns of transit commuters were analyzed based on the smartcard data collected from Shenzhen, China. Among the entire dataset (from 5th to 30th, March, 2012), the commuters’ card id were firstly identified based on the observations of individuals’ smartcard usage in workdays. Then, travel characteristics as well as statistics of the identified commuters were obtained, such as first-boarding time in workdays, average number of boardings per day for different types of cards and so on. Travel patterns and regularities of the identified commuters were analyzed by the use of two-step clustering method, and 2 clusters were automatically determined. Commuters belonging to the Cluster 1 (54.6%) have shown a travel pattern of high-intensity workday transit usage with better continuity, however, by contrast, the rest in Cluster 2 (45.4%) seem not to rely so much on the public transit for their commute to work.