Perspectives on Stability and Mobility of Passenger's Travel Behavior through Smart Card Data

Existing studies have extensively used temporalspatial data to mining the mobility patterns of different kinds of travelers. Smart Card Data (SCD) collected by the Automated Fare Collection (AFC) systems can reflect a general view of the mobility pattern of the whole bus and metro riders in urban area. Since the mobility and stability are temporally and spatially dynamic and therefore difficult to measure, few work focuses on the transition of their travel pattern between a long time interval. In this paper, an overview of the relation between stability and regularity of public transit riders based on SCD of Beijing is presented first. To analyze the temporal travel pattern of urban residents, travelers are classified into two categories, extreme and non-extreme travelers. We have two lines for profiling all cardholders, rule-based approach for extreme and improved density-based clustering method for nonextreme. Similar clusters are aggregated according their features of regularity and occasionality. By combining transition matrix of passenger’s temporal travel pattern and socioeconomic data of Beijing in the year of 2010 and 2014, several analyses about resident’s temporal mobility and stability are presented to shed lights on the interdependence between stability and mobility in the time dimension. The results indicate that passengers’ regularity is hard to predict, extreme travel patterns are more vulnerable and overall non-extreme travel patterns nearly stay the same.