Urban road traffic congestion is a mainly problem in cities of Taiwan, particularly in the peak hours. During peak period the commuter journey takes part in a majority proportion of the residents’ journey. Over the past two decades, smart card data have received increasing interest from transport researchers as a new source of data for journey behavior investigation. Collected by smart card systems, smart card data surpass traditional journey survey data in providing more comprehensive journey information about urban bus-based trips.

Commuter traffic is an important part of a city and has three characteristics, including heavy traffic flow, generally accounted for more than 60% of the total urban journey; obvious regularity, connecting residences and workplaces; fixed time, often taking place in the morning and evening peaks. Also commuter traffic is the main reason for traffic congestion in peak hours. This paper aims to identify the commuter journey among numerous bus journeys by using the bus smartcard data only. With the method of cluster analysis, the stops at which passengers get on and get off the bus are identified from the time and location recorded in smartcard data. Then the popular origins and destinations of commuter journey and the characteristics of journey are found based on the trip chaining theory and geographic information. A case study on Taichung city is conducted at last to verify the proposed method.