DEMAND FORECASTING FOR NEW RAILWAY STATIONS USING THE STATION CATCHMENT AREA METHOD AND TRANSPORTATION IC COMMUTER-PASS DATA

Abstract

Demand forecasting is essential in planning a new railway station because it supports decisions on station size and project feasibility. This study develops a forecasting method based on the station catchment area approach using population data from the Population Census and Economic Census, together with Mobile ICOCA commuter-pass data and automatic fare-gate records. JR usage rates by distance band are first estimated from observed usage at existing stations, and then used to estimate both newly generated users and users shifted from adjacent existing stations. Total ridership is obtained by adding non-commuter users. The method is validated using four stations that have already opened by comparing predicted and actual ridership at both the small district and station levels. The results indicate that the proposed method is applicable to a preliminary assessment of demand for new railway stations without additional surveys, while the treatment of distance bands, competing railway lines, and access conditions affects prediction accuracy.