Travel patterns analysis of urban residents using Automated Fare Collection System

Abstract

While Automated Fare Collection System is widely used in many cities all over the world, large amount of swiping card data has been recorded. By using the data, this paper proposed a novel method to recognize passenger flow direction to understand the dynamics of the residents' daily mobility patterns in urban city, which contributes to the planning and management of urban facilities and services. The method classifies subway stations into three kinds based on the land properties around the station and recognizes the passenger flow directions in peak hours. In the final part of paper, the travel patterns in Beijing are recognized, along with a further analysis.

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