Understanding temporal and spatial travel patterns of individual passengers by mining smart card data

Abstract

Metro systems have become the most preferred public transit services in many cities. It is important to understand individual passengers' spatio-temporal travel patterns inside metro. More specifically, for a specific passenger: what is the temporal access pattern? what is the spatio access pattern? is there any relationship between the temporal and spatio patterns? is this passenger's patterns normal or special? Answer all these questions can help us understanding the major reasons of why this passenger takes metro. In this paper, we analyze and understand the spatio-temporal travel patterns of individual passengers in Shenzhen, China. A systematic approach is proposed to extract temporal, spatial and anomaly features related to metro passengers. We analyze one month smart card data collected from Shenzhen. Combined with bus transaction data, we give an in-depth analysis and explanations for different groups.

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