Abstract
In this study, intraday correlations between station centralities and ridership at stations of the Athens metro system in Greece are explored. An unweighted L-space representation of the physical metro network is developed, and degree, closeness and betweenness are selected as station centrality measures. Hourly smart-card data are used for representing passenger flows. For station classification, principal component analysis and k-means clustering are utilized. The findings suggest that centrality and ridership usually move in opposite directions, morning peak-hour boardings are completely uncorrelated with station centrality, and metro stations can be classified as ‘central destinations’, ‘averagely central origins’, and ‘underutilized peripheral stations’.
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