Abstract
This paper is built around a research project developed with the support of the Regional Planning Authority of the Algarve Region in Portugal which assessed mobility patterns covering all modes of transport using heterogeneous data sources (time-series data). Data mining techniques helped to identify limitations in some data sets. The econometric analysis showed that integrated autoregressive models and moving averages for series with seasonality were successful in the prediction of passenger flows using time-series data gathered by the regional authority from transport operators and other entities.Results from the analysis are useful to support a strategy to reverse current trends on continued car growth (along with public transport decrease) and to devise policy measures to enable a sustainable mobility path towards decarbonisation and social equity goals until 2030.
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