Big Data Harmonization for Intelligent Mobility: A Dynamic Toll-Charging Scenario

The need for interoperability in mobility data is more crucial than ever. Due to a panoply of data sources, from traffic sensors to GPS data, mobility data is increasingly more complex in terms of volume, heterogeneity, availability and quality. To turn such complex data into shareable, meaningful data, interoperability approaches must be implemented, namely through the use of standards. The presented work, aims at developing an approach for transforming and harmonize, traffic related data acquired from highway sensor network, supported by an ITS reference data model (DATEX-II). CRISP-DM methodology is addressed here, as a methodology for guiding the developments of the proposed approach. The main challenge is to cope with a scalable big data- platform for traffic-related data collection, supporting an innovative dynamic toll-charging model in a real-world scenario. This work is supported by a European Commission-funded project, named OPTIMUM, and presents some preliminary results from data harmonization processes developed.