Personal Transport Advisor: an integrated platform of mobility patterns for Smart Cities to enable demand-adaptive transportation system

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The aim of this project is to develop a service platform that connects the providers and controllers of transport in cities with the travellers in a way that information flows are optimized while respecting and supporting the individual freedom safety and security of the traveller. Cities will get an integrated platform to enable the provision of citizen-centric, demand-adaptive city-wide transportation services. Travellers will get mobile applications that facilitate them in making travel priorities and choices for route and modality.

The work will result in a city-wide transportation system comprised of several sub-systems that involve transportation services and policies to be adaptive to the travel demand of the citizens. To achieve this, the platform:

  • fuses different data from various city sources, travel operators and citizens
  • performs a broad class of data analytics, including the detection of real-time events, the discovery of mobility patterns and the inference of predictive models
  • provides information to the transportation service management and city stakeholders to optimize the transportation offerings according to the citizens’ interests

The platform addresses key research challenges by

  • enabling a coherent model of mobility patterns via the capture of their multi-dimensional, collective, analytical and dynamic aspects
  • driving the application of this model via incorporation into various transportation services and city-level policy evaluations

The project includes a careful attention to the governance aspects on how to handle the public vs. private and privacy issues of connecting travellers, cities and transport providers through the PETRA platform.
Three cities with very different features played the role of case studies and instantiations of the platform, providing an evaluation of the platform and the potential of the implemented tools and services on each context:

  • Rome: case study focused on transport and vehicular traffic for residents, including as special event the 1-year Jubilee, from Dec 8th, 2015
  • Venice: characterized by touristic flows, focused on pedestrian movement and crowd management
  • Haifa: characterized by dense traffic in a small area, focused on access to specific events

The consortium:

Scientific/ICT partners:

  • KTH Stockholm, Project coordinator: Mobility simulation technologies, Gaming environments
  • IBM Ireland: Journey planning systems with uncertainty, Data management platforms
  • CNR Pisa: Mobility data analysis, Privacy risk assessment and mitigation

City mobility administrations:

  • Rome: Roma Servizi per la Mobilità
  • Venice: Azienda Veneziana Della Mobilità
  • Haifa: City of Haifa - Traffic department, Technion


  • TUD Delft
Trasarti, R., R. Guidotti, A. Monreale, and F. Giannotti, "MyWay: Location prediction via mobility profiling", Information Systems, vol. 64, pp. 350–367, 03/2017.
Guidotti, R., and M. Berlingerio, "Where Is My Next Friend? Recommending Enjoyable Profiles in Location Based Services", Complex Networks VII: Springer International Publishing, pp. 65–78, 2016.
Monreale, A., and H. Wendy Wang, "Privacy-Preserving Outsourcing of Data Mining", 40th IEEE Annual Computer Software and Applications Conference, {COMPSAC} Workshops 2016, Atlanta, GA, USA, June 10-14, 2016, Atlanta, GA, USA, IEEE Computer Society, 2016.
Guidotti, R., A. Monreale, S. Rinzivillo, D. Pedreschi, and F. Giannotti, "Unveiling mobility complexity through complex network analysis", Social Network Analysis and Mining, vol. 6, no. 1, pp. 59, 2016.
Guidotti, R., and P. Cintia, "Towards a Boosted Route Planner Using Individual Mobility Models", Software Engineering and Formal Methods: Springer Berlin Heidelberg, pp. 108–123, 2015.
Botea, A., S. Braghin, N. Lopes, R. Guidotti, and F. Pratesi, "Managing travels with PETRA: The Rome use case", 2015 31st IEEE International Conference on Data Engineering Workshops (ICDEW): IEEE, 2015.
Berlingerio, M., V. Bicer, A. Botea, S. Braghin, N. Lopes, R. Guidotti, and F. Pratesi, "Mobility Mining for Journey Planning in Rome", Machine Learning and Knowledge Discovery in Databases: Springer International Publishing, 2015.
de Lira, V M., V C. Times, C. Renso, and S. Rinzivillo, "ComeWithMe: An Activity-Oriented Carpooling Approach", 2015 {IEEE} 18th International Conference on Intelligent Transportation Systems: Institute of Electrical {&} Electronics Engineers ({IEEE}), 09/2015.


Image by Thomas Le Ngo CC BY-NC-ND 2.0, via Flickr
Start Date
1 February 2014
End Date
31 January 2017
European Project
Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)