Big Data and Artificial Intelligence for Mobility

BD&AIM-TC Co-chairs and contacts


  • Luis Moreira-Matias


Short description of BD&AIM-TC

The recent technological advances on telecommunications create a new reality on mobility sensing. Nowadays, we live in an era where ubiquitous digital devices are able to broadcast rich information about human mobility in real-time and at a high rate. Such fact exponentially increased the availability of large-scale mobility data (i.e. Big Data) which has been popularized in the media as the new currency, fueling the future vision of our smart cities that will transform our lives. The reality is that we just began to recognize significant research challenges across a spectrum of topics. Consequently, there is an increasing interest among different research communities (ranging from civil engineering to computer science) and industrial stakeholders on build Artificial Intelligence applications leveraging on such data sources. However, such availability also raise privacy issues that must be considered by both industrial and academic stakeholders on using these resources.
Data-driven ITS are a natural consequence of this recent technological context, where commercial solutions already started to follow such trend. Examples enclose intelligent routing applications for private vehicles, ridesharing services, advanced traffic incident and congestion prediction systems or even dynamic pricing tools (e.g. Mobility as a Service).
In this technical committee, we intend to promote activities within the IEEE ITSS that bring together cross-domain experts with interests in Artificial Intelligence topics for Knowledge Discovery, Predictive Analytics, and Intelligent Sequential Decision Making Processes (i.e. contextual Reinforcement Learning) as well as Game Theory equilibrium-seeking applications to Mobility and Transport in general. The ultimate goal is to promote collaborations and cross-disciplinary research that can trigger joint and yet sustainable roadmaps, from automotive and IT industrial stakeholders to governmental and ethic-related organizations.

Work Plan for 2018

The workplan for 2018 consists on developing three activities:
1. A workshop in intelligent public transport (already the 4th edition)
2. A workshop in AI for microscopic mobility (more focused for connected devices of individuals, smartphones and private vehicle FCD and microscopic traffic routing applications)
3. A special session on mobility data mining;
All these activities will be co-located with the IEEE ITSC, the flagship conference for these applications.


  • Different transportation modes and their interactions (road, rail, air and water-based)
  • Intelligent and real-time transportation control and operational management (logistics and mass transit)
  • Electrical Vehicles and energy management
  • Transportation planning and management
  • Trajectory mining and related applications
  • Failures detection and preventive maintenance
  • Distributed and ubiquitous transport technologies and policies
  • Visual Analytics methods for Transport
  • Travel demand analysis and prediction
  • Advanced traveler information systems
  • Intelligent mobility models and policies for urban environments
  • Automatic assessment and/or evaluation on the transport reliability (planning, control and other related policies)
  • Human mobility mining and pervasiveness applications
  • Privacy in collecting, storing and analyzing pervasive mobility/transportation data
  • Traffic control and demand forecasting for high-speed roadways
  • Pedestrians traffic analysis, prediction and safety issues
  • Social impact, land-use and trend analysis
  • Transit assignment and Activity-Choice models
  • Data-driven Intelligent Traffic Lights

Committee Members List

  • Achille Fonzone (Napier University, Edinburgh)
  • Francisco Camara Pereira (DTU, Danmark)
  • Oded Cats (TU Delft)
  • Gaetano Fusco (Sapienza University of Rome)
  • Jihed Khiary (NEC Labs Europe)
  • Joao Mendes-Moreira (University of Porto)
  • Francesco Viti (U. Luxembourg)
  • Mirco Nanni (STI-CNR, Pisa, Italy)
  • Nigel Wilson (MIT, USA)
  • Rahul Nair (IBM Ireland)
  • Roberto Trasarti (KDDLab, CNR-Pisa, Italy)
  • Javier del Ser Lorente (TECNALIA, Spain)