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Automotive IUI

Multimodal Transportation Systems

Multimodality and sharing resources is seen to be the future of transportation in condensed, urban areas. Multimodal transportation systems help people to find their optimal way of traveling by offering them shared transportation resources (vehicles, bikes, public transport etc.) as a complement to their own vehicles. In this way, not only do they assist individuals in optimizing their trips (time, money and effort wise), but also help solving some of the biggest problems of urban living: traffic congestion, noise and pollution.

To be able to leave cars at home or at parking places outside a city center and change to public transportation systems, people have to be aware of

  • Alternative connections and mobility services (e.g., (e)-car, (e)-bike sharing)
  • Parking places where they can leave their cars
  • Ticketing information
  • Real value, in terms of time, cost, carbon footprint, of the alternative choices computed on the basis of real time data (e.g., traffic jams, parking unavailability)
  • Reasons or stimuli to change the common mobility behavior

Integrating different data sources, considering a variety of user requirements, preferences and expectations and providing personal support makes creating a multimodal transportation system a challenging problem.

Data correlation is in the focus of our research. We develop techniques for gathering and pre-processing the real-time data that can affect the personalized intermodal route recommendations. The captured traffic data is analyzed regarding which route is affected, giving the input to the intermodal mobility data representation.