From an end users’ point of view, the AI-based ETA service improves the accessibility of intermodal transports and calculation of intermodal routes and transport durations. Therefore, an open data approach is used, where the system collects, preprocesses and learns from open data sources only to provide large-scale accessibility.
Essential Features
- Front End for planning and overview of intermodal transports
- Service-component to save and track transports generated in the Front End
- ETA-component which enables communication between data services and performs intermodal route optimization
- Translation of addresses to geocoordinates (using OSM Nominatim Geocoder)
- Road route optimization for road transports (using Valhalla Routing Engine)
- Intermodal route optimization for combined transports
- AI-component to perform ETA-prediction on road transports using live Germany highway data
- Implementation of data services, e.g. q,V-stations of German highway network
- Implementation of a weather service

Contact
Kai Hannemann, kai.hannemann@iml.fraunhofer.de
Alex Rotgang, alex.rotgang@iml.fraunhofer.de