| Bibtype |
Inbook |
| Bibkey |
Heppe/2017a |
| Author |
Heppe, Lukas and Liebig, Thomas |
| Ls8autor |
Heppe, Lukas
Liebig, Thomas
|
| Editor |
Kern-Isberner, Gabriele and Fürnkranz, Johannes and Thimm, Matthias |
| Title |
Real-Time Public Transport Delay Prediction for Situation-Aware Routing |
| Booktitle |
KI 2017: Advances in Artificial Intelligence: 40th Annual German Conference on AI, Dortmund, Germany, September 25--29, 2017, Proceedings |
| Pages |
128--141 |
| Address |
Cham |
| Publisher |
Springer International Publishing |
| Abstract |
Situation-aware route planning gathers increasing interest. The proliferation of various sensor technologies in smart cities allows the incorporation of real-time data and its predictions in the trip planning process. We present a system for individual multi-modal trip planning that incorporates predictions of future public transport delays in routing. Future delay times are computed by a Spatio-Temporal-Random-Field based on a stream of current vehicle positions. The conditioning of spatial regression on intermediate predictions of a discrete probabilistic graphical model allows to incorporate historical data, streamed online data and a rich dependency structure at the same time. We demonstrate the system with a real-world use-case at Warsaw city, Poland.
|
| Year |
2017 |
| Projekt |
vavel |
| Isbn |
978-3-319-67190-1 |
