Heppe/2017a: Real-Time Public Transport Delay Prediction for Situation-Aware Routing

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
Url https://doi.org/10.1007/978-3-319-67190-1_10

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