Dynamic route planning with real-time traffic predictions. (March 2017)

• Record Type: Journal Article
• Authors: Liebig, Thomas; Piatkowski, Nico; Bockermann, Christian; Morik, Katharina
• Is Part Of: Information systems. Volume 64(2017)
• Page Start: 258
• Page End: 265
• Publication Date: 2017-03
• Subjects: Trip planning -- Real-time traffic model -- Traffic flow estimation; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2016.01.007
• Languages: English
• ISSNs: 0306-4379

Abstract

Abstract: Situation aware route planning gathers increasing interest as cities become crowded and jammed. We present a system for individual trip planning that incorporates future traffic hazards in routing. Future traffic conditions are computed by a Spatio-Temporal Random Field based on a stream of sensor readings. In addition, our approach estimates traffic flow in areas with low sensor coverage using a Gaussian Process Regression. The conditioning of spatial regression on intermediate predictions of a discrete probabilistic graphical model allows us 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 from Dublin city, Ireland. Abstract : Highlights: Dynamic traffic cost prediction. Situation dependent trip planner. Prediction-as-a-service with TUD streams framework.