Real-time travel time prediction models in routing for car navigation applications

• Autorzy: Gaweł P. , Dembczyński K. , Kotłowski W. , Jaszkiewicz A.
• Języki publikacji: EN

Abstrakty

EN

We consider the problem of using real-time floating car data to construct vehicle travel time prediction models meant to be used as input to routing algorithms for finding the fastest (time-shortest) path in the traffic network. More specifically we target the on-line car navigation systems. The travel time estimates for such a system need to be computed efficiently and provided for all short segments (links) of the roads network. We compare several fast real-time methods such as last observation, moving average and exponential smoothing, each combined with a historical traffic pattern model. Through a series of large-scale experiments on real-world data we show that the described approach yields promising results and conclude that specific prediction function form may be less important than a proper control of bias-variance trade-off (achieved by historical and real-time models combination). In addition, we consider two different settings for testing the prediction quality of the models. The first setting concerns measuring the prediction error on short road segments, while the second on longer paths through the traffic network. We show the quality and model parameters vary depending on the assessment method.

Słowa kluczowe

EN

FCD; travel time; prediction; navigation; routing

PL

FCD; czas podróży; prognoza; nawigacja; trasowanie

• Wydawca: Polskie Stowarzyszenie Telematyki Transportu
• Czasopismo: Archives of Transport System Telematics
• Rocznik: 2013
• Tom: Vol. 6, iss. 4
• Strony: 4--8
• Opis fizyczny: Bibliogr. 8 poz.

Twórcy

autor

Gaweł P.

• Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland
• Navi Expert sp. z o.o., Dobrzyckiego 4, 61-692 Poznań, Poland

autor

Dembczyński K.

• Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland

autor

Kotłowski W.

• Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland

autor

Jaszkiewicz A.

• Poznań University of Technology, Piotrowo 2, 60-965 Poznań, Poland

Bibliografia

• [1] Billings , D., Yang , J.: Application of the ARIMA Models to Urban Roadway Travel Time Prediction-A Case Study. In: IEEE International Conference on Systems, Man and Cybernetics, 2006. SMC’06. vol. 3 (2006)
• [2] Dembczyński , K., Kotłowski , W., Gaweł, P., Szarecki, A., Jaszkiewicz, A.: Matrix factorization for travel time estimation in large traffic networks. In: Artificial Intelligence and Soft Computing, Lecture Notes in Computer Science, vol. 7895, pp. 500–510. Springer Berlin Heidelberg (2013)
• [3] Ehmke, J.F., Meisel , S., Mattfeld , D.C.: Floating car based travel times for city logistics. Transportation research part C: emerging technologies 21(1), 338–352 (2012)
• [4] Hiramatsu , A., Nose , K., Tenmoku , K., Morita , T.: Prediction of travel time in urban district based on state equation. Electronics and Communications in Japan 92(7), 1–11 (2009)
• [5] Lee, W., Tseng , S., Tsai, S.: A knowledge based real-time travel time prediction system for urban network. Expert Systems With Applications 36(3P1), 4239–4247 (2009)
• [6] Van Lint, J.: Reliable real-time framework for short-term freeway travel time prediction. Journal of Transportation Engineering 132, 921 (2006)
• [7] Van Lint, J., Hoogendoorn , S., Van Zuylen, H.: Accurate freeway travel time prediction with statespace neural networks under missing data. Transportation Research Part C 13(5-6), 347–369 (2005)
• [8] Zhu, T., Kong , X., Lv, W., Zhang , Y., Du, B.: Travel time prediction for float car system based on time series. In: Advanced Communication Technology (ICACT), 2010 The 12th International Conference on. vol. 2, pp. 1503–1508 (2010)