Bayesian predictive travel time methodology for advanced traveller information system
Author:
- 4 October 2010
- journal article
- Published by Wiley in Journal of Advanced Transportation
- Vol. 46 (1) , 67-79
Abstract
Travellers can benefit from the availability of point‐to‐point driving time estimates on a real time basis for making travel decisions such as route choice at strategic locations (e.g. junctions of major routes). This paper reports a predictive travel time methodology that features a Bayesian approach to fusing and updating information for use in advanced traveller information system. The methodology addresses the issue that data captured in real time on travel conditions becomes obsolete and has archival value only unless it is used as an input to a predictive travel time method for updating the information. The need for fusing real time data with other factors that influence travel time is defined and the concept of predictive travel time is discussed. The methodological framework and its components are advanced and an example application is provided for illustrating the fusion of data captured by infrastructure‐based and mobile technology with model‐based predictions in order to produce expected travel times. Copyright © 2010 John Wiley & Sons, Ltd.Keywords
This publication has 15 references indexed in Scilit:
- Traffic forecasting using least squares support vector machinesTransportmetrica, 2009
- Short-term prediction of traffic dynamics with real-time recurrent learning algorithmsTransportmetrica, 2009
- USING AUTOMATIC VEHICLE IDENIFICATION DATA FOR TRAVEL TIME ESTIMATION IN HONG KONGTransportmetrica, 2008
- Short‐term travel speed prediction models in car navigation systemsJournal of Advanced Transportation, 2006
- Travel Time Estimation by Combining Probe-Vehicle Data and VICS DataINFRASTRUCTURE PLANNING REVIEW, 2006
- Short-Term Arterial Travel Time Prediction for Advanced Traveler Information SystemsJournal of Intelligent Transportation Systems, 2004
- Predicting Travel Times for the South Jersey Real-Time Motorist Information SystemTransportation Research Record: Journal of the Transportation Research Board, 2003
- Dynamic Freeway Travel-Time Prediction with Probe Vehicle Data: Link Based Versus Path BasedTransportation Research Record: Journal of the Transportation Research Board, 2001
- Using traffic prediction models for providing predictive traveller informationInternational Journal of Technology Management, 2000
- Bayesian Regression-Based Urban Traffic ModelsTransportation Research Record: Journal of the Transportation Research Board, 1998