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Please use this identifier to cite or link to this item: http://hdl.handle.net/2262/20200

Title: Wavelet-Bayesian hierarchical stochastic model for short-term traffic flow at noncritical junctions
Other Titles: Procs of the 87th Annual Meeting of the Transportation Research Board
Author: GHOSH, BIDISHA
BASU, BISWAJIT
O'MAHONY, MARGARET MARY
Sponsor: Higher Education Authority
Author's Homepage: http://people.tcd.ie/mmmahony
http://people.tcd.ie/bghosh
http://people.tcd.ie/basub
Keywords: Intelligent Transportation System (ITS)
Urban transport system
road transport system
traffic volume
traffic condition forecasting
Issue Date: 2008
Citation: Ghosh, B., Basu, B. and O'Mahony, M, Wavelet-Bayesian hierarchical stochastic model for short-term traffic flow at noncritical junctions, Procs of the 87th Annual Meeting of the Transportation Research Board, Washington D.C., January, 2008, CDROM
Abstract: In ITS (Intelligent Transportation System) equipped urban transportation systems noncritical junctions are often ignored in short-term traffic condition prediction algorithms as the traffic data collection systems in these junctions are not adequate. The paper proposes a shortterm traffic volume model based on a combination of discrete wavelet transform (DWT) and Bayesian hierarchical methodology (BHM) applicable to non-critical junctions lacking continuous data collection systems. Unlike typical short-term traffic condition forecasting algorithms, large traffic flow datasets including information on current traffic scenarios are not required for the proposed model. In this model, a non-functional representation of the daily ‘trend’ of urban traffic flow observations is achieved using DWT while the fluctuations in the traffic flow in addition to the variations represented by the ‘trend’ are modeled as a stochastic process using BHM. The time-varying variance (within day) of these fluctuations over the ‘trend’ in urban traffic flow observations at a signalized intersection has been estimated in the model. The effectiveness and the accuracy of the model have been compared with a conventional short-term traffic flow forecasting time-series model based on Holt-Winters Exponential Smoothing (HWES) technique. Both the models are applied at two signalized intersections at the city-centre of Dublin and their performances have been discussed.
Description: PUBLISHED
Washington D.C.
URI: http://pubsindex.trb.org/paperorderform.pdf
http://hdl.handle.net/2262/20200
Related links: http://pubsindex.trb.org/paperorderform.pdf
Appears in Collections:Civil Structural & Environ Eng (Scholarly Publications)

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