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Title: Time-series modelling for forecasting vehicular traffic flow in Dublin
Other Titles: Annual Meeting of the Transportation Research Board Conference: 84th: Washington, D.C.: 2005
Sponsor: Higher Education Authority
Author's Homepage:
Keywords: urban transport network
public transport network
random walk model
Holt-Winters’ exponential smoothing technique
seasonal ARIMA model
traffic flow - Dublin
traffic forecasting
Issue Date: 2005
Publisher: Transportation Research Board of the National Academies
Citation: B. Ghosh, B. Basu and M. O'Mahony, Time-series modelling for forecasting vehicular traffic flow in Dublin: [in proceedings of the ] 84th Transportation Research Board Annual Meeting, Washington D.C., January 9th-13th, 2005, pp[1-22]
Abstract: The traffic flow at an arterial intersection in a congested urban transportation network in the city of Dublin is modelled in this paper. Three different time-series models, viz. random walk model, Holt-Winters’ exponential smoothing technique and seasonal ARIMA model are used for modeling of traffic flow in Dublin. Simulation and short-term forecasting of univariate traffic flow data are done using these models. The data used for modeling are obtained from loop-detectors at a certain junction in the city center of Dublin. Seasonal ARIMA and Holt-Winters’ exponential smoothing technique give highly competitive forecasts and match considerably well with the observed traffic flow data during rush hours.
Description: PUBLISHED
Appears in Collections:Civil Structural & Environ Eng (Scholarly Publications)

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