Time-series modelling for forecasting vehicular traffic flow in Dublin
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B. Ghosh, B. Basu and M. O'Mahony, Time-series modelling for forecasting vehicular traffic flow in Dublin, 84th Transportation Research Board Conference, National Academies, Washington D.C., Jan, 2005, CDROMDownload Item:
Ghosh, Basu and O'Mahony , time series modelling for forecasting vehicular traffic flow in Dublin.pdf (post-print (author's final copy, post-peer review)) 323.4Kb
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.
Author's Homepage:
http://people.tcd.ie/mmmahonyhttp://people.tcd.ie/basub
http://people.tcd.ie/bghosh
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PUBLISHEDWashington D.C.
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84th Transportation Research Board Conference, National AcademiesType of material:
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