Time-series modelling for forecasting vehicular traffic flow in Dublin
Item Type:Conference Paper
Citation: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, CDROM
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
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.
Other Titles:84th Transportation Research Board Conference, National Academies
Type of material:Conference Paper
Availability:Full text available