1. Multivariate traffic forecasting technique using cell transmission model and SARIMA model
- Author
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Szeto, W.Y., Ghosh, Bidisha, Basu, Biswajit, and O'Mahony, Margaret
- Subjects
Traffic estimation -- Models ,Traffic flow -- Research ,Engineering and manufacturing industries ,Science and technology ,Transportation industry - Abstract
The paper develops a short-term space-time traffic flow forecasting strategy integrating the empirical-based seasonal autoregressive integrated moving average (SARIMA) time-series forecasting technique with the theoretical-based first-order macroscopic traffic flow model--cell transmission model. A case study in Dublin city center which has serious traffic congestion is performed to test the effectiveness of the proposed multivariate traffic forecasting strategy. The results show that the forecasts at the junctions only deviate around 10% at a maximum from the original observations and seem to indicate that the proposed strategy is one of the effective approaches to predict the real-time traffic flow level in a congested network especially at the locations where no continuous data collection takes place. DOI: 10.1061/(ASCE)0733-947X(2009)135:9(658) CE Database subject headings: Traffic flow; Traffic models; Seasonal variations; Forecasting; Intersections; Data collections.
- Published
- 2009