Intelligent simulation and prediction of traffic flow dispersion

Fengxiang Qiao, Hai Yang and William H. K. Lam

Transportation Research Part B: Methodological, 2001, vol. 35, issue 9, 843-863

Abstract: Dispersion of traffic flow on urban road segments is often described by some typical statistical models such as the normal distribution model and the geometric distribution model. These probability-based models can fit traffic flow well under ideal physical environments but may not work satisfactory in certain complex cases because of their strict mathematical assumptions. A neural network-based system identification approach is used to establish an auto-adaptive model for simulating traffic flow dispersion. This model, being feasible to a wide variety of traffic circumstances, can be calibrated and used for on-line traffic flow forecasting. Data simulation and field-testing show reliable performance of the proposed intelligent approach.

Date: 2001
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