Short-term Traffic Prediction Model Based on Occupancy
Tan Gua-xian · Control Engineering of China · 2005
Many existing models for traffic prediction are based on traffic flows. As a dual-value function, flow data could not be used to find effectively whether the traffic on the road is good or in congestion. Time-occupancy, which is a single-valued function, is taken to establish a feasible analysis process and traffic prediction model based on ARIMA of urban intersection. In modeling a non-parametric inspection is used to validate the stationary of time series, the AIC rule to estimate orders and the LS method to estimate parameters. In the end, an updating prediction in a CBD intersection proves that occupancy is a better parameter and fit for online prediction in traffic control and information guidance systems quite well.