Comparison of traffic flow prediction based on AR model and BP model - Tingting ZHANG; Wuxiong ZHANG; Dong PEI; Cheng ZHAO; Han YU (Dianxin kexue)
Traffic flow modeling plays an important role in routing，MAC algorithm and protocol designs in vehicular Ad Hoc networks （VANET）. An accurate traffic flow model is crucial to traffic management of an intelligent transportation system （ITS）and information safety in a VANET. Based on Shanghai’s traffic flow data，the performance of the two different models was compared using auto regressive（AR）model and back-propagation（BP） network model，and the corresponding prediction result was given. Research finds that both of the two models can efficiently predict the traffic data，but they have different prediction accuracy for the data of different periods. The research result will provide support for future research on ITS and VANET.