Combined Method for Travel Time Prediction Based on Wavelet Denoising
The realization of the Intelligent Transportation Systems will effectively solve the problem of traffic congestion and urban traffic pollution, improve the road capacity and traffic safety. A crucial key of the realization of the ITS is the estimate and prediction of travel time: how to make and continuously update prediction of travel time for several minutes into the future using real-time data. In order to analyze the trend of the travel time accurately, combined with superiority of wavelet in dealing with time-varying information, a combined method for travel time prediction based on wavelet denoising and exponential smoothing and metabolic curve fitting model is presented in this paper. The new method has general adaptability because of the methods we selected and the combination strategy we proposed and the use of metabolic treatment in the model. We contrast the new model with models we choose at the end of the paper. And then make a clear analysis and compare on the models. The conclusion shows that the new model is applicable for the real condition and has a better result
component intelligent transportation systems combined prediction exponential smoothing metabolic curve fitting
Feng Jinqiao Sun Zhanquan Liu Wei
High Performance Computing Laboratory Shandong Computer Science Center Jinan, China
国际会议
太原
英文
267-271
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）