Title :
An applicable short-term traffic flow forecasting method based on chaotic theory
Author :
Hu, Jianming ; Zong, Chunguang ; Song, Jingyan ; Zhang, Zuo ; Ren, Jiangtao
Author_Institution :
Dept. of Autom., Tsinghua Univ., Beijing, China
Abstract :
Short-term traffic flow forecasting plays a very important role in urban traffic management and control. In this paper, According to the chaotic property of urban traffic flow, we compute the parameters of phrase space reconstruction for traffic flow system. Meanwhile, a local-forecasting method is introduced to predict urban road short-term traffic flow based on the theory of phrase space reconstruction. Self-organizing Map (SOM) network is introduced to seek the near neighbor. Case study using real traffic flow data from UTC-SCOOT system proves the validity of the method. The research in this paper is a significant attempt to forecast traffic flow from the viewpoint of non-linear time series.
Keywords :
forecasting theory; road traffic; self-organising feature maps; time series; SOM; UTC-SCOOT system; chaotic theory; nonlinear time series; phrase space reconstruction; self organizing map network; short term traffic flow forecasting method; traffic flow data; urban traffic flow system; urban traffic management; Artificial neural networks; Chaos; Communication system traffic control; Intelligent transportation systems; Modems; Stochastic systems; Telecommunication traffic; Time series analysis; Traffic control; Uncertainty;
Conference_Titel :
Intelligent Transportation Systems, 2003. Proceedings. 2003 IEEE
Print_ISBN :
0-7803-8125-4
DOI :
10.1109/ITSC.2003.1252024