The Model of Short-Time Traffic Flow Prediction on High-Grade Highway

Abstract:

Article Preview

In order to study the short-time traffic flow prediction on high-grade highway, the article proposed a model based on wavelet analysis and RBF neural network. Aiming to the traffic flow’s characteristic of highway, the study focus on three facet: network topology, the difference of continuous flow and discontinuous flow , the flow of lanes’ uplink and downlink are not equal. Thus the article use the wavelet analysis to do data preprocessing, then structure the model of short-term traffic flow prediction based on RBF neural network. The experiment result shows that the new hybrid model adapt to high-grade highway, and model considering traffic flow characteristic is better than the model which is not. Meanwhile the model has the higher precision of prediction.

Info:

Periodical:

Advanced Materials Research (Volumes 255-260)

Edited by:

Jingying Zhao

Pages:

4128-4132

DOI:

10.4028/www.scientific.net/AMR.255-260.4128

Citation:

H. Chen et al., "The Model of Short-Time Traffic Flow Prediction on High-Grade Highway", Advanced Materials Research, Vols. 255-260, pp. 4128-4132, 2011

Online since:

May 2011

Export:

Price:

$38.00

[1] REN Qi-liang, XIE Xiao-song: Journal of Highway and Transportation Research and Development , Vol. 25 (2008), pp.134-138.

[2] ONG Xiao-xiong, AN Guo-xian: Journal of Traffic and Transportation Engineering, Vol. 6(2006), pp.103-107.

[3] CHEGN Li-zhi, ANG Hong-xia, LUO Yong: Wavelet theory and application (China science press, Beijing 2004), in Chinese.

[4] HU Jie: Journal of Yangtze university, Vol. 4 (2007. 9), pp.74-76.

[5] ZHANG Xiao-li: Information and Control , Vol. 36(2007), pp.467-475.

[6] Nadhir Messai, Philippe Thomas, Dimirei Lefebvre: In: Proceedings of the 2002 IEEE International Conference on Control Applications. Scotland U.K. 2002. pp.984-989.

In order to see related information, you need to Login.