DocumentCode
2332250
Title
A neural network approach for freeway traffic flow prediction
Author
Messai, Nadhir ; Thomas, Philippe ; Lefebvre, Dimitri ; Moudni, Abdellah El
Author_Institution
SeT, UTBM, Belfort, France
Volume
2
fYear
2002
fDate
2002
Firstpage
984
Abstract
Traffic flow modeling is an essential component of any traffic control or monitoring system. This paper presents a new short term traffic flow prediction model based on a feedforward neural network. The structure determination of this neural network is viewed as a system identification problem, and the model performances are validated using both simulation and real traffic data obtained from the I-880 freeway in Hayward, California.
Keywords
feedforward neural nets; identification; road traffic; traffic control; traffic engineering computing; California; feedforward neural networks; flow prediction; macroscopic traffic models; road traffic; simulation; system identification; traffic flow modeling; traffic flow prediction; Communication system traffic control; Electronic mail; Feedforward systems; Neural networks; Nonlinear equations; Power system modeling; Predictive models; System identification; Telecommunication traffic; Traffic control;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Applications, 2002. Proceedings of the 2002 International Conference on
Print_ISBN
0-7803-7386-3
Type
conf
DOI
10.1109/CCA.2002.1038737
Filename
1038737
Link To Document