Traffic Flow Forecasting Model of Signalized Intersections Based on Particle Swarm Optimization

Author

Jianyu, Zhao ; Lei, Jia ; Yuehui, Chen ; Yong, Zhang

Author_Institution

Jinan Univ., Jinan

fYear

2007

Firstpage

38

Lastpage

40

Abstract

This paper´s research object is two typical adjacent intersections of city road network. A fuzzy neural network model based on particle swarm optimization to forecast the traffic flow is developed, aiming at the characteristic of the city road intersection having signal lamp control. The model comprises a fuzzy cluster module and several feed-forward neural network modules with a particle swarm optimization algorithm to optimize the weights of the NN and parameters of its activation functions. The simulation results show that the model is effective. Compared with BP NN, the model is more practical.

Keywords

feedforward neural nets; fuzzy neural nets; particle swarm optimisation; road traffic; traffic engineering computing; city road intersection; feed-forward neural network; fuzzy cluster module; fuzzy neural network model; particle swarm optimization; signal lamp control; traffic flow forecasting; Cities and towns; Communication system traffic control; Fuzzy control; Fuzzy neural networks; Neural networks; Particle swarm optimization; Predictive models; Roads; Telecommunication traffic; Traffic control; Feed-Forward NN; Forecasting Model; Particle Swarm Optimization; Traffic Flow;

fLanguage

English

Publisher

ieee

Conference_Titel

Control Conference, 2007. CCC 2007. Chinese

Conference_Location

Hunan

Print_ISBN

978-7-81124-055-9

Electronic_ISBN

978-7-900719-22-5

Type

conf

DOI

10.1109/CHICC.2006.4347038

Filename

4347038