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《Journal of Beijing Institute of Technology》 2004-04
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A Car-Following Model Based on Radial Basis Function Neural Network

REN Xue-mei~1,ZHU Ying-ping~1,WANG Wu-hong~2,HUANG Hong~1 (1.Department of Automatic Control, School of Information Science and Technology, Beijing Institute of Technology, Beijing100081, China; 2.School of Mechanical and Vehicular Engineering, Beijing Institute of Technology, Beijing100081, China)  
It is hard to establish a precise car-following model because of the uncertainty in driver's behavior. A car-following model is developed based on the radial basis function (RBF) network. With this the nearest neighbor-clustering algorithm (NNCA) is improved, and the results of modeling are examined by the car-following data. The simulation results show that the proposed RBF network has a higher precision and requires shorter training in the prediction of the car-following model compared with the multiplayer neural network.
【Fund】: 霍英东青年教师基金资助项目(81069);; 教育部优秀青年教师资助计划项目(1961)
【CateGory Index】: U491
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