Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/33610
Title: A neural-fuzzy controller for intelligent cruise control of vehicle in highways
Authors: Cai, L
Rad, AB
Chan, WL 
Ho, MH
Keywords: Fuzzy control
Fuzzy neural nets
Intelligent control
Neurocontrollers
Radial basis function networks
Road vehicles
Traffic control
Unsupervised learning
Velocity control
Issue Date: 2003
Publisher: IEEE
Source: 2003 IEEE Intelligent Transportation Systems, 2003 : proceedings : 12-15 October 2003, v. 2, p. 1389-1393 How to cite?
Abstract: This paper presents a neuro-fuzzy controller for intelligent cruise control (ICC) of vehicles. One of the objectives of ICC is to achieve automatic vehicle following in a safe, reliable and smooth way. This paper focuses on the longitudinal control by following the speed of the leading vehicle and keeping constant time headway safety distance at the same time. A fuzzy membership function based neural networks is used to combine the advantage of fuzzy logics and neural network. This network is similar to radial basis function network (RBFN) and can be used for online learning due to its fast training. Simulation results are included to show the validity of the algorithm.
URI: http://hdl.handle.net/10397/33610
ISBN: 0-7803-8125-4
DOI: 10.1109/ITSC.2003.1252712
Appears in Collections:Conference Paper

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