Freeway ramp metering using artificial neural networks

被引:85
|
作者
Zhang, HM [1 ]
Ritchie, SG
机构
[1] Univ Iowa, Dept Civil & Environm Engn, Iowa City, IA 52242 USA
[2] Univ Iowa, Publ Policy Ctr, Iowa City, IA 52242 USA
[3] Univ Calif Irvine, Dept Civil & Environm Engn, Irvine, CA 92697 USA
[4] Univ Calif Irvine, Inst Transportat Studies, Irvine, CA 92697 USA
关键词
ramp metering; feedback control; neural networks;
D O I
10.1016/S0968-090X(97)00019-3
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
This paper proposes a nonlinear approach for designing local traffic-responsive ramp controls using artificial neural networks. The problem is formulated as a nonlinear feedback control problem, where the system model is the well known hydrodynamic model developed by Lighthill and Whitham (1955), and Richards (1956), the model's flow-density relationship is nonlinear, and the feedback nonlinear controllers are composed of one or a number of feed-forward neural networks. These neural network controllers are of integral (I) or proportional-plus-integral (PI) type, and can be tuned on-line to achieve prescribed performance. Initial simulation results show that such an approach is promising. (C) 1997 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:273 / 286
页数:14
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