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基于非线性交通流模型的交通子区边界控制策略研究

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城市交通流具有复杂的非线性动态特征,用简化的线性交通流模型无法准确描述交通流的非线性特征.因此,在考虑扰动对子区边界控制影响的基础上,首先建立了考虑扰动的非线性城市宏观交通流模型,该模型能够更好地描述实际交通流的运行情况.其次,结合城市交通流运行的周期性特点,设计了基于迭代学习控制的子区边界控制策略,并利用Lipschitz条件和偏导数分析了迭代学习控制律的收敛性.最后,通过仿真案例验证了基于非线性交通流模型的交通子区边界控制策略的有效性.
Traffic Subarea Boundary Control Strategy Based on Nonlinear Traffic Flow Model
Urban traffic flow has complex nonlinear dynamic characteristics,which cannot be accurately described by a simplified linear traffic flow model.Therefore,in this paper,on the basis of considering the influence of perturbation on subarea boundary control,a nonlinear urban macroscopic traffic flow model considering perturbation is firstly established,so that the model can bet-ter describe the operation of actual traffic flow.Secondly,a subarea boundary control strategy based on iterative learning control is designed by combining the periodic characteristics of urban traffic flow operation,and the convergence of the iterative learning control law is analyzed by using the Lipschitz condition and partial derivatives.Finally,the effectiveness of the traffic subarea boundary control strategy based on the nonlinear traffic flow model is demonstrated by simulation cases.

Urban trafficPerimeter controlIterative learning controlNonlinear traffic flow model

王晓龙

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山西省智慧交通研究院有限公司 太原 030032

城市交通 边界控制 迭代学习控制 非线性交通流模型

国家自然科学基金

61703300

2024

计算机科学
重庆西南信息有限公司(原科技部西南信息中心)

计算机科学

CSTPCD北大核心
影响因子:0.944
ISSN:1002-137X
年,卷(期):2024.51(z1)
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