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Robust Perimeter Control for Two Urban Regions with Macroscopic Fundamental Diagrams: A Control-Lyapunov Function Approach

机译:具有宏观基本图的两个城市区域的鲁棒周界控制:Control-Lyapunov函数方法

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Abstract: The Macroscopic Fundamental Diagram (MFD) framework has been widely utilized to describe traffic dynamics in urban networks as well as to design perimeter flow control strategies under stationary (constant) demand and deterministic settings. In real world, both the MFD and demand however suffer from various intrinsic uncertainties while travel demand is of time-varying nature. Hence, robust control for traffic networks with uncertain MFDs and demand is much appealing and of greater interest in practice. In literature, there would be a lack of robust control strategies for the problem. One major hurdle is of requirement on model linearization that is actually a basis of most existing results. The main objective of this paper is to explore a new robust perimeter control framework for dynamic traffic networks with parameter uncertainty (on the MFD) and exogenous disturbance induced by travel demand. The disturbance in question is in general time-varying and stochastic. Our main contribution focuses on developing a control-Lyapunov function (CLF) based approach to establishing a couple of universal control laws, one is almost smooth and the other is Bang-bang like, for different implementation scenarios. Moreover, it is indicated that the almost smooth control is more suited for road pricing while the Bang-bang like is for signal timing. In sharp contrast to existing methods, in which adjusting extensive design parameters are usually needed, the proposed methods can determine the control in an automatic manner. Furthermore, numerical results demonstrate that the control can drive the system dynamics towards a desired equilibrium under various scenarios with uncertain MFDs and travel demand. Both stability and robustness can be substantially observed. As a major consequence, the proposed methods achieve not only global asymptotic stability but also appealing robustness for the closed-loop traffic system.
机译:摘要:宏观基本图(MFD)框架已被广泛用于描述城市网络中的交通动态,以及在固定(恒定)需求和确定性设置下设计周边流量控制策略。然而,在现实世界中,MFD和需求都遭受各种内在的不确定性,而旅行需求具有时变性质。因此,对于具有不确定的MFD和需求的交通网络的鲁棒控制非常有吸引力,并且在实践中引起了更大的兴趣。在文献中,将缺少针对该问题的鲁棒控制策略。对模型线性化的要求是一个主要障碍,实际上这是大多数现有结果的基础。本文的主要目的是探索一种具有参数不确定性(在MFD上)和由旅行需求引起的外源性干扰的动态交通网络的鲁棒周界控制框架。所讨论的干扰通常是随时间变化的并且是随机的。我们的主要贡献集中在开发基于控制李雅普诺夫函数(CLF)的方法,以建立几种通用控制律,一种适用于不同的实现方案,一种几乎是平滑的,另一种则类似于Bang-bang。此外,表明几乎平滑的控制更适合于道路定价,而Bang-bang之类的则用于信号定时。与通常需要调整大量设计参数的现有方法形成鲜明对比的是,提出的方法可以自动确定控制方式。此外,数值结果表明,在具有不确定的MFD和行程需求的各种情况下,该控制可以驱动系统动力学达到所需的平衡。可以同时观察到稳定性和鲁棒性。作为主要结果,所提出的方法不仅实现了全局渐近稳定性,而且还为闭环交通系统带来了吸引力。

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