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Symmetric Monotone Embedding of Traffic Flow Networks with First-In-First-Out Dynamics

机译:具有先进先出动态的交通流网络对称单调嵌入

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Abstract: We study a flow network model for vehicular traffic that captures congestion effects at diverging junctions. Standard approaches which rely on monotonicity of the flow dynamics do not immediately apply to such first-in-first-out models. The network model nonetheless exhibits a mixed monotonicity property. Mixed monotonicity enables the original system to be embedded in a system of twice the dimension that is monotone and symmetric. The dynamics of the original system are recovered on a subspace of the embedding system, and we prove global asymptotic stability for a class of networks by considering convergence properties of the embedding system.
机译:摘要:我们研究了一种用于车辆交通的流量网络模型,该模型捕获了在不同路口的拥堵效应。依赖于流动动力学的单调性的标准方法不能立即应用于这种先进先出模型。尽管如此,网络模型仍表现出混合的单调性。混合单调性使原始系统可以嵌入到单调和对称尺寸两倍的系统中。原始系统的动力学是在嵌入系统的子空间上恢复的,并且通过考虑嵌入系统的收敛性质,我们证明了一类网络的全局渐近稳定性。

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