论文标题

随机港口 - 哈米尔顿港的稳定性分析模型

Stability analysis of a stochastic port-Hamiltonian car-following model

论文作者

Rüdiger, Barbara, Tordeux, Antoine, Ugurcan, Baris

论文摘要

哈米尔顿港系统是许多非线性物理系统的相关表示。在这项研究中,我们制定和分析具有系统的港口港口结构的随机汽车跟随模型的一般类别。模型类是对经典汽车跟随方法的概括,包括Bando等人的最佳速度模型。 (1995),江等的完整速度差异模型。 (2001年),以及基于Ornstein-Uhlenbeck过程的最新随机模型。与传统模型完全不对称的传统模型(即仅取决于速度和距离前任的距离),哈米尔顿港(Port-Hamiltonian)的跟踪模型也取决于与追随者的距离。我们通过$ N $车辆和周期性界限确定有限系统的确切稳定性条件。稳定的系统具有巨像,具有独特的高斯不变度。使用数值模拟研究了模型的其他属性。事实证明,哈密顿的成分改善了流动稳定性并减少了系统中的总能量。此外,即使在存在随机扰动的情况下,它也可以防止具有振荡动力学的停止波的有问题形成。

Port-Hamiltonian systems are pertinent representations of many nonlinear physical systems. In this study, we formulate and analyse a general class of stochastic car-following models with a systematic port-Hamiltonian structure. The model class is a generalisation of classical car-following approaches, including the optimal velocity model of Bando et al. (1995), the full velocity difference model of Jiang et al. (2001), and recent stochastic following models based on the Ornstein-Uhlenbeck process. In contrast to traditional models where the interaction is totally asymmetric (i.e., depending only on the speed and distance to the predecessor), the port-Hamiltonian car-following model also depends on the distance to the follower. We determine the exact stability condition of the finite system with $N$ vehicles and periodic boundaries. The stable system is ergodic with a unique Gaussian invariant measure. Other properties of the model are studied using numerical simulation. It turns out that the Hamiltonian component improves the flow stability and reduces the total energy in the system. Furthermore, it prevents the problematic formation of stop-and-go waves with oscillatory dynamics, even in the presence of stochastic perturbations.

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