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Stability analysis methods and their applicability to car-following models in conventional and connected environments

机译:稳定性分析方法及其在常规和关联环境中对汽车跟踪模型的适用性

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摘要

The paper comprehensively reviews major methods for analysing local and string stability of car-following (CF) models. Specifically, three types of CF models are considered: basic, time-delayed, and multi-anticipative/cooperative CF models. For each type, notable methods in the literature for analysing its local stability and string stability have been reviewed in detail, including the characteristic equation based method (e.g., root extracting, the root locus method, the Routh-Hurwitz criterion, the Nyquist criterion and the Hopf bifurcation method), Lyapunov criterion, the direct transfer function based method, and the Laplace transform based method. In addition, consistency and applicability of stability criteria obtained using some of these methods are objectively compared with the simulation result from a series of numerical experiments. Finally, issues, challenges, and research needs of CF models' stability analysis in the era of connected and autonomous vehicles are discussed. (C) 2018 Elsevier Ltd. All rights reserved.
机译:本文全面回顾了主要的方法来分析汽车跟随(CF)模型的局部和弦稳定性。具体来说,考虑三种类型的CF模型:基本CF模型,延时CF模型和多预期/合作CF模型。对于每种类型,已经详细回顾了文献中用于分析其局部稳定性和弦稳定性的著名方法,包括基于特征方程的方法(例如,根提取,根轨迹方法,Routh-Hurwitz准则,Nyquist准则和(Hopf分叉法),Lyapunov准则,基于直接传递函数的方法和基于Laplace变换的方法。此外,将使用其中一些方法获得的稳定性标准的一致性和适用性与一系列数值实验的模拟结果进行了客观比较。最后,讨论了互联和自动驾驶时代CF模型稳定性分析的问题,挑战和研究需求。 (C)2018 Elsevier Ltd.保留所有权利。

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