扩展自适应时间间隙汽车跟随模型以提高自适应巡航控制系统的局部和串稳定性

IF 2.8 3区 工程技术 Q3 TRANSPORTATION Journal of Intelligent Transportation Systems Pub Date : 2023-01-02 DOI:10.1080/15472450.2021.1983810
Parthib Khound , Peter Will , Antoine Tordeux , Frank Gronwald
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引用次数: 9

摘要

在本文中,我们扩展了非线性自适应时隙跟车模型,以增强自适应巡航控制系统的局部稳定性和串稳定性,同时考虑了较低级别车辆动力学中的时滞和传感器时滞。过阻尼局部和管柱稳定性分析均采用数学方法进行,并通过仿真进行检验。过阻尼弦稳定性准则满足所有Lp稳定性范数,其中p∈[1,∞]。在这里,我们考虑了纵向控制系统架构的较低级别中运行的时滞、传感器时滞和车队车辆动力学的异质性。没有这些属性的自适应时间间隔模型本质上是稳定的。然而,事实证明,在较低的车辆水平中引入滞后、延迟或异质性会降低稳定性方面的性能,从而产生不安全的阻尼振荡集体行为。此后,我们在不改变基本动力学的情况下,通过将模型转换为均质结构来扩展模型以增强稳定性。结果表明,考虑到执行器时滞、传感器时滞和低水平车辆动力学的异质性,扩展模型满足局部和串稳定性的过阻尼准则。这样的特征被期望用于自动驾驶系统。
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Extending the adaptive time gap car-following model to enhance local and string stability for adaptive cruise control systems

In this paper, we extend the nonlinear adaptive time gap car-following model to enhance the local and string stability for adaptive cruise control systems considering a time-lag in the lower level vehicle dynamics and a sensor time-delay. Both over-damped local and string stability analyses are performed mathematically and examined by simulation. The over-damped string stability criterion fulfills all the Lp stability norms, where p[1,]. Here we consider a time-lag operating in the lower level of the longitudinal control system’s architecture, a sensor time-delay, and heterogeneity in the vehicle dynamics of the platoon. The adaptive time gap model without these attributes is intrinsically stable. However, it turns out that the introduction of a lag, a delay, or heterogeneity in the lower vehicular level reduces the performance in terms of stability, yielding unsafe damped oscillating collective behaviors. Henceforth we extend the model to enhance the stability by transforming the model to a homogeneous structure, without changing the fundamental dynamics. The results show that the extended model satisfies over-damped criteria for both local and string stability, considering actuator time-lag, sensor time-delay, and heterogeneity in the lower level vehicle dynamics. Such features are expected for automated driving systems.

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来源期刊
CiteScore
8.80
自引率
19.40%
发文量
51
审稿时长
15 months
期刊介绍: The Journal of Intelligent Transportation Systems is devoted to scholarly research on the development, planning, management, operation and evaluation of intelligent transportation systems. Intelligent transportation systems are innovative solutions that address contemporary transportation problems. They are characterized by information, dynamic feedback and automation that allow people and goods to move efficiently. They encompass the full scope of information technologies used in transportation, including control, computation and communication, as well as the algorithms, databases, models and human interfaces. The emergence of these technologies as a new pathway for transportation is relatively new. The Journal of Intelligent Transportation Systems is especially interested in research that leads to improved planning and operation of the transportation system through the application of new technologies. The journal is particularly interested in research that adds to the scientific understanding of the impacts that intelligent transportation systems can have on accessibility, congestion, pollution, safety, security, noise, and energy and resource consumption. The journal is inter-disciplinary, and accepts work from fields of engineering, economics, planning, policy, business and management, as well as any other disciplines that contribute to the scientific understanding of intelligent transportation systems. The journal is also multi-modal, and accepts work on intelligent transportation for all forms of ground, air and water transportation. Example topics include the role of information systems in transportation, traffic flow and control, vehicle control, routing and scheduling, traveler response to dynamic information, planning for ITS innovations, evaluations of ITS field operational tests, ITS deployment experiences, automated highway systems, vehicle control systems, diffusion of ITS, and tools/software for analysis of ITS.
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