提出新理论框架,分析自动驾驶车跟驰时的非线性振荡行为。
Nonlinear Oscillatory Response of Automated Vehicle Car-following: Theoretical Analysis with Traffic State and Control Input Limits
- 基于描述函数法,分解跟驰轨迹并建模非线性饱和效应。
- 揭示了加速度与速度极限下的振幅放大与相位偏移特征。
- 适合研究自动驾驶系统在复杂交通中的稳定性,尤其线性方法失效时。
本文基于描述函数(DF)和增量输入描述函数(incremental-input DF)理论,构建了考虑交通状态与控制输入限制的自动驾驶车辆(AV)跟驰系统非线性振荡响应的理论分析框架。现有方法普遍忽略加速度/减速度及速度的饱和限制,仅依赖线性串稳定性分析,而本框架通过将跟驰轨迹分解为稳态与振荡分量,并在振荡坐标系中重新定位受控系统,利用描述函数近似非线性饱和环节的频率响应,捕捉其放大比与相位偏移。由于自动驾驶控制系统具有闭环特性,系统状态与控制输入相互影响,因此需在环路内平衡放大比与相位偏移以保证一致性,该过程可能产生多解,故引入增量输入描述函数筛选合理解。方法经Simulink仿真验证,结果与仿真高度一致,且相比现有方法显著提升分析精度。此外,该框架在传统线性方法给出误导性结论时仍能有效评估串稳定性。
原文摘要 · Abstract (English)
This paper presents a framework grounded in the theory of describing function (DF) and incremental-input DF to theoretically analyze the nonlinear oscillatory response of automated vehicles (AVs) car-following (CF) amidst traffic oscillations, considering the limits of traffic state and control input. While prevailing approaches largely ignore these limits (i.e., saturation of acceleration/deceleration and speed) and focus on linear string stability analysis, this framework establishes a basis for theoretically analyzing the frequency response of AV systems with nonlinearities imposed by these limits. To this end, trajectories of CF pairs are decomposed into nominal and oscillatory trajectories, subsequently, the controlled AV system is repositioned within the oscillatory trajectory coordinates. Built on this base, DFs are employed to approximate the frequency responses of nonlinear saturation components by using their first harmonic output, thereby capturing the associated amplification ratio and phase shift. Considering the closed-loop nature of AV control systems, where system states and control input mutually influence each other, amplification ratios and phase shifts are balanced within the loop to ensure consistency. This balancing process may render multiple solutions, hence the incremental-input DF is further applied to identify the reasonable ones. The proposed method is validated by estimations from Simulink, and further comparisons with prevailing methods are conducted. Results confirm the alignment of our framework with Simulink results and exhibit its superior accuracy in analysis compared to the prevailing methods. Furthermore, the framework proves valuable in string stability analysis, especially when conventional linear methods offer misleading insights.
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