Time to Equilibrium in a Car-Following Scenario under Local Stable Conditions

Junfan Zhuo, Feng Zhu
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Abstract

In traffic flow stability analysis, extensive research has been conducted on stability criteria, offering binary classifications of stability, that is, defining flow as stable or unstable. Despite being informative, this classification falls short of providing detailed characteristics of stability, such as the time required for a vehicle to regain equilibrium subject to a disturbance from a preceding vehicle. To address this problem, in this study, a quantitative metric, the time to equilibrium (TTE), is introduced under the condition of local stability. In a car-following scenario of two vehicles, considering that the preceding vehicle undergoes a short-term deceleration–acceleration change, an analytical formulation of the TTE is derived by employing linear stability analysis with the disturbance approximated using the Dirac delta function. The bisection method is then applied to approximate analytical solutions. Subsequent simulation experiments, utilizing various car-following parameters and disturbance settings, demonstrate the general validity of the proposed analytical TTE, barring some large errors in extreme scenarios (unlikely in real-world driving) and the intrinsic features of the Dirac delta function. We then provide applicable ranges for car-following parameters with different selection criteria. Lastly, by using real-world vehicle trajectory data, the proposed TTE is further validated.
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在局部稳定条件下的汽车跟随情景中达到平衡的时间
在交通流稳定性分析中,对稳定性标准进行了大量研究,对稳定性进行了二元分类,即把交通流定义为稳定或不稳定。尽管这种分类方法很有参考价值,但却无法提供稳定性的详细特征,例如车辆在前车干扰下恢复平衡所需的时间。为解决这一问题,本研究在局部稳定性条件下引入了一个量化指标,即恢复平衡时间(TTE)。在两辆车跟车的情况下,考虑到前一辆车会发生短期的减速-加速变化,通过线性稳定性分析,并使用 Dirac delta 函数近似扰动,得出了 TTE 的解析公式。然后采用分段法求得近似分析解。随后,利用各种汽车跟随参数和干扰设置进行了模拟实验,证明了所提出的分析 TTE 的普遍有效性,但在极端情况下(在实际驾驶中不太可能出现)会出现较大误差,而且 Dirac delta 函数具有固有特征。然后,我们提供了不同选择标准下汽车跟随参数的适用范围。最后,通过使用真实世界的车辆轨迹数据,进一步验证了所提出的 TTE。
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