[论文解读] Are commercially implemented adaptive cruise control systems string stable?

George Gunter, Derek Gloudemans+10 more|arXiv (Cornell University)|May 6, 2019

Traffic control and management参考文献 48被引用 268

一句话总结

这项研究测试了七辆装配2018年ACC的车辆，发现它们都存在字符串不稳定性；通过对超过1,200英里驾驶数据进行数据驱动的延迟微分方程模型标定，并在一个8车编队中验证不稳定性。

ABSTRACT

In this article, we assess the string stability of seven 2018 model year adaptive cruise control (ACC) equipped vehicles that are widely available in the US market. Seven distinct vehicle models from two different vehicle makes are analyzed using data collected from more than 1,200 miles of driving in car-following experiments with ACC engaged by the follower vehicle. The resulting dataset is used to identify the parameters of a linear second order delay differential equation model that approximates the behavior of the black box ACC systems. The string stability of the data-fitted model associated with each vehicle is assessed, and the main finding is that all seven vehicle models have string unstable ACC systems. For one commonly available vehicle model that offers ACC as a standard feature on all trim levels, we validate the string stability finding with a multi-vehicle platoon experiment in which all vehicles are the same year, make, and model. In this test, an initial disturbance of 6 mph is amplified to a 25 mph disturbance, at which point the last vehicle in the platoon is observed to disengage the ACC. The data collected in the driving experiments is made available, representing the largest publicly available comparative driving dataset on ACC equipped vehicles.

研究动机与目标

• 评估当前商业化 ACC 系统在现实世界驾驶中的串稳定性。
• 开发一个基于数据驱动、带时延的跟车模型，以从实地数据近似 ACC 的行为。
• 量化每个测试 ACC 系统的串稳定性，并理解扰动在编队中的传播方式。
• 利用相同车辆进行多车编队实验来验证稳定性结论。

提出的方法

• 使用带时延的微分方程来建模 ACC 动力学，该方程类似于带相对速度项（OVRV）的最优速度模型，并包含一个时延： ˙s_i(t)=v_{i-1}(t)−v_i(t), ˙v_i(t)=k1[s_i(t−τ)−η−t_h v_i(t)]+k2[v_{i−1}(t−τ)−v_i(t)].
• 通过在训练数据上使用 NOMAD，最小化仿真跟随车速与实测车速之间的均方误差，以标定参数（k1、k2、t_h、τ、η）。
• 通过来自带时延系统的头对尾传递函数 Γ(z) 来分析串稳定性，并使用 DDE-BIFTOOL 探索稳定性参数区间。
• 在两种车型、七个模型的驾驶数据中收集超过1,200英里的数据，并进行两车测试以及一个八车编队测试以进行验证。
• 利用公开现场数据并发布数据集供公众使用。

实验结果

研究问题

• RQ1 Are seven commercially available 2018 ACC systems string stable in real-world driving?
• RQ2 Can a data-driven delayed car-following model accurately reproduce ACC behavior across different vehicle models?
• RQ3 Do calibrated ACC models exhibit string instability in simulated platoons?
• RQ4 Does a large platoon validate the instability observed in two-vehicle tests and lead to ACC disengagement in practice?

主要发现

• 在最小跟随和最大跟随设置下，所有七个测试的 ACC 模型都存在串不稳定性。
• 标定的模型参数在车辆之间不同，但产生不稳定的稳定性分类（k1、k2、t_h、τ、η在每辆车上不同）。
• 在一个八车编队中，一个6 mph 的扰动放大到25 mph，然后在最后一辆车退出 ACC，这演示了实际的不稳定性。
• 两车测试和仿真显示，在所研究的所有车辆中，编队中的扰动会增长。
• 公开发布的驾驶数据代表了迄今为止针对装有 ACC 的车辆测试的最大开放数据集。