论文标题
在受攻击的GPS数据下安全排列自动驾驶汽车
Secure Platooning of Autonomous Vehicles Under Attacked GPS Data
论文作者
论文摘要
在本文中，我们研究了如何在未知车辆受到攻击并存在有限的系统不确定性时确保自动驾驶汽车的排量。对于受攻击的车辆，可以通过恶意攻击者任意操纵GPS的位置和速度测量。首先，要找出正在攻击的车辆，通过使用相对测量值（通过摄像头或雷达）和通过相邻车辆的测量获得的本地创新提出了两个探测器。然后，根据检测器的结果，我们通过将饱和方法应用于测量创新，为每辆车设计一个局部状态观察者。此外，根据观察者提供的邻居状态估计，提出了一个分布式控制器以在车辆速度上达成共识，并保持两个相邻车辆之间的固定所需距离。观察者的估计误差和控制器的排量误差显示在某些条件下渐近上限。在数值模拟中还评估了所提出方法的有效性。
In this paper, we study how to secure the platooning of autonomous vehicles when an unknown vehicle is under attack and bounded system uncertainties exist. For the attacked vehicle, its position and speed measurements from GPS can be manipulated arbitrarily by a malicious attacker. First, to find out which vehicle is under attack, two detectors are proposed by using the relative measurements (by camera or radar) and the local innovation obtained through measurements from neighboring vehicles. Then, based on the results of the detectors, we design a local state observer for each vehicle by applying a saturation method to the measurement innovation. Moreover, based on the neighbor state estimates provided by the observer, a distributed controller is proposed to achieve the consensus in vehicle speed and keep fixed desired distance between two neighboring vehicles. The estimation error by the observer and the platooning error by the controller are shown to be asymptotically upper bounded under certain conditions. The effectiveness of the proposed methods is also evaluated in numerical simulations.
