In this paper, we consider coordinated movement of a network of vehicles consisting of a bounded number of malicious agents, that is, vehicles must reach consensus in longitudinal position and a common predefined velocity. The motions of vehicles are modeled by double-integrator dynamics and communications over the network are asynchronous with delays. Each normal vehicle updates its states by utilizing the information it receives from vehicles in its vicinity. On the other hand, misbehaving vehicles make updates arbitrarily and might threaten the consensus within the network by intentionally changing their moving direction or broadcasting faulty information in their neighborhood. We propose an asynchronous updating strategy for normal vehicles, based on filtering extreme values received from neighboring vehicles, to save them from being misguided by malicious vehicles. We show that there exist topological constraints on the network in terms of graph robustness under which the vehicles resiliently achieve coordinated movement. Numerical simulations are provided to evaluate the results.
翻译:在本文中,我们考虑由数量众多的恶意物剂组成的车辆网络的协调移动,即车辆必须在纵向位置和共同的预设速度上达成共识。车辆的移动模式是双集体动力和网络通信的模范,拖拉不动。每个普通车辆利用附近车辆提供的信息更新其状态。另一方面,行为不当的车辆任意更新,可能威胁网络内的共识,故意改变其移动方向或在其附近广播错误的信息。我们提议对普通车辆采取不同步的更新战略,其依据是过滤从邻近车辆收到的极端价值,以免其被恶意车辆误导。我们表明,在车辆以坚固的图形实现机动能力方面,网络存在地形限制。提供了数字模拟,以评价结果。