智能交通网络的可观测性与冗余性研究
On the Observability and Redundancy of Intelligent Transportation Networks
- Mechatronics Group, Faculty of Mechanical Engineering, Semnan University（萨姆南大学机械工程学院机电组）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本文针对混合交通网络，提出通过增加冗余提升智能交通系统安全可靠性，证明最少n条链路的强连通网络可保证可观测性，并给出图论冗余设计以增强抗故障能力。
AI中文摘要：
通过在车辆信息共享网络中增加冗余，可以显著提升智能交通系统（ITS）的安全性和可靠性。本文首先将有人驾驶车辆与自动驾驶车辆的混合交通建模为通信车辆网络上的分布式系统可观测性问题。我们明确证明，具有最少n条链路（其中n为网络规模）的强连通网络足以保证混合交通网络的可观测性。随后，我们提出图论结果，用于向变化的车辆网络添加冗余，使其能够抵御一定数量车辆/传感器或其数据共享链路失效的影响。最后，我们采用分布式观测器设计，在一个简单的混合交通示例上验证了我们的结果。
英文摘要：
The safety and reliability of intelligent-transportation-systems (ITS) can be greatly enhanced through adding redundancy in the information-sharing network of the vehicles. In this paper, we first model the mixed traffic of human-driven and autonomous vehicles as a distributed system observability problem over a network of communicating vehicles. We clearly show that a strongly-connected network with minimum n links (with n as network size) is sufficient for the observability of mixed traffic network. Then, we present graph-theoretic results on adding redundancy to the changing network of vehicles to make it resilient to the failure of certain number of vehicles/sensors or their data-sharing links. Finally, we employ distributed observer design to validate our results over a simple mixed traffic example.
