Finite State Markov Modeling of C-V2X Erasure Links For Performance and Stability Analysis of Platooning Applications
Finite State Markov Modeling of C-V2X Erasure Links For Performance and Stability Analysis of Platooning Applications
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DOI：
10.1109/syscon53536.2022.9773892
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发表时间：
2021-11
期刊：
影响因子：
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通讯作者：
Mahdi Razzaghpour;Adwait Datar;Daniel Schneider;Mahdi Zaman;H. Werner;Hannes Frey;J. Mohammadpour;Y. P. Fallah
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文献类型：
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作者：
Mahdi Razzaghpour;Adwait Datar;Daniel Schneider;Mahdi Zaman;H. Werner;Hannes Frey;J. Mohammadpour;Y. P. Fallah
协作驾驶系统，如排队，依赖于通信和信息交换，以创建每个代理的态势感知。因此，控制组件的设计和性能与通信组件的性能紧密耦合。车辆间的信息流对车队的动力学特性有着重要的影响。因此，车队的性能和稳定性不仅取决于车辆的控制器，而且还取决于信息流拓扑（IFT）。IFT会导致某些队列属性的限制，即，稳定性和可扩展性。蜂窝车联网（C-V2X）已成为支持互联和自动驾驶汽车应用的主要通信技术之一。由于数据包丢失，无线信道造成随机链路中断和网络拓扑的变化。在本文中，我们用一阶马尔可夫模型对车辆之间的通信链路进行建模，以捕获每个链路的普遍时间相关性。这些模型通过在系统设计阶段更好地近似通信链路来实现性能评估。我们的方法是使用数据从实验中建模的分组间间隙（IPG），使用马尔可夫链和推导出连续IPG状态的转移概率矩阵。训练数据是从高保真度模拟中收集的，该模拟使用基于各种不同车辆密度和通信速率的经验数据导出的模型。利用IPG模型，我们分析了均方稳定性的一排车辆与标准的共识协议调整为理想的通信和比较性能的退化，为不同的情况。我们还提出了一些初步的理论结果，揭示了独立的同分布（即）之间的连接。d.）建模方法，忽略了时间相关性的链接和建议的马尔可夫方法。
Cooperative driving systems, such as platooning, rely on communication and information exchange to create situational awareness for each agent. Design and performance of control components are therefore tightly coupled with communication component performance. The information flow between vehicles can significantly affect the dynamics of a platoon. Therefore, both the performance and the stability of a platoon depend not only on the vehicle’s controller but also on the information flow Topology (IFT). The IFT can cause limitations for certain platoon properties, i.e., stability and scalability. Cellular Vehicle-To-Everything (C-V2X) has emerged as one of the main communication technologies to support connected and automated vehicle applications. As a result of packet loss, wireless channels create random link interruption and changes in network topologies. In this paper, we model the communication links between vehicles with a first-order Markov model to capture the prevalent time correlations for each link. These models enable performance evaluation through better approximation of communication links during system design stages. Our approach is to use data from experiments to model the Inter-Packet Gap (IPG) using Markov chains and derive transition probability matrices for consecutive IPG states. Training data is collected from high fidelity simulations using models derived based on empirical data for a variety of different vehicle densities and communication rates. Utilizing the IPG models, we analyze the mean-square stability of a platoon of vehicles with the standard consensus protocol tuned for ideal communication and compare the degradation in performance for different scenarios. We additionally present some initial theoretical results that shed some light on the connection between the independent identical distributed (i.i. d.) modeling approach which neglects the time correlations in links and the proposed Markovian approach.