V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures
V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures
复制标题
采用基于混合高斯过程的模型结构的 V2X 系统架构
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Y. P. Fallah
中科院分区：
文献类型：
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作者：
Hossein Nourkhiz Mahjoub;Behrad Toghi;S. Gani;Y. P. Fallah
可扩展的通信是至关重要的可靠传播的时间敏感的信息在合作车辆自组织网络（VANESTs），这反过来又是一个重要的前提条件，适当的操作的关键合作安全应用程序。基于模型的通信（MBC）是近年来在文献中提出的一种可扩展性解决方案，它在很大程度上减少信道拥塞方面表现出了很大的潜力。在这项工作中，基于MBC概念，提出了一种用于车辆到万物（V2X）通信的技术不可知的混合模型选择策略，该策略受益于非参数贝叶斯推理技术，特别是高斯过程的特性。实验结果表明，该通信结构在降低所需的消息交换率和提高远程代理跟踪精度方面是有效的。
Scalable communication is of utmost importance for reliable dissemination of time-sensitive information in cooperative vehicular ad-hoc networks (VANETs), which is, in turn, an essential prerequisite for the proper operation of the critical cooperative safety applications. The model-based communication (MBC) is a recently-explored scalability solution proposed in the literature, which has shown a promising potential to reduce the channel congestion to a great extent. In this work, based on the MBC notion, a technology-agnostic hybrid model selection policy for Vehicle-to-Everything (V2X) communication is proposed which benefits from the characteristics of the non-parametric Bayesian inference techniques, specifically Gaussian Processes. The results show the effectiveness of the proposed communication architecture on both reducing the required message exchange rate and increasing the remote agent tracking precision.