Mesoscopic V2X simulation framework to enhance simulation performance

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Tamás Ormándi, Balázs Varga
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引用次数: 0

Abstract

The rapid evolution of vehicular communication has led to numerous new algorithms and applications based on this technology. Neglecting issues arising from wireless communication, such as the loss of information and delays, can result in problems such as reduced performance or compromised safety. However, while simulating V2X demands significant computational resources, it proves unsuitable for complex testing setups, including mixed-reality testing. This paper enhances V2X simulation by relying on an ecosystem based on SUMO, OMNeT++, Veins, and INET simulation tools. The proposed novel method introduces mesoscopic simulation in Vehicular Ad-hoc Networks to increase simulation performance to a level where real-time behavior is achievable. Meanwhile, it can also be beneficial in the acceleration of regular simulations. The presented solution introduces Meso nodes that are capable of aggregating communication across an entire traffic area, facilitated by a neural network function approximator. Results showed substantial performance gain while simulation accuracy was preserved.

Abstract Image

介观 V2X 仿真框架提升仿真性能
车辆通信的快速发展催生了大量基于该技术的新算法和应用。忽视无线通信所产生的问题,如信息丢失和延迟,可能会导致性能降低或安全受损等问题。然而,模拟 V2X 需要大量的计算资源,不适合复杂的测试设置,包括混合现实测试。本文依靠基于 SUMO、OMNeT++、Veins 和 INET 仿真工具的生态系统来增强 V2X 仿真。所提出的新方法在车载 Ad-hoc 网络中引入了介观仿真,将仿真性能提高到可实现实时行为的水平。同时,这种方法也有利于加速常规仿真。所提出的解决方案引入了中子节点,这些节点能够通过神经网络函数近似器在整个交通区域内汇聚通信。结果表明,在保持仿真精度的同时,性能也得到了大幅提升。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
7.20
自引率
4.30%
发文量
567
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