VANET应用测试与评估的多分辨率建模

M. Schiller, Thomas Behrens, A. Knoll
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引用次数: 4

摘要

由于需要可重复的场景和大规模的实验,未来基于车辆自组织网络(VANETs)的驾驶辅助系统在真实测试平台上的评估和测试非常困难。因此,提出了一种基于多分辨率建模的新框架,利用模拟环境中的虚拟试驾,在大规模场景中准确高效地测试汽车软件。该方法能够对现实世界的实现进行精确和大规模的评估。这是通过同步执行代表车辆和网络领域的多分辨率仿真模型,以及封装在虚拟电子控制单元中的应用程序来完成的。本文对应用的多分辨率方法进行了详细和正式的描述,并解释了开发的通用测试平台及其组成的组件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-resolution-Modeling for Testing and Evaluation of VANET Applications
The evaluation and testing of future driving assistance systems based on Vehicular Ad-hoc Networks (VANETs) in real testbeds is difficult due to the need for repeatable scenarios and large-scale experiments. Therefore, a novel framework based on multi-resolution modeling is presented to test automotive software both accurately and efficiently in large-scale scenarios using virtual test drives in a simulated environment. The approach enables the precise and large-scale evaluation of real-world implementations. This is done through the synchronized execution of simulation models of multiple resolutions representing the vehicle and network domain, as well as the applications encapsulated in virtual Electronic Control Units. This paper provides a detailed and formal description of the applied multi-resolution methodology and explains the developed generic testing platform and the components it is comprised of.
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