Analysis of intelligent and connected vehicles driving system modeling

Hong Zhang, Zan-Sheng Zheng, Hailiang Yu, Gang Yang, Shengdong Yuan
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Abstract

In response to the limitations of traditional offline static simulation modeling technology in accurately addressing the intricacies and complexities of intelligent and connected vehicles (ICVs) driving processes, this paper introduces the concept of an ICV driving system (ICVDS) model based on digital twin technology. Firstly, the paper delves into the theory of ICVDS digital twin modeling, covering aspects such as model elements and the operational mechanism of the model. The ICVDS, which relies on digital twin (DT) technology, is designed in accordance with the characteristics of ICVs, their technical requirements, and the architecture of the DT system. Subsequently, the paper explores four key areas: the modeling of driving elements, the modeling of the driving process, simulation modeling of the driving process, and a summary of modeling technology. The section on modeling driving elements primarily elucidates the methodology for creating twin models and illustrates how these models describe the system’s functionality in controlling the subject. The segment on modeling the driving process elucidates the approach to real-time data-driven modeling. The part on driving process simulation modeling explains the methodology for establishing simulation models and demonstrates how they predict the future state of the subject. Lastly, the paper introduces the construction of autonomous driving test scenarios based on ICVDS.
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智能互联汽车驾驶系统建模分析
针对传统离线静态仿真建模技术在准确处理错综复杂的智能互联汽车(ICV)驾驶过程方面的局限性,本文提出了基于数字孪生技术的ICV驾驶系统(ICVDS)模型的概念。首先,本文深入探讨了 ICVDS 数字孪生模型的理论,包括模型要素和模型运行机制等方面。根据 ICV 的特点、技术要求和数字孪生系统的架构,设计了基于数字孪生(DT)技术的 ICVDS。随后,本文探讨了四个关键领域:驾驶要素建模、驾驶过程建模、驾驶过程仿真建模和建模技术总结。驾驶要素建模部分主要阐明了创建孪生模型的方法,并说明了这些模型如何描述系统控制主体的功能。驾驶过程建模部分阐明了实时数据驱动建模的方法。驾驶过程仿真建模部分解释了建立仿真模型的方法,并演示了这些模型如何预测主体的未来状态。最后,本文介绍了基于 ICVDS 的自动驾驶测试场景的构建。
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