论文标题
6层模型,用于城市交通和环境的结构化描述和分类
6-Layer Model for a Structured Description and Categorization of Urban Traffic and Environment
论文作者
论文摘要
自动驾驶功能的验证和验证构成了巨大的挑战。当前,研究和行业中研究了基于方案的方法,目的是通过指定安全方案来减少测试工作。为了定义这些场景并在复杂的现实世界设计域中运行,需要对环境进行结构化描述。在Pegasus研究项目中,引入了6层模型(6LM),以描述公路场景。本文完善了6升,并将其扩展到城市交通和环境。正如Pegasus所定义的那样,6LM提供了对环境进行分类的可能性,因此可以作为后续方案描述的结构化基础。该模型可以对一般环境进行结构化描述和分类,而无需结合任何知识或预期参与者的任何功能。除此之外,本文中还详细阐述了6LM的其他多种应用。 6LM包括道路网络和交通指导对象的描述,路边结构,前者的临时修改,动态对象,环境条件和数字信息。手头的工作通过对其项目进行分类来指定每一层。制定了指南,并给出了解释性示例,以标准化该模型在客观环境描述中的应用。与以前的出版物相反,该模型及其设计被更详细地描述了。最后,提出的6LM的整体描述包括将概念扩展到机器感知方面时可能的未来工作的评论。
Verification and validation of automated driving functions impose large challenges. Currently, scenario-based approaches are investigated in research and industry, aiming at a reduction of testing efforts by specifying safety relevant scenarios. To define those scenarios and operate in a complex real-world design domain, a structured description of the environment is needed. Within the PEGASUS research project, the 6-Layer Model (6LM) was introduced for the description of highway scenarios. This paper refines the 6LM and extends it to urban traffic and environment. As defined in PEGASUS, the 6LM provides the possibility to categorize the environment and, therefore, functions as a structured basis for subsequent scenario description. The model enables a structured description and categorization of the general environment, without incorporating any knowledge or anticipating any functions of actors. Beyond that, there is a variety of other applications of the 6LM, which are elaborated in this paper. The 6LM includes a description of the road network and traffic guidance objects, roadside structures, temporary modifications of the former, dynamic objects, environmental conditions and digital information. The work at hand specifies each layer by categorizing its items. Guidelines are formulated and explanatory examples are given to standardize the application of the model for an objective environment description. In contrast to previous publications, the model and its design are described in far more detail. Finally, the holistic description of the 6LM presented includes remarks on possible future work when expanding the concept to machine perception aspects.