In the context of smart cities and digital twins, three-dimensional semantic city models are increasingly used for the analyses of large urban areas. While the representation of buildings, terrain, and vegetation has become standard for most city models, detailed spatio-semantic representations of streetspace have played a minor role so far. This is now changing (1) because of data availability, and (2) because recent and emerging applications require having detailed data about the streetspace. The upcoming version 3.0 of the international standard CityGML provides a substantially updated data model regarding the transportation infrastructure, including the representation of the streetspace. However, there already exist a number of other standards and data formats dealing with the representation and exchange of streetspace data. Thus, based on an extensive literature review of potential applications as well as discussions and collaborations with relevant stakeholders, seven key modelling aspects of detailed streetspace models are identified. This allows a structured discussion of representational capabilities of the proposed CityGML3.0 Transportation Model with respect to these aspects and in comparison to the other standards. Subsequently, it is shown that CityGML3.0 meets most of these aspects and that streetspace models can be derived from various data sources and for different cities. Models generated compliant to the CityGML standard are immediately usable for a number of applications. This is demonstrated for some applications, such as land use management, solar potential analyses, and traffic and pedestrian simulations.

中文翻译：

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多种应用的详细街道空间建模：关于拟议的CityGML 3.0运输模型的讨论

在智慧城市和数字双胞胎的背景下，三维语义城市模型越来越多地用于大型城市区域的分析。尽管建筑物，地形和植被的表示法已成为大多数城市模型的标准，但到目前为止，街道空间的详细时空语义表示法起着很小的作用。现在，这种情况正在改变（1）由于数据的可用性，以及（2）因为最近出现的应用程序需要具有有关街道空间的详细数据。国际标准CityGML即将发布的3.0版提供了有关交通基础设施（包括街道空间表示）的实质性更新数据模型。但是，已经存在许多其他有关街道空间数据表示和交换的标准和数据格式。从而，基于对潜在应用的广泛文献综述以及与相关利益相关者的讨论和协作，确定了详细街道空间模型的七个关键建模方面。这允许就这些方面以及与其他标准进行结构化的讨论，以提出的CityGML3.0运输模型的表示能力。随后，表明CityGML3.0满足了大多数这些方面，并且街道空间模型可以从各种数据源和不同城市中派生而来。生成的符合CityGML标准的模型可立即用于许多应用程序。这在某些应用中得到了证明，例如土地使用管理，太阳能潜力分析以及交通和行人模拟。