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Automatic Generation of Large-scale 3D Road Networks based on GIS Data
Computers & Graphics ( IF 2.5 ) Pub Date : 2021-04-03 , DOI: 10.1016/j.cag.2021.02.004
Hua Wang , Yue Wu , Xu Han , Mingliang Xu , Weizhe Chen

How to automatically generate a realistic large-scale 3D road network is a key point for immersive and credible traffic simulations. Existing methods cannot automatically generate various kinds of intersections in 3D space based on GIS data. In this paper, we propose a method to generate complex and large-scale 3D road networks automatically with the open source GIS data, including satellite imagery, elevation data and two-dimensional(2D) road center axis data, as input. We first introduce a semantic structure of road network to obtain high-detailed and well-formed networks in a 3D scene. We then generate 2D shapes and topological data of the road network according to the semantic structure and 2D road center axis data. At last, we segment the elevation data and generate the surface of the 3D road network according to the 2D semantic data and satellite imagery data. Results show that our method does well in the generation of various types of intersections and the high-detailed features of roads. The traffic semantic structure, which must be provided in traffic simulation, can also be generated automatically according to our method.



中文翻译:

基于GIS数据的大型3D道路网自动生成

如何自动生成逼真的大规模3D道路网络是沉浸式和可靠交通模拟的关键。现有方法无法基于GIS数据自动在3D空间中生成各种相交。在本文中,我们提出了一种使用开源GIS数据(包括卫星图像,高程数据和二维(2D)道路中心轴数据)作为输入自动生成复杂且大规模的3D道路网络的方法。我们首先介绍道路网络的语义结构,以获取3D场景中的高细节和结构良好的网络。然后,根据语义结构和2D道路中心轴数据,生成道路网络的2D形状和拓扑数据。终于,我们对海拔数据进行分割,并根据2D语义数据和卫星图像数据生成3D道路网的表面。结果表明,我们的方法在生成各种类型的交叉路口和道路的高细节特征方面效果很好。根据我们的方法,也可以自动生成交通仿真中必须提供的交通语义结构。

更新日期:2021-04-04
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