基于光滑弧样条的不同道路类型映射策略评价

Stephan Brummer, F. Janda, G. Maier, A. Schindler
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引用次数: 10

摘要

数字地图通过提供车辆的当地环境信息,丰富了先进的驾驶员辅助系统。本文给出了一种以光滑弧样条为几何模型的映射策略的各种结果。对于任意给定的公差,曲线逼近法(SMAP)生成具有尽可能少的曲线段数的光滑弧样条。评价结果表明,该方法在精度、数据量和显著曲率特征方面均取得了良好的效果。可以说,弧样条近似在信息内容和片段数量方面通常优于多边形表示,这对地图计算的计算复杂性和地图存储所需的数据量有直接影响。这些特性对于许多驾驶辅助系统的应用都是有益的,比如自动驾驶。此外,曲线顶点的曲率估计在较大的近似容差值范围内具有广泛的稳定性,这对曲线速度预警至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of a mapping strategy based on smooth arc splines for different road types
Digital maps enrich advanced driver assistance systems by providing information on the local environment of a vehicle. This paper presents various results of a mapping strategy which uses smooth arc splines as geometric model. For any given tolerance, the curve approximation method (SMAP) generates a smooth arc spline with the minimally possible number of curve segments. The evaluation shows the performance of this method regarding the accuracy, the data volume and significant curvature characteristics on both rural and highway roads. It can be stated that the arc spline approximation generally outperforms polygonal representations regarding the information content and the number of segments which has a direct influence on the computational complexity of map calculations and the required data volume for the map storage. These properties are beneficial for many driver assistance system applications like autonomous driving. Furthermore, it is shown that the curvature estimation in the curve apexes is widely stable for a broad range of approximation tolerance values which is crucial for curve speed warnings.
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