自动驾驶高清地图道路标线的摆线测绘

Barbara Gallazzi, Paolo Cudrano, Matteo Frosi, S. Mentasti, Matteo Matteucci
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引用次数: 2

摘要

车道级高清地图对于当前自动驾驶汽车的轨迹规划和控制至关重要。因此,应该采用合适的线模型来定义它们。虽然映射算法通常依赖于不准确的表示,但clo仿线曲线具有特殊的平滑特性,使其成为控制算法中道路线的理想表示。我们提出了一种基于梭线样条模型的多级管道,用于从单目视觉生成车道级高清地图。我们使用线检测算法获得线位置的测量,并且我们利用基于图的优化框架来达到最佳拟合。迭代贪心过程减少了模型的复杂度,去掉了不必要的曲面。我们在真实世界的数据集上验证我们的系统,我们在https://airlab.deib.polimi.it/datasets-and-tools/上公开提供进一步的研究。
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Clothoidal Mapping of Road Line Markings for Autonomous Driving High-Definition Maps
Lane-level HD maps are crucial for trajectory planning and control in current autonomous vehicles. For this reason, appropriate line models should be adopted to define them. Whereas mapping algorithms often rely on inaccurate representations, clothoid curves possess peculiar smoothness properties that make them desirable representations of road lines in control algorithms. We propose a multi-stage pipeline for the generation of lane-level HD maps from monocular vision relying on clothoidal spline models. We obtain measurements of the line positions using a line detection algorithm, and we exploit a graph-based optimization framework to reach an optimal fitting. An iterative greedy procedure reduces the model complexity removing unnecessary clothoids. We validate our system on a real-world dataset, which we make publicly available for further research at https://airlab.deib.polimi.it/datasets-and-tools/.
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