Automatic Road Structure Detection and Vectorization Using MLS Point Clouds-时空数据智能获取技术与应用教育部工程中心

Automatic Road Structure Detection and Vectorization Using MLS Point Clouds

石莹 2021-08-08 浏览

摘要

高精度三维道路结构信息及模型在智能交通中有重要应用，比如：导航、路径规划、道路资产管理、道路健康状况监测及自动驾驶等。本文提出了一种从车载激光点云数据中快速、鲁棒地自动提取结构化道路边界的方法。该方法主要包括三个内容：超体素快速生成，道路边界探测及道路驾驶空间估计。首先，将地面点云根据属性相似度划分形成超体素；然后基于道路边界的显著属性：点密度及高差，识别位于道路边界上的超体素，并聚类形成初始道路边界。此时提取的道路边界点云位于道路边界处的微立面上，基于此微立面，可根据需求拟合矢量化的道路2D/3D边界，估计道路驾驶空间等。本文通过2份基于Alpha3D 移动激光扫描系统获取的车载激光扫描点云数据验证该方法的有效性和合理性。

成果介绍

本文提出的道路结构提取及矢量化方法主要包括三个部分：地面滤波，结构化道路边界提取，道路驾驶空间估计，基本流程如图1所示。

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图1 基于车载激光点云的道路结构检测流程图

该方法的输入数据为车载激光点云数据与对应的轨迹数据，经地面滤波后，对地面点云生成超体素，生成的超体素如图2（b）所示。

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（a）地面规则体素（b）地面超体素

图2 超体素生成示意图

基于生成的路面超体素，提取出的道路结构如图3所示。

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图3 道路结构提取结果示意图

最后，本文通过2份数据验证该方法的有效性与合理性，实验结果如图4及图5所示。

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（a）原始点云（b）提取出的道路边界

图4 数据1道路边界提取结果

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（a）原始点云（b）提取出的道路边界

图5 数据2道路边界提取结果

Abstract

Accurate three-dimensional road structures and models are of great significance to intelligent transportation applications, such as vehicle navigation, inventory evaluation, construction quality control, self-driving vehicles and so on. This paper proposes an efficient and robust method to automatically extract structured road curbs from mobile laser scanning (MLS) data. The proposed method mainly consists of three steps: efficient supervoxel generation, road curbs detection and driving free space estimation. First, supervoxels are generated by assigning ground points with similar geometrical characteristics into the same group. Second, supervoxels with higher local projection density and height difference are identified and clustered as initial road curbs, which are continuous vertical curb facets. The continuous facades consisting of lots of scanned points on the road shoulder can be modeled as multi-dimensional boundary models depending on the requirements of the application, such as vector lines with or without height, micro-facades, etc. Finally, driving free space is obtained due to the road limits can be defined by road boundary in most scenarios. The proposed method is tested on two complex datasets acquired by an Alpha3D mobile laser scanning system from the urban area of Shanghai, China. Experimental results show that the road boundaries and driving free space can be accurately and efficiently extracted, which also demonstrates the superiority of the proposed method.

Automatic Road Structure Detection and Vectorization Using MLS Point Clouds

石莹 2021-08-08 _showDynClicks("wbnews", 1448217335, 1977)浏览

石莹 2021-08-08 浏览