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首页 > 过刊浏览>2023年第15卷第2期 >193-200. DOI:10.13878/j.cnki.jnuist.2023.02.008
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自动驾驶高精地图相对精度验证方法研究
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中图分类号:

U463.6

基金项目:

中国博士后科学基金(2022M710332)


Relative accuracy verification of high-definition map for autonomous driving
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    摘要:

    用于自动驾驶(Autonomous Driving,AD)的高精地图(High-Definition Map,HDM)是AD系统的重要组成部分.HDM可为AD系统提供高精度的车道线及道路辅助设施的先验数据,对HDM的合理的精度评估是一项重要的任务,而目前制图领域对普通地图相对精度评估的方法并不完全适用于HDM.本研究采用基于点集配准和重采样的方法评估车道线的相对精度,并基于相关的真实HDM数据进行实验.首先对待验证曲线上的点进行拟合采样,然后配准对齐点对,配准完成后再进行重采样,在此基础上完成相对精度计算.所验证的第1组车道线的相对极限误差为15.9 cm,小于20 cm,满足相对精度要求;其他3组车道线的相对极限误差也满足该要求.实验结果表明,基于该方法计算的车道线的相对精度比传统方法更准确、更可靠.

    Abstract:

    As an important component of Autonomous Driving (AD) system,High-Definition Map (HDM) can provide highly accurate prior data of lane lines and road auxiliary facilities for AD system.The reliable evaluation of HDM accuracy is extremely necessary,but has been troubled by the evaluation methods used in mapping.Here,a method based on point set alignment and resampling is proposed to evaluate the relative accuracy of lane lines,and experiments are conducted based on relevant HDM data.First,the points on the verification curve are fitted and sampled,and the aligned point pairs are registered and then resampled,based on which the relative accuracy is calculated.The results showed that the relative limit errors of all the 4 groups of lane lines were verified to be less than 20 cm,meeting the relative accuracy requirements,of which the first group has the relative limit error of 15.9 cm.It can be concluded that the proposed method is more accurate and reliable in accuracy evaluation of HDM than traditional methods.

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姜娜娜,汤咏林,黄鹤,于腾飞,孙鹏.自动驾驶高精地图相对精度验证方法研究[J].南京信息工程大学学报(自然科学版),2023,15(2):193-200
JIANG Nana, TANG Yonglin, HUANG He, YU Tengfei, SUN Peng. Relative accuracy verification of high-definition map for autonomous driving[J]. Journal of Nanjing University of Information Science & Technology, 2023,15(2):193-200

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历史
  • 收稿日期:2022-04-03
  • 在线发布日期: 2023-04-13

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