Representation strategies of high-precision map for advanced intelligent driving

doi:10.13474/j.cnki.11-2246.2026.0524

Abstract

Abstract: [Purposes] High-precision map serves as a core support for advanced intelligent driving,yet its large-scale application faces dual challenges: ensuring driving safety and safeguarding geographic information security.This study systematically examines the core representational requirements of high-precision map and proposes a multi-dimensionally optimized representation strategy.[Methods] The approach incorporates three key technical innovations: expanded map coverage,hierarchical categorization of feature elevations,and decomposition of continuous terrain fluctuations.Simulations,field tests,and case validations are conducted across various typical scenarios.[Findings] The results show that,on the premise of not breaching the bottom line of geospatial information security,this strategy can reduce the safety accident rate of high-level intelligent driving to about 1/10 of the original rate,meeting its safety requirements for misjudgment rate of feature ground objects and ground undulation error.[Conclusions] Based on this strategy,Guangzhou has successfully completed the map review work for five high-precision map projects,with the review efficiency improved by 75%,providing important support for the compliant application of high-precision map nationwide and the large-scale development of the intelligent connected vehicle industry.

Key words: intelligent driving, high-precision map, map review, geographic information security, driving safety

CLC Number:

DENG Guangran, ZHANG Yongli, FU Xiao, TAO Lan, OUYANG Xinqiu, HAN Jianzi, CHEN Zejia, DONG Guangsheng. Representation strategies of high-precision map for advanced intelligent driving[J]. Bulletin of Surveying and Mapping, 2026, 0(5): 149-154.

References

[1] 李德仁,洪勇,王密,等.测绘遥感能为智能驾驶做什么？[J].测绘学报,2021,50(11):1421-1431.
[2] 刘经南,詹骄,郭迟,等.智能高精地图数据逻辑结构与关键技术[J].测绘学报,2019,48(8):939-953.
[3] 冯昶,杜清运,范晓宇,等.高精动态地图基础平台众源更新技术路线研究[J].测绘地理信息,2023,48(1):10-15.
[4] 杜清运,况路路,任福,等.自动驾驶高精度地图特征分析及发展展望[J].地球信息科学学报,2024,26(1):15-24.
[5] 杨蒙蒙,江昆,温拓朴,等.自动驾驶高精度地图众源更新技术现状与挑战[J].中国公路学报,2023,36(5):244-259.
[6] 王柳,王东波,肖寒,等.智能驾驶“一张图”要素组织方法与应用[J].测绘科学技术学报,2025,42(3):304-311.
[7] Taxonomy and definitions for terms related to driving automation systems for on-road motor vehicles:SAE J 3016—2021[S].[S.l.]:Society of Automotive Engineers,2021.
[8] 国家市场监督管理总局,国家标准化管理委员会.汽车驾驶自动化分级:GB/T 40429—2021[S].北京:中国标准出版社,2021.
[9] 蔡忠亮,王孟琪,李伯钊,等.高精地图相关标准及数据模型的研究[J].测绘地理信息,2023,48(1):30-34.
[10] 张攀,刘经南.通用化高精地图数据模型[J].测绘学报,2021,50(11):1432-1446.
[11] 国家市场监督管理总局,国家标准化管理委员会.高级辅助驾驶地图审查要求:GB/T 44489—2024[S].北京:中国标准出版社,2024.
[12] 黄龙,章炜,乐鹏,等.智能网联汽车高精地图安全监管分析与技术研究[J].武汉大学学报(信息科学版),2025,50(10):2122-2134.
[13] 吴佳桐,狄琳,黄龙.智能驾驶高精地图数智化审查研究[J].测绘通报,2024(10):174-178.
[14] 陈会仙,章炜,杨蒙蒙,等.面向无人驾驶的高精地图公开应用趋势研究[J].武汉大学学报(信息科学版),2024,49(4):537-545.
[15] 刘永轩,董明,杨伯钢,等.高精度地图众源更新安全监管研究与路径探析[J].北京测绘,2024,38(2):189-194.
[16] 张想,彭力.融合标精地图先验的地图不确定性感知及拓扑推理[J/OL].计算机工程,1-11[2026-03-27].https://doi.org/10.19678/j.issn.1000-3428.0070312.
[17] 杜荣华,李宗,张金来,等.基于分层超点自注意力模型的自动驾驶3维语义分割研究[J].激光技术,2026,50(1):9-21.
[18] ZHANG Yifan,KANG Bingyi,HOOI B,et al.Deep long-tailed learning:a survey[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2023,45(9):10795-10816.
[19] 龙小羽,南新元.智能驾驶场景下的中小型障碍物检测方法[J].科学技术与工程,2025,25(9):3778-3787.
[20] 陶博,颜伏伍,尹智帅,等.基于高精度地图增强的三维目标检测算法[J].吉林大学学报(工学版),2023,53(3):802-809.
[21] BOSETTI P,DA LIO M,SAROLDI A.On the human control of vehicles:an experimental study of acceleration[J].European Transport Research Review,2014,6(2):157-170.
[22] 杨智博,张志强,秦孔建,等.基于自动驾驶机器人的自动驾驶汽车制动强度对驾驶员舒适度的主客观影响分析[J].制造业自动化,2021,43(9):111-116.
[23] 国家质量监督检验检疫总局,中国国家标准化管理委员会.道路交通信号灯:GB 14887—2011[S].北京:中国标准出版社,2012.
[24] 国家市场监督管理总局,国家标准化管理委员会.道路交通标志和标线第2部分:道路交通标志:GB 5768.2—2022[S].北京:中国标准出版社,2022.
[25] 张亚勤,李震宇,尚国斌,等.面向自动驾驶的车路云一体化框架[J].汽车安全与节能学报,2023,14(3):249-273.
[26] KUSANO K D,SCANLON J M,CHEN Y H,et al.Comparison of Waymo rider-only crash data to human benchmarks at 7.1 million miles[J].Traffic Injury Prevention,2024,25(sup1):S66-S77.