基于众源数据的自动化制图方法  

An automated mapping method based on crowdsourced data

作　　者：刘银 伍伟绩 王闯 肖慧 张京川 LIU Yin;WU Weiji;WANG Chuang;XIAO Hui;ZHANG Jingchuan(Beijing Branch,Hebei Quandao Technology Company Limited,Beijing 100102,China)

机构地区：[1]河北全道科技有限公司北京分公司,北京100102

出　　处：《北京测绘》2024年第5期773-779,共7页Beijing Surveying and Mapping

摘　　要：为解决在传统高精度地图生产中,由于专业测绘采集车辆采集、制图手段的局限性,高精地图制作成本高、周期长、更新不及时等问题,本文采用了一种基于众源车辆进行自动制图的方法。将车端的环境感知结果、惯性导航系统(INS)/全球卫星导航系统(GNSS)组合导航数据等回传,在云端完成三维(3D)数据重建、矢量拓扑构建、成果质检发布等处理,从而完成自动化制图。选取某区域300 km的多场景路段进行实例验证,结果表明,本文所设计的技术方法能够解决高精地图鲜度问题及更新成本问题,可满足快速更新智能驾驶地图的要求,为智能驾驶的落地应用提供地图数据支撑。Traditional high-precision map production faces limited collection and mapping methods of professional surveying and mapping vehicles,resulting in high production costs,long cycles,and untimely updates of high-precision maps.To address these issues,this paper proposed a method for automated mapping based on crowdsourced vehicles.The environmental perception results and inertial navigation system(INS)/global navigation satellite system(GNSS)integrated navigation data of the vehicle were transmitted back,so as to complete the three-dimensional(3D)data reconstruction,vector topology construction,and result quality inspection and release in the cloud,thus achieving automated mapping.A 300 km multi-scenario road section in a certain area was selected for verification.The results show that the technical method designed in this paper can solve the problems of high-precision map freshness and update cost,meet the requirements of quickly updating intelligent driving maps,and provide map data support for the actual application of intelligent driving.

关 键 词：智能驾驶 自动化制图 众源数据 三维数据重建 矢量拓扑构建 

分 类 号：P283.7[天文地球—地图制图学与地理信息工程]