An automated mapping method based on crowdsourced data
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.
intelligent drivingautomated mappingcrowdsourced datathree-dimensional(3D)data reconstructionvector topology construction
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