Lane-Level Map-Matching Method for Vehicle Localization Using GPS and Camera on a High-Definition Map

Sensors

TaeSung Yoon¹  JinBae Park²  JeongMin Kang²  Euntai Kim² 

[1] Department of Electrical Engineering, Changwon National University, Changwon 51140, Korea;Department of Electrical and Electronic Engineering, Yonsei University, Seoul 03722, Korea;

关键词: autonomous driving;    localization;    lane detection;    GNSS;    HD map;    map-matching;   

DOI  :  10.3390/s20082166

来源: DOAJ

【 摘 要 】

Accurate vehicle localization is important for autonomous driving and advanced driver assistance systems. Existing precise localization systems based on the global navigation satellite system cannot always provide lane-level accuracy even in open-sky environments. Map-based localization using high-definition (HD) maps is an interesting method for achieving greater accuracy. We propose a map-based localization method using a single camera. Our method relies on road link information in the HD map to achieve lane-level accuracy. Initially, we process the image—acquired using the camera of a mobile device—via inverse perspective mapping, which shows the entire road at a glance in the driving image. Subsequently, we use the Hough transform to detect the vehicle lines and acquire driving link information regarding the lane on which the vehicle is moving. The vehicle position is estimated by matching the global positioning system (GPS) and reference HD map. We employ iterative closest point-based map-matching to determine and eliminate the disparity between the GPS trajectories and reference map. Finally, we perform experiments by considering the data of a sophisticated GPS/inertial navigation system as the ground truth and demonstrate that the proposed method provides lane-level position accuracy for vehicle localization.

【 授权许可】

Unknown