Abstract
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.
Highlights
As increasing research on autonomous driving and advanced driver assistance systems (ADAS) is being conducted, more precise vehicle localization is required
Our method relies on road link information, which indicates the center of each lane in the HD map
The reference map is prebuilt with azimuth and link information, and the reference map dataset (RMDS) is updated at each sampling time using the data from the global positioning system (GPS) receiver
Summary
As increasing research on autonomous driving and advanced driver assistance systems (ADAS) is being conducted, more precise vehicle localization is required. Further research is still required for changes in the image processing techniques and determining the magnitude of errors in various environments Another approach for vehicle localization is to use a map-matching method using a precise high-definition (HD) map. A simple map-matching approach tailors the current position of the vehicle based on the nearest landmarks onto a vector representation of a road network, where point-to-point and point-to-curve matching methods were proposed [30,31] These methods were easy to implement; the amount of computation and location errors increase as the map becomes more complex. A method suggesting the accuracy of each point that is based on an iterative closest point (ICP) algorithm utilizing only GPS trajectory and map information was proposed [36] This method enabled calculation of the position errors via consideration of the information acquired by the high-end equipment as a ground truth.
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