A Novel Method for Ground-truth Determination of Lane Information through a Single Web Camera

The high-definition (HD) map is critical for the localization and motion planning of connected and automated vehicles (CAVs). With all the road and lane information pre-scanned in a certain area, the vehicles can know its position with respect to the lane marks and roadside, and hence make better decisions on planning future trajectories. A common issue, however, is the accuracy of the scanned outputs from different data sources. Because of the limitations of online maps (e.g., zooming and stretching in their image layers), visualizing the data in the bird's eye view on maps cannot satisfy the accuracy requirement of being the ground-truth system. To this end, a feasible method that can combine sensing data from different sources and obtain reliable ground-truth information is necessary. In this paper, we develop a novel method to transform the data points from the bird's eye view to the view angle of a web camera installed on the windshield of the ego vehicle. In such a case, the position of landmarks from the captured frames of the camera can be used as the ground-truth. In particular, we take the lane marking detection outputs from the Mobileye system as the reference for a better accuracy. We evaluate the proposed method using the field data on highway I-75 in Michigan, USA. The results show that this method has achieved a very good accuracy of over 90% for location determination of lane information. The main contribution of this paper is that the proposed method can be more intuitive and reliable than using the traditional maps in bird's eye view.