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http://dx.doi.org/10.5302/J.ICROS.2015.14.9005

Lane Map-based Vehicle Localization for Robust Lateral Control of an Automated Vehicle  

Kim, Dongwook (School of Mechanical and Aerospace Engineering, Seoul National University)
Jung, Taeyoung (Hyundai Mobis)
Yi, Kyong-Su (School of Mechanical and Aerospace Engineering, Seoul National University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.21, no.2, 2015 , pp. 108-114 More about this Journal
Abstract
Automated driving systems require a high level of performance regarding environmental perception, especially in urban environments. Today's on-board sensors such as radars or cameras do not reach a satisfying level of development from the point of view of robustness and availability. Thus, map data is often used as an additional data input to support these systems. An accurate digital map is used as a powerful additional sensor. In this paper, we propose a new approach for vehicle localization using a lane map and a single-layer LiDAR. The maps are created beforehand using a highly accurate DGPS and a single-layer LiDAR. A pose estimation of the vehicle was derived from an iterative closest point (ICP) match of LiDAR's intensity data to the lane map, and the estimated pose was used as an observation inside a Kalmanfilter framework. The achieved accuracy of the proposed localization algorithm is evaluated with a highly accurate DGPS to investigate the performance with respect to lateral vehicle control.
Keywords
map-based vehicle localization; map matching; iterative closest point; robust lateral control; automated driving;
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Times Cited By KSCI : 2  (Citation Analysis)
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