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http://dx.doi.org/10.22680/kasa2020.12.2.033

AVM Stop-line Detection based Longitudinal Position Correction Algorithm for Automated Driving on Urban Roads  

Kim, Jongho (서울대학교 기계항공공학부)
Lee, Hyunsung (서울대학교 기계항공공학부)
Yoo, Jinsoo (서울대학교 기계항공공학부)
Yi, Kyongsu (서울대학교 기계항공공학부)
Publication Information
Journal of Auto-vehicle Safety Association / v.12, no.2, 2020 , pp. 33-39 More about this Journal
Abstract
This paper presents an Around View Monitoring (AVM) stop-line detection based longitudinal position correction algorithm for automated driving on urban roads. Poor positioning accuracy of low-cost GPS has many problems for precise path tracking. Therefore, this study aims to improve the longitudinal positioning accuracy of low-cost GPS. The algorithm has three main processes. The first process is a stop-line detection. In this process, the stop-line is detected using Hough Transform from the AVM camera. The second process is a map matching. In the map matching process, to find the corrected vehicle position, the detected line is matched to the stop-line of the HD map using the Iterative Closest Point (ICP) method. Third, longitudinal position of low-cost GPS is updated using a corrected vehicle position with Kalman Filter. The proposed algorithm is implemented in the Robot Operating System (ROS) environment and verified on the actual urban road driving data. Compared to low-cost GPS only, Test results show the longitudinal localization performance was improved.
Keywords
Automated Driving; Position Correction; Stop-line Detection; ROS;
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