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http://dx.doi.org/10.5302/J.ICROS.2016.16.0172

Intensity Local Map Generation Using Data Accumulation and Precise Vehicle Localization Based on Intensity Map  

Kim, Kyu-Won (Electronic Engineering, Konkuk University)
Lee, Byung-Hyun (Hanwha Systems)
Im, Jun-Hyuck (Electronic Engineering, Konkuk University)
Jee, Gyu-In (Electronic Engineering, Konkuk University)
Publication Information
Journal of Institute of Control, Robotics and Systems / v.22, no.12, 2016 , pp. 1046-1052 More about this Journal
Abstract
For the safe driving of autonomous vehicles, accurate position estimation is required. Generally, position error must be less than 1m because of lane keeping. However, GPS positioning error is more than 1m. Therefore, we must correct this error and a map matching algorithm is generally used. Especially, road marking intensity map have been used in many studies. In previous work, 3D LIDAR with many vertical layers was used to generate a local intensity map. Because it can be obtained sufficient longitudinal information for map matching. However, it is expensive and sufficient road marking information cannot be obtained in rush hour situations. In this paper, we propose a localization algorithm using an accumulated intensity local map. An accumulated intensity local map can be generated with sufficient longitudinal information using 3D LIDAR with a few vertical layers. Using this algorithm, we can also obtain sufficient intensity information in rush hour situations. Thus, it is possible to increase the reliability of the map matching and get accurate position estimation result. In the experimental result, the lateral RMS position error is about 0.12m and the longitudinal RMS error is about 0.19m.
Keywords
accumulated intensity local map; autonomous vehicle; map matching; precise vehicle localization;
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Times Cited By KSCI : 1  (Citation Analysis)
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