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http://dx.doi.org/10.12652/Ksce.2022.42.4.0519

A Framework for Calculating the Spatiotemporal Activation Section of LDM-Based Autonomous Driving Information  

Kang, Chanmo (Yeungnam University)
Chung, Younshik (Yeungnam University)
Park, Jaehyung (Metabuild Co. Ltd.)
Publication Information
KSCE Journal of Civil and Environmental Engineering Research / v.42, no.4, 2022 , pp. 519-526 More about this Journal
Abstract
Basically, autonomous vehicles drive using road and traffic information collected by various sensors. However, it is known that there is a limitation to realizing fully autonomous driving with only such technologies and information. In recent, various efforts are being made to overcome the limitations of sensor-based autonomous driving, and efforts are also underway to utilize more specific and accurate road and traffic information, called local dynamic map (LDM). However, LDM-related data standards and specifications have not yet been sufficiently verified, and research on the spatiotemporal scope of LDM during autonomous driving is extremely limited. Based on this background, the purpose of this study is to identify these limitations through an analysis of previous LDM-related studies and to present a framework for calculating the spatiotemporal activation section of LDM-based road and traffic information.
Keywords
Autonomous driving; Traffic information; Local dynamic map (LDM); ADAS horizon;
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Times Cited By KSCI : 4  (Citation Analysis)
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