KSCE Journal of Civil and Environmental Engineering Research (대한토목학회논문집)

Korean Society of Civil Engeneers (대한토목학회)
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A Framework for Calculating the Spatiotemporal Activation Section of LDM-Based Autonomous Driving Information

동적지도정보 기반 자율주행 정보의 시공간적 활성화 구간 산정 프레임워크

  • 강찬모 (영남대학교 도시공학과) ;
  • 정연식 (영남대학교 도시공학과) ;
  • 박재형 (메타빌드(주) SW연구본부)
  • Received : 2022.02.24
  • Accepted : 2022.04.22
  • Published : 2022.08.01
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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.

자율주행 자동차는 기본적으로 차량과 도로에 설치된 센서를 활용해 수집된 도로·교통 정보를 통해 자율주행 기능을 수행한다. 그러나 이러한 기술과 정보만으로는 완전한 자율주행을 구현하는 것에 한계가 있음을 인정하고 있다. 최근에는 센서 기반 자율주행 기술의 한계를 극복하기 위해 다양한 방면에서 노력을 하고 있으며, 동적지도정보(local dynamic map: LDM)라 불리는 보다 구체적이고 정확한 도로 및 교통정보를 활용하는 노력도 진행 중이다. 그러나 LDM 관련 데이터 표준 및 데이터 세부항목 등이 아직 충분히 검증되지 않았으며, 자율주행 중 LDM의 시공간적 제공 범위에 대한 연구는 극히 제한적이다. 이러한 배경 하에, 본 연구의 목적은 기존 LDM 관련 연구 사례를 통해 기존 연구의 한계를 도출하고, 나아가 LDM 기반 도로·교통정보의 시공간적 활성화 구간 산정 프레임워크을 제시하는 것이다.

Keywords

Acknowledgement

본 연구는 국토교통과학기술진흥원의 크라우드 소싱 기반의 디지털 도로·교통 인프라 융합 플랫폼 기술 개발 과제(21AMDP-C161924-01)의 지원을 받아 수행되었음.

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