The Journal of Korea Robotics Society (로봇학회논문지)

Korea Robotics Society (한국로봇학회)
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High-Definition Map-based Local Path Planning for Dynamic and Static Obstacle Avoidance

동적 및 정적 물체 회피를 위한 정밀 도로지도 기반 지역 경로 계획

  • Received : 2021.02.10
  • Accepted : 2021.03.19
  • Published : 2021.05.31
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Abstract

Unlike a typical small-sized robot navigating in a free space, an autonomous vehicle has to travel in a designated road which has lanes to follow and traffic rules to obey. High-Definition (HD) maps, which include road markings, traffic signs, and traffic lights with high location accuracy, can help an autonomous vehicle avoid the need to detect such challenging road surroundings. With space constraints and a pre-built HD map, a new type of path planning algorithm can be conceived as a substitute for conventional grid-based path planning algorithms, which require substantial planning time to cover large-scale free space. In this paper, we propose an obstacle-avoiding, cost-based planning algorithm in a continuous space that aims to pursue a globally-planned path with the help of HD map information. Experimentally, the proposed algorithm is shown to outperform other state-of-the-art path planning algorithms in terms of computation complexity in a typical urban road setting, thereby achieving real-time performance and safe avoidance of obstacles.

Keywords

Acknowledgement

This work was supported by the research project "Development of A.I. based recognition, judgement and control solution for autonomous vehicle corresponding to an atypical driving environment," which is financed from the Institute for Information and Communications Technology Planning & Evaluation (Republic of Korea) and the Ministry of Science and ICT (Republic of Korea) Contract No. 2019-0-00399. The students are supported by the BK21 FOUR from the Ministry of Education (Republic of Korea)

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