• Title/Summary/Keyword: Autonomous Vehicle Competition(AVC)

Search Result 2, Processing Time 0.018 seconds

Development of an Autonomous Vehicle: A1 (자율주행자동차 개발: A1)

  • Chu, Keon-Yup;Han, Jae-Hyun;Lee, Min-Chae;Kim, Dong-Chul;Jo, Ki-Chun;Oh, Dong-Eon;Yoon, E-Nae;Gwak, Myeong-Gi;Han, Kwang-Jin;Lee, Dong-Hwi;Choe, Byung-Do;Kim, Yang-Soo;Lee, Kang-Yoon;Huh, Kun-Soo;SunWoo, Myoung-Ho
    • Transactions of the Korean Society of Automotive Engineers
    • /
    • v.19 no.4
    • /
    • pp.146-154
    • /
    • 2011
  • This article describes the Autonomous Vehicle #1 (A1), which won the 2010 Autonomous Vehicle Competition (AVC) organized by Hyundai Kia automotive group. The A1 was developed for high speed and stable driving without human intervention. The autonomous system of A1 was developed based on in-vehicle networks, electronic control units, and embedded software. Novel environment perception and navigation algorithm were evaluated and validated through the AVC. In this paper, we presented the system and software architecture of A1.

Path Planning for Static Obstacle Avoidance: ADAM III (정적 장애물 회피를 위한 경로 계획: ADAM III)

  • Choi, Heejae;Song, Bongsob
    • Transactions of the Korean Society of Automotive Engineers
    • /
    • v.22 no.3
    • /
    • pp.241-249
    • /
    • 2014
  • This paper presents a path planning algorithm of an autonomous vehicle (ADAM III) for collision avoidance in the presence of multiple obstacles. Under the requirements that a low-cost GPS is used and its computation should be completed with a sampling time of sub-second, heading angle estimation is proposed to improve performance degradation of its measurement and a hierarchical structure for path planning is used. Once it is decided that obstacle avoidance is necessary, the path planning consists in three steps: waypoint generation, trajectory candidate generation, and trajectory selection. While the waypoints and the corresponding trajectory candidates are generated based on position of obstacles, the final desired trajectory is determined with considerations of kinematic constraints as well as an optimal condition in a term of lateral deviation. Finally the proposed algorithm was validated experimentally through field tests and its demonstration was performed in Autonomous Vehicle Competition (AVC) 2013.