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Proactive Longitudinal Motion Planning for Improving Safety of Automated Bus using Chance-constrained MPC with V2V Communication

자율주행 버스의 주행 안전을 위한 차량 간 통신 및 모델 예측 제어 기반 종 방향 거동 계획

  • 조아라 (서울대학교 미래혁신연구원) ;
  • 유진수 (서울대학교 공과대학 기계공학부) ;
  • 곽지섭 (서울대학교 공과대학 기계공학부) ;
  • 권우진 (서울대학교 공과대학 기계공학부) ;
  • 이경수 (서울대학교 공과대학 기계공학부)
  • Received : 2022.11.07
  • Accepted : 2023.09.14
  • Published : 2023.12.31

Abstract

This paper presents a proactive longitudinal motion planning algorithm for improving the safety of an automated bus. Since the field of view (FOV) of the autonomous vehicle was limited depending on onboard sensors' performance and surrounding environments, it was necessary to implement vehicle-to-vehicle (V2V) communication for overcoming the limitation. After a virtual V2V-equipped target was constructed considering information obtained from V2V communication, the reference motion of the ego vehicle was determined by considering the state of both the V2V-equipped target and the sensor-detected target. Model predictive control (MPC) was implemented to calculate the optimal motion considering the reference motion and the chance constraint, which was deduced from manual driving data. The improvement in driving safety was confirmed through vehicle tests along actual urban roads.

Keywords

Acknowledgement

본 연구는 국토교통부와 국토교통과학기술진흥원 자율주행 기술개발 혁신사업의 연구비 지원(과제번호 RS-2021-KA162182)에 의해 수행되었습니다.

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