The Journal of The Korea Institute of Intelligent Transport Systems (한국ITS학회 논문지)

The Korea Institute of Intelligent Transport Systems (한국ITS학회)
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Design of Algorithm for Collision Avoidance with VRU Using V2X Information

V2X 정보를 활용한 VRU 충돌 회피 알고리즘 개발

  • 장선오 (국민대학교 자동차공학전문대학원) ;
  • 이상엽 (국민대학교 자동차공학전문대학원) ;
  • 박기홍 (국민대학교 자동차공학과) ;
  • 신재곤 (자동차안전연구원 자율주행연구처) ;
  • 엄성욱 (자동차안전연구원 자율주행실) ;
  • 조성우 (자동차안전연구원 자율주행실)
  • Received : 2021.12.18
  • Accepted : 2022.01.01
  • Published : 2022.02.28
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Abstract

Autonomous vehicles use various local sensors such as camera, radar, and lidar to perceive the surrounding environment. However, it is difficult to predict the movement of vulnerable road users using only local sensors that are subject to limits in cognitive range. This is true especially when these users are blocked from view by obstacles. Hence, this paper developed an algorithm for collision avoidance with VRU using V2X information. The main purpose of this collision avoidance system is to overcome the limitations of the local sensors. The algorithm first evaluates the risk of collision, based on the current driving condition and the V2X information of the VRU. Subsequently, the algorithm takes one of four evasive actions; steering, braking, steering after braking, and braking after steering. A simulation was performed under various conditions. The results of the simulation confirmed that the algorithm could significantly improve the performance of the collision avoidance system while securing vehicle stability during evasive maneuvers.

자율주행 차량은 레이더, 라이다 카메라 등 다양한 로컬 센서들을 활용하여 주변 환경을 인지하고 판단하여 주행한다. 하지만 로컬 센서만을 활용하여 주행할 경우 인지 범위 한계로 장애물에 가려진 보행자나 자전거와 같은 VRU(Vulnerable Road User, 취약 도로 사용자)의 거동 정보를 예측하기 어렵다. 본 논문에서는 이러한 로컬 센서의 한계를 극복하기 위해 V2X 통신 정보를 활용한 VRU 충돌 회피 알고리즘을 개발하였다. 알고리즘은 인프라로부터 충돌 위험이 있는 VRU의 정보를 전달 받아 미래 거동을 예측하고 주변 환경에 따라 적절하게 조향 및 제동 회피를 수행하도록 설계하였다. 개발된 알고리즘을 검증하기 위하여 다양한 조건의 시나리오에서 시뮬레이션을 수행하였으며, 그 결과, 기존 로컬 센서 정보만을 활용하였을 때보다 개선된 충돌 회피 성능을 보일 뿐만 아니라, 차량의 안정성 또한 확보할 수 있음을 확인하였다.

Keywords

Acknowledgement

본 연구는 국토교통부 및 국토교통과학기술진흥원의 연구비 지원(21PQOWB152473-03)으로 수행하였습니다.

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