차량 횡방향 운동 방정식을 고려한 차대도로간 트래킹 기법
A Study on Vehicle to Road Tracking Methodology with Consideration of vehicle lateral dynamics
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초록
본 논문에서는 확장형 칼만필터를 적용하여 영상센서 기반 차대도로간 트래킹 알고리즘을 제안한다. 일반적으로 횡방향 오프셋, 차선대비 상대경로각, 전방도로 곡률은 차선유지지원시스템의 경로추종 횡방향 제어기 구성 또는 차선이탈경보시스템의 경보 로직을 위한 중요 입력값으로 활용되는데 이를 위해 본 연구에서는 영상센서 차선인식 결과값인 이미지 상의 차선 추출점의 좌표값과 더불어 요레이트, 조향각, 차속 센서 측정값, 그리고 차량의 횡방향 운동방정식을 고려한 확장형 칼만필터를 적용하여 차대도로간 트래킹 정보를 추출한다. 제안된 차대도로간 트래킹 알고리즘의 유효성을 증명하기 위해 주행 테스트 도로 상에서DGPS-RTK 장비를 이용하여 비교 검증하여 그 유효성을 보였다.
Abstract
This paper proposes a vehicle to road tracking algorithm based on vision sensor by using EKF(Extended Kalman Filter). The lateral offset, heading angle, and curvature which are obtained from vehicle to road tracking might be used as inputs to steering controller of LKAS(Lane Keeping Assist System) or for the warning decision logic of LDWS(Lane Departure Warning System). To the end, in this paper, the yaw rate, steering angle, and vehicle speed as well as lane raw points together with considering of vehicle lateral dynamics are utilized to improve the exactness and convergence of the vehicle to road tracking. The proposed algorithm has been tested at a proving ground that consists of straight and curve sections and compared with GPS datum using DGPS-RTK equipment to show the feasibility of the proposed algorithm.
참고문헌 (8)
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