인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
Camera-based E2E (End-to-end) autonomous driving models map camera images directly to control commands. In onboard environments, real-time inference and driving performance are required. However, their performance depends on the resolution of the input image. High-resolution images preserve visual features of objects such as traffic lights and leading vehicles but increase computation and latency, while low-resolution images reduce latency but lose important visual information. This tradeoff between inference time and driving performance is an issue in onboard environments. This paper proposes a low- and high-resolution feature fusion module. The model extracts global features from low-resolution images and selectively fuses features from high-resolution regions of interest for traffic lights and leading vehicles. The proposed method was evaluated in the MORAI simulator and on the NVIDIA Orin AGX platform. The Driving Score, which evaluates driving performance, was 22.61% higher and the inference time was 35.91% faster than those of the model with high-resolution images. The proposed method alleviates the limitation of camera-based E2E caused by the tradeoff between inference time and driving performance in onboard environments.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
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UCI(KEPA) : I410-151-26-02-096351641
