본 논문에서는 도심 교차로에서 교통약자(VRU)의 위험 상태를 예측하고, 예측 결과와 판단 근거를 자연어 V2X 협력 메시지로 생성하는 인프라 기반
프레임워크를 제안한다. 제안 방식은 RSU 카메라 영상으로부터 VRU의 위치, 움직임, 신체 방향, 주변 맥락을 분석하여 구조화된 자연어 메시지로
출력한다. WatchoutPed benchmark 실험 결과, 제안 모델은 기존 pedestrian anticipation 모델 대비 우수한 성능을 보였으며, 자연어 메시지가 이종
차량 환경에서 설명 가능한 V2X 협력 정보로 활용될 수 있음을 확인하였다.
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