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엣지 디바이스에서의 딥러닝 기반 차량 인식 및 속도 추정을 통한 스마트 횡단보도 시스템의 설계 및 구현
장선혜,조희은,정진우,Jang, Sun-Hye,Cho, Hee-Eun,Jeong, Jin-Woo 한국정보통신학회 2020 한국정보통신학회논문지 Vol.24 No.4
Recently, the number of traffic accidents has also increased with the increase in the penetration rate of cars in Korea. In particular, not only inter-vehicle accidents but also human accidents near crosswalks are increasing, so that more attention to traffic safety around crosswalks are required. In this paper, we propose a system for predicting the safety level around the crosswalk by recognizing an approaching vehicle and estimating the speed of the vehicle using NVIDIA Jetson Nano-class edge devices. To this end, various machine learning models are trained with the information obtained from deep learning-based vehicle detection to predict the degree of risk according to the speed of an approaching vehicle. Finally, based on experiments using actual driving images and web simulation, the performance and the feasibility of the proposed system are validated.
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