Journal of the Korea Institute of Information and Communication Engineering (한국정보통신학회논문지)

The Korea Institute of Information and Commucation Engineering (한국정보통신학회)
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A Black Ice Detection Method Using Infrared Camera and YOLO

적외선 카메라와 YOLO를 사용한 블랙아이스 탐지 방법

  • Kim, Hyung Gyun (School of Computer Eng., Jeonju University) ;
  • Jang, Min Seok (School of Computer & Inf. & Comm. Eng., Kunsan National University) ;
  • Lee, Yon Sik (School of Computer & Inf. & Comm. Eng., Kunsan National University)
  • Received : 2021.10.22
  • Accepted : 2021.11.17
  • Published : 2021.12.31
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Abstract

Black ice, which occurs mainly on the road, vehicle traffic bridges and tunnel entrances due to the sub-zero temperature due to the slip of the road due to heavy snow, is not recognized because the image of asphalt is transmitted in the driver's view, so the vehicle loses braking power because it causes serious loss of life and property. In this paper, we propose a method to identify the black ice by using infrared camera and to identify the road condition by using deep learning to compensate for the disadvantages of existing black ice detection methods (artificial satellite imaging, checking the pattern of slip by ultrasonic reception, measuring the temperature of the road surface, and checking the difference in friction force of the tire during vehicle driving) and to reduce the size of the sensor to detect black ice.

폭설로 인한 도로 미끄러짐과 함께 영하의 기온으로 도로와 차량 통행용 다리, 터널 출입구 쪽에서 주로 발생하는 블랙아이스는 운전자의 시야에서는 아스팔트의 이미지가 투과되어 보이기에 잘 인식되지 않아서 자동차들이 미끄러지는 (슬립 현상) 상황을 발생시키기에 차량이 제동력을 잃어서, 대형 교통사고로 이어져 심각한 인명과 재산상 손실을 초래하고 있다. 본 논문에서는 기존에 연구되었던 블랙아이스 감지 방법들(인공위성 촬영, 초음파 수신으로 미끄러짐의 패턴을 확인, 도로 표면의 온도측정, 차량 주행 중 타이어의 마찰력 차이를 확인하기)의 단점들을 보완하고, 블랙아이스를 감지하는 센서의 크기를 줄여서 많은 이동체에 적용할 수 있도록 하고자 적외선 카메라를 이용하여 도로 상태를 확인하고, 이 정보를 딥러닝 학습을 통하여 블랙아이스를 판별하는 방법을 제안하고자 한다.

Keywords

Acknowledgement

This research was funded and conducted under the Competency Development Program for Industry Specialist of Korean Ministry of Trade, Industry and Energy(MOTIE), operated by Korea Institute for Advancement of Technology(KIAT) (N0002428, HRD Program for Future Car), a grant (21RITD-C161698-01) from Regional Innovation Technology Development Program funded by Ministry of Land, Infrastructure and Transport of Korean government and the Basic Science Research Program through the National Research Foundation of Korea(NRF) funded by the Ministry of Education(No. 2021R1F1A1047768).

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