Earticle

초록

영어

In low-visibility conditions, such as night-time driving or during bad weather, the risk of vehicle collisions rises dramatically. This is mainly because it becomes much harder to spot pedestrians and other obstacles on the road. To address this challenge, we developed a real-time vehicle collision prevention system using a Jetson Nano equipped with infrared cameras and the Yolov8n model. The system works by capturing heatemitting objects using thermal imaging technology, making it easier to detect obstacles even in difficult lighting conditions. To enhance its reliability, the system was mounted on a vehicle and tested in a range of environments, including both day and night. Throughout these tests, the system consistently proved capable of detecting potential hazards in real time, showcasing its potential to significantly improve driver safety and reduce collisions in challenging driving conditions.

목차

Abstract
I. INTRODUCTION
II. PROPOSED SYSTEM ARCHITECTURE
III. RESULTS AND ANALYSIS
IV. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

키워드

저자

• Hyun-Woong Choo [ dept. of Info. and Comm. Engineering Chosun University Gwangju, Republic of Korea ]
• Eun-Min Choi [ dept. of Info. and Comm. Engineering Chosun University Gwangju, Republic of Korea ]
• Da-Sol Cho [ dept. of Info. and Comm. Engineering Chosun University Gwangju, Republic of Korea ]
• Chan-Uk Yeom [ Division of AI Convergence College Chosun University Gwangju, Republic of Korea ] Corresponding Author
• Keun-Chang Kwak [ dept. of Electronics Engineering Chosun University Gwangju, Republic of Korea ] Corresponding Author

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004