DOI QR코드

DOI QR Code

Zero Accident, Connected Autonomous Driving Vehicle

사고제로, 커넥티드 자율이동체

  • Published : 2021.02.01

Abstract

In this thesis, we examine the development status of autonomous mobility services using various artificial intelligence algorithms and propose a solution by combining edge and cloud computing to overcome technical difficulties. A fully autonomous vehicle with enhanced safety and ethics can be implemented using the proposed solution. In addition, for the future of 2035, we present a new concept that enables two- and three-dimensional movement via cooperation between ecofriendly, low-noise, and modular fully autonomous vehicles. The zero-error autonomous driving system will safely and conveniently transport people, goods, and services without time and space constraints and contribute to the autonomous mobility services that are free from movement in connection with various mobility.

Keywords

References

  1. SAE, 국제표준 J3016, 2019.
  2. J. Long et al., "Fully convolutional networks for semantic segmentation," in Proc. IEEE Conf. Comput. Vision Pattern Recogn. (Boston, MA, USA), 2015.
  3. Cityscapes Dataset, https://www.cityscapes-dataset.com
  4. 민경욱, "고정밀맵 음영 환경의 완전자율주행 네비게이션 인공지능 기술개발" 한국전자통신연구원 연차보고서, 2020.
  5. TESLA, http://tesla.com
  6. 정보통신기획평가원, "ICT R&D 기술로드맵 2025-자율주행차분야," 2020. 10.
  7. 한국전자통신연구원, "지능정보사회로 가는 길: 기술발전지도 2035," 2020. 6.
  8. 관계부처합동, "도시의 하늘을 여는 한국형 도심항공교통(KUAM)로드맵," 2020. 5.
  9. 한국정부, "기후목표 정상회의 발언 중," 2020. 12.
  10. 한국정부, "2030 미래차 산업국가로드맵," 2019. 11.