지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 자료유형
- 학술저널
- 저자정보
- 발행연도
- 2021.8
- 수록면
- 572 - 577 (6page)
- DOI
- 10.5302/J.ICROS.2021.21.0064
이용수
초록· 키워드
오류제보하기
In a lane change decision-making technique based on RL (Reinforcement Learning), most data is related to keeping a lane; on the contrary, the data related to lane change is sparse. Consequently, an ego-vehicle fails to learn its policy. To overcome this issue, we propose a new RL-based lane change decision-making technique that uses a safety inspection module and augmented data. The safety inspection module restrains the collision of the ego-vehicle and generates virtual augmented data acquired from lane change situations. The introduction of virtual augmented data mitigates sparse lane-change data problems, which results in performance improvement. We simulated the proposed technique using an open-source simulator called CARLA.
목차
Abstract
I. 서론
II. 문제의 정의
III. 차선 변경 판단 학습 과정
IV. 실험 결과
V. 결론
REFERENCES
참고문헌 (20)
참고문헌 신청
C. Hoel, K. Wolff, and L. Laine, “Automated speed and lane change decision making using deep reinforcement learning,” Proc. of 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2148-2155, 2018.
T. Li, J. Wu, and C. Chan, “Evolutionary learning in decision making for tactical lane changing,” Proc. of 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 1826-1831, 2019.
B. Mirchevska, C. Pek, M. Werling, M. Althoff, and J. Boedecker, “High-level decision making for safe and reasonable autonomous lane changing using reinforcement learning,” Proc. of 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2156-2162, 2018.
S. Mo, X. Pei, and Z. Chen, “Decision-making for oncoming traffic overtaking scenario using double DQN,” Proc. of 2019 3rd Conference on Vehicle Control and Intelligence (CVCI), pp. 1-4, 2019.
A. Alizadeh, M. Moghadam, Y. Bicer, N. K. Ure, U. Yavas, and C. Kurtulus, “Automated lane change decision making using deep reinforcement learning in dynamic and uncertain highway environment,” Proc. of 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 1399-1404, 2019.
T. Li, J. Wu, and C. Chan, “Evolutionary learning in decision making for tactical lane changing,” Proc. of 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 1826-1831, 2019.
B. Mirchevska, C. Pek, M. Werling, M. Althoff, and J. Boedecker, “High-level decision making for safe and reasonable autonomous lane changing using reinforcement learning,” Proc. of 2018 21st International Conference on Intelligent Transportation Systems (ITSC), pp. 2156-2162, 2018.
S. Mo, X. Pei, and Z. Chen, “Decision-making for oncoming traffic overtaking scenario using double DQN,” Proc. of 2019 3rd Conference on Vehicle Control and Intelligence (CVCI), pp. 1-4, 2019.
A. Alizadeh, M. Moghadam, Y. Bicer, N. K. Ure, U. Yavas, and C. Kurtulus, “Automated lane change decision making using deep reinforcement learning in dynamic and uncertain highway environment,” Proc. of 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pp. 1399-1404, 2019.
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