1 |
R. S. Sutton, D. McAllester, S. Singh, Y. Mansour, "Policy gradient methods for reinforcement learning with function approximation," Advances in neural information processing systems, Vol.12, 1999.
|
2 |
L. Liangzhi, K. Ota and M. Dong, "Humanlike driving: Empirical decision-making system for autonomous vehicles," IEEE Transactions on Vehicular Technology, Vol.67, No.8, pp.6814-6823, 2018.
DOI
|
3 |
A. Folkers, M. Rick and C. Buskens, "Controlling an autonomous vehicle with deep reinforcement learning," 2019 IEEE Intelligent Vehicles Symposium (IV), 2019.
|
4 |
M. Yoshimura, G. Fujimoto, A. Kaushik, B. K. Padi, M. Dennison, I. Sood, K. Sarkar, A. Muneer, "Autonomous Emergency Steering Using Deep Reinforcement Learning For Advanced Driver Assistance System," 2020 59th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE), 2020.
|
5 |
D. Y. Yu, D. G. Kim, H. S. Choi and S. H. Hwang, "Hybrid Control Strategy for Autonomous Driving System using HD Map Information," Journal of Drive and Control, Vol.17, No.4, pp.80-86, 2020.
DOI
|
6 |
Y. Chen, C. Dong, P Palanisamy, P. Mudalige, K. Muelling and J. M. Dolan, "Attention-based hierarchical deep reinforcement learning for lane change behaviors in autonomous driving," Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.
|
7 |
K. S. Kim, J. I. Lee, S. W. Gwak, W. Y. Kang, D. Y. Shin and S. H. Hwang, "Construction of Database for Deep Learning-based Occlusion Area Detection in the Virtual Environment," Journal of Drive and Control, Vol.19, No.3, pp.9-15, 2022.
DOI
|
8 |
J. I. Lee, G. S. Gwak, K. S. Kim, W. Y. Kang, D. Y. Shin and S. H. Hwang, "Development of Virtual Simulator and Database for Deep Learning-based Object Detection," Journal of Drive and Control, Vol.18, No.4, pp.9-18, 2021.
DOI
|
9 |
C. Desjardins and B. Chaib-draa. "Cooperative adaptive cruise control: A reinforcement learning approach," IEEE Transactions on intelligent transportation systems, Vol.12, No.4, pp.1248-1260, 2021.
DOI
|
10 |
O. P. Gil, R. Barea, E. L. Guillen, L. M. Bergasa, C. G. Huelamo, R. Gutierrez and A. D. Diaz, "Deep reinforcement learning based control for autonomous vehicles in carla," Multimedia Tools and Applications, Vol.81, No.3, pp.3553-3576, 2022.
DOI
|
11 |
A. Feher, S. Aradi and T, Becsi, "Online Trajectory Planning with Reinforcement Learning for Pedestrian Avoidance," Electronics, Vol.11, No.15, 2022.
|
12 |
J. Schulman, F. Wolski, P. Dhariwal, A. Radford, O. Klimov, "Proximal policy optimization algorithms," arXiv:1707.06347, 2017.
|
13 |
A. Kesting, M. Treiber and D, Helbing. "Enhanced intelligent driver model to access the impact of driving strategies on traffic capacity," Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol.368, No.1928, pp-4585-4605, 2010.
DOI
|
14 |
J. Chen, B. Yuan and M. Tomizuka, "Model-free deep reinforcement learning for urban autonomous driving," 2019 IEEE intelligent transportation systems conference (ITSC), 2019.
|
15 |
C. Y. Chan, "Advancements, prospects, and impacts of automated driving systems," International journal of transportation science and technology, Vol.6, No.3, pp.208-216, 2017.
DOI
|
16 |
X. Liang, T. Wang, L. Yang and E. Xing, "Cirl: Controllable imitative reinforcement learning for vision-based self-driving," Proceedings of the European conference on computer vision (ECCV), pp-584-599, 2018.
|
17 |
S. Wang, D. Jia and X. Weng, "Deep reinforcement learning for autonomous driving," arXiv:1811.11329, 2018.
|