1 |
D. Geronimo, A. M. Lopez, A. D. Sappa, T. Graf, "Survey of pedestrian detection for advanced driver assistance systems," IEEE transactions on pattern analysis and machine intelligence, vol. 32, no. 7, pp. 1239-1258, July. 2010. DOI: https://doi.org/10.1109/TPAMI.2009.122
DOI
|
2 |
Hyunmin Chae, Chang Mook Kang, Chung Choo Chung, Jun Won Choi, "Deep Reinforcement Learning based Autonomous Braking System for safe Urban Driving," KSAE Conference, pp. 625-629, May. 2017
|
3 |
Ke Cao, el al. "Efficient Urban Broadcast Protocal for V2V Communications with Relay Control", IEEE Vehicular Networking Conference, pp. 24-30, 2013. DOI: https://doi.org/10.1109/VNC.2013.6737586
|
4 |
C. Watkins and P. Dayan. "Q-learning. Machine learning," 8(3-4), pp. 279-292, 1992. DOI: https://doi.org/10.1007/BF00992698
DOI
|
5 |
MNIH, Volodymyr, et al., "Playing atari with deep reinforcement learning." arXiv preprint, arXiv:1312.5602, 2013.
|
6 |
MNIH, Volodymyr, et al., "Human-level control through deep reinforcement learning," Nature, 518.7540: 529-533, 2015. DOI: https://doi.org/10.1038/nature14236
DOI
|
7 |
B. Huval, T. Wang, S. Tandon, J. Kiske, W.Song, J. Pazhayampallil, M. Andrilukam, P, Rajpurkar, T. Migimatsu, R. Cheng-Yue, F.Mujica, A. Coates, and A. Y. Ng, "An empirical evaluation of deep learning on highway driving," arXiv preprint, arXiv:1504.01716, pp. 1-7, Apr. 2015.
|
8 |
D. Tome, F. Monti, L. Baroffio, L. Bondi, M. Tagliasacchi and S. Tubaro, "Deep convolutional neural networks for pedestrian detection," Signal Processing: Image Communication, vol. 47, pp. 482-489, May. 2016. DOI: https://doi.org/10.1016/j.image.2016.05.007
DOI
|
9 |
R. S. Tomar, S. Verma, "Neural network based lane change trajectory prediction in autonomous vehicles," Transactions on computational science XIII, Springer, pp. 125-146, Berlin Heidelberg, 2011. DOI: https://doi.org/10.1007/978-3-642-22619-9_7
|