DRL-Based Trajectory Tracking for Motion-Related Modules in Autonomous Driving

R. C. Coulter, “Implementation of the pure pursuit path tracking algorithm,” Carnegie-Mellon UNIV Pittsburgh PA Robotics INST, Tech. Rep., 1992

1992

Earlier work this paper cites.

S. Haykin, Neural networks: a comprehensive foundation . Prentice Hall PTR, 1998

1998

Earlier work this paper cites.

S. Boyd, S. P. Boyd, and L. Vandenberghe, Convex optimization . Cambridge university press, 2004

2004

Earlier work this paper cites.

W. Li and E. Todorov, “Iterative linear quadratic regulator design for nonlinear biological movement systems.” in ICINCO (1) . Citeseer, 2004, pp. 222–229

2004

Earlier work this paper cites.

G. M. Hoffmann, C. J. Tomlin, M. Montemerlo, and S. Thrun, “Autonomous automobile trajectory tracking for off-road driving: Controller design, experimental validation and racing,” in 2007 American control conference . IEEE, 2007, pp. 2296–2301

2007

Earlier work this paper cites.

R. Rajamani, Vehicle dynamics and control . Springer Science & Business Media, 2011

2011

Earlier work this paper cites.

V. Mnih, K. Kavukcuoglu, D. Silver, A. Graves, I. Antonoglou, D. Wierstra, and M. Riedmiller, “Playing atari with deep reinforcement learning,” arXiv preprint arXiv:1312.5602 , 2013

Original

2013

Earlier work this paper cites.

G. F. Franklin, J. D. Powell, and A. Emami-Naeini, Feedback Control of Dynamic Systems , 7th ed. USA: Prentice Hall Press, 2014

2014

Earlier work this paper cites.

A. Liniger, A. Domahidi, and M. Morari, “Optimization-based autonomous racing of 1: 43 scale rc cars,” Optimal Control Applications and Methods , vol. 36, no. 5, pp. 628–647, 2015

2015

Earlier work this paper cites.

I. Goodfellow, Y. Bengio, and A. Courville, Deep learning . MIT press, 2016

2016

Cited alongside, same era.

G. Brockman, V. Cheung, L. Pettersson, J. Schneider, J. Schulman, J. Tang, and W. Zaremba, “Openai gym,” arXiv preprint arXiv:1606.01540 , 2016

Original

2016

Cited alongside, same era.

T. Gu, “Improved trajectory planning for on-road self-driving vehicles via combined graph search, optimization & topology analysis,” Ph.D. dissertation, Carnegie Mellon University, 2017

2017

Cited alongside, same era.

D. Silver, T. Hubert, J. Schrittwieser, I. Antonoglou, M. Lai, A. Guez, M. Lanctot, L. Sifre, D. Kumaran, T. Graepel, T. P. Lillicrap, K. Simonyan, and D. Hassabis, “Mastering chess and shogi by self-play with a general reinforcement learning algorithm,” ArXiv , vol. abs/1712.01815, 2017

Original

2017

Cited alongside, same era.

J. Schulman, F. Wolski, P. Dhariwal, A. Radford, and O. Klimov, “Proximal policy optimization algorithms,” arXiv preprint arXiv:1707.06347 , 2017

S. Fujimoto, H. Hoof, and D. Meger, “Addressing function approximation error in actor-critic methods,” in International conference on machine learning . PMLR, 2018, pp. 1587–1596

2018

Later among the works it cites.

T. Haarnoja, A. Zhou, P. Abbeel, and S. Levine, “Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor,” in International conference on machine learning . PMLR, 2018, pp. 1861–1870

2018

Later among the works it cites.

M. Bansal, A. Krizhevsky, and A. Ogale, “Chauffeurnet: Learning to drive by imitating the best and synthesizing the worst,” arXiv preprint arXiv:1812.03079 , 2018

Original

2018

Later among the works it cites.

I. Batkovic, M. Zanon, N. Lubbe, and P. Falcone, “A computationally efficient model for pedestrian motion prediction,” in 2018 European Control Conference (ECC) . IEEE, 2018, pp. 374–379

2018

Later among the works it cites.