Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control

H. Chernoff et al. , “A measure of asymptotic efficiency for tests of a hypothesis based on the sum of observations,” The Annals of Mathematical Statistics , vol. 23, no. 4, pp. 493–507, 1952

1952

Earlier work this paper cites.

R. Isermann, “Process fault detection based on modeling and estimation methods—a survey,” automatica , vol. 20, no. 4, pp. 387–404, 1984

1984

Earlier work this paper cites.

D. J. MacKay, “A practical Bayesian framework for backpropagation networks,” Neural computation , vol. 4, no. 3, pp. 448–472, 1992

1992

Earlier work this paper cites.

C. E. Shannon, “A mathematical theory of communication,” ACM SIGMOBILE mobile computing and communications review , vol. 5, no. 1, pp. 3–55, 2001

2001

Earlier work this paper cites.

C. M. Bishop, Pattern recognition and machine learning . springer, 2006

2006

Earlier work this paper cites.

A. Abate, M. Prandini, J. Lygeros, and S. Sastry, “Probabilistic reachability and safety for controlled discrete time stochastic hybrid systems,” Automatica , vol. 44, no. 11, pp. 2724–2734, 2008

2008

Earlier work this paper cites.

A. Legay, B. Delahaye, and S. Bensalem, “Statistical model checking: An overview,” in International conference on runtime verification . Springer, 2010, pp. 122–135

2010

Earlier work this paper cites.

A. Graves, “Practical variational inference for neural networks,” in Advances in neural information processing systems , 2011, pp. 2348–2356

2011

Earlier work this paper cites.

R. M. Neal, “MCMC using Hamiltonian dynamics,” arXiv e-prints , p. arXiv:1206.1901, June 2012

Original

2012

Earlier work this paper cites.

I. I. Gihman and A. V. Skorohod, Controlled stochastic processes . Springer Science & Business Media, 2012

2012

Earlier work this paper cites.

C. Blundell, J. Cornebise, K. Kavukcuoglu, and D. Wierstra, “Weight uncertainty in neural networks,” arXiv preprint arXiv:1505.05424 , 2015

Original

2015

Earlier work this paper cites.

R. Rothe, R. Timofte, and L. Van Gool, “Dex: Deep expectation of apparent age from a single image,” in Proceedings of the IEEE International Conference on Computer Vision Workshops , 2015, pp. 10–15

2015

Earlier work this paper cites.

M. Bojarski, D. Del Testa, D. Dworakowski, B. Firner, B. Flepp, P. Goyal, L. D. Jackel, M. Monfort, U. Muller, J. Zhang, et al. , “End to end learning for self-driving cars,” arXiv preprint arXiv:1604.07316 , 2016

Original

2016

Earlier work this paper cites.

Y. Gal and Z. Ghahramani, “Dropout as a bayesian approximation: Representing model uncertainty in deep learning,” in international conference on machine learning , 2016, pp. 1050–1059

2016

Cited alongside, same era.

K. Chatterjee, M. Chmelík, and M. Tracol, “What is decidable about partially observable markov decision processes with ω \omega -regular objectives,” Journal of Computer and System Sciences , vol. 82, no. 5, pp. 878–911, 2016

2016

Cited alongside, same era.

D. Tran, A. Kucukelbir, A. B. Dieng, M. Rudolph, D. Liang, and D. M. Blei, “Edward: A library for probabilistic modeling, inference, and criticism,” arXiv preprint arXiv:1610.09787 , 2016

Original

2016

Cited alongside, same era.

R. McAllister, Y. Gal, A. Kendall, M. Van Der Wilk, A. Shah, R. Cipolla, and A. V. Weller, “Concrete problems for autonomous vehicle safety: Advantages of bayesian deep learning.” International Joint Conferences on Artificial Intelligence, Inc., 2017

2017

Cited alongside, same era.

C. DMV, “Autonomous vehicle disengagement report,” https://www.dmv.ca.gov/portal/dmv/detail/vr/autonomous/disengagement˙report˙2017 , 2017, accessed: 2018-08-16

2018

Later among the works it cites.

D. T. Danny Yadron, “Tesla driver dies in first fatal crash while using autopilot mode,” https://www.theguardian.com/technology/2016/jun/30/tesla-autopilot-death-self-driving-car-elon-musk , 2016, accessed: 2018-08-16

2018

Later among the works it cites.

K. Lee, Z. Wang, B. I. Vlahov, H. K. Brar, and E. A. Theodorou, “Ensemble bayesian decision making with redundant deep perceptual control policies,” arXiv preprint arXiv:1811.12555 , 2018

Original

2018

Later among the works it cites.

D. Feng, L. Rosenbaum, and K. Dietmayer, “Towards safe autonomous driving: Capture uncertainty in the deep neural network for lidar 3d vehicle detection,” in 2018 21st International Conference on Intelligent Transportation Systems (ITSC) . IEEE, 2018, pp. 3266–3273

2018

Later among the works it cites.