Coordination and Trajectory Prediction for Vehicle Interactions via Bayesian Generative Modeling

H. Akaike, “Fitting autoregressive models for prediction,” Annals of the institute of Statistical Mathematics , vol. 21, no. 1, pp. 243–247, 1969

1969

Earlier work this paper cites.

H. Kantz and T. Schreiber, Nonlinear time series analysis . Cambridge university press, 2004, vol. 7

2004

Earlier work this paper cites.

J. Colyar and J. Halkias, “US highway 101 dataset,” in Federal Highway Administration (FHWA) Technique Report. FHWA-HRT-07-030 , 2007

2007

Earlier work this paper cites.

C. Laugier, I. Paromtchik, M. Perrollaz, Y. Mao, J.-D. Yoder, C. Tay, K. Mekhnacha, and A. Nègre, “Probabilistic analysis of dynamic scenes and collision risk assessment to improve driving safety,” Its Journal , vol. 3, no. 4, pp. 4–19, 2011

2011

Earlier work this paper cites.

D. M. Powers, “Evaluation: from precision, recall and f-measure to roc, informedness, markedness and correlation,” 2011

2011

Earlier work this paper cites.

D. P. Kingma and M. Welling, “Auto-encoding variational bayes,” arXiv preprint arXiv:1312.6114 , 2013

Original

2013

Earlier work this paper cites.

I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio, “Generative adversarial nets,” in Advances in neural information processing systems , 2014, pp. 2672–2680

2014

Earlier work this paper cites.

M. Mirza and S. Osindero, “Conditional generative adversarial nets,” arXiv preprint arXiv:1411.1784 , 2014

Original

2014

Earlier work this paper cites.

T. Chen, E. Fox, and C. Guestrin, “Stochastic gradient hamiltonian monte carlo,” in International Conference on Machine Learning , 2014, pp. 1683–1691

2014

Cited alongside, same era.

K. Sohn, H. Lee, and X. Yan, “Learning structured output representation using deep conditional generative models,” in Advances in Neural Information Processing Systems , 2015, pp. 3483–3491

2015

Cited alongside, same era.

W. Liu, H. He, and F. Sun, “Vehicle state estimation based on minimum model error criterion combining with extended kalman filter,” Journal of the Franklin Institute , vol. 353, no. 4, pp. 834–856, 2016

2016

Cited alongside, same era.

S. Depeweg, J. M. Hernández-Lobato, F. Doshi-Velez, and S. Udluft, “Learning and policy search in stochastic dynamical systems with bayesian neural networks,” arXiv preprint arXiv:1605.07127 , 2016

Original

2016

Cited alongside, same era.

J. Li, H. Ma, W. Zhan, and M. Tomizuka, “Generic probabilistic interactive situation recognition and prediction: From virtual to real,” in 2018 IEEE Intelligent Transportation Systems Conference , 2018

2018

Later among the works it cites.

J. Li, W. Zhan, and M. Tomizuka, “Generic vehicle tracking framework capable of handling occlusions based on modified mixture particle filter,” in Proceedings of 2018 IEEE Intelligent Vehicles Symposium (IV) , 2018, pp. 936–942

2018

Later among the works it cites.

L. Sun, W. Zhan, and M. Tomizuka, “Probabilistic prediction of interactive driving behavior via hierarchical inverse reinforcement learning,” in 2018 21st International Conference on Intelligent Transportation Systems (ITSC) . IEEE, 2018, pp. 2111–2117

2018

Later among the works it cites.

L. Sun, W. Zhan, M. Tomizuka, and A. D. Dragan, “Courteous autonomous cars,” in 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) . IEEE, 2018, pp. 663–670

2018