Fetching the paper…
Reading the bibliography…
Understanding the intentions of drivers at intersections is a critical component for autonomous vehicles.
E. Strigel, D. Meissner, F. Seeliger, B. Wilking, and K. Dietmayer, “The ko-per intersection laserscanner and video dataset,” in Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on . IEEE, 2014, pp. 1900–1901
1901
Earlier work this paper cites.
M.-P. Dubuisson and A. K. Jain, “A modified hausdorff distance for object matching,” in Pattern Recognition, 1994. Vol. 1-Conference A: Computer Vision & Image Processing., Proceedings of the 12th IAPR International Conference on , vol. 1. IEEE, 1994, pp. 566–568
1994
Earlier work this paper cites.
V. Alexiadis, J. Colyar, J. Halkias, R. Hranac, and G. McHale, “The next generation simulation program,” Institute of Transportation Engineers. ITE Journal , vol. 74, no. 8, p. 22, 2004
2004
Earlier work this paper cites.
H. Veeraraghavan, N. Papanikolopoulos, and P. Schrater, “Deterministic sampling-based switching kalman filtering for vehicle tracking,” in 2006 IEEE Intelligent Transportation Systems Conference . IEEE, 2006, pp. 1340–1345
2006
Earlier work this paper cites.
C. Thiemann, M. Treiber, and A. Kesting, “Estimating acceleration and lane-changing dynamics from next generation simulation trajectory data,” Transportation Research Record: Journal of the Transportation Research Board , no. 2088, pp. 90–101, 2008
2008
Earlier work this paper cites.
E. Choi, “Crash factors in intersection-related crashes: An on-scene perspective (no. dot hs 811 366),” US DOT National Highway Traffic Safety Administration , 2010
2010
Earlier work this paper cites.
M. Althoff and A. Mergel, “Comparison of markov chain abstraction and monte carlo simulation for the safety assessment of autonomous cars,” IEEE Transactions on Intelligent Transportation Systems , vol. 12, no. 4, pp. 1237–1247, 2011
2011
Earlier work this paper cites.
J. Wiest, M. Höffken, U. Kreßel, and K. Dietmayer, “Probabilistic trajectory prediction with gaussian mixture models,” in Intelligent Vehicles Symposium (IV), 2012 IEEE . IEEE, 2012, pp. 141–146
2012
Earlier work this paper cites.
H. Rouzikhah, M. King, and A. Rakotonirainy, “The validity of simulators in studying driving behaviours,” in Proceedings of Australasian Road Safety Research, Policing and Education Conference , 2012
2012
Earlier work this paper cites.
P. Kumar, M. Perrollaz, S. Lefevre, and C. Laugier, “Learning-based approach for online lane change intention prediction,” in Intelligent Vehicles Symposium (IV), 2013 IEEE . IEEE, 2013, pp. 797–802
2013
Earlier work this paper cites.
A. Graves, “Generating sequences with recurrent neural networks,” 2013
2013
Earlier work this paper cites.
T. Streubel and K. H. Hoffmann, “Prediction of driver intended path at intersections,” in 2014 IEEE Intelligent Vehicles Symposium Proceedings . IEEE, 2014, pp. 134–139
2014
Cited alongside, same era.
M. Schreier, V. Willert, and J. Adamy, “Bayesian, maneuver-based, long-term trajectory prediction and criticality assessment for driver assistance systems,” in Intelligent Transportation Systems (ITSC), 2014 IEEE 17th International Conference on . IEEE, 2014, pp. 334–341
2014
Cited alongside, same era.
Q. Tran and J. Firl, “Online maneuver recognition and multimodal trajectory prediction for intersection assistance using non-parametric regression,” in Intelligent Vehicles Symposium Proceedings, 2014 IEEE . IEEE, 2014, pp. 918–923
2014
Cited alongside, same era.
2014
Cited alongside, same era.
A. Kuefler, J. Morton, T. Wheeler, and M. Kochenderfer, “Imitating driver behavior with generative adversarial networks,” in Intelligent Vehicles Symposium (IV), 2017 IEEE . IEEE, 2017, pp. 204–211
2017
Later among the works it cites.
N. Lee, W. Choi, P. Vernaza, C. B. Choy, P. H. Torr, and M. Chandraker, “Desire: Distant future prediction in dynamic scenes with interacting agents,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2017, pp. 336–345
2017
Later among the works it cites.
2017
Later among the works it cites.
B. Coifman and L. Li, “A critical evaluation of the next generation simulation (ngsim) vehicle trajectory dataset,” Transportation Research Part B: Methodological , vol. 105, pp. 362 – 377, 2017. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S0191261517300838
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
GPy, “GPy: A gaussian process framework in python,” http://github.com/SheffieldML/GPy
2014
Cited alongside, same era.
“TensorFlow: Large-scale machine learning on heterogeneous systems,” 2015, software available from tensorflow.org. [Online]. Available: http://tensorflow.org/
2015
Cited alongside, same era.
A. Robicquet, A. Sadeghian, A. Alahi, and S. Savarese, “Learning social etiquette: Human trajectory understanding in crowded scenes,” in European conference on computer vision . Springer, 2016, pp. 549–565
2016
Cited alongside, same era.
A. Alahi, K. Goel, V. Ramanathan, A. Robicquet, L. Fei-Fei, and S. Savarese, “Social lstm: Human trajectory prediction in crowded spaces,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 961–971
2016
Cited alongside, same era.
A. Khosroshahi, E. Ohn-Bar, and M. M. Trivedi, “Surround vehicles trajectory analysis with recurrent neural networks,” in Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International Conference on . IEEE, 2016, pp. 2267–2272
2016
Cited alongside, same era.
D. Ha, A. Dai, and Q. V. Le, “Hypernetworks,” arXiv preprint arXiv:1609.09106 , 2016
2016
Cited alongside, same era.
D. J. Phillips, T. A. Wheeler, and M. J. Kochenderfer, “Generalizable intention prediction of human drivers at intersections,” in Intelligent Vehicles Symposium (IV), 2017 IEEE . IEEE, 2017, pp. 1665–1670
2017
Cited alongside, same era.
M. Ester, H.-P. Kriegel, J. Sander, X. Xu et al. , “A density-based algorithm for discovering clusters in large spatial databases with noise.”
Cited in the paper.
2017
Later among the works it cites.
A. Zyner, S. Worrall, J. Ward, and E. Nebot, “Long short term memory for driver intent prediction,” in Intelligent Vehicles Symposium (IV), 2017 IEEE . IEEE, 2017, pp. 1484–1489
2017
Later among the works it cites.
2017
Later among the works it cites.
2017
Later among the works it cites.
A. Zyner, S. Worrall, and E. Nebot, “A recurrent neural network solution for predicting driver intention at unsignalized intersections,” IEEE Robotics and Automation Letters , vol. 3, no. 3, pp. 1759–1764, 2018
2018
Closest in time.
2018
Closest in time.
2018
Closest in time.