Fetching the paper…
Reading the bibliography…
Predicting the collective motion of a group of pedestrians (a crowd) under the vehicle influence is essential for the development of autonomous vehicles to deal with mixed urban scenarios where interpersonal interaction and vehicle-crowd interaction (VCI) are significant.
A. Lerner, Y. Chrysanthou, and D. Lischinski, “Crowds by example,” in Computer Graphics Forum
2007
Earlier work this paper cites.
B. J. Mohler, W. B. Thompson, S. H. Creem-Regehr, H. L. Pick, and W. H. Warren, “Visual flow influences gait transition speed and preferred walking speed,” Experimental brain research
2007
Earlier work this paper cites.
S. Pellegrini, A. Ess, K. Schindler, and L. Van Gool, “You’ll never walk alone: Modeling social behavior for multi-target tracking,” in Computer Vision, 2009 IEEE 12th International Conference on
2009
Earlier work this paper cites.
F. Zanlungo, T. Ikeda, and T. Kanda, “Social force model with explicit collision prediction,” EPL (Europhysics Letters)
2011
Earlier work this paper cites.
B. Benfold and I. Reid, “Stable multi-target tracking in real-time surveillance video,” in CVPR 2011
2011
Earlier work this paper cites.
W. Daamen and S. Hoogendoorn, “Calibration of pedestrian simulation model for emergency doors by pedestrian type,” Transportation Research Record
2012
Earlier work this paper cites.
B. Zhou, X. Wang, and X. Tang, “Understanding collective crowd behaviors: Learning a mixture model of dynamic pedestrian-agents,” in 2012 IEEE Conference on Computer Vision and Pattern Recognition
2012
Earlier work this paper cites.
A. Geiger, P. Lenz, and R. Urtasun, “Are we ready for autonomous driving? the kitti vision benchmark suite,” in Conference on Computer Vision and Pattern Recognition (CVPR)
2012
Cited alongside, same era.
R. Faragher et al
2012
Cited alongside, same era.
N. Schneider and D. M. Gavrila, “Pedestrian path prediction with recursive bayesian filters: A comparative study,” german conference on pattern recognition
2013
Cited alongside, same era.
B. Anvari, M. G. Bell, A. Sivakumar, and W. Y. Ochieng, “Modelling shared space users via rule-based social force model,” Transportation Research Part C: Emerging Technologies
2015
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
D. Yang, A. Kurt, K. Redmill, and Ü. Özgüner, “Agent-based microscopic pedestrian interaction with intelligent vehicles in shared space,” in Proceedings of the 2nd International Workshop on Science of Smart City Operations and Platforms Engineering
2017
Later among the works it cites.
H. Cheng and M. Sester, “Mixed traffic trajectory prediction using lstm–based models in shared space,” in The Annual International Conference on Geographic Information Science
2018
Later among the works it cites.
M. Pfeiffer, G. Paolo, H. Sommer, J. Nieto, R. Siegwart, and C. Cadena, “A data-driven model for interaction-aware pedestrian motion prediction in object cluttered environments,” in 2018 IEEE International Conference on Robotics and Automation (ICRA)
2018
Later among the works it cites.
A. Lukežič, T. Vojíř, L. Č. Zajc, J. Matas, and M. Kristan, “Discriminative correlation filter tracker with channel and spatial reliability,” International Journal of Computer Vision
2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
2016
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
2016
Cited alongside, same era.
W. Zeng, P. Chen, G. Yu, and Y. Wang, “Specification and calibration of a microscopic model for pedestrian dynamic simulation at signalized intersections: A hybrid approach,” Transportation Research Part C: Emerging Technologies
2017
Cited alongside, same era.
2018
Later among the works it cites.
R. Krajewski, J. Bock, L. Kloeker, and L. Eckstein, “The highd dataset: A drone dataset of naturalistic vehicle trajectories on german highways for validation of highly automated driving systems,” in 2018 IEEE 21st International Conference on Intelligent Transportation Systems (ITSC)
2018
Later among the works it cites.