Publisher
Springer Science and Business Media LLC
Reference30 articles.
1. Chen, Y. F., Liu, M., Liu, S.-Y., Miller, J., & How, J. P. (2016). Predictive modeling of pedestrian motion patterns with Bayesian nonparametrics. In Proceedings of AIAA guidance navigation and control conference (pp.1861–1875). https://doi.org/10.2514/6.2016-1861. Accessed 8 Aug 2021.
2. Schneider, N., Gavrila, D. M., Weickert, J., Hein, M., & Schiele, B. (2013). Pedestrian path prediction with recursive Bayesian filters: A comparative study. Proceedings of German Conference on Pattern Recognition, Lecture Notes in Computer Science, 8142, 174–183.
3. Bonnin, S., Weisswange, T. H., Kummert, F., & Schmuedderich, J. (2014). General behavior prediction by a combination of scenario specific models. IEEE Transactions on Intelligent Transportation Systems, 15, 1478–1488.
4. Bera, A., & Manocha, D. (2017). PedLearn: Realtime pedestrian tracking, behavior learning, and navigation for autonomous vehicles. In Proceedings of 9th workshop on planning, perception and navigation for intelligent vehicles. http://ppniv17.irccyn.ec-nantes.fr/session4/Bera/paper.pdf. Accessed 8 Aug 2021.
5. Ziebart, B. D., Ratliff, N., Gallagher, G., Mertz, C., Peterson, K., Andrew Bagnell, J., Hebert, M., Dey, A. K., & Srinivasa, S. (2009). Planning-based prediction for pedestrians. In Proceedings of IEEE/RSJ international conference on intelligent robots and systems (pp. 3931–3936). https://doi.org/10.1109/IROS.2009.5354147.
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献