The Group Interaction Field for Learning and Explaining Pedestrian Anticipation

Author:

Wang Xueyang,Chen Xuecheng,Jiang Puhua,Lin HaozheORCID,Yuan XiaoyunORCID,Ji MengqiORCID,Guo Yuchen,Huang Ruqi,Fang LuORCID

Funder

Key Research and Development Program of Zhejiang Province

National Natural Science Foundation of China

Ministry of Science and Technology of the People's Republic of China

Publisher

Elsevier BV

Subject

General Engineering,Energy Engineering and Power Technology,Materials Science (miscellaneous),General Chemical Engineering,Environmental Engineering,General Computer Science

Reference59 articles.

1. 9–12; Cardiff;Rasouli A, Kotseruba I, Tsotsos JK. Pedestrian action anticipation using contextual feature fusion in stacked RNNs. In: Proceedings of the 30th British Machine Vision Conference (BMVC 2019);,2019

2. PORCA: modeling and planning for autonomous driving among many pedestrians;Luo;IEEE Robot Autom Lett,2018

3. Trautman P, Ma J, Murray RM, Krause A. Robot navigation in dense human crowds: the case for cooperation. In: Proceedings of the IEEE International Conference on Robotics and Automation; 2013 May 6–10; Karlsruhe, Germany. New York City: IEEE; 2013. p. 2153–60.

4. Yao X, Zhang J, Oh J. Following social groups: socially compliant autonomous navigation in dense crowds. 2019. arXiv:1911.12063.

5. A new lattice hydrodynamic model for bidirectional pedestrian flow with the consideration of pedestrian’s anticipation effect;Zhou;Nonlinear Dyn,2015

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