Agent State Estimation
Agent State Estimation is a computational method in traffic prediction that determines the current dynamical condition of a traffic participant by estimating its kinematic and positional attributes from sensor observations, distinguishing itself from broader prediction tasks by focusing exclusively on the instantaneous state rather than future behaviors or intentions.
155
Publications
8.8K
Citations
527
Authors
217
Institutions
Publications per year
2017–2026
90
155
Multi-Agent Reinforcement Leraning for Traffic Light Control
Marco Wiering · 2000 · 290 citations
Agile Autonomous Driving using End-to-End Deep Imitation Learning
Yunpeng Pan, Ching-An Cheng, Kamil Saigol et al. · 2018 · 255 citations · Full text
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University of Illinois Urbana-Champaign
Urbana, United States
6 h-index
12 publications
894 citations
ETH Zurich
Zurich, Switzerland
6 h-index
29 publications
1.5K citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
15 publications
1.1K citations
University of California, Berkeley
Berkeley, United States
4 h-index
9 publications
149 citations
University of Pennsylvania
Philadelphia, United States
3 h-index
6 publications
660 citations
University of Zurich
Zurich, Switzerland
3 h-index
9 publications
877 citations
East China University of Science and Technology
Shanghai, China
3 h-index
10 publications
611 citations
Nanyang Technological University
Singapore, Singapore
3 h-index
3 publications
191 citations
1–8 of 217
Repository · 9 publications · 487 citations
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7 publications · 588 citations
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5 publications · 257 citations
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4 publications · 309 citations
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3 publications · 154 citations
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