Interaction-aware Prediction
Interaction-Aware Prediction is a modeling paradigm in traffic participant forecasting that belongs to the class of trajectory prediction methods and is distinguished by its explicit incorporation of dynamic interdependencies and behavioral influences among multiple agents in shared environments.
63
Publications
4.1K
Citations
209
Authors
96
Institutions
Publications per year
2017–2026
54
63
1–5 of 63
209
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h-index
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96
University of California, Berkeley
Berkeley, United States
8 h-index
22 publications
967 citations
Nanyang Technological University
Singapore, Singapore
5 h-index
12 publications
575 citations

University of Waterloo
Waterloo, Canada
4 h-index
8 publications
304 citations
Technical University of Munich
Munich, Germany
4 h-index
13 publications
1.2K citations
Tongji University
Shanghai, China
3 h-index
7 publications
228 citations
BMW Group (Germany)
Munich, Germany
3 h-index
5 publications
658 citations

Peking University
Beijing, China
2 h-index
2 publications
75 citations

Central South University
Changsha, China
2 h-index
3 publications
224 citations
1–8 of 96
6 publications · 370 citations
6
h-index
ITIVBL · 6 publications · 659 citations
6
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Repository · 5 publications · 177 citations
5
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Conference · 2 publications · 91 citations
2
h-index
2 publications · 256 citations
2
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1–5