Rule-based Prediction Models
Rule-Based Prediction Models is a predictive modeling approach in traffic participant behavior forecasting that belongs to the class of deterministic methods relying on predefined logical rules derived from domain knowledge, distinguished by its use of explicit condition-action rules to simulate and predict motion patterns without probabilistic or learned components.
264
Publications
19.9K
Citations
1.1K
Authors
489
Institutions
Publications per year
2017–2026
63
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489
University Medical Center Utrecht
Utrecht, The Netherlands
12 h-index
51 publications
3.3K citations

Brigham and Women's Hospital
Boston, United States
8 h-index
30 publications
3.5K citations
Harvard University
Cambridge, United States
7 h-index
21 publications
15.9K citations
University of Pittsburgh
Pittsburgh, United States
7 h-index
22 publications
15.4K citations

Uppsala University
Uppsala, Sweden
6 h-index
16 publications
448 citations
University of Kansas
Lawrence, United States
6 h-index
12 publications
468 citations
Erasmus MC
Rotterdam, The Netherlands
6 h-index
13 publications
658 citations
Utrecht University
Utrecht, The Netherlands
5 h-index
11 publications
267 citations
1–8 of 489
TFS · 5 publications · 309 citations
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5 publications · 252 citations
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4 publications · 106 citations
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4 publications · 497 citations
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3 publications · 240 citations
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