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Forecasting Interactive Dynamics of Pedestrians With Fictitious Play

CVPR 2017 · Multi-agent systems and games › Human-AI and goal-conditioned · approach: Interactive multi-agent trajectory prediction · 155 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Model pedestrians' coupled decisions with Fictitious Play rather than independent MDP predictionsPedestrian trajectory forecasting · ZaraNLL: 43.3834 -> 42.1426Helped
Model pedestrians' coupled decisions with Fictitious Play rather than independent MDP predictionsPedestrian trajectory forecasting · ZaraSCR: 0.065 -> 0.013Helped
Model pedestrians' coupled decisions with Fictitious Play rather than independent MDP predictionsPedestrian trajectory forecasting · Town CentreNLL: 14.2471 -> 12.5804Helped
Model pedestrians' coupled decisions with Fictitious Play rather than independent MDP predictionsPedestrian trajectory forecasting · LIDAR TrajectorySCR: 0.056 -> 0.009Helped
Add appearance-based individualized speedFP · Town CentreNLL: 12.5804 -> 10.892Helped
Add appearance-based individualized speedFP · Town CentreSCR: 0.052 -> 0.049Helped
Add social compliance features to represent other pedestrians' predicted occupancy (ablation)FP · Town CentreNLL: 14.45 -> 12.58Helped
Add social compliance features to represent other pedestrians' predicted occupancy (ablation)FP · Town CentreSCR: 0.211 -> 0.043Helped
Add body-orientation features (ablation)FP with social compliance · Town CentreNLL: 12.65 -> 12.58Helped
Add body-orientation features (ablation)FP with social compliance · Town CentreSCR: 0.046 -> 0.043Helped

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