jiachenli94/Awesome-Interaction-Aware-Trajectory-Prediction resource

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1690 stars · 311 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A curated awesome-list of state-of-the-art research materials on interaction-aware behavior and trajectory prediction, including datasets, survey papers, code, and benchmarks. It covers vehicles, pedestrians, mobile robots, and sport players, maintained by researchers from Stanford and UC Berkeley.

Use cases

• find datasets for pedestrian trajectory prediction
• survey state-of-the-art papers on vehicle motion forecasting
• find public code implementations for multi-agent trajectory prediction
• locate benchmarks and evaluation metrics for trajectory forecasting
• research interaction-aware prediction for autonomous driving
• find trajectory prediction datasets for sport player analysis

When to choose

• starting research on trajectory or motion prediction and needing a literature map
• looking for datasets of vehicle, pedestrian, or sport player trajectories
• comparing methods and benchmarks for interaction-aware forecasting

When to avoid

• you need a runnable prediction model or library rather than a reading list
• you need production-ready forecasting software
• you need topics outside trajectory prediction such as decision making or motion planning (see the maintainers' companion list)

Facets

learning-resource · maturity active

machine-learning computer-vision data-science autonomous-vehicles artificial-intelligence machine-learning deep-learning robotics cross-platform awesome-list trajectory-prediction motion-prediction pedestrian-trajectories autonomous-driving multiagent-systems research-papers datasets

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