StanfordASL/Trajectron
Code accompanying "The Trajectron: Probabilistic Multi-Agent Trajectory Modeling with Dynamic Spatiotemporal Graphs" by Boris Ivanovic and Marco Pavone.
This project helps researchers and engineers predict the movement of multiple interacting agents, like pedestrians or vehicles, in dynamic environments. It takes in historical trajectory data from various scenes and outputs probable future paths for each agent. This is designed for robotics researchers, urban planners, or anyone studying multi-agent systems.
141 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to model and predict the behavior of multiple interacting entities, such as people in a crowd or vehicles on a road, and understand the uncertainty in their future movements.
Not ideal if you are looking for a pre-packaged application for real-time deployment or if your primary interest is in single-agent trajectory prediction.
Stars
141
Forks
40
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Dec 09, 2020
Commits (30d)
0
Dependencies
20
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