This model, from the paper Building reliable sim driving agents by scaling self-play, is a pre-trained policy for a reliable simulated driving agent. It was trained using self-play on the Waymo Open Motion Dataset and achieves a 99.8% goal completion rate with minimal undesired outcomes.
Project page: https://sites.google.com/view/reliable-sim-agents
Library: https://github.com/Emerge-Lab/gpudrive
To load a pre-trained policy, use the following:
from gpudrive.networks.late_fusion import NeuralNet
# Load pre-trained model via huggingface_hub
agent = NeuralNet.from_pretrained("daphne-cornelisse/policy_S10_000_02_27")
See tutorial 04 for all the details.
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