policy

SafeRL-AutonomousDriving

matteoamagliani · PyTorch

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Overview

Name

Author

matteoamagliani

Framework

PyTorch

License

MIT

Skill type

other

Evidence level

untested

Task description

Safe RL for Autonomous Driving: A project using Constrained MDPs to train a vehicle agent for lane-centering, speed adherence, and collision avoidance. Features kinematic modeling, reward shaping, and safety constraints.

Spaces

Action space

other · 0-dim · 0Hz

Observation space

type: other

Links

HuggingFace repo

null

Paper (arXiv)

null

Compatible robots

3+17 mentioned but not in catalog yet

SpotBoston Dynamics T1Booster Robotics ApolloApptronik

Compatible environments

No environments list SafeRL-AutonomousDriving yet.

Datasets that reference this policy

No datasets reference SafeRL-AutonomousDriving yet.