omarathon/rl-multi-agent-car-parking

simulation/RL - multi-agent car parking using reinforcement learning

27
/ 100
Experimental

This project helps robotics engineers or simulation designers develop and test intelligent systems for parking vehicles in complex environments. It takes a simulated car parking scenario as input and outputs optimized control policies for multiple autonomous agents (cars) to navigate and park efficiently. Professionals in autonomous vehicle development or smart city planning would find this useful for prototyping and evaluating parking solutions.

No commits in the last 6 months.

Use this if you are developing or researching multi-agent autonomous parking systems and need a simulation environment to train and evaluate reinforcement learning models.

Not ideal if you are looking for a ready-to-deploy parking management system or a tool for real-world car park operations.

autonomous-vehicles robotics-simulation smart-city-planning traffic-management AI-training
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 16 / 25
Community 6 / 25

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Stars

12

Forks

1

Language

C#

License

CC-BY-4.0

Last pushed

Aug 04, 2024

Commits (30d)

0

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