HighwayEnv is an OpenAI Gym-compatible environment focused on autonomous driving scenarios. It provides flexible simulations for testing decision-making algorithms in highway, intersection, and merging traffic situations.

Features

  • Simulates autonomous driving on highways and urban roads
  • Compatible with OpenAI Gym and RL libraries
  • Customizable traffic density and behaviors
  • Includes reward shaping for lane-keeping, safety, and efficiency
  • Supports multi-agent and adversarial scenarios
  • Visualization tools for rendering driving simulations

Project Samples

highway-env Screenshot 1

Project Activity

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Categories

Autonomous Driving, Reinforcement Learning Frameworks

License

MIT License

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Additional Project Details

Programming Language

Python

Related Categories

Python Autonomous Driving Software, Python Reinforcement Learning Frameworks

Registered

2025-03-13
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