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

See All Activity >

Categories

Autonomous Driving, Reinforcement Learning Frameworks

License

MIT License

Follow highway-env

highway-env Web Site

Other Useful Business Software
Awardco Employee Recognition Icon
Awardco Employee Recognition

For companies looking to recognize and reward their employees

Everything you love about Amazon is now available for rewards and recognition. Awardco has partnered with Amazon Business to bring millions of reward choices, lower vendor fees and dollar-for-dollar recognition spend to your organization. More choice, more capability, and less spend - all in one simple platform.
Learn More
Rate This Project
Login To Rate This Project

User Reviews

Be the first to post a review of highway-env!

Additional Project Details

Programming Language

Python

Related Categories

Python Autonomous Driving Software, Python Reinforcement Learning Frameworks

Registered

2025-03-13
Report inappropriate content