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
Build Agents and Models on One Platform Icon
Build Agents and Models on One Platform

Everything you need to build production-ready agents and models. Access 200+ Google and third-party AI models and tools.

Gemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
Start Free
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