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πŸš— autonomous-driving-rl-interpretability - Understand AI for Safer Driving

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πŸ“– Description

This project focuses on the interpretability of reinforcement learning (RL) agents used in autonomous driving. We use visual attribution methods to explain how AI makes decisions on the road. By understanding AI behavior, we can make driving systems safer and more reliable.

πŸš€ Getting Started

Follow these simple steps to download and run the application.

1. πŸ“₯ Visit the Releases Page

Go to the following link to access the software:

Visit the Releases Page

2. πŸ—‚οΈ Download the Application

On the Releases page, look for the latest version of the application. You will find a section labeled "Assets." Click the appropriate file for your operating system.

3. πŸ” Check System Requirements

Ensure your computer meets these basic requirements:

  • Operating System: Windows, macOS, or Linux
  • Memory: At least 4 GB of RAM
  • Disk Space: Minimum 500 MB available
  • Python 3.6 or later (if not bundled with the application)

4. βš™οΈ Install the Application

  1. Locate the downloaded file on your computer.
  2. If you downloaded a .zip file, extract it to your desired folder.
  3. Open the folder and look for the application file:
    • For Windows, you will see a .exe file.
    • For macOS, look for a .app file.
    • For Linux, you might find an executable file.

Double-click the file to run the application.

5. πŸ–₯️ Run the Application

Once the application opens, follow the on-screen instructions.

  • It may ask for permissions or specific settings; grant these for the best experience.
  • The application will guide you through the features, including visual attribution analysis of RL agents in autonomous driving.

πŸ“Š Features

  • Visual Attribution: Understand how AI decisions are made on the road.
  • User-Friendly Dashboard: Easy navigation and clear visuals enhance your experience.
  • Real-Time Analysis: Get insights while the AI processes driving data.
  • Export Options: Save your analysis results for further review.

πŸ“ Usage Instructions

  1. After running the application, you can select different scenarios to analyze.
  2. Choose settings that reflect real-world driving conditions.
  3. View the generated visualizations to understand the AI's decision-making process.
  4. You can export your findings in various formats for further analysis or sharing.

❓ FAQs

What if the application does not start?

If the application does not open, please check if your system meets the requirements. Ensure your operating system is supported and try again.

How can I provide feedback or report issues?

You have the option to report issues directly on the GitHub page under the "Issues" tab. Your feedback helps improve the software.

Can I use this software for educational purposes?

Absolutely! We encourage you to use it for learning about AI interpretation and decision-making in autonomous vehicles.

🌟 Acknowledgments

This project contributes to the ongoing efforts in making AI in autonomous driving more transparent and understandable. We thank the research community and contributors for their support.

πŸ”— Links

For more details about this project and updates, please refer to the following:

For any additional help, feel free to check our support page.

Download the latest version and dive into understanding AI today!

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πŸš— Analyze and visualize decision-making in autonomous driving RL agents using Integrated Gradients for clearer interpretability in complex driving tasks.

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