automr

Create a mini-application called 'AutoTestDrive' that leverages the 'automr' package to perform metamorphic testing on autonomous driving models. This application will simulate various driving scenarios and test the robustness of machine learning models designed for autonomous vehicles. Here’s a detailed breakdown of the steps and features required for this project:

1. **Setup Environment**: Begin by setting up your Python environment with the necessary packages including 'automr'. Ensure you have a virtual environment to manage dependencies.

2. **Model Integration**: Integrate an existing autonomous driving model into your application. This could be any pre-trained model that accepts sensor inputs (like Lidar or camera feeds) and outputs steering commands or collision predictions.

3. **Scenario Generation**: Develop a feature within AutoTestDrive to generate driving scenarios. These scenarios should include different road conditions, obstacles, and traffic situations. Each scenario should be represented as a set of input data and expected outcomes.

4. **Metamorphic Testing Setup**: Use the 'automr' package to define metamorphic relations for your driving scenarios. A metamorphic relation defines how the output of the model should change if certain aspects of the input data are altered. For example, if an obstacle moves closer, the model should predict a more severe collision risk.

5. **Execution and Validation**: Implement a function to execute each scenario through the autonomous driving model and validate the outputs against the expected outcomes using the metamorphic relations defined earlier.

6. **Report Generation**: Finally, create a reporting mechanism within AutoTestDrive to document the results of each test run. This report should highlight any discrepancies between the model's predictions and the expected outcomes based on the metamorphic relations.

Suggested Features:
- Support for multiple types of autonomous driving models (e.g., reinforcement learning, deep learning).
- Ability to customize scenarios with user-defined parameters.
- Visualization tools to display the test results and model behavior in different scenarios.
- Option to save and load test scenarios for future use.

By following these steps and utilizing the 'automr' package effectively, AutoTestDrive will serve as a valuable tool for developers and researchers looking to ensure the reliability and safety of autonomous driving systems.