This repository is a curated list of resources for autonomous vehicles, targeting researchers, engineers, and students interested in the field. It provides a comprehensive overview of foundational knowledge, academic courses, research papers, open-source software, hardware, datasets, companies, media, and legal aspects related to self-driving cars.

How It Works

The repository functions as a directory, aggregating and categorizing links to external resources. It's structured to guide users through various facets of autonomous vehicle development, from fundamental AI and robotics concepts to specific applications in perception, navigation, and control. The curated nature aims to save users time by filtering and organizing a vast amount of information.

Quick Start & Requirements

This is a curated list, not a software project. No installation or execution is required. Users can directly browse the provided links for courses, papers, datasets, and software.

Highlighted Details

• Extensive lists of academic courses from top universities (MIT, Stanford, Udacity) covering deep learning, computer vision, and robotics for autonomous driving.
• A broad collection of research papers categorized by topic (Perception, Navigation & Planning, Control, etc.) with publication years and references.
• Numerous datasets for training and benchmarking, including large-scale offerings like Waymo and nuScenes, and specialized datasets for specific conditions (e.g., foggy scenes, Indian roads).
• Links to key open-source software projects like Autoware and Comma.ai Openpilot, and hardware platforms like DonkeyCar.

Maintenance & Community

The repository is maintained by manfreddiaz. Contributions are welcomed via pull requests to add new links. Specific community channels (Discord/Slack) or active contributor information are not detailed in the README.

Licensing & Compatibility

The repository itself is a list of links and does not have a specific software license. The licenses of the linked resources vary and must be checked individually.

Limitations & Caveats

As a curated list, the content's accuracy and up-to-dateness depend on the maintainer and the linked external resources. Some links may become outdated or broken over time. The sheer volume of information may require significant effort to navigate and digest fully.