oskarnatan/end-to-end-driving
Implementation code for: End-to-end Autonomous Driving with Semantic Depth Cloud Mapping and Multi-agent, IEEE Trans. Intelligent Vehicles, 2022.
This project provides an end-to-end solution for autonomous driving, enabling vehicles to navigate complex environments using a combination of semantic understanding and depth perception. It takes in simulated driving data, including sensor readings and environmental context, and outputs robust driving decisions and control signals. This is ideal for researchers and engineers working on the development and evaluation of self-driving car technologies.
No commits in the last 6 months.
Use this if you are developing or evaluating autonomous driving systems and need to test different perception and control models in a simulated environment.
Not ideal if you are looking for a plug-and-play solution for real-world autonomous vehicles without extensive development work.
Stars
25
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7
Language
Python
License
MIT
Category
Last pushed
Mar 28, 2024
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