The paper describes a new way to build autonomous driving systems, called AD-H, that uses a hierarchical approach. Instead of having a single model that tries to handle all aspects of driving, AD-H splits the task into different "agents" or modules, each responsible for a specific part of the problem.
Jun 5, 2024
Jun 5, 2024 · We implement this idea through a hierarchical multi-agent driving system named AD-H, including a MLLM planner for high-level reasoning and a lightweight ...
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Jun 6, 2024 · The AD-H model offers a promising solution for autonomous driving by breaking down the task into manageable layers. This hierarchical approach ...
Jun 5, 2024 · LMDrive is introduced, a novel language-guided, end-to-end, closed-loop autonomous driving framework that uniquely processes and integrates ...
Jun 6, 2024 · Autonomous driving hierarchical agents are transforming vehicle technology with the AD-H system, leveraging MLLMs for superior navigation.
Jun 28, 2024 · 1/5 "AD-H: Autonomous Driving with Hierarchical Agents." This paper presents a novel framework for autonomous driving using hierarchical ...
We are currently organizing the code for AD-H. All dataset, checkpoints, and training code will be coming soon.
We consider a single1 human driver H and a single autonomous system A in control of their respective vehicles. The dynamics of the joint state xt ∈X ⊂ Rn ...
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Here is a collection of research papers and the relevant valuable open-source resources for awesome knowledge-driven autonomous driving (AD).
Understanding and interacting with human-driven cars are essential for autonomous driving cars to behave socially in cooperative scenarios, such as lane ...