Drive as You Speak: Enabling Human-Like Interaction with Large Language Models in Autonomous Vehicles

Author:

Cui Can1,Ma Yunsheng1,Cao Xu2,Ye Wenqian2,Wang Ziran1

Affiliation:

1. Purdue University,West Lafayette,IN,USA,47907

2. PediaMed.AI Lab,Shenzhen,China,518048

Publisher

IEEE

Reference35 articles.

1. Constitutional AI: Harmlessness from AI Feedback;Bai;arXiv,2022

2. Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data

3. Graph of Thoughts: Solving Elaborate Problems with Large Language Models

4. ChatGPT is a Knowledgeable but Inexperienced Solver: An Investigation of Commonsense Problem in Large Language Models;Bian;arXiv,2023

5. PaLM: Scaling Language Modeling with Pathways;Chowdhery;arXiv,2022

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1. Large models for intelligent transportation systems and autonomous vehicles: A survey;Advanced Engineering Informatics;2024-10

2. DrPlanner: Diagnosis and Repair of Motion Planners for Automated Vehicles Using Large Language Models;IEEE Robotics and Automation Letters;2024-10

3. Using Multimodal Large Language Models (MLLMs) for Automated Detection of Traffic Safety-Critical Events;Vehicles;2024-09-02

4. Receive, Reason, and React: Drive as You Say, With Large Language Models in Autonomous Vehicles;IEEE Intelligent Transportation Systems Magazine;2024-07

5. Invited Paper: DeepSLOs for the Computing Continuum;Proceedings of the 2024 Workshop on Advanced Tools, Programming Languages, and PLatforms for Implementing and Evaluating algorithms for Distributed systems;2024-06-17

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