Receive, Reason, and React: Drive as You Say, With Large Language Models in Autonomous Vehicles
Author:
Affiliation:
1. College of Engineering, Purdue University, West Lafayette, IN, USA
2. Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL, USA
3. Department of Computer Science, University of Virginia, Charlottesville, VA, USA
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/5117645/10589495/10491134.pdf?arnumber=10491134
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1. Reliability of Self-Driving Cars: When Can We Remove the Safety Driver?
2. Radar Enlightens the Dark: Enhancing Low-Visibility Perception for Automated Vehicles with Camera-Radar Fusion
3. REDFormer: Radar Enlightens the Darkness of Camera Perception with Transformers
4. Drive Like a Machine: A Green Reflection of Red Flag Acts for Intelligent Vehicles [History and Perspectives]
5. LLM4Drive: A survey of large language models for autonomous driving;Yang,2023
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