Retraction Notice: Chat With ChatGPT on Intelligent Vehicles: An IEEE TIV Perspective
This letter reports on a TIV DHW (decentralized and hybrid workshop) that explores the prospective influence of ChatGPT on research and development in intelligent vehicles. To assess the update capabilities of ChatGPT, we conducted tests involving both basic and technically relevant questions. Our preliminary testing revealed that ChatGPT's information can be updated and corrected at one time, but it may take some time for the changes to be reflected in ChatGPT's responses, so it may not always possess the latest knowledge regarding specific topics. We further discuss the prospective influence of ChatGPT on the field of intelligent vehicles, particularly possible applications of ChatGPT in areas like autonomous driving, human-vehicle interaction, and intelligent transportation systems, highlighting challenges and opportunities associated with these applications. Additionally, we address technical questions, such as the feasibility of training intelligent vehicles using the same methods as ChatGPT and the reflection of the intelligence of intelligent vehicles in the context of human-machine shared control. In conclusion, this letter presents a preliminary exploration of the potential of ChatGPT for intelligent vehicle research, from an IEEE TIV perspective, acknowledging the limitations and uncertainties of this emerging technology.
Authors
- Xiaoxiang Na (ORCID: https://orcid.org/0000-0002-6524-7122)
- Peijun Ye (ORCID: https://orcid.org/0000-0001-9987-9016)
- Chao Gou (ORCID: https://orcid.org/0000-0002-4128-886X)
- Guiyang Luo (ORCID: https://orcid.org/0000-0002-1912-8536)
- Siyu Teng (ORCID: https://orcid.org/0000-0002-6860-9547)
- Haiping Du (ORCID: https://orcid.org/0000-0002-3439-3821)
- Jiaqi Ma (ORCID: https://orcid.org/0000-0002-8184-5157)
- Hong Chen (ORCID: https://orcid.org/0000-0002-1724-8649)
- Hui Zhang (ORCID: https://orcid.org/0000-0001-7267-5179)
- Siji Ma (ORCID: https://orcid.org/0009-0005-2776-7943)
- Bai Li (ORCID: https://orcid.org/0000-0002-8966-8992)
- Xiao Wang (ORCID: https://orcid.org/0000-0002-0008-0659)
- Fei‐Yue Wang (ORCID: https://orcid.org/0000-0001-9185-3989)
- Qinghai Miao
Institutions
- Macau University of Science and Technology (MO)
- Tongji University (CN)
- Beijing University of Posts and Telecommunications (CN)
- Hong Kong Baptist University (HK)
- Anhui University (CN)
- Sun Yat-sen University (CN)
- University of California, Los Angeles (US)
- Hunan University (CN)
- Chinese Academy of Sciences (CN)
- University of Wollongong (AU)
- Beijing Jiaotong University (CN)
- University of Cambridge (GB)
- Beijing Academy of Artificial Intelligence (CN)
- Samueli Institute (US)
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- IEEE Transactions on Intelligent Vehicles
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1109/tiv.2024.3502095
- Citations
- 1
- Primary Topic
- Adversarial Robustness in Machine Learning
- Type
- article
- Field-Weighted Citation Impact
- 0.35