Advanced Applications of AI Technology in Automated Vehicles
- DOI
- 10.2991/978-94-6463-518-8_71How to use a DOI?
- Keywords
- AI; Automated vehicles; Automotive sector
- Abstract
Currently, driverless and artificial Intelligence (AI) technologies are both developing rapidly, and the combination of the two could be instrumental in the development of driverless cars while having great commercial value. Current research on AI focuses mainly on algorithms, and there is still less integration with actual machinery and facilities. The application of AI to drones is promising, but the technology for the public is still at a low level. This paper summarizes the existing applications of AI in unmanned vehicles and analyses the problems of AI when algorithmic development reaches its limits. Finally, it gives a method to promote the combination of the two technologies. This paper summarizes the existing applications of AI in unmanned vehicles by suggesting that AI has a wide range of applications in unmanned vehicles. In further development, in addition to the improvement of technology, it is also very important for the popularization of the technology. This research can give a boost to the future development of AI applications in drones.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Yushi Shen PY - 2024 DA - 2024/09/28 TI - Advanced Applications of AI Technology in Automated Vehicles BT - Proceedings of the 2024 International Conference on Mechanics, Electronics Engineering and Automation (ICMEEA 2024) PB - Atlantis Press SP - 743 EP - 749 SN - 2352-5401 UR - https://doi.org/10.2991/978-94-6463-518-8_71 DO - 10.2991/978-94-6463-518-8_71 ID - Shen2024 ER -