The Review of AI Efficiency in Autonomous Driving
This paper explores the impact of Artificial Intelligence (AI) on the development of autonomous driving, highlighting advancements, challenges, and future directions. The roles of adaptive learning, sensor fusion, and energy efficiency in improving vehicle autonomy are analyzed, drawing on case studies from Tesla and Waymo to illustrate real-world applications. Despite progress, issues such as data management and system integration persist. The study anticipates benefits such as enhanced safety and traffic efficiency, alongside increased adoption of autonomous vehicles. Emphasis is placed on the need for innovation, collaboration, and standardization in overcoming these challenges.
Authors
- Yue Wang
Institutions
- Shenzhen MSU-BIT University
Publication Details
- Journal
- Applied and Computational Engineering
- Published
- 2024-12-19
- DOI
- https://doi.org/10.54254/2755-2721/2024.18306
- Citations
- 1
- Primary Topic
- Impact of AI and Big Data on Business and Society
- Type
- article
- Field-Weighted Citation Impact
- 0.49