Research on Application of Deep Learning in Optimizing the Performance of Autonomous Vehicles

Linfeng Hao

European Journal of Engineering and Technologies, 2025, vol. 1, issue 1, 25-31

Abstract: With the rapid progress of automatic driving technology, deep learning has received extensive attention in the performance optimization of autonomous vehicles. With its excellent data processing and pattern recognition functions, deep learning has enhanced the perception accuracy, real-time response ability, security and positioning accuracy of the auto drive system. This study explores the practical application of deep learning in autonomous vehicles and provides a detailed analysis of optimization strategies in areas such as image processing, vehicle road collaboration, multi task learning, and global path planning. Aiming at the problems existing in the current auto drive system in terms of insufficient perception accuracy, low real-time performance, and poor positioning accuracy, a series of improvement measures based on deep learning are proposed to improve the overall operation performance of the system and ensure driving safety.

Keywords: deep learning; autonomous driving; performance optimization; image processing; vehicle road collaboration (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://pinnaclepubs.com/index.php/EJET/article/view/121/123 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:dba:ejetaa:v:1:y:2025:i:1:p:25-31

Access Statistics for this article

More articles in European Journal of Engineering and Technologies from Pinnacle Academic Press
Bibliographic data for series maintained by Joseph Clark ().