Understanding the Accuracy and Reliability of Predicting Orientation of Cars in Autonomous Driving System

Agashe, Harshal (2023) Understanding the Accuracy and Reliability of Predicting Orientation of Cars in Autonomous Driving System. Masters thesis, Dublin, National College of Ireland.

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Abstract

Autonomous driving systems revolutionize transportation but face critical challenges in accurately interpreting their surroundings. A fundamental challenge is the precise determination of the orientation of surrounding vehicles, essential for collision avoidance and traffic flow optimization. This thesis addresses this challenge by investigating the effectiveness of the YOLOv8 model, a cutting-edge deep learning algorithm, in predicting vehicle orientations in varied autonomous driving scenarios. The research evaluates the model’s performance in diverse environmental and traffic conditions, focusing on its accuracy and reliability. Using a comprehensive dataset from autonomous driving systems, the study conducts a thorough analysis of the YOLOv8 model, examining its capability to process and interpret complex image data. The findings aim to enhance understanding of the model’s strengths and limitations in real-world applications, offering valuable insights for the development of more robust and efficient autonomous driving technologies. This work not only contributes to the field of autonomous vehicle research but also provides a framework for future advancements in vehicle orientation prediction, a critical component for the safety and efficacy of autonomous transportation systems.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Sahani, Anu UNSPECIFIED
Uncontrolled Keywords:	You Only Look Once (YOLO)
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > TL Motor vehicles. Aeronautics. Astronautics Q Science > Q Science (General) > Self-organizing systems. Conscious automata > Machine learning H Social Sciences > HD Industries. Land use. Labor > Specific Industries > Motor Industry
Divisions:	School of Computing > Master of Science in Data Analytics
Depositing User:	Ciara O'Brien
Date Deposited:	29 Apr 2025 16:57
Last Modified:	06 May 2025 13:35
URI:	https://norma.ncirl.ie/id/eprint/7485

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