Authors : Brahma Reddy Katam

Volume/Issue : Volume 9 - 2024, Issue 8 - August

Google Scholar : https://tinyurl.com/56uypc7r

Scribd : https://tinyurl.com/2c9apt5n

DOI : https://doi.org/10.38124/ijisrt/IJISRT24AUG085

Abstract : The advancement of autonomous vehicles (AVs) heavily relies on their ability to process high volumes of sensor data and make real-time decisions. This paper explores how the integration of data engineering, machine learning (ML), artificial intelligence (AI), and a cohesive hardware-software approach can further enhance the performance and safety of AVs. We propose a comprehensive framework that leverages advanced data engineering techniques for efficient data management, employs state-of-the-art ML models for accurate perception and prediction, and utilizes AI- driven strategies for decision-making and control. The proposed solutions are designed to be effective in areas with limited internet connectivity and can operate on low- powered hardware, even with outdated software.

Keywords : Autonomous Vehicles, Data Engineering, Machine Learning, Artificial Intelligence, Hardware- Software Integration.

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