Autonomous Vehicle Navigation System using Machine Learning

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Rohit Singh; Dr. Nidhi Saxena

Autonomous Vehicle Navigation System using Machine Learning

Authors: Rohit Singh, Dr. Nidhi Saxena

Unique Paper ID: 171266
Volume: 11
Issue: 7
PageNo: 3126-3130

Keywords: Autonomous vehicles machine learning reinforcement learning neural networks navigation system sensor fusion real-time decision-making deep learning.

Abstract:
Autonomous vehicles (AVs) are rapidly evolving technologies that promise to reshape the transportation landscape by removing the need for human intervention in driving. The core challenge in autonomous driving lies in enabling the vehicle to safely navigate complex environments while processing a vast array of sensory inputs. This paper explores the use of machine learning (ML) for autonomous vehicle navigation, focusing on sensor data fusion, reinforcement learning algorithms, and neural network models for real-time decision-making. By integrating these technologies, we aim to develop a robust navigation system capable of responding to dynamic road conditions. Key experimental results demonstrate significant advancements in autonomous navigation, accuracy, and safety, presenting a potential framework for the next generation of self-driving vehicles.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 7
PageNo: 3126-3130

Autonomous Vehicle Navigation System using Machine Learning

Available:https://ijirt.org/article?manuscript=171266

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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