ADVANCED AUTONOMOUS VEHICLE SYSTEM USING BEHAVIOUR CLONING FOR PATH OPTIMISATION

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Patel Muhammad; Amar Kumar; Ganesh; Rishabh Singh; Dr. Gousia Thaniyath

ADVANCED AUTONOMOUS VEHICLE SYSTEM USING BEHAVIOUR CLONING FOR PATH OPTIMISATION

Authors: Patel Muhammad, Amar Kumar, Ganesh, Rishabh Singh, Dr. Gousia Thaniyath

Unique Paper ID: 179494
Volume: 11
Issue: 12
PageNo: 7601-7606

Keywords: No Keywords Found

Abstract:
This paper presents an autonomous driving system developed using computer vision techniques and AI algorithms. The system focuses on real-time lane detection and path planning by leveraging image processing, convolutional neural networks (CNNs), and behavior cloning to mimic human driving behavior. The methodology includes data acquisition using the Udacity self-driving car simulator, preprocessing of captured images, training a CNN model, and testing in a simulated environment. The system's performance is evaluated based on its ability to navigate autonomously in various simulated road scenarios, demonstrating lane-keeping accuracy and effective replication of human driving behavior. The project's industry relevance lies in its cost-efficient, camera-only approach, making it adaptable for ADAS, robotics, and smart mobility solutions.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 7601-7606

ADVANCED AUTONOMOUS VEHICLE SYSTEM USING BEHAVIOUR CLONING FOR PATH OPTIMISATION

Available:https://ijirt.org/article?manuscript=179494

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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