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Integrated Detection of Traffic Signs and Lane Changes Using Deep Learning for Autonomous Driving Systems

Year: 2025

Type: article

Abstract: : This research presents a modular deep learning- based pipeline designed to integrate traffic sign detection, lane segmentation, and lane change prediction for autonomous driv- ing. ThesystemutilizesYOLOv8 forobjectdetection (trafficsigns andspeedbreakers),andYOLOv8-segforlanesegmentation. A custom logic module processes lane masks for accurate lane changeprediction,whileGoogleText-to-Speech(gTTS)generates audio alerts. The pipeline supports real-time performance with GPU acceleration and processes videos offline with visual and verbalfeedback.Resultssuggesthighprecisionindetection and practical application for advanced driver assistance systems (ADAS).

Source: International Journal for Research in Applied Science and Engineering Technology

DOI: 10.22214/ijraset.2025.71655

Author: Atharav Ghadge

Language: English

Topic: Autonomous Vehicle Technology and Safety

Subfield: Automotive Engineering

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4410857475

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