International Journal of Innovative Research in Computer and Communication Engineering
ISSN Approved Journal | Impact factor: 8.771 | ESTD: 2013 | Follows UGC CARE Journal Norms and Guidelines
| Monthly, Peer-Reviewed, Refereed, Scholarly, Multidisciplinary and Open Access Journal | High Impact Factor 8.771 (Calculated by Google Scholar and Semantic Scholar | AI-Powered Research Tool | Indexing in all Major Database & Metadata, Citation Generator | Digital Object Identifier (DOI) |
| TITLE | Advancing Autonomous Vehicle Safety: An Arduino-Based Intelligent Navigation System with Real-Time Object Detection and Sensor Fusion |
|---|---|
| ABSTRACT | The demand for intelligent transportation continues growing worldwide, yet affordable autonomous platforms remain scarce. We developed a cost-effective self-driving vehicle using Arduino microcontroller technology, integrating computer vision with multi-modal sensors to enable safe navigation. Our implementation leverages YOLO deep learning for real-time identification of diverse road elements—traffic signs, signals, surface hazards, pedestrians, animals, and vehicles. Infrared sensors maintain lane positioning while ultrasonic transducers prevent collisions. Through strategic hardware-software integration, we establish that resource-limited embedded systems can execute fundamental autonomous functions effectively. Experimental validation across varied scenarios demonstrates reliable detection performance and responsive navigation, providing researchers and educators with a viable foundation for small-scale intelligent vehicle development. |
| AUTHOR | BHUVAN P H, YADHUKRISHNA M R, MANU V, NAGSHARAN L GOWDA, NAVEEN HANUMANT HANSANOOR Department of Information Science and Engineering, The Oxford College of Engineering Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India |
| VOLUME | 177 |
| DOI | DOI: 10.15680/IJIRCCE.2025.1312134 |
| pdf/134_Advancing Autonomous Vehicle Safety An Arduino-Based Intelligent Navigation System with Real-Time Object Detection and Sensor Fusion.pdf | |
| KEYWORDS | |
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