Identification of Objects in Autonomous Vehicles

R. Tejaswi, K. Navya, D. Bhavya Sree, C. Sarika Reddy, C. Anitha

2025

Abstract

In order to keep tabs on obstacles, people, autos, and traffic signs in real time, autonomous vehicles rely on object detecting systems. In this study, we look at the potential benefits of YOLO v11, a real-time object detection method that has recently been enhanced, for autonomous driving systems. YOLO v11's enhanced architectures, feature extraction networks, and detecting heads allow for faster and more accurate object recognition. Apt for use in mission-critical settings, the model swiftly processes high-resolution images. When it comes to low-light and bad-weather object detection, YOLO v11 shines after extensive training on huge datasets like KITTI and BDD100K. Autonomous vehicle sensor fusion and real-time decision-making modules are also integrated into YOLO v11 in this study. The reliability and security of autonomous driving are enhanced by better detection accuracy, processing efficiency, and resilience.

Paper Citation

in Harvard Style

Tejaswi R., Navya K., Sree D., Reddy C. and Anitha C. (2025). Identification of Objects in Autonomous Vehicles. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 224-229. DOI: 10.5220/0013895800004919

in Bibtex Style

@conference{icrdicct`2525,
author={R. Tejaswi and K. Navya and D. Sree and C. Reddy and C. Anitha},
title={Identification of Objects in Autonomous Vehicles},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={224-229},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013895800004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - Identification of Objects in Autonomous Vehicles
SN - 978-989-758-777-1
AU - Tejaswi R.
AU - Navya K.
AU - Sree D.
AU - Reddy C.
AU - Anitha C.
PY - 2025
SP - 224
EP - 229
DO - 10.5220/0013895800004919
PB - SciTePress