Vehicle and Parking Space Detection for Smart Parking Systems Using the YOLOv5 Method

Aditya Saputra, Aditya Saputra, Bernat Giawa, Bernat Giawa, Rajes Khana, Rajes Khana

2023

Abstract

The YOLOv5 network architecture has the advantage of fast and accurate object detection speed and has high real-time object detection capabilities. This research utilizes the YOLOv5 (You Only Look Once version 5) method to detect vehicles and parking spaces in a smart parking system. The main aim of this research is to increase the efficiency of parking space use. The research involved collecting and processing image data from a variety of different parking locations, which was used to train the YOLOv5 model. The proposed network is trained and evaluated on the Parking Lot dataset. The results of the YOLOv5s_Ghost experiment with a car vehicle detection confidence value of 93.0% and available space detection confidence of 94.0%. Using the best weights from YOLOv5s_Ghost increases the mean Average Precision (mAP) value to 94.9%, slightly above YOLOv5s which reaches 94.7%. The YOLOv5s_Ghost architecture shows a high level of accuracy in vehicle and parking space detection, even in various lighting conditions from morning to evening in the smart parking system. YOLOv5s_Ghost uses the GhostNet module, can be transferred to other classic models with comparable performance while reducing the number of parameters, optimizing computing resources, and increasing mAP and reducing loss.

Paper Citation

in Harvard Style

Saputra A., Giawa B. and Khana R. (2023). Vehicle and Parking Space Detection for Smart Parking Systems Using the YOLOv5 Method. In Proceedings of the 4th International Seminar and Call for Paper - Volume 1: ISCP UTA '45 JAKARTA; ISBN 978-989-758-691-0, SciTePress, pages 458-466. DOI: 10.5220/0012584700003821

in Bibtex Style

@conference{iscp uta '45 jakarta23,
author={Aditya Saputra and Bernat Giawa and Rajes Khana},
title={Vehicle and Parking Space Detection for Smart Parking Systems Using the YOLOv5 Method},
booktitle={Proceedings of the 4th International Seminar and Call for Paper - Volume 1: ISCP UTA '45 JAKARTA},
year={2023},
pages={458-466},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012584700003821},
isbn={978-989-758-691-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Seminar and Call for Paper - Volume 1: ISCP UTA '45 JAKARTA
TI - Vehicle and Parking Space Detection for Smart Parking Systems Using the YOLOv5 Method
SN - 978-989-758-691-0
AU - Saputra A.
AU - Giawa B.
AU - Khana R.
PY - 2023
SP - 458
EP - 466
DO - 10.5220/0012584700003821
PB - SciTePress