Traffic Flow Detection and Prediction Using YOLO11: A Threshold-Based Approach for Identifying Traffic Levels

Dheeraj Maladkar, E Aditya Sai Krishna, Satwik Nayak, Swaroop N Udasi, Channabasappa Muttal

2025

Abstract

Traffic congestion is a major problem in cities, making it important to have better systems to detect and predict traffic for better traffic management. This paper gives an insight about traffic flow detection and prediction model utilizing YOLO11, an updated and advanced object detection model. The primary objective of this research is to classify traffic levels based on the threshold set, serving a systematic approach for traffic monitoring. The system uses the number of vehicles detected on each image to classify it as a heavy traffic or light traffic based on the pre-defined threshold. This approach signifies an efficient and automated model to assess the traffic conditions, which can be applied in the developing cities and further help in traffic management and intelligent transportation system. YOLO11 incorporates innovations like the C3K2 block, SPPF module, and C2PSA block for increased accuracy and speed. The YOLO11 was compared with other YOLO models such as YOLOv8,YOLOv9,YOLOv10 and the results showed that latest YOLO11 model performed best with its accurate and faster results. The results highlight the effectiveness and efficiency of the YOLO11 in detecting vehicles with 8 different classes with accurate results.

Paper Citation

in Harvard Style

Maladkar D., Sai Krishna E., Nayak S., Udasi S. and Muttal C. (2025). Traffic Flow Detection and Prediction Using YOLO11: A Threshold-Based Approach for Identifying Traffic Levels. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 335-343. DOI: 10.5220/0013592000004664

in Bibtex Style

@conference{incoft25,
author={Dheeraj Maladkar and E Aditya Sai Krishna and Satwik Nayak and Swaroop N Udasi and Channabasappa Muttal},
title={Traffic Flow Detection and Prediction Using YOLO11: A Threshold-Based Approach for Identifying Traffic Levels},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT},
year={2025},
pages={335-343},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013592000004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 2: INCOFT
TI - Traffic Flow Detection and Prediction Using YOLO11: A Threshold-Based Approach for Identifying Traffic Levels
SN - 978-989-758-763-4
AU - Maladkar D.
AU - Sai Krishna E.
AU - Nayak S.
AU - Udasi S.
AU - Muttal C.
PY - 2025
SP - 335
EP - 343
DO - 10.5220/0013592000004664
PB - SciTePress