Fatigue Driving Warning Internet System of Vehicles Based on Trajectory and Facial Feature Fusion

Zihan Li, Siqi Yang, Teng Zhou

2024

Abstract

Fatigue driving is one of the common factors leading to traffic accidents. To mitigate its risks, this study proposes a vehicle network-based warning system for detecting fatigue driving through information fusion and develops a corresponding simulation prototype. First, the drivers' facial images and vehicle trajectory data are pre-processed to enhance model training accuracy. Then, a detection framework based on ResNet50 is constructed to integrate and analyze the facial features of drivers and vehicle trajectories for identifying fatigue driving behavior. Finally, the architecture of the vehicle network early warning system is designed to utilize the identification results. Once signs of fatigued driving are detected, the system will automatically issue an alert to help drivers prevent accidents caused by drowsy driving, ensuring road and driver safety. The code for the system part can be found at https://github.com/Theo-teng/Internet-of-Vehicles-Simulation.git.

Paper Citation

in Harvard Style

Li Z., Yang S. and Zhou T. (2024). Fatigue Driving Warning Internet System of Vehicles Based on Trajectory and Facial Feature Fusion. In Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML; ISBN 978-989-758-754-2, SciTePress, pages 412-417. DOI: 10.5220/0013525100004619

in Bibtex Style

@conference{daml24,
author={Zihan Li and Siqi Yang and Teng Zhou},
title={Fatigue Driving Warning Internet System of Vehicles Based on Trajectory and Facial Feature Fusion},
booktitle={Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML},
year={2024},
pages={412-417},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013525100004619},
isbn={978-989-758-754-2},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Analysis and Machine Learning - Volume 1: DAML
TI - Fatigue Driving Warning Internet System of Vehicles Based on Trajectory and Facial Feature Fusion
SN - 978-989-758-754-2
AU - Li Z.
AU - Yang S.
AU - Zhou T.
PY - 2024
SP - 412
EP - 417
DO - 10.5220/0013525100004619
PB - SciTePress