Paper Info
Title
On the Use of Artificial Intelligence and Sensor Fusion to Develop Accurate Eye Tracking and Driver’s Emotional State Estimation Systems
Abstract
The estimation of the driver’s emotional state is a fundamental activity to both improve the quality of driving and increase road safety. Indeed, on the one hand, the deployment of an accurate on-board measurement system for the emotional state of the driver allows the vehicle to tune some on-board settings (e.g. music, the screen brightness or the information given to the pilot). On the other hand, the estimation of the drowsiness of the pilot with such a measurement system can prevent dangerous situations by warning in advance the driver. Starting from an eye tracking system already presented in a previous article, our final project aims at merging information coming from the driver, the vehicle and the environment to properly estimate the emotional state of the driver. This paper discusses about the possibility to use Artificial Intelligence (AI) algorithms and sensor fusion to design a complete driver’s emotional and drowsiness state estimation system. The goal of the paper is twofold: firstly, this article aims at reviewing the current state-of-the-art on the field; secondly we want to outline the future improvements for our preliminary setup.
Year
DOI
Venue
2022
10.1109/MetroAutomotive54295.2022.9855021
2022 IEEE International Workshop on Metrology for Automotive (MetroAutomotive)
Keywords
DocType
ISBN
Artificial Intelligence,Machine Learning,CNN,Vision Based Measurement,Drowsiness Estimation,Eye Tracking,Computer Vision,ADAS,Driving Automation,Emotional State Estimation,Sensor Fusion,Deep Learning
Conference
978-1-6654-6690-5
Citations 
PageRank 
References 
0
0.34
19
Authors
6
Name
Order
Citations
PageRank
Tommaso Fedullo101.35
Valentina Di Pinto200.34
Alberto Morato301.35
Federico Tramarin401.35
Stefano Cattini500.34
Luigi Rovati600.68