Model-Based validation of Driver Drowsiness Detection System for ADAS

Gargano, Ivan Enzo (2022) Model-Based validation of Driver Drowsiness Detection System for ADAS. [Laurea magistrale], Università di Bologna, Corso di Studio in Advanced automotive electronic engineering [LM-DM270]
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Abstract

The work described in this Master’s Degree thesis was born after the collaboration with the company Maserati S.p.a, an Italian luxury car maker with its headquarters located in Modena, in the heart of the Italian Motor Valley, where I worked as a stagiaire in the Virtual Engineering team between September 2021 and February 2022. This work proposes the validation using real-world ECUs of a Driver Drowsiness Detection (DDD) system prototype based on different detection methods with the goal to overcome input signal losses and system failures. Detection methods of different categories have been chosen from literature and merged with the goal of utilizing the benefits of each of them, overcoming their limitations and limiting as much as possible their degree of intrusiveness to prevent any kind of driving distraction: an image processing-based technique for human physical signals detection as well as methods based on driver-vehicle interaction are used. A Driver-In-the-Loop simulator is used to gather real data on which a Machine Learning-based algorithm will be trained and validated. These data come from the tests that the company conducts in its daily activities so confidential information about the simulator and the drivers will be omitted. Although the impact of the proposed system is not remarkable and there is still work to do in all its elements, the results indicate the main advantages of the system in terms of robustness against subsystem failures and signal losses.

Abstract
Tipologia del documento
Tesi di laurea (Laurea magistrale)
Autore della tesi
Gargano, Ivan Enzo
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Driver Drowsiness Detection,driver-in-the-loop simulator,Model-Based Design,Advanced Driver Assistance System,PERCLOS,Vehicle Lane Position,Vehicle Lateral Position,steering wheel angle,binary classification
Data di discussione della Tesi
21 Marzo 2022
URI

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