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Driving Simulation in Automotive: Trouble Shooting for HMI Validation

Nicolo' Vanacore

Driving Simulation in Automotive: Trouble Shooting for HMI Validation.

Rel. Giovanni Battista Griva, Andrea Fighera, Fabrizio Picariello. Politecnico di Torino, Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica), 2022


In a world where technological development moves rapidly, people's needs move just as fast going hand in hand with it. The perennial quest and need for connection with the world has led to a disruption of development concepts, which are now based on a human-centric view. In this context, the automotive industry has greatly increased the development of new technologies in recent years. One of the central roles in this type of research is occupied by HMI teams that are precisely concerned with the development of human-machine interfaces (HMIs), trying to make the most usable and safe use of vehicle instrumentation that goes to meet the needs mentioned before. This led to the following paper, the result of a curricular internship carried out for the \textit{Politecnico di Torino} in collaboration with \textit{Maserati SPA}, at the Maserati Innovation Lab, based in Modena. The paper aims to focus on the validation process of new HMI components through user and/or expert testing, which will be handled with the use of a static driving simulator. The validation process will therefore be introduced and analyzed, initially from a general perspective, and as we go along we will provide the necessary tools for understanding the concept specific to the validation of HMI components. The static driving simulator also plays a central role in the paper, hence a range of information, useful for the reader, will be provided in order to better understand its operation and the relative potential derived from its use within a validation process. Finally, the various activities carried out to bring the driving simulator to an operational state useful for conducting an expert test will be described, the methodologies adopted and their results will be mentioned.

Relators: Giovanni Battista Griva, Andrea Fighera, Fabrizio Picariello
Academic year: 2022/23
Publication type: Electronic
Number of Pages: 71
Additional Information: Tesi secretata. Fulltext non presente
Corso di laurea: Corso di laurea magistrale in Mechatronic Engineering (Ingegneria Meccatronica)
Classe di laurea: New organization > Master science > LM-25 - AUTOMATION ENGINEERING
Aziende collaboratrici: MASERATI SPA
URI: http://webthesis.biblio.polito.it/id/eprint/25535
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