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Carrino Stefano

Professeur-e HES associé-e

Compétences principales

Professeur-e HES associé-e

Téléphone: +41 32 930 26 16

Haute Ecole Arc - Ingénierie
Espace de l'Europe 11, 2000 Neuchâtel, CH

Institut
Arc-Ingénierie

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Terminés

PenurIA - L'intelligence artificielle au service de la société : opportunités, défis et risques

Rôle: Requérant(e) principal(e)

Financement: Fonds de recherche et d’impulsions (FRI) HES-SO

Description du projet :

Le recrutement de talents et la pénurie de main-d’œuvre constituent un défi majeur en Suisse. Toutefois, l’émergence des nouvelles technologies basées sur l'intelligence artificielle (IA) a le potentiel de révolutionner le marché du travail. Le projet PenurIA vise à étudier l’impact potentiel de l’IA sur la pénurie de main-d’œuvre, en particulier dans les métiers de la Supply Chain. Le projet combine des méthodes quantitatives et qualitatives afin de fournir des recommandations à court, moyen et long terme aux entreprises suisses en vue d’une intégration optimale de l’IA dans les métiers de la Supply Chain, tout en tenant compte des enjeux éthiques et sociétaux.

Equipe de recherche au sein de la HES-SO: Carrino Stefano , Doan Karine , Martinelli Aris

Durée du projet: 01.11.2024 - 30.06.2025

Montant global du projet: 79'980 CHF

Statut: Terminé

2019

Owner Manuals Review and Taxonomy of ADAS Limitations in Partially Automated Vehicles

Article scientifique

Capallera Marine, Meteier Quentin, De Salis Emmanuel, Carrino Stefano, Angelini Leonardo, Abou Khaled Omar, Mugellini Elena

AutomotiveUI '19: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2019

Lien vers la publication

Résumé:

In the context of highly automated driving, the driver has to be aware of driving risks and to take over control of the car in hazardous situations. The goal of this paper is to categorize and analyze the factors that lead to such critical scenarios. To this purpose, we analyzed limitations of Advanced Driver-Assistance Systems (ADAS) extracted from owner manuals of 12 partially automated cars available on the market. A taxonomy with 6 macro-categories and 26 micro-categories is proposed to classify and better understand the limitations of these vehicles. We also investigated if these limitations are conveyed to the driver through Human-Machine Interaction (HMI) in the car. Some suggestions are made to better communicate these limitations to the driver in order to raise his/her situation awareness.

Workshop on explainable AI in automated driving: a user-centered interaction approach

Article scientifique

Meteier Quentin, Capallera Marine, Angelini Leonardo, Mugellini Elena, Abou Khaled Omar, Carrino Stefano, De Salis Emmanuel, Stéphane Galland, Susanne Boll

AutomotiveUI '19: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Proceedings, 2019

Lien vers la publication

Résumé:

With the increasing use of automation, users tend to delegate more tasks to the machines. Such complex systems are usually developed with "black box" Artificial Intelligence (AI), which makes these systems difficult to understand for the user. This assumption is particularly true in the field of automated driving since the level of automation is constantly increasing via the use of state-of-the-art AI solutions. We believe it is important to investigate the field of Explainable AI (XAI) in the context of automated driving since interpretability and transparency are key factors for increasing trust and security. In this workshop, we aim at gathering researchers and industry practitioners from different fields to brainstorm about XAI with a special focus on human-vehicle interaction. Questions like "what kind of explanation do we need", "which is the best trade-off between performance and explainability" and "how granular should the explanations be" will be addressed in this workshop.

Réalisations

PEOPLE@HES-SO
Annuaire et Répertoire des compétences

Carrino Stefano

Professeur-e HES associé-e

Compétences principales

Machine Learning

Artificial Intelligence (AI)

Human Computer Interaction

Professeur-e HES associé-e

PEOPLE@HES-SO Annuaire et Répertoire des compétences

Carrino Stefano

Professeur-e HES associé-e

Compétences principales

Machine Learning

Artificial Intelligence (AI)

Human Computer Interaction

Professeur-e HES associé-e

PEOPLE@HES-SO
Annuaire et Répertoire des compétences