Improving autonomous vehicle automation through human-system interaction

Puertas Ramirez, David, Fernandez Matellan, Raul, Martin Gomez, David, Boticario, Jesus G. y Tena Gago, David() .Improving autonomous vehicle automation through human-system interaction. Modelling and Simulation 2023 - European Simulation and Modelling Conference 2023, ESM 2023.En: Toulouse, Francia. (2023-10-24)

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Título de la Conferencia Modelling and Simulation 2023 - European Simulation and Modelling Conference 2023, ESM 2023
Fecha de inicio de la Conferencia 2023-10-24
Fecha fín de la Conferencia 2023-10-26
Lugar de la Conferencia Toulouse, Francia
Numeros de las páginas 294-300
Titulo Improving autonomous vehicle automation through human-system interaction
Autor(es) Puertas Ramirez, David
Fernandez Matellan, Raul
Martin Gomez, David
Boticario, Jesus G.
Tena Gago, David
Materia(s) Informática
Abstract Self-driving cars (a.k.a. Autonomous Vehicles) have many challenges to tackle before having them fully deployed in our roads and cities. A critical one, which has been somehow neglected till recently, is to consider the driver in the system-user loop of vehicle performance. The purpose here is to tackle some of the current pending challenges involved in scaling up the level of autonomy of these systems. We have designed two user-vehicle experiences in two different sites with a common methodology that serves as an umbrella to collect all features required to model the driver-user. These two sites allow us to contrast and fine-tune this modelling issue. The approach consists in following a Learning Apprentice approach, where both the user behaviour and the system behaviour are learned and improved in a symbiotic ecosystem. This paper focuses on discussing the advantages of this approach and the main issues that require further research.
Palabra clave Behavioural science
Control systems
Image processing
Transportation
Model design
Human Factors
Human- Vehicle Interactions
Computer Vision
Human-centred computing
Automation
User models
User centred design
Self-driving cars
Autonomous vehicles
Machine Learning
Editor(es) EUROSIS
Formato application/pdf
Identificador bibliuned:92-Ponencias-Dpuertas-0001
http://e-spacio.uned.es/fez/view/bibliuned:92-Ponencias-Dpuertas-0001
Total de paginas 294-300
Idioma eng
Versión de la publicación publishedVersion
Nivel de acceso y licencia http://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
Tipo de recurso conferenceObject
Tipo de acceso Acceso abierto

 
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Creado: Mon, 06 May 2024, 19:07:51 CET