On Driver Behavior Recognition for Increased Safety: A Roadmap

Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and co...
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Autor*in:	Luca Davoli [verfasserIn] Marco Martalò [verfasserIn] Antonio Cilfone [verfasserIn] Laura Belli [verfasserIn] Gianluigi Ferrari [verfasserIn] Roberta Presta [verfasserIn] Roberto Montanari [verfasserIn] Maura Mengoni [verfasserIn] Luca Giraldi [verfasserIn] Elvio G. Amparore [verfasserIn] Marco Botta [verfasserIn] Idilio Drago [verfasserIn] Giuseppe Carbonara [verfasserIn] Andrea Castellano [verfasserIn] Johan Plomp [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	Advanced Driver-Assistance System (ADAS) driver safety and comfort emotion recognition Artificial Intelligence (AI) Driver Complex State (DCS)

Übergeordnetes Werk:	In: Safety - MDPI AG, 2016, 6(2020), 4, p 55
Übergeordnetes Werk:	volume:6 ; year:2020 ; number:4, p 55

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3390/safety6040055

Katalog-ID:	DOAJ052846407

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topic_facet	Advanced Driver-Assistance System (ADAS) driver safety and comfort emotion recognition Artificial Intelligence (AI) Driver Complex State (DCS) Industrial safety. Industrial accident prevention Medicine (General)
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authorswithroles_txt_mv	Luca Davoli @@aut@@ Marco Martalò @@aut@@ Antonio Cilfone @@aut@@ Laura Belli @@aut@@ Gianluigi Ferrari @@aut@@ Roberta Presta @@aut@@ Roberto Montanari @@aut@@ Maura Mengoni @@aut@@ Luca Giraldi @@aut@@ Elvio G. Amparore @@aut@@ Marco Botta @@aut@@ Idilio Drago @@aut@@ Giuseppe Carbonara @@aut@@ Andrea Castellano @@aut@@ Johan Plomp @@aut@@
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callnumber-first	T - Technology
author	Luca Davoli
spellingShingle	Luca Davoli misc T55-55.3 misc R5-920 misc Advanced Driver-Assistance System (ADAS) misc driver safety and comfort misc emotion recognition misc Artificial Intelligence (AI) misc Driver Complex State (DCS) misc Industrial safety. Industrial accident prevention misc Medicine (General) On Driver Behavior Recognition for Increased Safety: A Roadmap
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topic_title	T55-55.3 R5-920 On Driver Behavior Recognition for Increased Safety: A Roadmap Advanced Driver-Assistance System (ADAS) driver safety and comfort emotion recognition Artificial Intelligence (AI) Driver Complex State (DCS)
topic	misc T55-55.3 misc R5-920 misc Advanced Driver-Assistance System (ADAS) misc driver safety and comfort misc emotion recognition misc Artificial Intelligence (AI) misc Driver Complex State (DCS) misc Industrial safety. Industrial accident prevention misc Medicine (General)
topic_unstemmed	misc T55-55.3 misc R5-920 misc Advanced Driver-Assistance System (ADAS) misc driver safety and comfort misc emotion recognition misc Artificial Intelligence (AI) misc Driver Complex State (DCS) misc Industrial safety. Industrial accident prevention misc Medicine (General)
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title	On Driver Behavior Recognition for Increased Safety: A Roadmap
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title_sort	on driver behavior recognition for increased safety: a roadmap
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title_auth	On Driver Behavior Recognition for Increased Safety: A Roadmap
abstract	Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.
abstractGer	Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.
abstract_unstemmed	Advanced Driver-Assistance Systems (ADASs) are used for increasing safety in the automotive domain, yet current ADASs notably operate without taking into account drivers’ states, e.g., whether she/he is emotionally apt to drive. In this paper, we first review the state-of-the-art of emotional and cognitive analysis for ADAS: we consider psychological models, the sensors needed for capturing physiological signals, and the typical algorithms used for human emotion classification. Our investigation highlights a lack of advanced Driver Monitoring Systems (DMSs) for ADASs, which could increase driving quality and security for both drivers and passengers. We then provide our view on a novel perception architecture for driver monitoring, built around the concept of Driver Complex State (DCS). DCS relies on multiple non-obtrusive sensors and Artificial Intelligence (AI) for uncovering the driver state and uses it to implement innovative Human–Machine Interface (HMI) functionalities. This concept will be implemented and validated in the recently EU-funded NextPerception project, which is briefly introduced.
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container_issue	4, p 55
title_short	On Driver Behavior Recognition for Increased Safety: A Roadmap
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