Advanced Drivers Assistant Systems in Automation
Identifieur interne : 002762 ( Istex/Corpus ); précédent : 002761; suivant : 002763Advanced Drivers Assistant Systems in Automation
Auteurs : Caterina Caleefato ; Roberto Montanari ; Fabio TangoSource :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: One of the current research areas in automotive field is aimed at improving driving safety with regards to the development of preventive support systems, also called ADAS (Advanced Driver Assistance Systems). These systems are able to detect a critical situation and to inform timely the driver, so that a repairing maneuver can be performed. From the human factors point of view, driving is considered as a complex cognitive task that can be summarized by four main sub-processes: perception, analysis, decision and action . To be performed, each phase presumes the achievement of the previous one, An exception occurs when humans overcome planning / decision phase and go directly from analysis / interpretation to action / execution (almost in automatic way). This paper intends to propose, following the main literature on human-centered automation, how the ADAS intervention can be designed without negative impact on driving safety. In particular, a forward collision warning has been studied. For this study, the Levels Of Automation (LOA) classified by Parasuramam and Sheridan (2000) has been used as well as the studies in the domain of the so-called Adaptive Automation (AA) (Kaber Riley, Endsley 2001; Scerbo 1996), that allow to adapt the information to the driver’s workload and to the context level of dangerousness.
Url:
DOI: 10.1007/978-3-540-73107-8_85
Links to Exploration step
ISTEX:6B02D3AA907F5F7FC74A9339DCCF5F326D168DA5Le document en format XML
<record><TEI wicri:istexFullTextTei="biblStruct"><teiHeader><fileDesc><titleStmt><title xml:lang="en">Advanced Drivers Assistant Systems in Automation</title><author><name sortKey="Caleefato, Caterina" sort="Caleefato, Caterina" uniqKey="Caleefato C" first="Caterina" last="Caleefato">Caterina Caleefato</name><affiliation><mods:affiliation>University of Turin, Department of Computer Sciences, Corso Svizzera 185 - 10149, Torino (Italy)</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: calefato@di.unito.it</mods:affiliation></affiliation></author><author><name sortKey="Montanari, Roberto" sort="Montanari, Roberto" uniqKey="Montanari R" first="Roberto" last="Montanari">Roberto Montanari</name><affiliation><mods:affiliation>University of Modena and Reggio Emilia, Department of Science and Methods of Engineering, Via Amendola 2, Padiglione Tamburini, 42100 Reggio Emilia, Italy</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: montanari.roberto@unimore.it</mods:affiliation></affiliation></author><author><name sortKey="Tango, Fabio" sort="Tango, Fabio" uniqKey="Tango F" first="Fabio" last="Tango">Fabio Tango</name><affiliation><mods:affiliation>Centro Ricerche Fiat, Department of Advanced Safety, Strada Torino 50, 10043, Orbassano, Italy</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: fabio.tango@crf.it</mods:affiliation></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">ISTEX</idno><idno type="RBID">ISTEX:6B02D3AA907F5F7FC74A9339DCCF5F326D168DA5</idno><date when="2007" year="2007">2007</date><idno type="doi">10.1007/978-3-540-73107-8_85</idno><idno type="url">https://api.istex.fr/document/6B02D3AA907F5F7FC74A9339DCCF5F326D168DA5/fulltext/pdf</idno><idno type="wicri:Area/Istex/Corpus">002762</idno></publicationStmt><sourceDesc><biblStruct><analytic><title level="a" type="main" xml:lang="en">Advanced Drivers Assistant Systems in Automation</title><author><name sortKey="Caleefato, Caterina" sort="Caleefato, Caterina" uniqKey="Caleefato C" first="Caterina" last="Caleefato">Caterina Caleefato</name><affiliation><mods:affiliation>University of Turin, Department of Computer Sciences, Corso Svizzera 185 - 10149, Torino (Italy)</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: calefato@di.unito.it</mods:affiliation></affiliation></author><author><name sortKey="Montanari, Roberto" sort="Montanari, Roberto" uniqKey="Montanari R" first="Roberto" last="Montanari">Roberto Montanari</name><affiliation><mods:affiliation>University of Modena and Reggio Emilia, Department of Science and Methods of Engineering, Via Amendola 2, Padiglione Tamburini, 42100 Reggio Emilia, Italy</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: montanari.roberto@unimore.it</mods:affiliation></affiliation></author><author><name sortKey="Tango, Fabio" sort="Tango, Fabio" uniqKey="Tango F" first="Fabio" last="Tango">Fabio Tango</name><affiliation><mods:affiliation>Centro Ricerche Fiat, Department of Advanced Safety, Strada Torino 50, 10043, Orbassano, Italy</mods:affiliation></affiliation><affiliation><mods:affiliation>E-mail: fabio.tango@crf.it</mods:affiliation></affiliation></author></analytic><monogr></monogr><series><title level="s">Lecture Notes in Computer Science</title><imprint><date>2007</date></imprint><idno type="ISSN">0302-9743</idno><idno type="eISSN">1611-3349</idno><idno type="ISSN">0302-9743</idno></series><idno type="istex">6B02D3AA907F5F7FC74A9339DCCF5F326D168DA5</idno><idno type="DOI">10.1007/978-3-540-73107-8_85</idno><idno type="ChapterID">85</idno><idno type="ChapterID">Chap85</idno></biblStruct></sourceDesc><seriesStmt><idno type="ISSN">0302-9743</idno></seriesStmt></fileDesc><profileDesc><textClass></textClass><langUsage><language ident="en">en</language></langUsage></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Abstract: One of the current research areas in automotive field is aimed at improving driving safety with regards to the development of preventive support systems, also called ADAS (Advanced Driver Assistance Systems). These systems are able to detect a critical situation and to inform timely the driver, so that a repairing maneuver can be performed. From the human factors point of view, driving is considered as a complex cognitive task that can be summarized by four main sub-processes: perception, analysis, decision and action . To be performed, each phase presumes the achievement of the previous one, An exception occurs when humans overcome planning / decision phase and go directly from analysis / interpretation to action / execution (almost in automatic way). This paper intends to propose, following the main literature on human-centered automation, how the ADAS intervention can be designed without negative impact on driving safety. In particular, a forward collision warning has been studied. For this study, the Levels Of Automation (LOA) classified by Parasuramam and Sheridan (2000) has been used as well as the studies in the domain of the so-called Adaptive Automation (AA) (Kaber Riley, Endsley 2001; Scerbo 1996), that allow to adapt the information to the driver’s workload and to the context level of dangerousness.</div></front></TEI><istex><corpusName>springer</corpusName><author><json:item><name>Caterina Caleefato</name><affiliations><json:string>University of Turin, Department of Computer Sciences, Corso Svizzera 185 - 10149, Torino (Italy),</json:string><json:string>E-mail: calefato@di.unito.it</json:string></affiliations></json:item><json:item><name>Roberto Montanari</name><affiliations><json:string>University of Modena and Reggio Emilia, Department of Science and Methods of Engineering, Via Amendola 2, Padiglione Tamburini, 42100 Reggio Emilia, Italy</json:string><json:string>E-mail: montanari.roberto@unimore.it</json:string></affiliations></json:item><json:item><name>Fabio Tango</name><affiliations><json:string>Centro Ricerche Fiat, Department of Advanced Safety, Strada Torino 50, 10043, Orbassano, Italy</json:string><json:string>E-mail: fabio.tango@crf.it</json:string></affiliations></json:item></author><language><json:string>eng</json:string></language><abstract>Abstract: One of the current research areas in automotive field is aimed at improving driving safety with regards to the development of preventive support systems, also called ADAS (Advanced Driver Assistance Systems). 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These systems are able to detect a critical situation and to inform timely the driver, so that a repairing maneuver can be performed. From the human factors point of view, driving is considered as a complex cognitive task that can be summarized by four main sub-processes: perception, analysis, decision and action . To be performed, each phase presumes the achievement of the previous one, An exception occurs when humans overcome planning / decision phase and go directly from analysis / interpretation to action / execution (almost in automatic way). This paper intends to propose, following the main literature on human-centered automation, how the ADAS intervention can be designed without negative impact on driving safety. In particular, a forward collision warning has been studied. 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These systems are able to detect a critical situation and to inform timely the driver, so that a repairing maneuver can be performed. From the human factors point of view, driving is considered as a complex cognitive task that can be summarized by four main sub-processes: perception, analysis, decision and action . To be performed, each phase presumes the achievement of the previous one, An exception occurs when humans overcome planning / decision phase and go directly from analysis / interpretation to action / execution (almost in automatic way). This paper intends to propose, following the main literature on human-centered automation, how the ADAS intervention can be designed without negative impact on driving safety. In particular, a forward collision warning has been studied. For this study, the Levels Of Automation (LOA) classified by Parasuramam and Sheridan (2000) has been used as well as the studies in the domain of the so-called Adaptive Automation (AA) (Kaber Riley, Endsley 2001; Scerbo 1996), that allow to adapt the information to the driver’s workload and to the context level of dangerousness.</Para></Abstract></ChapterHeader><NoBody></NoBody></Chapter></Part></Book></Series></Publisher></istex:document></istex:metadataXml><mods version="3.6"><titleInfo lang="en"><title>Advanced Drivers Assistant Systems in Automation</title></titleInfo><titleInfo type="alternative" contentType="CDATA" lang="en"><title>Advanced Drivers Assistant Systems in Automation</title></titleInfo><name type="personal"><namePart type="given">Caterina</namePart><namePart type="family">Caleefato</namePart><affiliation>University of Turin, Department of Computer Sciences, Corso Svizzera 185 - 10149, Torino (Italy)</affiliation><affiliation>E-mail: calefato@di.unito.it</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Roberto</namePart><namePart type="family">Montanari</namePart><affiliation>University of Modena and Reggio Emilia, Department of Science and Methods of Engineering, Via Amendola 2, Padiglione Tamburini, 42100 Reggio Emilia, Italy</affiliation><affiliation>E-mail: montanari.roberto@unimore.it</affiliation><role><roleTerm type="text">author</roleTerm></role></name><name type="personal"><namePart type="given">Fabio</namePart><namePart type="family">Tango</namePart><affiliation>Centro Ricerche Fiat, Department of Advanced Safety, Strada Torino 50, 10043, Orbassano, Italy</affiliation><affiliation>E-mail: fabio.tango@crf.it</affiliation><role><roleTerm type="text">author</roleTerm></role></name><typeOfResource>text</typeOfResource><genre type="conference [eBooks]" displayLabel="OriginalPaper"></genre><originInfo><publisher>Springer Berlin Heidelberg</publisher><place><placeTerm type="text">Berlin, Heidelberg</placeTerm></place><dateIssued encoding="w3cdtf">2007</dateIssued><copyrightDate encoding="w3cdtf">2007</copyrightDate></originInfo><language><languageTerm type="code" authority="rfc3066">en</languageTerm><languageTerm type="code" authority="iso639-2b">eng</languageTerm></language><physicalDescription><internetMediaType>text/html</internetMediaType></physicalDescription><abstract lang="en">Abstract: One of the current research areas in automotive field is aimed at improving driving safety with regards to the development of preventive support systems, also called ADAS (Advanced Driver Assistance Systems). These systems are able to detect a critical situation and to inform timely the driver, so that a repairing maneuver can be performed. From the human factors point of view, driving is considered as a complex cognitive task that can be summarized by four main sub-processes: perception, analysis, decision and action . To be performed, each phase presumes the achievement of the previous one, An exception occurs when humans overcome planning / decision phase and go directly from analysis / interpretation to action / execution (almost in automatic way). This paper intends to propose, following the main literature on human-centered automation, how the ADAS intervention can be designed without negative impact on driving safety. In particular, a forward collision warning has been studied. For this study, the Levels Of Automation (LOA) classified by Parasuramam and Sheridan (2000) has been used as well as the studies in the domain of the so-called Adaptive Automation (AA) (Kaber Riley, Endsley 2001; Scerbo 1996), that allow to adapt the information to the driver’s workload and to the context level of dangerousness.</abstract><relatedItem type="host"><titleInfo><title>Human-Computer Interaction. 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