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Conference

Analysis, Design, and Evaluation of Human-Machine Systems 

About: Analysis, Design, and Evaluation of Human-Machine Systems is an academic conference. The conference publishes majorly in the area(s): Usability & Situation awareness. Over the lifetime, 305 publications have been published by the conference receiving 1700 citations.

Papers published on a yearly basis

Papers
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Journal ArticleDOI
01 Jan 2007
TL;DR: Issues of human trust in automation, automation surprises, responsibility and authority, and how to improve the safety and comfort of a human-machine system are discussed.
Abstract: To improve the safety and comfort of a human-machine system, the machine needs to 'know,' in a real time manner, the human operator in the system The machine's assistance to the human can be fine tuned if the machine is able to sense the human's state and intent Related to this point, this paper discusses issues of human trust in automation, automation surprises, responsibility and authority Examples are given of a driver assistance system for advanced automobile

82 citations

Journal ArticleDOI
01 Jan 2016
TL;DR: In this article, the relationship between shared control and human-machine cooperation is viewed as similar to the sharp, pointy tip and the (blunt) shaft of a spear.
Abstract: As an introduction to the session of shared and cooperative control, this article will briefly look into the history, start with definitions and sketch a common framework of shared and cooperative control that sees the two phrases not as different concepts, but as different perspectives or foci on a common design space of shared intentionality, control and cooperation between humans and machines. One working hypothesis which the session will explore is that shared control can be understood as cooperation at the control level, while human machine cooperation can include shared control, but can also extend towards cooperation at higher levels, e.g. of guidance and navigation, of maneuvers and goals. We propose to view the relationship between shared control and human-machine cooperation as being similar to the relationship between the sharp, pointy tip and the (blunt) shaft of a spear. Shared control is where cooperation comes sharply into effect at the control level, but to be truly effective it should be supported by cooperation on all levels of interaction beyond the control level, e.g. on the guidance and navigation level.

81 citations

Journal ArticleDOI
01 Jan 2013
TL;DR: This paper presents a semantic-based AR system used for the integration of the existing information and knowledge, available in CAD/PDM systems, for real-time support of the human operator in an automotive use-case.
Abstract: Augmented Reality (AR) can help close the gap between product development and manufacturing operation, mainly because of its ability to reuse and reproduce digital information and knowledge, while supporting assembly operators. This paper presents a semantic-based AR system used for the integration of the existing information and knowledge, available in CAD/PDM systems, for real-time support of the human operator. This study is supported by an algorithm used for the generation of the AR instructions based on the product and process semantics. The results are demonstrated in an automotive use-case.

50 citations

Journal ArticleDOI
01 Jan 2013
TL;DR: The main team-SA constructs are synthesized, principles of humans-machines cooperation are presented and a Common Work Space is presented as a medium that allow cooperation in order to enrich team- SA constructs.
Abstract: Especially in life-critical systems decision-making entails cognitive functions such as monitoring, as well as fault prevention and recovery. People involved in the control and management of such systems play two kinds of roles: positive thanks to their unique involvement and capacity to deal with the unexpected; and negative with their ability to make errors. But they are also able to detect and correct these mistakes and able to learn from them. Thus human-machine system designer can allow the humans an innovative behavior to be “aware” and to cope with unknown situations by enhancing Situation Awareness (SA). As humans are more and more involved in collective works the constructs of team-SA are important. But the literature shows a great variety and some incoherence in their definitions. That makes difficult to build a design methodology favoring human SA. In parallel, human machine cooperation models have been developed in the last two decades and validated in different dynamic application fields: Air Traffic Control, fighter aircraft cockpit, reconnaissance robot. These studies showed an increase of the problem solving capabilities and a decrease of workload when the tasks are performed by cooperative teams. In this paper we first synthesize main team-SA constructs, we then present principles of humans-machines cooperation and present a Common Work Space as a medium that allow cooperation. We propose to extend it in order to enrich team-SA constructs.

42 citations

Journal ArticleDOI
01 Jan 2010
TL;DR: This work demonstrates some novel visualization tools that can be used for assessing the performance of alarm systems in terms of effectively identifying nuisance alarms and their utility is illustrated using real industrial alarm data.
Abstract: Alarms are important for safe and reliable operation of a process Ideally, every alarm that is presented to the operator requires an action Owing to the ease in implementing alarms, many modern day process plants have a large number of alarms configured in their alarm system Many of these alarms are set without proper rationalization resulting in the generation of nuisance alarms During process upsets, the volume of alarms presented to the operator is often too large to facilitate appropriate and timely actions This work demonstrates some novel visualization tools that can be used for assessing the performance of alarm systems in terms of effectively identifying nuisance alarms The utility of the developed tools is illustrated using real industrial alarm data

37 citations

Performance
Metrics
No. of papers from the Conference in previous years
YearPapers
201916
201624
201380
201085
200788
20042