Controlling safety-critical systems often includes several monitoring tasks to observe the current system state and to predict future system states that might affect the controlling activities.

Methods to get insights about users’ monitoring behavior either depend on the expertise of Human factor experts to model and predict stereotypic monitoring behavior or on performing eye tracking studies in simulated environments, which require subjects to be physically present and usually to be tested successively.

The Human Efficiency Evaluator (HEE) supports subject matter experts (SMEs), such as HMI designers and domain experts with no background in cognitive modeling to generate and benefit from attention predictions. With the HEE predictions can be performed by a cognitive human operator simulation in a very early design phase where only HMI design images or sketches of future interfaces are available. The HEE uses the Adaptive Information Expectancy model (AIE model) [Wortelen, 2013], which is based on the SEEV model [Wickens, 2003] and is a dynamic simulation model of attention distribution.

Monitoring in the Maritime Domain

A ship bridge is an example for such a safety-critical system. Modern bridge systems offer a broad range of automation of routine tasks and most of the navigation decisions (passage planning for instance) can be performed prior to the voyage. Therefore most of the time on a ship bridge is spent on the navigation monitoring task. This includes observing the ships status, its navigation path and watching out for future events that require adjusting the planned route of the vessel’s by changing its speed and heading to prevent dangerous situations.

Heatmap of an attention prediction in the maritime domain

Heatmap of an attention prediction in the maritime domain

Studies show that in between 75%-80% of accidents in ship navigation happen because the human operator had not access to information that could have prevented the accident [IMO,1999]. A study that investigated the lack of situation awareness of mariners revealed the importance of situation awareness for the decision making process in the maritime domain. From the 177 maritime accident reports analyzed, 71% percent of the human errors were situation awareness related. 58.5% of those could be classified as caused by failures in correctly perceiving information [Grech, 2002]. These types of failures are caused by data not being available, data not being easy to discriminate, misperceptions or failures in monitoring or observing data [Grech, 2002].

Publications

  • [PDF] [ppt] [DOI] S. Feuerstack and B. Wortelen, “Revealing Differences in Designers’ and User’s Perspectives: A Tool-supported Process for Visual Attention Prediction for Designing HMIs for Martime Monitoring Tasks,” in 15th IFIP TC 13 International Conference, Bamberg, Germany, September 14-18, 2015, Proceedings, Part IV, 2015, p. Pages 105-122.
    [Bibtex]
    @INPROCEEDINGS{Feuerstack2015c,
    author = {Sebastian Feuerstack and Bertram Wortelen},
    title = {Revealing Differences in Designers' and User's Perspectives: A Tool-supported
    Process for Visual Attention Prediction for Designing HMIs for Martime
    Monitoring Tasks},
    booktitle = {15th IFIP TC 13 International Conference, Bamberg, Germany, September
    14-18, 2015, Proceedings, Part IV},
    year = {2015},
    editor = {Abascal, J., Barbosa, S., Fetter, M., Gross, T., Palanque, P., Winckler,
    M.},
    volume = {LNCS},
    number = {9299},
    pages = {Pages 105-122},
    note = {ISBN 978-3-319-22722-1},
    comment = {HF},
    doi = {10.1007/978-3-319-22723-8},
    file = {Feuerstack2015c.pdf:Feuerstack2015c.pdf:PDF},
    owner = {sfeuer},
    timestamp = {2015.09.21}
    }
  • [PDF] S. Feuerstack and B. Wortelen, “A Model-driven Tool for getting Insights into Car Drivers’ Monitoring Behavior,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV’17), 2017, p. pp.861-868.
    [Bibtex]
    @InProceedings{Feuerstack2017,
    author = {Sebastian Feuerstack and Bertram Wortelen},
    title = {A Model-driven Tool for getting Insights into Car Drivers’ Monitoring Behavior},
    booktitle = {Proceedings of the IEEE Intelligent Vehicles Symposium (IV'17)},
    year = {2017},
    pages = {pp.861-868},
    month = {06},
    organization = {IEEE},
    owner = {sfeu},
    timestamp = {2017.04.01},
    }
  • S. Feuerstack and B. Wortelen, “The Human Efficiency Evaluator – A tool to predict and analyse monitoring behaviour; Kognitive Systeme,” in 6. Interdisziplinäre Workshop Kognitive Systeme: Mensch, Teams, Systeme und Automaten Verstehen, Beschreiben und Gestalten Kognitiver (Technischer) Systeme, Munich, 2017.
    [Bibtex]
    @INPROCEEDINGS{Feuerstack2017a,
    author = {Sebastian Feuerstack and Bertram Wortelen},
    title = {The Human Efficiency Evaluator - A tool to predict and analyse monitoring
    behaviour; Kognitive Systeme},
    booktitle = {6. Interdisziplinäre Workshop Kognitive Systeme: Mensch, Teams, Systeme
    und Automaten Verstehen, Beschreiben und Gestalten Kognitiver (Technischer)
    Systeme},
    year = {2017},
    address = {Munich},
    owner = {sfeu},
    timestamp = {2017.05.06}
    }
  • [PDF] [ppt] S. Feuerstack, B. Wortelen, C. Kettwich, and A. Schieben, “Theater-system Technique and Model-based Attention Prediction for the Early Automotive HMI Design Evaluation,” in Proceedings of the 8th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, 2016.
    [Bibtex]
    @INPROCEEDINGS{Feuerstack2016b,
    author = {Sebastian Feuerstack and Bertram Wortelen and Carmen Kettwich and
    Anna Schieben},
    title = {Theater-system Technique and Model-based Attention Prediction for
    the Early Automotive HMI Design Evaluation},
    booktitle = {Proceedings of the 8th International Conference on Automotive User
    Interfaces and Interactive Vehicular Applications},
    year = {2016},
    file = {Feuerstack2016b.pdf:Feuerstack2016b.pdf:PDF},
    owner = {sfeuer},
    timestamp = {2016.09.06}
    }
  • B. Wortelen and S. Feuerstack, “Comparing the Input Validity of Model-based Visual Attention Predictions based on presenting Exemplary Situations either as Videos or Static Images,” in ICCM – 15th International Conference on Cognitive Modelling (in press), 2017.
    [Bibtex]
    @INPROCEEDINGS{Wortelen2017,
    author = {Bertram Wortelen and Sebastian Feuerstack},
    title = {Comparing the Input Validity of Model-based Visual Attention Predictions
    based on presenting Exemplary Situations either as Videos or Static
    Images},
    booktitle = {ICCM - 15th International Conference on Cognitive Modelling (in press)},
    year = {2017},
    owner = {sfeu},
    timestamp = {2017.05.06}
    }
  • [PDF] [DOI] B. Wortelen and S. Feuerstack, “Tool-supported comparative visualizations to reveal the difference between what has been designed and how it is perceived for monitoring interface design,” in 2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA), 2016, pp. 192-197.
    [Bibtex]
    @INPROCEEDINGS{Wortelen2016,
    author = {B. Wortelen and S. Feuerstack},
    title = {Tool-supported comparative visualizations to reveal the difference
    between what has been designed and how it is perceived for monitoring
    interface design},
    booktitle = {2016 IEEE International Multi-Disciplinary Conference on Cognitive
    Methods in Situation Awareness and Decision Support (CogSIMA)},
    year = {2016},
    pages = {192-197},
    month = {March},
    doi = {10.1109/COGSIMA.2016.7497809},
    file = {Wortelen2016.pdf:Wortelen2016.pdf:PDF},
    keywords = {data visualisation;human computer interaction;HMI;cognitive attention
    prediction method;complex safety-critical system;interface design;operator
    attention distribution;operator visual attention;tool-supported comparative
    visualization;Computational modeling;Heating;Marine vehicles;Monitoring;Predictive
    models;Resource management;Visualization;attention allocation;interface
    design;rapid prototyping;virtual test user},
    owner = {sfeu},
    timestamp = {2016.10.07}
    }
  • [PDF] B. Wortelen, S. Feuerstack, and M. Behrendt, “Revealing Monitoring Behavior for HMI Designs is Easy with the Right Tool,” in INTERACT 2015 Adjunct Proceedings. IFIP WG 13.5 Workshop on Resilience, Reliability, Safety and Human Error in System Development, Bamberg, Germany, 2015.
    [Bibtex]
    @INPROCEEDINGS{Wortelen2015,
    author = {Bertram Wortelen and Sebastian Feuerstack and Marcus Behrendt},
    title = {Revealing Monitoring Behavior for HMI Designs is Easy with the Right
    Tool},
    booktitle = {INTERACT 2015 Adjunct Proceedings. IFIP WG 13.5 Workshop on Resilience,
    Reliability, Safety and Human Error in System Development},
    year = {2015},
    editor = {Christoph Beckmann, Tom Gross},
    address = {Bamberg, Germany},
    month = {14 September},
    publisher = {University of Bamberg Press},
    note = {ISBN 978-3-86309-352-5},
    comment = {HF},
    file = {Wortelen2015.pdf:Wortelen2015.pdf:PDF},
    owner = {sfeuer},
    timestamp = {2015.07.16},
    url = {https://opus4.kobv.de/opus4-bamberg/frontdoor/index/index/docId/25644}
    }

 Posters and Flyers

  • [PDF] S. Feuerstack and B. Wortelen, The Human Efficiency Evaluator – Flyer, 2016.
    [Bibtex]
    @MISC{Feuerstack2016,
    author = {Sebastian Feuerstack and Bertram Wortelen},
    title = {The Human Efficiency Evaluator - Flyer},
    year = {2016},
    file = {Feuerstack2016.pdf:Feuerstack2016.pdf:PDF},
    owner = {sfeuer},
    timestamp = {2016.01.11}
    }
  • [PDF] B. Wortelen and S. Feuerstack, Modeling Individual Drivers and Driver Groups with HEE, 2016.
    [Bibtex]
    @MISC{Wortelen2016b,
    author = {Bertram Wortelen and Sebastian Feuerstack},
    title = {Modeling Individual Drivers and Driver Groups with HEE},
    howpublished = {Poster for Interdisciplinary Research Center on Critical Systems
    Engineering for Socio-Technical Systems (CSE)},
    month = {January},
    year = {2016},
    file = {Wortelen2016b.pdf:Wortelen2016b.pdf:PDF},
    institution = {OFFIS e.V.},
    owner = {sfeuer},
    timestamp = {2016.01.11}
    }

References

[Grech, 2002] Michelle R Grech, Tim Horberry, and Andrew Smith. Human error in maritime operations: Analyses of accident reports using the leximancer tool. In Proceedings of the Human Factors and Ergonomics Society Annual Meeting, volume 46, pages 1718–1721. SAGE Publications, 2002

[IMO,1999] International Maritime Organization. Annex 24 – MCA guidance notes for voyage planning. Technical report, IMO RESOLUTION A.893(21), https://mcanet.mcga.gov.uk/public/c4/solas/solas_v/Annexes/Annex24.htm, 1999

[Wickens, 2003] Christopher D. Wickens, Juliana Goh, John Helleberg, William J. Horrey, and Donald A. Talleur. Attentional models of multitask pilot performance using advanced display technology. Human Factors, 45(3):360–380, 2003.

[Wortelen, 2013] Bertram Wortelen, Martin Baumann, and Andreas Lüdtke. Dynamic simulation and prediction of drivers’ attention distribution.Transportation Research Part F: Traffic Psychology and Behaviour, 21:278–294, 10 2013.