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Thill, S., Riveiro, M., Lagerstedt, E., Lebram, M., Hemeren, P., Habibovic, A. & Klingegård, M. (2018). Driver adherence to recommendations from support systems improves if the systems explain why they are given: A simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 56, 420-435
Open this publication in new window or tab >>Driver adherence to recommendations from support systems improves if the systems explain why they are given: A simulator study
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2018 (English)In: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 56, p. 420-435Article in journal (Refereed) Published
Abstract [en]

This paper presents a large-scale simulator study on driver adherence to recommendationsgiven by driver support systems, specifically eco-driving support and navigation support.123 participants took part in this study, and drove a vehicle simulator through a pre-defined environment for a duration of approximately 10 min. Depending on the experi-mental condition, participants were either given no eco-driving recommendations, or asystem whose provided support was either basic (recommendations were given in theform of an icon displayed in a manner that simulates a heads-up display) or informative(the system additionally displayed a line of text justifying its recommendations). A naviga-tion system that likewise provided either basic or informative support, depending on thecondition, was also provided.

Effects are measured in terms of estimated simulated fuel savings as well as engine brak-ing/coasting behaviour and gear change efficiency. Results indicate improvements in allvariables. In particular, participants who had the support of an eco-driving system spenta significantly higher proportion of the time coasting. Participants also changed gears atlower engine RPM when using an eco-driving support system, and significantly more sowhen the system provided justifications. Overall, the results support the notion that pro-viding reasons why a support system puts forward a certain recommendation improvesadherence to it over mere presentation of the recommendation.

Finally, results indicate that participants’ driving style was less eco-friendly if the navi-gation system provided justifications but the eco-system did not. This may be due to par-ticipants considering the two systems as one whole rather than separate entities withindividual merits. This has implications for how to design and evaluate a given driver sup-port system since its effectiveness may depend on the performance of other systems in thevehicle.

Keywords
Driver behaviour, System awareness, Eco-friendly behaviour, Driver recommendation systems
National Category
Psychology Human Computer Interaction Information Systems
Research subject
Interaction Lab (ILAB); Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:his:diva-15279 (URN)10.1016/j.trf.2018.05.009 (DOI)
Projects
TIEB
Funder
Swedish Energy Agency
Available from: 2018-06-04 Created: 2018-06-04 Last updated: 2018-06-05Bibliographically approved
Lagerstedt, E., Riveiro, M. & Thill, S. (2017). Agent Autonomy and Locus of Responsibility for Team Situation Awareness. In: HAI '17: Proceedings of the 5th International Conference on Human Agent Interaction. Paper presented at 5th International Conference on Human Agent Interaction, Bielefeld, October 17-20, 2017 (pp. 261-269). New York: Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Agent Autonomy and Locus of Responsibility for Team Situation Awareness
2017 (English)In: HAI '17: Proceedings of the 5th International Conference on Human Agent Interaction, New York: Association for Computing Machinery (ACM), 2017, p. 261-269Conference paper, Published paper (Refereed)
Abstract [en]

Rapid technical advancements have led to dramatically improved abilities for artificial agents, and thus opened up for new ways of cooperation between humans and them, from disembodied agents such as Siris to virtual avatars, robot companions, and autonomous vehicles. It is therefore relevant to study not only how to maintain appropriate cooperation, but also where the responsibility for this resides and/or may be affected. While there are previous organisations and categorisations of agents and HAI research into taxonomies, situations with highly responsible artificial agents are rarely covered. Here, we propose a way to categorise agents in terms of such responsibility and agent autonomy, which covers the range of cooperation from humans getting help from agents to humans providing help for the agents. In the resulting diagram presented in this paper, it is possible to relate different kinds of agents with other taxonomies and typical properties. A particular advantage of this taxonomy is that it highlights under what conditions certain effects known to modulate the relationship between agents (such as the protégé effect or the "we"-feeling) arise.

Place, publisher, year, edition, pages
New York: Association for Computing Machinery (ACM), 2017
Keywords
HAI, Locus of Responsibility, Agent Relationship, Classification of Artificial Agents
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB); Skövde Artificial Intelligence Lab (SAIL)
Identifiers
urn:nbn:se:his:diva-14269 (URN)10.1145/3125739.3125768 (DOI)2-s2.0-85034847392 (Scopus ID)978-1-4503-5113-3 (ISBN)
Conference
5th International Conference on Human Agent Interaction, Bielefeld, October 17-20, 2017
Projects
Dreams4Cars
Funder
EU, Horizon 2020, 731593
Available from: 2017-10-30 Created: 2017-10-30 Last updated: 2018-02-01Bibliographically approved
Da Lio, M., Mazzalai, A., Windridge, D., Thill, S., Svensson, H., Yueksel, M., . . . Heich, H.-J. (2017). Exploiting Dream-Like Simulation Mechanisms to Develop Safer Agents for Automated Driving The "Dreams4Cars" EU Research and Innovation Action. In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC): . Paper presented at 20th IEEE International Conference on Intelligent Transportation Systems (ITSC), Yokohama, Japan, October 16-19, 2017. IEEE
Open this publication in new window or tab >>Exploiting Dream-Like Simulation Mechanisms to Develop Safer Agents for Automated Driving The "Dreams4Cars" EU Research and Innovation Action
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2017 (English)In: 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), IEEE, 2017Conference paper, Published paper (Refereed)
Abstract [en]

Automated driving needs unprecedented levels of reliably and safety before marked deployment. The average human driver fatal accident rate is 1 every 100 million miles. Automated vehicles will have to provably best these figures. This paper introduces the notion of dream-like mechanisms as a simulation technology to produce a large number of hypothetical design and test scenarios - especially focusing on variations of more frequent dangerous and near miss events. Grounded in the simulation hypothesis of cognition, we show here some principles for effective simulation mechanisms and an artificial cognitive system architecture that can learn from the simulated situations.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE International Conference on Intelligent Transportation Systems, ISSN 2153-0009, E-ISSN 2153-0017
Keywords
Automated driving, Co-Driver Agent, Artificial Cognitive Systems, Learning by simulations, Simulation Hypothesis of Cognition
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-15584 (URN)10.1109/ITSC.2017.8317649 (DOI)000432373000064 ()2-s2.0-85046269567 (Scopus ID)978-1-5386-1526-3 (ISBN)978-1-5386-1527-0 (ISBN)
Conference
20th IEEE International Conference on Intelligent Transportation Systems (ITSC), Yokohama, Japan, October 16-19, 2017
Available from: 2018-06-14 Created: 2018-06-14 Last updated: 2018-06-14
Esteban, P. G., Baxter, P., Belpaeme, T., Billing, E., Cai, H., Cao, H.-L., . . . Ziemke, T. (2017). How to Build a Supervised Autonomous System for Robot-Enhanced Therapy for Children with Autism Spectrum Disorder. Paladyn - Journal of Behavioral Robotics, 8(1), 18-38
Open this publication in new window or tab >>How to Build a Supervised Autonomous System for Robot-Enhanced Therapy for Children with Autism Spectrum Disorder
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2017 (English)In: Paladyn - Journal of Behavioral Robotics, ISSN 2080-9778, E-ISSN 2081-4836, Vol. 8, no 1, p. 18-38Article in journal (Refereed) Published
Abstract [en]

Robot-Assisted Therapy (RAT) has successfully been used to improve social skills in children with autism spectrum disorders (ASD) through remote control of the robot in so-called Wizard of Oz (WoZ) paradigms.However, there is a need to increase the autonomy of the robot both to lighten the burden on human therapists (who have to remain in control and, importantly, supervise the robot) and to provide a consistent therapeutic experience. This paper seeks to provide insight into increasing the autonomy level of social robots in therapy to move beyond WoZ. With the final aim of improved human-human social interaction for the children, this multidisciplinary research seeks to facilitate the use of social robots as tools in clinical situations by addressing the challenge of increasing robot autonomy.We introduce the clinical framework in which the developments are tested, alongside initial data obtained from patients in a first phase of the project using a WoZ set-up mimicking the targeted supervised-autonomy behaviour. We further describe the implemented system architecture capable of providing the robot with supervised autonomy.

Place, publisher, year, edition, pages
De Gruyter Open, 2017
Keywords
Robot-Enhanced Therapy, Autism Spectrum Disorders, Supervised Autonomy, Multi-sensory Data, Cognitive Controller
National Category
Computer and Information Sciences
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-13559 (URN)10.1515/pjbr-2017-0002 (DOI)
Funder
EU, FP7, Seventh Framework Programme, 611391
Available from: 2017-05-16 Created: 2017-05-16 Last updated: 2018-01-13Bibliographically approved
Moore, R., Thill, S. & Marxer, R. (2017). Vocal Interactivity in-and-between Humans, Animals and Robots (VIHAR): (Dagstuhl Seminar 16442). Dagstuhl Reports, 6(10), 154-194
Open this publication in new window or tab >>Vocal Interactivity in-and-between Humans, Animals and Robots (VIHAR): (Dagstuhl Seminar 16442)
2017 (English)In: Dagstuhl Reports, E-ISSN 2192-5283, Vol. 6, no 10, p. 154-194Article in journal (Refereed) Published
Keywords
animal calls, human-robot interaction, language evolution, language universals, speech technology, spoken language, vocal expression, vocal interaction, vocal learning
National Category
Human Computer Interaction
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-13429 (URN)10.4230/DagRep.6.10.154 (DOI)000389272100001 ()
Available from: 2017-03-13 Created: 2017-03-13 Last updated: 2018-01-13Bibliographically approved
Sakreida, K., Effnert, I., Thill, S., Menz, M. M., Jirak, D., Eickhoff, C. R., . . . Binkofski, F. (2016). Affordance processing in segregated parieto-frontal dorsal stream sub-pathways. Neuroscience and Biobehavioral Reviews, 69, 89-112
Open this publication in new window or tab >>Affordance processing in segregated parieto-frontal dorsal stream sub-pathways
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2016 (English)In: Neuroscience and Biobehavioral Reviews, ISSN 0149-7634, E-ISSN 1873-7528, Vol. 69, p. 89-112Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Elsevier, 2016
Keywords
Object interaction, Affordances, Stable, Variable, Cognitive psychology, Parieto-frontal pathways, Ventro-dorsal, Dorso-dorsal, Neuroscience
National Category
Other Natural Sciences
Identifiers
urn:nbn:se:his:diva-12731 (URN)10.1016/j.neubiorev.2016.07.032 (DOI)000385323500007 ()27484872 (PubMedID)2-s2.0-84982728809 (Scopus ID)
Available from: 2016-07-31 Created: 2016-07-31 Last updated: 2017-11-28Bibliographically approved
Svensson, H. & Thill, S. (2016). Beyond bodily anticipation: Internal simulations in social interaction. Cognitive Systems Research, 40, 161-171
Open this publication in new window or tab >>Beyond bodily anticipation: Internal simulations in social interaction
2016 (English)In: Cognitive Systems Research, ISSN 2214-4366, E-ISSN 1389-0417, Vol. 40, p. 161-171Article in journal (Refereed) Published
Place, publisher, year, edition, pages
Elsevier, 2016
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:his:diva-12593 (URN)10.1016/j.cogsys.2016.06.003 (DOI)000382248800014 ()2-s2.0-84982090975 (Scopus ID)
Available from: 2016-06-26 Created: 2016-06-26 Last updated: 2018-01-10Bibliographically approved
Thill, S. & Vernon, D. (2016). How to Design Emergent Models of Cognition for Application-Driven Artificial Agents. In: Katherine Twomey, Gert Westermann, Padraic Monaghan and Alastair Smith (Ed.), Katherine Twomey, Gert Westermann, Padraic Monaghan & Alastair Smith (Ed.), Neurocomputational Models of Cognitive Development and Processing: Proceedings of the 14th Neural Computation and Psychology Workshop. Paper presented at 14th Neural Computation and Psychology Workshop, Lancaster University, UK, 21 – 23 August 2014 (pp. 115-129). Singapore: World Scientific
Open this publication in new window or tab >>How to Design Emergent Models of Cognition for Application-Driven Artificial Agents
2016 (English)In: Neurocomputational Models of Cognitive Development and Processing: Proceedings of the 14th Neural Computation and Psychology Workshop / [ed] Katherine Twomey, Gert Westermann, Padraic Monaghan & Alastair Smith, Singapore: World Scientific, 2016, p. 115-129Conference paper, Published paper (Refereed)
Abstract [en]

Emergent models of cognition are attractive for artificial cognitive agents because they overcome the brittleness of systems that are fully specified in axiomatic terms at design time, increasing, for example, the ability to deal with uncertainty and unforeseen events. When the agent is created to fulfil specific requirements defined by a given application, there is an apparent conflict between the emergent (i.e. self-defining) nature of the agent's behaviour and the pre-specified (i.e. axiomatically-defined) nature of the requirements.

Here, we develop a framework for the design of emergent models of cognition whose behaviour can be shaped to fulfil application requirements while retaining the desired characteristics of emergence. We achieve this by viewing the artificial agent as forming an eco-system with the environment in which it is deployed. Consequently, the objective function that determines the agent's behaviour is cast in terms that factor in interaction with the environment (while not being controlled by it) and therefore implicitly includes the application requirements.

This framework is particularly relevant to application driven research where artificial agents are designed to interact with humans in a certain manner. We illustrate this with the example of robot-enhanced therapy for children with autism spectrum disorder

Place, publisher, year, edition, pages
Singapore: World Scientific, 2016
Series
Progress in Neural Processing ; 22
National Category
Human Computer Interaction
Identifiers
urn:nbn:se:his:diva-12987 (URN)10.1142/9789814699341_0008 (DOI)978-981-4699-35-8 (ISBN)978-981-4699-33-4 (ISBN)
Conference
14th Neural Computation and Psychology Workshop, Lancaster University, UK, 21 – 23 August 2014
Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-01-10Bibliographically approved
Vernon, D., Thill, S. & Ziemke, T. (2016). The Role of Intention in Cognitive Robotics. In: Anna Esposito & Lakhmi C. Jain (Ed.), Toward Robotic Socially Believable Behaving Systems: Volume I (pp. 15-27). Switzerland: Springer
Open this publication in new window or tab >>The Role of Intention in Cognitive Robotics
2016 (English)In: Toward Robotic Socially Believable Behaving Systems: Volume I / [ed] Anna Esposito & Lakhmi C. Jain, Switzerland: Springer, 2016, p. 15-27Chapter in book (Refereed)
Abstract [en]

We argue that the development of robots that can interact effectively with people requires a special focus on building systems that can perceive and comprehend intentions in other agents. Such a capability is a prerequisite for all pro-social behaviour and in particular underpins the ability to engage in instrumental helping and mutual collaboration. We explore the prospective and intentional nature of action, highlighting the importance of joint action, shared goals, shared intentions, and joint attention in facilitating social interaction between two or more cognitive agents. We discuss the link between reading intentions and theory of mind, noting the role played by internal simulation, especially when inferring higher-level actionfocussed intentions. Finally, we highlight that pro-social behaviour in humans is the result of a developmental process and we note the implications of this for the challenge of creating cognitive robots that can read intentions.

Place, publisher, year, edition, pages
Switzerland: Springer, 2016
Series
Intelligent Systems Reference Library, ISSN 1868-4394 ; 105
Keywords
Robotics, Human-robot interaction, emotion, intention
National Category
Robotics
Research subject
Technology
Identifiers
urn:nbn:se:his:diva-11945 (URN)10.1007/978-3-319-31056-5_3 (DOI)000377156400004 ()2-s2.0-84961627492 (Scopus ID)978-3-319-31055-8 (ISBN)
Projects
DREAM: Development of Robot-enhanced Therapy for Children with Autism Spectrum Disorders
Funder
EU, FP7, Seventh Framework Programme, 611391
Available from: 2016-02-23 Created: 2016-02-23 Last updated: 2017-11-27Bibliographically approved
Moore, R. K., Marxer, R. & Thill, S. (2016). Vocal interactivity in-and-between humans, animals and robots. , 3, Article ID 61.
Open this publication in new window or tab >>Vocal interactivity in-and-between humans, animals and robots
2016 (English)In: Vol. 3, article id 61Article, review/survey (Refereed) Published
Abstract [en]

Almost all animals exploit vocal signals for a range of ecologically-motivated purposes: detecting predators/prey and marking territory, expressing emotions, establishing social relations and sharing information. Whether it is a bird raising an alarm, a whale calling to potential partners, a dog responding to human commands, a parent reading a story with a child, or a business-person accessing stock prices using \emph{Siri}, vocalisation provides a valuable communication channel through which behaviour may be coordinated and controlled, and information may be distributed and acquired. Indeed, the ubiquity of vocal interaction has led to research across an extremely diverse array of fields, from assessing animal welfare, to understanding the precursors of human language, to developing voice-based human-machine interaction. Opportunities for cross-fertilisation between these fields abound; for example, using artificial cognitive agents to investigate contemporary theories of language grounding, using machine learning to analyse different habitats or adding vocal expressivity to the next generation of language-enabled autonomous social agents. However, much of the research is conducted within well-defined disciplinary boundaries, and many fundamental issues remain. This paper attempts to redress the balance by presenting a comparative review of vocal interaction within-and-between humans, animals and artificial agents (such as robots), and it identifies a rich set of open research questions that may benefit from an inter-disciplinary analysis.

National Category
Human Computer Interaction
Identifiers
urn:nbn:se:his:diva-12984 (URN)10.3389/frobt.2016.00061 (DOI)000389272100001 ()
Available from: 2016-09-28 Created: 2016-09-28 Last updated: 2018-01-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1177-4119

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