21 research outputs found

    I Am The Passenger: Challenges in Supporting AR/VR HMDs In-Motion

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    This video provides an overview of our research into the use of Head Mounted Displays (HMDs) in-car and in-motion. These immersive HMDs offer new possibilities for entertainment and productivity during travel. However, their use is confounded by motion sickness, caused in-part by the conflict between visually and physically perceived motion. Moreover, consumer HMDs cannot currently distinguish between the head motion of the wearer and rotations of the car. These problems represent significant impediments to their use in-motion, which our research aims to overcome

    Digitizing human-to-human interaction for automated vehicles

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    Evaluation of variables for the communication of uncertainties using peripheral awareness displays

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    The communication of system uncertainties may be key for overcoming challenges related to overtrust in automated driving. Existing approaches are limited to conveying uncertainties using visual displays in the instrument cluster. This requires operators to regularly monitor the display in order to perceive changes which impedes the execution of nondriving related tasks and thereby degrades the user experience. This study evaluates variables for the communication of uncertainties using peripheral awareness displays, considering changes in brightness, hue, position, size, pulse frequency, and movement speed. All variables were assessed in terms of how well participants can distinguish different instances, how logical they are, and how interrupting to a secondary task. With the exception of changes in position, all variables were ranked highly in terms of logic while changes in pulse frequency were perceived as most interrupting. The results inform the development of unobtrusive interfaces for uncertainty communication

    Augmented reality displays for communicating uncertainty information in automated driving

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    Safe manual driving performance following takeovers in conditionally automated driving systems is impeded by a lack in situation awareness, partly due to an inappropriate trust in the system’s capabilities. Previous work has indicated that the communication of system uncertainties can aid the trust calibration process. However, it has yet to be investigated how the information is best conveyed to the human operator. The study outlined in this publication presents an interface layout to visualise function-specific uncertainty information in an augmented reality display and explores the suitability of 11 visual variables. 46 participants completed a sorting task and indicated their preference for each of these variables. The results demonstrate that particularly colour-based and animation-based variables, above all hue, convey a clear order in terms of urgency and are well-received by participants. The presented findings have implications for all augmented reality displays that are intended to show content varying in urgency

    Preliminary evaluation of variables for communicating uncertainties using a Haptic seat

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    Recent findings have indicated that the communication of uncertainties is a promising approach for overcoming human factors challenges associated with overtrust issues. The existing approaches, however, are limited in that they require operators to monitor the instrument cluster to perceive changes. As a consequence, significant changes may be missed and operators are regularly interrupted in the execution of non-driving related tasks even if the system is performing well. To overcome this, unobtrusive interfaces are required that are only interruptive if needed. This paper presents a lab-based study aiming at the preliminary evaluation of haptic variables for communicating automation uncertainties using a haptic vehicle seat. The initial results indicate that particularly increases in amplitude as well as a rhythm consisting of long vibrations separated by short breaks are well suited for communicating the exceedance of specified uncertainty thresholds. The communication of decreases in uncertainty using vibration cannot be recommended

    Investigating the Effect of Tactile Input and Output Locations for Drivers’ Hands on In-Car Tasks Performance

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    This paper reports a study investigating the effects of tactile input and output from the steering wheel and the centre console on non-driving task performance. While driving, participants were asked to perform list selection tasks using tactile switches and to experience tactile feedback on either the non-dominant, dominant or both hands as they were browsing the list. Our results show the average duration for selecting an item is 30% shorter when interacting with the steering wheel. They also show a 20% increase in performance when tactile feedback is provided. Our findings reveal that input prevails over output location when designing interaction for drivers. However, tactile feedback on the steering wheel is beneficial when provided at the same location as the input or to both hands. The results will help designers understand the trade-offs of using different interaction locations in the car

    Towards a Taxonomy for In-Vehicle Interactions Using Wearable Smart Textiles: Insights from a User-Elicitation Study

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    Textiles are a vital and indispensable part of our clothing that we use daily. They are very flexible, often lightweight, and have a variety of application uses. Today, with the rapid developments in small and flexible sensing materials, textiles can be enhanced and used as input devices for interactive systems. Clothing-based wearable interfaces are suitable for in-vehicle controls. They can combine various modalities to enable users to perform simple, natural, and efficient interactions while minimizing any negative effect on their driving. Research on clothing-based wearable in-vehicle interfaces is still underexplored. As such, there is a lack of understanding of how to use textile-based input for in-vehicle controls. As a first step towards filling this gap, we have conducted a user-elicitation study to involve users in the process of designing in-vehicle interactions via a fabric-based wearable device. We have been able to distill a taxonomy of wrist and touch gestures for in-vehicle interactions using a fabric-based wrist interface in a simulated driving setup. Our results help drive forward the investigation of the design space of clothing-based wearable interfaces for in-vehicle secondary interactions.</jats:p

    Exploration of smart infrastructure for drivers of autonomous vehicles

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    The connection between vehicles and infrastructure is an integral part of providing autonomous vehicles information about the environment. Autonomous vehicles need to be safe and users need to trust their driving decision. When smart infrastructure information is integrated into the vehicle, the driver needs to be informed in an understandable manner what the smart infrastructure detected. Nevertheless, interactions that benefit from smart infrastructure have not been the focus of research, leading to knowledge gaps in the integration of smart infrastructure information in the vehicle. For example, it is unclear, how the information from two complex systems can be presented, and if decisions are made, how these can be explained. Enriching the data of vehicles with information from the infrastructure opens unexplored opportunities. Smart infrastructure provides vehicles with information to predict traffic flow and traffic events. Additionally, it has information about traffic events in several kilometers distance and thus enables a look ahead on a traffic situation, which is not in the immediate view of drivers. We argue that this smart infrastructure information can be used to enhance the driving experience. To achieve this, we explore designing novel interactions, providing warnings and visualizations about information that is out of the view of the driver, and offering explanations for the cause of changed driving behavior of the vehicle. This thesis focuses on exploring the possibilities of smart infrastructure information with a focus on the highway. The first part establishes a design space for 3D in-car augmented reality applications that profit from smart infrastructure information. Through the input of two focus groups and a literature review, use cases are investigated that can be introduced in the vehicle's interaction interface which, among others, rely on environment information. From those, a design space that can be used to design novel in-car applications is derived. The second part explores out-of-view visualizations before and during take over requests to increase situation awareness. With three studies, different visualizations for out-of-view information are implemented in 2D, stereoscopic 3D, and augmented reality. Our results show that visualizations improve the situation awareness about critical events in larger distances during take over request situations. In the third part, explanations are designed for situations in which the vehicle drives unexpectedly due to unknown reasons. Since smart infrastructure could provide connected vehicles with out-of-view or cloud information, the driving maneuver of the vehicle might remain unclear to the driver. Therefore, we explore the needs of drivers in those situations and derive design recommendations for an interface which displays the cause for the unexpected driving behavior. This thesis answers questions about the integration of environment information in vehicles'. Three important aspects are explored, which are essential to consider when implementing use cases with smart infrastructure in mind. It enables to design novel interactions, provides insights on how out-of-view visualizations can improve the drivers' situation awareness and explores unexpected driving situations and the design of explanations for them. Overall, we have shown how infrastructure and connected vehicle information can be introduced in vehicles' user interface and how new technology such as augmented reality glasses can be used to improve the driver's perception of the environment.Autonome Fahrzeuge werden immer mehr in den alltäglichen Verkehr integriert. Die Verbindung von Fahrzeugen mit der Infrastruktur ist ein wesentlicher Bestandteil der Bereitstellung von Umgebungsinformationen in autonome Fahrzeugen. Die Erweiterung der Fahrzeugdaten mit Informationen der Infrastruktur eröffnet ungeahnte Möglichkeiten. Intelligente Infrastruktur übermittelt verbundenen Fahrzeugen Informationen über den prädizierten Verkehrsfluss und Verkehrsereignisse. Zusätzlich können Verkehrsgeschehen in mehreren Kilometern Entfernung übermittelt werden, wodurch ein Vorausblick auf einen Bereich ermöglicht wird, der für den Fahrer nicht unmittelbar sichtbar ist. Mit dieser Dissertation wird gezeigt, dass Informationen der intelligenten Infrastruktur benutzt werden können, um das Fahrerlebnis zu verbessern. Dies kann erreicht werden, indem innovative Interaktionen gestaltet werden, Warnungen und Visualisierungen über Geschehnisse außerhalb des Sichtfelds des Fahrers vermittelt werden und indem Erklärungen über den Grund eines veränderten Fahrzeugverhaltens untersucht werden. Interaktionen, welche von intelligenter Infrastruktur profitieren, waren jedoch bisher nicht im Fokus der Forschung. Dies führt zu Wissenslücken bezüglich der Integration von intelligenter Infrastruktur in das Fahrzeug. Diese Dissertation exploriert die Möglichkeiten intelligenter Infrastruktur, mit einem Fokus auf die Autobahn. Der erste Teil erstellt einen Design Space für Anwendungen von augmentierter Realität (AR) in 3D innerhalb des Autos, die unter anderem von Informationen intelligenter Infrastruktur profitieren. Durch das Ergebnis mehrerer Studien werden Anwendungsfälle in einem Katalog gesammelt, welche in die Interaktionsschnittstelle des Autos einfließen können. Diese Anwendungsfälle bauen unter anderem auf Umgebungsinformationen. Aufgrund dieser Anwendungen wird der Design Space entwickelt, mit Hilfe dessen neuartige Anwendungen für den Fahrzeuginnenraum entwickelt werden können. Der zweite Teil exploriert Visualisierungen für Verkehrssituationen, die außerhalb des Sichtfelds des Fahrers sind. Es wird untersucht, ob durch diese Visualisierungen der Fahrer besser auf ein potentielles Übernahmeszenario vorbereitet wird. Durch mehrere Studien wurden verschiedene Visualisierungen in 2D, stereoskopisches 3D und augmentierter Realität implementiert, die Szenen außerhalb des Sichtfelds des Fahrers darstellen. Diese Visualisierungen verbessern das Situationsbewusstsein über kritische Szenarien in einiger Entfernung während eines Übernahmeszenarios. Im dritten Teil werden Erklärungen für Situationen gestaltet, in welchen das Fahrzeug ein unerwartetes Fahrmanöver ausführt. Der Grund des Fahrmanövers ist dem Fahrer dabei unbekannt. Mit intelligenter Infrastruktur verbundene Fahrzeuge erhalten Informationen, die außerhalb des Sichtfelds des Fahrers liegen oder von der Cloud bereit gestellt werden. Dadurch könnte der Grund für das unerwartete Fahrverhalten unklar für den Fahrer sein. Daher werden die Bedürfnisse des Fahrers in diesen Situationen erforscht und Empfehlungen für die Gestaltung einer Schnittstelle, die Erklärungen für das unerwartete Fahrverhalten zur Verfügung stellt, abgeleitet. Zusammenfassend wird gezeigt wie Daten der Infrastruktur und Informationen von verbundenen Fahrzeugen in die Nutzerschnittstelle des Fahrzeugs implementiert werden können. Zudem wird aufgezeigt, wie innovative Technologien wie AR Brillen, die Wahrnehmung der Umgebung des Fahrers verbessern können. Durch diese Dissertation werden Fragen über Anwendungsfälle für die Integration von Umgebungsinformationen in Fahrzeugen beantwortet. Drei wichtige Themengebiete wurden untersucht, welche bei der Betrachtung von Anwendungsfällen der intelligenten Infrastruktur essentiell sind. Durch diese Arbeit wird die Gestaltung innovativer Interaktionen ermöglicht, Einblicke in Visualisierungen von Informationen außerhalb des Sichtfelds des Fahrers gegeben und es wird untersucht, wie Erklärungen für unerwartete Fahrsituationen gestaltet werden können

    Automation transparency: Implications of uncertainty communication for human-automation interaction and interfaces

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    Operators of highly automated driving systems may exhibit behaviour characteristic for overtrust issues due to an insufficient awareness of automation fallibility. Consequently, situation awareness in critical situations is reduced and safe driving performance following emergency takeovers is impeded. A driving simulator study was used to assess the impact of dynamically communicating system uncertainties on monitoring, trust, workload, takeovers, and physiological responses. The uncertainty information was conveyed visually using a stylised heart beat combined with a numerical display and users were engaged in a visual search task. Multilevel analysis results suggest that uncertainty communication helps operators calibrate their trust and gain situation awareness prior to critical situations, resulting in safer takeovers. Additionally, eye tracking data indicate that operators can adjust their gaze behaviour in correspondence with the level of uncertainty. However, conveying uncertainties using a visual display significantly increases operator workload and impedes users in the execution of non-driving related tasks
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