The Operation of Autonomous Mobile Robot Assistants in the Environment of Care Facilities Adopting a User-Centered Development Design

The successful development of autonomous mobile robot assistants depends significantly on the well-balanced reconcilements of the technically possible and the socially desirable. Based on empirical research 2 substantiated conclusions can be established for the suitability of "scenario-based design" (Rosson/Carroll 2003) for the successful development of mobile robot assistants and automated guided vehicles to be applied for service functions in stationary care facilities for seniors.User-Centered Technology Development, Knowledge-Transfer, Participative Assessment Methods, Robotics

Data-Driven Evaluation of In-Vehicle Information Systems

Today’s In-Vehicle Information Systems (IVISs) are featurerich systems that provide the driver with numerous options for entertainment, information, comfort, and communication. Drivers can stream their favorite songs, read reviews of nearby restaurants, or change the ambient lighting to their liking. To do so, they interact with large center stack touchscreens that have become the main interface between the driver and IVISs. To interact with these systems, drivers must take their eyes off the road which can impair their driving performance. This makes IVIS evaluation critical not only to meet customer needs but also to ensure road safety. The growing number of features, the distraction caused by large touchscreens, and the impact of driving automation on driver behavior pose significant challenges for the design and evaluation of IVISs. Traditionally, IVISs are evaluated qualitatively or through small-scale user studies using driving simulators. However, these methods are not scalable to the growing number of features and the variety of driving scenarios that influence driver interaction behavior. We argue that data-driven methods can be a viable solution to these challenges and can assist automotive User Experience (UX) experts in evaluating IVISs. Therefore, we need to understand how data-driven methods can facilitate the design and evaluation of IVISs, how large amounts of usage data need to be visualized, and how drivers allocate their visual attention when interacting with center stack touchscreens. In Part I, we present the results of two empirical studies and create a comprehensive understanding of the role that data-driven methods currently play in the automotive UX design process. We found that automotive UX experts face two main conflicts: First, results from qualitative or small-scale empirical studies are often not valued in the decision-making process. Second, UX experts often do not have access to customer data and lack the means and tools to analyze it appropriately. As a result, design decisions are often not user-centered and are based on subjective judgments rather than evidence-based customer insights. Our results show that automotive UX experts need data-driven methods that leverage large amounts of telematics data collected from customer vehicles. They need tools to help them visualize and analyze customer usage data and computational methods to automatically evaluate IVIS designs. In Part II, we present ICEBOAT, an interactive user behavior analysis tool for automotive user interfaces. ICEBOAT processes interaction data, driving data, and glance data, collected over-the-air from customer vehicles and visualizes it on different levels of granularity. Leveraging our multi-level user behavior analysis framework, it enables UX experts to effectively and efficiently evaluate driver interactions with touchscreen-based IVISs concerning performance and safety-related metrics. In Part III, we investigate drivers’ multitasking behavior and visual attention allocation when interacting with center stack touchscreens while driving. We present the first naturalistic driving study to assess drivers’ tactical and operational self-regulation with center stack touchscreens. Our results show significant differences in drivers’ interaction and glance behavior in response to different levels of driving automation, vehicle speed, and road curvature. During automated driving, drivers perform more interactions per touchscreen sequence and increase the time spent looking at the center stack touchscreen. These results emphasize the importance of context-dependent driver distraction assessment of driver interactions with IVISs. Motivated by this we present a machine learning-based approach to predict and explain the visual demand of in-vehicle touchscreen interactions based on customer data. By predicting the visual demand of yet unseen touchscreen interactions, our method lays the foundation for automated data-driven evaluation of early-stage IVIS prototypes. The local and global explanations provide additional insights into how design artifacts and driving context affect drivers’ glance behavior. Overall, this thesis identifies current shortcomings in the evaluation of IVISs and proposes novel solutions based on visual analytics and statistical and computational modeling that generate insights into driver interaction behavior and assist UX experts in making user-centered design decisions

A short curriculum of the robotics and technology of computer lab

Our research Lab is directed by Prof. Anton Civit. It is an interdisciplinary group of 23 researchers that carry out their teaching and researching labor at the Escuela Politécnica Superior (Higher Polytechnic School) and the Escuela de Ingeniería Informática (Computer Engineering School). The main research fields are: a) Industrial and mobile Robotics, b) Neuro-inspired processing using electronic spikes, c) Embedded and real-time systems, d) Parallel and massive processing computer architecture, d) Information Technologies for rehabilitation, handicapped and elder people, e) Web accessibility and usability In this paper, the Lab history is presented and its main publications and research projects over the last few years are summarized.Nuestro grupo de investigación está liderado por el profesor Civit. Somos un grupo multidisciplinar de 23 investigadores que realizan su labor docente e investigadora en la Escuela Politécnica Superior y en Escuela de Ingeniería Informática. Las principales líneas de investigaciones son: a) Robótica industrial y móvil. b) Procesamiento neuro-inspirado basado en pulsos electrónicos. c) Sistemas empotrados y de tiempo real. d) Arquitecturas paralelas y de procesamiento masivo. e) Tecnología de la información aplicada a la discapacidad, rehabilitación y a las personas mayores. f) Usabilidad y accesibilidad Web. En este artículo se reseña la historia del grupo y se resumen las principales publicaciones y proyectos que ha conseguido en los últimos años

Exploration of smart infrastructure for drivers of autonomous vehicles

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

Front-End Design Guidelines for Infotainment Systems

This paper presents a set of front-end design guidelines intended to provide a starting point to designers of user interfaces for infotainment systems. The proposed approach suggests guidance on four dimensions inferred from state of the art such as crucial to achieve well designed automotive interfaces: a) Design; b) Interaction; c) Security; and d) Connectivity. Guidelines were thought by integrating conceptual-insights from Graphic Design; User Centered Design; Human-Machine Interfaces; Usability; and Human-Computer interaction. Additionally, were specified and structured to be used also as a comparing tool (Like Heuristic- Evaluation technique) to analyze front-end of existent infotainment systems. Said duality allowed to revise the pertinence of the proposal through a case study where 30 participants (25 regular users and 5 technicalexperts) compared suggested guidelines’ specification against interactions provided by the front–end of Mazda Connect© infotainment System. Obtained results suggested that setting of proposed guidelines was compatible with participants’ perceptions facilitating to identify pain-points on current design; thus, proposed guidance could scaffold base-insights for new front-end designs

The operation of autonomous mobile robot assistants in the environment of care facilities adopting a user-centered development design

The participation of the Fraunhofer Institute for Manufacturing Engineering and Automation IPA (Stuttgart, Germany) and the companies User Interface Design GmbH (Ludwigsburg, Germany) plus MLR System GmbH (Ludwigsburg, Germany) enabled the research and findings presented in this paper; we would like to namely mention Birgit Graf and Theo Jacobs (Fraunhofer IPA) furthermore Peter Klein and Christiane Hartmann (User Interface Design GmbH).The successful development of autonomous mobile robot assistants depends significantly on the well-balanced reconcilements of the technically possible and the socially desirable. Based on empirical research substantiated conclusions can be established for the suitability of "scenario-based design" (Rosson/Carroll 2003) for the successful development of mobile robot assistants and automated guided vehicles to be applied for service functions in stationary care facilities for seniors.supported by the WiMi-Care project [http://www.wimi-care.de] funded by the German Federal Ministry for Education and Research (FKZ: 01FC08024-27)