Haptic Feedback for the Transfer of Control in Autonomous Vehicles

Vehicles offering autonomous features need effective methods for transferring the control from the driver to the vehicle and back. While most research focuses on presenting information the driver might need after retaking control, our study investigates ways to improve the process of transferring control itself. We investigated multimodal feedback with and without haptics and visuals in a simulator study. Results showed that visual and haptic feedback improved driving during handover. Subjective ratings described multimodal feedback without visual as more disruptive than with the visual feedback included. Furthermore, ratings showed a preference for including visual and haptic feedback. These results lead us a step closer to a safe, clear and accepted control transfer process between driver and vehicle

Human-centered User Interfaces for Automated Driving – (Un-)exploited Potentials

Designing user interfaces for (highly) automated driving is a complex task since users vary considerably regarding their needs and preferences. Therefore, a one-size-fits-all approach will not be sufficient for designing these interfaces. Thus, in this paper we aim to identify unexploited potentials in this area. We do so by performing a systematic literature review. Our contributions are 1) a systematization of human-centered user interface design for automated driving in four key aspects, 2) the research intensity per aspect, 3) the unexploited potential within each aspect and 4) the potentials of the relations between them. Concretely, current research lacks frameworks supporting the customization of the named interfaces based on user characteristics. Among others, personalization of displayed information shows unexploited potentials for acceptance and usability. Thus, we recommend future research to focus on human-centricity accounting for individual needs instead of the interface itself

Where's My Cellphone: Non-contact based Hand-Gestures and Ultrasound haptic feedback for Secondary Task Interaction while Driving

Drivers regularly use their smartphones to perform secondary tasks while driving, which can negatively impact traffic safety. In such complex interaction, multimodal feedback has been associated with lowering driver distraction. We investigated four methods for completing a phone-based secondary task while driving: smartphone in hand, smartphone in a rack, buttons on the steering wheel with Head-up-display (HUD), and mid-air gestures with an ultrasound haptic feedback and a HUD. Participants (N=16) drove the Lane Change Test (LCT) simulator with each method to complete predefined secondary tasks. To measure performance in primary task, we recorded lane deviations and for secondary task we measured response times and errors. Additionally, the participants filled in the NASA-TLX questionnaire and ranked each method according to their preferences. The results showed that the performance and preference for the hand and rack conditions were similar, while performance with buttons and gestures was worse, even with ultrasound haptic feedback, than in hand and rack conditions. The results highlight the importance of rigorous user testing when introducing new modalities for in-vehicle interaction to enhance primary and secondary task performance.acceptedVersionPeer reviewe

Using and Interacting with AI-Based Intelligent Technologies: Practical Applications on Autonomous Cars and Chatbots

L'intelligence artificielle (IA) est souvent considérée comme l'une des innovations les plus prometteuses et perturbatrices de notre époque. Malgré son développement rapide, il existe encore un haut niveau d'incertitude quant à la manière dont les consommateurs vont adopter l'IA. Dans ce contexte, cette thèse de quatre articles vise à comprendre comment les consommateurs utilisent et interagissent avec les technologies intelligentes, en se concentrant en particulier sur deux applications: les chatbots et les véhicules autonomes (VA). Dans un premier temps, nous effectuons une analyse approfondie de la littérature marketing existante en adoptant les approches scientométriques et la méthode Theory-Context-Characteristics-Methodology. Ainsi, nous définissons nos questions de recherche concernant 1) les réactions cognitives et émotionnelles des consommateurs lorsqu'ils interagissent avec des technologies basées sur l'IA capables de simuler des conversations de type humain ; 2) les facteurs affectant l'intention des consommateurs d'utiliser des technologies basées sur l'IA, et leur évolution à travers les niveaux d'automatisation ; 3) les préoccupations éthiques des consommateurs envers les produits IA et leur effet sur la confiance et les intentions d'utilisation. En mettant en œuvre trois plans expérimentaux inter-sujets, nous répondons à notre première question de recherche en comparant les interactions humain-humain et humain-chatbot et les interactions avec des chatbots hautement anthropomorphes et faiblement anthropomorphes. Nous nous appuyons principalement sur la Théorie de l'Evaluation Cognitive des Emotions (Roseman et al. 1990), la Théorie de l'Attribution (Weiner 2000) et la Théorie de l'Anthropomorphisme (Aggarwal and McGill 2007 ; Epley et al. 2018), en montrant que les réponses des consommateurs diffèrent lorsqu'ils interagissent avec un humain et un chatbot, en fonction des différentes attributions de responsabilité et des différents niveaux d'anthropomorphisme. Ensuite, nous étudions la manière dont l'expérience des consommateurs avec différents niveaux d'automatisation affecte les perceptions des technologies basées sur l'IA. Nous utilisons les VA comme unité d'analyse, en intégrant le cadre UTAUT avec la Théorie de la Confiance (Mcknight et al. 2011), la Théorie du Calcul de la Vie Privée (Dinev et Hart 2006) et la Théorie du Bien-être (Diener 1999). Après la mise en œuvre d'un design intra-sujet avec des études sur le terrain et sur simulateur, les résultats suggèrent que la différenciation entre les différents niveaux d'automatisation joue un rôle clé pour mieux comprendre les facteurs d’adoption ainsi que les réactions cognitives lors de l'utilisation d'applications intelligentes. Enfin, nous étudions les préoccupations éthiques des consommateurs concernant les chatbots et les VA. Nous utilisons une approche mixte, en utilisant la modélisation thématique et la modélisation par équation structurelle. Nous montrons que pour les chatbots, la composante interactionnelle et émotionnelle de la technologie est prédominante, les consommateurs soulignant, entre autres, le design émotionnel et le manque d'adaptabilité comme principaux soucis éthiques. En revanche, pour les VA, les préoccupations éthiques concernent plutôt des perceptions cognitives liées à la transparence des algorithmes, à la sécurité de la technologie et à l'accessibilité. Notre recherche offre des contributions à la littérature émergente sur les comportements des consommateurs liés aux produits intelligents en soulignant la nécessité de prendre en compte la complexité des technologies d'IA à travers leurs différents niveaux d'automatisation et en fonction de leurs caractéristiques. Nous offrons également des contributions méthodologiques grâce à la mise en œuvre de plans de recherche expérimentaux innovants, utilisant des outils avancés et combinant des approches qualitatives et quantitatives. […]Artificial Intelligence (AI) is often considered as one of the most promising and disruptive innovation of our times. Despite its rapid development, there is still a high level of uncertainty about how consumers are going to adopt AI. In this context, this four-article dissertation aims to comprehend how consumers use and interact with intelligent technologies, in particular focusing on two current applications: chatbots and autonomous vehicles (AVs). First, we conduct an in-depth analysis of the existing marketing literature adopting Scientometric and Theory-Context-Characteristics-Methodology approaches. Thus, we define our research questions related to 1) consumers ‘cognitive and emotional reactions when interacting with AI-based technologies that are able to simulate human-like conversations; 2) factors affecting consumers ‘intention to use AI-based technologies able to make decision in critical situations, and their evolution across levels of automation; 3) consumers ethical concerns towards AI products and their effect on trust and usage intentions. By applying three between-subject experimental designs, we answer our first research question comparing human–human versus human–chatbot interactions and highly anthropomorphic versus lowly anthropomorphic chatbots. We leverage insights mainly from Cognitive Appraisal Theory of Emotions (Roseman et al. 1990), Attribution Theory (Weiner 2000) and Theory of Anthropomorphism (Aggarwal and McGill 2007; Epley et al. 2018), showing that consumers’ responses differ when interacting with a human and a chatbot, according to the different attributions of responsibility and the different levels of anthropomorphism of the service agent. Next, we investigate the way consumers’ experience with different levels of automation affect perceptions of AI-based technologies. We use AVs as unit of analysis, integrating the UTAUT framework with Trust Theory (Mcknight et al. 2011), Privacy Calculus Theory (Dinev and Hart 2006) and Theory of Well-being (Diener 1999; Diener and Chan 2011). After implementing a within subject-design with field and simulator studies, results suggest that differentiating between the different automation levels play a key role to better understand the potential drivers of adoption as well as the cognitive reactions when using intelligent applications. Finally, we investigate consumers’ ethical concerns surrounding chatbots and AVs. We employ a mixed methods approach, using topic modeling and structural equation modeling. We show that for chatbots, the interactional and emotional component of the technology is predominant, as consumers highlight, between others, the emotional design and the lack of adaptability as main ethical issues. However, for autonomous cars, the ethical concerns rather involve cognitive perceptions related to the transparency of the algorithms, the ethical design, the safety of the technology and the accessibility. Our research offers contributions to the emerging literature on consumer behaviors related to intelligent products by highlighting the need to take into account the complexity of AI technologies across their different levels of automation and according to their intrinsic characteristics. We also offer methodological contributions thanks to the implementation of innovative experimental research designs, using advanced tools and combining qualitative and quantitative approaches. To conclude, we present implications for both managers and policymakers who want to implement AIbased disruptive technologies, such as chatbots and AVs

Automated landmine detection by means of a mobile robot

Tese de doutoramento em Engenharia Electrotécnica (Instrumentação e Controlo) apresentada à Faculdade de Ciências e Tecnologia da Universidade de CoimbraMillions of antipersonnel landmines are left in the ground after past war conicts across many countries. Being functional for more than 50 years they provide a lot of humanitarian and economical problems long after the conict is _nished. Cleaning the existing mine_elds, called humanitarian demining, is required in order to return the large areas of the land to normal use and save the local civilians from the danger. Currently, the only fully trustable solution for this problem is the manual clearance which is itself a very dangerous and slow procedure. Automation of the humanitarian demining may change the situation providing a faster approach which eliminates the participation of humans on the mine_eld. This work is a part of the e_ort toward the development of such approach. Automation of the humanitarian demining meets a lot of technical problems which currently do not have e_ective solutions. This work covers the ones related to the automatic detection of antipersonnel landmines assisted by a mobile scanning platform which carries the landmine detection sensors. The landmine detection approach developed in this work assumes the employing of several nonselective sensors most widely used for landmine detection which include metal detectors, infrared sensors, and ground penetrating radar. The approach has a multi-stage structure and is based on feature-level sensor fusion strategy. This process is understood as a step-by-step reduction of the false alarm rate depending on the quality of the available sensor data. During the _rst stage the sensor data are processed in order to distinguish all objects suspected to be landmines against the background. For this purpose a novel online algorithm was developed. It allows to detect the object during the robot movement and is hardly sensitive to the quality of the sensor data. The consequent stages are performed in order to recognize the landmines among the detected suspicious objects. A number of new classi_cation features were developed in order to perform this recognition. Based on the feature analysis a concept of selective training specially suited for the landmine recognition task was developed. This technique allows to account for the high overlapping of the classes and multimodal distributions of the classi_cation features. Finally, a concept of dominant class was introduced in order to provide high levels of detection rates even in case of poorly separated classes. Being specially designed for the speci_cs of landmine detection the proposed algorithms allow to improve the results. In order to assist the gathering of the sensor data, the problems related to the effective sensor data gathering,path planning and localization of the platform are also addressed. The developed solutions are implemented on the previously created pneumatic scanning platform acting as a prototype demining robot. A number of practical solutions improving the platform localization were developed. The positioning of the robot is based on its odometry, compass and a novel vision system which are combined together by means of a Kalman _lter. The vision system employees a simple CCD camera and is guided by a novel algorithm for the detection and association of natural landmarks found on the ground surface. Finally, considering the landmine detection problem in the scale of mine_eld the problem of the _eld exploration is addressed. Assuming a general case in which the mine_eld may be populated with some obstacles in unknown positions an algorithm for online unknown area coverage was developed. The algorithm guarantees regularity of the robot path necessary for the mapping of sensor data and the safety of the robot by planning its path only inside already covered area. The developed algorithms were implemented in a form of control software for the real platform. Testing of the proposed ideas in simulation and in real conditions (on a test mine_eld) provided promising results showing the perspective of the developed concepts. Based on the experimental results the recommendations for future work are formulated. The automatic landmine detection task raises a number of challenging problems which have connections to other areas of robotics, pattern recognition and control. In this regards the development of the methods proposed in this work was considered in a more broad sense. Thus, the results of this work can be used in the adjacent _elds of robotics: automatic subsurface sensing with online reaction to the found target, pattern recognition in case of poorly distinguished classes, and online unknown area coverage required for cleaning, grass cutting, agriculture, etc

Large space structures and systems in the space station era: A bibliography with indexes (supplement 03)

Bibliographies and abstracts are listed for 1221 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1991 and June 30, 1991. Topics covered include large space structures and systems, space stations, extravehicular activity, thermal environments and control, tethering, spacecraft power supplies, structural concepts and control systems, electronics, advanced materials, propulsion, policies and international cooperation, vibration and dynamic controls, robotics and remote operations, data and communication systems, electric power generation, space commercialization, orbital transfer, and human factors engineering