Multimodal feedback for mid-air gestures when driving

Mid-air gestures in cars are being used by an increasing number of drivers on the road. Us-ability concerns mean good feedback is important, but a balance needs to be found between supporting interaction and reducing distraction in an already demanding environment. Visual feedback is most commonly used, but takes visual attention away from driving. This thesis investigates novel non-visual alternatives to support the driver during mid-air gesture interaction: Cutaneous Push, Peripheral Lights, and Ultrasound feedback. These modalities lack the expressive capabilities of high resolution screens, but are intended to allow drivers to focus on the driving task. A new form of haptic feedback — Cutaneous Push — was defined. Six solenoids were embedded along the rim of the steering wheel, creating three bumps under each palm. Studies 1, 2, and 3 investigated the efficacy of novel static and dynamic Cutaneous Push patterns, and their impact on driving performance. In simulated driving studies, the cutaneous patterns were tested. The results showed pattern identification rates of up to 81.3% for static patterns and 73.5% for dynamic patterns and 100% recognition of directional cues. Cutaneous Push notifications did not impact driving behaviour nor workload and showed very high user acceptance. Cutaneous Push patterns have the potential to make driving safer by providing non-visual and instantaneous messages, for example to indicate an approaching cyclist or obstacle. Studies 4 & 5 looked at novel uni- and bimodal feedback combinations of Visual, Auditory, Cutaneous Push, and Peripheral Lights for mid-air gestures and found that non-visual feedback modalities, especially when combined bimodally, offered just as much support for interaction without negatively affecting driving performance, visual attention and cognitive demand. These results provide compelling support for using non-visual feedback from in-car systems, supporting input whilst letting drivers focus on driving.Studies 6 & 7 investigated the above bimodal combinations as well as uni- and bimodal Ultrasound feedback during the Lane Change Task to assess the impact of gesturing and feedback modality on car control during more challenging driving. The results of study Seven suggests that Visual and Ultrasound feedback are not appropriate for in-car usage,unless combined multimodally. If Ultrasound is used unimodally it is more useful in a binary scenario.Findings from Studies 5, 6, and 7 suggest that multimodal feedback significantly reduces eyes-off-the-road time compared to Visual feedback without compromising driving performance or perceived user workload, thus it can potentially reduce crash risks. Novel design recommendations for providing feedback during mid-air gesture interaction in cars are provided, informed by the experiment findings

Ambient hues and audible cues: An approach to automotive user interface design using multi-modal feedback

The use of touchscreen interfaces for in-vehicle information, entertainment, and for the control of comfort settings is proliferating. Moreover, using these interfaces requires the same visual and manual resources needed for safe driving. Guided by much of the prevalent research in the areas of the human visual system, attention, and multimodal redundancy the Hues and Cues design paradigm was developed to make touchscreen automotive user interfaces more suitable to use while driving. This paradigm was applied to a prototype of an automotive user interface and evaluated with respects to driver performance using the dual-task, Lane Change Test (LCT). Each level of the design paradigm was evaluated in light of possible gender differences. The results of the repeated measures experiment suggests that when compared to interfaces without both the Hues and the Cues paradigm applied, the Hues and Cues interface requires less mental effort to operate, is more usable, and is more preferred. However, the results differ in the degradation in driver performance with interfaces that only have visual feedback resulting in better task times and significant gender differences in the driving task with interfaces that only have auditory feedback. Overall, the results reported show that the presentation of multimodal feedback can be useful in design automotive interfaces, but must be flexible enough to account for individual differences

Human–Machine Interface in Transport Systems: An Industrial Overview for More Extended Rail Applications

This paper provides an overview of Human Machine Interface (HMI) design and command systems in commercial or experimental operation across transport modes. It presents and comments on different HMIs from the perspective of vehicle automation equipment and simulators of different application domains. Considering the fields of cognition and automation, this investigation highlights human factors and the experiences of different industries according to industrial and literature reviews. Moreover, to better focus the objectives and extend the investigated industrial panorama, the analysis covers the most effective simulators in operation across various transport modes for the training of operators as well as research in the fields of safety and ergonomics. Special focus is given to new technologies that are potentially applicable in future train cabins, e.g., visual displays and haptic-shared controls. Finally, a synthesis of human factors and their limits regarding support for monitoring or driving assistance is propose

Computational Modeling and Experimental Research on Touchscreen Gestures, Audio/Speech Interaction, and Driving

As humans are exposed to rapidly evolving complex systems, there are growing needs for humans and systems to use multiple communication modalities such as auditory, vocal (or speech), gesture, or visual channels; thus, it is important to evaluate multimodal human-machine interactions in multitasking conditions so as to improve human performance and safety. However, traditional methods of evaluating human performance and safety rely on experimental settings using human subjects which require costly and time-consuming efforts to conduct. To minimize the limitations from the use of traditional usability tests, digital human models are often developed and used, and they also help us better understand underlying human mental processes to effectively improve safety and avoid mental overload. In this regard, I have combined computational cognitive modeling and experimental methods to study mental processes and identify differences in human performance/workload in various conditions, through this dissertation research. The computational cognitive models were implemented by extending the Queuing Network-Model Human Processor (QN-MHP) Architecture that enables simulation of human multi-task behaviors and multimodal interactions in human-machine systems. Three experiments were conducted to investigate human behaviors in multimodal and multitasking scenarios, combining the following three specific research aims that are to understand: (1) how humans use their finger movements to input information on touchscreen devices (i.e., touchscreen gestures), (2) how humans use auditory/vocal signals to interact with the machines (i.e., audio/speech interaction), and (3) how humans drive vehicles (i.e., driving controls). Future research applications of computational modeling and experimental research are also discussed. Scientifically, the results of this dissertation research make significant contributions to our better understanding of the nature of touchscreen gestures, audio/speech interaction, and driving controls in human-machine systems and whether they benefit or jeopardize human performance and safety in the multimodal and concurrent task environments. Moreover, in contrast to the previous models for multitasking scenarios mainly focusing on the visual processes, this study develops quantitative models of the combined effects of auditory, tactile, and visual factors on multitasking performance. From the practical impact perspective, the modeling work conducted in this research may help multimodal interface designers minimize the limitations of traditional usability tests and make quick design comparisons, less constrained by other time-consuming factors, such as developing prototypes and running human subjects. Furthermore, the research conducted in this dissertation may help identify which elements in the multimodal and multitasking scenarios increase workload and completion time, which can be used to reduce the number of accidents and injuries caused by distraction.PHDIndustrial & Operations EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/143903/1/heejinj_1.pd

Accessible Autonomy: Exploring Inclusive Autonomous Vehicle Design and Interaction for People who are Blind and Visually Impaired

Autonomous vehicles are poised to revolutionize independent travel for millions of people experiencing transportation-limiting visual impairments worldwide. However, the current trajectory of automotive technology is rife with roadblocks to accessible interaction and inclusion for this demographic. Inaccessible (visually dependent) interfaces and lack of information access throughout the trip are surmountable, yet nevertheless critical barriers to this potentially lifechanging technology. To address these challenges, the programmatic dissertation research presented here includes ten studies, three published papers, and three submitted papers in high impact outlets that together address accessibility across the complete trip of transportation. The first paper began with a thorough review of the fully autonomous vehicle (FAV) and blind and visually impaired (BVI) literature, as well as the underlying policy landscape. Results guided prejourney ridesharing needs among BVI users, which were addressed in paper two via a survey with (n=90) transit service drivers, interviews with (n=12) BVI users, and prototype design evaluations with (n=6) users, all contributing to the Autonomous Vehicle Assistant: an award-winning and accessible ridesharing app. A subsequent study with (n=12) users, presented in paper three, focused on prejourney mapping to provide critical information access in future FAVs. Accessible in-vehicle interactions were explored in the fourth paper through a survey with (n=187) BVI users. Results prioritized nonvisual information about the trip and indicated the importance of situational awareness. This effort informed the design and evaluation of an ultrasonic haptic HMI intended to promote situational awareness with (n=14) participants (paper five), leading to a novel gestural-audio interface with (n=23) users (paper six). Strong support from users across these studies suggested positive outcomes in pursuit of actionable situational awareness and control. Cumulative results from this dissertation research program represent, to our knowledge, the single most comprehensive approach to FAV BVI accessibility to date. By considering both pre-journey and in-vehicle accessibility, results pave the way for autonomous driving experiences that enable meaningful interaction for BVI users across the complete trip of transportation. This new mode of accessible travel is predicted to transform independent travel for millions of people with visual impairment, leading to increased independence, mobility, and quality of life

The selection and evaluation of a sensory technology for interaction in a warehouse environment

In recent years, Human-Computer Interaction (HCI) has become a significant part of modern life as it has improved human performance in the completion of daily tasks in using computerised systems. The increase in the variety of bio-sensing and wearable technologies on the market has propelled designers towards designing more efficient, effective and fully natural User-Interfaces (UI), such as the Brain-Computer Interface (BCI) and the Muscle-Computer Interface (MCI). BCI and MCI have been used for various purposes, such as controlling wheelchairs, piloting drones, providing alphanumeric inputs into a system and improving sports performance. Various challenges are experienced by workers in a warehouse environment. Because they often have to carry objects (referred to as hands-full) it is difficult to interact with traditional devices. Noise undeniably exists in some industrial environments and it is known as a major factor that causes communication problems. This has reduced the popularity of using verbal interfaces with computer applications, such as Warehouse Management Systems. Another factor that effects the performance of workers are action slips caused by a lack of concentration during, for example, routine picking activities. This can have a negative impact on job performance and allow a worker to incorrectly execute a task in a warehouse environment. This research project investigated the current challenges workers experience in a warehouse environment and the technologies utilised in this environment. The latest automation and identification systems and technologies are identified and discussed, specifically the technologies which have addressed known problems. Sensory technologies were identified that enable interaction between a human and a computerised warehouse environment. Biological and natural behaviours of humans which are applicable in the interaction with a computerised environment were described and discussed. The interactive behaviours included the visionary, auditory, speech production and physiological movement where other natural human behaviours such paying attention, action slips and the action of counting items were investigated. A number of modern sensory technologies, devices and techniques for HCI were identified with the aim of selecting and evaluating an appropriate sensory technology for MCI. iii MCI technologies enable a computer system to recognise hand and other gestures of a user, creating means of direct interaction between a user and a computer as they are able to detect specific features extracted from a specific biological or physiological activity. Thereafter, Machine Learning (ML) is applied in order to train a computer system to detect these features and convert them to a computer interface. An application of biomedical signals (bio-signals) in HCI using a MYO Armband for MCI is presented. An MCI prototype (MCIp) was developed and implemented to allow a user to provide input to an HCI, in a hands-free and hands-full situation. The MCIp was designed and developed to recognise the hand-finger gestures of a person when both hands are free or when holding an object, such a cardboard box. The MCIp applies an Artificial Neural Network (ANN) to classify features extracted from the surface Electromyography signals acquired by the MYO Armband around the forearm muscle. The MCIp provided the results of data classification for gesture recognition to an accuracy level of 34.87% with a hands-free situation. This was done by employing the ANN. The MCIp, furthermore, enabled users to provide numeric inputs to the MCIp system hands-full with an accuracy of 59.7% after a training session for each gesture of only 10 seconds. The results were obtained using eight participants. Similar experimentation with the MYO Armband has not been found to be reported in any literature at submission of this document. Based on this novel experimentation, the main contribution of this research study is a suggestion that the application of a MYO Armband, as a commercially available muscle-sensing device on the market, has the potential as an MCI to recognise the finger gestures hands-free and hands-full. An accurate MCI can increase the efficiency and effectiveness of an HCI tool when it is applied to different applications in a warehouse where noise and hands-full activities pose a challenge. Future work to improve its accuracy is proposed

The cockpit for the 21st century

Interactive surfaces are a growing trend in many domains. As one possible manifestation of Mark Weiser’s vision of ubiquitous and disappearing computers in everywhere objects, we see touchsensitive screens in many kinds of devices, such as smartphones, tablet computers and interactive tabletops. More advanced concepts of these have been an active research topic for many years. This has also influenced automotive cockpit development: concept cars and recent market releases show integrated touchscreens, growing in size. To meet the increasing information and interaction needs, interactive surfaces offer context-dependent functionality in combination with a direct input paradigm. However, interfaces in the car need to be operable while driving. Distraction, especially visual distraction from the driving task, can lead to critical situations if the sum of attentional demand emerging from both primary and secondary task overextends the available resources. So far, a touchscreen requires a lot of visual attention since its flat surface does not provide any haptic feedback. There have been approaches to make direct touch interaction accessible while driving for simple tasks. Outside the automotive domain, for example in office environments, concepts for sophisticated handling of large displays have already been introduced. Moreover, technological advances lead to new characteristics for interactive surfaces by enabling arbitrary surface shapes. In cars, two main characteristics for upcoming interactive surfaces are largeness and shape. On the one hand, spatial extension is not only increasing through larger displays, but also by taking objects in the surrounding into account for interaction. On the other hand, the flatness inherent in current screens can be overcome by upcoming technologies, and interactive surfaces can therefore provide haptically distinguishable surfaces. This thesis describes the systematic exploration of large and shaped interactive surfaces and analyzes their potential for interaction while driving. Therefore, different prototypes for each characteristic have been developed and evaluated in test settings suitable for their maturity level. Those prototypes were used to obtain subjective user feedback and objective data, to investigate effects on driving and glance behavior as well as usability and user experience. As a contribution, this thesis provides an analysis of the development of interactive surfaces in the car. Two characteristics, largeness and shape, are identified that can improve the interaction compared to conventional touchscreens. The presented studies show that large interactive surfaces can provide new and improved ways of interaction both in driver-only and driver-passenger situations. Furthermore, studies indicate a positive effect on visual distraction when additional static haptic feedback is provided by shaped interactive surfaces. Overall, various, non-exclusively applicable, interaction concepts prove the potential of interactive surfaces for the use in automotive cockpits, which is expected to be beneficial also in further environments where visual attention needs to be focused on additional tasks.Der Einsatz von interaktiven Oberflächen weitet sich mehr und mehr auf die unterschiedlichsten Lebensbereiche aus. Damit sind sie eine mögliche Ausprägung von Mark Weisers Vision der allgegenwärtigen Computer, die aus unserer direkten Wahrnehmung verschwinden. Bei einer Vielzahl von technischen Geräten des täglichen Lebens, wie Smartphones, Tablets oder interaktiven Tischen, sind berührungsempfindliche Oberflächen bereits heute in Benutzung. Schon seit vielen Jahren arbeiten Forscher an einer Weiterentwicklung der Technik, um ihre Vorteile auch in anderen Bereichen, wie beispielsweise der Interaktion zwischen Mensch und Automobil, nutzbar zu machen. Und das mit Erfolg: Interaktive Benutzeroberflächen werden mittlerweile serienmäßig in vielen Fahrzeugen eingesetzt. Der Einbau von immer größeren, in das Cockpit integrierten Touchscreens in Konzeptfahrzeuge zeigt, dass sich diese Entwicklung weiter in vollem Gange befindet. Interaktive Oberflächen ermöglichen das flexible Anzeigen von kontextsensitiven Inhalten und machen eine direkte Interaktion mit den Bildschirminhalten möglich. Auf diese Weise erfüllen sie die sich wandelnden Informations- und Interaktionsbedürfnisse in besonderem Maße. Beim Einsatz von Bedienschnittstellen im Fahrzeug ist die gefahrlose Benutzbarkeit während der Fahrt von besonderer Bedeutung. Insbesondere visuelle Ablenkung von der Fahraufgabe kann zu kritischen Situationen führen, wenn Primär- und Sekundäraufgaben mehr als die insgesamt verfügbare Aufmerksamkeit des Fahrers beanspruchen. Herkömmliche Touchscreens stellen dem Fahrer bisher lediglich eine flache Oberfläche bereit, die keinerlei haptische Rückmeldung bietet, weshalb deren Bedienung besonders viel visuelle Aufmerksamkeit erfordert. Verschiedene Ansätze ermöglichen dem Fahrer, direkte Touchinteraktion für einfache Aufgaben während der Fahrt zu nutzen. Außerhalb der Automobilindustrie, zum Beispiel für Büroarbeitsplätze, wurden bereits verschiedene Konzepte für eine komplexere Bedienung großer Bildschirme vorgestellt. Darüber hinaus führt der technologische Fortschritt zu neuen möglichen Ausprägungen interaktiver Oberflächen und erlaubt, diese beliebig zu formen. Für die nächste Generation von interaktiven Oberflächen im Fahrzeug wird vor allem an der Modifikation der Kategorien Größe und Form gearbeitet. Die Bedienschnittstelle wird nicht nur durch größere Bildschirme erweitert, sondern auch dadurch, dass Objekte wie Dekorleisten in die Interaktion einbezogen werden können. Andererseits heben aktuelle Technologieentwicklungen die Restriktion auf flache Oberflächen auf, so dass Touchscreens künftig ertastbare Strukturen aufweisen können. Diese Dissertation beschreibt die systematische Untersuchung großer und nicht-flacher interaktiver Oberflächen und analysiert ihr Potential für die Interaktion während der Fahrt. Dazu wurden für jede Charakteristik verschiedene Prototypen entwickelt und in Testumgebungen entsprechend ihres Reifegrads evaluiert. Auf diese Weise konnten subjektives Nutzerfeedback und objektive Daten erhoben, und die Effekte auf Fahr- und Blickverhalten sowie Nutzbarkeit untersucht werden. Diese Dissertation leistet den Beitrag einer Analyse der Entwicklung von interaktiven Oberflächen im Automobilbereich. Weiterhin werden die Aspekte Größe und Form untersucht, um mit ihrer Hilfe die Interaktion im Vergleich zu herkömmlichen Touchscreens zu verbessern. Die durchgeführten Studien belegen, dass große Flächen neue und verbesserte Bedienmöglichkeiten bieten können. Außerdem zeigt sich ein positiver Effekt auf die visuelle Ablenkung, wenn zusätzliches statisches, haptisches Feedback durch nicht-flache Oberflächen bereitgestellt wird. Zusammenfassend zeigen verschiedene, untereinander kombinierbare Interaktionskonzepte das Potential interaktiver Oberflächen für den automotiven Einsatz. Zudem können die Ergebnisse auch in anderen Bereichen Anwendung finden, in denen visuelle Aufmerksamkeit für andere Aufgaben benötigt wird

Space Station Human Factors Research Review. Volume 4: Inhouse Advanced Development and Research

A variety of human factors studies related to space station design are presented. Subjects include proximity operations and window design, spatial perceptual issues regarding displays, image management, workload research, spatial cognition, virtual interface, fault diagnosis in orbital refueling, and error tolerance and procedure aids