890 research outputs found

    A user experience‐based toolset for automotive human‐machine interface technology development

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    The development of new automotive Human-Machine Interface (HMI) technologies must consider the competing and often conflicting demands of commercial value, User Experience (UX) and safety. Technology innovation offers manufacturers the opportunity to gain commercial advantage in a competitive and crowded marketplace, leading to an increase in the features and functionality available to the driver. User response to technology influences the perception of the brand as a whole, so it is important that in-vehicle systems provide a high-quality user experience. However, introducing new technologies into the car can also increase accident risk. The demands of usability and UX must therefore be balanced against the requirement for driver safety. Adopting a technology-focused business strategy carries a degree of risk, as most innovations fail before they reach the market. Obtaining clear and relevant information on the UX and safety of new technologies early in their development can help to inform and support robust product development (PD) decision making, improving product outcomes. In order to achieve this, manufacturers need processes and tools to evaluate new technologies, providing customer-focused data to drive development. This work details the development of an Evaluation Toolset for automotive HMI technologies encompassing safety-related functional metrics and UX measures. The Toolset consists of four elements: an evaluation protocol, based on methods identified from the Human Factors, UX and Sensory Science literature; a fixed-base driving simulator providing a context-rich, configurable evaluation environment, supporting both hardware and software-based technologies; a standardised simulation scenario providing a repeatable basis for technology evaluations, allowing comparisons across multiple technologies and studies; and a technology scorecard that collates and presents evaluation data to support PD decision making processes

    ELECTRONICALLY-VARIABLE AUTOMOTIVE SUSPENSION FOR HIGH PERFORMANCE VEHICLE

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    Vehicle suspension system plays a crucial role to ensure vehicle stability and ride comfort. A suspension system controls the vehicle body from excessive rolling and pitching while reduce the effect of shock forces from the road. Soft suspension system promotes good ride comfort while stiffer suspension promotes better car handling. Both comfort and good handling can be achieved by a variable suspension system. In the existing adjustable suspension unit, driver needs to stop the car, pop-up the hood and turn the selector knob manually to select the desired stiffness. By implementing a servo motor to replace the knob, the system now become an electronically – variable automotive suspension system that use motorized mechanism to control the suspension stiffness. With this system the driver can select suspension setting from inside the car while driving using touchscreen GUI. The system can have either selectable fixed-stiffness settings (fixed mode) or be made to respond to dynamic inputs - such as lateral G-force or vehicle speed – (adaptive mode), to become a semi-active suspension system

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

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    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

    Data-Driven Evaluation of In-Vehicle Information Systems

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    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

    Access to Personal Transportation for People with Disabilities with Autonomous Vehicles

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    The objective of this paper was to explore the potential of emerging technology of autonomous vehicles in accessible transportation and incorporate these findings a standardized transportation solution that readily accommodates future travelers with disabilities based on careful study on current trends in accessible transportation and interviews and surveys that were conducted as a part of this effort. The suggested solution and design principles associated with it took in account, the popular opinions of people with disabilities as well as various experts in the field of accessible transportation. The presented solution is based on emerging technology that is being actively pursued by the automotive industry and research institutions and seriously being considered through current and pending state legislation as a viable product in the near future. This paper explores the legal, technical and safety obstacles that lay in the path to making this a reality

    The cockpit for the 21st century

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    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 OberflĂ€chen weitet sich mehr und mehr auf die unterschiedlichsten Lebensbereiche aus. Damit sind sie eine mögliche AusprĂ€gung von Mark Weisers Vision der allgegenwĂ€rtigen Computer, die aus unserer direkten Wahrnehmung verschwinden. Bei einer Vielzahl von technischen GerĂ€ten des tĂ€glichen Lebens, wie Smartphones, Tablets oder interaktiven Tischen, sind berĂŒhrungsempfindliche OberflĂ€chen 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 BenutzeroberflĂ€chen werden mittlerweile serienmĂ€ĂŸig in vielen Fahrzeugen eingesetzt. Der Einbau von immer grĂ¶ĂŸeren, in das Cockpit integrierten Touchscreens in Konzeptfahrzeuge zeigt, dass sich diese Entwicklung weiter in vollem Gange befindet. Interaktive OberflĂ€chen ermöglichen das flexible Anzeigen von kontextsensitiven Inhalten und machen eine direkte Interaktion mit den Bildschirminhalten möglich. Auf diese Weise erfĂŒllen sie die sich wandelnden Informations- und InteraktionsbedĂŒrfnisse in besonderem Maße. Beim Einsatz von Bedienschnittstellen im Fahrzeug ist die gefahrlose Benutzbarkeit wĂ€hrend der Fahrt von besonderer Bedeutung. Insbesondere visuelle Ablenkung von der Fahraufgabe kann zu kritischen Situationen fĂŒhren, wenn PrimĂ€r- und SekundĂ€raufgaben mehr als die insgesamt verfĂŒgbare Aufmerksamkeit des Fahrers beanspruchen. Herkömmliche Touchscreens stellen dem Fahrer bisher lediglich eine flache OberflĂ€che bereit, die keinerlei haptische RĂŒckmeldung bietet, weshalb deren Bedienung besonders viel visuelle Aufmerksamkeit erfordert. Verschiedene AnsĂ€tze ermöglichen dem Fahrer, direkte Touchinteraktion fĂŒr einfache Aufgaben wĂ€hrend der Fahrt zu nutzen. Außerhalb der Automobilindustrie, zum Beispiel fĂŒr BĂŒroarbeitsplĂ€tze, wurden bereits verschiedene Konzepte fĂŒr eine komplexere Bedienung großer Bildschirme vorgestellt. DarĂŒber hinaus fĂŒhrt der technologische Fortschritt zu neuen möglichen AusprĂ€gungen interaktiver OberflĂ€chen und erlaubt, diese beliebig zu formen. FĂŒr die nĂ€chste Generation von interaktiven OberflĂ€chen im Fahrzeug wird vor allem an der Modifikation der Kategorien GrĂ¶ĂŸe und Form gearbeitet. Die Bedienschnittstelle wird nicht nur durch grĂ¶ĂŸere Bildschirme erweitert, sondern auch dadurch, dass Objekte wie Dekorleisten in die Interaktion einbezogen werden können. Andererseits heben aktuelle Technologieentwicklungen die Restriktion auf flache OberflĂ€chen auf, so dass Touchscreens kĂŒnftig ertastbare Strukturen aufweisen können. Diese Dissertation beschreibt die systematische Untersuchung großer und nicht-flacher interaktiver OberflĂ€chen und analysiert ihr Potential fĂŒr die Interaktion wĂ€hrend der Fahrt. Dazu wurden fĂŒr 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 OberflĂ€chen im Automobilbereich. Weiterhin werden die Aspekte GrĂ¶ĂŸe und Form untersucht, um mit ihrer Hilfe die Interaktion im Vergleich zu herkömmlichen Touchscreens zu verbessern. Die durchgefĂŒhrten Studien belegen, dass große FlĂ€chen neue und verbesserte Bedienmöglichkeiten bieten können. Außerdem zeigt sich ein positiver Effekt auf die visuelle Ablenkung, wenn zusĂ€tzliches statisches, haptisches Feedback durch nicht-flache OberflĂ€chen bereitgestellt wird. Zusammenfassend zeigen verschiedene, untereinander kombinierbare Interaktionskonzepte das Potential interaktiver OberflĂ€chen fĂŒr den automotiven Einsatz. Zudem können die Ergebnisse auch in anderen Bereichen Anwendung finden, in denen visuelle Aufmerksamkeit fĂŒr andere Aufgaben benötigt wird

    Real time embedded software system on a heterogeneous Digital Signal Processor and RISC processor architecture

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    International audienceThis paper discusses a generic telematics systems based on the OMAPTM (open multimedia application platform)heterogeneous ARMTM/DSP multiprocessor system. These 2 processors are integrated as SOC (system on chip)with a peripheral mix dedicated to the automotive requirements as a one chip solution. These processors are ableto run parallel various real time applications optimized either for the DSP or the ARM-RISC processor or sharedbetween both processors
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