In-vehicle technology for self-driving cars: Advantages and challenges for aging drivers

The development of self-driving cars or autonomous vehicles has progressed at an unanticipated pace. Ironically, the driver or the driver-vehicle interaction is a largely neglected factor in the development of enabling technologies for autonomous vehicles. Therefore, this paper discusses the advantages and challenges faced by aging drivers with reference to in-vehicle technology for self-driving cars, on the basis of findings of recent studies. We summarize age-related characteristics of sensory, motor, and cognitive functions on the basis of extensive age-related research, which can provide a familiar to better aging drivers. Furthermore, we discuss some key aspects that need to be considered, such as familar to learnability, acceptance, and net effectiveness of new in-vehicle technology, as addressed in relevant studies. In addition, we present research-based examples on aging drivers and advanced technology, including a holistic approach that is being developed by MIT AgeLab, advanced navigation systems, and health monitoring systems. This paper anticipates many questions that may arise owing to the interaction of autonomous technologies with an older driver population. We expect the results of our study to be a foundation for further developments toward the consideration of needs of aging drivers while designing self-driving vehicles.Korea (South). Ministry of Trade, Industry and Energy (Technology Innovation Program 1004761)Kookmin University. Faculty Research ProgramNew England University Transportation CenterSantos Family Foundatio

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

License to Supervise:Influence of Driving Automation on Driver Licensing

To use highly automated vehicles while a driver remains responsible for safe driving, places new – yet demanding, requirements on the human operator. This is because the automation creates a gap between drivers’ responsibility and the human capabilities to take responsibility, especially for unexpected or time-critical transitions of control. This gap is not being addressed by current practises of driver licensing. Based on literature review, this research collects drivers’ requirements to enable safe transitions in control attuned to human capabilities. This knowledge is intended to help system developers and authorities to identify the requirements on human operators to (re)take responsibility for safe driving after automation

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

Enhancing user experience and safety in the context of automated driving through uncertainty communication

Operators of highly automated driving systems may exhibit behaviour characteristic of 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. Previous research has indicated that conveying system uncertainties may alleviate these issues. However, existing approaches require drivers to attend the uncertainty information with focal attention, likely resulting in missed changes when engaged in non-driving-related tasks. This research project expands on existing work regarding uncertainty communication in the context of automated driving. Specifically, it aims to investigate the implications of conveying uncertainties under consideration of non-driving-related tasks and, based on the outcomes, develop and evaluate an uncertainty display that enhances both user experience and driving safety. In a first step, the impact of visually conveying uncertainties was investigated under consideration of workload, trust, monitoring behaviour, non-driving-related tasks, takeover performance, and situation awareness. For this, an anthropomorphic visual uncertainty display located in the instrument cluster was developed. While the hypothesised benefits for trust calibration and situation awareness were confirmed, the results indicate that visually conveying uncertainties leads to an increased perceived effort due to a higher frequency of monitoring glances. Building on these findings, peripheral awareness displays were explored as a means for conveying uncertainties without the need for focused attention to reduce monitoring glances. As a prerequisite for developing such a display, a systematic literature review was conducted to identify evaluation methods and criteria, which were then coerced into a comprehensive framework. Grounded in this framework, a peripheral awareness display for uncertainty communication was developed and subsequently compared with the initially proposed visual anthropomorphic uncertainty display in a driving simulator study. Eye tracking and subjective workload data indicate that the peripheral awareness display reduces the monitoring effort relative to the visual display, while driving performance and trust data highlight that the benefits of uncertainty communication are maintained. Further, this research project addresses the implications of increasing the functional detail of uncertainty information. Results of a driving simulator study indicate that particularly workload should be considered when increasing the functional detail of uncertainty information. Expanding upon this approach, an augmented reality display concept was developed and a set of visual variables was explored in a forced choice sorting task to assess their ordinal characteristics. Particularly changes in colour hue and animation-based variables received high preference ratings and were ordered consistently from low to high uncertainty. This research project has contributed a series of novel insights and ideas to the field of human factors in automated driving. It confirmed that conveying uncertainties improves trust calibration and situation awareness, but highlighted that using a visual display lessens the positive effects. Addressing this shortcoming, a peripheral awareness display was designed applying a dedicated evaluation framework. Compared with the previously employed visual display, it decreased monitoring glances and, consequentially, perceived effort. Further, an augmented reality-based uncertainty display concept was developed to minimise the workload increments associated with increases in the functional detail of uncertainty information.</div

Effects of modality, urgency and situation on responses to multimodal warnings for drivers

Signifying road-related events with warnings can be highly beneficial, especially when imminent attention is needed. This thesis describes how modality, urgency and situation can influence driver responses to multimodal displays used as warnings. These displays utilise all combinations of audio, visual and tactile modalities, reflecting different urgency levels. In this way, a new rich set of cues is designed, conveying information multimodally, to enhance reactions during driving, which is a highly visual task. The importance of the signified events to driving is reflected in the warnings, and safety-critical or non-critical situations are communicated through the cues. Novel warning designs are considered, using both abstract displays, with no semantic association to the signified event, and language-based ones, using speech. These two cue designs are compared, to discover their strengths and weaknesses as car alerts. The situations in which the new cues are delivered are varied, by simulating both critical and non-critical events and both manual and autonomous car scenarios. A novel set of guidelines for using multimodal driver displays is finally provided, considering the modalities utilised, the urgency signified, and the situation simulated

Public Education about Occupant Protection Technologies and Protecting Occupants with Disabilities

Occupant protection is the foundation of any traffic safety program. According to National Highway Traffic Safety Administration (NHTSA) estimates, improvements in vehicle safety have helped increase the number of lives saved annually from 115 in 1960 to 27,621 in 2012. Therefore, educating drivers about advanced new technologies in vehicle occupant protection is very important. However, these technologies are not useful or efficient unless drivers are aware of them and use them accordingly. The purpose of this project was first to comprehensively review all the technologies related to occupant protection and also all the technologies related to occupant protection for people with disabilities using all available websites and related articles. Overall, 26 active safety technologies and 8 passive safety technologies were found regarding general occupant protection technologies. Also, 19 technologies were found related to occupant protection for people with disabilities. Another goal of this project was to promote a culture of safety through public education and training about occupant protection technologies, especially for people with disabilities. To reach this goal, two educational webinars about available technologies that protect occupants and people with disabilities were held. In both webinars, the research team tried to emphasize the importance of occupant protection by providing facts about the safety of passengers and drivers during a crash and the potential severity of injuries. The first webinar was held on April 15, 2022. The general occupant protection technologies in this webinar were categorized into two main categories: 1. Active Safety Technologies (e.g., Blind Sport Detection, Forward Collision Warning, etc.); and 2. Passive Safety Technologies (e.g., Airbags, Seatbelts, Belt bags, Child Safety Seats, etc.). In the end, a summary of the technologies was presented to the audience. Moreover, a section was dedicated to Q&A with the audience. Overall, 24 people joined the webinar. Some of the audience expressed their feelings about learning more about \u201cchild safety seats\u201d and other new safety technologies. Moreover, some participants mentioned that the webinar introduced them to new technologies such as backseat airbags, belt bags, and turn assist. Moreover, to educate Maryland drivers about the advantages of new occupant protection technologies, an informative fact sheet was developed by the research team and distributed online and through social media. The second webinar was held on September 16, 2022, and focused on occupant protection technologies for people with disabilities. The first section of the webinar was a review of all the general occupant protection technologies that were presented in the first webinar. The second part of the webinar was about occupant protection for people with disabilities. First, some facts about the challenges that people with disabilities face in transportation were mentioned. Then, occupant protection technologies for people with disabilities were categorized into four main sections: 1. Safety Technologies for Visual Impairment Drivers (e.g., bioptic glasses, AV cars, etc.); 2. Safety Technologies for Hearing Impairment Drivers (Audio-Tactile Conversion, Audio-Visual Conversion, etc.); 3. Safety Technologies for Physical Impairment Drivers (hand controls, steering, handicap accessible vehicles, etc.); and 4. Smartphone Applications that Help Drivers with Disabilities (e.g., Wheelmap, FuelService, etc.). In the end, a summary of all the technologies was presented to the audience. Again, a section was dedicated to Q&A with the audience. Overall, 44 people joined the webinar. Some of the audience expressed their feelings about learning more in-depth about \u201cWaymo AV cars\u201d and some additional new safety technologies

Proceedings of the Human Factors and Ergonomics Society Europe Chapter 2014 Annual Conference:Human Factors in high reliability industries

On the occasion of the 2014 Meeting in Lisbon, Portuga