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

The decline of user experience in transition from automated driving to manual driving

Automated driving technologies are rapidly being developed. However, until vehicles are fully automated, the control of the dynamic driving task will be shifted between the driver and automated driving system. This paper aims to explore how transitions from automated driving to manual driving affect user experience and how that experience correlates to take-over performance. In the study 20 participants experienced using an automated driving system during rush-hour traffic in the San Francisco Bay Area, CA, USA. The automated driving system was available in congested traffic situations and when active, the participants could engage in non-driving related activities. The participants were interviewed afterwards regarding their experience of the transitions. The findings show that most of the participants experienced the transition from automated driving to manual driving as negative. Their user experience seems to be shaped by several reasons that differ in temporality and are derived from different phases during the transition process. The results regarding correlation between participants’ experience and take-over performance are inconclusive, but some trends were identified. The study highlights the need for new design solutions that do not only improve drivers’ take-over performance, but also enhance user experience during take-over requests from automated to manual driving

Individual Differences and Expectations of Automated Vehicles

Despite the benefits of automated vehicles (AVs), there are still barriers to their widespread adoption. Expectations about AVs have been identified as one of the most important factors in understanding AV adoption. Therefore, by understanding the public's expectations of AVs, we can better understand whether or when AVs are likely to be adopted on a wide scale. Individual differences, including demographics and personality, have been identified as factors that impact technology expectations and adoption. However, it is not clear whether and how individual differences can influence expectations of AVs. To examine this, we conducted an online survey with 443 U.S. drivers who were recruited and divided into subpopulations by age, gender, ethnicity, census region, educational level, marital status, income, driving frequency, driving experience, and personality traits. Results revealed that drivers' expectations of AVs differ significantly by age, gender, ethnicity, education levels, marital status, drive frequency, drive experience, and personality. More specifically, higher expectations are more often generated by drivers who are younger, men, White non-Hispanic, more highly educated, never married, with a higher frequency of driving, with less driving experience, and who are high in extraversion, agreeableness, conscientiousness, and emotional stability. The results of this study provide a foundation for future research related to expectations and have important implications on future design and development of AVs.McityPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/168566/1/Zhang et al. 2021 IJHCI.pdfDescription of Zhang et al. 2021 IJHCI.pdf : PreprintSEL

Driver’s Age and Automated Vehicle Explanations

Automated Vehicles (AV) have the potential to benefit our society. However, a lack of trust is a major barrier to the adoption of AVs. Providing explanations is one approach to facilitating AV trust by decreasing uncertainty about AV's decision-making and action. However, explanations might increase drivers’ cognitive effort and anxiety. Because of differences in cognitive ability across age groups, it is not clear whether explanations are equally beneficial for drivers across age groups in terms of trust, effort, and anxiety. To examine this, we conducted a mixed-design experiment with 40 participants divided into three age groups (i.e., younger, middle-age, and older). Participants were presented with: (1) no explanation, or (2) explanation given before or (3) after the AV took action, or (4) explanation along with a request for permission to take action. Results suggest that the explanations provided before AV take actions produced the highest trust and lowest effort for all drivers regardless of age group. The request-for-permission condition led to the highest trust and lowest effort only for older drivers. Younger drivers had the lowest anxiety and effort under the AV-explanation-after-action condition; however, this condition produced the highest level of anxiety and effort in middle-age and older drivers, respectively. These results have important implications in designing AV explanations and promoting trust.University of Michigan McityPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/166295/1/Zhang et al. 2021 [Final paper]-sustainability-0202.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/166295/3/Zhang et al. 2021.pdfDescription of Zhang et al. 2021 [Final paper]-sustainability-0202.pdf : PreprintSEL

Older Adults, New Mobility, and Automated Vehicles

58 pagesThe premise that autonomous vehicles will address older adults’ immobility is not a given. As argued in the Public Policy Institute’s publication Universal Mobility-as-a-Service, public- and private-sector actors need to come together to create a set of supportive circumstances that enable us to harness emerging technology for individual and societal benefit. This paper and associated framework lays out the myriad and interconnected factors that all stakeholders in this space should be thinking about so that the promise of autonomous vehicles and new shared-use mobility opportunities can be realized. The framework can be used as a checklist of design considerations for AV pilot testing, and it also may inform research and development programs. Moreover, it can provide an easy-to-consult reference for policymakers as they define roles and responsibilities among public- and privatesector actors whose actions can enable equitable access—or result in greater inequity. This research reveals a perennial flaw in our technology adoption process, at least in the mobility arena: the current default of designing for a broad clientele of mobile individuals is insufficient. The framework identified in this report is an important but only preliminary step to ensuring that the needs of harder-to-serve populations, such as frail older adults and people with mobility disabilities, are met. Additional, more tailored activity is needed. AARP looks forward to advancing this work

Mobility in the Advent of Autonomous Driving – Toward an Understanding of User Acceptance and Quality Perception Factors

Recent advancements in intelligent technologies and sensor-based data collections pave the way for autonomous driving and facilitate a radical transformation of today’s mobility. Based on auspicious market projections, traditional automotive manufacturers and technology companies invest heavily in the development of autonomous vehicles (AVs). In addition to the profits that the industry expects from self-driving vehicles, this new type of mobility should also solve societal issues like reducing traffic accidents and fatalities by eliminating human driving errors. More efficient autonomous driving is expected to bring improvements in terms of fewer congestions and less fuel consumption, thereby reducing greenhouse emissions. Besides, AVs pledge to entail advantages for their users. Specifically, they increase mobility for the disabled and the older generation. In contrast, younger passengers associate autonomous driving with improved productivity and an enhanced hedonic experience as non-driving activities, such as working or watching a movie, are made possible. Contrary to the above expectations, people also raise concerns regarding self-driving vehicles. They are worried about whether the sensors and systems can correctly interpret complex environmental conditions. Above all, there are doubts whether the technology, even being intelligent, can react appropriately in critical traffic situations made up of humans who sometimes behave unpredictably. In case of unavoidable traffic accidents, ethical questions come into play regarding how the vehicle makes decisions that could result in a person being injured or killed. Finally, the new and sophisticated technology could have vulnerabilities that can be exploited by cybercriminals or allow unauthorized third parties to obtain passenger data. Motivated by the anticipated improvements that AVs entail and the breadth of factors that might influence their adoption, a large body of research investigating relevant adoption factors has accumulated. In order to collect, organize, and combine extant findings, research paper A conducts a structured literature review on the acceptance of autonomous vehicles. Based on 58 articles, it develops an AV acceptance framework consisting of individual user characteristics, vehicle characteristics, and political/societal elements. The framework indicates for each factor whether available research results identify the effect as either positively or negatively significant. Thereby, the paper also sheds light on diverging construct operationalizations, aiming to support researchers in comparing available findings. Eventually, paper A proposes future research avenues across various themes and methods, which build a foundation for further research pursued in this dissertation’s subsequent papers. However, solely balancing significant against non-significant results can come to wrong conclusions since the sample size alone can lead to varying significance levels. Because of this, paper B builds on the literature review and conducts a meta-analysis to include further quantitative analyses. It calculates the mean effect sizes for each AV acceptance factor based on published research results. By doing so, the paper identifies attitude, perceived usefulness, efficiency, trust in AVs, safety, and subjective norms to correlate most strongly with the behavioral intention to use an automated car. A subsequent moderator-analysis shows that almost all acceptance factors are influenced by the study’s methodology and location, the AV’s level of automation, and the examined ownership model, i.e., private cars, car sharing, or public transport. In doing so, paper B observes that most of the available research is on privately owned AVs and hence lacks to assess public as well as shared automated mobility. To fill this gap, paper C investigates characteristics relevant for automated mobility as a service (AMaaS). Based on 23 exploratory interviews with the general public, the paper derives a set of AMaaS requirements. Mobility experts sort these requirements based on commonalities so that a cluster analysis can conceptualize the expected AMaaS characteristics from a practitioner’s view. The paper identifies traffic safety, information privacy, cybersecurity, regulations, flexibility, accessibility, efficiency, and convenience to be relevant service characteristics. It discusses each required characteristic and thereby delineates the constructs’ scopes so that subsequent research can build appropriate measurement instruments. Besides, paper C discovers strongly diverging priorities regarding the respective service characteristics when comparing the potential users’ conversation shares with the experts’ relevance ratings. Paper D builds on the qualitative results of paper C as it develops and validates a hierarchical quality scale for AMaaS. The paper proposes a theoretical model and operationalizes the previously identified service characteristics. Throughout multiple empirical studies with 1,431 participants, the proposed quality scale is refined iteratively until satisfactory psychometric properties are achieved. Nomological validity ensures the scale’s predictability. Paper D progresses research from focussing on the mere acceptance of autonomous driving to the user’s quality perception, which significantly influences user satisfaction and the success of AMaaS. This, in turn, is necessary to realize the promised benefits of autonomous driving in a sustainable manner

Autonome Shuttlebusse im ÖPNV

Automatisiertes Fahren wird aktuell auf allen Ebenen diskutiert. Dieses Open Access Buch greift das Thema aus Sicht des ÖPNV auf und stellt Chancen und Risiken des Einsatzes automatisierter Shuttlebusse im Nahverkehr dar. Am Beispiel Bad Birnbach/Niederbayern wird gezeigt, welche Herausforderungen bei der Einführung eines solchen Services zu erwarten sind und wie diese gelöst werden können. Dabei fokussiert sich das Buch auf die Vermittlung von im Feld erhobenen Daten, z.B. zu technischen Schwierigkeiten, Erfahrungsberichten von Anwohnern und Gästen, Akzeptanz in der Bevölkerung, infrastrukturellen Anforderungen, etc. Konkrete Handlungsempfehlungen für Städteplaner, ÖPNV-Betreiber/-Strategen oder Kommunen, die eine Einführung automatisierter Busse in Erwägung ziehen, runden das Werk ab

Autonome Shuttlebusse im ÖPNV

Automatisiertes Fahren wird aktuell auf allen Ebenen diskutiert. Dieses Open Access Buch greift das Thema aus Sicht des ÖPNV auf und stellt Chancen und Risiken des Einsatzes automatisierter Shuttlebusse im Nahverkehr dar. Am Beispiel Bad Birnbach/Niederbayern wird gezeigt, welche Herausforderungen bei der Einführung eines solchen Services zu erwarten sind und wie diese gelöst werden können. Dabei fokussiert sich das Buch auf die Vermittlung von im Feld erhobenen Daten, z.B. zu technischen Schwierigkeiten, Erfahrungsberichten von Anwohnern und Gästen, Akzeptanz in der Bevölkerung, infrastrukturellen Anforderungen, etc. Konkrete Handlungsempfehlungen für Städteplaner, ÖPNV-Betreiber/-Strategen oder Kommunen, die eine Einführung automatisierter Busse in Erwägung ziehen, runden das Werk ab