Unraveling Subjective ADAS Comprehension Considering Factors of Situational Complexity on the Example of Traffic Light ScenariosAdvanced driver assistance systems (ADAS) with increasing automation maturity and availability in urban contexts are entering the market. Meanwhile, the situational context has been identified to play a crucial role in system comprehension and usage, yet its subcomponents and their relation to system comprehension remain an open research question. To gain insights in the role of the situation complexity regarding subjective system comprehension and different methodological aspects, this study applies a mixed quantitative and qualitative approach, focusing on signaled intersections as an exemplary scenario. An on-road study with forty-six participants was conducted, involving six traffic light scenarios (all experienced twice). Results indicate that while comprehension was generally high, the situational context, including environmental and traffic-related factors, affected subjective system understanding. The proposed approach sheds light on the role of mixed methods in ADAS research, which may provide insights for system developers and suggestions for user training content.2025CBClaudia Buchner et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)AutoUI
Exploring Urban Challenges: Understanding Advanced Driver Assistance Systems in Different Situational ContextsNew Advanced Driver Assistance Systems (ADAS) are now available to support urban driving. To adequately use ADAS, especially in complex situations, drivers must comprehend them. An on-road study was conducted to investigate the mental model development while interacting with a state-of-the-art ADAS in both a rural (less complex) and an urban context (more complex). Forty-six participants experienced two rounds of each context. After each round, drivers rated their mental model, acceptance, and trust. Results indicate that for the rural context participants learned the system functionality in the first round without further improvement . In the urban context the mental model was generally less accurate, but improved in the second round. Trust increased from the first to the second rural round while acceptance did not show a significant change within the context. The results provide a first glimpse into the importance of evaluating different contexts and interaction scenarios for ADAS.2024CBClaudia Buchner et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)AutoUI
Improving Driver Engagement with Level 2 Automated Systems: The Impact of Fully Shared Longitudinal ControlAccording to the Society of Automotive Engineers (SAE), in Level 2 systems (L2 systems), the system executes the longitudinal and lateral control of the vehicle, with the driver required to monitor the environment and intervene when necessary. To further improve safety and driver engagement, we compared a fully shared longitudinal control system, which permits speed adjustments via acceleration and braking without deactivation, with a conventional system that disengages upon braking. In a simulator study involving 61 participants, both systems were well-received in terms of acceptance and user experience. The fully shared longitudinal control led to more frequent and earlier braking, suggesting anticipatory driving, without compromising perceived safety. Furthermore, it outperformed in hedonic qualities of user experience, and elicited a stronger intention to use. Our findings indicate that fully shared longitudinal control can enhance driver engagement, offering a valuable improvement for L2 automated systems.2024JIJohannes Illgner et al.Automated Driving Interface & Takeover DesignHead-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)AutoUI
Driven to Distraction: Exploring Mind Wandering During a Virtual Reality City DriveResearch has characterized mind-wandering as humans' natural mental state, with moments of task-focused attention being the exception. With this framing, mind-wandering while driving likely occurs more than generally acknowledged, and seems poised to increase with higher levels of automation. This in turn may have adverse effects on drivers' abilities to regain situation awareness or resume control when needed. Of the prior work on detecting mind-wandering while driving, none focuses on automation or complex urban environments. We ran an exploratory study (N=14) of an automated drive through New York City in a two-dimensional virtual reality context, focusing on physiological measures such as gaze distribution, pupillometry, and heart rate. We also explored how drivers missing critical events may be a potential new measure. Results varied between focused and mind-wandering mental states and between moving and stopped driving contexts. These observations are an initial step toward understanding mind-wandering across diverse driving scenarios.2024RCRebecca Currano et al.Automated Driving Interface & Takeover DesignEye Tracking & Gaze InteractionAutoUI
Listening to the Voices: Describing Ethical Caveats of Conversational User Interfaces According to Experts and Frequent UsersAdvances in natural language processing and understanding have led to a rapid growth in the popularity of conversational user interfaces (CUIs). While CUIs introduce novel benefits, they also yield risks that may exploit people's trust. Although research looking at unethical design deployed through graphical user interfaces (GUIs) established a thorough taxonomy of so-called dark patterns, there is a need for an equally in-depth understanding in the context of CUIs. Addressing this gap, we interviewed 27 participants from three cohorts: researchers, practitioners, and frequent users of CUIs. Applying thematic analysis, we develop five themes reflecting each cohort's insights about ethical design challenges and introduce the CUI Expectation Cycle, bridging system capabilities and user expectations while respecting each theme's ethical caveats. This research aims to inform future work to consider ethical constraints while adopting a human-centred approach.2024TMThomas Mildner et al.University of BremenVoice User Interface (VUI) DesignAI Ethics, Fairness & AccountabilityDark Patterns RecognitionCHI
Investigating Hazard Notifications for Cyclists in Mixed Reality: A Comparative Analysis with a Test Track StudyOne way to improve road safety for cyclists is the development of hazard notification systems. Instead of in field experiments, such systems could be tested in safe and more controlled simulated environments; however, their validity needs verification. We evaluated the validity of mixed reality (MR) simulation for bicycle support systems notifying of dooring hazards. In a mixed-design study (N=43) with environment type(MR/test track) as within and hazard notifications (with/without) as between factor, comparing subjective and objective measures across environments. In conclusion, MR simulation is absolutely valid for user experience and perceived safety and relatively valid for workload, standard deviation of lateral position, and speed. However, MR simulation was not valid for lateral distance, as participants cycled more in the center of the street than on the test track, perhaps to avoid simulator sickness. Thus, we conclude that MR simulation is valuable for studying bicycle safety.2023TSTamara von Sawitzky et al.External HMI (eHMI) — Communication with Pedestrians & CyclistsV2X (Vehicle-to-Everything) Communication DesignAutoUI
Development of a Perceived Security Scale for Shared Automated Vehicles (PSSAVS) and its Validation in Colombia and GermanyPerceived security is crucial for the widespread adoption of shared automated vehicles (SAVs) and shuttle buses. However, there is currently no validated instrument to measure perceived security in this context, and little research has been done to determine the factors that contribute to perceived security. We propose the Perceived Security Scale for Shared Automated Vehicles (PSSAV), a questionnaire that assesses various aspects of perceived security in SAVs. The scale was evaluated using an exploratory, data-driven approach in a pilot study with 60 German participants, and a main study with 114 German and 101 Colombian participants experiencing a positive or negative ride in an automated shuttle bus (between-subjects design) presented as videos in an online study. The results suggest that trust, privacy, and control are key factors that influence security in the context of SAVs. The PSSAV questionnaire is reliable and sensitive to manipulation, indicating its construct validity.2023MSMartina Schuß et al.Automated Driving Interface & Takeover DesignMotion Sickness & Passenger ExperienceAutoUI
Investigating Various Dynamics in the Box Task Combined With a Detection Response Task: Are There Performance Differences Between Uniform and Non-uniform Box Dynamics?The Box Task combined with a Detection Response Task (BT + DRT) is a relatively less investigated but promising method for evaluating visual-manual and cognitive task demand due to the interaction with in-vehicle information systems while driving. The BT includes the tracking of a dynamic box whose size and position follow a sinusoidal pattern with uniform amplitudes and frequencies. However, it is unclear whether participants are able to predict and adapt to these uniform dynamics, which might lead to a reduced sensitivity of the BT + DRT. Within the present study, it was aimed to examine differences in BT + DRT performance depending on uniform and non-uniform BT dynamics. A laboratory study was conducted with N = 41 participants. The experimental conditions differed in the type and difficulty level of the secondary tasks as well as in the BT dynamics (uniform, varying amplitude, varying frequency). While the uniform BT dynamics could be more predictable, the non-uniform BT dynamics were designed slightly easier in their difficulty using a lower frequency or amplitude. The results revealed no performance benefits when performing uniform BT dynamics compared to non-uniform BT dynamics. The frequency BT condition was related to a significantly lower variability of box position and higher gaze duration on the secondary task compared to the uniform BT dynamics. These findings suggest that participants are not or only negligible able to adapt to the uniform BT dynamics. Therefore, it is recommended to use the uniform BT dynamics as suggested and implemented in previous studies.2023DTDaniel Trommler et al.Head-Up Display (HUD) & Advanced Driver Assistance Systems (ADAS)Eye Tracking & Gaze InteractionAutoUI
Measuring user experience in automated driving: Developing a single-item measure Measuring user experience is highly important for human-centered development and thus for designing automated driving systems. Multi-item measures such as the System Usability Scale (SUS) or the Usability Metric for User Experience (UMUX) are commonly used for collecting user feedback on technical systems or products. The goal of the present study was to investigate the potentials of a single-item approach as an economic alternative for measuring user experience compared to multi-item scales. Therefore, a single-item measure was developed to assess both event-related and cumulative user experience in automated driving. User experience was manipulated in a between-subject design implemented in a real-world driving task and feedback was collected using the newly developed Single Item User Experience (SIUX) scale, the UMUX, and the SUS. Results indicate that the SIUX scale is more sensitive than the UMUX to differences in event-related user experience, but not in cumulative user experience. Both the SIUX and the UMUX were more sensitive than the SUS when measuring differences in cumulative user experience. Future studies should be aimed at investigating the applicability of the SIUX scale to domains other than automated driving and at collecting more extensive data on validity and reliability of all three instruments.2021CHChantal Himmels et al.Automated Driving Interface & Takeover DesignPrivacy by Design & User ControlUser Research Methods (Interviews, Surveys, Observation)AutoUI
How to Design the Perfect Prompt: A Linguistic Approach to Prompt Design in Automotive Voice Assistants – An Exploratory StudyIn-vehicle voice user interfaces (VUIs) are becoming increasingly popular while needing to handle more and more complex functions. While many guidelines exist in terms of dialog design, a methodical and encompassing approach to prompt design is absent in the scientific landscape. The present work closes this gap by providing such an approach in form of linguistic-centered research. By extracting syntactical, lexical, and grammatical parameters from a German contemporary grammar, we examine how their respective manifestations affect users’ perception of a given system output across different prompt types. Through exploratory studies with a total of 1,206 participants, we provide concrete best practices to optimize and refine the design of VUI prompts. Based on these best practices, three superordinate user needs regarding prompt design can be identified: a) a suitable level of (in)formality, b) a suitable level of complexity/simplicity, and c) a suitable level of (im)mediacy.2021AMAnna-Maria Meck et al.Voice User Interface (VUI) DesignIntelligent Voice Assistants (Alexa, Siri, etc.)AutoUI
What makes an automated vehicle a good driver? Exploring lane change announcements in dense traffic situations.An automated vehicle needs to learn how human road users experience the intentions of other drivers and understand how they communicate with each other in order to avoid misunderstandings and prevent giving a negative external image during interactions. The aim of the present study is to identify a cooperative lane change indication which other drivers understand unambiguously and prefer when it comes to lane change announcements in a dense traffic situation on the highway. A fixed-base driving simulator study is conducted with N = 66 participants in Germany in a car-following scenario. Participants rated, from the lag driver’s perspective, different lane change announcements of another driver which varied in lateral movements (i.e., duration, lateral offset). Main findings indicate that a medium offset and moderate duration of lateral movement is experienced as most cooperative. The results are crucial for the development of lane change strategies for automated vehicles.2018NKNina Kauffmann et al.BMW GroupAutomated Driving Interface & Takeover DesignV2X (Vehicle-to-Everything) Communication DesignCHI
P3 - How Usability Can Save the Day – Methodological Considerations for Making Automated Driving a Success StoryIt will not be long until Level 3 Automated Driving Systems (L3 ADS) enter the consumer market. An important role corresponds to methodology development. The present paper gives impetus to the process of developing robust methods for evaluating Human-Machine Interfaces (HMI) for L3 ADS. First, a literature review on automotive interfaces concerning methodology application is outlined showing that studies often lack to provide both self-report and observational data. To derive a comprehensive image of HMI quality, we recommend multi-method approach in user research. Subsequently, we provide an overview of state-of-the-art self-report and observational measures. From the availability of measures and the necessity to include both in user studies, the issue of the performance-preference dissociation arises. It threatens study designs and interpretation of results. Following methodological recommendations from the present work supports researchers and practitioners in the area of automated driving for proper study design and interpretation of study results.2018YFYannick Forster et al.Automated Driving Interface & Takeover DesignAutoUI
Calibration of Trust Expectancies in Conditionally Automated Driving by Brand, Reliability Information and Introductionary Videos: An Online StudyThe design of a priori information about a conditionally automated driving (CAD) function influences the extent of effective usage of this function. The present online study investigated the effects of preliminary reliability and brand information on trust and acceptance for CAD. N = 519 participants were randomly assigned to (1) a reliability condition (high or low) and (2) an original equipment manufacturer (OEM) reputation condition (i.e., above average, average, below average, baseline). To measure the effect of CAD experience, participants were additionally exposed to four short videos of a driver interacting with a CAD function. Study results provide first evidence for an influence of OEM branding and reliability on CAD evaluation. We observed a trend towards more favorable attitudes for high compared to low reliability. This effect depends on the respective OEM reputation. The findings hold implications for the design of communication on automated vehicles to calibrate a priori assessment.2018YFYannick Forster et al.Automated Driving Interface & Takeover DesignAI-Assisted Decision-Making & AutomationAutoUI