Inspired by the concepts of diminishing reality and ad-blocking in browsers, this study investigates the perceived benefits and concerns of blocking physical, real-world content, particularly ads, through Extended Reality (XR). To understand how users perceive this concept, we first conducted a user study (n=18) with an adblocking prototype to gather initial insights. The results revealed a mixed willingness to adopt XR blockers, with participants appreciating aspects such as customizability, convenience, and privacy. Expected benefits included enhanced focus and reduced stress, while concerns centered on missing important information and increased feelings of isolation. Hence, we investigated the user acceptance of different ad-blocking visualizations through a follow-up online survey (n=120), comparing six concepts based on related work. The results indicated that the XR ad-blocker visualizations play a significant role in how and for what kinds of advertisements such a concept might be used, paving the path for future feedback-driven prototyping.

Abstract Two-factor authentication (2FA) is an effective measure to safeguard against password attacks (e.g., guessing, credential stuffing). However, many existing 2FA methods are neither user-friendly nor protect adequately against phishing, particularly real-time (person-in-the-middle) attacks. We introduce BlueTOTP , a novel approach that leverages Bluetooth to automatically transmit time-based one-time passwords (TOTP) and verify the requesting domain before issuing the second factor. By reducing manual interactions and ensuring domain legitimacy, BlueTOTP streamlines the authentication process and mitigates phishing risks. We present the design and implementation of BlueTOTP, followed by an evaluation of its usability and performance. BlueTOTP not only improves the user experience during authentication but also significantly reduces the overall time required to complete 2FA authentication.

Multimodal interfaces increasingly blend voice, touch, and other inputs to enable natural interaction. However, transitions between modalities often introduce hidden cognitive costs not captured by traditional usability metrics. This Work-in-Progress paper presents the Modality-Switch Cognitive Cost (MSCC), a validated metric for quantifying the performance and workload penalties of switching between modalities. Building on an empirical study with 65 participants performing smart assistant tasks, we observed asymmetric switching costs, with Touch→Voice transitions producing higher cognitive load than Voice→Touch. We discuss MSCC as a foundation for adaptive multimodal design and outline ongoing work extending the metric to AR/VR and cross-device contexts.

Delivery robots are an emerging technology that promise benefits (reducing reliance on human-driven delivery vehicles and minimizing the impact of local traffic conditions). One limitation of such robots is their restricted range. A potential solution is to integrate these robots into existing public transport (PT) systems. One underexplored direction is extending their mobility through PT like buses. This scenario introduces distinct human–robot interaction (HRI) challenges: close physical proximity, shifting attention, implicit social norms, and multiple stakeholders occupying the same confined space.

There is great application potential for mobile robots that move along sidewalks, footpaths and cycle paths. At the same time, the legal framework for their operation is currently lacking, so that a realistic evaluation of the suitable characteristics of a robot, its behavior, and the resulting acceptance by the population is still pending. The currently running project RoboTraces aims to fill this gap and classifies the behavior of people during encounters with autonomous systems in everyday life. For this purpose, a multi-month study is currently being conducted in which a robot moves through Freiberg, a medium-size city with 40,000 inhabitants in Central Europe. We are recording the reactions of passers-by, classifying them according to the context of the situation and assessing their significance for the planning of movement corridors for small mobile systems.

Driving a car can be difficult when it comes to distractions caused by operating the in-vehicle infotainment system (IVIS). In-car passengers often help with performing IVIS-related tasks. However, an IVIS is often not designed with a focus on task collaboration. In this article, we focus on how to design in-car systems with the goal to support collaboration between a driver and a front-seat passenger. Based on infotainment-oriented tasks, we initially explore five key collaborative control concepts by means of an IVIS which differ from each other in terms of the number of available IVIS screens (one or two), access to menus (restricted and unrestricted), and the nature of performing tasks in parallel or one after the other. Results from a simulator study with N = 16 pairs show significant effects of the concepts on social collaboration in terms of perceived social connectedness (measured with sub-dimensions connectedness, affiliation, belongingness, companionship), team performance (coordination effectiveness and team cohesion), and fairness. We found that especially a dedicated passenger IVIS screen empowers front-seat passengers, reduces power dynamics, supports fairness, and minimizes driver distraction (caused by interacting passengers). We discuss the implications of these findings and posit recommendations to design future IVIS in passenger cars with improved driver-passenger collaboration by explicitly designing for balanced power roles, situational awareness, active communication, and a balance between drivers’ privacy and trust toward the passenger. Additionally, we outline a systematic overview of future work to explore the research field of driver-passenger collaboration in more breadth and depth.

With the gradual transition towards assisted and automated driving, the car will transform into a more social environment where passengers and drivers engage in Non-Driving-Related Activities (NDRA). To support collaboration among occupants in future vehicles, research suggests interactive systems controlled by several users at once. In this paper, we explore five concepts for the collaborative performance of NDRA with the use-case of music playlist creation. While prior work investigated the effect on social connectedness, we expand insights towards team performance and fairness. Results from a mixed-subject experiment (N=27) show that the concepts have major consequences on team performance and fairness. Certain concepts can promote or hinder coordination effectiveness and, in turn, impact intra-vehicular collaboration. Our observations also indicate that fairness is key to fostering social collaboration in AVs, while it does not naturally define a high team performance. Subsequently, we provide recommendations to guide future designs of collaborative NDRAs in vehicles.

Automated vehicles (AVs) are expected to enable users to engage in non-driving-related activities (NDRAs). However, users do not easily trust an automated vehicle which poses new challenges for automotive human-machine interfaces (HMIs). Over-presenting vehicle information can distract users from NDRAs, and under-presentation can impact trust and user experience (UX) negatively. To investigate how to best present vehicle information to foster users' trust and UX while performing NDRAs, we designed two in-vehicle HMI concepts: 1) A colored and animated light bar display around the windshield and 2) a windshield display interface presenting pictograms and numbers. Results from a simulator study ($N=18$) indicate that both concepts contribute to a high trust level and UX while not affecting the NDRA performance compared to the baseline of not showing vehicle information. In addition, the light bar provides better UX than the windshield display and is also preferred by users. With our findings, we contribute to the effective design of presenting vehicle information in automated vehicles.

Current research on external Human-Machine Interfaces (eHMIs) in facilitating interactions between automated vehicles (AVs) and pedestrians have largely focused on one-to-one encounters. In order for eHMIs to be viable in reality, they need to be scalable, i.e., facilitate interaction with more than one pedestrian with clarity and unambiguity. We conducted a virtual-reality-based empirical study to evaluate four eHMI designs with two pedestrians. Results show that even in this minimum criteria of scalability, traditional eHMI designs struggle to communicate effectively whom the AV intends to yield to. Road-projection-based eHMIs show promise in clarifying the specific yielding intention of an AV, although it may still not be an ideal solution. The findings point towards the need to consider the element of scalability early in the design process, and potentially the need to reconsider the current paradigm of eHMI design.

Spatial computing devices that blend virtual and real worlds have the potential to soon become ubiquitous. Yet, creating experiences for spatial computing is non-trivial and needs skills in programming and 3D content creation, rendering them inaccessible to a wider group of users. We present SpatialProto, an in-situ spatial prototyping system for lowering the barrier to engage in spatial prototyping. With a depth-sensing capable mixed reality headset, SpatialProto lets users record animated objects of the real-world environment (e.g. paper, clay, people, or any other prop), extract only the relevant parts, and directly place and transform these recordings in their physical environment. We describe the design and implementation of SpatialProto, a user study evaluating the system’s prototype with non-expert users (n = 9), and demonstrate applications where multiple captures are fused for compelling augmented reality experiences.

Automated vehicles (AVs) are on the edge of being available on the mass market. Research often focuses on technical aspects of automation, such as computer vision, sensing, or artificial intelligence. Nevertheless, researchers also identified several challenges from a human perspective that need to be considered for a successful introduction of these technologies. In this paper, we first analyze human needs and system acceptance in the context of AVs. Then, based on a literature review, we provide a summary of current research on in-car driver-vehicle interaction and related human factor issues. This work helps researchers, designers, and practitioners to get an overview of the current state of the art.

Understanding user needs and behavior in automated vehicles (AVs) while traveling is essential for future in-vehicle interface and service design. Since AVs are not yet market-ready, current knowledge about AV use and perception is based on observations in other transportation modes, interviews, or surveys about the hypothetical situation. In this paper, we close this gap by presenting real-world insights into the attitude towards highly automated driving and non-driving-related activities (NDRAs). Using a Wizard of Oz AV, we conducted a real-world driving study (N = 12) with six rides per participant during multiple days. We provide insights into the users’ perceptions and behavior. We found that (1) the users’ trust a human driver more than a system, (2) safety is the main acceptance factor, and (3) the most popular NDRAs were being idle and the use of the smartphone.

External human-machine interfaces (eHMIs) support automated vehicles (AVs) in interacting with vulnerable road users such as pedestrians. While related work investigated various eHMIs concepts, these concepts communicate their message in one go at a single point in time. There are no empirical insights yet whether distance-dependent multi-step information that provides additional context as the vehicle approaches a pedestrian can increase the user experience. We conducted a video-based study (N = 24) with an eHMI concept that offers pedestrians information about the vehicle’s intent without providing any further context information, and compared it with two novel eHMI concepts that provide additional information when approaching the pedestrian. Results show that additional distance-based information on eHMIs for yielding vehicles enhances pedestrians’ comprehension of the vehicle’s intention and increases their willingness to cross. This insight posits the importance of distance-dependent information in the development of eHMIs to enhance the usability, acceptance, and safety of AVs.

In this paper, we investigate the effect of an external human-machine interface (eHMI) and a conspicuous external vehicle appearance due to visible sensors on pedestrian interactions with automated vehicles (AVs). Recent research shows that AVs may need to explicitly communicate with the environment due to the absence of a driver. Furthermore, in interaction situations, an AV that looks different and conspicuous owing to an extensive sensor system may potentially lead to hesitation stemming from mistrust in automation. Thus, we evaluated in a virtual reality study how pedestrian attitude, the presence/absence of an eHMI, and a conspicuous sensor system affect their willingness to cross the road. Results recommend the use of an eHMI. A conspicuous appearance of automated-driving capability had no effect for the sample as a whole, although it led to more efficient crossing decisions for those with a more negative attitude towards AVs. Our findings contribute towards the effective design of future AV interfaces.

In this paper, we report user preferences regarding color and animation patterns to support the interaction between Automated Vehicles (AVs) and pedestrians through an external Human-Machine-Interface (eHMI). Existing concepts of eHMI differ -- among other things -- in their use of colors or animations to express an AV's yielding intention. In the absence of empirical research, there is a knowledge gap regarding which color and animation leads to highest usability and preferences in traffic negotiation situations. We conducted an online survey (N=400) to investigate the comprehensibility of a light band eHMI with a combination of 5 color and 3 animation patterns for a yielding AV. Results show that cyan is considered a neutral color for communicating a yielding intention. Additionally, a uniformly flashing or pulsing animation is preferred compared to any pattern that animates sideways. These insights can contribute in the future design and standardization of eHMIs.

In this paper we present use cases for affective user interfaces (UIs) in cars and how they are perceived by potential users in China and Germany. Emotion-aware interaction is enabled by the improvement of ubiquitous sensing methods and provides potential benefits for both traffic safety and personal well-being. To promote the adoption of affective interaction at an international scale, we developed 20 mobile in-car use cases through an inter-cultural design approach and evaluated them with 65 drivers in Germany and China. Our data shows perceived benefits in specific areas of pragmatic quality as well as cultural differences, especially for socially interactive use cases. We also discuss general implications for future affective automotive UI. Our results provide a perspective on cultural peculiarities and a concrete starting point for practitioners and researchers working on emotion-aware interfaces.

This paper investigates personalized voice characters for in-car speech interfaces. In particular, we report on how we designed different personalities for voice assistants and compared them in a real world driving study. Voice assistants have become important for a wide range of use cases, yet current interfaces are using the same style of auditory response in every situation, despite varying user needs and personalities. To close this gap, we designed four assistant personalities (Friend, Admirer, Aunt, and Butler) and compared them to a baseline (Default) in a between-subject study in real traffic conditions. Our results show higher likability and trust for assistants that correctly match the user's personality while we observed lower likability, trust, satisfaction, and usefulness for incorrectly matched personalities, each in comparison with the Default character. We discuss design aspects for voice assistants in different automotive use cases.

Focusing on pedestrian safety in the era of automated vehicles, we investigate the interaction between pedestrians and automated cars. In particular, we investigate the influence of external car displays (ECDs) on pedestrians' crossing behavior, and the time needed to make a crossing decision. We present a study in a high-immersion VR environment comparing three alternative car-situated visualizations: a smiling grille, a traffic light style indicator, and a gesturing robotic driver. Crossing at non-designated crossing points on a straight road and at a junction, where vehicles turn towards the pedestrian, are explored. We report that ECDs significantly reduce pedestrians' decision time, and argue that ECDs support comfort, trust and acceptance in automated vehicles. We believe ECDs might become a valuable addition for future vehicles.

Current navigation systems for motor cyclists use visual or auditory cues for guidance. However, this poses a challenge to the motorcyclists since their visual and auditory channels are already occupied with controlling the motorbike, paying attention to other road users, and planing the next turn. In this work, we explore how tactile feedback can be used to guide motorcyclists. We present MOVING (MOtorbike VIbrational Navigation Guidance), a smart kidney belt that presents navigation cues through 12 vibration motors. In addition, we report on the design process of this wearable and on an evaluation with 16 participants in a real world riding setting. We show that MOVING outperforms off-the-shelf navigation systems in terms of turn errors and distraction.

In the near future we expect automated driving to be available for specific segments of a journey, e.g., when driving on the highway. At the end of such a route segment, a (planned) control transition from system to driver occurs. While immediate (unpredictable) take-over situations are heavily investigated, there is still a gap in understanding how to present planned take-over requests, especially while drivers might be involved in non-driving-related activities (NDRAs). We investigated the effect of three different visual representations to indicate planned take-over requests (TOR) on usability, comfort, and driving quality. Additionally, we explored the influences of different NDRAs and the device used for this activity. The results of our simulator study (N=24) indicate that (1) upcoming take-over requests should be displayed dynamically, (2) preferred devices depend on the performed task and (3) take-over requests should be presented with auditory, visual, and tactile cues. Based on our findings, we contribute design recommendations to support the development of safe and comfortable planned control transitions.

Various on-the-road situations can make additional demands on the driver that go beyond the basic demands of driving. Thereby, they influence the appropriateness of in-vehicle input modalities to operate secondary tasks in the car. In this work, we assess the specific impacts of situational demands on gaze, gesture and speech input regarding driving performance, interaction efficiency and subjective ratings. An experiment with 29 participants in a driving simulator revealed significant interactions between situational demands and the input modality on secondary task completion times, perceived suitability and cognitive workload. Impairments were greatest when the situational demand addressed the same sensory channel as the used input modality. This was reflected differently in objective and subjective data depending on the used input modality. With this work, we explore the performance of natural input modalities across different situations and thereby support interaction designers that plan to integrate these modalities in automotive interaction concepts.

Autonomous cars will likely hit the market soon, but trust into such a technology is one of the big discussion points in the public debate. Drivers who have always been in complete control of their car are expected to willingly hand over control and blindly trust a technology that could kill them. We argue that trust in autonomous driving can be increased by means of a driver interface that visualizes the car's interpretation of the current situation and its corresponding actions. To verify this, we compared different visualizations in a user study, overlaid to a driving scene: (1) a chauffeur avatar, (2) a world in miniature, and (3) a display of the car's indicators as the baseline. The world in miniature visualization increased trust the most. The human-like chauffeur avatar can also increase trust, however, we did not find a significant difference between the chauffeur and the baseline.

In this paper we chart a design space for conversational in-vehicle information systems (IVIS). Our work is motivated by the proliferation of speech interfaces in our everyday life, which have already found their way into consumer electronics and will most likely become pervasive in future cars.

The objective of this tutorial is to provide MobileHCI newcomers to the domain of automotive user interfaces (AutomotiveUI) with an introduction and overview of the field. The tutorial will introduce the specifics and challenges of in-vehicle user interfaces that set this field apart from others. With a clear focus on the integration of mobile devices into the car, we will provide an overview of the specific requirements of AutomotiveUI, discuss the design of such interfaces, also with regard to standards and guidelines. We further outline how to evaluate interfaces in the car, discuss the challenges with upcoming automated driving and present trends and challenges in this domain.

In this paper we present a design space for interactive windshield displays in vehicles and discuss how this design space can support designers in creating windshield applications for drivers, passengers, and pedestrians. Our work is motivated by numerous examples in other HCI-related areas where seminal design space papers served as a valuable basis to evolve the respective field -- most notably mobile devices, automotive user interfaces, and interactive public displays. The presented design space is based on a comprehensive literature review. Furthermore we present a classification of 211 windshield applications, derived from a survey of research projects and commercial products as well as from focus groups. We showcase the utility of our work for designers of windshield applications through two scenarios. Overall, our design space can help building applications for diverse use cases. This includes apps inside and outside the car as well as applications for specific areas (fire fighters, police, ambulance).

In this paper, we present a proof-of-concept approach to estimating mental workload by measuring the user's pupil diameter under various controlled lighting conditions. Knowing the user's mental workload is desirable for many application scenarios, ranging from driving a car, to adaptive workplace setups. Typically, physiological sensors allow inferring mental workload, but these sensors might be rather uncomfortable to wear. Measuring pupil diameter through remote eye-tracking instead is an unobtrusive method. However, a practical eye-tracking-based system must also account for pupil changes due to variable lighting conditions. Based on the results of a study with tasks of varying mental demand and six different lighting conditions, we built a simple model that is able to infer the workload independently of the lighting condition in 75% of the tested conditions.

In this paper, we investigate which non-driving-related activities drivers want to perform while driving highly or fully automated. Beyond the available advanced driving assistance functions, we expect that highly automated driving will soon be available in production vehicles. While many technological aspects have been investigated, it is not yet clear (a) which activities the drivers want to perform once they do not have to steer or monitor their car any more and (b) which of those will be feasible. In contrast to prior (survey-based) research, we investigate the driver's needs for such activities by employing a combination of a web survey, in-situ observations, and an in-situ survey. Also, we have a look at the specific requirements of the European / German market in contrast to prior research conducted mostly for English-speaking countries.

Today, the vast majority of research on novel automotive user interface technologies is conducted in the lab, often using driving simulation. While such studies are important in early stages of the design process, we argue that ultimately studies need to be conducted in the real-world in order to investigate all aspects crucial for adoption of novel user interface technologies in commercial vehicles. In this paper, we present a case study that investigates introducing autostereoscopic 3D dashboards into cars. We report on studying this novel technology in the real world, validating and extending findings of prior simulator studies. Furthermore, we provide guidelines for practitioners and researchers to design and conduct real-world studies that minimize the risk for participants while at the same time yielding ecologically valid findings.

In this paper, we investigate user performance for stereoscopic automotive user interfaces (UI). Our work is motivated by the fact that stereoscopic displays are about to find their way into cars. Such a safety-critical application area creates an inherent need to understand how the use of stereoscopic 3D visualizations impacts user performance. We conducted a comprehensive study with 56 participants to investigate the impact of a 3D instrument cluster (IC) on primary and secondary task performance. We investigated different visualizations (2D and 3D) and complexities (low vs. high amount of details) of the IC as well as two 3D display technologies (shutter vs. autostereoscopy). As secondary tasks the participants judged spatial relations between UI elements (expected events) and reacted on pop-up instructions (unexpected events) in the IC. The results show that stereoscopy increases accuracy for expected events, decreases task completion times for unexpected tasks, and increases the attractiveness of the interface. Furthermore, we found a significant influence of the used technology, indicating that secondary task performance improves for shutter displays.

Computing technology is currently adopted in emerging countries. Especially mobile phones and smart phones become widely used - with a much higher penetration than traditional computers. In our work we investigate how computing technologies and particularly mobile devices can support education. While previous work focused on controlled experiments, in this paper we present the results of a 20 weeks long study of mobile phone usage in an emerging region. Our aim was not only to investigate how the phones are used for education but also to learn how they are adopted by children in daily life. By logging screenshots, we used an unsupervised approach that allowed to unobtrusively observe usage patterns without the presence of researchers. Instead of offering tailored teaching applications, we used general-purpose applications to support teaching and found that the phone itself was an empowering technology similar to pen and paper. Based on a detailed analysis of actual use in a natural setting, we derived a set of typical use cases for mobile phones in education and describe how they change learning. From in-depth interviews with a teacher, selected guardians and pupils we show that introducing mobiles phones has great potential for supporting education in emerging regions.

Calling while driving a car has become very common since the rise of mobile phones. Drivers use their phone despite the fact that calling in the car is potentially distracting and dangerous. Prohibiting communication while driving is not a good idea as there are also positive effects of calling (e.g., ability to notify about a delay, staying awake, preventing fatigue, guidance at foreign places).

Driving a car is becoming increasingly complex. Many new features (e.g., for communication or entertainment) that can be used in addition to the primary task of driving a car increase the driver's workload. Assessing the driver's workload, however, is still a challenging task. A variety of means are explored which rather focus on experimental conditions than on real world scenarios (e.g., questionnaires). We focus on physiological data that may be assessed in an non-obtrusive way in the future and is therefore applicable in the real world.

Implementing controls in the car becomes a major challenge: The use of simple physical buttons does not scale to the increased number of assistive, comfort, and infotainment functions. Current solutions include hierarchical menus and multi-functional control devices, which increase complexity and visual demand. Another option is speech control, which is not widely accepted, as it does not support visibility of actions, fine-grained feedback, and easy undo of actions. Our approach combines speech and gestures. By using speech for identification of functions, we exploit the visibility of objects in the car (e.g., mirror) and simple access to a wide range of functions equaling a very broad menu. Using gestures for manipulation (e.g., left/right), we provide fine-grained control with immediate feedback and easy undo of actions. In a user-centered process, we determined a set of user-defined gestures as well as common voice commands. For a prototype, we linked this to a car interior and driving simulator. In a study with 16 participants, we explored the impact of this form of multimodal interaction on the driving performance against a baseline using physical buttons. The results indicate that the use of speech and gesture is slower than using buttons but results in a similar driving performance. Users comment in a DALI questionnaire that the visual demand is lower when using speech and gestures.

Natural user interfaces by means of gesture and speech interaction have become a hot topic in research as well as already for real products. Most use cases currently center around consumer electronics devices like smart phones, TV sets, gaming, or other large screens like tabletops.

During the last decade, the number of functions of automotive user interfaces has increased rapidly. Besides traditional controls to drive a car, driver assistance, infotainment, entertainment, and comfort systems need to be controlled while driving. This does not only affect the driver's cognitive workload but also leads to increased complexity in designing automotive user interfaces. In this paper, we provide models and tools for rapid prototyping and the evaluation of user interfaces in this context. Usually, functional prototypes of user interfaces are implemented that allow the usability and quality to be assessed with time-consuming user studies. In contrast, in our approach we use an adapted Keystroke-Level Model (KLM) that is based on empirically collected data for typical operations in the car. It takes into account the aspect of attention switching in the car between primary tasks and other tasks. We present KLM operator times that we determined in a user study as well as a formula for estimating the task completion time. The presented model is the foundation for the MI-AUI prototyping tool that we implemented for permitting the creation of automotive interfaces using tangible controls. By demonstrating a typical operation with the MI-AUI prototype, the estimated task completion time can be calculated. MI-AUI is an evaluation tool that can be quickly and easily applied in early stages of the design process without the need to involve real drivers.

Currently, the development of mobile applications heavily relies on using conventional computers as development platform. MobiDev enables people in emerging countries without access to a computer but to a cell phone to develop their own locally relevant applications. The goal of the Mo-biDev project is to simplify development and deployment of applications directly on mobile phones. As a first step, we focus on the design of applications and try to support the computer science curriculum in developing countries to bootstrap the mobile developer culture and community. MobiDev allows the creation of graphical user interfaces (GUI) using various concepts. We present the results of a first system evaluation that show how people perceive the concepts for UI creation of MobiDev.

In past years, ubiquitous computing technologies have been successfully deployed for supporting children with special needs. One focus of current research has been on post-hoc behavior analysis based on video footage where one or multiple cameras were used to review situations in which children behaved in a certain way. As miniaturized cameras as well as portable devices are becoming available at low costs, we envision a new quality in supporting the diagnosis, observation, and education of children with special needs. In contrast to existing approaches that use cameras in fix locations, we suggest to use multiple mobile camera perspectives. In this way observation data from fellow classmates, teachers, and caregivers can be considered, even in highly dynamic outdoor situations. In this paper we present MuPerBeAn, a platform that allows multi-perspective video footage from mobile cameras to be collected, synchronously reviewed, and annotated. We report on interviews with caregivers and parents and present a qualitative study based on two scenarios involving a total of seven children with autism (CWA). Our findings show that observing multiple mobile perspectives can help children as well as teachers to better reflect on situations, particularly during education.

People spend a significant amount of time in their cars (US: 86 minutes/day, Europe: 43 minutes/day) while commuting, shopping, or traveling. Hence, the variety of entertainment in the car increases, and many vehicles are already equipped with displays, allowing for watching news, videos, accessing the Internet, or playing games. At the same time, the urbanization caused a massive increase of traffic volume, which led to people spending an ever-increasing amount of their time in front of red traffic lights. An observation of the prevailing forms of entertainment in the car reveals that content such as text, videos, or games are often a mere adaptation of content produced for television, public displays, PCs, or mobile phones and do not adapt to the situation in the car. In this paper we report on a web survey assessing which forms of entertainment and which types of content are considered to be useful for in-car entertainment by drivers. We then introduce an algorithm, which is capable of learning standing times in front of traffic lights based on GPS information only. This, on one hand, allows for providing content of appropriate length, on the other hand, for directing the attention of the driver back to-wards the street at the right time. Finally, we present a prototype implementation and a qualitative evaluation.