Veranstaltungsprogramm

Future voice assistants in automated cars are expected to provide a more interactive user experience by making proactive suggestions. For the design of proactive behavior, the right timing of the interaction is key to ensure user acceptance. Context situations during an automated ride are influenced by different factors, which need to be considered to initiate a proactive interaction. The goal of this study is to investigate how different context factors influence the suitability of proactive suggestions and relate to the suggested content. A conjoint analysis was designed to measure users’ preferences for different situations. Results indicate that selected context factors are considered suitable or unsuitable for a proactive approach, independent of the suggested content. The content’s relevancy contributes to the general acceptance, with more relevant suggestions considered suitable in more context situations. The presented results will inform the modelling approach of a voice assistant prototype for future studies.

As driving assistance driving systems become increasingly advanced, a correct understanding of the functionality of these systems is crucial for safe use. In this work we explored drivers’ explanation needs and current explanation methods from an important but underlooked perspective: driver training and vehicle acquisition. In a two-step approach, we conducted expert interviews with n = 7 driving instructors and vehicle salespeople in Germany and validated these results with an online survey of n = 105. Our results show that Driver Assistance Systems (DASs) and Advanced Driver Assistance Systems (ADASs), are currently covered in both driver training and vehicle acquisition but to a varying extent and in a very application-oriented manner. A drivers’ tendency for preferring comparative explanations that build upon knowledge about similar systems was found. Based on the combined results, we emphasize the need for mandatory and standardized explanation methods to ensure a safe transition to automated driving.

Automated vehicles will alter traffic fundamentally. Users can engage in various activities, such as working, reading, or sleeping. However, based on these activities, there are challenges and opportunities to adapt the vehicle, possibly transforming these into ``tiny houses''. Some activities will most likely be conducted, especially those already undertaken, such as making phone calls or listening to music. However, there are limited possibilities to derive activities occurring in longer trips or with a high level of automation. Therefore, we propose to derive non-driving-related activities based on a 12-day trip in a camper as a surrogate for prolonged exposure to automated driving. We report the autoethnographic results of our experiences and deduce relevant future research questions. We highlight the possibility of employing Vanlife as a method to study these upcoming challenges.

Charging electric vehicles (EVs) with renewable energy can lessen their environmental impact. However, the fluctuating availability of renewable energy affects the sustainability of public EV charging stations. Nearby public charging stations may utilize differing energy sources due to their microgrid connections - ranging from exclusively renewable to non-renewable or a combination of both - highlighting the substantial variability in energy supply types within short distances. This study investigates the near-future scenario of integrating dynamic renewable energy availability in charging station navigation to impact the choices of EV users towards renewable sources. We conducted a within-subjects design survey with 50 car users and semi-structured interviews with 10 EV users from rural, suburban, and urban areas. The results show that when choosing EV charging stations, drivers often prioritize either time savings or money savings based on the driving scenarios that influence drivers’ consumer value. Notably, EV users tend to select renewable-powered stations when they align with their main priority, be it saving money or time. This study offers end-user insights into the front-end graphic user interface and the development of the back-end ranking algorithm for navigation recommender systems that integrate dynamic renewable energy availability for the sustainable use of electric vehicles.

Partizipative Methoden öffnen Forschungsvorhaben in der Mensch-Maschine Interaktion für Gruppen, die traditionell nicht in akademischen Institutionen vertreten sind. Dabei werden Machtverhältnisse allerdings nicht zwingend ausreichend reflektiert, um einem transformativen Anspruch tatsächlich gerecht zu werden. In unserer Fallstudie von MACH'S AUF! zeigen wir, wie sich aus der Erforschung der Zugänglichkeit von Makerspaces für taube Personen ein methodologisches Konzept von solidarischer Forschung entwickelte, das über klassische Partizipation hinausgeht. Durch eine kritische Analyse unserer Aktivitäten und der damit verbundenen Implikationen für Zugangsqualitäten einerseits und methodologischen Aspekten andererseits präsentieren wir die vielschichtigen und verwobenen Überlegungen, die eine derartige Positionierung mit sich bringen kann. Wir zeigen auf, wie Zugänglichkeiten zu Makerspaces maßgeblich als sozio-technisch strukturiert verstanden werden muss, wobei zuvorderst ein kommunikativer, gebärdensprachlicher Zugang für gehörlose Personen vorhanden sein muss. Weiters illustrieren wir, wie solidarische Forschung als Konzept in einem realistischerweise unerreichbaren Idealzustand verhaftet, der dennoch nicht weniger anzustreben ist. Damit bieten wir dem Feld der Mensch-Maschine Interaktion ein nuanciertes Verständnis von Zugang zu Makerspaces aus einer bisher unterrepräsentierten Perspektive sowie eine methodologische Positionierung, welche transformative Forschungsvorhaben unterstützen kann.

Shared automated vehicles (SAVs) will offer a lot of benefits, from improving the overall mobility to environmental benefits. However, perceived security in SAVs is a major concern and may influence their acceptance and adoption negatively. To address this, we propose a digital companion (DC) concept embodied as an avatar inside the vehicle to accompany passengers in substitution of a human driver. In a co-creation workshop with participants (N = 6) we collected ideas about the appearance and personality of such DCs and derived two contrasting concepts (‘Baymax’ and ‘RoboCop’). Inspired by a design space from the gaming context, we implemented the two DCs and evaluated them in a VR study (N = 23) experiencing two scenarios in SAVs. The results show that a DC improves passengers’ perceived security. Generally, the ‘Baymax’ companion was preferred in both scenarios but no correlation between scenario and preferred personality type could be determined.