@inproceedings{AppelBoeckHompfetal.2025, author = {Appel, Patricia B. and B{\"o}ck, Henrike and Hompf, Filippa Viktoria Franziska and Pl{\"u}mer, Kolja Sam and Russ, Sarah and Riener, Andreas}, title = {Understanding Bystander Preferences for Medical Emergency Support Measures in VR-Simulated eVTOL Flights}, booktitle = {MuC´25: Proceedings of the 2025 Conference on Mensch und Computer}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1582-2}, doi = {https://doi.org/10.1145/3743049.3748549}, pages = {755 -- 760}, year = {2025}, abstract = {With the emergence of Urban Air Mobility (UAM), eVTOLs are set to revolutionize the way of traveling. However, there will be situations where things do not go as planned, such as medical emergencies during a flight. Due to the lack of cabin crew, tailored support measures must be identified to ensure passenger safety and well-being. To explore how potential passengers perceive medical emergencies on board as bystanders and what kind of assistance they expect, we conducted a VR study. The results show significant increases in negative emotions during a medical in-flight emergency. Moreover, support measures involving human interaction were rated significantly higher than those relying solely on information displayed on onboard screens. Particularly well-received were pilot announcements. For UAM to enter the market successfully, it is essential to address passenger needs in critical situations. Our findings provide valuable insights into shaping effective and user-centered emergency support strategies for eVTOL operations.}, language = {en} } @inproceedings{PeintnerMalveSadeghianetal.2025, author = {Peintner, Jakob and Malve, Bhavana and Sadeghian, Shadan and Riener, Andreas}, title = {Driving Together: An Analysis of Passengers' Needs and Desire for Cooperative Control in Automated Vehicles}, booktitle = {MuC´25: Proceedings of the 2025 Conference on Mensch und Computer}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1582-2}, doi = {https://doi.org/10.1145/3743049.3743061}, pages = {333 -- 344}, year = {2025}, abstract = {Driving automation aims to enhance comfort, safety, and traffic flow by removing the human driver from the control loop. However, the human experience of commuting involves more than just reaching a destination or assuming the role of a driver. Factors like personal driving style and courtesy towards fellow road users are integral to the driving experience but often overlooked in the development of driving algorithms for automated vehicles. In this study, we explored the needs of passengers in highly automated vehicles. A qualitative use case analysis was conducted (N=16). In a second study, N=15 participants experienced the resulting use cases in an automated vehicle. In these scenarios, they were able to interact with the automation through a cooperation HMI. Results indicate that most participants expressed a desire for cooperative driving, albeit varying with the driving situation. Moreover, allowing cooperation improves passengers' overall experience by satisfying psychological needs for autonomy, security, competence, and relatedness.}, language = {en} } @article{MangerVoglRiener2025, author = {Manger, Carina and Vogl, Annalena and Riener, Andreas}, title = {Cognitive Biases in User Interaction with Automated Vehicles: The Influence of Explainability and Mental Models}, volume = {15}, pages = {11030}, journal = {Applied Sciences}, number = {20}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {https://doi.org/10.3390/app152011030}, year = {2025}, abstract = {To develop truly human-centered automated systems, it is essential to acknowledge that human reasoning is prone to systematic deviations from rational judgment, known as Cognitive Biases. The present study investigated such flawed reasoning in the context of automated driving. In a multi-step study with N = 34 participants, the occurrence of four Cognitive Biases was examined: Truthiness Effect, Automation Bias, Action Bias, and Illusory Control. Additionally, the study explored how the Explainability of the automation's behavior and the driver's Mental Model influenced the manifestation of these biases. The findings indicate a notable susceptibility to the Truthiness Effect and Illusory Control, although all biases appeared highly dependent on the specific driving context. Moreover, Explainability strongly impacted the perceived credibility of information and participants' agreement with the system's behavior. Given the exploratory nature of the study, this work aims to initiate a discussion on how Cognitive Biases shape human reasoning and decision-making in interactions with automated vehicles. Based on the results, several directions for future research are proposed: (1) investigation of additional cognitive biases, (2) analysis of biases across different levels of automation, (3) exploration of mitigation strategies versus deliberate use of biases, (4) examination of dynamic and context-dependent manifestations, and (5) validation in high-fidelity simulations or real-world settings.}, language = {en} } @article{HimmelsBuchnerSchmitzetal.2025, author = {Himmels, Chantal and Buchner, Claudia and Schmitz, Jan and Parduzi, Arben and Riener, Andreas}, title = {Validity of Driver Assistance Systems in Driving Simulators: A Comparative Study of Real-World Driving and Two Simulator Environments}, volume = {41}, journal = {International Journal of Human-Computer Interaction}, number = {23}, publisher = {Taylor \& Francis}, address = {London}, issn = {1044-7318}, doi = {https://doi.org/10.1080/10447318.2025.2495120}, pages = {15197 -- 15214}, year = {2025}, language = {en} } @inproceedings{DecaroBogarinHeurichAppeletal.2025, author = {Decaro, Gianluca and Bogarin Heurich, Sofia and Appel, Patricia B. and Kul, Sergen and Riener, Andreas}, title = {Too Close for Comfort? The Impact of eVTOL-Overflights in Residential Areas on Non-Users' Acceptance}, booktitle = {MuC´25: Proceedings of the 2025 Conference on Mensch und Computer}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1582-2}, doi = {https://doi.org/10.1145/3743049.3748548}, pages = {744 -- 748}, year = {2025}, abstract = {Urban Air Mobility (UAM) has the potential to revolutionize commuting by allowing passengers to travel quickly and efficiently within and between cities and airports. However, this innovation also raises concerns for residents on the ground, who are expected to tolerate frequent eVTOL overflights above their homes - an issue that this paper seeks to address. To investigate acceptance of eVTOLs from the perspective of residents on the ground being overflown at 1000 ft, 1500 ft, and 2000 ft, a virtual reality study was conducted. Results showed significant differences in emotions, the feeling of being disturbed by the noise, the spatial proximity, and the presence of the eVTOL in lower altitudes. Additionally, privacy concerns were expressed. The findings help the scientific community and regulators in developing guidelines for operating eVTOLs in residential areas in an acceptable manner for non-passengers.}, language = {en} } @inproceedings{RollwagenHornSchmidtneretal.2025, author = {Rollwagen, Alice and Horn, Alexander and Schmidtner, Stefanie and Riener, Andreas}, title = {Communicating Uncertainty in Arrival Time Predictions for Public Transport: A Comparison of Point and Interval Forecasts}, booktitle = {MuC´25: Proceedings of the 2025 Conference on Mensch und Computer}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1582-2}, doi = {https://doi.org/10.1145/3743049.3748542}, pages = {515 -- 519}, year = {2025}, abstract = {In public transport, arrival times are typically communicated as point forecasts, aiming to present precise estimates. However, current prediction models are unable to provide such precise and reliable estimates due to unpredictable events. This results in arrival times on passenger information systems appearing inaccurate due to the lack of communicated uncertainty. We therefore investigated interval forecasts as an alternative in an online study, aiming to better communicate uncertainty in arrival times. Our findings indicate that interval forecasts improve the communication of uncertainty. Further, user satisfaction was driven primarily by waiting time, and this relationship was moderated by the forecast concept. Point forecasts were only well received when the bus arrived as predicted, otherwise users preferred the broader interval forecasts. Participants valued accuracy over precision when judging arrival times.}, language = {en} } @inproceedings{YuShedgeMohamedetal.2025, author = {Yu, Hang and Shedge, Krishnakant and Mohamed, Nourhan and Samak, Nada and Binsad, Waleed and Bhosale, Simantini and Kim, Eunji and Kondvilkar, Shreya and Riener, Andreas}, title = {AwareDoor: Enhancing Vehicle-Exit Safety via Multimodal Risk Communication}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3756856}, pages = {345 -- 348}, year = {2025}, language = {en} } @inproceedings{MangerPreiwischRiener2025, author = {Manger, Carina and Preiwisch, Anna and Riener, Andreas}, title = {Invisible Barriers: Understanding and Supporting the Mobility Needs and Challenges of Individuals with Mental Health Conditions}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3758489}, pages = {100 -- 105}, year = {2025}, language = {en} } @inproceedings{PeintnerMangerAlvarezetal.2025, author = {Peintner, Jakob and Manger, Carina and Alvarez, Ignacio and Riener, Andreas}, title = {Enhancing Pedestrian Realism in Adverse-Weather Driving Simulations Using Motion Capture Data}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3758507}, pages = {214 -- 219}, year = {2025}, language = {en} } @inproceedings{RollwagenAlvarezRiener2025, author = {Rollwagen, Alice and Alvarez, Ignacio and Riener, Andreas}, title = {Reality Check: Real-World Observations of State-of-the-Art Driver Assistance Systems}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3758487}, pages = {88 -- 93}, year = {2025}, language = {en} } @inproceedings{RaghvaniGerberRiener2025, author = {Raghvani, Vidhi and Gerber, Michael A. and Riener, Andreas}, title = {Inclusive Vehicle Dashboard Design: Supporting Neuro diverse ADHD Drivers Through Visual Simplicity}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3756860}, pages = {359 -- 361}, year = {2025}, language = {en} } @inproceedings{KarurRienerAlvarezetal.2025, author = {Karur, Krishna Sahithi and Riener, Andreas and Alvarez, Ignacio and Wintersberger, Philipp and Park, Jeongeun and Lee, Seulchan}, title = {1st Workshop on Exploring the Potential of XAI and HMI to Alleviate Ethical, Legal, and Social Conflicts in Automated Vehicles}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3749143}, pages = {295 -- 297}, year = {2025}, language = {en} } @inproceedings{BergerEbelRieneretal.2025, author = {Berger, Melanie and Ebel, Patrick and Riener, Andreas and Alvarez, Ignacio and Wintersberger, Philipp and Sadeghian, Shadan}, title = {Sustainable by Design: A Workshop on Life-Cycle-Aware Future Mobility}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3749137}, pages = {306 -- 309}, year = {2025}, language = {en} } @inproceedings{MohamedGerberRiener2025, author = {Mohamed, Nourhan and Gerber, Michael A. and Riener, Andreas}, title = {Investigation of Habituation Effects of Visual Variations of Cues to the Fallback-Driver for Automated Level 3 Vehicles}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3756862}, pages = {365 -- 368}, year = {2025}, language = {en} } @inproceedings{SolombrinoGerberRiener2025, author = {Solombrino, Laetitia Pina-Lydia and Gerber, Michael A. and Riener, Andreas}, title = {Dynamic Head-Up Display Design: Cognitive Load as a Parametric Driver}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3756861}, pages = {362 -- 364}, year = {2025}, language = {en} } @inproceedings{OenbaşGerberRiener2025, author = {{\"O}nba{\c{s}}, Tuğcan and Gerber, Michael A. and Riener, Andreas}, title = {Context-Aware Take-Over Requests for Promoting Emergency Corridor Formation in Level 3 Automated Vehicles}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3756855}, pages = {342 -- 344}, year = {2025}, language = {en} } @inproceedings{PreiwischRiener2025, author = {Preiwisch, Anna and Riener, Andreas}, title = {Exploring Human Abuse of Automated Vehicles: A Review Framed by Robot Abuse Research}, booktitle = {Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2014-7}, doi = {https://doi.org/10.1145/3744335.3758491}, pages = {114 -- 119}, year = {2025}, language = {en} } @unpublished{MosaferchiRienerMortezapoursoufianietal.2025, author = {Mosaferchi, Saeedeh and Riener, Andreas and Mortezapoursoufiani, Alireza and Naddeo, Alessandro}, title = {Enhancing UX in Automated Vehicles through Biophilic Interfaces: Insights from Prospective End Users}, titleParent = {SSRN}, publisher = {Elsevier}, address = {Amsterdam}, doi = {https://dx.doi.org/10.2139/ssrn.5359199}, year = {2025}, language = {en} } @inproceedings{RosbachGanzAmmelingetal.2025, author = {Rosbach, Emely and Ganz, Jonathan and Ammeling, Jonas and Riener, Andreas and Aubreville, Marc}, title = {Automation Bias in AI-assisted Medical Decision-making under Time Pressure in Computational Pathology}, booktitle = {Bildverarbeitung f{\"u}r die Medizin 2025: Proceedings, German Conference on Medical Image Computing, Regensburg March 09-11, 2025}, editor = {Palm, Christoph and Breininger, Katharina and Deserno, Thomas Martin and Handels, Heinz and Maier, Andreas and Maier-Hein, Klaus H. and Tolxdorff, Thomas}, publisher = {Springer Vieweg}, address = {Wiesbaden}, isbn = {978-3-658-47422-5}, doi = {https://doi.org/10.1007/978-3-658-47422-5_27}, pages = {129 -- 134}, year = {2025}, language = {en} } @inproceedings{IrawatiBolukbasiRiener2025, author = {Irawati, Diah Ayu and Bolukbasi, Elif and Riener, Andreas}, title = {Advancing Generative AI Collaboration in Design-to-Code Workflows: Insights from Two Empirical Studies}, booktitle = {Proceedings of MUM 2025: The 24th International Conference on Mobile and Ubiquitous Multimedia}, editor = {Sorce, Salvatore and Elagroudy, Passant and Khamis, Mohamed}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-2015-4}, doi = {https://doi.org/10.1145/3771882.3771913}, pages = {33 -- 46}, year = {2025}, abstract = {For expert users to accept Generative AI (GenAI) as a true collaborative partner, it must move beyond simple task-awareness to an understanding of their workflow's underlying structural rules. This paper introduces a paradigm for AI collaborators that moves beyond simple task awareness to an understanding of the semantic and hierarchical relationships within a component-based system. We investigate this concept within the context of the design-to-code workflow, where inefficiencies arise from the modification of components within design systems. Through two empirical studies with designers and developers, we found that GenAI output was often rejected because it violated the component hierarchy. Designers required granular and visual control for refinements, whereas developers valued automated setup but required transparent validation of the generated code's logic. Based on these findings, we contribute design guidelines for achieving Component-Structure Awareness (CSA), with two core principles: the Atomic Recommender, which provides assistance that respects the component hierarchy, and Communication Archetypes, which allow GenAI to adapt its interaction style to the user's role and the atomic nature of their task. This work provides a new, higher-level concept for designing the next generation of truly collaborative GenAI agents.}, language = {en} } @article{PeintnerMangerBergeretal.2025, author = {Peintner, Jakob and Manger, Carina and Berger, Melanie and Riener, Andreas}, title = {Balancing transparency and control: The impact of AI explanation detail on user perception in automated vehicles}, volume = {2025}, pages = {101742}, journal = {Transportation Research Interdisciplinary Perspectives}, number = {34}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2590-1982}, doi = {https://doi.org/10.1016/j.trip.2025.101742}, year = {2025}, abstract = {As automated vehicle technology advances, explainable AI has emerged as a critical tool to enable users to understand and predict the behavior of AI systems, particularly in safety-critical applications such as automated driving. However, increased transparency in AI explanations may inadvertently contribute to an "illusion of control", a cognitive bias in which drivers overestimate their influence or understanding of the AI's actions. We aim to better understand how the level of detail in AI explanations affects users of automated vehicles. In a virtual reality study, N = 44 participants experienced different explanation levels (low, medium, high) in an automated ride (SAE L4) compared to a baseline condition with no explanations. The results show a significant improvement in participants' user experience, acceptance, and explanation satisfaction, with more detailed explanations. Our findings also indicate that as AI explanations become more detailed, users' perceived level of control increases significantly, although this perception does not correlate with actual control capabilities. At the same time, it decreased their desire to take control, indicating users' susceptibility to the 'illusion of control' bias in the context of automated driving. Overall, this suggests that the design of explanation interfaces should strive for a balanced level of detail that promotes AI transparency without causing cognitive overload. At the same time, explainable AI can be utilized to decrease users' desire to intervene in the AI's actions.}, language = {en} } @inproceedings{GoebelMertensRiener2025, author = {G{\"o}bel, Jan-Philipp and Mertens, Jan Cedric and Riener, Andreas}, title = {Benchmarking the MQ-3 Gas Sensor for Alcohol Impairment Detection: Insights from a Driving Simulator Study}, booktitle = {Proceedings of ELMAR-2025: 67th International Symposium ELMAR-2025, 15-17 September 2025, Zadar, Croatia}, editor = {Muštra, Mario and Vuković, Josip and Božek, Jelena}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3315-9679-8}, doi = {https://doi.org/10.1109/ELMAR66948.2025.11194001}, pages = {77 -- 84}, year = {2025}, language = {en} }