TY - JOUR A1 - Schartmüller, Clemens A1 - Weigl, Klemens A1 - Löcken, Andreas A1 - Wintersberger, Philipp A1 - Steinhauser, Marco A1 - Riener, Andreas T1 - Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated Driving JF - Multimodal Technologies and Interaction N2 - (1) Background: Primary driving tasks are increasingly being handled by vehicle automation so that support for non-driving related tasks (NDRTs) is becoming more and more important. In SAE L3 automation, vehicles can require the driver-passenger to take over driving controls, though. Interfaces for NDRTs must therefore guarantee safe operation and should also support productive work. (2) Method: We conducted a within-subjects driving simulator study (N=53) comparing Heads-Up Displays (HUDs) and Auditory Speech Displays (ASDs) for productive NDRT engagement. In this article, we assess the NDRT displays’ effectiveness by evaluating eye-tracking measures and setting them into relation to workload measures, self-ratings, and NDRT/take-over performance. (3) Results: Our data highlights substantially higher gaze dispersion but more extensive glances on the road center in the auditory condition than the HUD condition during automated driving. We further observed potentially safety-critical glance deviations from the road during take-overs after a HUD was used. These differences are reflected in self-ratings, workload indicators and take-over reaction times, but not in driving performance. (4) Conclusion: NDRT interfaces can influence visual attention even beyond their usage during automated driving. In particular, the HUD has resulted in safety-critical glances during manual driving after take-overs. We found this impacted workload and productivity but not driving performance UR - https://doi.org/10.3390/mti5040021 KW - automated driving KW - take-over requests KW - conditional automation KW - non-driving related tasks KW - eye-tracking KW - performance KW - behavior KW - displays KW - productivity KW - visual attention Y1 - 2021 UR - https://doi.org/10.3390/mti5040021 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-10965 SN - 2414-4088 VL - 5 IS - 4 PB - MDPI CY - Basel ER - TY - JOUR A1 - Riegler, Andreas A1 - Riener, Andreas A1 - Holzmann, Clemens T1 - A systematic review of virtual reality applications for automated driving: 2009–2020 JF - Frontiers in human dynamics N2 - While virtual reality (VR) interfaces have been researched extensively over the last decades, studies on their application in vehicles have only recently advanced. In this paper, we systematically review 12 years of VR research in the context of automated driving (AD), from 2009 to 2020. Due to the multitude of possibilities for studies with regard to VR technology, at present, the pool of findings is heterogeneous and non-transparent. We investigated N = 176 scientific papers of relevant journals and conferences with the goal to analyze the status quo of existing VR studies in AD, and to classify the related literature into application areas. We provide insights into the utilization of VR technology which is applicable at specific level of vehicle automation and for different users (drivers, passengers, pedestrians) and tasks. Results show that most studies focused on designing automotive experiences in VR, safety aspects, and vulnerable road users. Trust, simulator and motion sickness, and external human-machine interfaces (eHMIs) also marked a significant portion of the published papers, however a wide range of different parameters was investigated by researchers. Finally, we discuss a set of open challenges, and give recommendation for future research in automated driving at the VR side of the reality-virtuality continuum. UR - https://doi.org/10.3389/fhumd.2021.689856 KW - virtual reality KW - automated driving KW - systematic review KW - user studies KW - augmented reality KW - user experience KW - usability KW - classifications Y1 - 2021 UR - https://doi.org/10.3389/fhumd.2021.689856 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-11067 SN - 2673-2726 VL - 3 PB - Frontiers Media CY - Lausanne ER - TY - JOUR A1 - Dey, Debargha A1 - Habibovic, Azra A1 - Löcken, Andreas A1 - Wintersberger, Philipp A1 - Pfleging, Bastian A1 - Riener, Andreas A1 - Martens, Marieke A1 - Terken, Jacques T1 - Taming the eHMI jungle: A classification taxonomy to guide, compare, and assess the design principles of automated vehicles' external human-machine interfaces JF - Transportation Research Interdisciplinary Perspectives N2 - There is a growing body of research in the field of interaction between automated vehicles and other road users in their vicinity. To facilitate such interactions, researchers and designers have explored designs, and this line of work has yielded several concepts of external Human-Machine Interfaces (eHMI) for vehicles. Literature and media review reveals that the description of interfaces is often lacking in fidelity or details of their functionalities in specific situations, which makes it challenging to understand the originating concepts. There is also a lack of a universal understanding of the various dimensions of a communication interface, which has impeded a consistent and coherent addressal of the different aspects of the functionalities of such interface concepts. In this paper, we present a unified taxonomy that allowsa systematic comparison of the eHMI across 18 dimensions, covering their physical characteristics and communication aspects from the perspective of human factors and human-machine interaction. We analyzed and coded 70eHMI concepts according to this taxonomy to portray the state of the art and highlight the relative maturity of different contributions. The results point to a number of unexplored research areas that could inspire future work. Additionally, we believe that our proposed taxonomy can serve as a checklist for user interface designers and researchers when developing their interfaces. UR - https://doi.org/10.1016/j.trip.2020.100174 KW - Automated vehicle KW - Vulnerable road user KW - Pedestrian KW - External human-machine interface KW - Taxonomy KW - Human factors KW - Human-computer interaction Y1 - 2020 UR - https://doi.org/10.1016/j.trip.2020.100174 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-9241 SN - 2590-1982 VL - 2020 IS - 7 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Riegler, Andreas A1 - Wintersberger, Philipp A1 - Riener, Andreas A1 - Holzmann, Clemens T1 - Augmented Reality Windshield Displays and Their Potential to Enhance User Experience in Automated Driving JF - i-com: Journal of Interactive Media UR - https://doi.org/10.1515/icom-2018-0033 KW - windshield displays KW - head-up displays KW - user preferences KW - automated driving KW - heatmaps Y1 - 2019 UR - https://doi.org/10.1515/icom-2018-0033 SN - 2196-6826 VL - 18 IS - 2 SP - 127 EP - 149 PB - De Gruyter CY - Berlin ER - TY - CHAP A1 - Rosbach, Emely A1 - Ammeling, Jonas A1 - Krügel, Sebastian A1 - Kießig, Angelika A1 - Fritz, Alexis A1 - Ganz, Jonathan A1 - Puget, Chloé A1 - Donovan, Taryn A1 - Klang, Andrea A1 - Köller, Maximilian C. A1 - Bolfa, Pompei A1 - Tecilla, Marco A1 - Denk, Daniela A1 - Kiupel, Matti A1 - Paraschou, Georgios A1 - Kok, Mun Keong A1 - Haake, Alexander F. H. A1 - de Krijger, Ronald R. A1 - Sonnen, Andreas F.-P. A1 - Kasantikul, Tanit A1 - Dorrestein, Gerry M. A1 - Smedley, Rebecca C. A1 - Stathonikos, Nikolas A1 - Uhl, Matthias A1 - Bertram, Christof A1 - Riener, Andreas A1 - Aubreville, Marc ED - Yamashita, Naomi ED - Evers, Vanessa ED - Yatani, Koji ED - Ding, Xianghua ED - Lee, Bongshin ED - Chetty, Marshini ED - Toups-Dugas, Phoebe T1 - "When Two Wrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology T2 - CHI'25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems N2 - Artificial intelligence (AI)-based decision support systems hold promise for enhancing diagnostic accuracy and efficiency in computational pathology. However, human-AI collaboration can introduce and amplify cognitive biases, like confirmation bias caused by false confirmation when erroneous human opinions are reinforced by inaccurate AI output. This bias may increase under time pressure, a ubiquitous factor in routine pathology, as it strains practitioners’ cognitive resources. We quantified confirmation bias triggered by AI-induced false confirmation and examined the role of time constraints in a web-based experiment, where trained pathology experts (n=28) estimated tumor cell percentages. Our results suggest that AI integration fuels confirmation bias, evidenced by a statistically significant positive linear-mixed-effects model coefficient linking AI recommendations mirroring flawed human judgment and alignment with system advice. Conversely, time pressure appeared to weaken this relationship. These findings highlight potential risks of AI in healthcare and aim to support the safe integration of clinical decision support systems. UR - https://doi.org/10.1145/3706598.3713319 Y1 - 2025 UR - https://doi.org/10.1145/3706598.3713319 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58797 SN - 979-8-4007-1394-1 PB - ACM CY - New York ER - TY - CHAP A1 - Manger, Carina A1 - Pusch, Florian A1 - Thöne, Manuel A1 - Wenger, Marco A1 - Löcken, Andreas A1 - Riener, Andreas ED - Michahelles, Florian ED - Knierim, Pascal ED - Häkkilä, Jonna T1 - Explainability in Automated Parking: The Effect of Augmented Reality Visualizations on User Experience and Situation Awareness T2 - Proceedings of MUM 2023: the 22nd International Conference on Mobile and Ubiquitous Multimedia UR - https://doi.org/10.1145/3626705.3627796 Y1 - 2023 UR - https://doi.org/10.1145/3626705.3627796 SN - 979-8-4007-0921-0 SP - 146 EP - 152 PB - ACM CY - New York ER - TY - INPR A1 - Rosbach, Emely A1 - Ammeling, Jonas A1 - Krügel, Sebastian A1 - Kießig, Angelika A1 - Fritz, Alexis A1 - Ganz, Jonathan A1 - Puget, Chloé A1 - Donovan, Taryn A1 - Klang, Andrea A1 - Köller, Maximilian C. A1 - Bolfa, Pompei A1 - Tecilla, Marco A1 - Denk, Daniela A1 - Kiupel, Matti A1 - Paraschou, Georgios A1 - Kok, Mun Keong A1 - Haake, Alexander F. H. A1 - de Krijger, Ronald R. A1 - Sonnen, Andreas F.-P. A1 - Kasantikul, Tanit A1 - Dorrestein, Gerry M. A1 - Smedley, Rebecca C. A1 - Stathonikos, Nikolas A1 - Uhl, Matthias A1 - Bertram, Christof A1 - Riener, Andreas A1 - Aubreville, Marc T1 - "When TwoWrongs Don’t Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology UR - https://doi.org/10.48550/arXiv.2411.01007 Y1 - 2024 UR - https://doi.org/10.48550/arXiv.2411.01007 PB - arXiv CY - Ithaca ER - TY - CHAP A1 - Riegler, Andreas A1 - Riener, Andreas A1 - Ostermayer, Gerald T1 - From Me to We: Combining Driving Simulation and Traffic Simulation for Holistic Usability and Safety Research T2 - 15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3581961.3609840 Y1 - 2023 UR - https://doi.org/10.1145/3581961.3609840 SN - 979-8-4007-0112-2 SP - 294 EP - 296 PB - ACM CY - New York ER - TY - JOUR A1 - Riegler, Andreas A1 - Riener, Andreas A1 - Holzmann, Clemens T1 - Augmented Reality for Future Mobility: Insights from a Literature Review and HCI Workshop JF - i-com: Journal of Interactive Media N2 - There is a growing body of research in the field of interaction between drivers/passengers and automated vehicles using augmented reality (AR) technology. Furthering the advancements and availability of AR, the number of use cases in and around vehicles rises. Our literature review reveals that in the past, AR research focussed on increasing road safety and displaying navigational aids, however, more recent research explores the support of immersive (non-)driving related activities, and finally enhance driving and passenger experiences, as well as assist other road users through external human-machine interfaces (HMIs). AR may also be the enabling technology to increase trust and acceptance in automated vehicles through explainable artificial intelligence (AI), and therefore help on the shift from manual to automated driving. We organized a workshop addressing AR in automotive human-computer interaction (HCI) design, and identified a number of challenges including human factors issues that need to be tackled, as well as opportunities and practical usages of AR in future mobility. We believe that our status-quo literature analysis and future-oriented workshop results can serve as a research agenda for user interface designers and researchers when developing automotive AR interfaces. UR - https://doi.org/10.1515/icom-2021-0029 Y1 - 2021 UR - https://doi.org/10.1515/icom-2021-0029 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-56402 SN - 2196-6826 VL - 20 IS - 3 SP - 295 EP - 318 PB - De Gruyter CY - Berlin ER - TY - JOUR A1 - von Sawitzky, Tamara A1 - Löcken, Andreas A1 - Grauschopf, Thomas A1 - Riener, Andreas T1 - Enhancing cyclist safety in cyclist-vehicle interactions through early hazard notifications: a comparison of bi-modal cues at head level JF - Traffic Safety Research N2 - Cyclists frequently face numerous hazards on the road. Often those hazards are posed by motorised vehicles. Advanced support systems that alert cyclists to potential dangers could enhance their safety. However, research in this area, particularly regarding hazard notifications for cyclists, remains sparse. This work assesses bi-modal early hazard notification concepts (combining visual cues with either auditory or tactile feedback) provided at head level (smart glasses with speakers, tactile headband). They are detailing the nature of the hazard, its direction relative to the cyclist, and the timing of exposure. This work investigates cyclists' preference and perception of the proposed concepts for two hazardous situations originating from interactions with vehicles: ‘dooring’, the hazard of a potential collision with an opening door of a parked vehicle (evaluated through a test track study, N = 32) and ‘being overtaken’ which poses the hazard of being cut off or hit by the overtaking vehicle (assessed in a bicycle simulator study, N = 21). The study involved comparisons of supported and unsupported rides, focusing on their impact on usability, intuitiveness, workload, and perceived safety. Our findings reveal varied preferences for the supporting feedback modality, with 56% favouring visual-auditory and 31% visual-tactile. The participants rated user experience, intuitiveness and perceived safety for the use of both concepts quite high. Further, the workload for assisted rides was rated as equally low as for unassisted rides. UR - https://doi.org/10.55329/bodb6366 Y1 - 2024 UR - https://doi.org/10.55329/bodb6366 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-56562 SN - 2004-3082 VL - 7 PB - Lund University CY - Lund ER - TY - CHAP A1 - Stojmenova, Kristina A1 - Lee, Seulchan A1 - Hong, Sara A1 - Schuß, Martina A1 - Sahin, Hatice A1 - Patel, Ankit R. A1 - Löcken, Andreas A1 - Dey, Debargha A1 - Riener, Andreas A1 - Mirnig, Alexander G. A1 - Jeon, Myounghoon T1 - How to Ensure Diversity and Inclusion at Conferences BT - A Workshop for General Chairs, Program Committee Members, Reviewers and Authors T2 - 15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3581961.3609838 Y1 - 2023 UR - https://doi.org/10.1145/3581961.3609838 SN - 979-8-4007-0112-2 SP - 241 EP - 244 PB - ACM CY - New York ER -