@article{SchartmuellerWeiglLoeckenetal.2021, author = {Schartm{\"u}ller, Clemens and Weigl, Klemens and L{\"o}cken, Andreas and Wintersberger, Philipp and Steinhauser, Marco and Riener, Andreas}, title = {Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated Driving}, volume = {5}, pages = {21}, journal = {Multimodal Technologies and Interaction}, number = {4}, publisher = {MDPI}, address = {Basel}, issn = {2414-4088}, doi = {https://doi.org/10.3390/mti5040021}, year = {2021}, abstract = {(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}, language = {en} } @article{RieglerRienerHolzmann2021, author = {Riegler, Andreas and Riener, Andreas and Holzmann, Clemens}, title = {A systematic review of virtual reality applications for automated driving: 2009-2020}, volume = {3}, pages = {689856}, journal = {Frontiers in human dynamics}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2673-2726}, doi = {https://doi.org/10.3389/fhumd.2021.689856}, year = {2021}, abstract = {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.}, language = {en} } @article{DeyHabibovicLoeckenetal.2020, author = {Dey, Debargha and Habibovic, Azra and L{\"o}cken, Andreas and Wintersberger, Philipp and Pfleging, Bastian and Riener, Andreas and Martens, Marieke and Terken, Jacques}, title = {Taming the eHMI jungle: A classification taxonomy to guide, compare, and assess the design principles of automated vehicles' external human-machine interfaces}, volume = {2020}, pages = {100174}, journal = {Transportation Research Interdisciplinary Perspectives}, number = {7}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2590-1982}, doi = {https://doi.org/10.1016/j.trip.2020.100174}, year = {2020}, abstract = {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.}, language = {en} } @article{RieglerWintersbergerRieneretal.2019, author = {Riegler, Andreas and Wintersberger, Philipp and Riener, Andreas and Holzmann, Clemens}, title = {Augmented Reality Windshield Displays and Their Potential to Enhance User Experience in Automated Driving}, volume = {18}, journal = {i-com: Journal of Interactive Media}, number = {2}, publisher = {De Gruyter}, address = {Berlin}, issn = {2196-6826}, doi = {https://doi.org/10.1515/icom-2018-0033}, pages = {127 -- 149}, year = {2019}, language = {en} } @inproceedings{RosbachAmmelingKruegeletal.2025, author = {Rosbach, Emely and Ammeling, Jonas and Kr{\"u}gel, Sebastian and Kießig, Angelika and Fritz, Alexis and Ganz, Jonathan and Puget, Chlo{\´e} and Donovan, Taryn and Klang, Andrea and K{\"o}ller, Maximilian C. and Bolfa, Pompei and Tecilla, Marco and Denk, Daniela and Kiupel, Matti and Paraschou, Georgios and Kok, Mun Keong and Haake, Alexander F. H. and de Krijger, Ronald R. and Sonnen, Andreas F.-P. and Kasantikul, Tanit and Dorrestein, Gerry M. and Smedley, Rebecca C. and Stathonikos, Nikolas and Uhl, Matthias and Bertram, Christof and Riener, Andreas and Aubreville, Marc}, title = {"When Two Wrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology}, pages = {528}, booktitle = {CHI'25: Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems}, editor = {Yamashita, Naomi and Evers, Vanessa and Yatani, Koji and Ding, Xianghua and Lee, Bongshin and Chetty, Marshini and Toups-Dugas, Phoebe}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1394-1}, doi = {https://doi.org/10.1145/3706598.3713319}, year = {2025}, abstract = {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.}, language = {en} } @inproceedings{MangerPuschThoeneetal.2023, author = {Manger, Carina and Pusch, Florian and Th{\"o}ne, Manuel and Wenger, Marco and L{\"o}cken, Andreas and Riener, Andreas}, title = {Explainability in Automated Parking: The Effect of Augmented Reality Visualizations on User Experience and Situation Awareness}, booktitle = {Proceedings of MUM 2023: the 22nd International Conference on Mobile and Ubiquitous Multimedia}, editor = {Michahelles, Florian and Knierim, Pascal and H{\"a}kkil{\"a}, Jonna}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-0921-0}, doi = {https://doi.org/10.1145/3626705.3627796}, pages = {146 -- 152}, year = {2023}, language = {en} } @unpublished{RosbachAmmelingKruegeletal.2024, author = {Rosbach, Emely and Ammeling, Jonas and Kr{\"u}gel, Sebastian and Kießig, Angelika and Fritz, Alexis and Ganz, Jonathan and Puget, Chlo{\´e} and Donovan, Taryn and Klang, Andrea and K{\"o}ller, Maximilian C. and Bolfa, Pompei and Tecilla, Marco and Denk, Daniela and Kiupel, Matti and Paraschou, Georgios and Kok, Mun Keong and Haake, Alexander F. H. and de Krijger, Ronald R. and Sonnen, Andreas F.-P. and Kasantikul, Tanit and Dorrestein, Gerry M. and Smedley, Rebecca C. and Stathonikos, Nikolas and Uhl, Matthias and Bertram, Christof and Riener, Andreas and Aubreville, Marc}, title = {"When TwoWrongs Don't Make a Right" - Examining Confirmation Bias and the Role of Time Pressure During Human-AI Collaboration in Computational Pathology}, publisher = {arXiv}, address = {Ithaca}, doi = {https://doi.org/10.48550/arXiv.2411.01007}, year = {2024}, language = {en} } @inproceedings{RieglerRienerOstermayer2023, author = {Riegler, Andreas and Riener, Andreas and Ostermayer, Gerald}, title = {From Me to We: Combining Driving Simulation and Traffic Simulation for Holistic Usability and Safety Research}, booktitle = {15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-0112-2}, doi = {https://doi.org/10.1145/3581961.3609840}, pages = {294 -- 296}, year = {2023}, language = {en} } @article{RieglerRienerHolzmann2021, author = {Riegler, Andreas and Riener, Andreas and Holzmann, Clemens}, title = {Augmented Reality for Future Mobility: Insights from a Literature Review and HCI Workshop}, volume = {20}, journal = {i-com: Journal of Interactive Media}, number = {3}, publisher = {De Gruyter}, address = {Berlin}, issn = {2196-6826}, doi = {https://doi.org/10.1515/icom-2021-0029}, pages = {295 -- 318}, year = {2021}, abstract = {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.}, language = {en} } @article{vonSawitzkyLoeckenGrauschopfetal.2024, author = {von Sawitzky, Tamara and L{\"o}cken, Andreas and Grauschopf, Thomas and Riener, Andreas}, title = {Enhancing cyclist safety in cyclist-vehicle interactions through early hazard notifications: a comparison of bi-modal cues at head level}, volume = {7}, pages = {e000070}, journal = {Traffic Safety Research}, publisher = {Lund University}, address = {Lund}, issn = {2004-3082}, doi = {https://doi.org/10.55329/bodb6366}, year = {2024}, abstract = {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.}, language = {en} } @inproceedings{StojmenovaLeeHongetal.2023, author = {Stojmenova, Kristina and Lee, Seulchan and Hong, Sara and Schuß, Martina and Sahin, Hatice and Patel, Ankit R. and L{\"o}cken, Andreas and Dey, Debargha and Riener, Andreas and Mirnig, Alexander G. and Jeon, Myounghoon}, title = {How to Ensure Diversity and Inclusion at Conferences}, booktitle = {15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings}, subtitle = {A Workshop for General Chairs, Program Committee Members, Reviewers and Authors}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-0112-2}, doi = {https://doi.org/10.1145/3581961.3609838}, pages = {241 -- 244}, year = {2023}, language = {en} }