@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{SchussWintersbergerRiener2021, author = {Schuß, Martina and Wintersberger, Philipp and Riener, Andreas}, title = {Security Issues in Shared Automated Mobility Systems: A Feminist HCI Perspective}, volume = {5}, pages = {43}, journal = {Multimodal Technologies and Interaction}, number = {8}, publisher = {MDPI}, address = {Basel}, issn = {2414-4088}, doi = {https://doi.org/10.3390/mti5080043}, year = {2021}, abstract = {The spread of automated vehicles (AVs) is expected to disrupt our mobility behavior. Currently, a male bias is prevalent in the technology industry in general, and in the automotive industry in particular, mainly focusing on white men. This leads to an under-representation of groups of people with other social, physiological, and psychological characteristics. The advent of automated driving (AD) should be taken as an opportunity to mitigate this bias and consider a diverse variety of people within the development process. We conducted a qualitative, exploratory study to investigate how shared automated vehicles (SAVs) should be designed from a pluralistic perspective considering a holistic viewpoint on the whole passenger journey by including booking, pick-up, and drop-off points. Both, men and women, emphasized the importance of SAVs being flexible and clean, whereas security issues were mentioned exclusively by our female participants. While proposing different potential solutions to mitigate security matters, we discuss them through the lens of the feminist HCI framework.}, 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{FrisonForsterWintersbergeretal.2020, author = {Frison, Anna-Katharina and Forster, Yannick and Wintersberger, Philipp and Geisel, Viktoria and Riener, Andreas}, title = {Where We Come from and Where We Are Going: A Systematic Review of Human Factors Research in Driving Automation}, volume = {10}, pages = {8914}, journal = {Applied Sciences}, number = {24}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {https://doi.org/10.3390/app10248914}, year = {2020}, abstract = {During the last decade, research has brought forth a large amount of studies that investigated driving automation from a human factor perspective. Due to the multitude of possibilities for the study design with regard to the investigated constructs, data collection methods, and evaluated parameters, at present, the pool of findings is heterogeneous and nontransparent. This literature review applied a structured approach, where five reviewers investigated n = 161 scientific papers of relevant journals and conferences focusing on driving automation between 2010 and 2018. The aim was to present an overview of the status quo of existing methodological approaches and investigated constructs to help scientists in conducting research with established methods and advanced study setups. Results show that most studies focused on safety aspects, followed by trust and acceptance, which were mainly collected through self-report measures. Driving/Take-Over performance also marked a significant portion of the published papers; however, a wide range of different parameters were investigated by researchers. Based on our insights, we propose a set of recommendations for future studies. Amongst others, this includes validation of existing results on real roads, studying long-term effects on trust and acceptance (and of course other constructs), or triangulation of self-reported and behavioral data. We furthermore emphasize the need to establish a standardized set of parameters for recurring use cases to increase comparability. To assure a holistic contemplation of automated driving, we moreover encourage researchers to investigate other constructs that go beyond safety.}, language = {en} } @article{KundingerYalavarthiRieneretal.2020, author = {Kundinger, Thomas and Yalavarthi, Phani Krishna and Riener, Andreas and Wintersberger, Philipp and Schartm{\"u}ller, Clemens}, title = {Feasibility of smart wearables for driver drowsiness detection and its potential among different age groups}, volume = {16}, journal = {International Journal of Pervasive Computing and Communications}, number = {1}, publisher = {Emerald}, address = {Bingley}, issn = {1742-7371}, doi = {https://doi.org/10.1108/IJPCC-03-2019-0017}, pages = {1 -- 23}, year = {2020}, 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{MichahellesRienerGrundeletal.2024, author = {Michahelles, Florian and Riener, Andreas and Grundel, Ida and Boztepe, Suzan and Trygg, Kristina and Israel, Habakuk and Pfleging, Bastian and Veenstra, Mettina and Wintersberger, Philipp}, title = {Urban-Engage: Pioneering Urban Planning with Citizen-Driven 15-Minute City Solutions}, booktitle = {Mensch und Computer 2024 - Workshopband}, publisher = {Gesellschaft f{\"u}r Informatik}, address = {Bonn}, doi = {https://doi.org/10.18420/muc2024-mci-ws16-393}, year = {2024}, abstract = {We propose an innovative approach to empower urban planners by integrating comprehensive and qualified citizen input into the planning of the 15-minute city (15mC) through immersive digital technologies. Our methodology includes (1) enabling citizens to annotate their real environment using augmented reality, (2) generating urban space alternatives based on generative AI and citizen annotations, (3) allowing modifications to AI-generated alternatives, (4) providing immersive 3D simulation environments for experiencing these alternatives, and (5) facilitating better negotiation between citizens and political players to identify the optimal solution. This process aims to account for diverse stakeholder interests, ensuring inclusive contributions and an experiential understanding of potential urban adaptation.}, language = {en} } @article{WintersbergerSchartmuellerSadeghianetal.2021, author = {Wintersberger, Philipp and Schartm{\"u}ller, Clemens and Sadeghian, Shadan and Frison, Anna-Katharina and Riener, Andreas}, title = {Evaluation of Imminent Take-Over Requests With Real Automation on a Test Track}, volume = {65}, journal = {Human Factors: The Journal of the Human Factors and Ergonomics Society}, number = {8}, publisher = {SAGE}, address = {London}, issn = {0018-7208}, doi = {https://doi.org/10.1177/00187208211051435}, pages = {1776 -- 1792}, year = {2021}, language = {en} } @inproceedings{EhsanWintersbergerLiaoetal.2021, author = {Ehsan, Upol and Wintersberger, Philipp and Liao, Q. Vera and Mara, Martina and Streit, Marc and Wachter, Sandra and Riener, Andreas and Riedl, Mark O.}, title = {Operationalizing Human-Centered Perspectives in Explainable AI}, pages = {94}, booktitle = {CHI'21: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems}, publisher = {ACM}, address = {New York}, isbn = {978-1-4503-8095-9}, doi = {https://doi.org/10.1145/3411763.3441342}, year = {2021}, language = {en} } @inproceedings{EhsanWatkinsWintersbergeretal.2025, author = {Ehsan, Upol and Watkins, Elizabeth Anne and Wintersberger, Philipp and Manger, Carina and Hubig, Nina and Savage, Saiph and Weisz, Justin and Riener, Andreas}, title = {New Frontiers of Human-centered Explainable AI (HCXAI): Participatory Civic AI, Benchmarking LLMs, XAI Hallucinations, and Responsible AI Audits}, pages = {793}, booktitle = {CHI'25: Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems}, editor = {Yamashita, Naomi and Evers, Vanessa and Yatani, Koji and Ding, Xianghua}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-1395-8}, doi = {https://doi.org/10.1145/3706599.3706713}, year = {2025}, language = {en} } @inproceedings{EhsanWatkinsWintersbergeretal.2024, author = {Ehsan, Upol and Watkins, Elizabeth Anne and Wintersberger, Philipp and Manger, Carina and Kim, Sunnie S. Y. and Van Berkel, Niels and Riener, Andreas and Riedl, Mark O}, title = {Human-Centered Explainable AI (HCXAI): Reloading Explainability in the Era of Large Language Models (LLMs)}, pages = {477}, booktitle = {CHI'24: Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems}, editor = {Mueller, Florian 'Floyd' and Kyburz, Penny and Williamson, Julie R. and Sas, Corina}, publisher = {ACM}, address = {New York}, isbn = {979-8-4007-0331-7}, doi = {https://doi.org/10.1145/3613905.3636311}, year = {2024}, language = {en} }