TY - CHAP A1 - Manger, Carina A1 - Vogl, Annalena A1 - Rosbach, Emely A1 - Ziegler, Carina A1 - Riener, Andreas T1 - Automation's Not Perfect But Neither Are We: Unveiling Illusionary Control And Automation Bias In Automated Driving T2 - 15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3581961.3609897 KW - Automated Driving KW - Cognitive Biases KW - User Study KW - Illusionary Control KW - Automation Bias Y1 - 2023 UR - https://doi.org/10.1145/3581961.3609897 SN - 979-8-4007-0112-2 SP - 25 EP - 29 PB - ACM CY - New York ER - TY - CHAP A1 - Manger, Carina A1 - Preiwisch, Anna A1 - Gambirasio, Chiara A1 - Golks, Simon A1 - Schuß, Martina A1 - Riener, Andreas ED - Michahelles, Florian ED - Knierim, Pascal ED - Häkkilä, Jonna T1 - We're in This Together: Exploring Explanation Needs and Methods in Shared Automated Shuttle Buses T2 - Proceedings of MUM 2023: the 22nd International Conference on Mobile and Ubiquitous Multimedia UR - https://doi.org/10.1145/3626705.3627798 Y1 - 2023 UR - https://doi.org/10.1145/3626705.3627798 SN - 979-8-4007-0921-0 SP - 145 EP - 151 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 - CHAP A1 - Manger, Carina A1 - Peintner, Jakob A1 - Devaraju, Manoj A1 - Riener, Andreas ED - Michahelles, Florian ED - Knierim, Pascal ED - Häkkilä, Jonna T1 - Good Vibes Only: A Comparative Study of Seat Vibration Concepts for Redirecting Driver Attention During Visual Distraction T2 - Proceedings of MUM 2023: the 22nd International Conference on Mobile and Ubiquitous Multimedia UR - https://doi.org/10.1145/3626705.3631786 Y1 - 2023 UR - https://doi.org/10.1145/3626705.3631786 SN - 979-8-4007-0921-0 SP - 492 EP - 494 PB - ACM CY - New York ER - TY - CHAP A1 - Escher, Bengt A1 - Manger, Carina A1 - Daou, Makram A1 - Dünninger, Theresa A1 - Riener, Andreas ED - Michahelles, Florian ED - Knierim, Pascal ED - Häkkilä, Jonna T1 - A Comparative Analysis of Preferred Communication Options of Passengers in Networked Shared Automated Vehicles T2 - Proceedings of MUM 2023: the 22nd International Conference on Mobile and Ubiquitous Multimedia UR - https://doi.org/10.1145/3626705.3631801 Y1 - 2023 UR - https://doi.org/10.1145/3626705.3631801 SN - 979-8-4007-0921-0 SP - 541 EP - 543 PB - ACM CY - New York ER - TY - CHAP A1 - Ehsan, Upol A1 - Watkins, Elizabeth Anne A1 - Wintersberger, Philipp A1 - Manger, Carina A1 - Hubig, Nina A1 - Savage, Saiph A1 - Weisz, Justin A1 - Riener, Andreas ED - Yamashita, Naomi ED - Evers, Vanessa ED - Yatani, Koji ED - Ding, Xianghua T1 - New Frontiers of Human-centered Explainable AI (HCXAI): Participatory Civic AI, Benchmarking LLMs, XAI Hallucinations, and Responsible AI Audits T2 - CHI’25: Extended Abstracts of the 2025 CHI Conference on Human Factors in Computing Systems UR - https://doi.org/10.1145/3706599.3706713 Y1 - 2025 UR - https://doi.org/10.1145/3706599.3706713 SN - 979-8-4007-1395-8 PB - ACM CY - New York ER - TY - CHAP A1 - Ehsan, Upol A1 - Watkins, Elizabeth Anne A1 - Wintersberger, Philipp A1 - Manger, Carina A1 - Kim, Sunnie S. Y. A1 - Van Berkel, Niels A1 - Riener, Andreas A1 - Riedl, Mark O ED - Mueller, Florian 'Floyd' ED - Kyburz, Penny ED - Williamson, Julie R. ED - Sas, Corina T1 - Human-Centered Explainable AI (HCXAI): Reloading Explainability in the Era of Large Language Models (LLMs) T2 - CHI'24: Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems UR - https://doi.org/10.1145/3613905.3636311 Y1 - 2024 UR - https://doi.org/10.1145/3613905.3636311 SN - 979-8-4007-0331-7 PB - ACM CY - New York ER - TY - JOUR A1 - Peintner, Jakob A1 - Manger, Carina A1 - Riener, Andreas T1 - Increasing system transparency through confidence information in cooperative, automated driving JF - Behaviour & Information Technology UR - https://doi.org/10.1080/0144929X.2024.2407018 Y1 - 2024 UR - https://doi.org/10.1080/0144929X.2024.2407018 SN - 1362-3001 SN - 0144-929X VL - 44 IS - 11 SP - 2724 EP - 2741 PB - Taylor & Francis CY - London ER - TY - CHAP A1 - Manger, Carina A1 - Peintner, Jakob A1 - Hoffmann, Marion A1 - Probst, Mirella A1 - Wennmacher, Raphael A1 - Riener, Andreas T1 - Providing Explainability in Safety-Critical Automated Driving Situations through Augmented Reality Windshield HMIs T2 - 15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3581961.3609874 Y1 - 2023 UR - https://doi.org/10.1145/3581961.3609874 SN - 979-8-4007-0112-2 SP - 174 EP - 179 PB - ACM CY - New York ER - TY - CHAP A1 - Schuß, Martina A1 - Manger, Carina A1 - Löcken, Andreas A1 - Riener, Andreas T1 - You’ll Never Ride Alone: Insights into Women’s Security Needs in Shared Automated Vehicles T2 - Main Proceedings: 14th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications UR - https://doi.org/10.1145/3543174.3546848 KW - shared automated vehicles KW - participatory design KW - security KW - women KW - senior citizens Y1 - 2022 UR - https://doi.org/10.1145/3543174.3546848 SN - 978-1-4503-9415-4 SP - 13 EP - 23 PB - ACM CY - New York ER - TY - CHAP A1 - Peintner, Jakob A1 - Manger, Carina A1 - Riener, Andreas T1 - “Can you rely on me?” Evaluating a Confidence HMI for Cooperative, Automated Driving T2 - Main Proceedings: 14th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications UR - https://doi.org/10.1145/3543174.3546976 KW - cooperative driving KW - confidence HMIs KW - transparency KW - predictability KW - explainable AI Y1 - 2022 UR - https://doi.org/10.1145/3543174.3546976 SN - 978-1-4503-9415-4 SP - 340 EP - 348 PB - ACM CY - New York ER - TY - CHAP A1 - Peintner, Jakob A1 - Funk Drechsler, Maikol A1 - Manger, Carina A1 - Seifert, Georg A1 - Reway, Fabio A1 - Huber, Werner A1 - Riener, Andreas T1 - Comparing Different Pedestrian Representations for Testing Automated Driving Functions in Mixed Reality Environments T2 - Proceedings of the International Conference on Vehicle Electronics and Safety (ICVES 2022) UR - https://doi.org/10.1109/ICVES56941.2022.9986669 KW - Target tracking KW - Roads KW - Mixed reality KW - Virtual environments KW - Motion capture KW - Complexity theory KW - Safety Y1 - 2022 UR - https://doi.org/10.1109/ICVES56941.2022.9986669 SN - 978-1-6654-7698-0 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Peintner, Jakob A1 - Manger, Carina A1 - Riener, Andreas T1 - Communication of Uncertainty Information in Cooperative, Automated Driving: A Comparative Study of Different Modalities T2 - 15th International ACM Conference on Automotive User Interfaces: Main Conference Proceedings UR - https://doi.org/10.1145/3580585.3607154 KW - Cooperative Driving KW - Confidence HMIs KW - Interface Modalities KW - Transparency KW - Predictability KW - Explainable AI Y1 - 2023 UR - https://doi.org/10.1145/3580585.3607154 SN - 979-8-4007-0105-4 SP - 322 EP - 332 PB - ACM CY - New York ER - TY - CHAP A1 - Peintner, Jakob A1 - Himmels, Chantal A1 - Rock, Teresa A1 - Manger, Carina A1 - Jung, Oliver A1 - Riener, Andreas T1 - Driving Behavior Analysis: A Human Factors Perspective on Automated Driving Styles T2 - 2024 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV55156.2024.10588527 Y1 - 2024 UR - https://doi.org/10.1109/IV55156.2024.10588527 SN - 979-8-3503-4881-1 SP - 3312 EP - 3317 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Himmels, Chantal A1 - Peintner, Jakob A1 - Manger, Carina A1 - Rock, Teresa A1 - Jung, Oliver A1 - Riener, Andreas T1 - In Search of Social Presence: Evoking an Impression of Real Pedestrian Behavior Using Motion Capture T2 - 2024 IEEE Intelligent Vehicles Symposium (IV) UR - https://doi.org/10.1109/IV55156.2024.10588404 Y1 - 2024 UR - https://doi.org/10.1109/IV55156.2024.10588404 SN - 979-8-3503-4881-1 SP - 82 EP - 90 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Peintner, Jakob A1 - Manger, Carina A1 - Berger, Melanie A1 - Riener, Andreas T1 - Explaining Away Control: Exploring the Relationship between Explainable AI and Passengers' Desire for Control in Automated Vehicles T2 - 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3641308.3685040 Y1 - 2024 UR - https://doi.org/10.1145/3641308.3685040 SN - 979-8-4007-0520-5 SP - 155 EP - 160 PB - ACM CY - New York ER - TY - CHAP A1 - Manger, Carina A1 - Preiwisch, Anna A1 - Peintner, Jakob A1 - Martelaro, Nikolas A1 - Krome, Sven A1 - Dey, Debargha A1 - Riener, Andreas T1 - Reality Check: Insights from Experienced Users of Current Automated Driving Systems for an Updated AutoUI Research Agenda T2 - 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3641308.3677401 Y1 - 2024 UR - https://doi.org/10.1145/3641308.3677401 SN - 979-8-4007-0520-5 SP - 249 EP - 252 PB - ACM CY - New York ER - TY - CHAP A1 - Manger, Carina A1 - Preiwisch, Anna A1 - Peintner, Jakob A1 - Riener, Andreas T1 - Reality Check: How Do Real-World Users Experience Current Automated Driving Systems? T2 - 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3641308.3685016 Y1 - 2024 UR - https://doi.org/10.1145/3641308.3685016 SN - 979-8-4007-0520-5 SP - 16 EP - 20 PB - ACM CY - New York ER - TY - JOUR A1 - Peintner, Jakob A1 - Escher, Bengt A1 - Detjen, Henrik A1 - Manger, Carina A1 - Riener, Andreas T1 - How to Design Human-Vehicle Cooperation for Automated Driving: A Review of Use Cases, Concepts, and Interfaces JF - Multimodal Technologies and Interaction N2 - Currently, a significant gap exists between academic and industrial research in automated driving development. Despite this, there is common sense that cooperative control approaches in automated vehicles will surpass the previously favored takeover paradigm in most driving situations due to enhanced driving performance and user experience. Yet, the application of these concepts in real driving situations remains unclear, and a holistic approach to driving cooperation is missing. Existing research has primarily focused on testing specific interaction scenarios and implementations. To address this gap and offer a contemporary perspective on designing human–vehicle cooperation in automated driving, we have developed a three-part taxonomy with the help of an extensive literature review. The taxonomy broadens the notion of driving cooperation towards a holistic and application-oriented view by encompassing (1) the “Cooperation Use Case”, (2) the “Cooperation Frame”, and (3) the “Human–Machine Interface”. We validate the taxonomy by categorizing related literature and providing a detailed analysis of an exemplar paper. The proposed taxonomy offers designers and researchers a concise overview of the current state of driver cooperation and insights for future work. Further, the taxonomy can guide automotive HMI designers in ideation, communication, comparison, and reflection of cooperative driving interfaces. UR - https://doi.org/10.3390/mti8030016 KW - automated driving KW - cooperative driving KW - human–computer interaction KW - taxonomy development KW - literature survey Y1 - 2024 UR - https://doi.org/10.3390/mti8030016 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-47152 SN - 2414-4088 VL - 8 IS - 3 PB - MDPI CY - Basel ER - TY - JOUR A1 - Manger, Carina A1 - Vogl, Annalena A1 - Riener, Andreas T1 - Cognitive Biases in User Interaction with Automated Vehicles: The Influence of Explainability and Mental Models JF - Applied Sciences N2 - 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. UR - https://doi.org/10.3390/app152011030 Y1 - 2025 UR - https://doi.org/10.3390/app152011030 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-63831 SN - 2076-3417 VL - 15 IS - 20 PB - MDPI CY - Basel ER - TY - CHAP A1 - Ehsan, Upol A1 - Wintersberger, Philipp A1 - Liao, Q. Vera A1 - Watkins, Elizabeth Anne A1 - Manger, Carina A1 - Daumé III, Hal A1 - Riener, Andreas A1 - Riedl, Mark O. ED - Diniz Junqueira Barbosa, Simone ED - Lampe, Cliff ED - Appert, Caroline ED - Shamma, David T1 - Human-Centered Explainable AI (HCXAI): Beyond opening the black-box of AI T2 - CHI’22: Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems UR - https://doi.org/10.1145/3491101.3503727 KW - explainable artifcial intelligence KW - interpretable machine learning KW - interpretability KW - artifcial intelligence KW - responsible AI KW - trust in automation KW - algorithmic fairness Y1 - 2022 UR - https://doi.org/10.1145/3491101.3503727 SN - 978-1-4503-9156-6 PB - ACM CY - New York ER - TY - CHAP A1 - Ehsan, Upol A1 - Wintersberger, Philipp A1 - Watkins, Elizabeth Anne A1 - Manger, Carina A1 - Ramos, Gonzalo A. A1 - Weisz, Justin A1 - Daumé III, Hal A1 - Riener, Andreas A1 - Riedl, Mark O. T1 - Human-Centered Explainable AI (HCXAI): Coming of age T2 - CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems UR - https://doi.org/10.1145/3544549.3573832 Y1 - 2023 UR - https://doi.org/10.1145/3544549.3573832 SN - 978-1-4503-9422-2 PB - ACM CY - New York ER - TY - CHAP A1 - Dong, Jiayuan A1 - Nadri, Chihab A1 - Alvarez, Ignacio A1 - Diels, Cyriel A1 - Lee, Myeongkyu A1 - Li, Jingyi A1 - Liao, Pei Hsuan A1 - Manger, Carina A1 - Sadeghian, Shadan A1 - Schuß, Martina A1 - Walker, Bruce N. A1 - Walker, Francesco A1 - Wang, Yiyuan A1 - Jeon, Myounghoon T1 - “Play Your Anger”: A Report on the Empathic In-vehicle Interface Workshop T2 - 15th International ACM Conference on Automotive User Interfaces: Adjunct Conference Proceedings UR - https://doi.org/10.1145/3581961.3609865 KW - HCI KW - Empathy KW - Human Vehicle Interaction KW - In-Vehicle User Interface Y1 - 2023 UR - https://doi.org/10.1145/3581961.3609865 SN - 979-8-4007-0112-2 SP - 168 EP - 173 PB - ACM CY - New York ER - TY - CHAP A1 - Ammeling, Jonas A1 - Manger, Carina A1 - Kwaka, Elias A1 - Krügel, Sebastian A1 - Uhl, Matthias A1 - Kießig, Angelika A1 - Fritz, Alexis A1 - Ganz, Jonathan A1 - Riener, Andreas A1 - Bertram, Christof A1 - Breininger, Katharina A1 - Aubreville, Marc ED - Stolze, Markus ED - Loch, Frieder ED - Baldauf, Matthias ED - Alt, Florian ED - Schneegass, Christina ED - Kosch, Thomas ED - Hirzle, Teresa ED - Sadeghian, Shadan ED - Draxler, Fiona ED - Bektas, Kenan ED - Lohan, Katrin ED - Knierim, Pascal T1 - Appealing but Potentially Biasing - Investigation of the Visual Representation of Segmentation Predictions by AI Recommender Systems for Medical Decision Making T2 - Mensch und Computer 2023: Building Bridges: Tagungsband (Proceedings) UR - https://doi.org/10.1145/3603555.3608561 Y1 - 2023 UR - https://doi.org/10.1145/3603555.3608561 SN - 979-8-4007-0771-1 SP - 330 EP - 335 PB - ACM CY - New York ER - TY - CHAP A1 - Manger, Carina A1 - Preiwisch, Anna A1 - Riener, Andreas T1 - Invisible Barriers: Understanding and Supporting the Mobility Needs and Challenges of Individuals with Mental Health Conditions T2 - Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia UR - https://doi.org/10.1145/3744335.3758489 Y1 - 2025 UR - https://doi.org/10.1145/3744335.3758489 SN - 979-8-4007-2014-7 SP - 100 EP - 105 PB - ACM CY - New York ER - TY - CHAP A1 - Peintner, Jakob A1 - Manger, Carina A1 - Alvarez, Ignacio A1 - Riener, Andreas T1 - Enhancing Pedestrian Realism in Adverse-Weather Driving Simulations Using Motion Capture Data T2 - Adjunct Conference Proceedings: 17th International ACM Conference on Automotive User Interfaces and Interactive Vehicular Applications, September 22-25, 2025, Brisbane, Australia UR - https://doi.org/10.1145/3744335.3758507 Y1 - 2025 UR - https://doi.org/10.1145/3744335.3758507 SN - 979-8-4007-2014-7 SP - 214 EP - 219 PB - ACM CY - New York ER - TY - CHAP A1 - Manger, Carina A1 - Albrecht, Kathrin A1 - Riener, Andreas ED - Maedche, Alexander ED - Beigl, Michael ED - Gerling, Kathrin ED - Mayer, Sven T1 - Explanation Needs in Automated Driving: Insights from German Driving Education and Vehicle Acquisition T2 - MuC'24: Proceedings of the 2024 Conference on Mensch und Computer N2 - 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. UR - https://doi.org/10.1145/3670653.3670679 Y1 - 2024 UR - https://doi.org/10.1145/3670653.3670679 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-50497 SN - 979-8-4007-0998-2 SP - 288 EP - 298 PB - ACM CY - New York ER - TY - JOUR A1 - Peintner, Jakob A1 - Manger, Carina A1 - Berger, Melanie A1 - Riener, Andreas T1 - Balancing transparency and control: The impact of AI explanation detail on user perception in automated vehicles JF - Transportation Research Interdisciplinary Perspectives N2 - 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. UR - https://doi.org/10.1016/j.trip.2025.101742 Y1 - 2025 UR - https://doi.org/10.1016/j.trip.2025.101742 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64740 SN - 2590-1982 VL - 2025 IS - 34 PB - Elsevier CY - Amsterdam ER - TY - INPR A1 - Peintner, Jakob A1 - Manger, Carina A1 - Berger, Melanie A1 - Riener, Andreas T1 - Balancing Transparency and Control: The Impact of Ai Explanation Detail on User Perception in Automated Vehicles T2 - SSRN UR - https://dx.doi.org/10.2139/ssrn.5027721 Y1 - 2024 UR - https://dx.doi.org/10.2139/ssrn.5027721 PB - Elsevier CY - Amsterdam ER -