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 - 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 - 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 - JOUR A1 - Wintersberger, Philipp A1 - Janotta, Frederica A1 - Peintner, Jakob A1 - Löcken, Andreas A1 - Riener, Andreas T1 - Evaluating feedback requirements for trust calibration in automated vehicles JF - it – Information Technology UR - https://doi.org/10.1515/itit-2020-0024 KW - automated driving KW - trust in automation KW - user acceptance KW - user studies KW - mixed/augmented reality KW - adaptive UIs KW - personalized UIs Y1 - 2021 UR - https://doi.org/10.1515/itit-2020-0024 SN - 1611-2776 VL - 63 IS - 2 SP - 111 EP - 122 PB - De Gruyter CY - Berlin ER - TY - JOUR A1 - Himmels, Chantal A1 - Parduzi, Arben A1 - Löcken, Andreas A1 - Protschky, Valentin A1 - Venrooij, Joost A1 - Riener, Andreas T1 - Validating risk behavior in driving simulation using naturalistic driving data JF - Transportation Research Part F: Traffic Psychology and Behaviour UR - https://doi.org/10.1016/j.trf.2024.09.026 Y1 - 2024 UR - https://doi.org/10.1016/j.trf.2024.09.026 SN - 1369-8478 SN - 1873-5517 VL - 2024 IS - 107 SP - 710 EP - 725 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Wintersberger, Philipp A1 - Dey, Debargha A1 - Löcken, Andreas T1 - Editorial: Interaction between automated vehicles and other road users JF - Frontiers in Robotics and AI UR - https://doi.org/10.3389/frobt.2023.1228093 KW - automated driving KW - vulnerable road user (VRU) KW - traffic safety KW - external human-machine interface (eHMI) KW - human-computer interaction Y1 - 2023 UR - https://doi.org/10.3389/frobt.2023.1228093 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-37603 SN - 2296-9144 VL - 10 PB - Frontiers Media CY - Lausanne ER - TY - CHAP A1 - Matviienko, Andrii A1 - Boot, Mario A1 - Löcken, Andreas A1 - Pfleging, Bastian A1 - Löchtefeld, Markus A1 - Von Sawitzky, Tamara A1 - Savino, Gian-Luca A1 - Sturdee, Miriam A1 - Andres, Josh A1 - Boyer, Kristy Elizabeth A1 - Brewster, Stephen A1 - Mueller, Florian 'Floyd' ED - Mueller, Florian 'Floyd' ED - Kyburz, Penny ED - Williamson, Julie R. ED - Sas, Corina T1 - Learning from Cycling: Discovering Lessons Learned from CyclingHCI T2 - CHI'24: Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Systems UR - https://doi.org/10.1145/3613905.3636291 Y1 - 2024 UR - https://doi.org/10.1145/3613905.3636291 SN - 979-8-4007-0331-7 PB - ACM CY - New York ER -