| 1. |
- Dey, Debargha, et al.
(författare)
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Color and Animation Preferences for a Light Band EHMI in Interactions Between Automated Vehicles and Pedestrians
- 2020
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Ingår i: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems. - New York, NY, USA : Association for Computing Machinery.
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Konferensbidrag (refereegranskat)abstract
- In this paper, we report user preferences regarding color and animation patterns to support the interaction between Automated Vehicles (AVs) and pedestrians through an external Human-Machine-Interface (eHMI). Existing concepts of eHMI differ – among other things – in their use of colors or animations to express an AV’s yielding intention. In the absence of empirical research, there is a knowledge gap regarding which color and animation leads to highest usability and preferences in traffic negotiation situations. We conducted an online survey (N=400) to investigate the comprehensibility of a light band eHMI with a combination of 5 color and 3 animation patterns for a yielding AV. Results show that cyan is considered a neutral color for communicating a yielding intention. Additionally, a uniformly flashing or pulsing animation is preferred compared to any pattern that animates sideways. These insights can contribute in the future design and standardization of eHMIs.
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| 2. |
- Dey, Debargha, et al.
(författare)
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Communicating the intention of an automated vehicle to pedestrians : The contributions of eHMI and vehicle behavior
- 2021
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Ingår i: IT-Information Technology. - : Walter de Gruyter GmbH. - 1611-2776 .- 2196-7032. ; 63:2, s. 123-141
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Tidskriftsartikel (refereegranskat)abstract
- External Human-Machine Interfaces (eHMIs) are expected to bridge the communication gap between an automated vehicle (AV) and pedestrians to replace the missing driver-pedestrian interaction. However, the relative impact of movement-based implicit communication and explicit communication with the aid of eHMIs on pedestrians has not been studied and empirically evaluated. In this study, we pit messages from an eHMI against different driving behaviors of an AV that yields to a pedestrian to understand whether pedestrians tend to pay more attention to the motion dynamics of the car or the eHMI in making road-crossing decisions. Our contributions are twofold: we investigate (1) whether the presence of eHMIs has any objective effect on pedestrians’ understanding of the vehicle’s intent, and (2) how the movement dynamics of the vehicle affect the perception of the vehicle intent and interact with the impact of an eHMI. Results show that (1) eHMIs help in convincing pedestrians of the vehicle’s yielding intention, particularly when the speed of the vehicle is slow enough to not be an obvious threat, but still fast enough to raise a doubt about a vehicle’s stopping intention, and (2) pedestrians do not blindly trust the eHMI: when the eHMI message and the vehicle’s movement pattern contradict, pedestrians fall back to movement-based cues. Our results imply that when explicit communication (eHMI) and implicit communication (motion-dynamics and kinematics) are in alignment and work in tandem, communication of the AV’s yielding intention can be facilitated most effectively. This insight can be useful in designing the optimal interaction between AVs and pedestrians from a user-centered design perspective when driver-centric communication is not available.
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| 3. |
- Dey, Debargha, et al.
(författare)
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Taming the eHMI jungle : A classification taxonomy to guide, compare, and assess the design principles of automated vehicles' external human-machine interfaces
- 2020
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Ingår i: Transportation Research Interdisciplinary Perspectives. - : Elsevier Ltd. - 2590-1982. ; 7
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Tidskriftsartikel (refereegranskat)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 allows a 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 70 eHMI 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. © 2020 The Authors
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| 4. |
- Matviienko, Andrii, et al.
(författare)
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Learning from Cycling: Discovering Lessons Learned from CyclingHCI
- 2024
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Ingår i: CHI 2024 - Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Sytems. - : Association for Computing Machinery (ACM).
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Konferensbidrag (refereegranskat)abstract
- Cycling plays an essential role in sustainable mobility, health, and socializing. This workshop aims to collect and discuss the lessons learned from Cycling Human-Computer Interaction (CyclingHCI). For this, we will gather researchers and experts in the field to discuss what we learned from designing, building, and evaluating CyclingHCI systems. We will start the workshop with three lessons learned from CyclingHCI defined by the organizers and their experience in the field, which include (1) a lack of theories, tools, and perspectives, (2) knowledge about designing for safety and inclusive cycling, and (3) evaluation methods and environments. Taken together, with this work, we aim to promote interactive technology to get more people cycling, profiting from the many associated benefits.
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| 5. |
- Matviienko, Andrii, et al.
(författare)
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QuantiBike : Quantifying Perceived Cyclists' Safety via Head Movements in Virtual Reality and Outdoors
- 2023
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Ingår i: Proceedings - SUI 2023: ACM Symposium on Spatial User Interaction. - : Association for Computing Machinery (ACM).
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Konferensbidrag (refereegranskat)abstract
- The current level of road safety for cyclists is estimated mainly based on police reports and self-reports collected during surveys. However, the former focuses on post-accident situations, while the latter is based on subjective perception and focuses only on road sections. This work builds the foundation to automatically assess perceived cyclists' safety by analyzing their head movements. In an indoor experiment (N = 12) using a Virtual Reality bicycle simulator, we discovered that perceived safety correlates with head rotation frequency and duration but not with head rotation angles. Based on this, we implemented a novel and minimalistic approach to detect head movements based on sensor data from Apple AirPods and an iPhone and conducted an outdoor experiment (N = 8). Our results indicate that perceived safety correlates with head rotation frequency and duration only at uncontrolled intersections when turning left and does not necessarily apply to all situations.
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| 6. |
- Matviienko, Andrii, et al.
(författare)
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Quantified cycling safety : Towards a mobile sensing platform to understand perceived safety of cyclists
- 2021
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Ingår i: Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems. - New York, NY, USA : Association for Computing Machinery (ACM). ; , s. 1-6
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Konferensbidrag (refereegranskat)abstract
- Today’s level of cyclists’ road safety is primarily estimated using accident reports and self-reported measures. However, the former is focused on post-accident situations and the latter relies on subjective input. In our work, we aim to extend the landscape of cyclists’ safety assessment methods via a two-dimensional taxonomy, which covers data source (internal/external) and type of measurement (objective/subjective). Based on this taxonomy, we classify existing methods and present a mobile sensing concept for quantified cycling safety that fills the identified methodological gap by collecting data about body movements and physiological data. Finally, we outline a list of use cases and future research directions within the scope of the proposed taxonomy and sensing concept.
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