Increasing User Experience and Trust in Automated Vehicles via an Ambient Light Display

Löcken, Andreas; Frison, Anna-Katharina; Fahn, Vanessa; Kreppold, Dominik; Götz, Maximilian; Riener, Andreas

doi:10.1145/3379503.3403567

Cited by 18 publications

(8 citation statements)

References 39 publications

(66 reference statements)

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“…The participants were divided into two hue groups, blue (468 nm) and orange (589 nm), depending on individual preference. While the earlier studies focused on the effects of light behaviors on self-assessments [48,36,37,33,50,11], our experiment demonstrated the drivers' physiological effect alongside self-assessments. The two hue groups showed similar tendencies in the EEG responses and the subjective assessments.…”

Section: A General Discussionmentioning

confidence: 47%

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User Responses to Dynamic Light in Automobiles With EEG and Self-Assessments

et al. 2022

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This study investigates the emotional responses to vehicle interior lighting by measuring physiological reactions and psychological judgments. Individually controllable LEDs are installed in the front area of the passenger car (Sonata DN8, Hyundai Motor Company) and generate light stimuli by varying the attributes of the LEDs for the user experiment. Forty participants volunteered in the experiment and opted to evaluate either blue (468 nm) and orange (589 nm) light prior to the main session. Each participant was presented with twelve lighting signatures made with six lighting behaviors applied to two types of placements. During the experiment, we collected the alpha and beta waves using an electroencephalography (EEG) and subjective assessments of the lighting with seven questions. The ratio of the beta waves was the highest in the Blink mode, followed by the Fade and Collide modes. We combined the EEG responses with subjective assessments of seven adjective pairs toward evidence-based guidance for designing user-centered light in automobiles.

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Section: A General Discussionmentioning

confidence: 47%

“…Recent studies on dynamic light behaviors distinguished the lighting signatures by varying their speed [48,36,37] and characteristics [33,50,11]. In addition, studies focused on visual feedback when light is provided and the transferred effects of the lighting.…”

Section: Related Work a The Potential Of Lighting Behaviors In Vehicl...mentioning

confidence: 99%

User Responses to Dynamic Light in Automobiles With EEG and Self-Assessments

et al. 2022

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“…For example, peripheral LED strips acting as chase lights to influence the driver's perception of speed [250] or using peripheral light flashes behind the steering wheel to indicate a TOR [323]. Some approaches utilize ambient light, e.g., to highlight pedestrian trajectories [235]. Most approaches in our synthesis used screens of various sizes and functions, e.g., [189,193,354,393].…”

Section: Output Modalitiesmentioning

confidence: 99%

A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

Jansen

Colley

Rukzio

2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Automotive user interfaces constantly change due to increasing automation, novel features, additional applications, and user demands. While in-vehicle interaction can utilize numerous promising modalities, no existing overview includes an extensive set of human sensors and actuators and interaction locations throughout the vehicle interior. We conducted a systematic literature review of 327 publications leading to a design space for in-vehicle interaction that outlines existing and lack of work regarding input and output modalities, locations, and multimodal interaction. To investigate user acceptance of possible modalities and locations inferred from existing work and gaps unveiled in our design space, we conducted an online study (N=48). The study revealed users' general acceptance of novel modalities (e.g., brain or thermal activity) and interaction with locations other than the front (e.g., seat or table). Our work helps practitioners evaluate key design decisions, exploit trends, and explore new areas in the domain of in-vehicle interaction.

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“…Following the credo that an invisible interface is also not usable, we, for example, suggest placing the screen closer to the instrument cluster. Considering that a driver's visual focus is mainly on the street during manual driving, it may be even more beneficial to actively address peripheral vision using an ambient light display (cf., [61,62]) or another display modality that does not address a cognitive resource that is already loaded by the maintaining situational awareness and possibly performing the NDRT. The design of this interface may impact the performance when handing back driving control to the automation and thus help optimizing safety.…”

Section: Implications For Future Interfacesmentioning

confidence: 99%

Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated Driving

Schartmüller

Weigl

Löcken

et al. 2021

MTI

Self Cite

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(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.

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Increasing User Experience and Trust in Automated Vehicles via an Ambient Light Display

Cited by 18 publications

References 39 publications

User Responses to Dynamic Light in Automobiles With EEG and Self-Assessments

User Responses to Dynamic Light in Automobiles With EEG and Self-Assessments

A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated Driving

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