Designing a user-defined gesture vocabulary for an in-vehicle climate control system

Fariman, Hessam Jahani; Alyamani, Hasan J.; Kavakli, Manolya; Hamey, Len

doi:10.1145/3010915.3010955

Cited by 31 publications

(22 citation statements)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…After the review of related work on commands and references for smart home devices (especially [4,5,[9][10][11]14,[24][25][26][27][28][29]), we identified a list of commands that were frequently used and applicable in multiple devices. We listed all commands and then removed those that referred to particular controls of a user interface.…”

Section: Referentsmentioning

confidence: 99%

Frame-Based Elicitation of Mid-Air Gestures for a Smart Home Device Ecosystem

Vogiatzidakis

Koutsabasis

2019

Informatics

View full text Add to dashboard Cite

If mid-air interaction is to be implemented in smart home environments, then the user would have to exercise in-air gestures to address and manipulate multiple devices. This paper investigates a user-defined gesture vocabulary for basic control of a smart home device ecosystem, consisting of 7 devices and a total of 55 referents (commands for device) that can be grouped to 14 commands (that refer to more than one device). The elicitation study was conducted in a frame (general scenario) of use of all devices to support contextual relevance; also, the referents were presented with minimal affordances to minimize widget-specific proposals. In addition to computing agreement rates for all referents, we also computed the internal consistency of user proposals (single-user agreement for multiple commands). In all, 1047 gestures from 18 participants were recorded, analyzed, and paired with think-aloud data. The study reached to a mid-air gesture vocabulary for a smart-device ecosystem, which includes several gestures with very high, high and medium agreement rates. Furthermore, there was high consistency within most of the single-user gesture proposals, which reveals that each user developed and applied her/his own mental model about the whole set of interactions with the device ecosystem. Thus, we suggest that mid-air interaction support for smart homes should not only offer a built-in gesture set but also provide for functions of identification and definition of personalized gesture assignments to basic user commands.

show abstract

Section: Referentsmentioning

confidence: 99%

Frame-Based Elicitation of Mid-Air Gestures for a Smart Home Device Ecosystem

Vogiatzidakis

Koutsabasis

2019

Informatics

View full text Add to dashboard Cite

show abstract

“…Several works have investigated GBI in the context of human-computer interaction (Fariman, Alyamani, Kavakli, & Hamey, 2016; Geiger, Nieschulz, Zobl, & Lang, 2002; März, Schwahlen, Geisler, & Kopinski; May, Gable, Wu, Sardesai, & Walker, 2016). However, there is no gesture set that is widely accepted and commonly used or precise guidelines on how gesture interaction systems should be designed from a user’s perspective (Zhang & Angell, 2014).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Gesture-Based In-Vehicle Interaction: User Experience and the Potential to Reduce Driver Distraction

Graichen

Krems

2019

Hum Factors

View full text Add to dashboard Cite

Objective: We observe the effects of in-vehicle system gesture-based interaction versus touch-based interaction on driver distraction and user experience. Background: Driver distraction is a major problem for traffic safety, as it is a contributing factor to a number of accidents. Visual distraction in particular has a highly negative impact on the driver. One possibility for reducing visual driver distraction is to use new forms of interaction in the vehicle, such as gesture-based interaction. Method: In this experiment, participants drove on a motorway or in a city scenario while using touch-based interaction or gesture-based interaction. Subjective data, such as acceptance and workload, and objective data, including glance behavior, were gathered. Results: As a result, participants rated their subjective impressions of safe driving as higher when using gesture-based interaction. More specifically, acceptance and attractiveness were higher, and workload was lower. The participants performed significantly fewer glances to the display and the glances were much shorter. Conclusion: Gestures are a positive alternative for in-vehicle interaction since effects on driver distraction are less significant when compared to touch-based interaction. Application: Potential application of this research includes interaction design of typical in-vehicle information and entertainment functions.

show abstract

“…Several works have investigated GBI in the context of human–computer interaction (HCI; Fariman et al, 2016; Geiger et al, 2002; May et al, 2016; März et al, 2016). However, most of today’s applications are adopted for entertainment (e.g., video game controllers, virtual reality, and motion-controlled drones).…”

Section: Introductionmentioning

confidence: 99%

Effects of Gesture-Based Interaction on Driving Behavior: A Driving Simulator Study Using the Projection-Based Vehicle-in-the-Loop

Graichen

Krems

2020

Hum Factors

View full text Add to dashboard Cite

Objective We observe the driving performance effects of gesture-based interaction (GBI) versus touch-based interaction (TBI) for in-vehicle information systems (IVISs). Background As a contributing factor to a number of traffic accidents, driver distraction is a significant problem for traffic safety. More specifically, visual distraction has a strong negative impact on driving performance and risk perception. Thus, the implementation of new interaction systems that use midair gestures to encourage glance-free interactions could reduce visual distraction among drivers. Methods In this experiment, participants drove a projection-based Vehicle-in-the-Loop. The projection-based technology combines a visual simulation with kinesthetic, vestibular, and auditory feedback from a car on a test track. While driving, participants used GBI or TBI to perform IVIS tasks. To investigate driving behavior related to critical driving situations and car-following maneuvers, vehicle data based upon longitudinal and lateral driving were collected. Results Participants reacted faster to critical driving situations when using GBI compared to TBI. For drivers using TBI, steering performance decreased and time headway to a preceding vehicle was higher. Conclusion Gestures provide a safe alternative to in-vehicle interactions. Moreover, GBI has fewer effects on driver distraction than TBI. Application Potential applications of this research include all in-vehicle interaction systems used by drivers.

show abstract

Designing a user-defined gesture vocabulary for an in-vehicle climate control system

Cited by 31 publications

References 18 publications

Frame-Based Elicitation of Mid-Air Gestures for a Smart Home Device Ecosystem

Frame-Based Elicitation of Mid-Air Gestures for a Smart Home Device Ecosystem

Evaluation of Gesture-Based In-Vehicle Interaction: User Experience and the Potential to Reduce Driver Distraction

Effects of Gesture-Based Interaction on Driving Behavior: A Driving Simulator Study Using the Projection-Based Vehicle-in-the-Loop

Contact Info

Product

Resources

About