Augmented reality warnings in vehicles: Effects of modality and specificity on effectiveness

Schwarz, Felix; Fastenmeier, Wolfgang

doi:10.1016/j.aap.2017.01.019

Cited by 70 publications

(25 citation statements)

References 37 publications

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“…Previous research by Werneke and Vollrath [78] found that augmented feedback in the form of a bird's eye view received more positive ratings from drivers than a late warning in the form of a sphere that highlighted a dangerous vehicle. Schwarz and Fastenmeier [79] found that augmented reality warnings (i.e., scenario-specific icons accompanied by arrows coming from the direction of danger) were rated more highly than unspecific visual or auditory warnings.…”

Section: Subjective Datamentioning

confidence: 99%

Rolling Out the Red (and Green) Carpet: Supporting Driver Decision Making in Automation-to-Manual Transitions

Eriksson

Petermeijer

Zimmermann

et al. 2019

IEEE Trans. Human-Mach. Syst.

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This paper assessed four types of human-machine interfaces (HMIs), classified according to the stages of automation proposed by Parasuraman et al. ["A model for types and levels of human interaction with automation," IEEE Trans. Syst. Man, Cybern. A, Syst. Humans, vol. 30, no. 3, pp. 286-297, May 2000]. We hypothesized that drivers would implement decisions (lane changing or braking) faster and more correctly when receiving support at a higher automation stage during transitions from conditionally automated driving to manual driving. In total, 25 participants with a mean age of 25.7 years (range 19-36 years) drove four trials in a driving simulator, experiencing four HMIs having the following different stages of automation: baseline (information acquisitionlow), sphere (information acquisition-high), carpet (information analysis), and arrow (decision selection), presented as visual overlays on the surroundings. The HMIs provided information during two scenarios, namely a lane change and a braking scenario. Results showed that the HMIs did not significantly affect the drivers' initial reaction to the take-over request. Improvements were found, however, in the decision-making process: When drivers experienced the carpet or arrow interface, an improvement in correct decisions (i.e., to brake or change lane) occurred. It is concluded that visual HMIs can assist drivers in making a correct braking or lane change maneuver in a take-over scenario. Future research could be directed toward misuse, disuse, errors of omission, and errors of commission.

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Section: Subjective Datamentioning

confidence: 99%

Rolling Out the Red (and Green) Carpet: Supporting Driver Decision Making in Automation-to-Manual Transitions

Eriksson

Petermeijer

Zimmermann

et al. 2019

IEEE Trans. Human-Mach. Syst.

View full text Add to dashboard Cite

show abstract

“…The tactile channel is also affected by existing vibrations from the engine and hydraulics of a heavy vehicle and through the movement in the terrain during groundworks. Moreover, there are prior studies [12][13][14] that indicate a strong user preference for the visual channel, compared to other senses, which can then be used to improve performance further.…”

Section: Introductionmentioning

confidence: 99%

Evaluating Mixed Reality Notifications to Support Excavator Operator Awareness

Wallmyr

Sitompul

Holstein

et al. 2019

Human-Computer Interaction – INTERACT 2019

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Operating heavy vehicles, for instance an excavator, requires a high level of attention to the operation done using the vehicle and awareness of the surroundings. Digital transformation in heavy vehicles aims to improve productivity and user experience, but it can also increase the operators mental load because of a higher demand of attention to instrumentation and controls, subsequently leading to reduced situation awareness. One way to mitigate this, is to display information within the operators' field of view, which enhances information detectability through quick glances, using mixed reality interfaces. This work explores two types of mixed reality visualizations and compares them to a traditional display setup in a simulated excavator environment. We have utilized eye-tracking glasses to study users' attention to the task, surrounding awareness, and interfaces, followed by a NASA-RTLX questionnaire to evaluate the users' reported mental workload. The results indicate benefits for the mixed reality approaches, with lower workload ratings together with an improved rate in detection of presented information.

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“…In addition, the placement of overlaid information was investigated using the same approach. Due to the research goal, the experimental approach of Sanders and McCormick (1993) was adopted. In experimental research, variables are manipulated and their effect on human performance or the system is evaluated.…”

Section: Methodsmentioning

confidence: 99%

Virtual prototyping in the design of see-through features in mobile machinery

2019

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Limited visibility from a mobile machine cab can decrease task performance and lead to accidents. Therefore, it is important to consider visibility issues already in the design phase. This paper describes the use of virtual prototyping in the evaluation of see-through features of mobile work machines. The goal is to evaluate whether two different machine boom transparency levels have an effect on task performance. In addition, two alternative placements of overlaid information in the operators' field of view are assessed. A within-subject design was used in this study. Based on the results, there was no significant difference in performance between the transparency levels. However, the test participants preferred a transparency level of 70-80% (where 0% is completely opaque). Similar results were found with the placement of the overlaid information, which had no significant effect on task performance. Both placements, on the windscreen and on the tunnel wall, were equally favoured by the participants. The findings of this study contribute to the design of see-through features for mobile work machines. In addition, the study demonstrates the use of virtual prototyping in the design of novel features in human-machine systems.

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Augmented reality warnings in vehicles: Effects of modality and specificity on effectiveness

Cited by 70 publications

References 37 publications

Rolling Out the Red (and Green) Carpet: Supporting Driver Decision Making in Automation-to-Manual Transitions

Rolling Out the Red (and Green) Carpet: Supporting Driver Decision Making in Automation-to-Manual Transitions

Evaluating Mixed Reality Notifications to Support Excavator Operator Awareness

Virtual prototyping in the design of see-through features in mobile machinery

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