Inattentional Blindness in Augmented Reality Head-Up Display-Assisted Driving

Wang, Yuwei; Wu, Yimin A.; Chen, Cheng; Wu, Bohan; Ma, Shu; Wang, Duming; Li, Hongting; Yang, Zhen

doi:10.1080/10447318.2021.1970434

Cited by 30 publications

(9 citation statements)

References 53 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this state, object disappearances are more challenging to detect for the pilot than monitoring the other vital parameters of the aircraft. It is also reported that multiple changes in a central position are detected easily compared to the extreme end [17,18]. Avionics display intends to provide better SA but also depends on display brightness.…”

Section: Literature Reviewmentioning

confidence: 99%

Human Factors While Using Head-Up-Display in Low Visibility Flying Conditions

Kumar¹,

Saini²,

Agrawal³

et al. 2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

Flying an aircraft in low visibility is still a challenging task for the pilot. It requires precise and accurate situational awareness (SA) in real-time. A Headup Display (HUD) is used to project collimated internal and external flight information on a transparent screen in the pilot's forward field of view, which eliminates the change of eye position between Head-Down-Display (HDD) instruments and outer view through the windshield. Implementation of HUD increases the SA and reduces the workload for the pilot. But to provide a better flying capability for the pilot, projecting extensive information on HUD causes human factor issues that reduce pilot performance and lead to accidents in low visibility conditions. The literature shows that human error is the leading cause of more than 70% of aviation accidents. In this study, the ability of the pilot able to read background and symbology information of HUD at a different level of background seen complexity, such as symbology brightness, transition time, amount of Symbology, size etc., in low visibility conditions is discussed. The result shows that increased complexity on the HUD causes more detection errors.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Human Factors While Using Head-Up-Display in Low Visibility Flying Conditions

Kumar¹,

Saini²,

Agrawal³

et al. 2023

Intelligent Automation &Amp; Soft Computing

View full text Add to dashboard Cite

show abstract

“…Thus, we split the existing training systems in two categories. The first category [1] - [10] is based on AR and VR. The second category [11] - [13] uses both IoT and IVT technologies for creating safety training systems.…”

Section: Training Based On Ivt/iot Technologiesmentioning

confidence: 99%

“…For the first category, Wang et al [1] provided an integrated design framework for leveraging current advancements in AR to improve the safety of highway-workers by providing real-time multimodal alerts on-the-spot. Furthermore, this study highlights the interest and commitment of highway employees to both the proposed technology and the suggested user interface.…”

Section: Training Based On Ivt/iot Technologiesmentioning

confidence: 99%

A New Model for Cognitive IVT based on loT for Critical Safety Solutions: Firefighter Use Case

Sassi

Saghafian

Battisti

et al. 2022

2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops (VRW)

View full text Add to dashboard Cite

Immersive visual technologies and Internet of things are considered the main paradigms in defining new models of immersive training for critical safety applications. Accordingly, matching appropriate devices and technologies with the training requirements and its individual, technological, and operational factors is mandatory to achieve the training goals. In this context, we investigate and classify different factors based on immersive technologies, emerging devices, and sensors. Furthermore, we propose a new model for cognitive immersive visual technologies for critical safety solutions. The proposed model is validated in a use case of a fire brigade intervention after an earthquake. The use of this model mitigates heterogeneity conflicts due to the variety of immersive technologies for a specific situation by respecting stakeholders' requirements. This paper helps future researchers, industrial and enterprise stockholders to select adequate immersive visual technologies, devices, and engines for creating further critical safety solutions.

show abstract

“…It can reduce mental workload by leading students to manage their attention better and focus on the most relevant information. On the other hand, they may struggle to prioritize information and allocate their cognitive resources, leading to an increase in their workload (Wang et al, 2022). Hence, it is necessary to investigate how students' metacognitive status (i.e., overconfidence vs. underconfidence) influences their workload in the design of AR environments to ensure they are optimized for efficient information processing and reduced mental workload.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Virtual Instructor and Metacognition on Workload in a Location-Based Augmented Reality Learning Environment

Kim,

Yu,

Seo

et al. 2023

Proceedings of the Human Factors and Ergonomics Society Annual

View full text Add to dashboard Cite

Augmented Reality (AR) technology offers the possibility of experiencing virtual images with physical objects and provides highquality hands-on experiences in an engineering lab environment. However, students still need help navigating the educational content in AR environments due to a mismatch problem between computer-generated 3D images and actual physical objects. This limitation could significantly influence their learning processes and workload in AR learning. In addition, a lack of student awareness of their learning process in AR environments could negatively impact their performance improvement. To overcome those challenges, we introduced a virtual instructor in each AR module and asked a metacognitive question to improve students' metacognitive skills. The results showed that student workload was significantly reduced when a virtual instructor guided students during AR learning. Also, there is a significant correlation between student learning performance and workload when they are overconfident. The outcome of this study will provide knowledge to improve the AR learning environment in higher education settings.

show abstract

Inattentional Blindness in Augmented Reality Head-Up Display-Assisted Driving

Cited by 30 publications

References 53 publications

Human Factors While Using Head-Up-Display in Low Visibility Flying Conditions

Human Factors While Using Head-Up-Display in Low Visibility Flying Conditions

A New Model for Cognitive IVT based on loT for Critical Safety Solutions: Firefighter Use Case

The Effect of Virtual Instructor and Metacognition on Workload in a Location-Based Augmented Reality Learning Environment

Contact Info

Product

Resources

About