Augmented, Virtual and Mixed Reality Passenger Experiences

McGill, Mark; Li, Gang; Ng, A. W. M; Bajorunaite, Laura; Williamson, Julie R.; Pollick, Frank E.; Brewster, Stephen

doi:10.1007/978-3-030-77726-5_17

Cited by 7 publications

(9 citation statements)

References 82 publications

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“…In their research work, McGill et al [28] explore the potential of AR/VR/MR technologies in improving passenger comfort during transportation. Through the synchronization of virtual augmentations with real-world surroundings, immersive technologies present a promising approach to mitigate motion-induced distress by harmonizing perceived and actual motion.…”

Section: Related Workmentioning

confidence: 99%

Motion Sickness in Mixed-Reality Situational Awareness System

Haamer,

Mikhailava,

Podliesnova

et al. 2024

Applied Sciences

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This research focuses on enhancing the user experience within a Mixed-Reality Situational Awareness System (MRSAS). The study employed the Simulator Sickness Questionnaire (SSQ) in order to gauge and quantify the user experience and to compare the effects of changes to the system. As the results of SSQ are very dependant on inherent motion sickness susceptibility, the Motion Sickness Susceptibility Questionnaire (MSQ) was used to normalize the results. The experimental conditions were tested on a simulated setup which was also compared to its real-life counterpart. This simulated setup was adjusted to best match the conditions found in the real system by using post-processing effects. The test subjects in this research primarily consisted of 17–28 years old university students representing both male and female genders as well as a secondary set with a larger age range but predominantly male. In total, there were 41 unique test subjects in this study. The parameters that were analyzed in this study were the Field of View (FoV) of the headset, the effects of peripheral and general blurring, camera distortions, camera white balance and users adaptability to VR over time. All of the results are presented as the average of multiple user results and as scaled by user MSQ. The findings suggest that SSQ scores increase rapidly in the first 10–20 min of testing and level off at around 40–50 min. Repeated exposure to VR reduces MS buildup, and a FoV of 49–54 is ideal for a MRSAS setup. Additionally camera based effects like lens distortion and automatic white balance had negligible effests on MS. In this study a new MSQ based SSQ normalization technique was also developed and utilized for comparison. While the experiments in this research were primarily conducted with the goal of improving the physical Vegvisir system, the results themselves may be applicable for a broader array of VR/MR awareness systems and can help improve the UX of future applications.

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Section: Related Workmentioning

confidence: 99%

Motion Sickness in Mixed-Reality Situational Awareness System

Haamer,

Mikhailava,

Podliesnova

et al. 2024

Applied Sciences

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“…McGill et al [46] noted that regardless of if the action is seen as socially acceptable, the physical space, seatbelts and other passengers sitting nearby would require more discreet interactions with immersive devices. Recent work on the topic [45,63] has already started exploring how confined spaces can be adapted to immersive technology use, suggesting that by using the available furniture, such as seats and backrests we can create new input methods that are more comfortable for a public transport environment.…”

Section: Key Challenges Of Using Immersive Technologies In Public Spacesmentioning

confidence: 99%

Reality Anchors: Bringing Cues from Reality to Increase Acceptance of Immersive Technologies in Transit

Bajorunaite,

Brewster,

Williamson

2023

Proc. ACM Hum.-Comput. Interact.

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Immersive technologies allow us to control and customise how we experience reality, but are not widely used in transit due to safety, social acceptability, and comfort barriers. We propose that cues from reality can create reference points in virtuality, which we call Reality Anchors, will reduce these barriers. We used simulated public transportation journeys in a lab setting to explore Reality Anchors using speculative methods in two studies. Our first study (N=20) explored how elements of reality like objects, furniture, and people could be used as anchors, demonstrating that visibility of other passengers and personal belongings could reduce barriers. Our second study (N=19) focused on journey types that emerged from the first study - self-managed vs. externally managed journeys - revealing that self-managed journeys increased the need for anchors. We conclude that Reality Anchors can reduce concerns associated with immersive technology use in transit, especially for self-managed journeys.

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“…Broadly, there are two approaches to correcting this issue [33,35]. The first is to subtract the vehicle IMU (vIMU ) yaw angle from the headset IMU (hIMU ) yaw angle, effectively removing the influence of the vehicle motion on headset tracking.…”

Section: Technical Challenges 51 Headset Pose Within Car Reference Framementioning

confidence: 99%

“…6DoF headsets with camera-based visual inertial tracking, 3DoF headsets with IMU tracking alone. PassengXR supports several routes towards correcting the headset pose, building on proposals outlined by McGill et al [33] as well as approaches used in research [13,15,17,34], and we outline some of the most common XR headset targets we have encountered thus far, and how our platform can support their correct operation in moving vehicles. Note that we exclude solutions that rely on outside-in tracking (e.g.…”

Section: Technical Challenges 51 Headset Pose Within Car Reference Framementioning

confidence: 99%

“…In an attempt to make it easier for designers to create or test in-car XR interfaces, research has started developing toolkits or platforms that provide templates, and open-source codebases for detecting and using data about the movement and actions of a vehicle, and a user within it. In these situations, it is crucial to separate the sensing of the Head-Mounted Display (HMD) and vehicle motion, so that car movement does not interfere with the user's agency over their experience, or the immersive effect of head-tracking [33,35]. Most platforms use an Inertial Measurement Unit (IMU) to track vehicle orientation, combined with sensors attached to the On-Board Diagnostic (OBD-II) port of the vehicle to poll velocity [13-15, 17, 52].…”

Section: Introductionmentioning

confidence: 99%

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