This paper presents a novel approach to visual attention training for novice tram drivers by combining a tram driving simulator with eye-tracking-enabled Augmented Reality (AR) glasses. Based on previous eye-tracking studies and interviews with tram driving instructors, we identified issues related to the attention distribution of novice drivers. That is, we found that driver field-of-view areas critical to tram-driving safety, are often neglected by novices. For instance, such areas enable drivers to check the right-side mirror before turning right. The training system proposed here aims to direct novice visual attention to critical areas by highlighting overlooked regions, displaying directional arrows, or providing auditory cues from the left or right side. Integration of real-time eye tracking into AR glasses supports continuous monitoring of trainee gaze patterns, offering instructors valuable information on trainee visual behavior. Such real-time data allows for dynamic adaptation of training cues, ensuring that visual attention guidance is both relevant and personalized. The proposed system has the potential to enhance situational awareness among tram drivers.

Augmented reality (AR) is emerging in visual search tasks for increasingly immersive interactions with virtual objects. We propose an AR approach providing visual and audio hints along with gaze-assisted instant post-task feedback for search tasks based on mobile head-mounted display (HMD). The target case was a book-searching task, in which we aimed to explore the effect of the hints together with the task feedback with two hypotheses. H1: Since visual and audio hints can positively affect AR search tasks, the combination outperforms the individuals. H2: The gaze-assisted instant post-task feedback can positively affect AR search tasks. The proof-of-concept was demonstrated by an AR app in HMD and a comprehensive user study (n=96) consisting of two sub-studies, Study I (n=48) without task feedback and Study II (n=48) with task feedback. Following quantitative and qualitative analysis, our results partially verified H1 and completely verified H2, enabling us to conclude that the synthesis of visual and audio hints conditionally improves the AR visual search task efficiency when coupled with task feedback.

As a cutting edge technique requiring high-precision equipment, augmented reality (AR) and its users are influenced by the ambient environment. With the tremendous effect brought by COVID-19 pandemic, most people have shifted from on-site working to remote working. In this study, we propose an initial solution to explore the impact of COVID-19 pandemic on AR users working in these two situations. We develop a prototype application facilitated with gamification process in which users are requested to play an AR game in headset both in on-site and remote working environments. This game, which is highly dependent on the ambient environment, enables people to memorize, distinguish, and place virtual objects when immersing themselves into different surroundings with distinct distractors. We envision to conduct more user studies investigating how COVID-19 affects AR users, which could lead to more in-depth studies in the future.

Augmented reality (AR) is today becoming more widely utilized as it allows for interacting with the virtual objects. In this study, we propose an head-mounted display (HMD) AR system supporting book searching with visual cues. The visual cue is represented as a light-green blob hinting users for task completion, which significantly strengthens the overall performance. The system is implemented by using Microsoft HoloLens 2. The proof-of-concept version of the proposed solution is demonstrated in a pilot user study (n=8) comprising an experimental group (with visual cues, n=4) and a control group (without visual cues, n=4), followed by quantitative analysis of task completion time (TCT) and NASA task load index (TLX). The results show that our proposed HMD AR solution improved the task performance and had cognitive benefits for book searching tasks.

This paper presents an approach towards aiding the rehabilitation exercises in amblyopia care using mixed reality technology.The Lazy Eye Syndrome is tackled here through an interactive holographic application implemented on Microsoft HoloLens device.It provides an entertaining way for the handicapped eye workout as it is based on a simple game of skill.The game is designed in a way that the majority of awarerequiring objects and events are displayed for the cured eye only, remaining the other eye responsible for background and additional information perception.Such disproportion forces an increased activity of the lazy eye, which is to perform more movements and impose the brain to process the sight more extensively.The proposed prototype is an extension of a novel approach towards treating amblyopia, employing software-based stimulation techniques, which could be easily adapted to various age and ability correlated needs of the user, with minimal requirements regarding the exercise setting and preparation.

Reliable transmission is one of the key objectives of research on wireless network optimization. The backpressure-based Max-Weight Scheduling (MWS) policy is theoretically proven to be the optimal solution for achieving the highest available throughput. On the other hand, proactive routing protocols, such as Optimized Link State Protocol (OLSR), are able to compute reliable paths, which, in turn, can be used as a basis for MWS-based resource allocation. However, in its standard implementation, OLSR is a single-path protocol, whereas it is known that at least in some scenarios MWS algorithms can provide better network performance when used together with multi-path packet forwarding. Following this motivation, we implemented a modification of the OLSR protocol aimed at realizing multi-path routing in cooperation with the backpressure policy. The scheduling component was implemented at the application layer, and was supported by a mechanism for an indirect estimation of the MAC-layer queue state. Thanks to this approach, the system may work with the unmodified existing 802.11 MAC, and can be deployed in existing wireless networks. We tested the proposed solutions in a realistic wireless network scenario.