Search Results (96)

This study proposes a modelling framework for simulating cyclist–vehicle interactions at urban intersections characterised by geometric constraints and variable visibility conditions. A Digital Model (DM) of the intersection geometry was developed in SUMO, complemented by a custom behavioural model calibrated using experimental trajectory data to capture cyclists’ and drivers’ perception–reaction and braking behaviour. These two components were combined to simulate scenarios with varying visibility conditions and perception-triggered braking responses in severe conflict situations. Results show that reduced visibility significantly reduces temporal safety margins, with over 50% of all simulated interactions yielding differential time-to-arrival (TTA₂) values below 2 s. Furthermore, obstructed conditions lead to higher- and more-dispersed relative crossing speeds (DV), typically increasing by 0.5–1.0 m/s compared to unobstructed conditions. Simulation data confirmed that clear visibility promotes anticipatory and adaptive user behaviour, whereas limited sightlines reduce braking availability and increase the likelihood and severity of conflicts, with distributions conditioned by the intersection’s geometry. The ability to generate detailed synthetic datasets of cyclist–vehicle interactions, often not obtainable through field observation, demonstrates the potential of the proposed framework for safety assessment. This approach supports the evaluation of mitigation strategies, including C-ITS-based solutions, and provides a basis for developing predictive AI models to enhance the safety of vulnerable road users. Full article

Road transport across Asia is undergoing rapid motorisation and exemplifies growing road safety challenges, with rising accident rates closely linked to driver behaviour. Recent reports indicate that Vietnamese drivers often perceive risk as manageable and enforcement as inconsistent, contributing to habitual violations such as speeding, signal ignoring, and risky manoeuvres, particularly when traffic is light. Evidence shows that riders, especially young adults, feel confident controlling their vehicles and frequently disregard safety warnings. This study investigates traffic safety awareness among motorcyclists and car drivers in Hanoi, based on a questionnaire survey of 393 respondents. Principal Component Analysis (PCA) was used to group 11 attitudinal statements into key components influencing road safety perceptions, identifying five: non-compliance with traffic regulations (Component 1), aggressive driving behaviour (Component 2), traffic signal issues (Component 3), road quality and infrastructure (Component 4), and preventive measures (Component 5). Multiple Correspondence Analysis (MCA) and two-step cluster analysis (TCA) were then applied to determine user clusters by socio-demographic characteristics, producing three groups: young adults in employment riding motorcycles (Cluster 1), young adults in education riding motorcycles (Cluster 2), and mature adults in employment driving cars (Cluster 3). Finally, Multinomial Logistic Regression (MLR) was applied to assess variations in road safety perceptions across the different groups (clusters). Mature adults driving cars (Cluster 3) identified the first four components as significant, with Components 1 and 2 showing negative associations and Components 3 and 4 positive associations. Full article

Background: With the widespread application of three-dimensional (3D) display technology, enhancing the realism of users’ experience in virtual 3D space has become important. A deep understanding of the mechanisms of human depth perception is therefore crucial. Objective: This study aims to investigate the influence of motion parallax, color, and object position cues on depth perception in 3D space. Method: Random-dot stereograms based on binocular disparity cues were constructed; three experiments were designed, varying the stimulus movement speed, color, and position; two-alternative forced-choice (2AFC) psychophysical paradigms were employed to collect participants’ responses regarding depth perception; and statistical analyses were conducted to examine the influences of these three cues on depth perception specified by binocular disparity. Results: A relatively small amount of motion parallax indicated a certain inhibitory effect on depth perception, whereas a larger amount might enhance the perceived depth. Introducing red, green, or blue color to the moving stimuli might also have a certain promoting effect. Furthermore, a significant difference in perceived depth was observed when the positions of the Test Stimulus and the Standard Stimulus differed within a trial, which might involve areas of higher-level brain function (such as visual attention). In conclusion, when multiple visual cues are present concurrently, they exhibit complex interactions that affect human depth perception. Full article

This study investigates how next-generation digital infrastructures—terahertz (THz) communication and AI-driven network orchestration—shape perceived service quality, luxury perception, and loyalty within the context of luxury hospitality. An empirical survey was conducted among 693 guests at Torre Melina Gran Meliá (Barcelona) between June 2024 and June 2025. Using a refined 38-item Likert-scale instrument, a three-factor structure was validated: (F1) Network Performance (speed, stability, coverage, seamless roaming, and multi-device reliability), (F2) Luxury Perception (modernity, innovation, and brand image), and (F3) Service Loyalty (satisfaction, return intentions, recommendations, and willingness to pay a premium). The results reveal that superior network performance functions both practically and symbolically. Functionally, it enables uninterrupted video calls, smooth streaming, low-latency gaming, and reliable multi-device usage—now considered essential utilities for contemporary travelers. Symbolically, high-performing and intelligently managed connectivity conveys technological leadership and exclusivity, thereby enhancing the hotel’s luxury image. Collectively, these effects create a “virtuous cycle” in which technical excellence reinforces perceptions of luxury, which in turn amplifies satisfaction and loyalty behaviors. From a managerial perspective, advanced connectivity should be viewed as a strategic investment and brand differentiator rather than a cost center. THz-ready, AI-orchestrated networks support personalization, dynamic bandwidth allocation (i.e., real-time adjustment of network capacity in response to fluctuating user demand), and monetizable premium service tiers, directly strengthening guest retention and brand equity. Ultimately, next-generation connectivity emerges not as an ancillary amenity but as a defining pillar of luxury hospitality in the emerging 6G era. Full article

The H.266/Versatile Video Coding (VVC) standard was developed to address the growing demand for compressing ultra-high-definition video content, supporting resolutions ranging from 4K to 8K and beyond. H.266/VVC improves coding efficiency by introducing a flexible quadtree with nested multi-type tree (QT-MTT) partitioning and various advanced coding tools. However, these improvements substantially increase the encoding complexity. To address this issue, we propose a perception-driven and object-aware algorithm that accelerates the MTT process in H.266/VVC intra coding. Our method integrates pixel-level saliency detection with object bounding box detection. Specifically, visually distinguishable (VD) pixels are identified using a just noticeable distortion (JND) model based on average background luminance, while detected-object regions are extracted using a YOLO object detection network. These two types of perceptual information are combined to guide adaptive encoding decisions. For each frame, a perception-driven pixel map labeled with VD pixels and a YOLO-based object map are generated. Within the MTT framework, partitioning decisions are determined jointly by standard deviation metrics derived from VD pixels and detected-object region coverage. By incorporating flexible threshold settings, the proposed method can meet different users’ requirements. In this paper, we performed experiments under three threshold settings. The experimental results demonstrate that the proposed method reduces H.266/VVC intra coding time by 27.94% to 43.11%, with BDBR increases of only 1.02% to 1.53%, thus achieving an appropriate trade-off between encoding speed and coding efficiency. Full article

Large-scale Low Earth Orbit (LEO) satellite constellations have become critical infrastructure for global communications, yet routing optimization remains challenging. Due to high-speed satellite mobility and limited local perception capabilities, traditional shortest-path algorithms struggle to adapt to dynamic topology changes and effectively handle random fluctuations in traffic loads and inter-satellite link states. Meanwhile, as constellation scales expand, centralized routing mechanisms face deployment difficulties due to high communication latency and computational complexity. To address these issues, this paper proposes a hierarchical load-balanced routing optimization algorithm based on geographic partitioning. The algorithm divides the constellation into multiple regions by latitude and longitude, establishing a hierarchical cooperative decision mechanism: the upper layer handles inter-region routing decisions while the lower layer manages intra-region routing optimization. Within regions, a load-aware K-shortest paths algorithm enables path diversification, achieving global coordination through cross-region information sharing and dynamic path selection, thereby reducing end-to-end routing latency while enhancing adaptability to dynamic environments and balancing routing performance with system scalability. In simulation scenarios with a Starlink-like architecture of 1512 satellites, experimental results demonstrate that compared to shortest-path routing, the algorithm reduces end-to-end latency by 14.1% and average satellite load by 15.9%. Under dynamic load scenarios with incrementally increasing user traffic, the algorithm maintains stable performance, validating its robustness under traffic fluctuations and link state variations. Full article

This study examines the effectiveness of a fine-tuned generative AI system—trained with a domain question bank—for question generation and automated grading in programming education, and evaluates its instructional usability. Methodologically, we constructed an annotated question bank covering nine item types and, under a controlled environment, compared pre- and post-fine-tuning performance on question-type recognition and answer grading using Accuracy, Macro Precision, Macro Recall, and Macro F1. We also collected student questionnaires and open-ended feedback to analyze subjective user experience. Results indicate that the accuracy of question-type recognition improved from 0.6477 to 0.8409, while grading accuracy increased from 0.9474 to 0.9605. Students’ subjective perceptions aligned with these quantitative trends, reporting higher ratings for grading accuracy and question generation quality; overall interactive experience was moderately high, though system speed still requires improvement. These findings provide course-aligned empirical evidence that fine-tuning with domain data can jointly enhance the effectiveness and usability of both automatic question generation and automated grading. Full article

This study explores the psychosocial factors that predispose young e-scooter users (18 to 24 years) to engage in illegal speeding by adopting a theory-driven approach across the Theory of Planned Behavior (TPB). The study, based on survey data of 474 participants, and analyzed with Structural Equation Modeling (SEM), found that emotional regulation and internal locus of control predict speeding intention and behavior and are significantly negative (β = +0.66 and β = −0.52, respectively). Satisfactory robustness was assured by model fit indices (0.93 CFI, 0.91 TLI, 0.045 RMSEA, and 0.071 SRMR). Findings indicate that the effect of emotional regulation is more on attitude and perception of behavioral control, but the connection between self-regulation and speeding intention is mediated by internal control. The inclusion of psychosocial variables in the TPB contributes to the behavioral theory of micro-mobility contexts and the behavioral study of sustainable-mobility research to emotional and cognitive aspects of risk behavior. The policy suggestions include incorporating short emotion-management courses into rider-training applications, collaborating with scooter-sharing institutions on incentive-based safety interventions, and developing interventions that promote responsibility, self-control, and emotional sensitivity among young people. These results reiterate the fact that psychological antecedents of risky riding require attention to achieve socially and environmentally sustainable urban mobility. Full article

Ensuring thermal comfort in waiting areas is essential for visitor satisfaction and well-being. In the context of nearly zero-energy buildings (nZEBs), these spaces—typically characterized by short-term occupancy, transient user behavior, and the need for rapid temperature adjustment—pose specific challenges for HVAC control in balancing comfort and energy demand. This study investigates the influence of a ceiling-mounted fan coil unit (FCU) operating in heating mode on thermal comfort conditions in an nZEB office waiting area. Measurements were conducted at multiple points within the space to assess microclimate parameters, followed by the calculation of the predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) indices, supported by occupant feedback collected through short interviews. The results showed that although the FCU effectively increased the average temperature, its intermittent operation and localized air jets during the heating phase caused temporary discomfort near the unit. Occupant feedback confirmed sensations of discomfort due to strong air movement during FCU operation but indicated slightly higher overall dissatisfaction and smaller variability compared to model-based PPD values, reflecting the averaging effect of occupant perception over time. These findings highlight the need for optimized FCU control strategies in waiting areas, such as operating at reduced fan speeds and preheating the heat exchanger, to enhance occupant comfort. This study contributes to improving HVAC control concepts for semi-transient spaces in nZEBs. Full article

Wearable auditory feedback systems have demonstrated potential to support gait rehabilitation, yet user experience and engagement remain underexplored. This feasibility study investigated the usability and perceptions of an IMU-based (WT901BLECL, WitMotion) sonification system designed to deliver real-time gait feedback. Twenty healthy participants walked on a treadmill at two speeds under three conditions: no feedback, discrete bass tones, and continuous whoosh tones. The proposed system, with an IMU sensor embedded in a flexible garment, combined real-time gait analysis with auditory cues. Participants reported high levels of comfort, with most (90%) indicating that they had a positive overall experience. Discrete bass tones enhanced awareness of specific gait phases, particularly heel strike and initial contact, whereas continuous whoosh sounds extended awareness to the trunk and hips but were occasionally perceived as distracting. Motivation effects were mixed, and no significant correlations were found between subjective ratings and biomechanical measures, reflecting individual variability in auditory cue interpretation. These results emphasized the role of sound modality in influencing gait perception and highlighted the importance of user-centered design in wearable rehabilitation technologies. The study provides foundational evidence for refining personalized auditory feedback systems and supports future investigations with clinical populations, such as stroke survivors and individuals with Parkinson’s Disease. Full article

Recent advances in multimodal large language models (MLLMs)—particularly vision– language models (VLMs)—introduce new possibilities for integrating visual perception with natural-language understanding in human–machine collaboration (HMC). Unmanned aerial vehicles (UAVs) are increasingly deployed in dynamic environments, where adaptive autonomy and intuitive interaction are essential. Traditional UAV autonomy has relied mainly on visual perception or preprogrammed planning, offering limited adaptability and explainability. This study introduces a novel reference architecture, the multimodal AI–HMC system, based on which a dedicated UAV use case architecture was instantiated and experimentally validated in a controlled laboratory environment. The architecture integrates VLM-powered reasoning, real-time depth estimation, and natural-language interfaces, enabling UAVs to perform context-aware actions while providing transparent explanations. Unlike prior approaches, the system generates navigation commands while also communicating the underlying rationale and associated confidence levels, thereby enhancing situational awareness and fostering user trust. The architecture was implemented in a real-time UAV navigation platform and evaluated through laboratory trials. Quantitative results showed a 70% task success rate in single-obstacle navigation and 50% in a cluttered scenario, with safe obstacle avoidance at flight speeds of up to 0.6 m/s. Users approved 90% of the generated instructions and rated explanations as significantly clearer and more informative when confidence visualization was included. These findings demonstrate the novelty and feasibility of embedding VLMs into UAV systems, advancing explainable, human-centric autonomy and establishing a foundation for future multimodal AI applications in HMC, including robotics. Full article

Electric bikes (e-bikes) offer a low-carbon, space-efficient solution for campus mobility, yet their sustainable potential is increasingly challenged by patterns of non-compliant use, including speeding, informal parking, and unauthorized charging. This study integrates the Theory of Planned Behavior (TPB) and the Technology Acceptance Model (TAM) to examine the cognitive and contextual factors that shape such behaviors among university students. Drawing on a survey of 408 e-bike users and structural equation modeling, the results show that non-compliance is primarily driven by perceived usefulness, ease of action, and behavioral feasibility, with affective and normative factors playing indirect, reinforcing roles. Importantly, actual behavior is influenced not only by intention but also by students’ perceived capacity to act within low-enforcement environments. These findings highlight the need to align behavioral perceptions with sustainability goals. The study contributes to sustainable mobility governance by clarifying key psychological pathways and offering targeted insights for designing perception-sensitive interventions in campus transport systems. Furthermore, by promoting compliance-oriented campus mobility, this research highlights a pathway toward enhancing the resilience of transport systems through behavioral adaptation within semi-regulated environments. Full article

Understanding automated vehicle (AV) behavior in complex road environments and user attitudes in such contexts is critical for their safe and effective integration into smart cities. Despite growing deployment, limited public data exist on AV performance in construction zones; highly dynamic settings marked by irregular lane markings, shifting detours, and unpredictable human presence. This study investigates AV behavior in these conditions through qualitative, video-based analysis of user-documented experiences on YouTube, focusing on Tesla’s supervised Full Self-Driving (FSD) and Waymo systems. Spoken narration, captions, and subtitles were examined to evaluate AV perception, decision-making, control, and interaction with humans. Findings reveal that while AVs excel in structured tasks such as obstacle detection, lane tracking, and cautious speed control, they face challenges in interpreting temporary infrastructure, responding to unpredictable human actions, and navigating low-visibility environments. These limitations not only impact performance but also influence user trust and acceptance. The study underscores the need for continued technological refinement, improved infrastructure design, and user-informed deployment strategies. By addressing current shortcomings, this research offers critical insights into AV readiness for real-world conditions and contributes to safer, more adaptive urban mobility systems. Full article

In the era of precision medicine, effective data visualisation plays a pivotal role in supporting clinical decision-making by translating complex, multidimensional datasets into intuitive and actionable insights. This paper explores the foundational principles of visual perception, with a specific focus on pre-attentive attributes such as colour, shape, size, orientation, and spatial position, which are processed automatically by the human visual system. Drawing from cognitive psychology and perceptual science, we demonstrate how these attributes can enhance the clarity and usability of medical visualisations, reducing cognitive load and improving interpretive speed in high-stakes clinical environments. Through detailed case studies and visual examples, particularly within the field of oncology, we highlight best practices and common pitfalls in the design of dashboards, nomograms, and interactive platforms. We further examine the integration of advanced tools—such as genomic heatmaps and temporal timelines—into multidisciplinary workflows to support personalised care. Our findings underscore that visually intelligent design is not merely an aesthetic concern but a critical factor in clinical safety, efficiency, and communication, advocating for user-centred and evidence-based approaches in the development of health data interfaces. Full article

Visual perception of screen elements depends on their color, font, and position in the user interface design. Objects in the central part of the screen are perceived more easily than those in the peripheral areas. However, the peripheral space is valuable for applications like advertising and promotion and should not be overlooked. Optimizing the design of elements in this area can improve user attention to peripheral visual stimuli during focused tasks. This study aims to evaluate how different combinations of text and background color affect the visibility of moving textual stimuli in the peripheral areas of the screen, while attention is focused on a central task. This study investigates how background color, combined with white or black text, affects the attention of participants. It also identifies which background color makes a specific word most noticeable in the peripheral part of the screen. We designed quizzes to present stimuli with black or white text on various background colors in the peripheral regions of the screen. The background colors tested were blue, red, yellow, green, white, and black. While saturation and brightness were kept constant, the color tone was varied. Among ten combinations of background and text color, we aimed to determine the most noticeable combination in the peripheral part of the screen. The combination of white text on a blue background resulted in the shortest detection time (1.376 s), while black text on a white background achieved the highest accuracy rate at 79%. The results offer valuable insights for improving peripheral text visibility in user interfaces across various visual communication domains such as video games, television content, and websites, where peripheral information must remain noticeable despite centrally focused user attention and complex viewing conditions. Full article