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Abstract Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. We provide a dataset on human decision-making during evacuations from virtual buildings, captured using experimental methods that controlled specific building layout parameters. An online experiment assigned participants a random subset of tasks featuring T-intersections. Data from 208 respondents, aged 17 to 71, were analyzed, considering education levels and excluding those with significant technical issues. Quantitative data on user interaction and evacuation route choices included decision time, mouse rotation, and the selected corridor, recorded through mouse clicks on invisible areas of interest. Respondents also self-reported their choice confidence on a Likert scale. Additionally, responses to final retrospective evaluation questionnaires were recorded. This dataset offers diverse research opportunities, particularly in emergency evacuation planning, where understanding evacuation choices in simulations can inform real-world strategies. It supports the development of models to predict human behavior in emergencies using machine learning and predictive modeling and is accessible for both academic and commercial use.

Abstract Understanding pedestrian movement remains crucial for designing efficient and safe transportation structures such as terminals, stations, or airports. The significance of conducting a granular analysis in pedestrian mobility dynamics research is evident in refining crowd behavior modeling. It is essential for gaining insights into potential terminal layouts, crowd management strategies, and evacuation procedures, all of which enhance safety and efficiency. In this context, we offer an original empirical dataset of 24,000,000 samples of trajectory spatial movement at traffic terminals in Havlíčkův Brod and Pardubice, Czech Republic. The dataset was collected using a high-resolution camera system installed at the railway station. Subsequently, algorithmic post-processing was applied to extract anonymous data on the spatial movement of recorded pedestrians. Thanks to this dataset, researchers can delve into the distances between pedestrians in a transportation terminal, considering factors such as group composition, group-to-group distances, and movement speed.

Abstract Early identification of cognitive or physical overload is critical in fields where human decision making matters when preventing threats to safety and property. Pilots, drivers, surgeons, and operators of nuclear plants are among those affected by this challenge, as acute stress can impair their cognition. In this context, the significance of paralinguistic automatic speech processing increases for early stress detection. The intensity, intonation, and cadence of an utterance are examples of paralinguistic traits that determine the meaning of a sentence and are often lost in the verbatim transcript. To address this issue, tools are being developed to recognize paralinguistic traits effectively. However, a data bottleneck still exists in the training of paralinguistic speech traits, and the lack of high-quality reference data for the training of artificial systems persists. Regarding this, we present an original empirical dataset collected using the BESST experimental protocol for capturing speech signals under induced stress. With this data, our aim is to promote the development of pre-emptive intervention systems based on stress estimation from speech.

Immersive Virtual Reality (iVR) presents a promising avenue for treating acrophobia through Virtual Reality Exposure Therapy (VRET). This paper explores the current state of VRET for acrophobia, identifying significant technological and practical barriers that limit its effectiveness and hinder widespread adoption. Key challenges include the need for more advanced and realistic user experiences, and for the integration of biofeedback mechanisms. Additionally, the role of therapists remains crucial, as therapist-led VRET sessions demonstrate better outcomes compared to automated interventions. The potential of Collaborative Immersive Virtual Environments (CIVEs) to enhance VRET by simulating real-life interactions and improving patient-therapist engagement is also discussed. Future research should focus on developing comprehensive guidelines for CIVE design and evaluating integrated VRET and CIVE systems for treating phobias, including acrophobia. Addressing these issues will enhance the therapeutic experience, making VRET a more effective and accessible tool for treating acrophobia.

IntroductionAltered subjective visual sensitivity manifests as feelings of discomfort or overload elicited by intense and irritative visual stimuli. This can result in a host of visual aberrations including visual distortions, elementary visual hallucinations and visceral responses like dizziness and nausea, collectively referred to as “pattern glare.” Current knowledge of the underlying neural mechanisms has focused on overall excitability of the visual cortex, but the individual contribution of excitatory and inhibitory systems has not yet been quantified.MethodsIn this study, we focus on the role of glutamate and γ-aminobutyric acid (GABA) as potential mediators of individual differences in subjective visual sensitivity, measured by a computerized Pattern Glare Test—a series of monochromatic square-wave gratings with three different spatial frequencies, while controlling for psychological variables related to sensory sensitivity with multiple questionnaires. Resting neurotransmitter concentrations in primary visual cortex (V1) and right anterior insula were studied in 160 healthy participants using magnetic resonance spectroscopy.ResultsData showed significant differences in the perception of visual distortions (VD) and comfort scores between men and women, with women generally reporting more VD, and therefore the modulatory effect of sex was considered in a further examination. A general linear model analysis showed a negative effect of occipital glutamate on a number of reported visual distortions, but also a significant role of several background psychological traits. When assessing comfort scores in women, an important intervening variable was the menstrual cycle.DiscussionOur findings do not support that baseline neurotransmitter levels have a significant role in overreactivity to aversive stimuli in neurotypical population. However, we demonstrated that biological sex can have a significant impact on subjective responses. Based on this additional finding, we suggest that future studies investigate aversive visual stimuli while examining the role of biological sex.

Abstract The building design is a crucial factor that can be actively adjusted and optimized to prevent human and property threats in emergency scenarios. Previous research suggests that specific building layouts may significantly influence human behaviour during evacuation. However, detailed empirical data about human behaviour in various types of buildings with different layouts are still missing and only marginal recommendations from this field are reflected in actual construction practice. In this study, desktop VR technologies were employed to study human decision-making in problematic T-intersections in the context of an emergency evacuation. More specifically, we studied fundamental attributes of buildings such as the width and length of the corridors and the presence of stairs to explore how they influence the choice of the evacuation route. The space-syntax isovist method was used to describe spatial parameters of corridors, which makes the results applicable to all buildings. Behavioural data from 208 respondents were analysed using multilevel regression models. Our results support previous claims concerning the importance of specific spatial layouts of evacuation corridors because respondents systematically chose wider and shorter corridors with visible staircases as the preferred evacuation route. The present findings further promote the ongoing discussion on the design of marked evacuation routes and building design that takes human factors into consideration.

Agent-based evacuation modeling represents an effective tool for making predictions about evacuation aspects of buildings such as evacuation times, congestions, and maximum safe building capacity. Collection of real behavioral data for calibrating agent-based evacuation models is time-consuming, costly, and completely impossible in the case of buildings in the design phase, where predictions about evacuation behavior are especially needed. In recent years evacuation experiments conducted in virtual reality (VR) have been frequently proposed in the literature as an effective tool for collecting data about human behavior. However, empirical studies which would assess validity of VR-based data for such purposes are still rare and considerably lacking in the agent-based evacuation modeling domain. This study explores opportunities that the VR behavioral data may bring for refining outputs of agent evacuation models. To this end, this study employed multiple input settings of agent-based evacuation models (ABEMs), including those based on the data gathered from the VR evacuation experiment that mapped out evacuation behaviors of individuals within the building. Calibration and evaluation of models was based on empirical data gathered from an original evacuation exercise conducted in a real building (N = 35) and its virtual twin (N = 38). This study found that the resulting predictions of single agent models using data collected in the VR environment after proposed corrections have the potential to better predict real-world evacuation behavior while offering desirable variance in the data outputs necessary for practical applications.

Cognitive styles are commonly studied constructs in cognitive psychology. The theory of field dependence-independence was one of the most important cognitive styles. Yet in the past, its measurement had significant shortcomings in validity and reliability. The theory of analytic and holistic cognitive styles attempted to extend this theory and overcome its shortcomings. Unfortunately, the psychometric properties of its measurement methods were not properly verified. Furthermore, new statistical approaches, such as analysis of reaction times, have been overlooked by current research. The aim of this pre-registered study was to verify the psychometric properties (i.e., factor structure, split-half reliability, test-retest reliability, discriminant validity with intelligence and personality, and divergent, concurrent and predictive validity) of several methods routinely applied in the field. We developed/adapted six methods based on self-report questionnaires, rod-and-frame principles, embedded figures, and hierarchical figures. The analysis was conducted on 392 Czech participants, with two data collection waves. The results indicate that the use of methods based on the rod-and-frame principle may be unreliable, demonstrating no absence of association with intelligence. The use of embedded and hierarchical figures is recommended. The self-report questionnaire used in this study showed an unsatisfactory factor structure and also cannot be recommended without futher validation on independent samples. The findings also did not correspond with the original two-dimensional theory.

Previous studies showed significant differences between expert architects and laypeople in aesthetic evaluations of buildings. However, studies exploring the aesthetic preferences of architecture students are lacking. The present study focused on a population of students and young architects to explore the aesthetic opinion shift within architectural careers. This study was intended to be a conceptual replication of the study of Brown and Gifford (2001) in a Central European context. A total of 109 participants (21–28 years old) evaluated 40 randomized pictures of houses to detect whether non-architecture undergraduates and fresh graduates of architecture would express different aesthetic preferences compared with their peers from the general population. The study also examined whether laypersons can predict the preferences of architects, and vice versa. Results show a trend that is contrary to the original research, that is, young architects and laypeople did not significantly differ in their aesthetic evaluations of the given stimuli. Analyses revealed high prediction ability in young architects and their non-architect peers. Moreover, the existing professional experience of young architects had no influence on the accuracy of their estimations. Findings suggest that the professional shift in architects’ expertise is obscured at an early career stage, as revealed in their aesthetic preferences. Keywords: Environmental aesthetics, Aesthetic preferences, Building aesthetics, Environmental apperception, Professional opinion shift

Three-dimensional geovisualizations are currently pushed both by technological development and by the demands of experts in various applied areas. In the presented empirical study, we compared the features of real 3D (stereoscopic) versus pseudo 3D (monoscopic) geovisualizations in static and interactive digital elevation models. We tested 39 high-school students in their ability to identify the correct terrain profile from digital elevation models. Students’ performance was recorded and further analysed with respect to their spatial abilities, which were measured by a psychological mental rotation test and think aloud protocol. The results of the study indicated that the influence of the type of 3D visualization (monoscopic/stereoscopic) on the performance of the users is not clear, the level of navigational interactivity has significant influence on the usability of a particular 3D visualization, and finally no influences of the spatial abilities on the performance of the user within the 3D environment were identified.

In the present theoretical paper, the current body of knowledge regarding the use of wearable virtual reality (VR) technologies for traffic psychological examination (TPE) is introduced, critically discussed and a specific application is suggested. The combination of wearable head-mounted displays for VR with an interactive and cost-effective haptic driving interface is emphasized as a valid and viable platform for a driving skills psychological assessment, which is in several aspects superior to standard TPE as well as driving simulators. For this purpose, existing psychological examination methods and psychological phenomena relevant in the process of driving are discussed together with VR technology’s properties and options. Special focus is dedicated to situation awareness as a crucial, but currently hardly measurable construct, where VR in combination with embedded eye-tracking (ET) technology represents a promising solution. Furthermore, the suitability and possibilities of these VR tools for valid traffic psychological examination are analyzed and discussed. Additionally, potentially desirable measures for driving assessment based on recent advances of VR are outlined and practical applications are suggested. The aim of this article is to bring together recent advances in TPE, VR and ET; revise previous relevant studies in the field; and to propose concept of the cost effective, mobile and expandable HMD-based driving simulator, which can be suitable for an ecologically valid driving assessment and follow-up TPE in common practice.

The use of 3D visualization technologies has increased rapidly in many applied fields, including geovisualization, and has been researched from many different perspectives. However, the findings for the benefits of 3D visualization, especially in stereoscopic 3D forms, remain inconclusive and disputed. Stereoscopic "real" 3D visualization was proposed as encouraging the visual perception of shapes and volume of displayed content yet criticised as problematic and limited in a number of ways, particularly in visual discomfort and increased response time in tasks. In order to assess the potential of real 3D visualization for geo-applications, 91 participants were engaged in this study to work with digital terrain models in different 3D settings. The researchers examined the effectivity of stereoscopic real 3D visualization compared to monoscopic 3D (or pseudo 3D) visualization under static and interactive conditions and applied three tasks with experimental stimuli representing different geo-related phenomena, i.e. objects in the terrain, flat areas marked in the terrain and terrain elevation profiles. The authors explored the significant effects of real 3D visualization and interactivity factors in terms of response time and correctness. Researchers observed that the option to interact (t = -10.849, p < 0.001) with a virtual terrain and its depiction with real 3D visualization (t = 4.64, p < 0.001) extended the participants' response times. Counterintuitively, the data demonstrated that the static condition increased response correctness (z = 5.38, p < 0.001). Regarding detailed analysis of data, an interactivity factor was proposed as a potential substitute for real 3D visualization in 3D geographical tasks.

From the user perspective, 3D geospatial data visualizations are one of the bridges between the physical and the digital world. As such, the potential of 3D geospatial data visualizations is frequently discussed within and beyond the digital twins. The effects on human cognitive processes in complex spatial tasks is rather poorly known. No uniform standards exist for the 3D technologies used in these tasks. Although stereoscopic geovisualizations presented using 3D technologies enhance depth perception, it has been suggested that the visual discomfort experienced when using 3D technology outweighs its benefits and results in lower efficiency and errors. In the present study, sixty participants using 3D technologies were tested in terms of their ability to make informed decisions in selecting the correct position of a virtual transmitter in a digital twin and a digital terrain model, respectively. Participants (n = 60) were randomly assigned into two groups, one using 3D technology engaging stereoscopic shutter glasses and the second working with standard computer screen-based visualizations. The results indicated that the participants who used shutter glasses performed significantly worse in terms of response time (W = 175.0; p < 0.001, r = −0.524). This finding verifies previous conclusions concerning the unsuitability of stereoscopic visualization technology for complex decision-making in geospatial tasks.

Human performance and navigation activity in virtual environments can be measured and assessed with the aim to draw specific conclusions about human cognition. This paper presents an original virtual geographic environment (VGE) designed and used for this purpose. The presented research is rooted in an interdisciplinary approach combining knowledge and principles from the fields of psychology, cartography, and information technologies. The VGE was embedded with user logging functionality to provide a basis from which conclusions about human cognitive processes in a VGE could be drawn. The scope of this solution is introduced, described, and discussed under a behavioral measurement framework. An exploratory research design was adopted to demonstrate the environment’s utility in proof-of-concept user testing. Twenty participants were observed in interactive, semi-interactive and non-interactive tasks, their performance and individual differences were analyzed. The behavioral measurements were supplemented by Object-Spatial Imagery and a Verbal Questionnaire to determine the participants’ cognitive styles. In this sample, significant differences in exploration strategies between men and women were detected. Differences between experienced and non-experienced users were also found in their ability to identify spatial relations in virtual scenes. Finally, areas for future research areas and development were pinpointed.

Immersive virtual reality (iVR) devices are rapidly becoming an important part of our lives and forming a new way for people to interact with computers and each other. The impact and consequences of this innovative technology have not yet been satisfactory explored. This empirical study investigated the cognitive and social aspects of collaboration in a shared, immersive virtual reality. A unique application for implementing a collaborative immersive virtual environment (CIVE) was developed by our interdisciplinary team as a software solution for educational purposes, with two scenarios for learning about hypsography, i.e., explanations of contour line principles. Both scenarios allow switching between a usual 2D contour map and a 3D model of the corresponding terrain to increase the intelligibility and clarity of the educational content. Gamification principles were also applied to both scenarios to augment user engagement during the completion of tasks. A qualitative research approach was adopted to obtain a deep insight into the lived experience of users in a CIVE. It was thus possible to form a deep understanding of very new subject matter. Twelve pairs of participants were observed during their CIVE experience and then interviewed either in a semistructured interview or a focus group. Data from these three research techniques were analyzed using interpretative phenomenological analysis, which is research method for studying individual experience. Four superordinate themes—with detailed descriptions of experiences shared by numerous participants—emerged as results from the analysis; we called these (1) Appreciation for having a collaborator, (2) The Surprising “Fun with Maps”, (3) Communication as a challenge, and (4) Cognition in two realities. The findings of the study indicate the importance of the social dimension during education in a virtual environment and the effectiveness of dynamic and interactive 3D visualization.

Interactive 3D visualizations of geospatial data are currently available and popular through various applications such as Google EarthTM and others. Several studies have focused on user performance with 3D maps, but static 3D maps were mostly used as stimuli. The main objective of this paper was to identify differences between interactive and static 3D maps. We also explored the role of different tasks and inter-individual differences of map users. In the experimental study, we analyzed effectiveness, efficiency, and subjective preferences, when working with static and interactive 3D maps. The study included 76 participants and used a within-subjects design. Experimental testing was performed using our own testing tool 3DmoveR 2.0, which was based on a user logging method and open web technologies. We demonstrated statistically significant differences between interactive and static 3D maps in effectiveness, efficiency, and subjective preferences. Interactivity influenced the results mainly in ‘spatial understanding’ and ‘combined’ tasks. From the identified differences, we concluded that the results of the user studies with static 3D maps as stimuli could not be transferred to interactive 3D visualizations or virtual reality.

This article delves into the dynamics of human interaction with artificial intelligence (AI), emphasizing the optimization of these interactions to enhance human productivity. Employing a Grounded Theory Literature Review (GTLR) methodology, the study systematically identifies and analyzes themes from literature published between 2018 and 2023. Data were collected primarily from the Scopus database, with the Web of Science used to corroborate findings and include additional sources identified through a snowball effect. At the heart of this exploration is the pivotal role of socio-emotional attributes such as trust, empathy, rapport, user engagement, and anthropomorphization—elements crucial for the successful integration of AI into human activities. By conducting a comprehensive review of existing literature and incorporating case studies, this study illuminates how AI systems can be designed and employed to foster deeper trust and empathetic understanding between humans and machines. The analysis reveals that when AI systems are attuned to human emotional and cognitive needs, there is a marked improvement in collaborative efficiency and productivity. Furthermore, the paper discusses the ethical implications and potential societal impacts of fostering such human-AI relationships. It argues for a paradigm shift in AI development—from focusing predominantly on technical proficiency to embracing a more holistic approach that values the socio-emotional aspects of human-AI interaction. This shift could pave the way for more meaningful and productive collaborations between humans and AI, ultimately leading to advancements that are both technologically innovative and human-centric.