تأثیر سرعت و مقیاس بر رفتارهای حرکتی در محیط‌‌های مجازی

دوره 23، شماره 155
اردیبهشت 1405
صفحه 43-56

نوع مقاله : مقالۀ پژوهشی

نویسندگان

گروه مهندسی معماری، دانشکده مهندسی عمران و معماری، دانشگاه ملایر، ایران

چکیده
بیان مسئله: موفقیت در طراحی محیط‌های مجازی نیازمند به حداکثر رساندن کیفیت تجربۀ انسانی کاربران در محیط مجازی است. این محیط‌ها همچنین امکان تنظیم خصوصیات بنیادی محیط ازجمله سرعت آواتار و مقیاس فضا را فراهم می‌کنند؛ لذا توجه و درک اثر تغییر این متغیرهای بنیادین بر رفتار کاربر محیط و به‌خصوص رفتارهای حرکتی ضروری به نظر می‌رسد. 
هدف پژوهش: در این راستا، هدف این پژوهش بررسی اثر سرعت آواتار، مقیاس ساختار محیط و همچنین چگالی اطلاعات محیطی بر راهبردهای حرکتی کاربران است. امید است این مطالعه نتایج مفیدی برای کاربردهای مختلف، از طراحی بازی گرفته تا محیط‌های مجازی توان‌بخشی داشته باشد.
روش پژوهش: پارادایم این پژوهش پسااثبات‌‌گرا است و به‌لحاظ هدف جزو پژوهش‌های کاربردی است. داده‌های پژوهش ازطریق مشاهدۀ رفتار کاربران - شامل 18 شرکت‌کننده با تجربۀ بازی‌های کامپیوتری - در حین جستجو در محیط مجازی و استخراج رفتارهای آن‌ها توسط نه کاربر دیگر به دست آمد. اعتبارسنجی یافته‌‌های این بخش ازطریق آزمون دلفی انجام شد. داده‌‌های جمع‌‌آوری‌شده با استفاده از آزمون‌های رگرسیون برای هر متغیر وابسته به‌صورت مجزا تجزیه‌وتحلیل شد.
نتیجه‌گیری: نتایج نشان می‌دهد که سرعت، مقیاس و چگالی اطلاعات محیطی بر رفتارهای حرکتی اتخاذشده توسط کاربران محیط مجازی تأثیر دارند. سرعت و چگالی اطلاعات محیطی به‌خصوص بر رفتارهای مبتنی‌بر استراتژی حرکتی مانند طول پیمودهشده در مسیرهای مستقیم اثر دارند و مقیاس بیشتر بر رفتارهای مرتبط با ساختار فضایی مانند فاصلۀ ترجیحی از دیوار و لبه‌ها متأثر است. کارایی فرد در جستجو نیز متأثر از چگالی اطلاعات محیطی است.

کلیدواژه‌ها

موضوعات

عنوان مقاله English

The Effect of Speed and Scale on Movement Behaviors in Virtual Environments

نویسندگان English

Arash Hosseini Alamdari
Zahra Torkaman
Seyedeh Faezeh Etemad Sheykhaleslami
Department of Architecture, Faculty of Civil Engineering and Architecture, Malayer University, Iran
چکیده English

Problem statement: Success in designing virtual environments requires maximizing the quality of users’ experience within these digital spaces. Such environments also allow for the adjustment of fundamental environmental properties, including avatar speed and spatial scale. Therefore, understanding the effects of altering these basic variables on user behavior, particularly movement behaviors, is essential. 
Research objective: In this regard, the present research investigates the effect of avatar speed, environmental structure scale, and environmental information density on users’ movement strategies. It is hoped that this study will provide useful results for various applications, from game design to assistive virtual environments.
Research method: The paradigm of this research is post-positivist, and in terms of objective, it falls under applied research. The research data were obtained by observing the behavior of users -including 18 participants experienced in computer games - during search activities in a virtual environment, and then extracting their behavioral patterns by 9 other users. The findings from this part were validated through a Delphi method. The collected data were analyzed using regression tests for each dependent variable separately.
Conclusion: The results indicate that speed, scale, and environmental information density influence the movement behaviors adopted by users in the virtual environment. Speed and environmental information density particularly affect motion-strategy-based behaviors, such as the distance traveled in straight paths, whereas scale primarily influences behaviors related to spatial structure, such as the preferred distance from walls and edges. An individual’s search efficiency is also affected by environmental information density.

کلیدواژه‌ها English

  • Avatar movement speed
  • Spatial structure scale
  • Environmental information density
  • Movement behaviors
  • Virtual environment
Benhamou, S., & Collet, J. (2015). Ultimate failure of the Lévy foraging hypothesis: Two-scale searching strategies outperform scale-free ones even when prey are scarce and cryptic. Journal of Theoretical Biology, 387, 221–227. https://doi.org/10.1016/j.jtbi.2015.09.034 
Bozgeyikli, E., Raij, A., Katkoori, S., & Dubey, R. (2016). Locomotion in virtual reality for individuals with autism spectrum disorder. Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility (pp. 247–248). https://doi.org/10.1145/2983310.2985763 
Caminiti, R., Ferraina, S., & Johnson, P. B. (1996). The sources of visual information to the primate frontal lobe: A novel role for the superior parietal lobule. Cerebral Cortex, 6 (3), 319–328. https://doi.org/10.1093/cercor/6.3.319 
Carbone, F., Bondi, E., Massalha, Y., Anastasi, A., Ferro, A., Pizzolante, M., ... & Maggioni, E. (2024). Exploring brain activity during awe-inducing virtual reality experiences: A multi-metric EEG frequency analysis. In 2024 46th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 1–4). IEEE. https://doi.org/10.1109/EMBC53108.2024.10782046
Carlson, C., Aytur, S., Gardner, K., & Rogers, S. (2012). Complexity in built environment, health, and destination walking: A neighborhood-scale analysis. Journal of Urban Health, 89 (2), 270–284. https://doi.org/10.1007/s11524-011-9652-8 
Chirico, A., Ferrise, F., Cordella, L., & Gaggioli, A. (2018). Designing awe in virtual reality: An experimental study. Frontiers in Psychology, 8, 2351. https://doi.org/10.3389/fpsyg.2017.02351
Christman, Z. J., Wilson-Genderson, M., Heid, A., & Pruchno, R. (2020). The effects of neighborhood built environment on walking for leisure and for purpose among older people. The Gerontologist, 60 (4), 651–660. https://doi.org/10.1093/geront/gnz093 
Daneshjo, K., Hoseini Alamdari, A., & Yeganeh, M. (2022). Upgrading isovist models by introducing a new set of variables based on the position of the open edges. Haft Hesar J Environ Stud, 11 (41), 5-16. http://dx.doi.org/10.52547/hafthesar.11.41.3 
Dijkstra, J., de Vries, B., & Jessurun, J. (2014). Wayfinding search strategies and matching familiarity in the built environment through virtual navigation. Transportation Research Procedia, 2, 141–148. https://doi.org/10.1016/j.trpro.2014.09.018
Epstein, R. A., Patai, E. Z., Julian, J. B., & Spiers, H. J. (2017). The cognitive map in humans: Spatial navigation and beyond. Nature Neuroscience, 20 (11), 1504–1513. https://doi.org/10.1038/nn.4656
Francová, A., Jablonská, M., & Fajnerová, I. (2023). Design and evaluation of virtual reality environments for claustrophobia. PRESENCE: Virtual and Augmented Reality, 32, 23–34. https://doi.org/10.1162/pres_a_00385
Gibson, J. J. (1979). The ecological approach to visual perception. Houghton Mifflin.
Gifford, R. (2013). Environmental psychology: Principles and practice (5th ed.). Optimal Books.
Hafting, T., Fyhn, M., Molden, S., Moser, M.-B., & Moser, E. I. (2005). Microstructure of a spatial map in the entorhinal cortex. Nature, 436, 801–806. https://doi.org/10.1038/nature03721
Hepperle, D., & Wölfel, M. (2023). Similarities and differences between immersive virtual reality, real world, and computer screens: a systematic scoping review in human behavior studies. Multimodal Technologies and Interaction, 7(6), 56. https://doi.org/10.3390/mti7060056
Hills, T. T., Kalff, C., & Wiener, J. M. (2013). Adaptive Lévy processes and area-restricted search in human foraging. PLOS ONE, 8 (4), e60488. https://doi.org/10.1371/journal.pone.0060488
Humphries, N. E., Weimerskirch, H., Queiroz, N., Southall, E. J., & Sims, D. W. (2014). Optimal foraging strategies: Lévy walks balance searching and patch exploitation under a very broad range of conditions. Journal of Theoretical Biology, 358, 179–193. https://doi.org/10.1016/j.jtbi.2014.05.032
Iftikhar, H., Shah, P., & Luximon, Y. (2021). Human wayfinding behaviour and metrics in complex environments: a systematic literature review. Architectural Science Review, 64(5), 452–463. https://doi.org/10.1080/00038628.2020.1777386 
Jansen, S. E. M., Toet, A., & Werkhoven, P. J. (2011). Human locomotion through a multiple obstacle environment: strategy changes as a result of visual field limitation. Experimental Brain Research, 212(3), 449–456. https://doi.org/10.1007/s00221-011-2757-1
Kerster, B. E., Rhodes, T., & Kello, C. T. (2016). Spatial memory in foraging games. Cognition, 148, 85–96. https://doi.org/10.1016/j.cognition.2015.12.015
Langbehn, E., Lubos, P., Bruder, G., & Steinicke, F. (2017, March). Application of redirected walking in room-scale VR. In 2017 IEEE Virtual Reality (VR) (pp. 449–450). IEEE. https://doi.org/10.1109/VR.2017.7892373
LeDoux, J. E. (2012). Rethinking the emotional brain. Neuron, 73 (4), 653–676. https://doi.org/10.1016/j.neuron.2012.02.004
Lhuillier, S., Dutriaux, L., Nicolas, S., & Gyselinck, V. (2024). Manipulating objects during learning shrinks the global scale of spatial representations in memory: a virtual reality study. Scientific Reports, 14(1), 2656. https://doi: 10.1038/s41598-024-53239-1
Maguire, E. A., Burgess, N., & O›Keefe, J. (1999). Human spatial navigation: Cognitive maps, sexual dimorphism, and neural substrates. Current Opinion in Neurobiology, 9(2), 171–177. https://doi.org/10.1016/S0959-4388(99)80023-3 
Moser, E. I., Kropff, E., & Moser, M.-B. (2008). Place cells, grid cells, and the brain›s spatial representation system. Annual Review of Neuroscience, 31, 69–89. https://doi.org/10.1146/annurev.neuro.31.061307.090723 
Moura, B., & Menezes, J. (2021). Behavioural movement strategies in cyclic models. Scientific Reports, 11, 6413. https://doi.org/10.1038/s41598-021-85590-y
Netto, V.M., Peres, O.M., Cacholas, C. (2025). Entropy and the city: Origins, trajectories and explorations of the concept in urban science. In Rybski, D. (Ed.), Compendium of Urban Complexity. Understanding Complex Systems. Springer. https://doi.org/10.1007/978-3-031-82666-5_12
New, J., Krasnow, M. M., Truxaw, D., & Gaulin, S. J. C. (2007). Spatial adaptations for plant foraging: Women excel and calories count. Proceedings of the Royal Society B: Biological Sciences, 274 (1626), 2679–2684. https://doi.org/10.1098/rspb.2007.0826 ]
Nolé, M. L., Montañana, A., Barranco-Merino, R., Higuera-Trujillo, J. L., & Llinares, C. (2024). Cognitive bias in perceptions of industrialized housing. Buildings, 14 (9), 2665. https://doi.org/10.3390/buildings14092665
Passini, R. (1980). Wayfinding in complex buildings: An environmental analysis. Man-Environment Systems, 10(1), 31–40. https://doi.org/10.1177/0013916514550243
Piryankova, I. V., Wong, H. Y., Linkenauger, S. A., Stinson, C., Longo, M. R., Bülthoff, H. H., & Mohler, B. J. (2014). Owning an overweight or underweight body: distinguishing the physical, experienced and virtual body. PLOS ONE, 9(8), e103428. https://doi.org/ 10.1371/journal.pone.0103428
Raichlen, D. A., Wood, B. M., Gordon, A. D., Mabulla, A. Z. P., Marlowe, F. W., & Pontzer, H. (2014). Evidence of Lévy walk foraging patterns in human hunter-gatherers. Proceedings of the National Academy of Sciences, 111 (2), 728–733. https://doi.org/10.1073/pnas.1318616111
Rondinel-Oviedo, D. R., & Keena, N. (2023). Entropy and cities: A bibliographic analysis towards more circular and sustainable urban environments. Entropy, 25 (3), 532. https://doi.org/10.3390/e25030532
Ruddle, R. A., & Lessels, S. (2009). The benefits of using a walking interface to navigate virtual environments. ACM Transactions on Computer-Human Interaction, 16 (1), 1–18. https://doi.org/10.1145/1502800.1502805
Saelens, B. E., & Handy, S. L. (2008). Built environment correlates of walking: A review. Medicine & Science in Sports & Exercise, 40 (7), S550–S566. https://doi.org/10.1249/MSS.0b013e31817c67a4
Singh, A., Joshi, K., Shuaib, M., Bharany, S., Alam, S., & Ahmad, S. (2022). Navigation and speed regulation aimed at travel through immersive virtual environments: A review. In 2022 IEEE International Conference on Current Development in Engineering and Technology (CCET) (pp. 1–6). IEEE. https://doi.org/10.1109/CCET56606.2022.10080751
Slater, M., Spanlang, B., & Corominas, D. (2010). Simulating virtual environments within virtual environments as the basis for a psychophysics of presence. ACM Transactions on Graphics, 29 (4), 1–9. https://doi.org/10.1145/1778765.1778829 
Stults-Kolehmainen, M. A. (2023). Humans have a basic physical and psychological need to move the body: Physical activity as a primary drive. Frontiers in Psychology, 14, 1134049. https://doi.org/10.3389/fpsyg.2023.1134049 
van der Zee, T. J., Mundinger, E. M., & Kuo, A. D. (2022). A biomechanics dataset of healthy human walking at various speeds, step lengths and step widths. Scientific Data, 9(1), 704. https://doi.org/ 10.1038/s41597-022-01817-1
van Nes, A., & Yamu, C. (2021). Theoretical representations of the built environment. In A. van Nes & C. Yamu (Eds.), Introduction to space syntax in urban studies (pp. 171–212). Springer. https://doi.org/10.1007/978-3-030-59140-3_6
Viswanathan, G. M., Buldyrev, S. V., Havlin, S., da Luz, M. G. E., Raposo, E. P., & Stanley, H. E. (1999). Optimizing the success of random searches. Nature, 401, 911–914. https://doi.org/10.1038/44831 
Weinstein, B. G., Irvine, L., & Friedlaender, A. S. (2018). Capturing foraging and resting behavior using nested multivariate Markov models in an air-breathing marine vertebrate. Movement Ecology, 6 (1), 16. https://doi.org/10.1186/s40462-018-0134-4
Xie, X., Paris, R. A., McNamara, T. P., & Bodenheimer, B. (2018). The effect of locomotion modes on spatial memory and learning in large immersive virtual environments: A comparison of walking with gain to continuous motion control. In Creem-Regehr, S., Schöning, J., Klippel, A. (Eds.), Spatial Cognition XI (Vol. 11034, pp. 58–73). Springer. https://doi.org/10.1007/978-3-319-96385-3_5 
Zhang, Z., Sun, T., Fisher, T., & Wang, H. (2024). The relationships between the campus built environment and walking activity. Scientific Reports, 14, 20330. https://doi.org/10.1038/s41598-024-60820-1
Zhou, Y., & Yu, Y. (2021). Human visual search follows a suboptimal Bayesian strategy revealed by a spatiotemporal computational model and experiment. Communications Biology, 4, 34. https://doi.org/10.1038/s42003-020-01485-0