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Universal Design of Signage Through Virtual Human Simulation

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Cultural Space on Metaverse

Part of the book series: KAIST Research Series ((KAISTRS))

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Abstract

Intuition behind sign placement and wayfinding features of architectural design can rarely encompass the needs of a wide range of building users. To help in automating sign placement, recent research has combined the use of agent-based simulation with optimization algorithms for maximizing visibility and wayfinding throughout a building model. As with many instances of machine learning applications, these too have unfortunately been dominated by an assumed young, healthy, and perfectly sighted virtual human. In this paper, we present an analysis of virtual human agents exploring a digital space using a combined vision and modified A* algorithm across multiple postures and visual impairments common amongst building occupants. We show how the inclusion of head angle and limited sights can change the results of what may be considered an optimal sign location.

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References

  1. Schwartz M (2021) Human centric accessibility graph for environment analysis. Autom Constr 127:103557

    Article  Google Scholar 

  2. Dubey RK, Khoo WP, Morad MG, Hölscher C, Kapadia M (2020) Autosign: a multi-criteria optimization approach to computer aided design of signage layouts in complex buildings. Comput Graph 88:13–23

    Article  Google Scholar 

  3. Johnson C, Haworth B (2022) Cognitive model of agent exploration with vision and signage understanding. Comput Graph Forum 41(8) (Special Issue on ACM SIGGRAPH/Eurographics Symposium on Computer Animation)

    Google Scholar 

  4. Connell BR (1997) The principles of universal design, version 2.0. http://www.design.ncsu.edu/cud/univ_design/princ_overview.htm

  5. Story MF (2001) Principles of universal design. Universal Design Handbook

    Google Scholar 

  6. Lee JK, Eastman CM, Lee J, Kannala M, Jeong YS (2010) Computing walking distances within buildings using the universal circulation network. Environ Plann B: Plann Des 37(4):628–645

    Google Scholar 

  7. Shin J, Lee JK (2019) Indoor walkability index: BIM-enabled approach to quantifying building circulation. Autom Constr 106:102845

    Article  Google Scholar 

  8. Suter G (2013) Structure and spatial consistency of network-based space layouts for building and product design. Comput Aided Des 45(8–9):1108–1127

    Article  Google Scholar 

  9. Fuchkina E (2017) Pedestrian movement graph analysis. Arbeitspapiere Informatik Architektur. https://doi.org/10.25643/bauhaus-universitaet.2738

    Article  Google Scholar 

  10. Péroche M, Léone F, Gutton R (2014) An accessibility graph-based model to optimize tsunami evacuation sites and routes in Martinique, France. Adv Geosci

    Google Scholar 

  11. Lamarche F (2009) Topoplan: a topological path planner for real time human navigation under floor and ceiling constraints. Comput Graph Forum 28:649–658

    Google Scholar 

  12. Pettre J, Laumond JP, Thalmann D (2005) A navigation graph for real-time crowd animation on multilayered and uneven terrain. In: First international workshop on crowd simulation, vol. 43. Pergamon Press, New York, p 194

    Google Scholar 

  13. Nagy D, Villaggi L, Stoddart J, Benjamin D (2017) The buzz metric: a graph-based method for quantifying productive congestion in generative space planning for architecture. Technol|Architect + Desi 1(2):186–195

    Google Scholar 

  14. Schwartz M, Das S (2019) Interpretting non-flat surfaces for walkability analysis. In: Proceedings of the symposium on simulation for architecture and urban design, SIMAUD ’19. Society for Computer Simulation International, San Diego, CA, USA, pp 19:1–19:8

    Google Scholar 

  15. Kallmann M, Kapadia M (2014) Navigation meshes and real-time dynamic planning for virtual worlds. In: ACM SIGGRAPH 2014 courses. ACM, p 3 (2014)

    Google Scholar 

  16. Benedikt ML (1979) To take hold of space: isovists and isovist fields. Environ Plann B Plann Des 6(1):47–65

    Article  Google Scholar 

  17. Lozano-Pérez T, Wesley MA (1979) An algorithm for planning collision-free paths among poly-hedral obstacles. Commun ACM 22(10):560–570

    Article  Google Scholar 

  18. Turner A, Doxa M, O’sullivan D, Penn A (2001) From isovists to visibility graphs: a methodology for the analysis of architectural space. Environ Plann B Plann Des 28(1):103–121

    Article  Google Scholar 

  19. Conroy RA (2001) Spatial navigation in immersive virtual environments. Ph.D. thesis, Citeseer

    Google Scholar 

  20. Fisher-Gewirtzman D (2018) Integrating ‘weighted views’ to quantitative 3d visibility analysis as a predictive tool for perception of space. Environ Plann B: Urban Analytics City Sci 45(2):345–366

    Google Scholar 

  21. Koltsova A, Tunçer B, Schmitt G (2013) Visibility analysis for 3d urban environments

    Google Scholar 

  22. Lu Y, Gou Z, Ye Y, Sheng Q (2019) Three-dimensional visibility graph analysis and its application. Environ Plann B: Urban Anal City Sci 46(5):948–962

    Google Scholar 

  23. Nutsford D, Reitsma F, Pearson AL, Kingham S (2015) Personalising the viewshed: visibility analysis from the human perspective. Appl Geogr 62:1–7

    Article  Google Scholar 

  24. Varoudis T, Psarra S (2014) Beyond two dimensions: architecture through three dimensional visibility graph analysis. J Space Syntax 5(1):91–108

    Google Scholar 

  25. Varoudis T, Penn A (2015) Visibility, accessibility and beyond: next generation visibility graph analysis. In: SSS 2015–10th international space syntax symposium

    Google Scholar 

  26. Schwartz M, Vinnikov M, Federici J (2021) Adding visibility to visibility graphs: weighting visibility analysis with attenuation coefficients. In: Proceedings of the 12th annual symposium on simulation for architecture and urban design, SimAUD ’21. Society for Computer Simulation International, San Diego, CA, USA

    Google Scholar 

  27. Bruce ND, Tsotsos JK (2009) Saliency, attention, and visual search: an information theoretic approach. J Vis 9(3):5–5

    Article  Google Scholar 

  28. Treue S (2003) Visual attention: the where, what, how and why of saliency. Curr Opin Neurobiol 13(4):428–432

    Article  Google Scholar 

  29. Kapadia M, Pelechano N, Allbeck J, Badler N (2015) Virtual crowds: steps toward behavioral realism. In: Synthesis lectures on visual computing: computer graphics, animation, computational photography, and imaging, vol 7, no 4. pp 1–270

    Google Scholar 

  30. Thalmann D, Musse SR (2013) Crowd simulation, 2nd edn. Springer

    Google Scholar 

  31. van Toll W, Pettré J (2021) Algorithms for microscopic crowd simulation: advancements in the 2010s. Comput Graph Forum 40:731–754

    Google Scholar 

  32. Helbing D, Farkas I, Vicsek T (2000) Simulating dynamical features of escape panic. Nature 407(6803):487–490

    Article  Google Scholar 

  33. Helbing D, Molnar P (1995) Social force model for pedestrian dynamics. Phys Rev E 51(5):4282

    Article  Google Scholar 

  34. Karamouzas I, Heil P, van Beek P, Overmars MH (2009) A predictive collision avoidance model for pedestrian simulation. In: MiG. Springer, pp 41–52 (2009)

    Google Scholar 

  35. van den Berg J, Guy SJ, Lin M, Manocha D (2011) Reciprocal n-body collision avoidance. Robot Res 70:3–19

    Google Scholar 

  36. Van den Berg J, Lin M, Manocha D (2008) Reciprocal velocity obstacles for real-time multi-agent navigation. In: IEEE international conference on robotics and automation. IEEE, pp 1928–1935

    Google Scholar 

  37. Fiorini P, Shiller Z (1993) Motion planning in dynamic environments using the relative velocity paradigm. In: Proceedings of the IEEE international conference on robotics and automation. IEEE, pp 560–565

    Google Scholar 

  38. Fiorini P, Shiller Z (1998) Motion planning in dynamic environments using velocity obstacles. Int J Robot Res 17(7):760–772

    Article  Google Scholar 

  39. Ondřej J, Pettré J, Olivier AH, Donikian S (2010) A synthetic-vision based steering approach for crowd simulation, vol 29. ACM TOG, ACM, p 123

    Google Scholar 

  40. Berseth G, Kapadia M, Faloutsos P (2015) Robust space-time footsteps for agent-based steering. Comput Animation Virtual Worlds

    Google Scholar 

  41. Singh S, Kapadia M, Reinman G, Faloutsos P (2011) Footstep navigation for dynamic crowds. Comput Animation Virtual Worlds 22(2–3):151–158

    Article  Google Scholar 

  42. Wolinski D, Lin MC, Pettré J (2016) Warpdriver: context-aware probabilistic motion prediction for crowd simulation. ACM Trans Graph (TOG) 35(6):164

    Article  Google Scholar 

  43. Singh S, Kapadia M, Hewlett B, Reinman G, Faloutsos P (2011) A modular framework for adaptive agent-based steering. In: Proceedings of I3D. ACM, pp 141–150. https://doi.org/10.1145/1944745.1944769

  44. Kremer M, Caruana P, Haworth B, Kapadia M, Faloutsos P (2021) Psm: parametric saliency maps for autonomous pedestrians. In: Motion, interaction and games, MIG’21. Association for Computing Machinery, New York, NY, USA

    Google Scholar 

  45. Kremer M, Caruana P, Haworth B, Kapadia M, Faloutsos P (2022) Automatic estimation of parametric saliency maps (PSMs) for autonomous pedestrians. Comput Graph 104:86–94

    Article  Google Scholar 

  46. Kallmann M, Kapadia M (2016) Geometric and discrete path planning for interactive virtual worlds. In: Synthesis lectures on visual computing: computer graphics, animation, computational photography, and imaging vol 8, no 1. pp 1–201

    Google Scholar 

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Authors and Affiliations

  1. University of Victoria, Victoria, Canada

    Brandon Haworth & Colin Johnson

  2. New Jersey Institute of Technology, Newark, NJ, USA

    Mathew Schwartz

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  1. Brandon Haworth
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  2. Colin Johnson
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  3. Mathew Schwartz
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Correspondence to Brandon Haworth .

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Editors and Affiliations

  1. Graduate School of Culture Technology (GSCT), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea (Republic of)

    Ji-Hyun Lee

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Haworth, B., Johnson, C., Schwartz, M. (2024). Universal Design of Signage Through Virtual Human Simulation. In: Lee, JH. (eds) Cultural Space on Metaverse. KAIST Research Series. Springer, Singapore. https://doi.org/10.1007/978-981-99-2314-4_4

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  • DOI: https://doi.org/10.1007/978-981-99-2314-4_4

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-2313-7

  • Online ISBN: 978-981-99-2314-4

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