“Crowd-driven mid-scale layout design” by Feng, Yu, Yeung, Yin and Zhou
Conference:
Type:
Session Title:
- PROCEDURAL MODELING
Title:
- Crowd-driven mid-scale layout design
Moderator(s):
Presenter(s)/Author(s):
Abstract:
We propose a novel approach for designing mid-scale layouts by optimizing with respect to human crowd properties. Given an input layout domain such as the boundary of a shopping mall, our approach synthesizes the paths and sites by optimizing three metrics that measure crowd flow properties: mobility, accessibility, and coziness. While these metrics are straightforward to evaluate by a full agent-based crowd simulation, optimizing a layout usually requires hundreds of evaluations, which would require a long time to compute even using the latest crowd simulation techniques. To overcome this challenge, we propose a novel data-driven approach where nonlinear regressors are trained to capture the relationship between the agent-based metrics, and the geometrical and topological features of a layout. We demonstrate that by using the trained regressors, our approach can synthesize crowd-aware layouts and improve existing layouts with better crowd flow properties.
References:
1. AlHalawani, S., and Mitra, N. J. 2015. Congestion-aware warehouse flow analysis and optimization. In Advances in Visual Computing. Springer, 702–711.Google Scholar
2. AlHalawani, S., Yang, Y.-L., Wonka, P., and Mitra, N. J. 2014. What makes London work like London? Computer Graphics Forum 33, 5 (Aug.), 157–165.Google ScholarDigital Library
3. Ali, W., and Moulin, B. 2005. 2d-3d multiagent geosimulation with knowledge-based agents of customers’ shopping behavior in a shopping mall. In Spatial Information Theory, A. Cohn and D. Mark, Eds., vol. 3693 of Lecture Notes in Computer Science. Springer Berlin Heidelberg, 445–458. Google ScholarDigital Library
4. Aliaga, D. G., Vanegas, C. A., and Beneš, B. 2008. Interactive example-based urban layout synthesis. ACM Trans. Graph. 27, 5 (Dec.), 160:1–160:10. Google ScholarDigital Library
5. Aliaga, D. G. 2012. 3d design and modeling of smart cities from a computer graphics perspective. International Scholarly Research Notices 2012.Google ScholarCross Ref
6. Aschwanden, G. D., Haegler, S., Bosché, F. N., Van Gool, L., and Schmitt, G. 2011. Empiric design evaluation in urban planning. Automation in construction 20, 3 (May), 299–310.Google Scholar
7. Bao, F., Yan, D.-M., Mitra, N. J., and Wonka, P. 2013. Generating and exploring good building layouts. ACM Trans. Graph. 32, 4 (July), 122:1–122:10. Google ScholarDigital Library
8. Beneš, J., Wilkie, A., and Křivánek, J. 2014. Procedural modelling of urban road networks. Computer Graphics Forum 33, 6, 132–142.Google ScholarDigital Library
9. Bloch, P. H., Ridgway, N. M., and Dawson, S. A. 1994. The shopping mall as consumer habitat. Journal of Retailing 70, 1, 23–42.Google ScholarCross Ref
10. Brown, M. G. 1999. Design and value: Spatial form and the economic failure of a mall. Journal of Real Estate Research 17, 189–225.Google ScholarCross Ref
11. Castillo, L. F., Bedia, M. G., Uribe, A. L., and Isaza, G. 2009. A formal approach to test commercial strategies: Comparative study using multiagent based techniques. Journal of Physical Agents 3, 3, 25–30.Google Scholar
12. Chen, G., Esch, G., Wonka, P., Müller, P., and Zhang, E. 2008. Interactive procedural street modeling. ACM Trans. Graph. 27, 3 (Aug.), 103:1–103:10. Google ScholarDigital Library
13. Clave, S. A. 2007. The Global Theme Park Industry. CABI.Google Scholar
14. D. Beyard, M., Corrigan, M. B., Kramer, A., Pawlukiewicz, M., and Bach, A. 2006. Ten Principles of Rethinking the Mall. Urban Land Institute.Google Scholar
15. ESRI, 2016. ArcGIS. http://arcgis.com. Accessed: 01-01-2016.Google Scholar
16. Fang, Z., Lo, S., and Lu, J. 2003. On the relationship between crowd density and movement velocity. Fire Safety Journal 38, 3, 271–283.Google ScholarCross Ref
17. Fisher, M., Savva, M., Li, Y., Hanrahan, P., and Niessner, M. 2015. Activity-centric scene synthesis for functional 3d scene modeling. ACM Trans. Graph. 34, 6 (Oct.), 179:1–179:13. Google ScholarDigital Library
18. Galin, E., Peytavie, A., Maréchal, N., and Guérin, E. 2010. Procedural generation of roads. Computer Graphics Forum 29, 2, 429–438.Google ScholarCross Ref
19. Galin, E., Peytavie, A., Guérin, E., and Benes, B. 2011. Authoring hierarchical road networks. Computer Graphics Forum 30, 7, 2021–2030.Google ScholarCross Ref
20. Galle, P. 1981. An algorithm for exhaustive generation of building floor plans. Communications of ACM 24, 12 (Dec.), 813–825. Google ScholarDigital Library
21. Gloor, C., 2016. Pedsim. http://pedsim.silmaril.org. Accessed: 01-01-2016.Google Scholar
22. Guy, S. J., van den Berg, J., Liu, W., Lau, R., Lin, M. C., and Manocha, D. 2012. A statistical similarity measure for aggregate crowd dynamics. ACM Trans. Graph. 31, 6 (Nov.), 190:1–190:11. Google ScholarDigital Library
23. Hall, E. T. 1990. The Hidden Dimension. A Doubleday anchor book. Anchor Books.Google Scholar
24. Harada, M., Witkin, A., and Baraff, D. 1995. Interactive physically-based manipulation of discrete/continuous models. In Proceedings of the 22nd Annual Conference on Computer Graphics and Interactive Techniques, ACM, New York, NY, USA, SIGGRAPH ’95, 199–208. Google ScholarDigital Library
25. Hastings, W. K. 1970. Monte Carlo sampling methods using Markov chains and their applications. Biometrika 57, 1 (Apr.), 97–109.Google ScholarCross Ref
26. Helbing, D., and Molnar, P. 1995. Social force model for pedestrian dynamics. Physical review E 51, 5, 4282.Google Scholar
27. Huerre, S., Lee, J., Lin, M., and O’Sullivan, C. 2010. Simulating believable crowd and group behaviors. In SIGGRAPH Asia 2010 Courses. Google ScholarDigital Library
28. ICSC. 2015. U.S. Shopping-Center Classification and Characteristics. ICSC Research and CoStar Realty Information, Inc., mar.Google Scholar
29. INRIA, 2016. scikit-learn. http://scikit-learn.org. Accessed: 01-01-2016.Google Scholar
30. Kirkpatrick, S., Gelatt, C. D., and Vecchi, M. P. 1983. Optimization by simulated annealing. SCIENCE 220, 4598, 671–680.Google Scholar
31. Li, X., and Liu, X. 2008. Embedding sustainable development strategies in agent-based models for use as a planning tool. International Journal of Geographical Information Science 22, 1, 21–45. Google ScholarDigital Library
32. Li, W., Di, Z., and Allbeck, J. 2012. Crowd distribution and location preference. Computer Animation and Virtual Worlds 23, 3, 343–351. Google ScholarDigital Library
33. Liaw, A., and Wiener, M. 2002. Classification and regression by randomforest. R News 2, 3, 18–22.Google Scholar
34. Liu, H., Yang, Y.-L., AlHalawani, S., and Mitra, N. J. 2013. Constraint-aware interior layout exploration for precast concrete-based buildings. Visual Computer (CGI Special Issue). Google ScholarDigital Library
35. Machleit, K. A., Eroglu, S. A., and Mantel, S. P. 2000. Perceived retail crowding and shopping satisfaction: What modifies this relationship? Journal of Consumer Psychology 9, 1, 29–42.Google ScholarCross Ref
36. Massive Software, 2016. Massive. http://massivesoftware.com. Accessed: 01-01-2016.Google Scholar
37. Merrell, P., Schkufza, E., and Koltun, V. 2010. Computer-generated residential building layouts. ACM Trans. Graph. 29, 6 (Dec.), 181:1–181:12. Google ScholarDigital Library
38. Merrell, P., Schkufza, E., Li, Z., Agrawala, M., and Koltun, V. 2011. Interactive furniture layout using interior design guidelines. ACM Trans. Graph. 30, 4 (July), 87:1–87:10. Google ScholarDigital Library
39. Metropolis, N., Rosenbluth, A. W., Rosenbluth, M. N., Teller, A. H., and Teller, E. 1953. Equation of state calculations by fast computing machines. The Journal of Chemical Physics 21, 6, 1087–1092.Google ScholarCross Ref
40. Michalek, J., Choudhary, R., and Papalambros, P. 2002. Architectural layout design optimization. Engineering Optimization 34, 12, 461–484.Google ScholarCross Ref
41. Narain, R., Golas, A., Curtis, S., and Lin, M. C. 2009. Aggregate dynamics for dense crowd simulation. ACM Trans. Graph. 28, 5 (Dec.), 122:1–122:8. Google ScholarDigital Library
42. Ng, C. F. 2003. Satisfying shoppers’ psychological needs: From public market to cyber-mall. Journal of Environmental Psychology 23, 4, 439–455.Google ScholarCross Ref
43. Niles, R., 2012. Robert’s rules for the perfect theme park. http://themeparkinsider.com/flume/201212/3304, Dec. Accessed: 01-01-2016.Google Scholar
44. Nishida, G., Garcia-Dorado, I., and Aliaga, D. G. 2015. Example-driven procedural urban roads. Computer Graphics Forum.Google Scholar
45. Older, S. J. 1964. Pedestrians. Department of Scientific and Industrial Research Laboratory, Crowthorne, England.Google Scholar
46. Parish, Y. I. H., and Müller, P. 2001. Procedural modeling of cities. In Proceedings of the 28th Annual Conference on Computer Graphics and Interactive Techniques, ACM, New York, NY, USA, SIGGRAPH ’01, 301–308. Google ScholarDigital Library
47. Peng, C.-H., Yang, Y.-L., and Wonka, P. 2014. Computing layouts with deformable templates. ACM Trans. Graph. 33, 4 (July), 99:1–99:11. Google ScholarDigital Library
48. Peng, C.-H., Mitra, N. J., Bao, F., Yan, D.-M., and Wonka, P. 2015. Computational Network Design from Functional Specifications. ArXiv e-prints (Oct.).Google Scholar
49. Pettré, J., Kallmann, M., and Lin, M. C. 2008. Motion planning and autonomy for virtual humans. In ACM SIGGRAPH 2008 Courses, ACM, 42. Google ScholarDigital Library
50. Prusinkiewicz, P., and Lindenmayer, A. 1996. The Algorithmic Beauty of Plants. Springer-Verlag New York, Inc., New York, NY, USA. Google ScholarDigital Library
51. Shao, W., and Terzopoulos, D. 2005. Autonomous pedestrians. In Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, ACM, New York, NY, USA, SCA ’05, 19–28. Google ScholarDigital Library
52. Shaviv, E. 1974. A Model for Space Allocation in Complex Buildings: A Computer Graphics Approach. Working papers. Faculty of Architecture and Town Planning.Google Scholar
53. Sun, J., Yu, X., Baciu, G., and Green, M. 2002. Template-based generation of road networks for virtual city modeling. In Proceedings of the ACM Symposium on Virtual Reality Software and Technology, ACM, New York, NY, USA, VRST ’02, 33–40. Google ScholarDigital Library
54. The AnyLogic Company, 2016. Anylogic. http://anylogic.com. Accessed: 01-01-2016.Google Scholar
55. Thunderhead Engineering Consultants, Inc., 2016. Pathfinder. http://thunderheadeng.com/pathfinder. Accessed: 01-01-2016.Google Scholar
56. TranSafety, Inc. 1997. Study compares older and younger pedestrian walking speeds. Road Engineering Journal.Google Scholar
57. Treuille, A., Cooper, S., and Popović, Z. 2006. Continuum crowds. ACM Trans. Graph. 25, 3 (July), 1160–1168. Google ScholarDigital Library
58. Tu, X., and Terzopoulos, D. 1994. Artificial fishes: Physics, locomotion, perception, behavior. In Proceedings of the 21st Annual Conference on Computer Graphics and Interactive Techniques, ACM, New York, NY, USA, SIGGRAPH ’94, 43–50. Google ScholarDigital Library
59. Vanegas, C. A., Aliaga, D. G., Benes, B., and Waddell, P. 2009. Interactive design of urban spaces using geometrical and behavioral modeling. ACM Trans. Graph. 28, 5, 111:1–111:10. Google ScholarDigital Library
60. Vanegas, C. A., Garcia-Dorado, I., Aliaga, D. G., Benes, B., and Waddell, P. 2012. Inverse design of urban procedural models. ACM Trans. Graph. 31, 6 (Nov.), 168:1–168:11. Google ScholarDigital Library
61. Vanegas, C. A., Kelly, T., Weber, B., Halatsch, J., Aliaga, D. G., and Müller, P. 2012. Procedural generation of parcels in urban modeling. Computer Graphics Forum 31, 2pt3 (May), 681–690. Google ScholarDigital Library
62. Weber, B., Mller, P., Wonka, P., and Gross, M. 2009. Interactive geometric simulation of 4d cities. Computer Graphics Forum 28, 2, 481–492.Google ScholarCross Ref
63. Wilkie, D., Sewall, J., and Lin, M. 2013. Flow reconstruction for data-driven traffic animation. ACM Trans. Graph. 32, 4 (July), 89:1–89:10. Google ScholarDigital Library
64. Xu, K., Zhang, H., Cohen-Or, D., and Chen, B. 2012. Fit and diverse: Set evolution for inspiring 3d shape galleries. ACM Trans. Graph. 31, 4 (July), 57:1–57:10. Google ScholarDigital Library
65. Yang, Y.-L., Wang, J., Vouga, E., and Wonka, P. 2013. Urban pattern: Layout design by hierarchical domain splitting. ACM Trans. Graph. 32, 6 (Nov.), 181:1–181:12. Google ScholarDigital Library
66. Yu, Q., and Terzopoulos, D. 2007. A decision network framework for the behavioral animation of virtual humans. In Proceedings of the 2007 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, Eurographics Association, Aire-la-Ville, Switzerland, Switzerland, SCA ’07, 119–128. Google ScholarDigital Library
67. Yu, L.-F., Yeung, S.-K., Tang, C.-K., Terzopoulos, D., Chan, T. F., and Osher, S. J. 2011. Make it home: Automatic optimization of furniture arrangement. ACM Trans. Graph. 30, 4 (July), 86:1–86:12. Google ScholarDigital Library
68. Yu, L.-F., Yeung, S.-K., Terzopoulos, D., and Chan, T. F. 2012. Dressup!: Outfit synthesis through automatic optimization. ACM Trans. Graph. 31, 6 (Nov.), 134:1–134:14. Google ScholarDigital Library
