Muhammad Usman
ABSTRACT
The importance of social distancing for public health is well established. However, the policies and regulations regarding occupancy rates have not been designed with this in mind. While there are analytical tools and related measures that are used in practice to evaluate how the design of a built environment serves the needs of its intended occupants, these metrics cannot directly apply to the problem of preventing the spread of infectious diseases such as COVID-19. By using a crowd-based simulator using three levels of behavior and agent control in a given environment, a novel evaluation metric for a space layout can be calculated to reflect the proclivity of maintaining a safe distance throughout the shopping experience. We refer to this metric as the Social Distancing Index (SDI), accounting for the occupancy throughput and number of distance-based violations found. Through a case study of a realistic retail store, we demonstrate the proposed platforms performance and output on multiple scenarios by changing agent-behavior, occupancy rate, and navigational guidelines.
- Glen Berseth, Muhammad Usman, Brandon Haworth, Mubbasir Kapadia, and Petros Faloutsos. 2015. Environment optimization for crowd evacuation. CAVW 26, 3-4 (2015), 377–386.Google Scholar
- Vincius J Cassol, Estêvão Smania Testa, Cláudio Rosito Jung, Muhammad Usman, Petros Faloutsos, Glen Berseth, Mubbasir Kapadia, Norman I Badler, and Soraia Raupp Musse. 2017. Evaluating and optimizing evacuation plans for crowd egress. CGA 37, 4 (2017), 60–71.Google ScholarDigital Library
- Benoît Claude, Dimitri Perrin, and Heather J Ruskin. 2009. Considerations for a social and geographical framework for agent-based epidemics. In Computational Aspects of Social Networks. IEEE, 149–154.Google Scholar
- Geoffrey A. Fowler. [n.d.]. Smartphone data reveal which Americans are social distancing. https://www.washingtonpost.com/technology/2020/03/24/social-distancing-maps-cellphone-location/.Google Scholar
- Robert J Glass, Laura M Glass, Walter E Beyeler, and H Jason Min. 2006. Targeted social distancing designs for pandemic influenza. Emerging infectious diseases 12, 11 (2006), 1671.Google Scholar
- Brandon Haworth, Muhammad Usman, Glen Berseth, Mahyar Khayatkhoei, Mubbasir Kapadia, and Petros Faloutsos. 2017. CODE: Crowd-optimized design of environments. CAVW 28, 6 (2017), e1749.Google Scholar
- Michael Brandon Haworth, Muhammad Usman, Davide Schaumann, Nilay Chakraborty, Glen Berseth, Petros Faloutsos, and Mubbasir Kapadia. 2020. Gamification of Crowd-Driven Environment Design. CGA (2020).Google Scholar
- Dirk Helbing and Peter Molnar. 1995. Social force model for pedestrian dynamics. Physical review E 51, 5 (1995), 4282.Google Scholar
- Mubbasir Kapadia, Nathan Marshak, and Norman I Badler. 2014. ADAPT: The agent development and prototyping testbed. TVCG1(2014), 1.Google Scholar
- Mubbasir Kapadia, Nuria Pelechano, Jan Allbeck, and Norm Badler. 2015. Virtual crowds: Steps toward behavioral realism. Synthesis lectures on visual computing 7, 4 (2015), 1–270.Google Scholar
- Mubbasir Kapadia, Shawn Singh, William Hewlett, and Petros Faloutsos. 2009. Egocentric affordance fields in pedestrian steering. In I3D. ACM, 215–223.Google Scholar
- Ioannis Karamouzas, Peter Heil, Pascal Van Beek, and Mark H Overmars. 2009. A predictive collision avoidance model for pedestrian simulation. In MIG. Springer, 41–52.Google Scholar
- David B Lantrip. 1993. Predicting satisfaction with the office environment by measuring constraints to worker activities. In Human Factors and Ergonomics Society Annual Meeting, Vol. 37. SAGE, 489–493.Google ScholarCross Ref
- Sang Min Lee, Won Sub Kang, Ah-Rang Cho, Tae Kim, and Jin Park. 2018. Psychological impact of the 2015 MERS outbreak on hospital workers and quarantined hemodialysis patients. Comprehensive Psychiatry 87 (2018), 123 – 127.Google ScholarCross Ref
- Ming C Lin, Avneesh Sud, Jur Van den Berg, Russell Gayle, Sean Curtis, Hengchin Yeh, Stephen Guy, Eric Andersen, Sachin Patil, Jason Sewall, 2008. Real-time path planning and navigation for multi-agent and crowd simulations. In MIG. Springer, 23–32.Google Scholar
- Marc Lipsitch, Lyn Finelli, Richard T Heffernan, Gabriel M Leung, and Stephen Redd. 2011. Improving the evidence base for decision making during a pandemic: the example of 2009 influenza A/H1N1. Biosecurity and bioterrorism: biodefense strategy, practice, and science 9, 2(2011), 89–115.Google Scholar
- Mehdi Moussaïd, Mubbasir Kapadia, Tyler Thrash, Robert W Sumner, Markus Gross, Dirk Helbing, and Christoph Hölscher. 2016. Crowd behaviour during high-stress evacuations in an immersive virtual environment. The Royal Society Interface 13, 122 (2016), 20160414.Google ScholarCross Ref
- World Health Organization. [n.d.]. Coronavirus disease (COVID-2019) situation reports. https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports.Google Scholar
- Xiaoshan Pan, Charles S Han, Ken Dauber, and Kincho H Law. 2007. A multi-agent based framework for the simulation of human and social behaviors during emergency evacuations. AI & Society 22, 2 (2007), 113–132.Google ScholarDigital Library
- Xue Bin Peng, Glen Berseth, KangKang Yin, and Michiel Van De Panne. 2017. Deeploco: Dynamic locomotion skills using hierarchical deep reinforcement learning. TOG 36, 4 (2017), 41.Google ScholarDigital Library
- Craig W Reynolds. 1987. Flocks, herds and schools: A distributed behavioral model. Vol. 21. ACM.Google Scholar
- Jaeyoung Shin and Jin-Kook Lee. 2019. Indoor Walkability Index: BIM-enabled approach to Quantifying building circulation. Automation in Construction 106 (2019), 102845. https://doi.org/10.1016/j.autcon.2019.102845Google ScholarCross Ref
- Anna Sieben, Jette Schumann, and Armin Seyfried. 2017. Collective phenomena in crowds—Where pedestrian dynamics need social psychology. PLoS one 12, 6 (2017), e0177328.Google ScholarCross Ref
- Alasdair Turner, Maria Doxa, David O’sullivan, and Alan Penn. 2001. From isovists to visibility graphs: a methodology for the analysis of architectural space. Environment and Planning B: Planning and design 28, 1 (2001), 103–121.Google Scholar
- Muhammad Usman, Davide Schaumann, Brandon Haworth, Mubbasir Kapadia, and Petros Faloutsos. 2019. Joint Exploration and Analysis of High-Dimensional Design–Occupancy Templates. In Motion, Interaction and Games. 1–5.Google Scholar
- Jur Van den Berg, Ming Lin, and Dinesh Manocha. 2008. Reciprocal velocity obstacles for real-time multi-agent navigation. In Robotics and Automation. IEEE, 1928–1935.Google Scholar
- Yuzhen Zhang, Bin Jiang, Jiamin Yuan, and Yanyun Tao. 2020. The impact of social distancing and epicenter lockdown on the COVID-19 epidemic in mainland China: A data-driven SEIQR model study. medRxiv (2020).Google Scholar
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