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Paper in CAAD Future Conference

Paper “Social distancing and behavior modeling with Agent-based simulation” is accepted to the CAAD Future 2021 conference and inclusion into the CAAD Futures 2021 Springer Proceedings.

Presentation. 16 – 18 JULY 2021.

Abstract

The research discusses applying agent-based simulation (ABS) technology to analyze the social distancing in public space during the COVID-19 pandemic to facilitate design and planning decisions. The ABS is used to simulate pedestrian flow and construct the micro-level complexity within a simulated environment. This paper describes the various computational methods related to the ABS and design space under the new social distancing guidelines. We focus on the linear phases of agent activities, including (1) environmental query, (2) waiting in a zone, (3) waiting in a queue, and (4) tasks (E-Z-Q-T)  in response to design iterations related to crowd control and safety distance. The design project is extended to the agents’ interactions driven by a set of tasks in a simulated grocery store, restaurant, and public restroom.  We applied a quantitative analysis method and proximity analysis to evaluate architectural layouts and crowd control strategies. We discussed social distancing, pedestrian flow efficiency, public accessibility, and ways of reducing congestion through the intervention of the E-Z-Q-T phases.  

Keywords: agent-based simulation, social distancing, crowd control

Figure 3.  Agent density and space proximity map. ABS without social distancing vs. with social distancing rules. Each agent’s autonomous “action” lies in modifying its movement based on its rules and environment. Top. Floor plan and interior perspective of a check-in area of a restaurant. Middle: proximity map without social distancing. Bottom: proximity map with 2-meter social distancing with the same number of agents in the same given time. Notice the hot waiting areas’ issues are replaced with a larger waiting area, while some agents choose not to walk in the restaurant after EQ. Right. Compare the number of occupancies. Red: agents with social distancing. Blue: agents without social distancing.

This research was funded by UC Forward, as a part of the Price Hill project at UC.

paper accepted at CAADRIA conference

Ming Tang’s paper From agent to avatar: Integrate avatar and agent simulation in the virtual reality for wayfinding is accepted at the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA) 2018 conference in Beijing, China.  This paper describes a study of using immersive virtual reality (VR) technology to analyze user behavior related to wayfinding, and integrated it with the multi-agent simulation and space syntax. Starting with a theoretical framework, the author discussed the constraints of agent-based simulation (ABS) and space syntax to construct the micro-level interactions within a simulated environment. The author then focuses on how cognitive behavior and spatial knowledge can be achieved with a player controlled avatar in response to other computer controlled agents in a VR environment. The multi-phase approach starts with defining the Avatar Agent VR system (AAVR), which is used for capturing an avatar’s movement in real time and form the spatial data, and then visualize the data with various representation methods. Combined with space syntax and ABS, AAVR can exam various avatars’ wayfinding behavioral related to gender, spatial recognition level, and spatial features such as light, sound, and architectural simulations.

Check out the full paper there:

Tang, M. From agent to avatar: Integrate avatar and agent simulation in the virtual reality for wayfinding. Proceedings of the 23rd International Conference of the Association for Computer-Aided Architectural Design Research in Asia (CAADRIA). Beijing, China. 2018.

Virtual DAAP

Virtual DAAP extends to the discussion of technological constraints of VR such as field of vision, peripheral vision, and vestibular indices. The multi-phase approach starts with defining the immersive VR system, which is used for capturing real agent’s movement within a digital environment to form raw data in the cloud, and then visualize it with heat-map and path network. Combined with graphs, survey data is also used to compare various agents’ way-finding behavioral related to gender, spatial recognition level, and spatial features such as light, sound, and architectural simulations.

 

More information about virtual DAAP.

Crowd Simulation through Multi-Agent Modeling

Use Agent Based Modeling to simulate large crowd behavior. way-finding and egress analysis.

The research discusses experiential outcome in the application of crowd simulation technology to analyze the pedestrian circulation in the public space to facilitate design and planning decisions.  We focus on how to connect space design with agent-based simulation (ABS) for various design and planning scenarios., and investigate the process of visualizing and representing pedestrian movement, as well as the path-finding and crowd behavior study.

 

Publication:

Check more >> Crowd Simulation