A novel approach for occupants' horizontal and vertical movement modeling in non-residential buildings using Immersive Virtual Environment (IVE)

Abstract

• Presented a general framework for the analysis of occupant behavior in IVEs • Established an IVE platform for occupant behavior observational experiments • Investigated occupant's horizontal and vertical movements in buildings respectively • Analyzed and extracted key features and typical patterns for occupant's movement • Built agent-based model to simulate stochastic occupant movement in buildings Occupant's movement in buildings is one of the most essential factors that influence building energy consumption. Understanding the movement of occupants in buildings is crucial for building design and operations. The advances in virtual reality (VR), especially immersive virtual environments (IVEs), offer new and cost-effective alternatives for occupant behavior studies in unbuilt buildings at design phase and establishing controlled experimental scenarios. This paper presents a general framework for the investigation, analysis, and modelling of the horizontal and vertical movements of occupants in buildings using IVE experimental platform. We first established an IVE experimental platform and conduct the experiment in IVE platform to observe occupant horizontal and vertical movement in buildings. The collected experimental data were then used to statistically analyze and extract key features of the occupant's vertical and horizontal movement patterns, based on which a set of agent-based models (ABMs) are built to simulate stochastic occupant's horizontal and vertical movement patterns in buildings. The proposed method can efficiently capture the occupants’ movement patterns, therefore creating more realistic ABMs for simulation. The proposed method provides an efficient approach to utilizing IVE technology for occupant movement pattern observations and modeling horizontal and vertical moving patterns for advanced building design and management.