A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments

Abstract

Due to their strong immersion and real-time interactivity, helmet-mounted virtual reality (VR) devices are becoming increasingly popular. Based on these devices, an immersive virtual geographic environment (VGE) provides a promising method for research into crowd behavior in an emergency. However, the current cheaper helmet-mounted VR devices are not popular enough, and will continue to coexist with personal computer (PC)-based systems for a long time. Therefore, a heterogeneous distributed virtual geographic environment (HDVGE) could be a feasible solution to the heterogeneous problems caused by various types of clients, and support the implementation of spatiotemporal crowd behavior experiments with large numbers of concurrent participants. In this study, we developed an HDVGE framework, and put forward a set of design principles to define the similarities between the real world and the VGE. We discussed the HDVGE architecture, and proposed an abstract interaction layer, a protocol-based interaction algorithm, and an adjusted dead reckoning algorithm to solve the heterogeneous distributed problems. We then implemented an HDVGE prototype system focusing on subway fire evacuation experiments. Two types of clients are considered in the system: PC, and all-in-one VR. Finally, we evaluated the performances of the prototype system and the key algorithms. The results showed that in a low-latency local area network (LAN) environment, the prototype system can smoothly support 90 concurrent users consisting of PC and all-in-one VR clients. HDVGE provides a feasible solution for studying not only spatiotemporal crowd behaviors in normal conditions, but also evacuation behaviors in emergency conditions such as fires and earthquakes. HDVGE could also serve as a new means of obtaining observational data about individual and group behavior in support of human geography research.

Reflections and speculations on the progress in Geographic Information Systems (GIS): a geographic perspective

“…Such functionality would both popularise GIS and contribute to the collection of human behaviour-related data for studies on human-land interactions, especially at the local and fine scales, e.g. for evacuation from a fire (Li et al 2017a;Shen et al 2018). However, due to the high cost of traditional equipment, e.g.…”

Geospatial Information Visualization and Extended Reality Displays

“…A modern description of a VGE is a digital geographic environment "generated by computers and related technologies that users can use to experience and recognize complex geographic systems and further conduct comprehensive geographic analyses, through equipped functions, including multichannel human-computer interactions (HCIs), distributed geographic modeling and simulations, and network geo-collaborations" (Chen and Lin 2018, p. 329). Since their conception, VGEs have attracted considerable attention in the geographic information science research community over the last few decades (e.g., Goodchild 2009;Huang et al 2018;Jia et al 2015;Konecny 2011;Liang et al 2015;Mekni 2010;Priestnall et al 2012;Rink et al 2018;Shen et al 2018;Torrens 2015;Zhang et al 2018;Zheng et al 2017). Much like the "digital twin" idea, and well-aligned with the Digital Earth concept, VGEs often aim to mirror realworld geographic environments in virtual ones.…”

Collaborative Immersive Virtual Environments for Education in Geography

“…Immersive VR finds a purpose in many fields, for example, in psychotherapy and diagnostics [1][2][3][4], cognitive training [5,6], relaxation [7,8], rehabilitation [9,10], medicine [11,12], training in the industry [13][14][15], tourism and cultural heritage [16][17][18], journalism [19], and sport [20,21]. The rich potential of immersive virtual reality is also utilized in areas that use geographical data, for example, evacuation planning [22,23], geospatial data exploration and analysis [24][25][26][27], navigation in urban areas [28,29], visualization of spatial data quality [30], and urban planning [31].…”