A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments
Abstract
:1. Introduction
1.1. Background
1.2. Related Works
2. HDVGE Conceptual Framework
2.1. Conceptual Framework
- Virtual Human: HDVGE regards the human as the core, and emphasizes the subjectivity of human beings. The virtual human in the HDVGE includes avatars controlled by real users, and agents driven by computer programs. They can interact with other elements as well as themselves, such as interactions between avatars or avatars and agents. Multiple virtual human form a group through social relations, roles, and tasks. Massive groups in collective activities form a crowd.
- Environment: The environment is the background of the VGEx, and is the static part of the VGE. We mainly use 3D models to simulate the real geographical environment, including terrain, vegetation, architecture, etc., which constitute the physical part of the VGE. Similar to the real environment, it can be perceived and recognized. At the same time, different environments will constrain a virtual human’s behaviors.
- Entity: Entity refers to the dynamic variable entities in VGE. They have the ability to interact with humans. They can not only be perceived by humans, they can also provide feedback to the humans. For example, small obstacles in the evacuation process, such as desks and chairs, can affect the route choice of virtual humans; meanwhile, their state variables can also be changed by the humans. An essential issue in HDVGE is how the consistency of entity state variables in heterogeneous clients can be maintained.
2.2. HDVGE Design Principles
- Similarity in geographic space–time: The time and space in VGE should be similar to that in the real geographic environment (RGE). That is, the spatial scale and time scale in VGE should be identical to the real ones. This similarity provides principles for modeling the 3D virtual environment and process simulation. It requires strict reference to the size and proportion of real space when modeling VGE. Additionally, the time scale of the VGE cannot be changed.
- Similarity in spatial attributes: The spatial attributes and distributions of entities and processes in the VGE should be similar to that in the RGE. VGEx includes the simulation of processes in natural geography and human geography. This principle stipulates that the modeling and presentation of objects and geographic processes should be similar to reality.
- Similarity in group composition: Through the observation of pedestrians in public places [39], at least 70% of pedestrians in a given population are not traveling alone, but walk in groups. In a VGEx for spatiotemporal behavior research, group composition and member attributes must be similar to reality. Due to the limitations of the 3D modeling, VGEx cannot provide every user with an elaborate avatar. We use avatar models that are easy to discern to represent the members of the group, while those who are outside the group use an avatar with a different appearance. This similarity provides the basis for group modeling, observation, record, and analysis.
- Similarity in perception: The subject of a VGEx perceives the environment, entities, other subjects’ spatiotemporal positions, attributes, and group relations from a first-person perspective. The results of this perception process should be similar to the perception results of a RGE. For example, during a fire, the subjects’ perceptions of the evacuating crowd, and their own companions in the VGEx, should be similar to those in an actual fire environment. This similarity could stimulate the subject to behave similarly to reality. Therefore, this similarity provides the framework and principles for virtual scene design, process simulation, and interactions between multiple subjects.
3. HDVGE Architecture and Key Technologies
3.1. HDVGE Architecture
3.2. Key Technologies
3.2.1. Abstract Interaction Layer for Heterogeneous Clients
3.2.2. Protocol-Based Interactions between Heterogeneous Clients
3.2.3. Adjusted Dead Reckoning Algorithm for Client Prediction
4. Prototype System
4.1. Heterogeneous Distributed Virtual Evacuation Prototype System
4.2. Performance Evaluation of Key Algorithms
4.3. System Overall Performance Test
4.4. Data Analysis
5. Discussion
6. Conclusions and Future Works
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Shen, S.; Gong, J.; Liang, J.; Li, W.; Zhang, D.; Huang, L.; Zhang, G. A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments. ISPRS Int. J. Geo-Inf. 2018, 7, 54. https://doi.org/10.3390/ijgi7020054
Shen S, Gong J, Liang J, Li W, Zhang D, Huang L, Zhang G. A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments. ISPRS International Journal of Geo-Information. 2018; 7(2):54. https://doi.org/10.3390/ijgi7020054
Chicago/Turabian StyleShen, Shen, Jianhua Gong, Jianming Liang, Wenhang Li, Dong Zhang, Lin Huang, and Guoyong Zhang. 2018. "A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments" ISPRS International Journal of Geo-Information 7, no. 2: 54. https://doi.org/10.3390/ijgi7020054
APA StyleShen, S., Gong, J., Liang, J., Li, W., Zhang, D., Huang, L., & Zhang, G. (2018). A Heterogeneous Distributed Virtual Geographic Environment—Potential Application in Spatiotemporal Behavior Experiments. ISPRS International Journal of Geo-Information, 7(2), 54. https://doi.org/10.3390/ijgi7020054