@inproceedings{Kim2024Building,
    author = {Kim, Ryan and Torrens, Paul M.},
    title = {Building Verisimilitude in VR With High-Fidelity Local Action Models: A Demonstration Supporting Road-Crossing Experiments},
    year = {2024},
    isbn = {9798400703638},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3615979.3656060},
    doi = {10.1145/3615979.3656060},
    abstract = {We examine how issues of investigative and experimental parity between real-world domain science and virtual reality (VR) involving human-environment behavior might be advanced, particularly in the use case of safety science for road-crossing. Our contribution centers on a VR-based traffic flow simulation to recreate, with high fidelity relative to the real world, dynamics of hyper-local interaction between traffic, people, and the roadside environment. An initial demonstration of the system shows that 22 participants responded with high levels of presence, and with high propensity toward natural behavior across road-crossing dimensions. We report these findings even with low-resolution graphic elements. Our results highlight that high levels of user-identified situational verisimilitude (i.e., appearing authentic, particularly to the senses) can be achieved, even with low-resolution graphical depictions. The key, we argue, is the design of appropriate low-level action models to drive user embodiment relative to VR assets. We contend that this finding has wider relevance to consideration of potential channels for VR experience more generally.},
    booktitle = {Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation},
    pages = {119-130},
    numpages = {12},
    keywords = {3D interaction, AI, Behavioral tree, Embodiment, Microscopic traffic flow, Pathfinding, Pedestrian, Presence, Realism, Simulation, Task load, Virtual reality},
    location = {Atlanta, GA, USA},
    series = {SIGSIM-PADS '24}
}