Inverse augmentation: Transposing real people into pedestrian models

Inverse augmentation: Transposing real people into pedestrian models
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逆向增强:将真人转变为行人模型

DOI:
10.1016/j.compenvurbsys.2022.101923
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发表时间:
2023
期刊:
Environment and Urban Systems
影响因子:
--
通讯作者:
Gu, Simin
Gu, Simin
中科院分区:
--
文献类型:
--
作者:
Torrens, Paul M.;Gu, Simin

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我们介绍了一个计划沉浸在城市模拟的真实的人类用户,并使他们能够将他们的具体行为转化为模型。我们通过反向增强来实现这一点,颠覆了增强现实的传统哲学。我们不是从现实世界的场景开始,用图形来修饰它们,而是从一个充满代理角色的合成的、建模的街景的基础上进行,我们用真实的人类用户来增强。然后,允许参与者使用他们的自然能力来探索模拟场景。我们通过采用移动的虚拟现实来实现这一点,允许用户在融合的地理模拟和虚拟地理环境中建立动态存在,他们可以物理地查看和走动。我们的中心论点是,这种反转允许将人类行为的细节和细微差别直接带入模拟中,而这些细节和细微差别在传统上是难以捕捉和表示的。我们表明,地面上的真实的身体活动和模型世界中的动作之间的紧密匹配可以实现,通过空间分析和用户大脑活动的脑电图测量。我们证明了该方法的实用性与应用研究行人过马路行为。
We introduce a scheme for immersing real human users in urban simulations, and for enabling them to transpose their embodied behavior into models. We achieve this by inverse augmentation, flipping traditional philosophies of augmented reality. Rather than beginning with real-world scenes and embellishing them with graphics, we proceed from a base of synthetic, modeled, streetscapes filled with agent characters, which we augment with real human users. Participants are then allowed to use their natural abilities to explore the simulation scenarios. We achieve this by employing mobile virtual reality to allow users to build dynamic presence in a fused geosimulation and virtual geographic environment that they can physically view and walk around in. Our central argument is that inversion of this kind allows for the detail and nuances of human behavior to be brought directly into simulation, where they would traditionally be difficult to capture and represent. We show that close matches between real physical activity on the ground and actions in the model world can be achieved, as measured by spatial analysis and encephalography of user brain activity. We demonstrate the usefulness of the approach with an application to studying pedestrian road-crossing behavior.
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