Assessing crowd management strategies for the 2010 Love Parade disaster using computer simulations and virtual reality

Experiments as Code and its application to VR studies in human-building interaction

Experiments as Code (ExaC) is a concept for reproducible, auditable, debuggable, reusable, & scalable experiments. Experiments are a crucial tool to understand Human-Building Interactions (HBI) and build a coherent theory around it. However, a common concern for experiments is their auditability and reproducibility. Experiments are usually designed, provisioned, managed, and analyzed by diverse teams of specialists (e.g., researchers, technicians, engineers) and may require many resources (e.g., cloud infrastructure, specialized equipment). Although researchers strive to document experiments accurately, this process is often lacking. Consequently, it is difficult to reproduce these experiments. Moreover, when it is necessary to create a similar experiment, the "wheel is very often reinvented". It appears easier to start from scratch than trying to reuse existing work. Thus valuable embedded best practices and previous experiences are lost. In behavioral studies, such as in HBI, this has contributed to the reproducibility crisis. To tackle these challenges, we propose the ExaC paradigm, which not only documents the whole experiment, but additionally provides the automation code to provision, deploy, manage, and analyze the experiment. To this end, we define the ExaC concept, provide a taxonomy for the components of a practical implementation, and provide a proof of concept with an HBI desktop VR experiment that demonstrates the benefits of its "as code" representation, that is, reproducibility, auditability, debuggability, reusability, & scalability.

Global urban homogenization and the loss of emotions

Urban expansion is generating unprecedented homogenization of landscapes across the world. This uniformization of urban forms brings along dramatic environmental, social, and health problems. Reverting such processes requires activating people's sense of place, their feeling of caring for their surroundings, and their community engagement. While emotions are known to have a modulating effect on behavior, their role in urban transformation is unknown. Drawing on large cognitive-psychological experiments in two countries, we demonstrate for the first time that urban homogenization processes lower people's affective bounds to places and ultimately their intentions to engage with their neighbourhoods. The dulled emotional responses in peri-urban areas compared to urban and rural areas can be explained by lower social cohesion and place attachment. The findings highlight the significance of considering emotions in shaping just, equitable, sustainable, and resilient cities.

The One-Man-Crowd: Single User Generation of Crowd Motions Using Virtual Reality

Crowd motion data is fundamental for understanding and simulating realistic crowd behaviours. Such data is usually collected through controlled experiments to ensure that both desired individual interactions and collective behaviours can be observed. It is however scarce, due to ethical concerns and logistical difficulties involved in its gathering, and only covers a few typical crowd scenarios. In this work, we propose and evaluate a novel Virtual Reality based approach lifting the limitations of real-world experiments for the acquisition of crowd motion data. Our approach immerses a single user in virtual scenarios where he/she successively acts each crowd member. By recording the past trajectories and body movements of the user, and displaying them on virtual characters, the user progressively builds the overall crowd behaviour by him/herself. We validate the feasibility of our approach by replicating three real experiments, and compare both the resulting emergent phenomena and the individual interactions to existing real datasets. Our results suggest that realistic collective behaviours can naturally emerge from virtual crowd data generated using our approach, even though the variety in behaviours is lower than in real situations. These results provide valuable insights to the building of virtual crowd experiences, and reveal key directions for further improvements.

Exploring the Spatial Relationships Between Real and Virtual Experiences: What Transfers and What Doesn't

Virtual environments are commonly used to assess spatial cognition in humans. For the past few decades, researchers have used virtual environments to investigate how people navigate, learn, and remember their surrounding environment. In combination with tools such as electroencephalogram, neuroimaging, and electrophysiology, these virtual environments have proven invaluable in their ability to help elucidate the underlying neural mechanisms of spatial learning and memory in humans. However, a critical assumption that is made whenever using virtual experiences is that the spatial abilities used in the navigation of these virtual environments accurately represents the spatial abilities used in the real-world. The aim of the current study is to investigate the spatial relationships between real and virtual environments to better understand how well the virtual experiences parallel the same experiences in the real-world. Here, we performed three independent experiments to examine whether spatial information about object location, environment layout, and navigation strategy transfers between parallel real-world and virtual-world experiences. We show that while general spatial information does transfer between real and virtual environments, there are several limitations of the virtual experience. Compared to the real-world, the use of information in the virtual-world is less flexible, especially when testing spatial memory from a novel location, and the way in which we navigate these experiences are different as the perceptual and proprioceptive feedback gained from the real-world experience can influence navigation strategy.