Estimating density limits for walking pedestrians keeping a safe interpersonal distancing

With or Without You: Effect of Contextual and Responsive Crowds on VR-based Crowd Motion Capture

While data is vital to better understand and model interactions within human crowds, capturing real crowd motions is extremely challenging. Virtual Reality (VR) demonstrated its potential to help, by immersing users into either simulated virtual crowds based on autonomous agents, or within motion-capture-based crowds. In the latter case, users' own captured motion can be used to progressively extend the size of the crowd, a paradigm called Record-and-Replay (2R). However, both approaches demonstrated several limitations which impact the quality of the acquired crowd data. In this paper, we propose the new concept of contextual crowds to leverage both crowd simulation and the 2R paradigm towards more consistent crowd data. We evaluate two different strategies to implement it, namely a Replace-Record-Replay (3R) paradigm where users are initially immersed into a simulated crowd whose agents are successively replaced by the user's captured-data, and a Replace-Record-Replay-Responsive (4R) paradigm where the pre-recorded agents are additionally endowed with responsive capabilities. These two paradigms are evaluated through two real-world-based scenarios replicated in VR. Our results suggest that the behaviors observed in VR users with surrounding agents from the beginning of the recording process are made much more natural, enabling 3R or 4R paradigms to improve the consistency of captured crowd datasets.

Controlling inter-particle distances in crowds of motile, cognitive, active particles

Distance control in many-particle systems is a fundamental problem in nature. This becomes particularly relevant in systems of active agents, which can sense their environment and react by adjusting their direction of motion. We employ agent-based simulations to investigate the complex interplay between agent activity, characterized by Péclet number Pe , reorientation maneuverability Ω , vision angle θ and vision range R 0 , and agent density, which determines agent distancing and dynamics. We focus on semi-dense crowds, where the vision range is much larger than the particle size. The minimal distance to the nearest neighbors, exposure time, and persistence of orientation direction are analyzed to characterize the behavior. With increasing particle speed at fixed maneuverability, particles approach each other more closely, and exhibit shorter exposure times. The temporal persistence of motion decreases with increasing Pe , reflecting the impact of activity and maneuverability on direction changes. For a vision angle θ = π / 4 , we observe the emergence of flocking aggregates with a band-like structure, somewhat reminiscent of the bands in the Vicsek model. Additionally, for vision angles θ ≥ π / 2 , several quantities are found to display a universal scaling behavior with scaling variablePe 3 / 2 / Ω . Our results are in good agreement with recent experiments of pedestrians in confined spaces.

Evaluating the dynamic interplay of social distancing policies regarding airborne pathogens through a temporal interaction-driven model that uses real-world and synthetic data

OBJECTIVE

The recent SARS-CoV-2 pandemic has exhibited diverse patterns of spread across countries and communities, emphasizing the need to consider the underlying population dynamics in modeling its progression and the importance of evaluating the effectiveness of non-pharmaceutical intervention strategies in combating viral transmission within human communities. Such an understanding requires accurate modeling of the interplay between the community dynamics and the disease propagation dynamics within the community.

METHODS

We build on an interaction-driven model of an airborne disease over contact networks that we have defined. Using the model, we evaluate the effectiveness of temporal, spatial, and spatiotemporal social distancing policies. Temporal social distancing involves a pure dilation of the timeline while preserving individual activity potential and thus prolonging the period of interaction; spatial distancing corresponds to social distancing pods; and spatiotemporal distancing pertains to the situation in which fixed subgroups of the overall group meet at alternate times. We evaluate these social distancing policies over real-world interactions' data and over history-preserving synthetic temporal random networks. Furthermore, we evaluate the policies for the disease's with different number of initial patients, corresponding to either the phase in the progression of the infection through a community or the number of patients infected together at the initial infection event. We expand our model to consider the exposure to viral load, which we correlate with the meetings' duration.

RESULTS

Our results demonstrate the superiority of decreasing social interactions (i.e., time dilation) within the community over partial isolation strategies, such as the spatial distancing pods and the spatiotemporal distancing strategy. In addition, we found that slow-spreading pathogens (i.e., pathogens that require a longer exposure to infect) spread roughly at the same rate as fast-spreading ones in highly active communities. This result is surprising since the pathogens may follow different paths. However, we demonstrate that the dilation of the timeline considerably slows the spread of the slower pathogens.

CONCLUSIONS

Our results demonstrate that the temporal dynamics of a community have a more significant effect on the spread of the disease than the characteristics of the spreading processes.

Capacity, Collision Avoidance and Shopping Rate under a Social Distancing Regime

Capacity restrictions in stores, maintained by mechanisms like spacing customer intake, became familiar features of retailing in the time of the pandemic. Shopping rates in a crowded store under a social distancing regime are prone to considerable slowdown. Inspired by the random particle collision concepts of statistical mechanics, we introduce a dynamical model of the evolution of the shopping rate as a function of a given customer intake rate. The slowdown of each individual customer is incorporated as an additive term to the baseline value of the shopping time, proportionally to the number of other customers in the store. We determine analytically and via simulation the trajectory of the model as it approaches a Little's law equilibrium and identify the point beyond which equilibrium cannot be achieved. By relating the customer shopping rate to the slowdown compared with the baseline, we can calculate the optimal intake rate leading to maximum equilibrium spending. This turns out to be the maximum rate compatible with equilibrium. The slowdown due to the largest possible number of shoppers is more than compensated for by the increased volume of shopping. This macroscopic model is validated by simulation experiments in which avoidance interactions between pairs of shoppers are responsible for shopping delays.

Monitoring speed variation and pedestrian crossing distraction in Enna (Sicily) during different pandemic phases

The growing phenomenon of teleworking and the recent covid-19 pandemic have caused the volumes of pedestrians who routinely cross the city to change since March 2020. This change may have resulted in further damage to the health of pedestrians due to limited activity. Some recent studies point to slight changes in walking speed and stride length compared to changes in the number of steps, these changes were consistently seen during the state of emergency, they showed that people tried to walk faster in their outdoor walking. For the safety of pedestrians, it is necessary to analyse not only the change in speed when crossing but also the potential factors influencing it. These factors include user-related variables (gender, age, weight) and variables related to potential distractors such as smartphone use or walking in groups. The results of measurements made during the pandemic period (4 different phases) in pedestrian traffic in the zebra crossing area are also presented. The research was conducted in a zebra crossing area located in a small town in Sicily (Enna) frequently used by workers, students and elderly people. The results showed that during the first and second pandemic phases (May to October 2021) there were significant changes in the way of moving and the speed of pedestrians at crossings. The same crossings were also examined in the late autumn of 2021 (third and fourth pandemic phases) and the data show further changes in pedestrian behaviour. The data collected can help to improve safety in the area of pedestrian crossings through infrastructural actions or educational programmes and campaigns, especially among vulnerable groups of pedestrians.

Crowd dynamics research in the era of Covid-19 pandemic: Challenges and opportunities

With the issues of crowd control and physical distancing becoming central to disease prevention measures, one would expect that crowd research should become a focus of attention during the Covid-19 pandemic era. However, I will show, based on a variety of metrics, that not only has this not been the case, but also, the first two years of the pandemic have posed an undisputable setback to the development and growth of crowd science. Without intervention, this could potentially aggravate further and cause a long-lasting recession in this field. This article, in addition to documenting and highlighting this issue, aims to outline potential avenues through which crowd research can reshape itself in the era of Covid-19 pandemic, maintain its pre-pandemic momentum and even further expand the diversity of its topics. Despite significant changes that the pandemic has brought to human life, issues related to congregation and mobility of pedestrians, building fires, crowd incidents, rallying crowds and the like have not disappeared from societies and remain relevant. Moreover, the diversity of pandemic-related problems itself creates a rich ground for making novel scientific discoveries. This could provide grounds for establishing fresh dimensions in crowd dynamics research. These potential new dimensions extend to all areas of this field including numerical and experimental investigations, crowd psychology and applications of computer vision and artificial intelligence methods in crowd management. The Covid-19 pandemic may have posed challenges to crowd researchers but has also created ample potential opportunities. This is further evidenced by reviewing efforts taken thus far in pandemic-related crowd research.

A dynamic physical-distancing model to evaluate spatial measures for prevention of Covid-19 spread

Motivated by the global pandemic of COVID-19, this study investigates the spatial factors influencing physical distancing, and how these affect the transmission of the SARS-CoV-2 virus, by integrating pedestrian dynamics with a modified susceptible-exposed-infectious model. Contacts between infected and susceptible pedestrians are examined by determining physical-distancing pedestrian dynamics in three types of spaces, and used to estimate the proportion of newly infected pedestrians in these spaces. Desired behaviour for physical distancing can be observed from simulation results, and aggregated simulation findings reveal that certain layouts enable physical distancing to reduce the transmission of SARS-CoV-2. We also provide policymakers with several design guidelines on how to proactively design more effective and resilient space layouts in the context of pandemics to keep low transmission risks while maintaining a high pedestrian volume. This approach has enormous application potential for other infectious-disease transmission and space assessments.

Spontaneous emergence of counterclockwise vortex motion in assemblies of pedestrians roaming within an enclosure

The emergence of coherent vortices has been observed in a wide variety of many-body systems such as animal flocks, bacteria, colloids, vibrated granular materials or human crowds. Here, we experimentally demonstrate that pedestrians roaming within an enclosure also form vortex-like patterns which, intriguingly, only rotate counterclockwise. By implementing simple numerical simulations, we evidence that the development of swirls in many-particle systems can be described as a phase transition in which both the density of agents and their dissipative interactions with the boundaries play a determinant role. Also, for the specific case of pedestrians, we show that the preference of right-handed people (the majority in our experiments) to turn leftwards when facing a wall is the symmetry breaking mechanism needed to trigger the global counterclockwise rotation observed.

A novel social distance model reveals the sidewall effect at bottlenecks

Intermittent and periodic outbreaks of infectious diseases have had profound and lasting effects on societies throughout human history. During the global spread of SARS-CoV-2 and the resulting coronavirus disease (COVID-19), social distance has been imposed worldwide to limit the spread of the virus. An additional deliberate intention of keeping a minimum safety distance from neighbors can fundamentally alter the "social force" between individuals. Here, we introduce a new "social distance" term inspired by gas molecular dynamics and integrate it into an existing agent-based social force model to describe the dynamics of crowds under social-distanced conditions. The advantage of this "social distance" term over the simple increasing of the repulsive range of other alternatives is that the fundamental crowd properties are precisely described by our model parameters. We compare the new model with the Helbing and Molnar's classical model and experimental data, and show that this new model is superior in reproducing experimental data. We demonstrate the usability of this model with a bottleneck motion base case. The new model shows that the bottleneck effect can be significantly alleviated through small wall modifications. Lastly, we explain the mechanism of this improvement and conclude that this improvement is due to spatial asymmetry.