ReviewFrontiers in robotics and AI2018
Virtual Sensing and Virtual Reality: How New Technologies Can Boost Research on Crowd Dynamics.
Review in Frontiers in robotics and AI, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed, 40 citations in OpenAlex.
- People Counting Using YOLO-Based Detection and Clustering for a Mobile Robot.Sensors (Basel, Switzerland) · 2026Article
- Sensing Techniques in Virtual Reality for Human Interaction: A Bibliometric Analysis.Sensors (Basel, Switzerland) · 2026Review
- Social and spatial predictors of collective search behaviors.Scientific reports · 2025Article
- Individual and ecological heterogeneity promote complex communication in social vertebrate group decisions.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Review
- Experiments as Code and its application to VR studies in human-building interaction.Scientific reports · 2024Article
- A Novel Sentiment Analysis Model of Museum User Experience Evaluation Data Based on Unbalanced Data Analysis Technology.Computational intelligence and neuroscience · 2022Article
- The effect of navigation method and visual display on distance perception in a large-scale virtual building.Cognitive processing · 2021Article
- Gait coordination in overground walking with a virtual reality avatar.Royal Society open science · 2020Article
- Assessing crowd management strategies for the 2010 Love Parade disaster using computer simulations and virtual reality.Journal of the Royal Society, Interface · 2020Article
- The interaction between map complexity and crowd movement on navigation decisions in virtual reality.Royal Society open science · 2020Article
- Tracing Physical Behavior in Virtual Reality: A Narrative Review of Applications to Social Psychology.Journal of experimental social psychology · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The collective behavior of human crowds often exhibits surprisingly regular patterns of movement. These patterns stem from social interactions between pedestrians such as when individuals imitate others, follow their neighbors, avoid collisions with other pedestrians, or push each other. While some of these patterns are beneficial and promote efficient collective motion, others can seriously disrupt the flow, ultimately leading to deadly crowd disasters. Understanding the dynamics of crowd movements can help urban planners manage crowd safety in dense urban areas and develop an understanding of dynamic social systems. However, the study of crowd behavior has been hindered by technical and methodological challenges. Laboratory experiments involving large crowds can be difficult to organize, and quantitative field data collected from surveillance cameras are difficult to evaluate. Nevertheless, crowd research has undergone important developments in the past few years that have led to numerous research opportunities. For example, the development of crowd monitoring based on the virtual signals emitted by pedestrians' smartphones has changed the way researchers collect and analyze live field data. In addition, the use of virtual reality, and multi-user platforms in particular, have paved the way for new types of experiments. In this review, we describe these methodological developments in detail and discuss how these novel technologies can be used to deepen our understanding of crowd behavior.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.