The flow of human crowds

By Roger L. Hughes. 2003

727 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Control and Systems Engineering, Ocean Engineering

View Paper: https://www.semanticscholar.org/paper/4e8b9b7d4f3a8caf4065e9b653c6ddece6847961

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In Biomedical Engineering

In Control and Systems Engineering

In Ocean Engineering

Citations in the corpus

A synthetic-vision based steering approach for crowd simulation (2010, background): “Crowd simulation was also studied as a flowing continuum [Hughes 2003; Treuille et al. 2006] that allows simulating numerous walkers in real-time.”
Existence and uniqueness of measure solutions for a system of continuity equations with non-local flow (2011, background): “Some of these models are local in ρ (see [4,11,17,18,20,21]); other models use not only the local density ρ(t, x) but the entire distribution of ρ, typically they depend on the convolution product ρ(t) ∗ η (see [6–9,14,23]) which represents the spatial average of the density.”
Crowds by Example (2007, background): “Some popular approaches take ideas from fluid mechanics [Hug03, TCP06], while others make use of particles and social forces [HM95, HLTC03].”
Understanding collective crowd behaviors: Learning a Mixture model of Dynamic pedestrian-Agents (2012, background): “Continuum-based pedestrian models [8, 20] treated the crowd motion as fluid with manually assigned parameters.”
Learning Social Etiquette: Human Trajectory Understanding In Crowded Scenes (2016, background): “For instance, two leading families of methods for target trajectory forecasting (Social Forces [14,15,1,2] and Gaussian Processes [16,17,12]) have shown promising results on existing datasets [18,11]; however, they have never been tested at scale and in real-world scenarios where multiple classes of”
Aggregate dynamics for dense crowd simulation (2009, methodology): “This observation has been exploited by previous work on continuum models for medium-density crowds [Hughes 2003; Treuille et al. 2006], and it has been noted that crowds at high density show behavior similar to granular ﬂows [Helbing et al. 2005].”
Pedestrian flows and non‐classical shocks (2005, methodology): “The study of models for pedestrian flows is receiving an increasing attention in the specialized literature, see [12, 13, 14, 15, 16, 23, 24].”
On the Modeling of Traffic and Crowds: A Survey of Models, Speculations, and Perspectives (2011, background): “The generalization is immediate as both equations can be written in two space dimensions (see Hughes [123], [124]) as   ∂tρ+∇x · (ρ ξ) = 0 ,”
Specification of the Social Force Pedestrian Model by Evolutionary Adjustment to Video Tracking Data (2007, background): “[23, 25]) and uid-dynamic models [6, 16, 17 ] have facilitated insights into the large-scale dynamics of pedestrian crowds, in particular into the phenomon of intermittent ows and stop-and-go trac emerging at extreme densities [11].”