Macroscopic crowd dynamics refers to the study and modeling of large groups of pedestrians as a continuous medium rather than as collections of discrete individuals, typically employing fluid-like continuum formulations in which aggregate quantities such as crowd density, flow velocity, and flux evolve according to coupled partial differential equations over space and time. This perspective matters for WiFi and CSI-based sensing research because it provides principled theoretical frameworks for interpreting spatially distributed signal perturbations as indicators of crowd density and movement patterns, enabling crowd analytics without individual tracking. Key variants include Eulerian continuum models such as Hughes' dynamic continuum model, which couples a density-dependent speed function with an eikonal equation governing pedestrian navigation decisions, as well as extensions that incorporate anisotropic flow, multiple crowd streams, or computational reformulations designed for efficient numerical solution in complex two-dimensional environments.
Source Papers
- A continuum theory for the flow of pedestrians ↗ — A continuum theory for the flow of pedestrians
- A high-resolution meshfree particle method for numerical investigation of second-order macroscopic pedestrian flow models ↗ — A high-resolution meshfree particle method for numerical inv
- Continuum theory for pedestrian traffic flow: Local route choice modelling and its implications ↗ — Continuum theory for pedestrian traffic flow: Local route ch
- Physics of Human Crowds ↗ — Physics of Human Crowds
- Revisiting Hughes’ dynamic continuum model for pedestrian flow and the development of an efficient solution algorithm ↗ — Revisiting Hughes’ dynamic continuum model for pedestrian fl
- State-of-the-art crowd motion simulation models ↗ — State-of-the-art crowd motion simulation models