Gibelli / Bellomo Crowd Dynamics, Volume 5

From Human Complexity to Scientific Machine Learning
Erscheinungsjahr 2026
ISBN: 978-3-032-02221-9
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 219 Seiten

Reihe: Modeling and Simulation in Science, Engineering and Technology

This contributed volume explores innovative research in the modeling, simulation, and control of crowd dynamics. Chapter authors approach the topic from the perspectives of mathematics, physics, engineering, and psychology, providing a comprehensive overview of the work carried out in this challenging interdisciplinary research field.  

The volume begins by focusing on modeling at the macroscopic and microscopic scales, with chapters demonstrating how stress conditions evolve in time and space and influence pedestrian dynamics, particularly regarding high density patterns.  Different aspects of behavioral dynamics are considered in the following chapters, which explore how mathematical models can incorporate parameters that capture shifts in people’s mental states.  The final two chapters go beyond the usual modeling-based assumptions, discussing how control problems can be developed using drones to guide crowds and methods for interpreting crowd behavior using artificial intelligence, respectively.

is ideal for mathematicians, engineers, physicists, and other researchers working in the rapidly growing field of modeling and simulation of human crowds.

Zielgruppe

Research

Autoren/Hrsg.

Gibelli, Livio

Bellomo, Nicola

Inhaltsverzeichnis

Chapter 1. From the Complexity of Human Crowds to Research Perspectives.- Chapter 2. Exploring Dense Crowd Dynamics: State of the Art and Emerging Paradigms.- Chapter 3. Macroscopic modeling of crowd evacuation under stress: comparing first-order and second-order models.- Chapter 4. On mathematical modeling of social crowds.- Chapter 5. Evacuation movement and behaviour of preschool children.- Chapter 6. Surveillance-guidance of crowds via Lagrangian controls.- Chapter 7. Recent Deep Learning in Crowd Behaviour Analysis: A Brief Review.

Über Autor(innen)

Livio Gibelli is a Senior Lecturer in Mechanical Engineering at the University of Edinburgh. He received a Ph.D. in Applied Mathematics from the Politecnico di Milano. Before joining Edinburgh in 2018, he held research positions at the University of Warwick, the Politecnico di Milano, the Politecnico di Torino, and the University of British Columbia. His research focuses on the mesoscopic modelling of crowds, non-equilibrium multiphase flows, and numerical methods for kinetic equations. He has authored over 50 peer-reviewed publications and edited four previous volumes on crowd dynamics.

Nicola Bellomo is a distinguished professor at the University of Granada and a professor emeritus at the Polytechnic University of Torino. He started his career in 1980 when he was called to cover the chair of mathematical physics and applied mathematics due to his scientific achievements on the mathematical theory of the Boltzmann equation and of stochastic differential equations. Subsequently, he moved his scientific interests to the study of living systems, becoming one of the pioneers of the development of active particles methods to the modeling of large systems of self-propelled interacting entities. He is the author of two books published by Birkhaüser devoted to this topic. Nicola delivered, in 2009, the prestigious Shank Lecture at the Vanderbilt University on the modeling of immune competition. He was awarded the “Third Level of Honor” for scientific merits by the President of the Italian Republic.