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Pedestrian crowds encompass a complex interplay of intentional movements aimed at reaching specific destinations, fluctuations due to personal and interpersonal variability, and interactions with each other and the environment. Previous…

Physics and Society · Physics 2025-03-10 Caspar A. S. Pouw , Geert G. M. van der Vleuten , Alessandro Corbetta , Federico Toschi

Currently, the safety of people has become a very important problem in different places including subway station, universities, colleges, airport, shopping mall and square, city squares. Therefore, considering intelligence event detection…

Computer Vision and Pattern Recognition · Computer Science 2020-08-11 Constantinou Miti , Demetriou Zatte , Siraj Sajid Gondal

Active particle systems of interacting self-propelled particles offer a versatile framework for modeling complex systems. When employed to describe aspects of animal behavior, the complexity of animal movement and decision-making often…

Biological Physics · Physics 2025-01-09 Amir Haluts , Dan Gorbonos , Nir S. Gov

In this paper, a simple 1D crowd model is proposed, which aim is to properly describe the crowd-flow phenomena occurring when pedestrians walk on a flexible footbridge. The crowd is assumed to behave like a continuous compressible fluid and…

Classical Physics · Physics 2009-01-13 Joanna Bodgi , Silvano Erlicher , Pierre Argoul

It is shown, that the Boltzmann-like equations allow the formulation of a very general model for behavioral changes. This model takes into account spontaneous (or externally induced) behavioral changes and behavioral changes by pair…

Statistical Mechanics · Physics 2009-10-31 Dirk Helbing

To better design safe and comfortable urban spaces, understanding the nature of human crowd movement is important. However, precise interactions among pedestrians are difficult to measure in the presence of their complex decision-making…

Learning to forecast trajectories of intelligent agents has caught much more attention recently. However, it remains a challenge to accurately account for agents' intentions and social behaviors when forecasting, and in particular, to…

Computer Vision and Pattern Recognition · Computer Science 2025-03-11 Conghao Wong , Ziqian Zou , Beihao Xia , Xinge You

In this paper, we present a computational modeling approach for the dynamics of human crowds, where the spreading of an emotion (specifically fear) has an influence on the pedestrians' behavior. Our approach is based on the methods of the…

Physics and Society · Physics 2021-02-19 Daewa Kim , Kaylie O'Connell , William Ott , Annalisa Quaini

Inspired by the works of Hughes [17, 18], we formalize and prove the well posedness of a hyperbolic--elliptic system whose solutions describe the dynamics of a moving crowd. The resulting model is here shown to be well posed and the time of…

Analysis of PDEs · Mathematics 2016-10-25 Rinaldo M. Colombo , Maria Gokieli , Massimiliano D. Rosini

People tend to walk in groups, and interactions with those groups have a significant impact on crowd behavior and pedestrian traffic dynamics. Social norms can be seen as unwritten rules regulating people interactions in social settings.…

Physics and Society · Physics 2025-10-31 Saleh Albeaik , Faisal Alsallum , Mohamad Alrished

Pedestrian trajectory prediction remains a challenge for autonomous systems, particularly due to the intricate dynamics of social interactions. Accurate forecasting requires a comprehensive understanding not only of each pedestrian's…

Computer Vision and Pattern Recognition · Computer Science 2024-12-09 Haleh Damirchi , Ali Etemad , Michael Greenspan

Generating accurate and efficient predictions for the motion of the humans present in the scene is key to the development of effective motion planning algorithms for robots moving in promiscuous areas, where wrong planning decisions could…

We propose in this paper a minimal speed-based pedestrian model for which particle dynamics are intrinsically collision-free. The speed model is an optimal velocity function depending on the agent length (i.e.\ particle diameter), maximum…

Physics and Society · Physics 2015-12-19 Antoine Tordeux , Mohcine Chraibi , Armin Seyfried

We use topological data analysis and machine learning to study a seminal model of collective motion in biology [D'Orsogna et al., Phys. Rev. Lett. 96 (2006)]. This model describes agents interacting nonlinearly via attractive-repulsive…

We investigate dynamics of deformable self-propelled particles with a repulsive interaction whose magnitude depends on the relative direction of elongation of a pair of particles. A collective motion of the particles appears in two…

Soft Condensed Matter · Physics 2015-05-27 Yu Itino , Takahiro Ohkuma , Takao Ohta

Interaction is so ubiquitous that imaging a world free from it is a difficult fantasy exercise. At the same time, in understanding any complex physical system, our ability of accounting for the mutual interaction of its constituents is…

Quantum Physics · Physics 2015-01-19 Roberto D'Agosta

We introduce a stochastic agent-based model for the flocking dynamics of self-propelled particles that exhibit velocity-alignment interactions with neighbours within their field of view. The stochasticity in the dynamics of the model arises…

Statistical Mechanics · Physics 2019-07-24 Trilochan Bagarti , Shakti N. Menon

A simple model to handle the flow of people in emergency evacuation situations is considered: at every point x, the velocity U(x) that individuals at x would like to realize is given. Yet, the incompressibility constraint prevents this…

Analysis of PDEs · Mathematics 2010-02-04 Bertrand Maury , Aude Roudneff-Chupin , Filippo Santambrogio

Increasing attention is being given to the modeling and simulation of traffic flow and crowd movement, two phenomena that both deal with interactions between pedestrians and cars in many situations. In particular, crowd simulation is…

Multiagent Systems · Computer Science 2019-12-10 Mingliang Xu , Chaochao Li , Pei Lv , Wei Chen , Zhigang Deng , Bing Zhou , Dinesh Manocha

Quantifying uncertainties in collective human behavior and decision making is crucial for ensuring public health and safety, enabling effective disaster response, informing the design of transportation and communication networks, and…

Physics and Society · Physics 2016-12-02 Kimberly J. Schlesinger , Chantal Nguyen , Imtiaz Ali , Jean M. Carlson
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