Pedestrians moving in dark: Balancing measures and playing games on lattices

We present two conceptually new modeling approaches aimed at describing the motion of pedestrians in obscured corridors: * a Becker-D\"{o}ring-type dynamics * a probabilistic cellular automaton model. In both models the group formation is affected by a threshold. The pedestrians are supposed to have very limited knowledge about their current position and their neighborhood; they can form groups up to a certain size and they can leave them. Their main goal is to find the exit of the corridor. Although being of mathematically different character, the discussion of both models shows that it seems to be a disadvantage for the individual to adhere to larger groups. We illustrate this effect numerically by solving both model systems. Finally we list some of our main open questions and conjectures

Mean-Field-Type Games in Engineering

A mean-field-type game is a game in which the instantaneous payoffs and/or the state dynamics functions involve not only the state and the action profile but also the joint distributions of state-action pairs. This article presents some engineering applications of mean-field-type games including road traffic networks, multi-level building evacuation, millimeter wave wireless communications, distributed power networks, virus spread over networks, virtual machine resource management in cloud networks, synchronization of oscillators, energy-efficient buildings, online meeting and mobile crowdsensing.Comment: 84 pages, 24 figures, 183 references. to appear in AIMS 201

Modelling the behavior of human crowds as coupled active-passive dynamics of interacting particle systems

The modelling of human crowd behaviors offers many challenging questions to science in general. Specifically, the social human behavior consists of many physiological and psychological processes which are still largely unknown. To model reliably such human crowd systems with complex social interactions, stochastic tools play an important role for the setting of mathematical formulations of the problems. In this work, using the description based on an exclusion principle, we study a statistical-mechanics-based lattice gas model for active-passive population dynamics with an application to human crowd behaviors. We provide representative numerical examples for the evacuation dynamics of human crowds, where the main focus in our considerations is given to an interacting particle system of active and passive human groups. Furthermore, our numerical results show that the communication between active and passive humans strongly influences the evacuation time of the whole population even when the "faster-is-slower" phenomenon is taken into account. To provide an additional inside into the problem, a stationary state of our model is analyzed via current representations and heat map techniques. Finally, future extensions of the proposed models are discussed in the context of coupled data-driven modelling of human crowds and traffic flows, vital for the design strategies in developing intelligent transportation systems.Comment: 12 figures, 23 page

Towards a Mathematical Theory of Behavioral Human Crowds

Nicola Bellomo acknowledges the support of the University of Granada, Project Modeling in Nature MNat from micro to macro, https://www.modelingnature.org.This paper has been partially supported by the MINECO-Feder (Spain) research Grant Number RTI2018-098850-B-I00, the Junta de Andalucia (Spain) Project PY18-RT-2422, A-FQM-311-UGR18, and B-FQM-580-UGR20. Livio Gibelli, gratefully acknowledges the financial support of the Engineering and Physical Sciences Research Council (EPSRC) Under Grants EP/N016602/1, EP/R007438/1. Annalisa Quaini acknowledges support from the Radcliffe Institute for Advanced Study at Harvard University where she has been a 2021-2022 William and Flora Hewlett Foundation Fellow. Alessandro Reali acknowledges the partial support of the MIUR-PRIN Project XFAST-SIMS (No. 20173C478N).The first part of our paper presents a general survey on the modeling, analytic problems, and applications of the dynamics of human crowds, where the specific features of living systems are taken into account in the modeling approach. This critical analysis leads to the second part which is devoted to research perspectives on modeling, analytic problems, multiscale topics which are followed by hints towards possible achievements. Perspectives include the modeling of social dynamics, multiscale problems and a detailed study of the link between crowds and swarms modeling.University of Granada, Project Modeling in Nature MNat from micro to macroSpanish Government RTI2018-098850-B-I00Junta de AndaluciaEuropean Commission PY18-RT-2422 A-FQM-311-UGR18 B-FQM-580-UGR20UK Research & Innovation (UKRI)Engineering & Physical Sciences Research Council (EPSRC) EP/N016602/1 EP/R007438/1Radcliffe Institute for Advanced Study at Harvard UniversityMinistry of Education, Universities and Research (MIUR) 20173C478

Modeling, Evaluation, and Scale on Artificial Pedestrians: A Literature Review

Modeling pedestrian dynamics and their implementation in a computer are challenging and important issues in the knowledge areas of transportation and computer simulation. The aim of this article is to provide a bibliographic outlook so that the reader may have quick access to the most relevant works related to this problem. We have used three main axes to organize the article's contents: pedestrian models, validation techniques, and multiscale approaches. The backbone of this work is the classification of existing pedestrian models; we have organized the works in the literature under five categories, according to the techniques used for implementing the operational level in each pedestrian model. Then the main existing validation methods, oriented to evaluate the behavioral quality of the simulation systems, are reviewed. Furthermore, we review the key issues that arise when facing multiscale pedestrian modeling, where we first focus on the behavioral scale (combinations of micro and macro pedestrian models) and second on the scale size (from individuals to crowds). The article begins by introducing the main characteristics of walking dynamics and its analysis tools and concludes with a discussion about the contributions that different knowledge fields can make in the near future to this exciting area

Modeling Family Behaviors in Crowd Simulation

Modeling human behavior for a general situation is difficult, if not impossible. Crowd simulation represents one of the approaches most commonly used to model such behavior. It is mainly concerned with modeling the different human structures incorporated in a crowd. These structures could comprise individuals, groups, friends, and families. Various instances of these structures and their corresponding behaviors are modeled to predict crowd responses under certain circumstances and to subsequently improve event management, facility and emergency planning. Most currently existing modeled behaviors are concerned with depicting individuals as autonomous agents or groups of agents in certain environments. This research focuses on providing structural and state-based behavioral models for the concept of a family incorporated in the crowd. The structural model defines parents, teenagers, children, and elderly as members of the family. It also draws on the associated interrelationships and the rules that govern them. The behavioral model of the family encompasses a number of behavioral models associated with the triggering of certain well-known activities that correspond to the family’s situation. For instance, in normal cases, a family member(s) may be hungry, bored, or tired, may need a restroom, etc. In an emergency case, a family may experience the loss of a family member(s), the need to assist in safe evacuation, etc. Activities that such cases trigger include splitting, joining, carrying children, looking for family member(s), or waiting for them. The proposed family model is implemented on top of the RVO2 library that is using agent-based approach in crowd simulation. Simulation case studies are developed to answer research questions related to various family evacuation approaches in emergency situations

Common Crowd Dynamics: Shaping Behavioral Intention Models

As the human population grows, so too does the need to understand human behavior. One particularly important aspect of human behavior is how it changes within conglomerations of people, i.e. crowds. In this thesis, a method for modeling crowd behavior is proposed. This method draws inspiration from the concept of behavioral intention and the related forces of attitudes, influences, and social norms. These topics are first defined and detailed, followed by a survey of related research. Next, the model is presented and adapted to three common crowd dynamics, each stressing a different component of behavioral intention. Observations are made about these models, and extensions to the models and directions for future research are considered

Noblesse Oblige? Determinants of Survival in a Life and Death Situation

This paper explored the determinants of survival in a life and death situation created by an external and unpredictable shock. We are interested to see whether pro-social behaviour matters in such extreme situations. We therefore focus on the sinking of the RMS Titanic as a quasi-natural experiment do provide behavioural evidence which is rare in such a controlled and life threatening event. The empirical results support that social norm such as “women and children first” survive in such an environment. We also observe that women of reproductive age have a higher probability of surviving among women. On the other hand, we observe that crew members used their information advantage and their better access to resources (e.g. lifeboats) to generate a higher probability of surviving. The paper also finds that passenger class, fitness, group size, and cultural background matter.decision under pressure, altruism, social norms, interdependent preferences, excess of demand