Optimizing evacuation flow in a two-channel exclusion process

We use a basic setup of two coupled exclusion processes to model a stylised situation in evacuation dynamics, in which evacuees have to choose between two escape routes. The coupling between the two processes occurs through one common point at which particles are injected, the process can be controlled by directing incoming individuals into either of the two escape routes. Based on a mean-field approach we determine the phase behaviour of the model, and analytically compute optimal control strategies, maximising the total current through the system. Results are confirmed by numerical simulations. We also show that dynamic intervention, exploiting fluctuations about the mean-field stationary state, can lead to a further increase in total current.Comment: 16 pages, 6 figure

Evakuointitilanteissa olevien riskisten agenttien kuvaileminen spatiaalipelillä

Threat to survival launches a primitive fight-or-flight reaction both in animals and humans. Both individual actions and the actions of others affect an individual's survival when escaping as a part of a crowd. Human characteristics play a big role in decision making under evacuation circumstances. Attitudes towards risks make some people try their luck, and some others to act as carefully as possible. An individual's view of the seriousness of a threat in the current situation can be modeled bu using a personal cost function. The shape of the cost function determines whether one is more risk-averse or risk-taking. This thesis seeks to find out how crowd egress flow is affected when evacuees' cost functions differ from each other. Previous studies have treated evacuees as homogenous individuals who all have the same cost function. Evolutionary game theory serves as the decision making framework for this study. Classical Hawk-Dove game can be used to model human behavior alternatives, e.g., an individual to play Impatient or Patient under an evacuation situation. This individual's behavior can be observed by the other evacuees, who react to this behavior according to their own cost functions. The study in this thesis is limited to two different types of evacuees: risk-averse and risk-taking. The model developed will reveal new kinds of phenomena that do not occur when all evacuees are considered homogenous. For example, mixing the two types of evacuees in the same crowd will cause a formation of a certain area in the middle of the crowd where all the risk-averse evacuees take the action Patient, and all the risk-taking evacuees take the action Impatient.Uhka selviytymiselle laukaisee alkukantaisen taistele tai pakene -reaktion sekä eläimissä että ihmisissä. Sekä yksilölliset että muiden tekemät toimet vaikuttavat yksilön selviytymiseen paettaessa osana väkijoukkoa. Ihmisten luonteenpiirteillä on merkittävä osa päätöksenteossa evakuointitilanteissa. Asenteet riskejä kohtaan saavat toiset kokeilemaan onneaan ja toiset toimimaan niin varovaisesti kuin mahdollista. Yksilön näkemystä uhan vakavuudesta nykyisessä tilanteessa voidaan mallintaa henkilökohtaisella kustannusfunktiolla. Kustannusfunktion muoto määrittää onko yksilö riskiä karttava vai riskihakuinen. Tämä diplomityö pyrkii selvittämään kuinka väkijoukon ulosvirtaukseen vaikuttaa evakuoitavien toisistaan poikkeavat kustannusfunktiot. Edelliset tutkimukset ovat ajatelleet evakuoitavia homogeenisina yksilöinä, joilla on kaikilla sama kustannusfunktio. Tässä tutkimuksessa käytetään evoluutiopeliteoriaa pelaajien, tai agenttien, toiminnan ennustamiseen. Esimerkiksi klassisen Haukka-Kyyhky-pelin toimintavaihtoehdot ovat "Kärsimätön" ja "Kärsivällinen" evakuointitilanteissa. Muut havaitsevat yksilön käyttäytymisen ja reagoivat tähän oman kustannusfunktionsa mukaisesti. Tässä diplomityössä tutkimus on rajoitettu kahdentyyppisiin evakuoitaviin: riskiä karttaviin ja riskihakuisiin. Kehitetyllä mallilla tehdyt simuloinnit tuottavat uudenlaisia ilmiöitä, joita ei tapahdu saman tyyppisten agenttien tapauksessa. Esimerkiksi kahta eri tyyppiä olevien agenttien sekoittaminen samaan agenttijoukkoon muodostaa joukon keskelle tietyn alueen, jossa kaikki riskiä karttavat evakuoitavat käyttäytyvät kärsivällisesti ja kaikki riskihakuiset evakuoitavat käyttäytyvät kärsimättömästi

Cellular Automata Applications in Shortest Path Problem

Cellular Automata (CAs) are computational models that can capture the essential features of systems in which global behavior emerges from the collective effect of simple components, which interact locally. During the last decades, CAs have been extensively used for mimicking several natural processes and systems to find fine solutions in many complex hard to solve computer science and engineering problems. Among them, the shortest path problem is one of the most pronounced and highly studied problems that scientists have been trying to tackle by using a plethora of methodologies and even unconventional approaches. The proposed solutions are mainly justified by their ability to provide a correct solution in a better time complexity than the renowned Dijkstra's algorithm. Although there is a wide variety regarding the algorithmic complexity of the algorithms suggested, spanning from simplistic graph traversal algorithms to complex nature inspired and bio-mimicking algorithms, in this chapter we focus on the successful application of CAs to shortest path problem as found in various diverse disciplines like computer science, swarm robotics, computer networks, decision science and biomimicking of biological organisms' behaviour. In particular, an introduction on the first CA-based algorithm tackling the shortest path problem is provided in detail. After the short presentation of shortest path algorithms arriving from the relaxization of the CAs principles, the application of the CA-based shortest path definition on the coordinated motion of swarm robotics is also introduced. Moreover, the CA based application of shortest path finding in computer networks is presented in brief. Finally, a CA that models exactly the behavior of a biological organism, namely the Physarum's behavior, finding the minimum-length path between two points in a labyrinth is given.Comment: To appear in the book: Adamatzky, A (Ed.) Shortest path solvers. From software to wetware. Springer, 201

A Semi-Lagrangian scheme for a modified version of the Hughes model for pedestrian flow

In this paper we present a Semi-Lagrangian scheme for a regularized version of the Hughes model for pedestrian flow. Hughes originally proposed a coupled nonlinear PDE system describing the evolution of a large pedestrian group trying to exit a domain as fast as possible. The original model corresponds to a system of a conservation law for the pedestrian density and an Eikonal equation to determine the weighted distance to the exit. We consider this model in presence of small diffusion and discuss the numerical analysis of the proposed Semi-Lagrangian scheme. Furthermore we illustrate the effect of small diffusion on the exit time with various numerical experiments

Modeling Helping Behavior in Emergency Evacuations Using Volunteer's Dilemma Game

People often help others who are in trouble, especially in emergency evacuation situations. For instance, during the 2005 London bombings, it was reported that evacuees helped injured persons to escape the place of danger. In terms of game theory, it can be understood that such helping behavior provides a collective good while it is a costly behavior because the volunteers spend extra time to assist the injured persons in case of emergency evacuations. In order to study the collective effects of helping behavior in emergency evacuations, we have performed numerical simulations of helping behavior among evacuees in a room evacuation scenario. Our simulation model is based on the volunteer's dilemma game reflecting volunteering cost. The game theoretic model is coupled with a social force model to understand the relationship between the spatial and social dynamics of evacuation scenarios. By systematically changing the cost parameter of helping behavior, we observed different patterns of collective helping behaviors and these collective patterns are summarized with a phase diagram.Comment: International Conference on Computational Science (ICCS) 2020 Conference Pape

Uncertainty in a spatial evacuation model

Pedestrian movements in crowd motion can be perceived in terms of agents who basically exhibit patient or impatient behavior. We model crowd motion subject to exit congestion under uncertainty conditions in a continuous space and compare the proposed model via simulations with the classical social force model. During a typical emergency evacuation scenario, agents might not be able to perceive with certainty the strategies of opponents (other agents) owing to the dynamic changes entailed by the neighborhood of opponents. In such uncertain scenarios, agents will try to update their strategy based on their own rules or their intrinsic behavior. We study risk seeking, risk averse and risk neutral behaviors of such agents via certain game theory notions. We found that risk averse agents tend to achieve faster evacuation time whenever the time delay in conflicts appears to be longer. The results of our simulations also comply with previous work and conform to the fact that evacuation time of agents becomes shorter once mutual cooperation among agents is achieved. Although the impatient strategy appears to be the rational strategy that might lead to faster evacuation times, our study scientifically shows that the more the agents are impatient, the slower is the egress time