Jaroslaw Was

Cellular automata model of pedestrian dynamics for normal and evacuation conditions

The knowledge of the issues connected with pedestrian can be very helpful in the proper desing of buildings or other facilities. A simulation should take into consideration both, normal as well as evacuation conditions. Over the recent years several models of pedestrian movement have been created. The first part of the article contains a brief review of some available models. Then, the author propose a model of pedestrians group dynamics in normal and evacuation situations. A 2D cellular automata, multi-agent model is created. The model proposed takes into account some strategic abilities of each agent/pedestrian. In the model, all decisions are made by an agent in correlation with other agents.

Experiments on Evacuation Dynamics for Different Classes of Situations

The article presents experiments on pedestrian evacuation in different situations. The presented experiments involved evacuation of a lecture room. A group of 31 students took part in four evacuation experiments. The experiments are devoted for three classes of situations: normal conditions, controlled evacuation (noncompetitive evacuation) and panic (competitive evacuation).

Some Criteria of Making Decisions in Pedestrian Evacuation Algorithms

The main goal of this paper is to introduce a model of intelligent behavior in pedestrian dynamics using cellular automata. Authors take into account classical situation of large room evacuation, where several exits are available. Presented model includes some criteria of making decisions by a particular pedestrian. Proposed criteria are: distance to all exits, density of crowd in each exit neighborhood, throughput of particular exit and following the other persons.

Discrete Modeling and Simulation [Guest editors' introduction]

This special issue of CiSE magazine deals with the application of discrete modeling and simulation tools to problems from different fields, including physics, engineering, environment science, social science, and life sciences. Many of the authors highlighted here examine the computing abilities and principles of discrete models with a focus on their expressive dynamics, their emergent computation, and their inherent parallelism, making them suitable for high-performance computing. Such models can also successfully tackle the computational bottleneck in terms of the complexity inherent in so many mesh-based and analytical numerical simulations.

An implementation of the Social Distances Model using multi-GPU systems

We propose a new approach for using GPUs in large scale simulations of pedestrian evacuation. The Social Distances Model is designed for efficient modeling of pedestrian dynamics. This cellular automata based model, when implemented on the most modern GPUs, can simulate up to 106–108 entities. However, a valuable simulation of pedestrian evacuation must include various factors that govern pedestrian movement, for example, information provided by event organizers and navigation or allocation of other pedestrians. The most common method for introducing such information into simulations is the application of different floor fields. The floor fields provide “local knowledge” that affects pedestrians by modifying the transition functions of an applied cellular automaton. The main disadvantage of this method is its time consuming updating process. We propose a GPU based calculation of static and dynamic floor fields, whereby simulations that use several different floor fields can be efficiently calculated. A single GPU is able to cope with the Social Distance Model calculations, while other GPUs update dynamic floor fields constantly or when required. We also present the classic approach to performing cellular automata based simulations on systems with multiple processing units. The lattice is simply partitioned between the available GPUs. We compare these two approaches in terms of performance and functionality.

A GPU Implemented 3F Cellular Automata-Based Model for a 2D Evacuation Simulation Pattern

This study presents the principles of a Cellular Automata (CA) based model that incorporates an enhanced version of the floor-field model targeting the fire spreading representation, thus called fire-floor-field (3F). The aim of the model is to simulate evacuation processes fast and reliably, in order to act as the core module of a near real-time effective anticipation system. To this direction, the model takes advantage of massive parallelism, an inherent feature of CA, by employing the efficient response of the floor field model and the accurate computational reproduction of fire-front evolution. Furthermore, a Graphic Processing Unit (GPU) based implementation of the proposed model is presented. Such a realisation aims at further speeding up the response of the model and it reinforces the fundamental goal of rapid activation. The model is validated quantitatively and qualitatively by being applied in the case of the two-dimensional (2D) simulated evacuation of the Building B, of the Department of Electrical and Computer Engineering, Democritus University of Thrace, under fire spreading conditions.