Vladislav A. Karbovskii

Personal Decision Support Mobile Service for Extreme Situations

Abstract This article discusses aspects of implementation of a massive personal decision support mobile service for evacuation process in extreme situations, based on cloud computation platform CLAVIRE and a virtual society model. The virtual society model was constructed using an agent-based approach. To increase credibility the individual motivation methods (personal decision support and user training) were used.

Multiscale Agent-based Simulation in Large City Areas: Emergency Evacuation use Case☆

Abstract Complex phenomena are increasingly attracting the interest of researchers from various branches of computational science. So far, this interest has conditioned the demand not only for more sophisticated autonomous models, but also for mechanisms that would bringthem together. This paper presents a multiscale agent-based modeling and simulation technique based on the incorporation of multiple modules. Two key principles are presented as guiding such an integration: common abstract space as a space, where entities of different models interact, and commonly controlled agents – abstract actors operating in a common space, which can be handled by different agent-based models. The proposed approach is evaluated through a series of experiments simulating the emergency evacuation from acinema building to the city streets, where building and street levels are reproduced in heterogeneous models.

Multimodel agent-based simulation environment for mass-gatherings and pedestrian dynamics

Abstract The increasing interest in complex phenomena, especially in crowd and pedestrian dynamics, has conditioned the demand not only for more sophisticated autonomous models but also for mechanisms that would bring these models together. This paper presents a multimodel agent-based simulation technique based on the incorporation of multiple modules. Two key principles are presented to guide this integration: a common abstract space where entities of different models interact, and commonly controlled agents—abstract actors operating in the common space, which can be handled by different agent-based models. In order to test the proposed methodology, we run a set of simulations of cinema building evacuation using the general-purpose PULSE simulation environment. In this paper we utilize crowd pressure as a metric to estimate the capacity of different emergent conditions to traumatically affect pedestrians in the crowd. The proposed approach is evaluated through a series of experiments simulating the emergency evacuation from a cinema building to the city streets, where building and street levels are reproduced in heterogeneous models. This approach paves the way for modeling realistic city-wide evacuations.

The Framework for Rapid Graphics Application Development: The Multi-scale Problem Visualization☆

Abstract Interactive real-time visualization plays a significant role in simulation research domain. Multi-scale problems are in need of high performance visualization with good quality and the same could be said about other problem domains, e.g. big data analysis, physics simulation, etc. The state of the art shows that a universal tool for solving such problem is non-existent. Modern computer graphics requires enormous efforts to implement efficient algorithms on modern GPUs and GAPIs. In the first part of our paper we introduce a framework for rapid graphics application development and its extensions for multi-scale problem visualization. In the second part of the paper we provide a prototype of multi-scale problems solution in simulation and monitoring of high-precision agent movements starting from behavioral patterns in an airport and up to world-wide flight traffic. Finally we summarize our results and speculate about future investigations.

Agent-based Modelling Using Ensemble Approach with Spatial and Temporal Composition☆

Abstract Crowd behavior and its movement has been an actively studied domain during last three decades. There are microscopic models used for realistic simulation of crowds in different conditions. Such models reproduce pedestrian movement quite well, however, their efficiency can vary depending on the conditions of simulation. For instance, some models show realistic results in high density of pedestrians and vice versa in low density. This work describes an early study aimed at developing an approach to combine several microscopic models using an ensemble approach to overcome individual weaknesses of the models. Possible ways to build hybrid models, as well as the main classes of ensembles are described. A prior calibration procedure was implemented using the evolutionary approach to create an ensemble of the most suitable models using dynamical macro-parameters such as density and speed as the optimization objectives. Several trial experiments and comparisons with single models were carried out for selected types of hybridization.

Towards a Performance-realism Compromise in the Development of the Pedestrian Navigation Model

Abstract Despite the emergence of new approaches and increasingly powerful processing resources, there are cases in the domain of pedestrian modeling that require the maintenance of compromise between the computational performance and realism of the behavior of the simulated agents. Present paper seeks to address this issue through comparative computational experiments and visual validation of the simulations using the real-world data. Acquired results show that a reasonable compromise may be reached for in the multi-level navigation incorporating both route planning and collision avoidance.

Toolbox for Visual Explorative Analysis of Complex Temporal Multiscale Contact Networks Dynamics in Healthcare

Public healthcare can be cast as a complex systems and network analysis is one of the methodological approaches that are commonly used to study these types of systems. In this paper we describe a multiscale and multi-level interpretation of complex networks in public healthcare. Our contribution is to provide a toolbox for visualization and visual data-driven analysis of complex multiscale temporal contact networks that allows to simulate various dynamic processes using user-defined models. An example of explorative analysis of a dataset from real clinical data obtained from the Federal Almazov North-West Medical Research Centre in Saint Petersburg is described.

The Multi-agent Simulation-based Framework for Optimization of Detectors Layout in Public Crowded Places☆

Abstract In this work the framework for detectors layout optimization based on a multi-agent simulation is proposed. Its main intention is to provide a decision support team with a tool for automatic design of social threat detection systems for public crowded places. Containing a number of distributed detectors, this system performs detection and an identification of threat carriers. The generic model of detector used in the framework allows to consider detection of various types of threats, e.g. infections, explosives, drugs, radiation. The underlying agent-based models provide data on social mobility, which is used along with a probability based quality assessment model within the optimization process. The implemented multi-criteria optimization scheme is based on a genetic algorithm. For experimental study the framework has been applied in order to get the optimal detectors’ layout in Pulkovo airport.

The study of the influence of obstacles on crowd dynamics

This paper presents the research on the influence of obstacles on crowd dynamics. We have performed experiments for four base scenarios of interaction in crowd: unidirectional flow, bidirectional flow, merging flows and intersection. Movement of pedestrians has been studied in simple shape areas: straight corridor, T-junction and intersection. The volumes and basic directions of pedestrian flows were determined for each of the areas. Layout of physical obstacles has been built from different combinations of columns and barriers. In order to acquire characteristics of the crowd dynamics a set of simulations was conducted using PULSE simulation environment. In the result, we have managed to obtain several dependences between layout of obstacles and crowd dynamics were obtained.

Short-term Multiagent Simulation-based Prediction in Mass Gatherings Decision Support

Mass gatherings emerging both for specific occasions and spontaneously, are naturally associated with the risk of stampedes and crowd clashes that may trigger dramatic consequences in shorter or longer term perspectives. In order to address such issues the present paper suggests the application of the agent- based modeling approach to short-term predictions of future states of large congregates of people. The latter is of prime value for practitioners who seek to identify the potentially dangerous areas where the risk of stampede-induced injuries is assumed the highest based on the estimations of the crowd pressure at a given spot. In this paper, we outline the algorithm for generating forecasts and on its basis, propose a system of decision support. The test of system applicability has been performed based on the 2018 World Football Championship stadium use case. The object under investigation is expected to be put into operation in 2018.