VIRTUAL REALITY FOR MANAGEMENT OF SITUATIONAL AWARENESS DURING GLOBAL MASS GATHERINGS

This paper presents a training technology for staff of mass events for development of action skills in large gatherings of people, including crowd dynamic management and actions in extreme situations caused by the panic. The technology is based on the multi-agent model of crowd dynamic with dynamically re-computable navigation fields. We implemented the software system that provides a collaborative and distributed process of training activities in the virtual reality environment. The following characteristics of the developed software system available from experimental studies were analyzed: computational intensity of simulations, scalability of rendering system and reactivity of the final system when rendering computationally intensive scenes. The proposed models and infrastructure for training through collaborative immersion in the virtual reality can improve situational awareness of events staff prior to the event. The developed technology is a unique tool for improving the quality and safety of disposable and unique events involving the broad masses of people, including unfunded by retrospective experience mass gatherings. Developed technology was tested within the Kumbh Mela festival in Ujjain, India

Geospatial data analysis in Russia’s geoweb

The chapter examines the role of geospatial data in Russia’s online ecosystem. Facilitated by the rise of geographic information systems and user-generated content, the distribution of geospatial data has blurred the line between physical spaces and their virtual representations. The chapter discusses different sources of these data available for Digital Russian Studies (e.g., social data and crowdsourced databases) together with the novel techniques for extracting geolocation from various data formats (e.g., textual documents and images). It also scrutinizes different ways of using these data, varying from mapping the spatial distribution of social and political phenomena to investigating the use of geotag data for cultural practices’ digitization to exploring the use of geoweb for narrating individual and collective identities online

Simulating an Impact of Road Network Improvements on the Performance of Transportation Systems under Critical Load: Agent-based Approach

In this paper, we analyze the impact of planned road network development on the dynamics of the automobile transportation system during the departure of visitors after the semifinal match of the 2018 FIFA World Cup, which will take place in the newly built stadium on Krestovsky Island. To perform such an analysis, we utilize an agent-based traffic flow simulation, which requires the construction of several models. This paper covers the following progress: (1) modeling the road network in Saint Petersburg, Russia (2) a population synthesis based on data provided by the Russian Federal Migration Service (FMS) (3) a comparative analysis of the simulated system behavior using the current and improved road network and (4) a sustainability analysis of the transportation system of the studied area. We estimate the impact of road improvements on traffic flow by simulating various scenarios and determining changes in distribution of agents travel time and load redistribution among exits from the area of interest. This paper is part of the project which aims to develop a large-scale agent-based traffic flow model of Saint Petersburg urban area applicable for a wide range of research tasks from transportation planning to disaster management