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October 12, 2026
Road Injuries Leading Cause of Death Among Men Aged 10 to 39
Worldwide, road injuries are the leading cause of death among males aged 10–39. An international team of researchers reached this conclusion as part of the Global Burden of Disease Study 2023, analysing data from 204 countries between 1990 and 2023. Their findings have been published in The Lancet Public Health, with HSE University Professor Vasily Vlassov listed among the collaborators.
October 8, 2026
HSE Experts Take Part in 23rd Annual Meeting of Valdai Discussion Club
The 23rd Annual Meeting of the Valdai Discussion Club was held from September 28 to October 1, 2026 under the theme ‘Responsibility for the Future: Limits of the Possible, or Limitless Possibilities?’ The forum brought together 120 experts from 40 countries, including representatives of China, the United States, India, Brazil, the United Kingdom, Germany, Egypt, Iran, and Japan.
October 7, 2026
‘Our Team Consists of True Leaders in Their Respective Academic Disciplines
The HSE International Centre of Decision Choice and Analysis studies a wide range of methods for analysing decision-making and possible scenarios for the development of natural, socio-economic, and political phenomena using various mathematical models. The application of advanced mathematical methods to forecasting helps to prevent negative outcomes and avoid erroneous decisions. The HSE News Service spoke to the centre’s director, Prof. Fuad Aleskerov, about its work.

 

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Сценарное моделирование движения беспилотных транспортных средств в искусственной дорожной сети с использованием FLAME GPU

Искусственные общества. 2021. Т. 16. № 1. С. 1–23.
Akopov A. S., Beklaryan A.

This article presents a model of the ground autonomous vehicles (AVs) motion in the Artificial Road Network (ARN) belonging to the "Manhattan Lattice" type with the implementation of the large-scale agent-based modeling framework FLAME GPU. The most important scenarios of the traffic situation development are investigated, in particular, which are associated with reducing visibility on the roads, especially in conditions of unusual behaviour of some agents of the traffic system, e.g. the unexpected appearance of obstacles such as agent-pedestrians and chaotic maneuvering of usual (i.e. manned) vehicles (MVs) having abnormal characteristics. A new approach to designing large-scale agent-based transportation simulations based on ARNs with a complex configuration and implementation using supercomputer technologies is proposed.

Research target: Computer Science Mathematics
Language: Russian
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Keywords: агентное моделированиебеспилотные транспортные средстваAutonomous vehiclesagent-based modellingFLAME GPUartificial transport systemsFLAME GPUискусственные транспортные системы
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