A RUDN Mathematician Calculated Parameters for Optimal Crowd and Traffic Control
The majority of physical processes can be described using differential equations. To do so, an unknown quantity (e.g. temperature or velocity) is presented as a function. A differential equation may be written for such a function, and its solution will describe the behavior of the unknown quantity. However, in some cases writing a differential equation is impossible, and mathematicians have to use so-called differential containments - equations in which the equality sign is replaced with the sign of containment or inclusion. A RUDN mathematician developed a comprehensive solution for a group of differential containments and showed its possible applications in city management cases.
Optimal control problems are covered by a special theory in mathematics. The idea of such problems lies in developing (quantitatively or theoretically) a control law that would bring a system to a certain given state in the most efficient way. Imagine a car that is approaching traffic lights. When the distance between them is 250 meters, the green light turns on and remains for 30 seconds. One has to calculate how the car should move to reduce its energy consumption to the minimum. At first this may appear as a problem for school children, but not that both acceleration and slowdown consume the fuel. Therefore, such a problem lies in the scope of the optimal control theory and can be solved using a differential containment.
Using the differential containment in question, one can describe the movement of a crowd. Imagine there are a lot of people in a room, and each of them needs to leave it as quickly as possible. However, there is only one exit. The results obtained by the mathematicians will help calculate the trajectory and speed of movement for each particular person.
The results of the study may be practically applied to the calculation of optimal routes for robotic cars. Another possible area of application is multi-agent robotic systems, i.e. systems of several AI robots working on the same task, such as sorting or transportation of goods. Several robots of this kind form a crowd, and for their work to be efficient, optimal speeds and trajectories should be calculated for each of them.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.
Imagine a world where everyone has enough food, clean water, access to education, and decent work. A world where nature is protected and the future of our planet is cared for. These are the Sustainable Development Goals—to achieve a sustainable future for all! To this end, in 2015, the United Nations (UN) defined 17 Sustainable Development Goals (SDGs). The SDGs are a global plan that helps countries and people work together towards a better future. All 193 UN member states have joined the plan.
Researchers from the Faculty of Artificial Intelligence at RUDN University conducted a large-scale study that revealed systemic errors in large language models (LLMs) when diagnosing depression based on text. This work, carried out in collaboration with colleagues from AIRI, Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, Ivannikov Institute for System Programming of the Russian Academy of Sciences, Moscow Institute of Physics and Technology, and MBZUAI, not only identifies the problem but also lays the foundation for the creation of more reliable and secure tools for detecting depression and anxiety.
Alexandra Sentyabreva, a junior researcher at the Laboratory of Cell Technologies and Tissue Engineering at RUDN Research Institute of Molecular and Cellular Medicine at the Russian University of People's Friendship, won the competition for young scientists at the All-Russian Scientific Conference “Topical Issues of Morphogenesis in Norm and Pathology.” She was awarded the Academician A.P. Avtsyn Prize.