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Roads are a shared resource which can be used either by drivers and autonomous vehicles. Since the total number of vehicles increases annually, each considered vehicle spends more time in traffic jams, and thus the total travel time prolongs. The main purpose while planning the road system is to reduce the time spent on traveling. The optimization of transportation networks is a current goal, thus the formation of traffic flows by creating certain ligaments of the roads is of high importance. The Braess paradox states the existence of a network where the construction of a new edge leads to the increase of traveling time. The objective of this paper is to propose various solutions to the Braess paradox in the presence of autonomous vehicles. One of the methods of solving transportation topology problems is to introduce artificial restrictions on traffic. As an example of such restrictions, this article considers designated lanes which are available only for a certain type of vehicles. Designated lanes have their own location in the network and operating conditions. This article observes the most common two-roads traffic situations, analyzes them using analytical and numerical methods and presents the model of optimal traffic flow distribution, which considers different ways of lanes designation on isolated transportation networks. It was found that the modeling of designated lanes eliminates Braess’ paradox and optimizes the total traveling time. The solutions were shown on artificial networks and on the real-life example. A modeling algorithm for Braess network was proposed and its correctness was verified using the real-life example.

The present article describes the authors’ model of construction of the distributed computer network and realization in it of the distributed calculations which are carried out within the limits of the software-information environment providing management of the information, automated and engineering systems of intellectual buildings. The presented model is based on the functional approach with encapsulation of the non-determined calculations and various side effects in monadic calculations that allows to apply all advantages of functional programming to a choice and execution of scenarios of management of various aspects of life activity of buildings and constructions. Besides, the described model can be used together with process of intellectualization of technical and sociotechnical systems for increase of level of independence of decision-making on management of values of parameters of the internal environment of a building, and also for realization of methods of adaptive management, in particular application of various techniques and approaches of an artificial intellect. An important part of the model is a directed acyclic graph, which is an extension of the blockchain with the ability to categorically reduce the cost of transactions taking into account the execution of smart contracts. According to the authors it will allow one to realize new technologies and methods — the distributed register on the basis of the directed acyclic graph, calculation on edge and the hybrid scheme of construction of artificial intellectual systems — and all this together can be used for increase of efficiency of management of intellectual buildings. Actuality of the presented model is based on necessity and importance of translation of processes of management of life cycle of buildings and constructions in paradigm of Industry 4.0 and application for management of methods of an artificial intellect with universal introduction of independent artificial cognitive agents. Model novelty follows from cumulative consideration of the distributed calculations within the limits of the functional approach and hybrid paradigm of construction of artificial intellectual agents for management of intellectual buildings. The work is theoretical. The article will be interesting to scientists and engineers working in the field of automation of technological and industrial processes both within the limits of intellectual buildings, and concerning management of complex technical and social and technical systems as a whole.

Simulation multiagent model of artificial life was created. Competitive ad-vantages of directed movement and diverse strategies of its using in population of protozoa in illumination gradient were considered. The results consistent with r-K selection theory were obtained. Agents behavior in artificial ecosystem are in qualitative agreement with behavior observed in nature.

Course “Natural models of parallel computing”, given for senior students of the Faculty of Computational Mathematics and Cybernetics, Moscow State University, is devoted to the issues of supercomputer implementation of natural computational models and is, in fact, an introduction to the theory of natural computing, a relatively new branch of science, formed at the intersection of mathematics, computer science and natural sciences (especially biology). Topics of the natural computing include both already classic subjects such as cellular automata, and relatively new, introduced in the last 10–20 years, such as swarm intelligence. Despite its biological origin, all these models are widely applied in the fields related to computer data processing. Research in the field of natural computing is closely related to issues and technology of parallel computing. Presentation of theoretical material of the course is accompanied by a consideration of the possible schemes for parallel computing, in the practical part of the course it is supposed to perform by the students a software implementation using MPI technology and numerical experiments to investigate the effectiveness of the chosen schemes of parallel computing.