An important quality of technical systems that allows them to be classified as intelligent is the presence of such properties as:

■ learnability – the ability to generate new knowledge and data (models, decision rules) based on inductive inference mechanisms, generalization of statistical data, etc.;

■ classification ability – the ability of the system to independently differentiate control objects, environmental influences, control signals, automatically structure data;

■ adaptation – the ability of the system to adapt to the changing conditions of the operating environment, correctly take into account the non-stationarity of control data, etc

One of the promising approaches to the creation of intelligent systems may be to attract the ideas of situational management as a system – wide approach based on formal methods of theoretical artificial intelligence – logical-linguistic models, models of learning technical systems in the construction of management procedures for current situations, deductive systems for building multistep solutions, etc. In this important area of research, as well as in the development of general methodology, theoretical foundations and specific applications, priority undoubtedly belongs to Russian scientists.

The problem of industrial implementation of intelligent information systems capable of processing data with their inherent a priori uncertainty in railway transport is becoming more and more urgent. In many cases, the data is not only inaccurate and uncertain, but also incomplete, and sometimes unreliable. The development of methods that allow obtaining reliable conclusions based on such data is another direction for fundamental research.

Currently, the development of various automated control systems in railway transport is increasingly taking place in the direction of their intellectualization. As a rule, intelligent railway systems are created to control individual processes.

World experience shows that the greatest effect is achieved when developing and implementing an integrated interconnected complex of intelligent systems. In this case, a unified information support is created, the mutual influence of managed processes is taken into account.

General integration principles

An illustrative example of the need to create an integrated complex of intelligent systems is the existing network (TCC) and regional (RTCC) automated dispatch control centers. There are dozens of automated workstations (AWSs) in various areas of organization of the transportation process, maintenance and repair of infrastructure and rolling stock devices, as well as security. Each AWS as a human-machine system performs a specific target function. However, a full-fledged interconnection of these functions can be carried out only with the integrated construction of a complex of intelligent dispatch systems. In principle, we can talk about a unified intelligent system in automated dispatch control centers. Let’s consider this provision in relation to regional (road) control centers – RTCC.

In each RTCC, a hierarchical dispatching structure solves tasks of three main types:

1) ensuring loading in accordance with the daily and current loading plans;

2) ensuring the passage of trains (including those performing local work) in accordance with the traffic schedule, the formation plan and the plan for the transfer of wagons along internal and external joints with unconditional compliance with traffic safety;