MODELING OF SOCIAL INTERACTIONS BASED ON GRAPH APPROACHES

The article describes the results of the development and implementation of the intelligent controlsystem of the «Lastochka» unmanned train on the Moscow Central Ring. The peculiarity of the unmannedcontrol system for railway transport is: relatively high speed and large mass of trains, which determine along braking distance. It is necessary to solve the problem of accurate determination of the distance to theobstacle, its identification and determination of the exact location of the train on the track. This task canbe solved by an intelligent decision-making system based on the integration of vision and high-precisionpositioning systems. The main element of the control system is a specialised computer using artificial intelligencetechnologies. To recognise and identify obstacles, the control system uses an artificial neuralnetwork, which is part of the computer software. Technical vision operates in four ranges of electromagneticwaves. The vision system can be considered as an information-measuring system that performs inputand processing of information without human participation. The structure of the integrated vision system,which includes on-board, infrastructure and mobile systems, is presented. The experiment has shown thatthe vision system reacts faster than a human on average by 14 seconds. The composition of the equipmentof the integrated high-precision positioning system is proposed, which in addition to global navigationsatellite system, platform-free inertial system and odometers, includes a digital track model. The model isthe source of the exact location of the reference infrastructure objects, relative to which the positioning ofthe transportation object with high accuracy is determined and the basis for zeroing the increasing errorof measurements of the inertial navigation system and odometer. The results of practical implementationof the intelligent control system on the Moscow Central Circle are described.