An Intelligent Algorithm for Automated Control of Railway-Crossing Signaling

• Published in: Russian electrical engineering Vol. 94; no. 10; pp. 726 - 731
• Main Authors: Tretyakov, G. M., Tarasova, A. E., Tarasov, E. M.
• Format: Journal Article
• Language: English
• Published: Moscow Pleiades Publishing 01.10.2023; Springer Nature B.V
• Subjects: Algorithms; Automatic control; Control systems; Engineering; Intelligent transportation systems; Machine learning; Machines; Manufacturing; Processes; Railroad crossings; Railway tracks; Self tuning; automated crossing signaling; machine learning; increasing capacity; intelligent transport systems; pattern recognition
• ISSN: 1068-3712; 1934-8010
• DOI: 10.3103/S1068371223100127

The concept of an intelligent transport system representing a “person–vehicle” integrated system of interaction between transport subjects is considered. Properties of the system that are considered intelligent are presented. In particular, such characteristics such as learning ability, classification ability, and adaptation are discussed. As an example, an automated control system for railway crossings that regulate the flow of vehicles across railway tracks is considered. An algorithm is proposed based on the principle of intelligent control using machine learning and self-tuning under the action of destabilizing factors. A unit diagram of an intelligent control system for crossing protection devices is also presented.