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The paper demonstrates the possibilities of a scientometric approach using CiteSpace II software analysis of the field of railway dynamics with detection of research front, main clusters of cross-cited papers, their evolution and pivotal points (see terms in Sections 2.1 and 2.2). The initial database contained 5126 Web Of Science records published between 1975 and 2019 (45 years). The linguistic analysis determined the evolution of burst terms and grouped the papers in 14 clusters that corresponded with the view of the specialists in the field. 'Railway vehicle', 'Curved track' (hunting stability and derailment risk), 'Unconventional railway truck', 'Railway turnout (crossing)' and 'Polygonal wear' clusters were analysed in more detail with a determination of top-cited papers in each cluster and papers that determined connections between clusters (pivotal papers). Two pivotal papers were verified with their authors.

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