## 1 Introduction
### Related Works
#### 1.3.4 BIM in Railway Transport  
The review study [34] analyses the BIM issues over the last 10 years and focuses on the monitoring of railway structures. The authors propose an extension of the IFC format to capture parameters using sensors, address the optimization of sensor data and interoperability between different BIM platforms. Furthermore, they address the optimization of different sensing technologies for error detection and management of large amounts of data and the consideration of environmental impacts of railway structures. Surveying of railway tunnels using laser scanning and automatic identification of structural elements on the track is discussed in [35]. The method involves two basic operations: point cloud classification and model parameter estimation. The authors of [36] propose a new algorithm to measure the similarity between two BIM components based on their attribute information and similarity. The method enables efficient retrieval of information from BIM models for further use (e.g., SMART City). Testing the geometry quality of railway structures in the context of a BIM model is the topic of paper [37]. The paper details formal methods for checking the correct link between 3D BIM and bill of material (BOM) and describes formal approaches for checking the semantic-geometric coherence of BIM objects. The study [38] is the first in the world to integrate BIM and machine learning to locate defects in railway infrastructure. The developed learning model is beneficial to the railway industry for better asset management and efficient maintenance. A similar issue is addressed in [39]. In [40], Infrastructure Building Information Modelling (InfraBIM), which is a management information system of digital processes for infrastructure, is described. The real innovation lies in the creation of a plug-in that allows extrapolation directly from the design program to the computational model, which then simulates the proposed transport structure in a real context. The project of using BIM in conjunction with the Internet of Things (IoT) is described in [41]. It is an efficient planning and design of rail transport lines with 3D visualization and scenic modeling of the railway environment. The system can be used for visual management of railway infrastructure operation and maintenance. The prevention of risks on the rail line is addressed in [42]. The central element is the LOD (Level of Detail) in the BIM model, which represents the risk object (e.g., a switch) with all geometric and non-geometric information. The main objective of the project in [43] was to systematize the information of the digitized railway infrastructure in order to assess possible performance gaps within the national infrastructure. The project proposed a digitization strategy to define surveying activities and implement openBIM systems to develop an object library and a federated digital asset management model. In [44], the authors developed a 3D BIM model based on the IFC standard, which is extended with geometric information description and hierarchy to model the multi-component subsoil in a railway station. On this basis, an automatic workflow is established to convert the original design data into the corresponding BIM model. Optimization of design in railway construction using BIM is also addressed in other works [45; 46; 47; 48; 49; 50]. Test of the possibilities and capabilities of storing GIS data in the open standard Industry Foundation Classes (IFC) for BIM was solved in [51]. The study [52] analyses the requirements specified in the Deutsche Bahn AG guidelines for the technical design of railway structures and investigates the feasibility of implementing these rules in a BIM model. A specific application of BIM to a station building in London using Revit-based simulation of the construction works was discussed [53]. It proposes the transformation of a 3D building model into a 6D building information model. A comparative study of railway building projects in South Korea is contained in [54].