To adapt to the “fine” and “extensive” management characteristics of railway signal equipment operation and maintenance, achieving real-time and interactive monitoring of signal equipment operation status, and developing an integrated approach to equipment operation and maintenance, this paper takes a comprehensive management perspective. To create a lightweight BIM model, the Garland folding algorithm is utilized to simplify the IFC file format. Building on this approach, the data are divided based on building component division standards to obtain separate files containing geometric information and semantic attributes. The geometric information files are converted to a 3D Tiles format, combining BIM semantic attributes with semantic attribute files through an intermediate format. Dynamic data management is achieved by setting the octree space index structure in combination with a view-frustum culling algorithm. Then, the 3D Tiles target file is imported into the Cesium platform, and Node.js is used to achieve three-dimensional visualization of railway signal operation and maintenance. The proposed method is verified using an inbound signal as an example to assess its feasibility. The results demonstrate the potential of the proposed method to achieve stable integration between BIM equipment full lifecycle maintenance and GIS geographical space display. Railway signal equipment is endowed with comprehensive one-click information query functions for equipment positioning and spatial analysis, improving the efficiency and scientific decision-making level of equipment operation and maintenance.

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In order to improve the sustainability of modern cities, the safe operation of rail transportation is critical. Meanwhile, rail signaling safety is also fundamental for rail transportation, and quantitative analysis of railway signaling safety factors can guarantee this basis. To achieve this, this research proposes an improved rail signaling 5M (Management-Machine-Man-Media-Mission) accident cause hierarchical model, which can make up for the previous lack of objectivity and statistics. According to the demands of rail signaling accident analysis, this research collects and classifies the rail signaling accident data from 2000 to 2017. Then, the hierarchical association rule method is used to calculate the relationships between the 5M factors, and the factor analysis method is applied to measure the weights of the 5M subfactors. Therefore, the safety evaluation index system for railway signaling system is established. The results show that the Management element is the most important factor in rail signaling accidents, while the Mission element is dispensable. Moreover, the subfactors, such as the equipment material, safety management, external humans affected, and hidden danger should also not be ignored. Eventually, the rail signaling accidents analysis is conducted between the 5M model and the improved 5M model; the comparison shows that the improved 5M can not only improve the safety factors influence rate by more than 84.64%, but it can also improve the railway signaling safety, which can provide strong support for the safe operation of rail transportation and sustainable development of a modern city.