With the rapid advancement of urban rail transit construction in China, the networked layout of lines has been continuously improved, and the demand for intelligent operation has been steadily rising. However, the shortcomings of the existing traditional signaling system in terms of resource utilization and scalability have become increasingly prominent, making it difficult to meet the operational requirements of modern urban rail transit, such as high density, high reliability, and efficient operation and maintenance. In response to this problem, the core purpose of this study is to clarify the development path of the next-generation signaling system empowered by cloud platforms, break through the application bottlenecks of the traditional signaling system, and provide theoretical support and practical reference for the upgrading and iteration of urban rail transit signaling systems. In the research process, the comparative analysis method was adopted to systematically sort out the architectural limitations and application pain points of the traditional signaling system. This study. This study focuses on analyzing the overall architectural composition of the cloud-based signaling system, and proposes targeted architectural design ideas and key technology application schemes for the cloud-based signaling system in in combination with the actual operational needs of urban rail transit. In addition, in-depth research is conducted cloud-based SIL 4 safety technology, safe real-time train-to-ground communication technology, and adaptation technology between traditional signaling service applications and secure cloud platforms. The research results indicate that the cloud-based signaling system can effectively make up for the deficiencies of the traditional signaling system, improve the operational efficiency and maintenance level of the signaling system, and provide strong support for the networked and intelligent development of urban rail transit. The findings provide a useful reference for the design, optimization, and engineering implementation of cloud-based signaling systems, and may support the transition of urban rail transit signaling systems toward cloud-based and intelligent architectures.