This paper presents a schematic plan outlining a methodology for determining train positions using digital twin technology and commercially available positioning sensors. The plan involves an offline step and an online step. The task in the offline step includes: building a library of 3D models for objects on railway tracks, and constructing a real digital twin environment. Then in the online step, train positions can be accurately determined by automatically generating real-time semantic point clouds from images and matching them with the 3D objects in the digital twin. Along with these tasks, a City Geography Markup Language (CityGML) Application Domain Extension (ADE) for modeling railway tracks in 3D will be developed and suggested as Open Geospatial Consortium (OGC) standard for similar applications. All these procedures will be conducted in a controlled environment using remote-controlled cars before being applied to an actual railway track. It is hoped that this localization methodology can enhance traditional positioning methods, ultimately leading to improved network operation and maintenance.