A new study by Professor Ke Guan of Beijing Jiaotong University found that digital twins can enhance railway systems globally by changing how we construct, operate, and maintain them. However, despite this, they currently need more technological bandwidth to reach their full potential:
“Accurate and efficient modeling of radio wave propagation and wireless channel over a wide range of frequency bands is the primary challenge in achieving DT,” illustrated Professor Ke Guan,
The study underscores the current challenges faced by digital twins as a tool for enhancing railway systems. Specifically, the limitations in radio wave propagation and wireless channels across different frequencies are hindering their effectiveness. The study proposes potential solutions to this issue, including:
- Scenario modeling with 3D construction techniques and deep neural networks for scenario recognition.
- The employment of ray tracing with AI to ensure efficiency and precision in modeling.
- The development of simulation platforms to ensure that planning across various scenarios and frequencies is supported. Examples of platforms like this include Nvidia Omniverse.
All in all, despite the current constraints, digital twins offer untapped potential in the rail industry. Successful deployments will likely see mass increases in efficiency and cost savings, as shown in sectors such as construction that are beginning to use them.
