Railway transportation has long been thought of as conservative or ‘old school’, but current trends are rapidly pushing the rail industry to digitalise and embrace cutting-edge technologies. From an environmental standpoint, rail emits over 6x less CO2 per passenger than air travel, making rail clearly preferable for those wanting to combat climate change. Meanwhile, the world’s growing population continues to urbanise, putting more pressure on railways to help move more people more efficiently, and over-congested global supply chains need every possible bit of added transportation productivity to help alleviate ongoing shortages.
Railway efficiency is not bounded by gauge or speed. Rather, AI deployed on railway computing infrastructure, especially at the network edge, has tremendous potential to improve operations and bottom lines. When implemented in trucks, a 2020 study found that driverless vehicles realised 29% to 45% cost savings compared to those driven manually, and total cost of vehicle ownership dropped by over 15 percent. Analogous improvements can be found in rail transportation. AI effectively eliminates the delays and errors caused by humans in everyday operation, and automated driving negates the need for engineers to operate trains
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