A Neural Network Will Design “Perpetual” Roads in Russia’s Permafrost Regions
Russian researchers have developed an AI system capable of designing durable, year‑round roads for heavy machinery across some of the country’s most inaccessible permafrost and swamp regions
A Breakthrough for Remote Infrastructure
Scientists at Perm National Research Polytechnic University have created an AI model that can accurately design road structures using advanced geosynthetic materials—an engineering task that was previously impossible to calculate with precision. The technology promises to resolve long‑standing infrastructure barriers that limit development in remote forest regions and inflate transportation costs.
Russia’s forest territories exceed 894 million hectares, but lack of reliable roads has historically restricted access. Temporary winter roads—known as zimniki—are becoming unreliable due to climate change and shorter cold seasons. Permanent roads built on weak soils often fail quickly, driving up costs and forcing repeated reconstruction. Existing engineering methods lacked accurate predictive tools for modern reinforcement materials.
A Neural Network With No Global Analogues
According to the researchers, the system is the first of its kind. After running hundreds of virtual experiments, the neural network learned to analyze 13 road‑design parameters—from soil properties to the type of reinforcement material. It forecasts two critical outcomes: the amount of surface settlement and the stress level inside the geosynthetic layer.
The system also identifies which factors most influence long‑term road durability. For example, it found that weak soil is the main threat to structural stability, while asphalt thickness plays the strongest role in preventing ruts. Such insights help engineers optimize road designs, improving both strength and cost‑efficiency.
A Roadmap to Unlocking Forest Resources
By digitizing the design process, the technology accelerates construction, reduces costs, and opens access to valuable forest regions long considered unreachable. Its strategic importance extends beyond Russia—countries with extreme climates and complex landscapes could benefit from the same approach.
The system has the potential to lower logistics expenses throughout the entire supply chain—from timber harvesting to manufacturing products such as paper and furniture—strengthening both economic and environmental sustainability across the global forest industry. Researchers plan to patent the software soon to support large‑scale adoption.
