Researchers at MIPT have crafted and deployed an autonomous system that optimizes the operational plan for the Prognosis railway program. This system can generate a fresh train timetable in emergency scenarios within three seconds, and the capability was shared with socialbites.ca. [Citation: MIPT Laboratory]
Artificial intelligence already sits at the core of managing train flows on the strategic Zhetygen-Altynkol corridor, a route considered essential for Kazakhstan’s economy. This railway line, stretching to the Chinese border and spanning 191 kilometers, is overseen entirely by automated traffic management. When a minor disruption occurs, the neural network can forecast the situation for the following day, showing how the delay of one train may ripple through the entire system. [Citation: MIPT Laboratory]
To resolve an incident and craft a revised movement plan that accounts for ongoing repair work and redirected rails, the Forecast intelligent system needs no more than three seconds. A human dispatcher would typically spend far more time on problems of this complexity. Yet there are cases where the neural network cannot match the expertise of a seasoned operator. [Citation: MIPT Laboratory]
Under standard operations, the expert (grafist) who designs traffic schedules usually has seven days to produce an optimal plan that satisfies the needs of multiple services and gains approval from the responsible parties. Re-entering data and re-running calculations can add days to the timeline. The AI component that generates the regulatory diagrams significantly assists the dispatcher by processing more than 50 parameters and constraints critical to traffic operations, from the priority of each train to the current condition of the track on any given segment. These insights were described by Andrey Novikov, the chief engineer of the Wave Processes and Control Systems division at MIPT. [Citation: MIPT Laboratory]
In more complex sections, the Prediction neural network acts as a guiding tool for the dispatcher, while areas with fewer than 20 trains per day are slated to move toward full automation in the future. Busy zones with heavy maneuvering still require a human expert to manage nuanced decisions and ensure safety and efficiency. [Citation: MIPT Laboratory]
Looking at a broader historical arc, Russia has explored AI applications such as dolphin detection by analyzing whistle patterns, a research thread that highlights the evolving capabilities and creative uses of artificial intelligence. [Citation: MIPT Laboratory]