Adaptive Control of Rail Freight Transportation: an Agent-Based Concept of Stability Through Local Protocols

The article is devoted to developing a concept for transitioning from the traditional centralized dispatching system for freight rail transportation to a decentralized agent-based architecture of adaptive control. The relevance of the study is driven by the structural imbalance of the network and the high turbulence of freight flows, under which the classical hierarchical model demonstrates critical delays in control actions and an inability to prevent cascading failures. The proposed concept builds upon previously developed dynamic models describing two operating modes of the railway network – "at capacity" and "pendulum load" – and envisions the formation of a community of autonomous agents: trains, stations, temporary cargo storage zones, and regulators. The key principle of the architecture is the rejection of vertical commands: each agent makes decisions solely based on signal exchange with its immediate neighbors. Local interaction protocols are described that ensure adaptation to peak loads, automatic redistribution of excess freight flows, and maintenance of stable cargo movement. Steps for implementing a pilot project on a congested section of the railway network are discussed, including the creation of a software environment, calibration of the model on real operational data, and stress testing under conditions of abrupt disturbances. The research lays the theoretical and methodological foundation for creating sustainable, self-organizing transport systems capable of adapting to peak loads without directive external intervention. The application of the proposed approach will increase infrastructure capacity through more uniform load distribution and a reduction in the frequency of traffic stoppages.