Development of an agent-based model for railway infrastructure project appraisal

The planning of transport infrastructure must consider both the short-term capacity demand and the equipment’s maintenance needs, as well as the long-term evolution of the transportation system. In the freight transportation system, long-term evolutions stem from the individual behaviours of several stakeholders and their dynamic relationships. Their actions may change how the infrastructure is used, giving rise to bottlenecks, or novel development opportunities. However, existing project planning techniques tend to make static assumptions on these agents’ behaviours when predicting future developments. Furthermore, there is a need for models able to simulate short-term developments in transport operations alongside long-term system evolutions. This work aims to contribute towards solving these gaps, particularly in what concerns the consideration of stakeholder adaptation strategies when confronted with infrastructure alterations. We propose a novel a dual-approach Agent-based Modelling concept, based on Hybrid Modelling methodologies. This framework is comprised of two distinct modules: the micro module reproduces short-term freight transport operations in the physical network, while the macro module captures the stakeholders’ decision-making in the long-term. These modules continuously communicate with one another, updating critical information regarding system conditions throughout the simulation period. The developed modelling concept was assessed through a set of simulation trials, which revealed its sensitivity to different scenarios of railway project implementation and demonstrated its potential for capturing the possible outcomes of distinct infrastructure projects, stimulating the responses of stakeholders to the new market conditions, and identifying network bottlenecks.