Rail transport modelling

Rail transport modelling uses mathematical and computational models to represent railway networks, services, demand, and operations for analysis, forecasting, and planning.

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Railway network: A connected system of railway lines, junctions, stations, and associated infrastructure. Its topology defines the routes and connections that a rail model can represent.
Graph theory: The mathematical study of structures made of vertices connected by edges. Rail networks can be encoded as connected nodes and links for routing and analysis.
Transport planning: The process of assessing and shaping transport systems to meet future mobility needs. Rail models provide evidence for network and service decisions within broader transport plans.
Four-step travel demand model: A sequential transport forecasting framework covering trip generation, distribution, mode choice, and assignment. It offers a conventional aggregate framework that may represent rail within a wider transport system.
Model uncertainty: Uncertainty in a model’s structure, parameters, inputs, or resulting predictions. Rail forecasts depend on uncertain demand, operating assumptions, and future conditions.
Timetable: A schedule assigning train movements and station calls to specified times. Timetables translate service plans into time-dependent train movements.
Operations research: The use of mathematical methods to support decisions about complex systems and resource allocation. Rail planning draws on its optimization and decision methods.
Travel demand forecasting: The estimation of future trips and travel choices under specified demographic, economic, and transport conditions. Forecasts estimate how rail use may change with new services or policies.
Agent-based model: A computational model that simulates individual agents and their interactions under defined rules. It can represent heterogeneous passenger choices more explicitly than aggregate rail demand models.
Sensitivity analysis: The study of how changes in model inputs affect its outputs. It identifies which assumptions most influence rail planning results.