The first step in the planning process is to understand real operations by analysing aggregated operational data, such as station passing times, track circuit data, on-board train monitoring and ticketing data. This analysis provides a vast series of diagrams and statistics for further analysis including the identification of disturbances and critical points. This analysis often suggests simple improvements to increase system performance.
Modelling and Validation
The second step in the planning process is to create a microscopic simulation model of the current operations. After validating the model under undisturbed conditions, the operational variables (departure delays, dwell times, and driving styles) that characterise current operations are inserted. These variables are derived by filtering out the effects of delay propagation from the analysis of current operations. The simulation is repeated with the operational variables following a Monte Carlo approach until a satisfactory residual delay is obtained when comparing aggregated model outputs to real delays.
The main outcome of analysing and simulating current operations is a deep understanding of the critical timetable, infrastructure and process elements. Using our understanding of these elements and considering the time-horizon and other goals of the clients, we propose alternative scenarios designed to help improve service quality with a minimum investment cost.
Simulation of Alternatives
The alternative scenarios are tested using the same inputs and Monte Carlo approach used in the simulation of current operations. This ensures that they are tested under realistic conditions, and that the results are consistent. In the case of longer-term scenarios or when major changes in the operational conditions are expected, a sensitivity analysis of variable delays or dwell times is used to estimate the robustness of alternatives under variable conditions.
Analysis of Results
In this final step, the outcomes of all simulation scenarios are compared using the same diagrams and statistics used to analyse current operations. In addition to helping planners understand the weaknesses and strengths of all scenarios, this approach directly compares current operations to proposed alternative scenarios using the same KPIs used in practice to benchmark the quality of railway services.
TRENOplus is a powerful timetable planning tool developed from scratch to take maximum advantage of the latest research in network analysis modelling and algorithms. It integrates a macroscopic model and the trenissimo microscopic model into a package that supports users in estimating running times for use in planning timetables and infrastructure at different levels of detail.
Understanding the processes and dynamics of real operations is a key factor for successful railway planning. Even the best planned timetables can show unsatisfactory reliability when put into operation. TRENOanalysis identifies, measures and visualizes the causes and impacts of delays or real railway traffic and thereby helps planners develop effective measures to maximise service quality.