A method for using stochastic blocking times to improve timetable planning

This paper presents a method for introducing stochastic blocking times to support timetable planning. The approach redefines timetable conflicts by associating a probability with each conflict estimated as a function of process-time variability. The method consists of calibrating a motion equation using data collected on board the train. The calibration set can then be used to compute the stochastic behaviour of individual trains or in micro-simulation models. In this research the behaviour of individual trains was investigated and tested. The method consists of repeatedly simulating an individual train run on a microscopic infrastructure model using the estimated performance parameter distributions obtained in the calibration. The resulting blocking times are stored and depicted in a time–distance diagram using transparencies to represent each run. The diagram presents a wider occupation staircase, in which colour intensity is proportional to the occupation probability. When a second train is inserted into the diagram the probabilistic occupation steps of the two trains can overlap, showing the conflict probability. The software also computes and displays a series of data including the probability of conflicts. The method has been tested on the mixed-traffic, double-track line between Trieste and Venice. The results were a good representation of train blocking times over several operational days.