Strategies for the Use of Data and Algorithm Approaches in Railway Traffic Management

Abstract

Resonate are interested in looking at different strategies / models / techniques for dealing with the problem of rescheduling a railway timetable when it's unexpectedly disrupted, the likely strengths and risks of these, and how they might be adapted to improve existing solutions. Nine different approaches (drawn from machine learning, network models and stochastic models) to defining the efficiency of a station in dissipating delays were considered. They fell broadly into two groups: those that sought to understand the propagation of delays and those that sought to offer strategies for minimising delays.