Can Machine Learning improve railway operational performance?

Similarly, an Indian travel start-up, RailYatri, has created an Estimated Arrival Time prediction algorithm using Machine Learning and statistical modelling techniques to predict the arrival time of trains. The system, trained on historical data, can provide customers with realistic estimated times for the arrival of their trains. According to Kapil Raizada, Cofounder of RailYatri, the method to predict the arrival time of trains in India had not changed over decades and was typically based on a distance by speed ratio for trains with some buffer time. RailYatri's Machine Learning algorithm takes into considerations other parameters ("ground realities") such as increasing traffic, rush, seasonality, etc, and adapts as it learns from subsequent inputs, making the predictions better with time. It uses clustering techniques to organise historical train runs into thousands of patterns where time series data attributes are similar.