Trenolab helps clients develop timetable-based solutions for existing operating problems, create and evaluate alternative future timetables, and prepare short-term timetable changes such as unplanned maintenance.
In these studies, we use our TRENO software to analyse existing conditions in detail, then develop and test alternative timetable solutions. Since we created this software, we are able to develop new timetables very efficiently and quickly. Our deep understanding of timetable development also helps us identify highly effective timetable improvements.
One of the keys to improving railway service is understanding timetable robustness. Robustness is defined as the ability of a railway timetable to recover from disruptions. Trenolab performs timetable robustness modelling using an advanced predictive micro-simulation to recreate traffic conditions under many possible operational delay scenarios.
We have used our approach on a variety of railway networks from national networks to metro systems. We’ve successfully helped clients estimate reliability and capacity, develop alternatives, evaluate the performance of alternatives, and assess the effects of delays across their network. Our objective is to help clients identify a timetable that uses fully utilises railway capacity without unduly impacting robustness.