Evaluating Passenger Seating Capacity at NS Using Simulation

In this thesis we develop a discrete-event simulation framework capable of evaluating the KPI “transport capacity during rush hour”. The problem is split into several subproblems, namely (i) modeling passenger arrivals, (ii) representing the planned timetable and rolling stock schedule, and (iii) determining passenger routes. Finally, we consider the impact of deviations from the planned timetable and rolling stock schedule in the form of train cancellations and rolling stock mismatches. In order to evaluate our simulation framework, we use passenger check-in/check-out data, and the planned timetable and rolling stock schedule for January 12 in order to predict the KPI of February 9. We conclude that we are adequately able to predict passenger arrivals, but tend to underestimate the KPI with respect to the realized KPI by about 3%. Furthermore we provide some insight into the KPI. We see that overall both train cancellations and rolling stock mismatches negatively impact the KPI, although the effect of mismatches is much larger. We also notice that mismatches have different effect for dif-ferent compositions: for high-capacity compositions the effect is negative, but low-capacity compositions actually benefit from rolling stock mismatches.