A model to quantify the resilience of mass railway transportation systems

Traditional risk management approaches focus on perturbation events׳ likelihood and their consequences. However, recent events show that not all perturbation events can be foreseen. The concept of resilience has been introduced to measure not only the system׳s ability to absorb perturbations, but also its ability to rapidly recover from perturbations. In this work, we propose a simulation-based model for quantifying resilience in mass railway transportation systems by quantifying passenger delay and passenger load as the system׳s performance indicators. We integrate all subsystems that make up mass railway transportation systems (transportation, power, telecommunication and organisation subsystems) and their interdependencies. The model is applied to the Paris mass railway transportation system. The model׳s results show that since trains continue running within the system even by decreasing their speed, the system remains resilient. During the normal operation of the system as well as during perturbation, the model shows similarities with reality. The perturbation management plan that consists of setting up temporary train services on part of the impacted line while repairing the failed system׳s component is considered in this work. We also assess the extent to which some resilient system׳s capacities (i.e. absorption, adaptation and recovery) can increase the resilience of the system.