IMMUNER: Integrated Multimodal Mobility Under Network Disruptions

Targeting at improving door-to-door accessibility, efficiency and reducing environmental impact, recent decades have witnessed vigorous development of multimodal transport. Coupled through passenger transfer, the failure of one mode, however, is likely to cause cascading disruptions to the complete system. Therefore, to maintain safe and efficient operations, the integrated recovery of the multimodal transportation system becomes an important, timely topic, given increasingly complex schedule interactions. This study proposes a mathematical model to handle the integrated recovery problem of multimodal transportation network by minimizing the passenger travel cost and mode recovery cost under failures of multiple critical infrastructures. For a case study on air/HSR interaction in China, our model incorporates decisions in terms of aircraft recovery, railway timetable rescheduling, and passenger routing with realistic constraints (e.g. max travel time, max transfer time). A column-and-row generation based heuristic solution algorithm is developed in order to solve the complex model with given computational budgets. Results reveal that real-world test disruption scenarios can be solved within 20 minutes with a small relaxation gap. A significant amount of passenger traveling time can be reduced in contrast to a sequential recovery approach with independent reaction decisions for each transport mode. This work contributes towards the development of support tools for integrated disruption management of multimodal transportation.