The TRANSIT project started by conducting a review of the state-of-the-art of intermodal solutions and elaborating a high-level specification of a set of innovative intermodal concepts based on information sharing between the ATM system and ground transport modes. In particular, two solutions are proposed: a strategic solution for air-rail Intermodal Timetable Synchronisation that optimises the connection times between flights and ground services, and a tactical Intermodal Disruption Management solution that modifies flight schedules to reduce the number of passengers stranded at the airport in situations of disruptions in the ground access network, without causing significant delays in other flights. In parallel, a performance framework was developed to deal with the specificities of multimodal trips. The TRANSIT indicator framework includes new user-centric indicators and an updated definition of previously existing indicators, usually unimodal, for the assessment of multimodal systems, considering the interdependencies between trip legs.
The next step of the project was the development of a set of data analytics techniques for the characterisation of long-distance travellers and the detailed reconstruction of urban airport access and egress and long distance multimodal trips from the fusion of survey and mobile network data. The developed algorithms address different challenges in the reconstruction of trips from passively collected geolocated data, such as passenger segmentation by sociodemographic profile, the analysis of modal choices in the airport access and egress legs, and demand segmentation according to trip purpose (leisure/business). Then, TRANSIT developed a modelling and simulation framework consisting of two enhanced tools, MATSim and J TAP, for the simulation of multimodal trips. The MATSim enhanced model enables the simulation of travel behaviour (mode or route change) for unplanned disruptions in the airport access/egress legs of a multimodal trip. The enhanced J-TAP model enables the simulation of long-distance multimodal trips, capturing mode shifts as a reaction to better mode coordination.
Finally, the developed data analysis and simulation tools were used to conduct an assessment of the two proposed intermodal concepts:
- A J-TAP model of Spain was used to test the impact of the the Intermodal Timetable Synchronisation tools to optimise the rail-air timetable for the Valencia Lanzarote pair. This pair does not have a direct flight and is currently connected with a scale in Madrid. Adding the HSR station at the airport increases the HSR share of access trips from 35% to approximately 40%. Timetable synchronisation, in conjunction with building a new HSR station at the airport, boosts the rail modal share to over 50%.
- A MATSim model for the region of Ile de France was used to test the Intermodal Disruption Management tool. A disruption on the main rail service connecting Paris city’s centre with the airport was simulated. The implementation of the solution was able to reduce the number of stranded passengers with minimal changes to the arrival and departure schedules.
The work carried out by TRANSIT has translated into three main solutions:
- The TRANSIT Intermodality Assessment Framework, which consists of: (1) a set of multimodal, passenger centric, door-to-door performance indicators encompassing, among other aspects, travel time, travel time reliability, affordability, environmental impact and resilience; (2) a set of data analytics techniques for the detailed reconstruction of long-distance multimodal trips through the analysis of new big data sources and their fusion with more conventional data; (3) an open-source simulation framework that integrates a long distance travel demand model (J-TAP) with a simulation model of airport access and egress (MATSim).
- The TRANSIT Intermodal Timetable Synchronisation tool.
- The TRANSIT Intermodal Disruption Management tool.
