Periodic Reporting for period 2 - TRANSIT (Travel Information Management for Seamless Intermodal Transport)
Periodo di rendicontazione: 2021-05-01 al 2022-10-31
1. Propose innovative intermodal transport solutions based on information sharing and coordinated decision making between air transport and other transport modes.
2. Develop multimodal KPIs to evaluate the quality and efficiency of the door to door passenger journey.
3. Investigate new methods and algorithms for mobility data collection, fusion and analysis enabling a detailed reconstruction of the different stages of long-distance multimodal trips and the measurement of the new multimodal KPIs.
4. Develop a modelling and simulation framework for the analysis of long-distance travel behaviour that enables a comprehensive assessment of intermodal solutions in terms of the proposed multimodal KPIs.
5. Assess the expected impact of the proposed intermodal concepts and derive guidelines and recommendations for their practical development and implementation.
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.
- TRANSIT has extended existing performance frameworks to take into account the nature of trips with multiple legs and capture the contribution of each stage of a trip to different performance areas.
- The project has advanced the state-of-the-art in the extraction of travel demand information from mobile network data, by developing new machine learning algorithms for the estimation of trip purpose (business vs leisure), passenger socioeconomic profile, and airport access modes.
- TRANSIT has advanced the state-of-the-art in the modelling and simulation of long-distance multimodal travel: first, by developing the enhanced versions of the agent-based modelling frameworks MATSim and J-TAP; second, by developing new model calibration techniques based on mobile network data and other big data sources.
The solutions delivered by TRANSIT are expected the have the following impacts:
- The TRANSIT Intermodality Assessment Framework will enable the design of intermodal solutions that are better adapted to passenger preferences and behaviour, contributing to improving KPIs in a variety of KPAs (especially Efficiency, Punctuality and Predictability, Environment and Resilience) as well as to enhancing passenger experience.
- The TRANSIT Intermodal Timetable Synchronisation solution enables the design of synchronised timetables between air transport and ground public transport modes. The timetables built by using TRANSIT’s Intermodal Timetable Synchronisation solution will improve the Efficiency, Punctuality and Predictability, and Resilience of the multimodal trips that use public transport to reach the airport.
- The TRANSIT Intermodal Disruption Management Tool provides a mechanism for the tactical management of unplanned disruptions in the airport access modes, such as an unexpected rail or subway shutdown. This solution is expected to improve different KPIs in the areas of Efficiency, Punctuality and Predictability, and Resilience.