D23.1 - Co-modal Transshipments and Terminals (intermediate)
This Deliverable is basing on the general aims of CAPACITY4RAIL (C4R): to pave the way for the future railway system, delivering coherent, demonstrated, innovative and sustainable solutions.
The deliverable objective is the conceptual design of transhipment technologies and Interchanges of the future 2030 and 2050 (rail yards, intermodal terminals, shunting facilities, rail-sea ports, etc.), according to their role in co-modal transhipment to influence freight demand distribution, both by operation improvements and logistic advantages.
Indeed, European rail freight has not progressed in parallel with the European economy: during the last century, the single wagon was the core business of railways; today, in contrast to the decline of conventional rail freight, combined transport has shown signs of growth.
Currently, rail freight transport consists of two main typologies: conventional rail freight services (wagonload) and combined transport services, which include the notion of transhipment and the flow of goods from an origin to an intermediate destination, and from there to another destination.
Terminals are a key element of transport services and, in this study, the main goal has been to suggest suitable methods to evaluate the performance of different types of rail freight terminals, which are applicable to various families of terminals:
– Rail to road for long distance and shorter range units transfer;
– Rail to rail for shunting and/or gauge interchange;
– Rail to waterways (sea and inland).
To evaluate the performance of the typologies of terminals listed above and the influence of innovative operational measures and new technologies on their operation, we have chosen to use both analytical methods based on sequential application of algorithms (e.g. from queuing theory) and discrete event simulation models.
These methods and models have been tested on different terminals for the three typical case studies (Road-Rail, Sea-Rail, and Rail-Rail), evaluating both the global performance of the terminal and the performance of its components.
The first case study selected for the pilot application of methods and models and the evaluation of future scenarios is the terminal located in Munich Riem, operated by the DB owned company DUSS.
The set of road-rail terminals considered as case studies includes three intermodal terminals located in Antwerp: Combinant, Hupac and Zomerweg.
The Port of Valencia’s Principe Felipe Railway Terminal has been the selected as a case study for searail terminals.
Finally, Hallsberg case study deals with the largest marshalling yard in Sweden, both in the number of wagons handled and surface extension.
To evaluate the impact of the technological and management innovations introduced, the selected methods and models calculated corresponding Key Performances Indicators (KPI) for each of the scenarios.
The calculation of KPIs uses both analytical methods and the simulation models, compared with real world data, the case studies, allowing an estimation of the achievable level of accuracy.
Moreover, two logistic chains have been analysed, to identify the main measurable elements potentially affecting the operational and management phases, as well as the typical distribution of costs, distance and time and the distribution between rail, road and transhipment for case studies 1 and 2.
It emerged that novel technologies such as Information and Communication Technology (ICT) systems and Intelligent Transport Systems (ITS) are useful for freight management in an intermodal transport chain.
Based on the innovative operational measures and technologies considered in WP2.1 and WP2.2, the scenarios for the case studies to be analyzed include a combination of elements. The analysis use the selected methods and models, taking into account their progressive temporal implementation.
The application of the selected analytical methods and simulation models has provided results illustrated in histograms for the most reliable results of a selection of KPI.
The implementation of new technologies and operational measures lead to a general increase of the key performance indicators and, consequently, an increase of terminal performance.