To support railway traffic management in taking optimised rescheduling decisions in case of disturbances, conflict detection and resolution models are being developed. The existing models mostly refer to conventional fixed-block signalling systems. In these fixed-block systems, minimum train separation distances are determined based on a preset number of blocks considering worst-case braking distances. In fixed-block distance-to-go signalling systems, such as the European Train Control System (ETCS), minimum train separation is based on absolute braking distances. Hence, a different dependency on train speed is required in conflict detection and resolution models for distance-to-go signalling than in models for conventional fixed-block signalling. In this paper, we propose enhancements for existing conflict detection and resolution models to describe distance-to-go operations. The enhancements include the introduction of speed profile options and the redefinition of train blocking times. As a proof of concept, we apply these enhancements to the state-of-the-art rescheduling model RECIFE-MILP, originally developed for conventional fixed-block signalling. The enhanced model is verified and compared with the original model in terms of delay and rescheduling decisions in two case studies of a complex junction and a corridor. The results indicate that the distance-to-go model can propose different rescheduling decisions than the conventional fixed-block one, exploiting distance-to-go operations for a better delay recovery.@en

Moving Block (MB) and Virtual Coupling (VC) rail signalling will change current train operation paradigm by migrating vital equipment from trackside to onboard to reduce train separation and maintenance costs. Their actual deployment is however constrained by the industry's need to identify configurations of MB and VC signalling equipment which can effectively guarantee safe train movements even under degraded operational conditions involving component faults. In this paper, we analyse the effectivity of MB and VC in safely supervising train separation under nominal and degraded conditions by using an innovative approach which combines Fault Tree Analysis (FTA) and Stochastic Activity Networks (SAN). An FTA model of unsafe train movement is defined for both MB and VC capturing functional interactions and cause-effect relations among the different signalling components. The FTA is used as a basis to apportion signalling component failure rates needed to feed the SAN model. Effective MB and VC train supervision is analysed by means of SAN-based simulations in the specific scenario of an error in the Train Position Report (TPR) for five rail market segments featuring different traffic characteristics, namely high-speed, mainline, regional, urban and freight. Results show that the thresholds of the design variables depend on the considered signalling system alternative and the investigated market segment. In particular, the TPR delay threshold allowed for MB is higher than for VC. This means that to ensure a safe train movement, VC cannot absorb a TPR delay of longer than 1.5 s, which corresponds to the mainline market segment. For MB instead, the results show that the maximum TPR delay can reach 3.9 s for high-speed and freight railways. In addition, results showed that the integration of an FTA in a SAN model can provide a better understanding of the safety-performance behaviour of a system where VC showed a higher number of braking indications with respect to MB for the same TPR error failure rate. This means that for VC to effectively supervise the train separation at the same safety level as MB, we would need to have a much higher reliability of the TPR. The overall approach can support infrastructure managers, railway undertakings, and rail signalling suppliers in investigating the effectiveness of MB and VC to safely supervise train movements in scenarios involving different types of degraded conditions and failure events. The proposed method can hence support the railway industry in identifying effective and safe design configurations of next-generation rail signalling systems.

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For effective railway operations, real-time railway traffic management is crucial. In case of disturbances, traffic management can apply rescheduling and rerouting measures to resolve conflicts while minimising the propagation of delay. To support human dispatchers in taking optimised decisions, conflict detection and resolution (CDR) models are developed. Predominantly based on alternative graphs or mixed integer linear programming (MILP), the existing models mostly refer to conventional signalling systems in which the track is discretised into fixed blocks. Only at block entries, trains can receive a brake indication. Hence, train separation is based on a number of blocks. With the implementation of continuous braking curve supervision in distance-to-go (DTG) signalling systems such as the European Train Control System (ETCS), train separation is based on absolute braking distances. Consequently, an explicit relation between speed and train separation is required in CDR models for DTG signalling. Recently, we proposed enhancements for existing CDR models
to describe DTG operations. The enhancements relate to track discretisation, speed profile options and train separation. We applied these enhancements to RECIFE-MILP, resulting in a tailored CDR model for DTG signalling. In this research, we consider the model for the more advanced DTG signalling systems of ETCS Level 3: Fixed Virtual Block and Moving Block. In these train-centric signalling systems, train position and integrity are monitored onboard
– as opposed to conventional trackside train detection. We update the DTG model accordingly, and we investigate the impact of track discretisation granularity on the model performance. The impact is assessed in terms of delay recovery and rescheduling decisions. The results indicate that, depending on the track and traffic scenario, a finer granularity can lead to different rescheduling and rerouting decisions due to shorter train separation.@en

In case of disturbed railway operations, traffic management can apply rescheduling measures to resolve conflicts while minimising delay propagation. This can be optimised by conflict detection and resolution (CDR) models. Usually based on alternative graph or mixed integer linear programming (MILP) formulations, existing models mostly refer to conventional signalling systems in which the track is discretised into blocks. Only at block entries, trains can receive a brake indication. Hence, train separation distances are based on a number of blocks. With the implementation of continuous braking curve supervision in distance-to-go (DTG) signalling systems such as the European Train Control System (ETCS), train separation is based on absolute braking distances. Consequently, an explicit relation between speed and train separation is required in CDR models for DTG signalling. Recently, we enhanced the CDR model RECIFE-MILP to DTG operations. The enhancements relate to track discretisation and speed-dependent train separation. In this research, we investigate the effect of track discretisation granularity on the performance of the enhanced model for next-generation DTG signalling systems: ETCS Level 3 Fixed Virtual Block and Moving Block. The performance is assessed regarding total delay and rescheduling decisions. The results indicate that, depending on the track and traffic scenario, a finer granularity can lead to different rescheduling decisions due to shorter train separation.@en

Conflict detection and resolution models are being developed to support railway traffic management in taking optimised rescheduling decisions in case of disturbances. Existing models mostly concern fixed-block signalling systems, in which minimum train separation distances are determined based on a preset number of blocks representing worst-case braking distances. In a moving-block signalling system, minimum train separation is based on absolute braking distances and hence depends on train speed differently from how fixed-block conflict detection and resolution models. In this paper, we propose a conflict detection and resolution model that approximates moving-block operations. The model enhances the state-of-the-art fixed-block rescheduling model RECIFE-MILP. The enhancements include a reconsideration of the discretisation of the infrastructure, the introduction of a speed profile alternative and a redefinition of the blocking times. We verify the model by comparing the solutions of the moving-block version with the fixed-block version for a specific scenario. The results indicate that the moving-block model can propose different rescheduling decisions than the fixed-block model with a better delay recovery.@en

This paper reviews the concept of self-organisation as defi ned in diff erent fi elds and attempts to provide a defi nition of goal-oriented self-organization that can be applied in the context of railway traffi c. Based on the provided defi nition a modelling approach for self-organising rail traffi c is then proposed to set the basis for future research and exploration of such a concept which could revolutionise the current rail transport to meet long-term capacity and competitiveness goals envisaged by the railway industry.@en

Automatic Train Operation (ATO) is a technology to support or automate train driving for increasing service punctuality, energy efficiency and rail infrastructure capacity. Conflict-free train path planning is crucial to the effective deployment of ATO, which allows ATO-equipped trains to operate according to schedule with different train driving strategies. As different train driving strategies lead to various passing times, current planning practice is inadequate to avoid route conflicts as it only sets target arrival or passing times at stops or major junctions. Therefore, conflict-free train path planning needs the definition of a Train Path Envelope (TPE) that contains time targets or windows defined at discrete locations called timing points to tolerate schedule deviations due to different driving styles. The number and location of the timing points, as well as the associated time targets or windows, is a decision problem. This paper proposes a framework to design a robust set of timing points and their associated time windows in a TPE to enable operational conflict-free train path planning against the driving strategies utilised. This framework relies on a Train Path Slot model which extends the definition of TPE from time windows at a discrete set of locations to an integrated blocking time stairway pattern continuously defined across all locations over a train route. The Train Path Slot model considers three relevant train driving strategies, i.e., energy-efficient driving with or without coasting as well as minimum-time driving considering slight delays. A Linear Programming model is formulated to compute the conflict-free Train Path Slots as constraints for train operation. To meet the optimised Train Path Slots, we analyse several possible sets of timing points in a TPE that are only located at stops or signal positions along the train routes. Those timing point sets are then compared in terms of total Train Path Slot overlap time, capacity, energy efficiency and driving performance indicators. Our research supports infrastructure managers in resolving the imminent problem of timing point determination and TPE computation to reach their capacity goals. At the same time, it allows sufficient driving flexibility for railway undertakings.@en

Developments in the railway industry are continuously evolving and long-term transition strategies can enable an efficient implementation of signalling technologies that provide a significant increase in network capacity and operation efficiency. Virtual Coupling (VC) advances moving block signalling by further reducing train separation to less than an absolute braking distance using train-to-train communication and cooperative train control within a Virtually-Coupled Train Set (VCTS). This paper proposes a method to develop scenario-based roadmaps based on a SWOT and hybrid Delphi-AHP multi-criteria analysis. Step-changes are identified and initially assessed in a Swimlane based on priorities and time order collected from stakeholders through a survey and further developed in a workshop. Optimistic and pessimistic scenarios are assessed regarding various factors and timelines. Step-changes are initially defined in a Swimlane and then enriched with optimistic and pessimistic scenarios to ultimately derive scenario-based roadmaps. Durations for each of the step-changes are developed into scenario-based roadmaps that can be used as an efficient tool for stakeholders to identify and solve potential criticalities/risks to the deployment of VC as well as to setup investment and development plans. The approach is applied to deliver implementation roadmaps of VC for different market segments with particular focus on mainline railways.

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Railway traffic management is responsible for the detection and resolution of conflicts in case of disturbed operations. To minimise delay propagation, rescheduling decisions are taken by human dispatchers, possibly supported by mathematical models. Existing conflict detection and resolution (CDR) models mostly refer to conventional fixed-block multi-aspect signalling systems, in which minimum train headways are determined based on a preset number of blocks considering worst-case braking distances and number of signal aspects. In moving-block signalling systems, minimum headways are based on absolute braking distances. This paper reviews literature on CDR with the aim to identify gaps and to propose next steps in the research on CDR under moving-block signalling. A research agenda presents various modelling options, for which modelling approaches are proposed based on a comparative analysis.

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This deliverable contains the output of the activities performed for Task 4.3 “Guidelines on integrated traffic management architectures for safe and optimised moving-block operations” of the EC Shift2Rail PERFORMINGRAIL project. A real-time model for Moving Block traffic conflict detection and resolution is mathematically specified based on the formulation introduced in Deliverable D4.1. A mathematical formulation of the RECIFE-MILP rescheduling tool extended for Moving Block rail operations is reported together with a detailed description of the objective function and constraints. The proposed MB traffic conflict detection and resolution model is then verified for a given network layout and compared to the original RECIFE-MILP formulation for fixed-block to assess modelling and performance impacts of introduced MB constraints. A validation has successively investigated the applicability and effectiveness of the proposed MB traffic management algorithm by testing it on two real railway networks in France (Gonesse junction and a portion on the Paris-Le Havre line) for different traffic scenarios. The validation experiment shows that with respect to fixed-block, Moving block can reduce delay propagation especially: i) for junctions where trains are not stopping, ii) in denser peak-hour traffic and iii) when train rerouting decisions are taken. A detailed description is the provided for the early-warning MB hazard prediction modules introduced in PERFORMINGRAIL Deliverable D4.1. A specification of input/output data and main functionalities is reported together with practical examples illustrating the usefulness of those modules in mitigating potential MB safety risks in the short and medium term. A functional TMS architecture is then defined for a safe and optimised real-time management of MB traffic operations. Guidelines are outlined for the different functional TMS modules, specifying input/output data, main functionalities and interactions with other components within and without the TMS. A set of recommendations is eventually provided to support both science and the industry in further development and implementation of functional modules and an advanced TMS architecture for MB rail traffic. Recommendations particularly refer to novel modules introduced in PERFORMINGRAIL, namely the MB conflict detection and resolution and the early-warning MB hazard prediction models. In addition, indications are given for further development and practical implementation of the proposed functional TMS architecture for safe and optimised MB railway operations. The main highlighted points regard the need of interfacing current Traffic Monitoring systems with satellite-based train location systems as the removal of track-side train detection will compromise the use of existing train describers. That also leads to then necessity of the TMS architecture to include proposed modules for early-warning hazard prediction to mitigate safety risks which can arise for MB in locations with compromised GNSS or GSM-R signal availability. Another essential recommendation refers to data interface standardisation to enable seamless communication among functional modules within the TMS and with external supporting systems.@en

Moving Block (MB) and Virtual Coupling (VC) rail signalling will change current train operation paradigm by migrating vital equipment from trackside to onboard to reduce train separation and maintenance costs. Their actual deployment is however constrained by the industry’s need to identify configurations of MB and VC signalling equipment which can effectively guarantee safe train movements even under degraded operational conditions involving component faults. In this paper, we analyse the effectivity of MB and VC in safely supervising train separation under nominal and degraded conditions by using an innovative approach which combines Fault Tree Analysis (FTA) and Stochastic Activity Network (SAN). A FTA model of unsafe train movement is defined for both MB and VC capturing functional interactions and cause effect relations among the different signalling components. The FTA is then used as a basis to apportion signalling component failure rates needed to feed the SAN model. Effective MB and VC train supervision is analysed by means of SAN-based simulations in the specific scenario of an error in the Train Position Reporting (TPR) for five rail market segments featuring different traffic characteristics, namely high-speed, mainline, regional, urban and freight. Results show that the overall approach can support infrastructure managers, railway undertakings, and rail system suppliers in investigating effectiveness of MB and VC in safely supervising train movements in scenarios involving different types of degraded conditions and failure events. The proposed method can hence support the railway industry in identifying effective and safe design configurations of next-generation rail signalling systems.@en

Railway industry is developing advanced signalling systems like moving block to improve network capacity. In traditional fixed-block systems, safe train separation is determined based on a fixed number of block sections representing worst-case braking distances. In moving-block systems, the train separation is reduced to absolute braking distances. The introduction of moving-block signalling requires a change in operational rules and hence in real-time conflict detection and resolution methods in case of disturbances. Existing conflict detection and resolution models are mainly based on fixed-block signalling and the available models for moving-block signalling do not sufficiently represent the dynamic relation between safe train separation and actual train speeds.
To address this gap, we propose a conflict detection and resolution model that approximates moving-block operations. The model enhances the state-of-the-art fixed-block model RECIFE-MILP. The enhancements include a reconsideration of the discretisation of the infrastructure, the introduction of a speed profile alternative and a redefinition of blocking times. With this, the model is able to include speed-dependent occupation times, train separation based on absolute braking distances and continuous braking curve supervision.
We present the reformulated MILP (mixed integer linear programming) model and apply it to two French case studies: the Gonesse junction and a part of the Paris-Le Havre line. For various one-hour periods, rescheduling strategies and disturbance scenarios, we compare the optimal solutions of the enhanced and the original RECIFE-MILP model in terms of total train delay and rescheduling decisions. The results show that the enhanced model can propose different rescheduling decisions than the original model, with a better delay recovery exploiting the moving-block system.@en

Moving Block (MB) and Virtual Coupling (VC) rail signalling will change current train operation paradigm by migrating vital equipment from trackside to onboard to reduce train separation and maintenance costs. Their actual deployment is however constrained by the industry’s need to identify confi gurations of MB and VC signalling equipment which can eff ectively guarantee safe train movements even under de-graded operational conditions involving component faults. In this paper, we analyse the eff ectivity of MB and VC in safely supervising train separation under nominal and degraded conditions by using an innovative approach which combines Fault Tree Analysis (FTA) and Stochastic Activity Network (SAN). A FTA model of unsafe train movement is defi ned for both MB and VC capturing functional interactions and cause-eff ect relations among the diff erent signalling components. The FTA is then used as a basis to apportion signalling component failure rates needed to feed the SAN model. Eff ective MB and VC train supervision is analysed by means of SAN-based simulations in the specifi c scenario of an error in the Train Position Reporting (TPR) for fi ve rail mar-ket segments featuring diff erent traffi c characteristics, namely high-speed, mainline, regional, urban and freight. Results show that the overall approach can support infra-structure managers, railway undertakings, and rail system suppliers in investigating ef-fectiveness of MB and VC in safely supervising train movements in scenarios involving diff erent types of degraded conditions and failure events. The proposed method can hence support the railway industry in identifying eff ective and safe design confi gura-tions of next-generation rail signalling systems.@en

To address the ever-growing rail transport demand, the concept of Virtual Coupling train operations is gradually gaining ground within the railway industry. Thanks to a Vehicle-to-Vehicle communication, trains could be separated by less than an absolute braking distance and even form connected platoons to increase capacity at bottlenecks. However, a major concern about this concept regards the risk of safety violations in case of operational hazards pertaining to delays in train communication and control or emergency train stops. In this paper, the notion of dynamic safety margin is introduced for Virtual Coupling to dynamically adjust train separations so to always keep required safety distances also when hazardous operational events occur. The dynamic safety margin is embedded in a multi-state train-following model to analyse Virtual Coupling operations in presence of operational risk factors. A three-step methodology is applied in a real case study to fine-tune and verify the model, perform a sensitivity analysis, and identify capacity gains in several test scenarios including nominal and degraded traffic conditions. Results show that the use of a dynamic safety margin provides substantial capacity benefits to Virtual Coupling while respecting safe train distances even in case of sudden failures of the train control or communication systems. The notion of a dynamic safety margin can hence contribute to a safer version of Virtual Coupling operations and be considered by the railway industry in defining system requirements.

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This paper analyzes the effectiveness of decentralized strategies for dispatching rolling stock and train drivers in a railway system. Such strategies give operators a robust alternative in case centralized control fails due to an abundance of infrastructure or rolling stock disruptions or information system malfunctions. We test the performance of four rolling stock and two driver dispatching strategies in a microscopic simulation. Our test case is a part of the Dutch railway network, containing eleven stations linked by four train lines. We find that with the decentralized dispatching strategies, target frequencies of the lines are approximately met and train services are highly regular without large delays. Especially strategies that allow rolling stock to switch between lines result in a high performance.

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More and more people in big cities choose urban rail transit as the main means of public transportation. With the increasing unbalanced passenger flow in time and space, the traditional operation mode with fixed train formation (or composition) is difficult to satisfy the varying passenger demands. This paper distinguishes different train formations in urban rail transit, and specifies the definition and the operation process for flexible composition of trains. An integrated train scheduling problem with flexible train composition is proposed, where the key constraints for practical train operation and the utilization of rolling stocks are considered. These constraints involve turnaround constraints, flexible train formation constraints, headway constraints and passenger flow constraints. The resulting problem is a mixed integer nonlinear programming problem, which can be transformed into a mixed integer linear programming problem and then be solved using existing optimization solvers, e.g., CPLEX. Based on the practical infrastructure and passenger demand data of the Beijing Daxing International Airport Express, a set of case studies is carried out to demonstrate the effectiveness of the presented model and solution approach. The computational results show that the train schedule with flexible train compositions can largely reduce the number of waiting passenger when compared with the train schedules with fixed train compositions and with multiple train compositions.@en

This deliverable has the objective to define a mathematical model for an optimised real-time management of railway traffic under Moving Block (MB). The formulated real-time traffic management model contains: i) a core module for the detection and the sub-optimal resolution of track occupation conflicts under MB and ii) a non-vital module for providing early-warning predictions of potentially hazardous MB traffic situations. The proposed real-time traffic management model includes a mathematical translation of requirements and constraints identified for both MB signalling within WP2 (namely deliverables D2.1 and D2.2) and the GNSS localisation and train integrity devices within WP3 (i.e. deliverables D3.1 – D3.3). An extensive literature review on real-time traffic management models and algorithms shows that so far research efforts have mainly focused on fixed-block and distance-to-go railway operations. Significant gaps still exist in the modelling of MB train operations, despite an increasing number of research works on MB signalling technology is observed since year 2003. A modelling gap analysis is here performed which indicates the need of enhancing existing real-time traffic management algorithms to better align them to the MB concept in terms of infrastructure representation and speed-headway functional dependency. To this end, the RECIFE-MILP real-time traffic management algorithm is enhanced. On one hand a finer infrastructure discretisation is implemented to offer a more suitable track representation under moving block which no longer uses fixed block sections. On the other hand, two different speed levels (namely maximum speed and scheduled speed) are introduced enabling a speed-dependent headway computation in either nominal or delayed traffic scenarios, thereby overcoming the limitation of speed-independent headways, typical of fixed-block traffic rescheduling models. A non-vital early-warning prediction model of hazardous MB traffic conditions is also proposed which includes a short- and a medium-term hazard identification method. In the short-term, potentially hazardous MB traffic condition are identified as violations of safety-critical threshold values of design variables relating to MB train operations (e.g. driving reaction times), the GNSS system (e.g. GNSS error or latency) and/or the GSM-R layer (e.g. MA communication delay). Safety-critical thresholds of the different design variables are identified by means of an extensive sensitivity analysis which uses a Stochastic Activity Network built for MB within WP2. In the medium-term warnings of potentially hazardous MB conditions are instead triggered whenever RECIFE-MILP detects track occupation conflicts in geographical areas with limited GNSS and/ or GSM-R signal availability, such as deep valleys or tunnels. The defined models contribute to the definition of an optimised automated Traffic Management System for Moving Block which can also support traffic dispatchers in preventively avoiding the occurrence of potentially dangerous MB traffic conditions. @en

Automatic Train Operation (ATO) is well-known in urban railways and gets increasing interest from mainline railways at present to improve capacity and punctuality. A main function of ATO is the train trajectory generation that specifies the speed profile over the given running route considering the timetable and the characteristics of the train and infrastructure. This paper proposes and assesses different possible ATO architecture configurations through allocating the intelligent components on the trackside or onboard. The set of analyzed ATO architecture configurations is based on state-of-the-art architectures proposed in the literature for the related Connected Driver Advisory System (C-DAS). Results of the SWOT analysis highlight that different ATO configurations have diverse advantages or limitations, depending on the type of railway governance and the technological development of the existing railway signaling and communication equipment. In addition, we also use the results to spotlight operational, technological, and business advantages/limitations of the proposed ATO-over-ETCS architecture that is being developed by the European Union Agency for Railways (ERA) and provide a scientific argumentation for it.

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The Hyperloop is a concept of a ground transportation system consisting of capsules (called pods) traveling at very high-speeds in near-vacuum tubes. The hyperloop aims to be a fast, cheap, and sustainable alternative to short-haul flights and high-speed rail. The small pod size requires very high frequencies to respond to future high levels of passenger and cargo demands. Media and representatives of the emerging Hyperloop industry acclaim the Hyperloop as a very capacity-effective transport system, however there is no clear scientific evidence proving that. A theoretical investigation is therefore necessary to understand which capacity the Hyperloop could safely provide and whether that could satisfy the future transport demand. This paper provides a comparative analysis of the capacity that the Hyperloop can offer for several operational scenarios and different signalling systems, including Moving-Block and the advanced concept of Virtual Coupling. Results show that Moving-Block could achieve required transport capacity levels only if pods could use high deceleration rates likely to be unsafe and uncomfortable to passengers. Virtual Coupling is instead observed to be a more satisfactory operational concept that could address transport demand while respecting safety and comfort standards if reliable pod platooning technologies are available.@en