R.M.P. Goverde
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European railway capacity management is moving towards earlier capacity strategies, models and offers. These products must be translated into feasible national timetables, but the literature commonly treats technical capacity, line and timetable design, and institutional allocation separately. This paper develops the Railway Capacity Allocation Framework (RCAF), a literature-derived, relational characterisation framework with three dimensions: physical-technical configuration, train-service and timetable configuration, and institutional capacity-allocation arrangement. The dimensions are specified through eight sub-dimensions; train-service formation and timetable construction are mutually dependent within the second dimension. Four relations concern capacity use and feasibility, service formation and allocation, capacity definition and infrastructure provision, and macro-micro translation.
The RCAF is applied in a qualitative case study centred on the Netherlands, with supporting applications to Belgium and Switzerland. Evidence combines literature, documents, network indicators and interviews involving 30 participants. Dutch capacity allocation connects a dense and polycentric network, mixed and strongly periodic services, nationwide microscopic annual-timetable planning years ahead, and formal infrastructure-manager responsibility with production knowledge distributed across actors. Belgium shares the macro-micro transition problem in a more Brussels-centred arrangement; Switzerland combines similar network intensity and node dependence with a more explicit long-term link between service concepts, infrastructure and financing. The comparison shows that individual Dutch characteristics are shared, while their interaction creates a tightly coupled national allocation profile. For the European transition, early capacity products require explicit validation status, a governed service--capacity interface and traceability across planning horizons. The RCAF is offered as a common qualitative language, not a performance score or universal taxonomy. ...
The RCAF is applied in a qualitative case study centred on the Netherlands, with supporting applications to Belgium and Switzerland. Evidence combines literature, documents, network indicators and interviews involving 30 participants. Dutch capacity allocation connects a dense and polycentric network, mixed and strongly periodic services, nationwide microscopic annual-timetable planning years ahead, and formal infrastructure-manager responsibility with production knowledge distributed across actors. Belgium shares the macro-micro transition problem in a more Brussels-centred arrangement; Switzerland combines similar network intensity and node dependence with a more explicit long-term link between service concepts, infrastructure and financing. The comparison shows that individual Dutch characteristics are shared, while their interaction creates a tightly coupled national allocation profile. For the European transition, early capacity products require explicit validation status, a governed service--capacity interface and traceability across planning horizons. The RCAF is offered as a common qualitative language, not a performance score or universal taxonomy. ...
European railway capacity management is moving towards earlier capacity strategies, models and offers. These products must be translated into feasible national timetables, but the literature commonly treats technical capacity, line and timetable design, and institutional allocation separately. This paper develops the Railway Capacity Allocation Framework (RCAF), a literature-derived, relational characterisation framework with three dimensions: physical-technical configuration, train-service and timetable configuration, and institutional capacity-allocation arrangement. The dimensions are specified through eight sub-dimensions; train-service formation and timetable construction are mutually dependent within the second dimension. Four relations concern capacity use and feasibility, service formation and allocation, capacity definition and infrastructure provision, and macro-micro translation.
The RCAF is applied in a qualitative case study centred on the Netherlands, with supporting applications to Belgium and Switzerland. Evidence combines literature, documents, network indicators and interviews involving 30 participants. Dutch capacity allocation connects a dense and polycentric network, mixed and strongly periodic services, nationwide microscopic annual-timetable planning years ahead, and formal infrastructure-manager responsibility with production knowledge distributed across actors. Belgium shares the macro-micro transition problem in a more Brussels-centred arrangement; Switzerland combines similar network intensity and node dependence with a more explicit long-term link between service concepts, infrastructure and financing. The comparison shows that individual Dutch characteristics are shared, while their interaction creates a tightly coupled national allocation profile. For the European transition, early capacity products require explicit validation status, a governed service--capacity interface and traceability across planning horizons. The RCAF is offered as a common qualitative language, not a performance score or universal taxonomy.
The RCAF is applied in a qualitative case study centred on the Netherlands, with supporting applications to Belgium and Switzerland. Evidence combines literature, documents, network indicators and interviews involving 30 participants. Dutch capacity allocation connects a dense and polycentric network, mixed and strongly periodic services, nationwide microscopic annual-timetable planning years ahead, and formal infrastructure-manager responsibility with production knowledge distributed across actors. Belgium shares the macro-micro transition problem in a more Brussels-centred arrangement; Switzerland combines similar network intensity and node dependence with a more explicit long-term link between service concepts, infrastructure and financing. The comparison shows that individual Dutch characteristics are shared, while their interaction creates a tightly coupled national allocation profile. For the European transition, early capacity products require explicit validation status, a governed service--capacity interface and traceability across planning horizons. The RCAF is offered as a common qualitative language, not a performance score or universal taxonomy.
Migration from legacy railway signalling to the European Rail Traffic Management System/European Train Control System (ERTMS/ETCS) must be phased while the railway remains operational. Existing deployment studies primarily address feasibility and cost, rather than using the performance of intermediate network states to guide implementation. This paper develops a multi-period optimisation approach that integrates network performance into strategic migration decisions. It is applied to the Dutch railway network, represented by 340 consolidated implementation units. Global efficiency and meshedness are converted into vertex-level gains that are either calculated once or updated after each implementation decision. The gains enter a lexicographic objective that prioritises network performance, followed by cost and completion time. A holistic mixed-integer linear programme is compared with sequential fixed-gain and dynamic-gain procedures under budget, implementation capacity, asset end-of-life, transition cost and regulatory target constraints. The holistic model achieves a 5.9\% (meshedness) to 9.4\% (global efficiency) higher cumulative network performance than the sequential fixed model. The sequential dynamic model produces more spatially connected intermediate networks and completes earlier and at lower cost than its fixed counterpart. Under global efficiency, its computation time is approximately one-tenth as long. Optimising global efficiency improves intermediate connectivity at a cost increase of approximately 14.6\% relative to cost-only optimisation. Sensitivity analysis identifies available implementation time, rather than budget, as the main constraint on target compliance. The results show that planning horizon and indicator updating materially affect migration sequences and should be considered explicitly in long-term railway signalling transitions.
...
Migration from legacy railway signalling to the European Rail Traffic Management System/European Train Control System (ERTMS/ETCS) must be phased while the railway remains operational. Existing deployment studies primarily address feasibility and cost, rather than using the performance of intermediate network states to guide implementation. This paper develops a multi-period optimisation approach that integrates network performance into strategic migration decisions. It is applied to the Dutch railway network, represented by 340 consolidated implementation units. Global efficiency and meshedness are converted into vertex-level gains that are either calculated once or updated after each implementation decision. The gains enter a lexicographic objective that prioritises network performance, followed by cost and completion time. A holistic mixed-integer linear programme is compared with sequential fixed-gain and dynamic-gain procedures under budget, implementation capacity, asset end-of-life, transition cost and regulatory target constraints. The holistic model achieves a 5.9\% (meshedness) to 9.4\% (global efficiency) higher cumulative network performance than the sequential fixed model. The sequential dynamic model produces more spatially connected intermediate networks and completes earlier and at lower cost than its fixed counterpart. Under global efficiency, its computation time is approximately one-tenth as long. Optimising global efficiency improves intermediate connectivity at a cost increase of approximately 14.6\% relative to cost-only optimisation. Sensitivity analysis identifies available implementation time, rather than budget, as the main constraint on target compliance. The results show that planning horizon and indicator updating materially affect migration sequences and should be considered explicitly in long-term railway signalling transitions.
Rail transit has long been important in Europe, and with it challenges such as interoperability between the rail transportation systems of its member states. To resolve this, the common standards of the European Rail Traffic Management System (ERTMS), including the European Train Control System (ETCS) have been and continue to be developed. While the adoption of this system increases, so does its technical development. The latter includes the recent addition of specifications for Automatic Train Operation (ATO) over ETCS.
ETCS, in order fulfil its role as a control system, has a broad set of functions. Among the core of these is the ability to monitor train motion in terms of distance and speed. But ETCS goes further and supervises these for safety. Doing this requires being able to make predictions and responses, and that requires having a model of train motion, including how that motion is stopped through braking. In 2023, the European Union Agency for Railways (ERA) introduced version 4.0.0 of its train braking model within ETCS. This braking model is of greatly increased complexity and sophistication compared to a more conventional, simpler, constant, just-in-time braking model.
This thesis sought to examine what impact, if any, this new model’s braking curve supervision would have on train trajectories, blocking times, pairwise minimum headway and homogenous train throughput in a corridor for ATO-driven trains. It was examined using the Hanzelijn corridor between Lelystad Centrum and Zwolle Station as a case study. This was done by starting with an existing Python implementation of a train motion model, produced by Wang et al. (2025). This was then modified to replace the conventional braking model used with an implementation that brakes the train following the ETCS Warning (W) Curve as defined in the official ERA specification. This implementation was verified by checking against separate calculations in Microsoft Excel and with a set of test cases run in the ERA’s own Braking Curve Simulation Tool (provided by the ERA to help implementation of this new and complex model.)
This implementation was then used to examine the impact of different configurations of the relevant parameters of the model, in particular braking rates, overlap distances, and balise layouts. The implementation, with a specific set of parameters, then examined the effect of the new braking model along the Dutch Hanzelijn corridor using three different ATO strategies: Minimum Time Train Control (MTTC), Reduced Maximum Speed (RMS), and Energy Efficient Train Control (EETC). This was investigated in terms of effects on speed profiles, impact to blocking time diagrams, and impact to pairwise minimum headway and homogenous train throughput.
It was found that the MTTC driving strategy was the most affected, with braking sections starting and ending 63 m and 47 m earlier respectively under the new model at a speed limit reduction of 160 km/h to 140 km/h; block reservations starting up to 5.4s earlier; and minimum headway increasing from 204.63 s to 206.19 s. The RMS and EETC driving strategies were affected in a similar manner but to a lesser extent. This was due to having fewer braking regimes in their motion. Blocking time diagrams were frequently impacted. The start times of block reservations were often affected because of the approach times being impacted by braking changes. These impacts were again minor in magnitude, however. Lastly in terms of throughput, the new braking model caused an increase in minimum headway of 1.56 s (0.76%) and a resultant reduction in throughput of 0.13 trains/hour (0.74%).
The conclusion was thus that, for the Hanzelijn case with the selected train and guideway parameters, the conventional, constant, just-in-time braking model, is a good approximation in terms of homogenous train throughput for the new, far more sophisticated braking model, with some larger differences of blocking times and trajectories near braking targets. The braking rate used in the conventional model, however, was 34% lower than the lowest available rate in the ETCS Braking Model.
...
ETCS, in order fulfil its role as a control system, has a broad set of functions. Among the core of these is the ability to monitor train motion in terms of distance and speed. But ETCS goes further and supervises these for safety. Doing this requires being able to make predictions and responses, and that requires having a model of train motion, including how that motion is stopped through braking. In 2023, the European Union Agency for Railways (ERA) introduced version 4.0.0 of its train braking model within ETCS. This braking model is of greatly increased complexity and sophistication compared to a more conventional, simpler, constant, just-in-time braking model.
This thesis sought to examine what impact, if any, this new model’s braking curve supervision would have on train trajectories, blocking times, pairwise minimum headway and homogenous train throughput in a corridor for ATO-driven trains. It was examined using the Hanzelijn corridor between Lelystad Centrum and Zwolle Station as a case study. This was done by starting with an existing Python implementation of a train motion model, produced by Wang et al. (2025). This was then modified to replace the conventional braking model used with an implementation that brakes the train following the ETCS Warning (W) Curve as defined in the official ERA specification. This implementation was verified by checking against separate calculations in Microsoft Excel and with a set of test cases run in the ERA’s own Braking Curve Simulation Tool (provided by the ERA to help implementation of this new and complex model.)
This implementation was then used to examine the impact of different configurations of the relevant parameters of the model, in particular braking rates, overlap distances, and balise layouts. The implementation, with a specific set of parameters, then examined the effect of the new braking model along the Dutch Hanzelijn corridor using three different ATO strategies: Minimum Time Train Control (MTTC), Reduced Maximum Speed (RMS), and Energy Efficient Train Control (EETC). This was investigated in terms of effects on speed profiles, impact to blocking time diagrams, and impact to pairwise minimum headway and homogenous train throughput.
It was found that the MTTC driving strategy was the most affected, with braking sections starting and ending 63 m and 47 m earlier respectively under the new model at a speed limit reduction of 160 km/h to 140 km/h; block reservations starting up to 5.4s earlier; and minimum headway increasing from 204.63 s to 206.19 s. The RMS and EETC driving strategies were affected in a similar manner but to a lesser extent. This was due to having fewer braking regimes in their motion. Blocking time diagrams were frequently impacted. The start times of block reservations were often affected because of the approach times being impacted by braking changes. These impacts were again minor in magnitude, however. Lastly in terms of throughput, the new braking model caused an increase in minimum headway of 1.56 s (0.76%) and a resultant reduction in throughput of 0.13 trains/hour (0.74%).
The conclusion was thus that, for the Hanzelijn case with the selected train and guideway parameters, the conventional, constant, just-in-time braking model, is a good approximation in terms of homogenous train throughput for the new, far more sophisticated braking model, with some larger differences of blocking times and trajectories near braking targets. The braking rate used in the conventional model, however, was 34% lower than the lowest available rate in the ETCS Braking Model.
...
Rail transit has long been important in Europe, and with it challenges such as interoperability between the rail transportation systems of its member states. To resolve this, the common standards of the European Rail Traffic Management System (ERTMS), including the European Train Control System (ETCS) have been and continue to be developed. While the adoption of this system increases, so does its technical development. The latter includes the recent addition of specifications for Automatic Train Operation (ATO) over ETCS.
ETCS, in order fulfil its role as a control system, has a broad set of functions. Among the core of these is the ability to monitor train motion in terms of distance and speed. But ETCS goes further and supervises these for safety. Doing this requires being able to make predictions and responses, and that requires having a model of train motion, including how that motion is stopped through braking. In 2023, the European Union Agency for Railways (ERA) introduced version 4.0.0 of its train braking model within ETCS. This braking model is of greatly increased complexity and sophistication compared to a more conventional, simpler, constant, just-in-time braking model.
This thesis sought to examine what impact, if any, this new model’s braking curve supervision would have on train trajectories, blocking times, pairwise minimum headway and homogenous train throughput in a corridor for ATO-driven trains. It was examined using the Hanzelijn corridor between Lelystad Centrum and Zwolle Station as a case study. This was done by starting with an existing Python implementation of a train motion model, produced by Wang et al. (2025). This was then modified to replace the conventional braking model used with an implementation that brakes the train following the ETCS Warning (W) Curve as defined in the official ERA specification. This implementation was verified by checking against separate calculations in Microsoft Excel and with a set of test cases run in the ERA’s own Braking Curve Simulation Tool (provided by the ERA to help implementation of this new and complex model.)
This implementation was then used to examine the impact of different configurations of the relevant parameters of the model, in particular braking rates, overlap distances, and balise layouts. The implementation, with a specific set of parameters, then examined the effect of the new braking model along the Dutch Hanzelijn corridor using three different ATO strategies: Minimum Time Train Control (MTTC), Reduced Maximum Speed (RMS), and Energy Efficient Train Control (EETC). This was investigated in terms of effects on speed profiles, impact to blocking time diagrams, and impact to pairwise minimum headway and homogenous train throughput.
It was found that the MTTC driving strategy was the most affected, with braking sections starting and ending 63 m and 47 m earlier respectively under the new model at a speed limit reduction of 160 km/h to 140 km/h; block reservations starting up to 5.4s earlier; and minimum headway increasing from 204.63 s to 206.19 s. The RMS and EETC driving strategies were affected in a similar manner but to a lesser extent. This was due to having fewer braking regimes in their motion. Blocking time diagrams were frequently impacted. The start times of block reservations were often affected because of the approach times being impacted by braking changes. These impacts were again minor in magnitude, however. Lastly in terms of throughput, the new braking model caused an increase in minimum headway of 1.56 s (0.76%) and a resultant reduction in throughput of 0.13 trains/hour (0.74%).
The conclusion was thus that, for the Hanzelijn case with the selected train and guideway parameters, the conventional, constant, just-in-time braking model, is a good approximation in terms of homogenous train throughput for the new, far more sophisticated braking model, with some larger differences of blocking times and trajectories near braking targets. The braking rate used in the conventional model, however, was 34% lower than the lowest available rate in the ETCS Braking Model.
ETCS, in order fulfil its role as a control system, has a broad set of functions. Among the core of these is the ability to monitor train motion in terms of distance and speed. But ETCS goes further and supervises these for safety. Doing this requires being able to make predictions and responses, and that requires having a model of train motion, including how that motion is stopped through braking. In 2023, the European Union Agency for Railways (ERA) introduced version 4.0.0 of its train braking model within ETCS. This braking model is of greatly increased complexity and sophistication compared to a more conventional, simpler, constant, just-in-time braking model.
This thesis sought to examine what impact, if any, this new model’s braking curve supervision would have on train trajectories, blocking times, pairwise minimum headway and homogenous train throughput in a corridor for ATO-driven trains. It was examined using the Hanzelijn corridor between Lelystad Centrum and Zwolle Station as a case study. This was done by starting with an existing Python implementation of a train motion model, produced by Wang et al. (2025). This was then modified to replace the conventional braking model used with an implementation that brakes the train following the ETCS Warning (W) Curve as defined in the official ERA specification. This implementation was verified by checking against separate calculations in Microsoft Excel and with a set of test cases run in the ERA’s own Braking Curve Simulation Tool (provided by the ERA to help implementation of this new and complex model.)
This implementation was then used to examine the impact of different configurations of the relevant parameters of the model, in particular braking rates, overlap distances, and balise layouts. The implementation, with a specific set of parameters, then examined the effect of the new braking model along the Dutch Hanzelijn corridor using three different ATO strategies: Minimum Time Train Control (MTTC), Reduced Maximum Speed (RMS), and Energy Efficient Train Control (EETC). This was investigated in terms of effects on speed profiles, impact to blocking time diagrams, and impact to pairwise minimum headway and homogenous train throughput.
It was found that the MTTC driving strategy was the most affected, with braking sections starting and ending 63 m and 47 m earlier respectively under the new model at a speed limit reduction of 160 km/h to 140 km/h; block reservations starting up to 5.4s earlier; and minimum headway increasing from 204.63 s to 206.19 s. The RMS and EETC driving strategies were affected in a similar manner but to a lesser extent. This was due to having fewer braking regimes in their motion. Blocking time diagrams were frequently impacted. The start times of block reservations were often affected because of the approach times being impacted by braking changes. These impacts were again minor in magnitude, however. Lastly in terms of throughput, the new braking model caused an increase in minimum headway of 1.56 s (0.76%) and a resultant reduction in throughput of 0.13 trains/hour (0.74%).
The conclusion was thus that, for the Hanzelijn case with the selected train and guideway parameters, the conventional, constant, just-in-time braking model, is a good approximation in terms of homogenous train throughput for the new, far more sophisticated braking model, with some larger differences of blocking times and trajectories near braking targets. The braking rate used in the conventional model, however, was 34% lower than the lowest available rate in the ETCS Braking Model.
Railway incident response requires rapid dispatching while maintaining sufficient responder availability for subsequent incidents. Existing approaches primarily minimise travel time to the current incident, although each assignment also affects future responder workload, availability and geographical distribution. This study develops a sequential event-based optimisation framework for real-time railway incident dispatching that incorporates these system-level consequences. Three optimisation models focusing on workload balancing and geographical coverage are compared with ProRail’s travel-timebased Smart Alerting model across 48 simulation scenarios. The results show that the added value of optimisation increases as consecutive dispatching decisions become more interdependent. The Workload Model provides the strongest and most
consistent overall performance, substantially reducing excessive workload under demanding conditions while generally maintaining competitive travel times relative to the baseline. In contrast, the anticipated travel-time improvements of the Coverage Models do not materialise consistently. These findings demonstrate that workload-based optimisation provides a promising foundation for moving from incident-oriented responder assignments towards a more system-oriented approach to real-time railway incident dispatching. ...
consistent overall performance, substantially reducing excessive workload under demanding conditions while generally maintaining competitive travel times relative to the baseline. In contrast, the anticipated travel-time improvements of the Coverage Models do not materialise consistently. These findings demonstrate that workload-based optimisation provides a promising foundation for moving from incident-oriented responder assignments towards a more system-oriented approach to real-time railway incident dispatching. ...
Railway incident response requires rapid dispatching while maintaining sufficient responder availability for subsequent incidents. Existing approaches primarily minimise travel time to the current incident, although each assignment also affects future responder workload, availability and geographical distribution. This study develops a sequential event-based optimisation framework for real-time railway incident dispatching that incorporates these system-level consequences. Three optimisation models focusing on workload balancing and geographical coverage are compared with ProRail’s travel-timebased Smart Alerting model across 48 simulation scenarios. The results show that the added value of optimisation increases as consecutive dispatching decisions become more interdependent. The Workload Model provides the strongest and most
consistent overall performance, substantially reducing excessive workload under demanding conditions while generally maintaining competitive travel times relative to the baseline. In contrast, the anticipated travel-time improvements of the Coverage Models do not materialise consistently. These findings demonstrate that workload-based optimisation provides a promising foundation for moving from incident-oriented responder assignments towards a more system-oriented approach to real-time railway incident dispatching.
consistent overall performance, substantially reducing excessive workload under demanding conditions while generally maintaining competitive travel times relative to the baseline. In contrast, the anticipated travel-time improvements of the Coverage Models do not materialise consistently. These findings demonstrate that workload-based optimisation provides a promising foundation for moving from incident-oriented responder assignments towards a more system-oriented approach to real-time railway incident dispatching.
Automatic planning for railway shunting yards in the Netherlands is a challenging problem, as these yards form a critical link between rolling stock circulation and the timetable. Trains must be decoupled, coupled, serviced, and departed within tight time windows, while infrastructure and train drivers are limited. The resulting planning problem is large-scale, highly constrained, and characterized by strong interdependencies between operational and driver decisions. In the current state-of-the-art approach, driver scheduling is handled by a heuristic procedure embedded within a local search algorithm. While efficient, this restricts the decision space and may yield suboptimal plans.
This thesis investigates how integrating driver-scheduling decisions into the main local search affects solution quality and search performance. Several integration mechanisms are presented, with increasing levels of integration of driver scheduling decisions. Computational experiments on realistic instances show that integrating driver decisions into the local search consistently improves performance compared to the state-of-the-art approach. Under small time budgets, the greatest improvements are obtained when only part of the driver decision space is integrated, allowing the search to correct harmful heuristic decisions while keeping the search space manageable. With larger time budgets, more integrated methods catch up, indicating that the richer decision space can be exploited when sufficient time is available.
To manage the increase in search space complexity, a novel two-stage search scheme is introduced in which the algorithm first optimizes while keeping driver decisions heuristically decided, and subsequently activates explicit driver-related decision variables. Experiments show that dividing the available computation time between these two stages yields better results than allocating the entire time budget to either stage. This demonstrates that progressive enlargement of the decision space can effectively balance model expressiveness and computational tractability. ...
This thesis investigates how integrating driver-scheduling decisions into the main local search affects solution quality and search performance. Several integration mechanisms are presented, with increasing levels of integration of driver scheduling decisions. Computational experiments on realistic instances show that integrating driver decisions into the local search consistently improves performance compared to the state-of-the-art approach. Under small time budgets, the greatest improvements are obtained when only part of the driver decision space is integrated, allowing the search to correct harmful heuristic decisions while keeping the search space manageable. With larger time budgets, more integrated methods catch up, indicating that the richer decision space can be exploited when sufficient time is available.
To manage the increase in search space complexity, a novel two-stage search scheme is introduced in which the algorithm first optimizes while keeping driver decisions heuristically decided, and subsequently activates explicit driver-related decision variables. Experiments show that dividing the available computation time between these two stages yields better results than allocating the entire time budget to either stage. This demonstrates that progressive enlargement of the decision space can effectively balance model expressiveness and computational tractability. ...
Automatic planning for railway shunting yards in the Netherlands is a challenging problem, as these yards form a critical link between rolling stock circulation and the timetable. Trains must be decoupled, coupled, serviced, and departed within tight time windows, while infrastructure and train drivers are limited. The resulting planning problem is large-scale, highly constrained, and characterized by strong interdependencies between operational and driver decisions. In the current state-of-the-art approach, driver scheduling is handled by a heuristic procedure embedded within a local search algorithm. While efficient, this restricts the decision space and may yield suboptimal plans.
This thesis investigates how integrating driver-scheduling decisions into the main local search affects solution quality and search performance. Several integration mechanisms are presented, with increasing levels of integration of driver scheduling decisions. Computational experiments on realistic instances show that integrating driver decisions into the local search consistently improves performance compared to the state-of-the-art approach. Under small time budgets, the greatest improvements are obtained when only part of the driver decision space is integrated, allowing the search to correct harmful heuristic decisions while keeping the search space manageable. With larger time budgets, more integrated methods catch up, indicating that the richer decision space can be exploited when sufficient time is available.
To manage the increase in search space complexity, a novel two-stage search scheme is introduced in which the algorithm first optimizes while keeping driver decisions heuristically decided, and subsequently activates explicit driver-related decision variables. Experiments show that dividing the available computation time between these two stages yields better results than allocating the entire time budget to either stage. This demonstrates that progressive enlargement of the decision space can effectively balance model expressiveness and computational tractability.
This thesis investigates how integrating driver-scheduling decisions into the main local search affects solution quality and search performance. Several integration mechanisms are presented, with increasing levels of integration of driver scheduling decisions. Computational experiments on realistic instances show that integrating driver decisions into the local search consistently improves performance compared to the state-of-the-art approach. Under small time budgets, the greatest improvements are obtained when only part of the driver decision space is integrated, allowing the search to correct harmful heuristic decisions while keeping the search space manageable. With larger time budgets, more integrated methods catch up, indicating that the richer decision space can be exploited when sufficient time is available.
To manage the increase in search space complexity, a novel two-stage search scheme is introduced in which the algorithm first optimizes while keeping driver decisions heuristically decided, and subsequently activates explicit driver-related decision variables. Experiments show that dividing the available computation time between these two stages yields better results than allocating the entire time budget to either stage. This demonstrates that progressive enlargement of the decision space can effectively balance model expressiveness and computational tractability.
Introducing flexibility in any-start-time safe interval path planning
A case study on the Dutch railway network
During the daily operation of the railway network, ProRail is responsible for handling delays and planning ad hoc train movements. Train handling documents aid the traffic controllers in common situations. But when multiple trains are delayed, and these documents do not apply, they are left to their own expertise.
In this thesis, we introduce FlexSIPP, an algorithm to plan or replan agents in an existing multi-agent plan. FlexSIPP builds upon the prior works of any-start-time safe interval path planning, where the current routes of the agents are seen as moving obstacles. FlexSIPP loosens this restriction by introducing flexibility: the ability for an agent to delay its plan while minimally impacting other agents.
This algorithm is evaluated on the Dutch railway network. By finding tipping points, that is, the moment it is better to switch the order of two trains on the track to minimize the delay, we can recreate train handling documents. We show that FlexSIPP finds the same solutions within a minute in the case that no other trains are delayed. This implies that FlexSIPP is also able to aid traffic controllers in the case that other trains are delayed ...
In this thesis, we introduce FlexSIPP, an algorithm to plan or replan agents in an existing multi-agent plan. FlexSIPP builds upon the prior works of any-start-time safe interval path planning, where the current routes of the agents are seen as moving obstacles. FlexSIPP loosens this restriction by introducing flexibility: the ability for an agent to delay its plan while minimally impacting other agents.
This algorithm is evaluated on the Dutch railway network. By finding tipping points, that is, the moment it is better to switch the order of two trains on the track to minimize the delay, we can recreate train handling documents. We show that FlexSIPP finds the same solutions within a minute in the case that no other trains are delayed. This implies that FlexSIPP is also able to aid traffic controllers in the case that other trains are delayed ...
During the daily operation of the railway network, ProRail is responsible for handling delays and planning ad hoc train movements. Train handling documents aid the traffic controllers in common situations. But when multiple trains are delayed, and these documents do not apply, they are left to their own expertise.
In this thesis, we introduce FlexSIPP, an algorithm to plan or replan agents in an existing multi-agent plan. FlexSIPP builds upon the prior works of any-start-time safe interval path planning, where the current routes of the agents are seen as moving obstacles. FlexSIPP loosens this restriction by introducing flexibility: the ability for an agent to delay its plan while minimally impacting other agents.
This algorithm is evaluated on the Dutch railway network. By finding tipping points, that is, the moment it is better to switch the order of two trains on the track to minimize the delay, we can recreate train handling documents. We show that FlexSIPP finds the same solutions within a minute in the case that no other trains are delayed. This implies that FlexSIPP is also able to aid traffic controllers in the case that other trains are delayed
In this thesis, we introduce FlexSIPP, an algorithm to plan or replan agents in an existing multi-agent plan. FlexSIPP builds upon the prior works of any-start-time safe interval path planning, where the current routes of the agents are seen as moving obstacles. FlexSIPP loosens this restriction by introducing flexibility: the ability for an agent to delay its plan while minimally impacting other agents.
This algorithm is evaluated on the Dutch railway network. By finding tipping points, that is, the moment it is better to switch the order of two trains on the track to minimize the delay, we can recreate train handling documents. We show that FlexSIPP finds the same solutions within a minute in the case that no other trains are delayed. This implies that FlexSIPP is also able to aid traffic controllers in the case that other trains are delayed
Passenger-centric robust timetabling in railways
A case study for the Eindhoven-Den Bosch-Tilburg network
Punctuality in railway transport is a critical concern for passengers, especially during unavoidable disturbances. Therefore, a sufficiently robust timetable is necessary. This thesis proposes a new timetabling method that minimizes passenger delay as the optimization objective, aiming to create a passenger-centric robust timetable. The model is implemented in the Dutch railway network in the Eindhoven-Den Bosch-Tilburg area to verify and validate its correctness and functionality. Experimental results demonstrate that the proposed model significantly reduces passenger delays when dealing with specific disturbances, and the improvement in robustness becomes more pronounced as the severity of the disturbances increases.
...
Punctuality in railway transport is a critical concern for passengers, especially during unavoidable disturbances. Therefore, a sufficiently robust timetable is necessary. This thesis proposes a new timetabling method that minimizes passenger delay as the optimization objective, aiming to create a passenger-centric robust timetable. The model is implemented in the Dutch railway network in the Eindhoven-Den Bosch-Tilburg area to verify and validate its correctness and functionality. Experimental results demonstrate that the proposed model significantly reduces passenger delays when dealing with specific disturbances, and the improvement in robustness becomes more pronounced as the severity of the disturbances increases.
Optimizing Railway Infrastructure to Meet Future Demand
A Macroscopic Timetabling Model
This paper proposes an innovative macroscopic timetabling model aiming to optimize railway infrastructure to accommodate the future increasing demand. The model applies the PESP formulation to railway operations and formulates it as a MILP model. The number of tracks on each portion of the infrastructure is flexible, and so are the conflicts between different trains. The model minimizes the overall construction and operation costs while ensuring a conflict-free timetable for the long-term demand. A case study on the Swedish Mälarbanan line demonstrates the model’s application and validates the microscopic feasibility of the produced timetables. Model shows promising results by suggesting low infrastructure upgrades while offering total travel times almost equivalent to the case where the entire line is upgraded.
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This paper proposes an innovative macroscopic timetabling model aiming to optimize railway infrastructure to accommodate the future increasing demand. The model applies the PESP formulation to railway operations and formulates it as a MILP model. The number of tracks on each portion of the infrastructure is flexible, and so are the conflicts between different trains. The model minimizes the overall construction and operation costs while ensuring a conflict-free timetable for the long-term demand. A case study on the Swedish Mälarbanan line demonstrates the model’s application and validates the microscopic feasibility of the produced timetables. Model shows promising results by suggesting low infrastructure upgrades while offering total travel times almost equivalent to the case where the entire line is upgraded.
Robust Shunting in a Dynamic Environment
Deriving Proactive Schedules from a Reactive Policy
When trains are not actively traveling on the main rail network, they to be parked and prepared for their next journey. This is a complex problem, involving several interconnected subproblems. Additionally, there is uncertainty in this environment which can render initial plans infeasible during their execution. To ensure trains are able to depart in time, having finished all their required service tasks, a schedule is created in advance.
The focus of this thesis is to address the challenges associated with generating robust initial shunting plans in an uncertain environment. This thesis focuses on a sequential problem formulation, modeled as a Markov Decision Process (MDP) and uses a policy optimized for this environment. The goal is to design a method capable of deriving robust initial shunting plans from the policy that are likely to remain feasible for a large number of possible plan executions.
The limitation addressed in this thesis, is that conventional policy-rollout techniques generate action sequences that overlook most alternative outcomes, thereby making the overall plan not feasible for a large number of plan realizations. To address this issue, the thesis proposes two distinct solution methods, aimed to consider every possible state that might be encountered, either directly or indirectly.
Through experimentation on realistically generated problem instances, the research concludes that both proposed methods significantly outperform the baseline approach, demonstrating the possibility of extracting robust initial shunting plans from a given policy that was not explicitly designed for this purpose. ...
The focus of this thesis is to address the challenges associated with generating robust initial shunting plans in an uncertain environment. This thesis focuses on a sequential problem formulation, modeled as a Markov Decision Process (MDP) and uses a policy optimized for this environment. The goal is to design a method capable of deriving robust initial shunting plans from the policy that are likely to remain feasible for a large number of possible plan executions.
The limitation addressed in this thesis, is that conventional policy-rollout techniques generate action sequences that overlook most alternative outcomes, thereby making the overall plan not feasible for a large number of plan realizations. To address this issue, the thesis proposes two distinct solution methods, aimed to consider every possible state that might be encountered, either directly or indirectly.
Through experimentation on realistically generated problem instances, the research concludes that both proposed methods significantly outperform the baseline approach, demonstrating the possibility of extracting robust initial shunting plans from a given policy that was not explicitly designed for this purpose. ...
When trains are not actively traveling on the main rail network, they to be parked and prepared for their next journey. This is a complex problem, involving several interconnected subproblems. Additionally, there is uncertainty in this environment which can render initial plans infeasible during their execution. To ensure trains are able to depart in time, having finished all their required service tasks, a schedule is created in advance.
The focus of this thesis is to address the challenges associated with generating robust initial shunting plans in an uncertain environment. This thesis focuses on a sequential problem formulation, modeled as a Markov Decision Process (MDP) and uses a policy optimized for this environment. The goal is to design a method capable of deriving robust initial shunting plans from the policy that are likely to remain feasible for a large number of possible plan executions.
The limitation addressed in this thesis, is that conventional policy-rollout techniques generate action sequences that overlook most alternative outcomes, thereby making the overall plan not feasible for a large number of plan realizations. To address this issue, the thesis proposes two distinct solution methods, aimed to consider every possible state that might be encountered, either directly or indirectly.
Through experimentation on realistically generated problem instances, the research concludes that both proposed methods significantly outperform the baseline approach, demonstrating the possibility of extracting robust initial shunting plans from a given policy that was not explicitly designed for this purpose.
The focus of this thesis is to address the challenges associated with generating robust initial shunting plans in an uncertain environment. This thesis focuses on a sequential problem formulation, modeled as a Markov Decision Process (MDP) and uses a policy optimized for this environment. The goal is to design a method capable of deriving robust initial shunting plans from the policy that are likely to remain feasible for a large number of possible plan executions.
The limitation addressed in this thesis, is that conventional policy-rollout techniques generate action sequences that overlook most alternative outcomes, thereby making the overall plan not feasible for a large number of plan realizations. To address this issue, the thesis proposes two distinct solution methods, aimed to consider every possible state that might be encountered, either directly or indirectly.
Through experimentation on realistically generated problem instances, the research concludes that both proposed methods significantly outperform the baseline approach, demonstrating the possibility of extracting robust initial shunting plans from a given policy that was not explicitly designed for this purpose.
Over 700 trains in the Netherlands are used daily for passenger transportation. Train operations involve tasks like parking, recombination, cleaning, and maintenance, which take place in shunting yards. The train unit shunting problem (TUSP) is a complex planning problem made more difficult by uncertainties such as delays. Most existing approaches overlook these disturbances and the approaches that consider them incorporate heuristics to enhance the robustness of their solutions to disturbances. This thesis proposes an alternative approach: utilizing probabilistic programming to turn an existing planning algorithm and simulator into a generative model of the TUSP. The model introduces disturbances without the need to modify the planning algorithm or simulator. Through two types of inference, we infer a distribution of robust solutions for the TUSP. Empirical results demonstrate the effectiveness of our approach for inferring robust plans in small-scale scenarios.
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Over 700 trains in the Netherlands are used daily for passenger transportation. Train operations involve tasks like parking, recombination, cleaning, and maintenance, which take place in shunting yards. The train unit shunting problem (TUSP) is a complex planning problem made more difficult by uncertainties such as delays. Most existing approaches overlook these disturbances and the approaches that consider them incorporate heuristics to enhance the robustness of their solutions to disturbances. This thesis proposes an alternative approach: utilizing probabilistic programming to turn an existing planning algorithm and simulator into a generative model of the TUSP. The model introduces disturbances without the need to modify the planning algorithm or simulator. Through two types of inference, we infer a distribution of robust solutions for the TUSP. Empirical results demonstrate the effectiveness of our approach for inferring robust plans in small-scale scenarios.
To develop a demand-oriented train service plan, the railway passenger demand characteristics are needed to be analyzed first. The analysis mainly starts with the volume and structure of the demand, and based on these characteristics, periods that have similar characteristics are classified into the same pattern. Thus a period of time, for example, a week, can be divided into several periods with different demand patterns. One period is considered as the base demand period among all those periods, and the demand contained in this period is always present during the week, its fluctuations are small and occupy the vast majority of the time except for the peak period.
Unlike the existing method that the train service is designed according to the peak hour demand, the train plan will first be designed based on the base demand. This base service will exist all through the period (e.g. in one week) and provide service for all base demand services. The service adaption will be made and added to the base service for all other periods. According to the different demand patterns, those adaptions can be add-on or subtracted services. Those adaptions can adjust the service to match the changed demand over time. ...
Unlike the existing method that the train service is designed according to the peak hour demand, the train plan will first be designed based on the base demand. This base service will exist all through the period (e.g. in one week) and provide service for all base demand services. The service adaption will be made and added to the base service for all other periods. According to the different demand patterns, those adaptions can be add-on or subtracted services. Those adaptions can adjust the service to match the changed demand over time. ...
To develop a demand-oriented train service plan, the railway passenger demand characteristics are needed to be analyzed first. The analysis mainly starts with the volume and structure of the demand, and based on these characteristics, periods that have similar characteristics are classified into the same pattern. Thus a period of time, for example, a week, can be divided into several periods with different demand patterns. One period is considered as the base demand period among all those periods, and the demand contained in this period is always present during the week, its fluctuations are small and occupy the vast majority of the time except for the peak period.
Unlike the existing method that the train service is designed according to the peak hour demand, the train plan will first be designed based on the base demand. This base service will exist all through the period (e.g. in one week) and provide service for all base demand services. The service adaption will be made and added to the base service for all other periods. According to the different demand patterns, those adaptions can be add-on or subtracted services. Those adaptions can adjust the service to match the changed demand over time.
Unlike the existing method that the train service is designed according to the peak hour demand, the train plan will first be designed based on the base demand. This base service will exist all through the period (e.g. in one week) and provide service for all base demand services. The service adaption will be made and added to the base service for all other periods. According to the different demand patterns, those adaptions can be add-on or subtracted services. Those adaptions can adjust the service to match the changed demand over time.
Master thesis
(2023)
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G.A.M. Hornung, Vasso Reppa, E. Quaglietta, D Middelkoop, R.M.P. Goverde, B. Atasoy
The Dutch railway network is a dense network with 7000 kilometers of railway tracks spread over only 42,000 square kilometers [1, 2]. Additionally, the railways are responsible for 1.4 million passengers every working day [1]. These factors make both the infrastructure and timetable of the Dutch railway network extremely intricate. On top of that, the number of train trips is expected to grow by 40% by 2040 [3], and with that the complexity of managing the railway network will increase even more.
In the case of conflicts in the timetable, action must be taken to resolve these conflicts in order for train operations to continue. In current Dutch practice, this task resides with train dispatchers. However, it can be difficult for the dispatcher to oversee the situation when multiple trains are involved, and actions taken will have consequences for other trains. This increasingly complex task has resulted in growing interest in so-called Traffic Management Systems (TMS), which are intelligent systems that use conflict resolution algorithms to find solutions to timetable conflicts.
A TMS can be used to support train dispatchers in managing railway traffic. ...
In the case of conflicts in the timetable, action must be taken to resolve these conflicts in order for train operations to continue. In current Dutch practice, this task resides with train dispatchers. However, it can be difficult for the dispatcher to oversee the situation when multiple trains are involved, and actions taken will have consequences for other trains. This increasingly complex task has resulted in growing interest in so-called Traffic Management Systems (TMS), which are intelligent systems that use conflict resolution algorithms to find solutions to timetable conflicts.
A TMS can be used to support train dispatchers in managing railway traffic. ...
The Dutch railway network is a dense network with 7000 kilometers of railway tracks spread over only 42,000 square kilometers [1, 2]. Additionally, the railways are responsible for 1.4 million passengers every working day [1]. These factors make both the infrastructure and timetable of the Dutch railway network extremely intricate. On top of that, the number of train trips is expected to grow by 40% by 2040 [3], and with that the complexity of managing the railway network will increase even more.
In the case of conflicts in the timetable, action must be taken to resolve these conflicts in order for train operations to continue. In current Dutch practice, this task resides with train dispatchers. However, it can be difficult for the dispatcher to oversee the situation when multiple trains are involved, and actions taken will have consequences for other trains. This increasingly complex task has resulted in growing interest in so-called Traffic Management Systems (TMS), which are intelligent systems that use conflict resolution algorithms to find solutions to timetable conflicts.
A TMS can be used to support train dispatchers in managing railway traffic.
In the case of conflicts in the timetable, action must be taken to resolve these conflicts in order for train operations to continue. In current Dutch practice, this task resides with train dispatchers. However, it can be difficult for the dispatcher to oversee the situation when multiple trains are involved, and actions taken will have consequences for other trains. This increasingly complex task has resulted in growing interest in so-called Traffic Management Systems (TMS), which are intelligent systems that use conflict resolution algorithms to find solutions to timetable conflicts.
A TMS can be used to support train dispatchers in managing railway traffic.
Master thesis
(2023)
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R. ZHOU, R.M.P. Goverde, Z. Wang, G. Homem de Almeida Correia, Edith Philipsen
With the strong backing and advocacy from the EU for railway transport, it is crucial to focus on innovative and efficient technologies to maintain service quality. In daily train operations, traffic uncertainties lead to perturbations, which may result in two types of track conflicts: disturbances and disruptions.
In the current research, we aim to add and optimize timetable flexibility in traffic disturbance management for railway transport. A new definition is proposed for timetable flexibility. Timetable flexibility is defined as the ability of a timetable to be easily modified to withstand small disturbances and absorb delays, as well as to offer a larger solution space in the application of dispatching measures (retiming, reordering, rerouting) to solve larger disturbances without changing the given (re)scheduled timetable.
In order to minimize the deviation of the rescheduling plan from the rigid timetable, and maximize the timetable flexibility, the conflict resolution problem is modeled using an Alternative Graph (AG)-based Mixed Integer Linear Programming (MILP) model.
In order to investigate the impacts of different parameter inputs on timetable flexibility, a case study is conducted on a part of the Dutch railway network. To investigate the influencing factors of timetable flexibility, one illustrative application and two sensitivity analyses are conducted. Based on the results, practical implications on train dispatchers and signalers, as well as on railway passengers are concluded. ...
In the current research, we aim to add and optimize timetable flexibility in traffic disturbance management for railway transport. A new definition is proposed for timetable flexibility. Timetable flexibility is defined as the ability of a timetable to be easily modified to withstand small disturbances and absorb delays, as well as to offer a larger solution space in the application of dispatching measures (retiming, reordering, rerouting) to solve larger disturbances without changing the given (re)scheduled timetable.
In order to minimize the deviation of the rescheduling plan from the rigid timetable, and maximize the timetable flexibility, the conflict resolution problem is modeled using an Alternative Graph (AG)-based Mixed Integer Linear Programming (MILP) model.
In order to investigate the impacts of different parameter inputs on timetable flexibility, a case study is conducted on a part of the Dutch railway network. To investigate the influencing factors of timetable flexibility, one illustrative application and two sensitivity analyses are conducted. Based on the results, practical implications on train dispatchers and signalers, as well as on railway passengers are concluded. ...
With the strong backing and advocacy from the EU for railway transport, it is crucial to focus on innovative and efficient technologies to maintain service quality. In daily train operations, traffic uncertainties lead to perturbations, which may result in two types of track conflicts: disturbances and disruptions.
In the current research, we aim to add and optimize timetable flexibility in traffic disturbance management for railway transport. A new definition is proposed for timetable flexibility. Timetable flexibility is defined as the ability of a timetable to be easily modified to withstand small disturbances and absorb delays, as well as to offer a larger solution space in the application of dispatching measures (retiming, reordering, rerouting) to solve larger disturbances without changing the given (re)scheduled timetable.
In order to minimize the deviation of the rescheduling plan from the rigid timetable, and maximize the timetable flexibility, the conflict resolution problem is modeled using an Alternative Graph (AG)-based Mixed Integer Linear Programming (MILP) model.
In order to investigate the impacts of different parameter inputs on timetable flexibility, a case study is conducted on a part of the Dutch railway network. To investigate the influencing factors of timetable flexibility, one illustrative application and two sensitivity analyses are conducted. Based on the results, practical implications on train dispatchers and signalers, as well as on railway passengers are concluded.
In the current research, we aim to add and optimize timetable flexibility in traffic disturbance management for railway transport. A new definition is proposed for timetable flexibility. Timetable flexibility is defined as the ability of a timetable to be easily modified to withstand small disturbances and absorb delays, as well as to offer a larger solution space in the application of dispatching measures (retiming, reordering, rerouting) to solve larger disturbances without changing the given (re)scheduled timetable.
In order to minimize the deviation of the rescheduling plan from the rigid timetable, and maximize the timetable flexibility, the conflict resolution problem is modeled using an Alternative Graph (AG)-based Mixed Integer Linear Programming (MILP) model.
In order to investigate the impacts of different parameter inputs on timetable flexibility, a case study is conducted on a part of the Dutch railway network. To investigate the influencing factors of timetable flexibility, one illustrative application and two sensitivity analyses are conducted. Based on the results, practical implications on train dispatchers and signalers, as well as on railway passengers are concluded.
Master thesis
(2022)
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Julian Aantjes, P.H.A.J.M. van Gelder, R.M.P. Goverde, W.M.T. Mennen, G.M. Verduijn
The Dutch railway transport system is a system of systems and also a sociotechnical system that will migrate to a radio-based signalling standard ERTMS (European Rail Traffic Management System). ERTMS will influence the train drivers and dispatchers the most, especially due to the introduction of the signalling and control element of ERTMS: the European train control system (ETCS). A reliability requirement for the migration towards ERTMS obligates to demonstrate that the reliability of the system stays the same or improves. Reliability can be quantified if all the possible risks are known, but identifying risks with traditional models is insufficient, because they do not capture the complexities and dynamics of socio-technical systems.
The hazard analysis technique ‘systems theoretic process analysis’ (STPA) is a promising technique to sufficiently identify hazards that models the system in a control structure and searches systematically for hazards. The main research question of this thesis is: ‘To what extent can STPA be applied to identify risks and determine the system reliability of interactions between ETCS, train drivers and dispatchers?’ What are the risks caused by those interactions and how can STPA be applied for an effective risk assessment are the two research objectives.
STPA consists of 4 structured steps. First the analysed system is described and the purpose of the analysis is set. The system is modelled in a control structure in the second step. The third step of STPA is to identify unsafe control actions with guided words. 27 unsafe control actions are identified for the 8 control actions that are present in the control structure. The last step of STPA is to identify loss scenarios that could lead to the unsafe control actions, those were formulated with system experts.
The desk research and this research demonstrates that STPA is completer and more thorough in identifying hazards than the tradition hazard analysis technique ‘failure mode effect and criticality analysis’ (FMECA). In this research, STPA identified 70 loss scenarios in the analysed procedure (compared to 4 issues identified with FMECA), those hazards ranged from missing or inadequate feedback mechanisms to inconsistent process models of the train drivers or dispatchers. STPA identified besides technical failures also design flaws in the procedure and unsafe interaction between the ETCS, train drivers and dispatchers.
Besides the conclusion that STPA turned out to be more complete and thorough in identifying hazards, another advantages of STPA is that performing STPA is very structured and not superficial. An identified disadvantage of STPA is that the method stops immediately after the hazards are defined. Determining the probability of occurrence and the impact expressed in train delay minutes can result in prioritization of the hazards and a better risk assessment.
To conclude, this research recommends applying STPA for complex systems where multiple controllers are involved. An STPA expert, someone who has experience with applying STPA in different projects, is a key to successfully implement STPA in an organisation. ...
The hazard analysis technique ‘systems theoretic process analysis’ (STPA) is a promising technique to sufficiently identify hazards that models the system in a control structure and searches systematically for hazards. The main research question of this thesis is: ‘To what extent can STPA be applied to identify risks and determine the system reliability of interactions between ETCS, train drivers and dispatchers?’ What are the risks caused by those interactions and how can STPA be applied for an effective risk assessment are the two research objectives.
STPA consists of 4 structured steps. First the analysed system is described and the purpose of the analysis is set. The system is modelled in a control structure in the second step. The third step of STPA is to identify unsafe control actions with guided words. 27 unsafe control actions are identified for the 8 control actions that are present in the control structure. The last step of STPA is to identify loss scenarios that could lead to the unsafe control actions, those were formulated with system experts.
The desk research and this research demonstrates that STPA is completer and more thorough in identifying hazards than the tradition hazard analysis technique ‘failure mode effect and criticality analysis’ (FMECA). In this research, STPA identified 70 loss scenarios in the analysed procedure (compared to 4 issues identified with FMECA), those hazards ranged from missing or inadequate feedback mechanisms to inconsistent process models of the train drivers or dispatchers. STPA identified besides technical failures also design flaws in the procedure and unsafe interaction between the ETCS, train drivers and dispatchers.
Besides the conclusion that STPA turned out to be more complete and thorough in identifying hazards, another advantages of STPA is that performing STPA is very structured and not superficial. An identified disadvantage of STPA is that the method stops immediately after the hazards are defined. Determining the probability of occurrence and the impact expressed in train delay minutes can result in prioritization of the hazards and a better risk assessment.
To conclude, this research recommends applying STPA for complex systems where multiple controllers are involved. An STPA expert, someone who has experience with applying STPA in different projects, is a key to successfully implement STPA in an organisation. ...
The Dutch railway transport system is a system of systems and also a sociotechnical system that will migrate to a radio-based signalling standard ERTMS (European Rail Traffic Management System). ERTMS will influence the train drivers and dispatchers the most, especially due to the introduction of the signalling and control element of ERTMS: the European train control system (ETCS). A reliability requirement for the migration towards ERTMS obligates to demonstrate that the reliability of the system stays the same or improves. Reliability can be quantified if all the possible risks are known, but identifying risks with traditional models is insufficient, because they do not capture the complexities and dynamics of socio-technical systems.
The hazard analysis technique ‘systems theoretic process analysis’ (STPA) is a promising technique to sufficiently identify hazards that models the system in a control structure and searches systematically for hazards. The main research question of this thesis is: ‘To what extent can STPA be applied to identify risks and determine the system reliability of interactions between ETCS, train drivers and dispatchers?’ What are the risks caused by those interactions and how can STPA be applied for an effective risk assessment are the two research objectives.
STPA consists of 4 structured steps. First the analysed system is described and the purpose of the analysis is set. The system is modelled in a control structure in the second step. The third step of STPA is to identify unsafe control actions with guided words. 27 unsafe control actions are identified for the 8 control actions that are present in the control structure. The last step of STPA is to identify loss scenarios that could lead to the unsafe control actions, those were formulated with system experts.
The desk research and this research demonstrates that STPA is completer and more thorough in identifying hazards than the tradition hazard analysis technique ‘failure mode effect and criticality analysis’ (FMECA). In this research, STPA identified 70 loss scenarios in the analysed procedure (compared to 4 issues identified with FMECA), those hazards ranged from missing or inadequate feedback mechanisms to inconsistent process models of the train drivers or dispatchers. STPA identified besides technical failures also design flaws in the procedure and unsafe interaction between the ETCS, train drivers and dispatchers.
Besides the conclusion that STPA turned out to be more complete and thorough in identifying hazards, another advantages of STPA is that performing STPA is very structured and not superficial. An identified disadvantage of STPA is that the method stops immediately after the hazards are defined. Determining the probability of occurrence and the impact expressed in train delay minutes can result in prioritization of the hazards and a better risk assessment.
To conclude, this research recommends applying STPA for complex systems where multiple controllers are involved. An STPA expert, someone who has experience with applying STPA in different projects, is a key to successfully implement STPA in an organisation.
The hazard analysis technique ‘systems theoretic process analysis’ (STPA) is a promising technique to sufficiently identify hazards that models the system in a control structure and searches systematically for hazards. The main research question of this thesis is: ‘To what extent can STPA be applied to identify risks and determine the system reliability of interactions between ETCS, train drivers and dispatchers?’ What are the risks caused by those interactions and how can STPA be applied for an effective risk assessment are the two research objectives.
STPA consists of 4 structured steps. First the analysed system is described and the purpose of the analysis is set. The system is modelled in a control structure in the second step. The third step of STPA is to identify unsafe control actions with guided words. 27 unsafe control actions are identified for the 8 control actions that are present in the control structure. The last step of STPA is to identify loss scenarios that could lead to the unsafe control actions, those were formulated with system experts.
The desk research and this research demonstrates that STPA is completer and more thorough in identifying hazards than the tradition hazard analysis technique ‘failure mode effect and criticality analysis’ (FMECA). In this research, STPA identified 70 loss scenarios in the analysed procedure (compared to 4 issues identified with FMECA), those hazards ranged from missing or inadequate feedback mechanisms to inconsistent process models of the train drivers or dispatchers. STPA identified besides technical failures also design flaws in the procedure and unsafe interaction between the ETCS, train drivers and dispatchers.
Besides the conclusion that STPA turned out to be more complete and thorough in identifying hazards, another advantages of STPA is that performing STPA is very structured and not superficial. An identified disadvantage of STPA is that the method stops immediately after the hazards are defined. Determining the probability of occurrence and the impact expressed in train delay minutes can result in prioritization of the hazards and a better risk assessment.
To conclude, this research recommends applying STPA for complex systems where multiple controllers are involved. An STPA expert, someone who has experience with applying STPA in different projects, is a key to successfully implement STPA in an organisation.
Master thesis
(2022)
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B.L.K. Kwee, R.M.P. Goverde, A.A. Nunez Vicencio, Bogdan Godziejewski, Mark van Hesse
A heuristic method for the operation of shunting yards is created that considers the sorting process of wagons with dangerous goods. This concerns shunting yards where the wagons are distributed manually, and communication takes place by telephone. The first problem is that an entire train is considered dangerous if there is a wagon with dangerous goods on the accompanying wagon list. The wagon list shows where each wagon is positioned within a train composition. Due to safety regulations, a certain distance must be kept between wagons for certain dangerous goods classes. Because entire trains are considered dangerous, adjacent tracks must be left empty. This is at the expense of the capacity of the yard.
The second problem is that the wagon list is not 100% correct due to human errors. Random checks show that the wagon list does not always turn out to be correct and that mistakes are made in creating the list. Therefore, smart camera techniques have been developed to detect which wagon contains which dangerous goods on arrival to confirm the wagon list. This opens up new possibilities concerning the sorting strategy of wagons from the arrival track onto the classification tracks in accordance with their destination.
Research is done to find out what this new sorting strategy should look like. Therefore, the following research question is formulated: ‘What kind of method can distribute wagons, including wagons carrying dangerous goods, on a rail yard, considering safety?’. In order to answer the research question, qualitative research was carried out into the various existing strategies and methods that could be applied. A model is created in which wagons are sorted over classification tracks. The model chooses the track on which the wagons should be placed based on the destination. Specific attention is given to wagons with dangerous goods, for which the model ensures that a specific distance is kept from other wagons on the (neighboring) classification tracks. The model then determines the most appropriate departure time, and the train departs. Different scenarios are tested that the model has to deal with. A distinction is made here between whether the number of classification tracks is equal or not equal to the number of destinations, and whether the rate of dangerous goods over the destinations is equal or not. This makes a total of four scenarios that have been tested.
The effect of using a buffer on the track is examined so that a wagon carrying dangerous goods never stands next to another wagon carrying dangerous goods of a different class if they are not allowed to stand together. This is tested in the model, and the output showed the placement of the wagons and the processing times.
...
The second problem is that the wagon list is not 100% correct due to human errors. Random checks show that the wagon list does not always turn out to be correct and that mistakes are made in creating the list. Therefore, smart camera techniques have been developed to detect which wagon contains which dangerous goods on arrival to confirm the wagon list. This opens up new possibilities concerning the sorting strategy of wagons from the arrival track onto the classification tracks in accordance with their destination.
Research is done to find out what this new sorting strategy should look like. Therefore, the following research question is formulated: ‘What kind of method can distribute wagons, including wagons carrying dangerous goods, on a rail yard, considering safety?’. In order to answer the research question, qualitative research was carried out into the various existing strategies and methods that could be applied. A model is created in which wagons are sorted over classification tracks. The model chooses the track on which the wagons should be placed based on the destination. Specific attention is given to wagons with dangerous goods, for which the model ensures that a specific distance is kept from other wagons on the (neighboring) classification tracks. The model then determines the most appropriate departure time, and the train departs. Different scenarios are tested that the model has to deal with. A distinction is made here between whether the number of classification tracks is equal or not equal to the number of destinations, and whether the rate of dangerous goods over the destinations is equal or not. This makes a total of four scenarios that have been tested.
The effect of using a buffer on the track is examined so that a wagon carrying dangerous goods never stands next to another wagon carrying dangerous goods of a different class if they are not allowed to stand together. This is tested in the model, and the output showed the placement of the wagons and the processing times.
...
A heuristic method for the operation of shunting yards is created that considers the sorting process of wagons with dangerous goods. This concerns shunting yards where the wagons are distributed manually, and communication takes place by telephone. The first problem is that an entire train is considered dangerous if there is a wagon with dangerous goods on the accompanying wagon list. The wagon list shows where each wagon is positioned within a train composition. Due to safety regulations, a certain distance must be kept between wagons for certain dangerous goods classes. Because entire trains are considered dangerous, adjacent tracks must be left empty. This is at the expense of the capacity of the yard.
The second problem is that the wagon list is not 100% correct due to human errors. Random checks show that the wagon list does not always turn out to be correct and that mistakes are made in creating the list. Therefore, smart camera techniques have been developed to detect which wagon contains which dangerous goods on arrival to confirm the wagon list. This opens up new possibilities concerning the sorting strategy of wagons from the arrival track onto the classification tracks in accordance with their destination.
Research is done to find out what this new sorting strategy should look like. Therefore, the following research question is formulated: ‘What kind of method can distribute wagons, including wagons carrying dangerous goods, on a rail yard, considering safety?’. In order to answer the research question, qualitative research was carried out into the various existing strategies and methods that could be applied. A model is created in which wagons are sorted over classification tracks. The model chooses the track on which the wagons should be placed based on the destination. Specific attention is given to wagons with dangerous goods, for which the model ensures that a specific distance is kept from other wagons on the (neighboring) classification tracks. The model then determines the most appropriate departure time, and the train departs. Different scenarios are tested that the model has to deal with. A distinction is made here between whether the number of classification tracks is equal or not equal to the number of destinations, and whether the rate of dangerous goods over the destinations is equal or not. This makes a total of four scenarios that have been tested.
The effect of using a buffer on the track is examined so that a wagon carrying dangerous goods never stands next to another wagon carrying dangerous goods of a different class if they are not allowed to stand together. This is tested in the model, and the output showed the placement of the wagons and the processing times.
The second problem is that the wagon list is not 100% correct due to human errors. Random checks show that the wagon list does not always turn out to be correct and that mistakes are made in creating the list. Therefore, smart camera techniques have been developed to detect which wagon contains which dangerous goods on arrival to confirm the wagon list. This opens up new possibilities concerning the sorting strategy of wagons from the arrival track onto the classification tracks in accordance with their destination.
Research is done to find out what this new sorting strategy should look like. Therefore, the following research question is formulated: ‘What kind of method can distribute wagons, including wagons carrying dangerous goods, on a rail yard, considering safety?’. In order to answer the research question, qualitative research was carried out into the various existing strategies and methods that could be applied. A model is created in which wagons are sorted over classification tracks. The model chooses the track on which the wagons should be placed based on the destination. Specific attention is given to wagons with dangerous goods, for which the model ensures that a specific distance is kept from other wagons on the (neighboring) classification tracks. The model then determines the most appropriate departure time, and the train departs. Different scenarios are tested that the model has to deal with. A distinction is made here between whether the number of classification tracks is equal or not equal to the number of destinations, and whether the rate of dangerous goods over the destinations is equal or not. This makes a total of four scenarios that have been tested.
The effect of using a buffer on the track is examined so that a wagon carrying dangerous goods never stands next to another wagon carrying dangerous goods of a different class if they are not allowed to stand together. This is tested in the model, and the output showed the placement of the wagons and the processing times.
Master thesis
(2022)
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M.L. Janssens, V. Reppa, E. Quaglietta, R.R. Negenborn, R.M.P. Goverde, Dick Middelkoop
Railway networks are to play an increasingly large role in European transportation. This has boosted the urgency of railway innovations, of which the development of decision support systems for conflict resolution is an important aspect. This research contributes to this development by formulating a suitable mathematical approach for railway networks equipped with moving block signalling systems. Two dispatching actions to reschedule trains are applied, namely retiming and reordering. The designed approach is an extension to an existing method, based on graph theory, that is able to reschedule trains in case of conflict. The novel method uses additional node- and arc types in order to ensure moving block suitability. The new node type enables the possibility to create nodes that are related to trains, rather than infrastructure. The new arc type ensures a continuously safe time interval between two trains in the absence of trackside signals. An optimization problem, with the objective of minimizing the maximum propagated delay, is formulated. Hereafter, the performance is evaluated by a case study in the Rotterdam-The Hague corridor. According to the experimental results, the designed model is able to reduce delay propagation up to 50% for the majority of input situations within 10 seconds of computation time. Overall, the designed method shows promising results, but further research will be necessary to make it applicable in practice.
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Railway networks are to play an increasingly large role in European transportation. This has boosted the urgency of railway innovations, of which the development of decision support systems for conflict resolution is an important aspect. This research contributes to this development by formulating a suitable mathematical approach for railway networks equipped with moving block signalling systems. Two dispatching actions to reschedule trains are applied, namely retiming and reordering. The designed approach is an extension to an existing method, based on graph theory, that is able to reschedule trains in case of conflict. The novel method uses additional node- and arc types in order to ensure moving block suitability. The new node type enables the possibility to create nodes that are related to trains, rather than infrastructure. The new arc type ensures a continuously safe time interval between two trains in the absence of trackside signals. An optimization problem, with the objective of minimizing the maximum propagated delay, is formulated. Hereafter, the performance is evaluated by a case study in the Rotterdam-The Hague corridor. According to the experimental results, the designed model is able to reduce delay propagation up to 50% for the majority of input situations within 10 seconds of computation time. Overall, the designed method shows promising results, but further research will be necessary to make it applicable in practice.
Disruptions occur frequently in railway networks, requiring adjustments to the timetable, rolling stock planning and crew planning while causing delays and cancellations. Although the evolution of system performance during a disruption can be visualized in the resilience curve, not much is known about performance during disruptions or the extent to which the curve applies in practice. The limited quantitative knowledge about the resilience of railway networks makes it hard to design appropriate recovery measures. In this thesis, a data-driven evaluation approach is presented to make an ex post assessment of the resilience of railway networks. Several resilience metrics are extracted from literature and two new resilience metrics are introduced. Using historical traffic realization data, resilience curves are reconstructed for a large and heterogeneous set of single disruptions and are quantified in terms of the resilience metrics. Among others, the values of the resilience metrics are compared across disruptions of different causes using Welch’s ANOVA and the Games-Howell test. The approach is applied to a case study of the Dutch railway network, with a focus on the five most common disruption causes. The results of the case study show that there is significant heterogeneity in the shape of the resilience curve, even within disruptions of the same cause. Train defects are found to be the least impactful disruptions on multiple resilience metrics, while collisions are found to be the most impactful disruptions on multiple resilience metrics. The successful application of the approach shows that it can be used by practitioners to assess which types and which parts of disruptions deserve attention to improve disruption management practices, and thus, improve resilience.
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Disruptions occur frequently in railway networks, requiring adjustments to the timetable, rolling stock planning and crew planning while causing delays and cancellations. Although the evolution of system performance during a disruption can be visualized in the resilience curve, not much is known about performance during disruptions or the extent to which the curve applies in practice. The limited quantitative knowledge about the resilience of railway networks makes it hard to design appropriate recovery measures. In this thesis, a data-driven evaluation approach is presented to make an ex post assessment of the resilience of railway networks. Several resilience metrics are extracted from literature and two new resilience metrics are introduced. Using historical traffic realization data, resilience curves are reconstructed for a large and heterogeneous set of single disruptions and are quantified in terms of the resilience metrics. Among others, the values of the resilience metrics are compared across disruptions of different causes using Welch’s ANOVA and the Games-Howell test. The approach is applied to a case study of the Dutch railway network, with a focus on the five most common disruption causes. The results of the case study show that there is significant heterogeneity in the shape of the resilience curve, even within disruptions of the same cause. Train defects are found to be the least impactful disruptions on multiple resilience metrics, while collisions are found to be the most impactful disruptions on multiple resilience metrics. The successful application of the approach shows that it can be used by practitioners to assess which types and which parts of disruptions deserve attention to improve disruption management practices, and thus, improve resilience.
Master thesis
(2020)
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J. Zomer, R.M.P. Goverde, N. Besinovic, M.M. de Weerdt, J.J.H.M. Holtzer, W. Oldenziel
The current research addresses a problem found in the area of railway operations regarding the maintenance of rolling stock units. It focuses on the situation in The Netherlands and approaches the problem from the perspective of its main railway operator N.V. Nederlandse Spoorwegen (NS).
The increasing use of the capacity of the railway network leads to two issues. First, the complexity of the scheduling process is increasing, raising the need for tools that automate this process. Second, since NS is considering to perform more maintenance activities during daytime, raising the question at which locations maintenance teams needs to be stationed to perform daytime maintenance. These issues are interrelated.
The model development in the current research, tackling the aforementioned issues, can be understood as a three-stage framework. Assuming a given rolling stock circulation, the first stage aims to find the maintenance schedule and maintenance location choice minimizing the total number of nighttime maintenance activities. The second stage introduces a model to compute the required capacity. The third stage integrates the first and second stage, aiming to find a solution to the first-stage model that satisfies some predetermined maintenance location capacity constraints that can be determined by the second-stage model.
First, it is shown that, for a scenario with 20 maintenance locations for daytime maintenance, up to 42.0% of the work can be performed during daytime. Also, the second model can be used to efficiently (i.e. within seconds) compute required capacity and an accurate maintenance activity planning. Moreover, results for the third model have been generated showing, for example, that in one considered problem instance, the number of maintenance shifts for which the required capacity exceeds the available capacity can be reduced from 21 to 5 in 7.6 minutes. In addition to the aforementioned experimental results, a more practical approach is taken as well by constructing a small use case, demonstrating how the current research can be applied in practical situations. To this end, planning software Viriato is used, by which various visualizations of maintenance schedules can be provided. ...
The increasing use of the capacity of the railway network leads to two issues. First, the complexity of the scheduling process is increasing, raising the need for tools that automate this process. Second, since NS is considering to perform more maintenance activities during daytime, raising the question at which locations maintenance teams needs to be stationed to perform daytime maintenance. These issues are interrelated.
The model development in the current research, tackling the aforementioned issues, can be understood as a three-stage framework. Assuming a given rolling stock circulation, the first stage aims to find the maintenance schedule and maintenance location choice minimizing the total number of nighttime maintenance activities. The second stage introduces a model to compute the required capacity. The third stage integrates the first and second stage, aiming to find a solution to the first-stage model that satisfies some predetermined maintenance location capacity constraints that can be determined by the second-stage model.
First, it is shown that, for a scenario with 20 maintenance locations for daytime maintenance, up to 42.0% of the work can be performed during daytime. Also, the second model can be used to efficiently (i.e. within seconds) compute required capacity and an accurate maintenance activity planning. Moreover, results for the third model have been generated showing, for example, that in one considered problem instance, the number of maintenance shifts for which the required capacity exceeds the available capacity can be reduced from 21 to 5 in 7.6 minutes. In addition to the aforementioned experimental results, a more practical approach is taken as well by constructing a small use case, demonstrating how the current research can be applied in practical situations. To this end, planning software Viriato is used, by which various visualizations of maintenance schedules can be provided. ...
The current research addresses a problem found in the area of railway operations regarding the maintenance of rolling stock units. It focuses on the situation in The Netherlands and approaches the problem from the perspective of its main railway operator N.V. Nederlandse Spoorwegen (NS).
The increasing use of the capacity of the railway network leads to two issues. First, the complexity of the scheduling process is increasing, raising the need for tools that automate this process. Second, since NS is considering to perform more maintenance activities during daytime, raising the question at which locations maintenance teams needs to be stationed to perform daytime maintenance. These issues are interrelated.
The model development in the current research, tackling the aforementioned issues, can be understood as a three-stage framework. Assuming a given rolling stock circulation, the first stage aims to find the maintenance schedule and maintenance location choice minimizing the total number of nighttime maintenance activities. The second stage introduces a model to compute the required capacity. The third stage integrates the first and second stage, aiming to find a solution to the first-stage model that satisfies some predetermined maintenance location capacity constraints that can be determined by the second-stage model.
First, it is shown that, for a scenario with 20 maintenance locations for daytime maintenance, up to 42.0% of the work can be performed during daytime. Also, the second model can be used to efficiently (i.e. within seconds) compute required capacity and an accurate maintenance activity planning. Moreover, results for the third model have been generated showing, for example, that in one considered problem instance, the number of maintenance shifts for which the required capacity exceeds the available capacity can be reduced from 21 to 5 in 7.6 minutes. In addition to the aforementioned experimental results, a more practical approach is taken as well by constructing a small use case, demonstrating how the current research can be applied in practical situations. To this end, planning software Viriato is used, by which various visualizations of maintenance schedules can be provided.
The increasing use of the capacity of the railway network leads to two issues. First, the complexity of the scheduling process is increasing, raising the need for tools that automate this process. Second, since NS is considering to perform more maintenance activities during daytime, raising the question at which locations maintenance teams needs to be stationed to perform daytime maintenance. These issues are interrelated.
The model development in the current research, tackling the aforementioned issues, can be understood as a three-stage framework. Assuming a given rolling stock circulation, the first stage aims to find the maintenance schedule and maintenance location choice minimizing the total number of nighttime maintenance activities. The second stage introduces a model to compute the required capacity. The third stage integrates the first and second stage, aiming to find a solution to the first-stage model that satisfies some predetermined maintenance location capacity constraints that can be determined by the second-stage model.
First, it is shown that, for a scenario with 20 maintenance locations for daytime maintenance, up to 42.0% of the work can be performed during daytime. Also, the second model can be used to efficiently (i.e. within seconds) compute required capacity and an accurate maintenance activity planning. Moreover, results for the third model have been generated showing, for example, that in one considered problem instance, the number of maintenance shifts for which the required capacity exceeds the available capacity can be reduced from 21 to 5 in 7.6 minutes. In addition to the aforementioned experimental results, a more practical approach is taken as well by constructing a small use case, demonstrating how the current research can be applied in practical situations. To this end, planning software Viriato is used, by which various visualizations of maintenance schedules can be provided.
Seven disrupted scenarios have been simulated on the railway corridor Utrecht-Den Bosch, each over three signalling configurations to find the effect of in-cab signalling and reduced block section lengths on resilience. Furthermore, the place of resilience in decision making and design of railway signalling has been investigated. Although resilience is only one of the factors in the decision making and design of ETCS-projects, besides factors such as capacity, safety and interoperability, a quantification of resilience can help to either compare alternatives on all factors including resilience, to compare alternatives on resilience only, or to find the relation between design choices and resilience. Simulation of seven disrupted traffic scenarios has shown that using in-cab signalling with ETCS L2 compared to line-side signalling with NS'54/ATB has saved 10% of the delay in the scenarios on average. By using reduced block sections lengths in combination with in-cab signalling, 20% of the delay has been saved on average. For absolute resilience, short block sections should be placed along the whole track. As this is not realistic from cost perspective, decreased block sections are in each case advised nearby yards and switches.
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Seven disrupted scenarios have been simulated on the railway corridor Utrecht-Den Bosch, each over three signalling configurations to find the effect of in-cab signalling and reduced block section lengths on resilience. Furthermore, the place of resilience in decision making and design of railway signalling has been investigated. Although resilience is only one of the factors in the decision making and design of ETCS-projects, besides factors such as capacity, safety and interoperability, a quantification of resilience can help to either compare alternatives on all factors including resilience, to compare alternatives on resilience only, or to find the relation between design choices and resilience. Simulation of seven disrupted traffic scenarios has shown that using in-cab signalling with ETCS L2 compared to line-side signalling with NS'54/ATB has saved 10% of the delay in the scenarios on average. By using reduced block sections lengths in combination with in-cab signalling, 20% of the delay has been saved on average. For absolute resilience, short block sections should be placed along the whole track. As this is not realistic from cost perspective, decreased block sections are in each case advised nearby yards and switches.
Master thesis
(2019)
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Alexander Warmelink, Rob Goverde, Niels van Oort, Halmar Kranenburg, Wijnand Veeneman, Wibout Van Ede
Mass rapid transit plays an important role in providing a sustainable form of transport in densely populated areas. Public transport operators worldwide are experiencing an increase in popularity of their network and are experiencing ridership growth on their metro networks. To accommodate ridership growth, many transport operators are tasked with increasing the capacity of their metro network. While widening or elongating trains can be a too costly alternative to increase capacity, increasing frequencies can be interesting. However, the offered level of service might be jeopardised. Increasing frequencies might lead to higher delays and irregular services, resulting in a lower level of service than when lower frequencies are maintained. With the use of microscopic simulation tool OpenTrack, this research has given a quantitative analysis of the effects of increasing frequencies on timetable reliability. For a case study of the Rotterdam metro network, this research has developed four growth scenarios in which the frequencies are increased. It has found that a timetable with trunk section intervals up to 150 seconds still yield reliable services, however lower intervals yield more unreliable services. The implementation of moving block signaling can reduce delays of 40-50 percent, depending on the timetable. However, for irregularity, removing the driver from the front of the train, creating more buffer time at terminal stations, yields higher improvements than moving block does. This research has shown that moving block and metro automation can enable reliable services for timetables with very high frequencies. However, the operator is still faced with a choice to either strive for punctual trains, or to strive for regular trains.
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Mass rapid transit plays an important role in providing a sustainable form of transport in densely populated areas. Public transport operators worldwide are experiencing an increase in popularity of their network and are experiencing ridership growth on their metro networks. To accommodate ridership growth, many transport operators are tasked with increasing the capacity of their metro network. While widening or elongating trains can be a too costly alternative to increase capacity, increasing frequencies can be interesting. However, the offered level of service might be jeopardised. Increasing frequencies might lead to higher delays and irregular services, resulting in a lower level of service than when lower frequencies are maintained. With the use of microscopic simulation tool OpenTrack, this research has given a quantitative analysis of the effects of increasing frequencies on timetable reliability. For a case study of the Rotterdam metro network, this research has developed four growth scenarios in which the frequencies are increased. It has found that a timetable with trunk section intervals up to 150 seconds still yield reliable services, however lower intervals yield more unreliable services. The implementation of moving block signaling can reduce delays of 40-50 percent, depending on the timetable. However, for irregularity, removing the driver from the front of the train, creating more buffer time at terminal stations, yields higher improvements than moving block does. This research has shown that moving block and metro automation can enable reliable services for timetables with very high frequencies. However, the operator is still faced with a choice to either strive for punctual trains, or to strive for regular trains.