November 04, 2015

Simulation aids decision making on Munich S-Bahn

Written by  Dipl-Ing Dr Marc-Andre Klemenz
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Intensive operations on Munich's S-Bahn network leave little room for error, so when disturbances do occur the impact soon spreads across the entire network. Dipl-Ing Dr Marc-André Klemenz, head of international projects at DB International, explains how simulating operations, and potential disturbances, is helping to minimise delays and improve punctuality.

MUNICH S-Bahn's core network is one of the most densely-used sections of railway in Europe. The network consists of seven branches on the west and five on the east side of the Munich metropolitan area, which are linked by a core track section, the so-called Stammstrecke. This 11km-long section runs between Pasing and East Station and can carry up to 30 trains per hour per direction (phpd) at peak times.

OpsManThe basic service interval on an individual S-Bahn branch line is 20 minutes. Nevertheless on some lines additional trains are in use which reduces headways to 10 minutes during peak hours, which equates to 120 second headways on the core section.

By using tight headways, even a minor delay to a single train on the outer reaches of the network can result in delays in the core section. As a result continuous monitoring and analysis of the network is required to operate services according to the specific headways and to guarantee consistent quality of service with measures to optimise the service determined and implemented quickly.

Punctuality is inevitably one of the most relevant quality criteria for customers. Actual and subjective punctuality is a significant reference point to assess the quality of the service and its public image, with punctuality affecting passenger usage behaviour, and consequently revenues. In Munich an S-Bahn train is defined as punctual if the delay at a predetermined measurement station is less than six minutes. The punctuality of the entire system is determined as the average of all measured trains.

To continue offering a consistent service in challenging operating conditions, DB Regio subsidiary Munich S-Bahn is cooperating with Bavarian Railway Authority (BEG), which oversees all railway operations in Bavaria, to introduce measures to improve punctuality. Several technical and operational measures to accelerate operational procedures are already in place and others are planned. These measures take a general approach to improve all sub-systems in a coherent manner, but in particular the infrastructure and the rolling stock, by taking into account the dependencies and interactions between these two main elements.

Within the scope of a joint-project between DB Networks and DB Regio, DB International was assigned to examine the operation of the suburban railway. One of the project's main objectives was to improve the understanding of the system's actions, reactions and coherences following certain events and incidents by using simulation software.

Opsfig1Simulation was used to analyse and evaluate the various measures used to improve punctuality in the event of a delay, and to assess different dispatching actions after a predefined disturbance or failure.

The software tool RailSys, supplied by railway management consultant RMCon, Germany, was used to provide a microscopic model of the S-Bahn's infrastructure during a normal weekday using the 2013 timetable.

The next step was to introduce actual average delays such as extended dwell times provided by Munich's Operations Control Centre. This data was necessary to model realistic daily disturbances across a whole day of operations. The resulting timetable was used as a base variant for comparison with all further timetable modifications, examinations and scenarios. In total over 60 different variants or scenarios were simulated and evaluated.

What follows are the most important results and conclusions of the investigation into the different scenarios, with a focus on the impact of delays on punctuality.

Opsfig2Emergencies, which are defined as an injury to a passenger requiring medical attention, occur frequently, irregularly and randomly at station platforms or on trains operating in the core Stammstrecke. The average duration of an emergency is 15 minutes. During this time trains operating on the core section are normally stationary, which results in almost inevitable delays to trains operating on the branch lines. Due to the network's intense service operation, it then takes a significant period to recover this time, especially during peak hours when 30 trains phpd are in operation.

Reductions in the duration of an emergency will reduce the number of delayed trains and also the dimension of the delays. But without a precise simulation, the effect on punctuality of the specific measures implemented to achieve this is hard to estimate.

The simulation consequently evaluates the varying durations of these emergencies (five, 10 and 15 minutes) at Hirschgarten station on the core section during the morning peak. The evaluation parameters are punctuality and the delay.
Inevitably the simulation found that the longer the duration of an emergency, the lower the punctuality and the higher the delay. It also found that reducing the length of this delay helped to improve punctuality:

  • a delay of five minutes resulted in no significant negative effects on punctuality
  • a reduction from 15 minutes to 10 minutes increases the daily punctuality to 0.75%, and
  • a reduction from 15 minutes to 5 minutes increases the daily punctuality to 1.4%.

During the peak the scheduled timetable is more susceptible to delays due to longer dwell times at crowded stations because of increased passenger boarding and alighting times. The
S-Bahn is looking to improve this by reducing the required time for departure procedures by reducing door opening times by using centralised door opening and closing. Operational simulation makes it possible to see simply and quickly whether these steps will offer a solution by evaluating whether the time saved reduces delays and allows the next train to arrive sooner.

Based on a centralised door opening and a technical departure assistance strategy, four scenarios were evaluated.

  • scenario 1: centralised door opening
  • scenario 2a: all stations on the core line are equipped with technical departure assistance
  • scenario 2b: a selection of stations on the core line are equipped with technical departure assistance, and
  • scenario 3: combination of 1 + 2a.

The simulation confirmed that modifying departure procedures can reduce dwell times by between two and six seconds per stop for trains at each of the 11 stations on the core section.

The simulation also shows that implementing any of these four scenarios increases the punctuality and reduces the delay. Scenario 3 which combines centralised door opening (scenario 1) with technical departure assistance (scenario 2a) at all stations offered the best results.

The simulation also shows reductions in delays in comparison with the base variant as follows:

  • scenario 1: 6%
  • scenario 2a: 8%
  • scenario 2b: 4%, and
  • scenario 3: 14%

Munich S-Bahn has developed standardised dispatching programmes to handle general disturbances and effective operation on the Stammstrecke. These programmes are only used in the case of large disturbances and effectively split the service into two parts (east branches and west branches). They also accelerate the process to identify appropriate solutions by using uniform communication for employees and customers.

In addition the S-Bahn has developed dispatching measures for use in the event of smaller delays. However, the impact of these methods is difficult to evaluate and is only possible to estimate using empirical values. Indeed without an appropriate decision guidance system for dispatchers it is not possible to offer an effective and an efficient method of handling small disturbances, or to quantify their effect on punctuality and reducing delays.
The simulation was subsequently employed to evaluate the effect of different dispatching measures on punctuality and delay development, with several typical disturbance scenarios modelled:

  • type of disturbance: emergency in a train or station
  • time of disturbance: morning peak hour
  • duration of disturbance: dwell time of 15 minutes
  • location of disturbance: Hirschgarten station
  • direction of operation: west - east.

Typical dispatching measures are:

  • terminating selected services at Pasing or East Station so they do not enter the central section
  • redirecting selected lines, and
  • a combination of these options.

Overall the effects of 10 dispatching measures on punctuality and delays were examined and compared. Figure 3 shows the punctuality if each of these dispatching measures is executed. The results show that all variants lead to system stabilisation of the system, increases in punctuality and a reduction in delays in comparison with the base variant where no dispatching measure was issued.

The differences between the measurements and their impact on punctuality depend on the number of redirected trains and the timing of the dispatching measure. As a result, the simulation offered the following findings:

  • selecting the specific dispatching measure depends on when the disturbance occurs
  • redirecting more trains and preventing entry to the core line after a disturbance results in higher punctuality and fewer delays
  • the earlier the trains are redirected, the higher the punctuality and the lower the system delay
  • all dispatching measures increase the punctuality and reduce the delay
  • the longer the duration of a disturbance, the more effective the dispatching measures, and
  • selecting the correct dispatching measure is dependent on the location of the disturbance.

Depending on daily or hourly demand, it is possible to increase transport capacity by using single, double or triple train formations, with coupling taking place primarily in Pasing and East Station at the beginning of the morning peak. However, with different branch lines merging at Pasing and East Station delays in coupling can lead to additional delays.

Operational simulation was again employed to identify which coupling processes could be eliminated to minimise delays and improve punctuality. Four variants of the coupling process were analysed and the simulation shows that omitting coupling at East Station and at Pasing decreases the total delay and increases the punctuality on the core line with the fewer coupling processes, the greater impact of these measures.

Based on the results of the simulations, the study offers the following significant findings:

  • selecting a specific dispatching measure depends on when the disturbance occurs
  • preventing more trains from entering the core line following a disturbance will offer better punctuality and reduce delays
  • early redirection of trains results in better punctuality and lower system delays
  • efficient dispatching measures increases punctuality and reduces delays
  • longer disturbances result in more effective dispatching measures
  • selecting a specific dispatching measure is dependent on the location of the disturbance
  • efficient measures to reduce entry increase punctuality and reduce delays, and
  • identifying a quick solution to a disturbance to avoid bottlenecks reduces delays.

Based on these findings it is essential that an efficient dispatching system with the capability of issuing instructions quickly is available.

Simulation based on a microscopic modelling of the system is an effective tool to increase the efficiency of dispatching and to optimise operations in complex railway systems through its ability to clearly and easily show dynamic operations and the interdependencies of the system.

By offering a better understanding of how the railway system works, Munich S-Bahn benefits from more efficient, fast and effective operations solutions.

DB Regio is currently integrating the findings into the S-Bahn's operational planning and control processes, providing dispatchers with the opportunity to quantify the outcome of the potential benefits of specific dispatching measures in certain situations.

The results of the simulation are useful to validate disturbance/ emergency management procedures. The simulation results can optimise the dispatching concepts and dispatching measures, which have been developed by Munich S-Bahn's competent and experienced operators over many years. Indeed the subjective experience of a dispatcher is now supplemented with the objective results of the simulation to offer the best possible response in the event of a disturbance. It can also be used to train new dispatchers and is becoming a vital medium during time-critical disturbances.

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