WO2018036759A1 - Prediction of the run of a train - Google Patents

Prediction of the run of a train Download PDF

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Publication number
WO2018036759A1
WO2018036759A1 PCT/EP2017/069388 EP2017069388W WO2018036759A1 WO 2018036759 A1 WO2018036759 A1 WO 2018036759A1 EP 2017069388 W EP2017069388 W EP 2017069388W WO 2018036759 A1 WO2018036759 A1 WO 2018036759A1
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WO
Grant status
Application
Patent type
Prior art keywords
train
data
current
expected
trains
Prior art date
Application number
PCT/EP2017/069388
Other languages
German (de)
French (fr)
Inventor
Gerald SEIDLER
Original Assignee
Siemens Aktiengesellschaft
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date

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Classifications

    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00Central traffic control systems ; Track-side control or specific communication systems
    • B61L27/0011Regulation, e.g. scheduling, time tables
    • B61L27/0022Following schedules
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00Central traffic control systems ; Track-side control or specific communication systems
    • B61L27/0011Regulation, e.g. scheduling, time tables
    • B61L27/0027Track-side optimisation of vehicle or vehicle train operation
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00Central traffic control systems ; Track-side control or specific communication systems
    • B61L27/0077Track-side train data handling, e.g. vehicle or vehicle train data, position reports
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00Central traffic control systems ; Track-side control or specific communication systems
    • B61L27/0038Track-side control of safe travel of vehicle or vehicle train, e.g. braking curve calculation
    • B61L2027/0044Track-side control of safe travel of vehicle or vehicle train, e.g. braking curve calculation using European Train Control System [ETCS]
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B61RAILWAYS
    • B61LGUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00Central traffic control systems ; Track-side control or specific communication systems
    • B61L27/0038Track-side control of safe travel of vehicle or vehicle train, e.g. braking curve calculation
    • B61L2027/005Track-side control of safe travel of vehicle or vehicle train, e.g. braking curve calculation using Communication-based Train Control [CBTC]

Abstract

The invention relates to a method (1) and to a system for predicting the expected run of a train. In order to be able to objectively better predict the expected train run, according to the invention, historical frame conditions and driving data from a database are compared (3) with current frame conditions and driving data, and based on the historical frame conditions and driving data, the train run to be expected is determined (7).

Description

description

Predicting the movement of trains

The invention relates to a method and system for predicting the expected movement of trains of a train. Furthermore, be ¬, the invention applies to a computer program product with Pro ¬ program code. Moreover, the invention relates to a compu ¬ terlesbaren disk.

In order to predict the prescribed schedule the anticipated train route of the train even with variations, is currently resorted to the experience of dispatchers or dispatchers. Based on these experiences of other sections of the route can be estimated. Further action can be taken based on the experience in order to minimize the impact of the departure on the other sections of the route. If the travel service provider or the dispatcher not experienced enough, neither the expected train route may still predicted to the impact of the departure-minimizing measures are taken.

The invention is therefore based on the object to provide a method and a system for predicting the expected movement of trains a train, the train movement can be objectively ge ¬ more precisely predicted and on the exact ¬ ren forecasts, action can be taken based to the equalize the expected train route to the predetermined schedule of the train.

For the aforementioned method, the object is achieved by providing current conditions of the current of the train with historical conditions prior trains are in the process of comparing historical conditions that are the current conditions closest to be selected, and the selected conditions associated with driving data are the previous train journeys selected and used to predict the expected train route of the train, the environment and associated with driving data are provided by a train control system is available. The object is achieved for the initially ge ¬ foregoing system in that the system is adapted to perform the inventive method. For the aforementioned computer program product of the invention is as ¬ achieved by, that the inventive method can be carried out with the program code, when the computer program product is run on a computer. For the above-genann ¬ th data carrier, the invention is achieved in that the computer program product according to the invention is stored on the disk.

For predicting the expected movement of trains so no subjective experience are no longer necessary. Consequently, an appropriate and, if possible at historical deviations successful measure the expected train movement can be determined more accurately and to approximate the movement of trains at the specified timetable to be taken.

The inventive solution can be further improved by various each for themselves advantageous and, unless stated otherwise combined together in any configurations. In this embodiments and their associated benefits is discussed below.

Thus, the selected trip data for predicting the movement of trains expected to be at least partially statistically ¬ upgraded. For statistical analysis, a relative frequency distribution of selected or all of the selected trip data can be determined. Alternatively, moving averages of selected or all of the selected drive data can be used to predict the expected movement of trains. Furthermore, the moving median of selected or all of the selected trip data can be used to predict. Statistical analysis of the selective trip data allows for easier and more precise before ¬ forecasting the expected movement of trains using a reduced when compared to all the selected trip data amount of data, namely the overall by the statistical analysis of data acquired.

Of the selected trip data can be selected those that come the current trip data of the train at the next and the expected train movement can be determined on the basis of belonging to the selected trip data train routings. Optionally, the selected trip data can be statistically analyzed. In this way only particularly relevant selective ride data to predict ¬ expected of the movement of trains are used, so that the accuracy of the pre ¬ forecasting improved.

The anticipated train movement can be repeated and determined aktuali ¬ terraced framework and associated drive data. By considering the current conditions and trip data again the accuracy of the prediction improved.

The time interval between two determinations of the expected movement of trains can vary depending on the planned route of the train, expected or existing interference on the line and / or on the train, the current deviation of the recent movement of trains from the planned train route of the train, a waste prior to a go ahead on the same road section ¬ the train and / or at least a part of the selected drive data can be selected. By such consideration, the prediction can be performed more accurately.

The method for predicting the expected movement of trains can be started when a difference of the actual movement of trains of turn from a predetermined timetable exceeds a predetermined threshold. The threshold may be a configurable delay value. Consequently, the method can be used in particular in a disturbed and deviate from the schedule sections of the route for accurate and possibly even the automatic alignment of the road map to the other sections of the route and / or for estimation of action to correct the movement of trains.

In order to expand existing where the data for forecasting the movement of trains, the current travel data and their associated current conditions can be stored to create another historic trip data and those belonging conditions, for example in a database.

The current conditions and associated current trip data can be therefore stored in itself as raw data so that a distortion of the stored data is excluded. Alternatively, the current Rahmenbedin- to conditions and its current trip data is stored statistically evaluated, for example in the data ¬ Bank. Hereby, the space required can be reduced and the prediction of the expected movement of trains accel ¬ Nigen because the statistical analysis not separately by - is out, but can be rather use already existing statistical data ¬ tables.

The conditions may include :, train type that Zugpriorität, the place where the train is located, the cur- rent day, whether currently at the site of the train are school holidays or public holidays, the current time, the aim of to ¬ ges, intermediate targets of the train, the Zugbelegung, so the on ¬ number of passengers in the train, possibly with reference to the Capa ¬ capacity of the train, the planned route, whether sites or Toggle particular planned or unplanned disturbances at or on the ge ¬ planned route are present, the existing punctuality or the current punctuality of the train if vo ¬ out moving trains occupy the same track section, whether an accident has happened on the planned route, and / or whether a technical fault on the train and / or on the track in front of ¬ is , The type of technical failure or expected effects of the disorder or an accident or the speed of the preceding train can be saved as conditions.

The trip data, the previous and / or current punctuality of the train, the previous and the current Ge ¬ speed of the train, past and / or current arrival kunfts- or affect departure times and other train movements of the train. The intervals in which the method for predicting the expected movement of trains of the train to be performed repeatedly, may depend on whether the preceding vehicle train is present and at what speed for slower moving train departs from conditions of the planned route, for examples game whether construction sites are available for the intended route, and, like the previous and current punctuality of the train.

Disorders can be, for example road works and accidents on the planned route or technical faults on the train or at the track.

The current conditions and the associated drive data can be stored permanently, for example, with the current Zugposi- tion and other information such as arrival and from ¬ ride messages. This can be not only for a train, for the expected train route is to be predicted, performed. Rather, these records for all trains of a section, an overall ografischen area or the entire route network vomit ¬ chert can be. This increases the statistical evaluation ¬ From improved compared to the use of isolated historical data. For example, the records at an interface of a train control system can occur, for example ETCS or CBTC, for operations control, as the operations control designate the data to be recorded generally for other purposes already gets. This data can therefore be unadulterated raw data that can be stored statistically evaluated by itself or. Influences of currently recorded data can therefore be considered directly in the prediction of the expected movement of trains.

As current trip data detailed motion Informa ¬ tions at least the train whose expected train route is to be predicted, are collected and stored. In particular, the detailed movement information of all trains can be stored. The train control systems already make this information available, so that the technical expenditure for implementing the method is low. In ¬ play as based traits recorded in transport several times a minute, the ak ¬ tual train position for ETCS guided trains over long distances or CBTC.

The time interval between two provisions of the expected movement of trains may also depend on the route topology of the planned route of the train and the timetable of the train. The anticipated train movement can the expected

Driving history, while also expected delays umfas ¬ sen. Here, those historical data can be used, which are the current turn for the next, for example, the same day of the week and / or similar time. The predictions and / or actions taken to improve the punctuality of the train and its effects can be stored for example in the database. Furthermore, accuracy values which the accuracy of predictions or a deviation of the prediction of then ¬ beaten train routings can be saved.

The data record of the current train positions can be done continuously or permanently, allowing in steadily improving standing for predicting the Availability checked ¬ supply of data. Has the train route be monitored and possibly be planned by ¬ personnel to solve a current fault, can at least predict or even several possible predictions of to he ¬ waiting movement of trains, for example, as an additional line in the time-distance line diagram for the train or as additional information are presented in a table to simply show the staff the anticipated train route discoverable to promising measures to minimize the effects of the disorder can be identified and taken. Specifically, the method, draw a comparison with similar train routings from the past and the typi cally ¬ expected travel progress in solving a current fault possible. The disk can be used as a USB flash drive, a floppy disk, optical disk (CD, DVD, etc.) or provided as an other portable storage medium. Furthermore, the disk can be online, so over a network and, for example, via the Internet, to be accessible, so that the computer-program product is provided, for example, as a download.

The above-described characteristics, features and advantages of this invention and the manner of attaining them, will become more apparent and clearly understood in connection with the following description of embodiments, which are explained in connection with the drawings. In the following the invention is exemplified based on from ¬ EMBODIMENTS with reference to the drawings. The different features of the embodiments can thereby be combined independently of one another, as has already been stated in the individual advantageous embodiments.

In the drawings: Figure 1 is a schematic illustration of an exemplary embodiment of the inventive method for predicting the expected movement of trains, Figure 2 is a schematic illustration of an exemplary embodiment of an inventive system for predicting the expected movement of trains.

First, the structure and function of the method for predicting the expected movement of trains a train with respect to the embodiment of Figure 1 are be ¬ wrote.

Figure 1 shows the method 1 according to the invention schematically as a flowchart. The process 1 starts with a first method step 2. In the first process step 2, the current train route can be compared with the predetermined schedule of the train. Furthermore, current conditions and driving data of the running of the train can be determined and stored. The determination and storage of the current conditions and current trip data can be carried out independently of a possibly existing deviation of the actual movement of trains on schedule. Is a deviation of the actual movement of trains from the schedule above a predetermined threshold, a further process step 3 can be carried out after the step. 2 If the deviation is below the threshold value, then the current conditions and the current Fahrtda- th can be determined and stored periodically or continuously and compared with the road map. In step 3, the prevailing conditions with historical conditions are compared. For this, the historical conditions from a database can read the advertising. The determined in step 2 current conditions and current trip data can be stored in this database or be. At step 3, a method step 4 can fol ¬ gen, in the historical conditions that are the current conditions closest to be selected. At step 4, a step 5 fol ¬ gen, where the corresponding to the selected conditions historical trip data are determined. The determined pertinent historical trip data can be evaluated statistically optional. For example, the rela- tive frequency distribution whose moving averages or their sliding median for statistical analysis can be determined.

Optionally, a step may be followed by 6, may follow the turn of the process ¬ step 5 on the step 4 first. In step 6, the associated conditions for the selected historical travel data with the current trip data can be compared. The historic journey data coming the current trip data the following can be selected and only the selected historical travel data in step 5 is used and statistically optional.

Based on the formed in step 5 and op- tional statistically evaluated trip data in step 7, the expected train route can be determined. In ¬ play as historical driving data belonging to the histo ¬ generic framework and / or come to the current trip data the following, and this historic journey data can be used in historical trips following trip data and evaluated optional statistically to predict the expected train route ,

When in the subsequent step 8, the process ends. For example, can be determined from a possible deviation of the actual movement of trains from the previous schedule if and when or how frequently the method is restarted. Figure 2 shows an embodiment of an inventive system for predicting the expected movement of trains to a ¬ ges schematically.

The system 10 is preferably configured to perform the method. 1 For example, system 10 comprises a data ¬ bank 11, in the historical conditions and those associated historical travel data are stored. Optionally, statistically evaluated historical framework and associated drive data be stored as an alternative or in addition to the historical conditions and their associated travel data in the database. 11 Are statistically evaluated data in the database 11 are stored, the system 10 may include a ¬ evaluation means 12 further formed to evaluate conditions and trip data statistically. The evaluation device 12 is then data-transmitting manner with the data bank. 11 The evaluation device 12 may be a

His computer and, for example an industrial PC, a server, a desktop PC or a controller or aufwei ¬ sen. The database 11 may be data-transmitting manner with a control plant. 13 In the control system 13 can be predicted based on the information provided by the database 11 available data, the expected train route of the train. Alternatively, a data processing device, between the database 11 and the control system 13 may be ge ¬ on, in which the expected train route is predicted based on the data of the database. 11

The process control system 13 can output the predicted train route of the train at an operator station 14 for a dispatcher or another person who is busy with the line of the train. Based on the issued forecasts, the expected train movement can be easily recognized. Of the expected end sections of the route deviates too much on the timetable of the train, it can be well estimated based on the anticipated movement of trains and on the basis of histori ¬-specific data, which measures the approximation of Zugslaufs be taken to the timetable were made subservient.

The current conditions and the associated

to be able to easily determine trip data with low personnel costs and save, they can be supplied from a Zugsicherungssys- tem 15th The train protection system 15 is data-transmitting manner with the control plant. 13 The process control system 13 can store the determined current Rahmenbe ¬ conditions and transfer data in the database. 11 Optionally, the train protection system 15 may technology system 13 to the database 11, bypassing the conductivity be data-transmitting ver ¬ prevented and store the current conditions and the associated drive data in the database. 11

Although the invention has been illustrated in detail by preferred embodiments and examples in more detail described, the invention is not limited by the disclosed examples and other variations can be derived therefrom by the skilled artisan without departing from the scope of the invention.

Claims

claims
Are selected first method (1) for predicting the expected movement of trains a train, are compared with the current conditions of the current of the train with historical conditions of previous train (3), historical conditions that are the current conditions closest (4 ), and the selected conditions associated with the previous drive data trains are selected and used to calculate the expected train route of the train predict (7), wherein the framework and the associated driving data are provided by a train control system is available.
2. The method (1) according to claim 1,
characterized in that
the selected drive data are analyzed at least partially randomly for predicting the expected movement of trains to (5).
3. The method (1) according to claim 1 or 2,
characterized in that
be selected from the selected ride data those corresponding to the current travel data of the train come (6) closest to and the expected train movement is determined by the belonging to the out ¬ selected trip data train routings (6, 7).
4. The method (1) according to one of claims 1 to 3,
characterized in that
the expected train route repeatedly and is determined with updated frameworks and associated drive data.
5. The method (1) according to claim 4,
characterized in that
the temporal distance between two determinations of the expected movement of trains depending on the planned route of the train, expected or existing interference on the line and / or on the train, the current deviation of the recent movement of trains from the planned train route of the train, a distance to an on the same track section preceding train and / or at least a part of the selected drive data is overall selects (8).
6. The method (1) according to one of claims 1 to 5,
characterized in that
the method (1) is started (2), when a difference of the actual movement of trains of turn exceeds a predetermined schedule of a predetermined threshold.
7. The method (1) according to one of claims 1 to 6,
characterized in that
the current drive data and the current conditions associated therewith are stored for generating another historic travel data and these associated conditions (2).
8. The method (1) according to claim 7,
characterized in that
current conditions and associated current trip data is stored statistically evaluated by itself or.
9. System (10) for forecasting the movement of trains ei ¬ nes train, said system (10) is formed, the procedural ¬ ren (1) according to any one of claims 1 to 8 to perform.
10. Computer program product with program code for performing the method (1) according to one of claims 1 to 8, if the
Computer program product is run on a computer.
11. The computer readable media on which the computer program product of claim stored 10th
PCT/EP2017/069388 2016-08-23 2017-08-01 Prediction of the run of a train WO2018036759A1 (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
DE201610215767 DE102016215767A1 (en) 2016-08-23 2016-08-23 Predicting the movement of trains
DE102016215767.1 2016-08-23

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WO (1) WO2018036759A1 (en)

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EP2548784A2 (en) * 2011-07-20 2013-01-23 Hitachi Ltd. Train control system
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EP2674722A2 (en) * 2011-02-03 2013-12-18 TomTom Development Germany GmbH Method of determining a deviation from expected jam conditions
EP2548784A2 (en) * 2011-07-20 2013-01-23 Hitachi Ltd. Train control system
EP2631152A1 (en) * 2012-02-24 2013-08-28 Schweizerische Bundesbahnen SBB Method and device for managing resources in a railway network
GB2507388A (en) * 2012-09-28 2014-04-30 Hitachi Ltd Taking power consumption into account when rescheduling trains following a delay
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