EP3388307A2 - Fusion de données liées à l'infrastructure, en particulier de données liées à l'infrastructure pour véhicules ferroviaires - Google Patents

Fusion de données liées à l'infrastructure, en particulier de données liées à l'infrastructure pour véhicules ferroviaires Download PDF

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Publication number
EP3388307A2
EP3388307A2 EP18166626.4A EP18166626A EP3388307A2 EP 3388307 A2 EP3388307 A2 EP 3388307A2 EP 18166626 A EP18166626 A EP 18166626A EP 3388307 A2 EP3388307 A2 EP 3388307A2
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EP
European Patent Office
Prior art keywords
data
record
vehicles
infrastructure
records
Prior art date
Legal status (The legal status 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 status listed.)
Granted
Application number
EP18166626.4A
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German (de)
English (en)
Other versions
EP3388307B1 (fr
EP3388307A3 (fr
Inventor
Bernd Foißner
Martin Deuter
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Knorr Bremse Systeme fuer Schienenfahrzeuge GmbH
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Knorr Bremse Systeme fuer Schienenfahrzeuge GmbH
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Publication of EP3388307A3 publication Critical patent/EP3388307A3/fr
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L15/00—Indicators provided on the vehicle or train for signalling purposes
    • B61L15/0058—On-board optimisation of vehicle or vehicle train operation
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/40—Handling position reports or trackside vehicle data
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B61—RAILWAYS
    • B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
    • B61L27/00—Central railway traffic control systems; Trackside control; Communication systems specially adapted therefor
    • B61L27/50—Trackside diagnosis or maintenance, e.g. software upgrades
    • B61L27/53—Trackside diagnosis or maintenance, e.g. software upgrades for trackside elements or systems, e.g. trackside supervision of trackside control system conditions

Definitions

  • the present invention relates to a method for merging infrastructure-related data, in particular infrastructure-related data for vehicles, in particular rail vehicles, a computer program product for carrying out this method and an apparatus for carrying out this method.
  • such infrastructure-related data includes information about the route characteristic, such as the grade, information on maximum allowable speeds or the positions of stops, and the like. Also information regarding the maintenance intervals or the general condition of the route are conceivable.
  • Under track-bound vehicles are to be understood hereinafter as vehicles which follow a fixed track and these can not leave, or leave only under certain conditions, such as maglev trains or driverless transport vehicles.
  • This invention is based on the task of generating new data records from existing infrastructure-related data sets that are consistent, complete, with the corresponding level of detail and with the corresponding data quality.
  • a method which creates at least one new data record which contains infrastructure data for vehicles.
  • the creation of the new data record preferably proceeds essentially by first reading in at least one existing data record from at least one source and subsequently converting it to at least one new data record having a uniform format, wherein the at least one existing data record contains data which includes an infrastructure segment
  • the standardized format is suitable for making the new data record accessible to a driver assistance system of a vehicle, thereby enabling the operation of such a driver assistance system.
  • a new data record is created by means of a data fusion of at least two existing data records, whereby the information content of the new data record is at least as high as the information content of the at least two existing data records.
  • the merged, new data set now contains the data and information of both data sets, whereby the information content of this data set is higher than that of the two individual data sets.
  • an evaluation of a quality of the data records takes place, whereby certain data are identified on the basis of the quality as trusted data records for the further fusion.
  • the quality of a data record preferably describes how much the data record is suitable for the description of an infrastructure section and the further processing.
  • the evaluation of the quality can be done by analyzing a data set for its information content. If there are two plausibly evaluated data sets that describe the course of the same route, which is characterized by strongly varying slope, then the data set with the higher quality is to be evaluated, which has the higher resolution, that has more nodes. As a result, this record describes the track in much greater detail compared to the other record. A high level of detail, ie a high number of interpolation points, can thus be a measure of high data quality.
  • the assessment of the quality can also be made or influenced by the user by incorporating his own assessment of the quality in the process.
  • an identification of data of both data sets takes place, which describe the same infrastructure section in order to avoid duplication of the data in the later fused data set.
  • certain trusted data sets are determined which serve as a data basis in the further procedure, if other data sets provide conflicting data.
  • such a trusted dataset is a dataset which has been previously read from the sources, or it has been specially created for this purpose and provided for further processing of the method.
  • connecting points of the at least two data records are also identified in order to fuse them, corresponding to the infrastructure.
  • the at least two data sets are checked before and / or after the merger with regard to existing data gaps and / or further inconsistencies, these being identified for further processing.
  • the source from which the data records are read in may preferably be existing data records which have a static character, that is to say are immutable.
  • dynamically generated data records can be read in from other sources, which are generated, for example, during operation of the vehicles or by the driver. These dynamically generated data records are preferably used to supplement the already existing static data records.
  • the at least two data records are merged into at least one new data record, a plausibility check of the existing data records and / or the at least one new data record takes place.
  • At least one existing data record is defined as a trusted data record as a reference for the plausibility check.
  • This trusted dataset serves as the sole data source when multiple datasets describe one and the same leg of the route, but provide different or contradictory information.
  • the selection of the trustworthy data source can preferably take place via a weighting or evaluation of the quality between the individual data records which serve as data sources.
  • a plausibility check involves checking for data consistency.
  • a review of the elevation data is carried out primarily at the transition points between individual data sets, whereby discontinuities are avoided.
  • the driver assistance systems located in the vehicles are designed to carry out the autonomous or semi-autonomous operation of the vehicles on the basis of the newly generated data records.
  • the newly created datasets have infrastructure-related information about a road network in which the vehicles move.
  • these are rail vehicles which move on a rail network.
  • the invention is provided as a computer program product with program code stored on a machine-readable carrier for carrying out the method described above, wherein the carrier can be, for example, a USB stick or the like, or the computer program product via a server by means of a suitable data connection can be made available.
  • the carrier can be, for example, a USB stick or the like, or the computer program product via a server by means of a suitable data connection can be made available.
  • the invention is in the form of a device which processes the method described above.
  • Such devices are preferably devices which are designed for installation in vehicles, for example in the form of an on-board unit, or path-side devices, such as signal boxes or control stations.
  • the device When installed in a vehicle, the device preferably serves to process the data records present on the vehicle, so that no new data records have to be generated.
  • the device is provided in a planning office, which undertakes long-term care of the data, which serve as the basis for the operation of the vehicles on a road network, which is formed from several infrastructure sections.
  • the device has at least one suitable interface to the vehicle or the path-side device, which is adapted to determine the required data for the method described above.
  • the device has the option of developing the required data for carrying out the method, for example via data carriers or data connections.
  • the device preferably has at least one user-accessible interface so that the user can transmit additional information and / or static or dynamic data to the device via this interface.
  • the user can transfer data from a test drive, which was undertaken to supplement existing data records, to the device via this interface.
  • a test drive which was undertaken to supplement existing data records
  • the device via this interface.
  • the device is designed to be installed in a track-bound vehicle, in particular a rail vehicle, and to interact with it.
  • Fig. 1 shows a flowchart of an embodiment of the method according to the invention with the essential steps of the method.
  • Static data is to be understood as meaning all infrastructure-related data which are essentially static, that is unchangeable.
  • An example of static data is information about the slope of a link as it does not change further during normal operation.
  • Dynamic data is preferably understood to mean data that was generated during the operation of the vehicles or through special test drives. These dynamic data represent a possibility to supplement or close existing data gaps of the static data, but they can also be used for enriching the static data with further information, such as the position of a temporary construction site.
  • a plausibility check S3 of the read-in data takes place.
  • non-plausible data such as negative maximum speeds, or height information that does not correspond to the typical terrain course, sorted out, or at least marked as faulty for further processing.
  • the plausibility check S3 can be compared with other data classified as correct or plausible, such as, for example, map data.
  • the evaluation S4 of a quality of the data records that were read in beforehand takes place.
  • the quality of a data record describes how much the data set is suitable for the description of an infrastructure segment and further processing.
  • the quality of the data is weighted such that at least one data source is defined or recognized as more trustworthy or more accurate than the other data sources and whose data parameters are adopted in case of doubt or in the case of several data sources which supply the same data parameters. a majority vote can be taken. It is also conceivable to define different trustworthy data for different route sections.
  • a first record for a first stretch can be defined as trusted. However, this turns out to be bad or unfit for a subsequent second stretch. Instead, a second record is trusted and used as a possible data foundation.
  • This weighting happens on a case-by-case basis not only on a data source-specific basis, but can also be changed by data-parameter-specific exemptions. For example, in case of doubt the data of a data source should be used, if especially the data parameter "Direction Indicator" is contradictory, it should be taken over by another data source.
  • the data records defined as trustworthy are also referred to as nodes or anchor points. They serve, as described above, the possibility of retreating to these data records, if other data sets contain plausible or erroneous information.
  • the now prepared data records are merged into a further step by means of data fusion S5 to form a data record in unit format.
  • filters and compensation calculations are applied to data gaps or implausible locations which are not determined by the anchor points could be resolved.
  • the compensation calculations can also be used to correct the resolution of the data records in order to obtain a desired node resolution of the new data record.
  • a routing mechanism can be used to use closely adjacent routes (in this way) In one case, for example, the GPS measured route data is prioritized higher than the timetable data for a route section).
  • Result of the data fusion S5 is a data record in the unit format, which is subjected in a further step to a further plausibility check S6 to ensure that the transition points of this data record to a next, subsequent data record, which already exists in the unit format, are consistent and plausible.
  • This plausibility check S6 essentially follows the same steps as those during the data fusion S5, except that now a check is made against adjacent data records.
  • This method has the advantage of generating, in large part, automatically a large number of consistent, complete data records which have at least the same or a higher degree of detail and at least the same or a higher data quality.
  • Fig. 2 shows a further flowchart of an embodiment of the method according to the invention with a detailed representation of individual processing steps up to the completion of the merged new data set 60th
  • a standardization of the format of individual data records 10a, 10b, 10c, 10d is carried out via a conversion 12.
  • the individual data sets 10a, 10b, 10c, 10d are in various formats before conversion by individually adapted converters 12a, 12b, 12c, 12d. That they describe certain sections of the route in different ways.
  • the data set 10a describes a distance based on absolute distance kilometers, whereas data set 10b only describes distances between two stops.
  • the converters 12a, 12b, 12c, 12d fulfill the task of converting all data records to a desired, uniform format.
  • the thus unified data sets 10a, 10b, 10c, 10d are subsequently fused by means of the data fusion 14 into a data record in unit format, whereby a data pool 16 in the unit format is obtained.
  • the consolidation 18 of the data pool 16 takes place, wherein redundancies, ie overlaps and doublings of data of the data pool 16 are determined and / or corrected.
  • the data pool 20 thus obtained is then subjected to a general plausibility check 22, which basically checks whether the data records 10a, 10b, 10c, 10d are now linked in the correct format and in a suitable form to a data pool 20. If necessary, corrections of the data pool 20 are made at this point and / or process steps are carried out again and / or messages are output to a user.
  • a general plausibility check 22 basically checks whether the data records 10a, 10b, 10c, 10d are now linked in the correct format and in a suitable form to a data pool 20. If necessary, corrections of the data pool 20 are made at this point and / or process steps are carried out again and / or messages are output to a user.
  • the data pool 24 thus obtained is now linked by means of an application-dependent link 26 with further application-dependent data, such as, for example, vehicle or track-specific data, or specific routes.
  • the data pool 28 thus linked is subsequently subjected to a number of checks in order finally to obtain a finished, error-free new data record 60.
  • steps 30, 34, 38, 42 track characteristics are checked to ensure that particular information has not been altered or deleted by data fusion 14 in unit format.
  • the gradient determination 42 checks whether an existing gradient is plausible, or whether the merger has given rise to a gradient value which is too high for the operation of a rail vehicle.
  • the data pool 44 in unit format thus obtained is subsequently examined in further checks with regard to special features of the infrastructure.
  • steps 46, 50, 54 starting from the data pool 44 in the unified format, a check of the speed limits 46 is first made, so that it is ensured that the data pool 48 in the unit format contains the necessary and safety-critical speed restrictions.
  • a crossing point of two intersecting sections in the data pool 52 is determined in unit format, it can be ascertained from the height profiles of both sections whether these two sections actually intersect, or if an underpass is present through which both sections run independently of each other ,
  • level crossings or bridges are detected or corrected in this step.
  • correction or supplementation of this information takes place, for example, by the user, or by the automatic setting of the transitions, intersections or stops by the, as trusted classified data.
  • the generation 58 of application data from the previously created data pool 56 takes place in unit format.
  • the general information of the data pool 56 is transferred into vehicle-specific new data records 60 in order to be able to transfer these to any vehicles.

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  • Engineering & Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • General Health & Medical Sciences (AREA)
  • Traffic Control Systems (AREA)
  • Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
EP18166626.4A 2017-04-13 2018-04-10 Fusion de données liées à l'infrastructure, en particulier de données liées à l'infrastructure pour véhicules ferroviaires Revoked EP3388307B1 (fr)

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
DE102017206446.3A DE102017206446A1 (de) 2017-04-13 2017-04-13 Fusion von infrastrukturbezogenen Daten, insbesondere von infrastrukturbezogenen Daten für Schienenfahrzeuge

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EP3388307A2 true EP3388307A2 (fr) 2018-10-17
EP3388307A3 EP3388307A3 (fr) 2018-11-14
EP3388307B1 EP3388307B1 (fr) 2021-10-20

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EP18166626.4A Revoked EP3388307B1 (fr) 2017-04-13 2018-04-10 Fusion de données liées à l'infrastructure, en particulier de données liées à l'infrastructure pour véhicules ferroviaires

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EP (1) EP3388307B1 (fr)
DE (1) DE102017206446A1 (fr)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110497938A (zh) * 2019-08-26 2019-11-26 湖南中车时代通信信号有限公司 一种用于列车运行监控系统的质量实时监测诊断方法、装置以及计算机可读存储介质
EP3812239A1 (fr) * 2019-10-21 2021-04-28 Siemens Mobility GmbH Plateforme assistée par ordinateur permettant de représenter une infrastructure ferroviaire et son procédé de fonctionnement
WO2022266863A1 (fr) * 2021-06-22 2022-12-29 华为技术有限公司 Procédé de communication de coordination véhicule-route, procédé de traitement de données, système de détection et appareil de fusion

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DE102017206446A1 (de) 2017-04-13 2018-10-18 Knorr-Bremse Systeme für Schienenfahrzeuge GmbH Fusion von infrastrukturbezogenen Daten, insbesondere von infrastrukturbezogenen Daten für Schienenfahrzeuge

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110497938A (zh) * 2019-08-26 2019-11-26 湖南中车时代通信信号有限公司 一种用于列车运行监控系统的质量实时监测诊断方法、装置以及计算机可读存储介质
EP3812239A1 (fr) * 2019-10-21 2021-04-28 Siemens Mobility GmbH Plateforme assistée par ordinateur permettant de représenter une infrastructure ferroviaire et son procédé de fonctionnement
WO2022266863A1 (fr) * 2021-06-22 2022-12-29 华为技术有限公司 Procédé de communication de coordination véhicule-route, procédé de traitement de données, système de détection et appareil de fusion

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Publication number Publication date
EP3388307B1 (fr) 2021-10-20
EP3388307A3 (fr) 2018-11-14
DE102017206446A1 (de) 2018-10-18

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