GPS Data and Kilometer Marker Mapping Method, System, Device and Storage Medium

Abstract

The present invention discloses a method, system, device and storage medium for mapping GPS data and kilometer markers, relating to the field of train control. In this solution, first, a kilometer marker-GPS mapping prediction model is established based on the mapping relationship between the kilometer markers and GPS data of each station, so as to obtain the mapping relationship between the kilometer markers and predicted GPS data of each working condition generated by the kilometer marker-GPS mapping prediction model. Furthermore, a GPS-kilometer marker mapping prediction model is established, and then the real-time GPS data sent by the train is substituted into the GPS-kilometer marker mapping prediction model to determine the real-time kilometer marker corresponding to the real-time GPS data. It can be seen that in this application, a model for determining the corresponding kilometer marker through GPS data is established, and the real-time kilometer marker can be determined through the real-time GPS data during the operation of the train, so as to determine whether the train is about to run into the corresponding working condition, and thus the stability control of the train can be carried out in advance.

Description

Technical Field

[0001] The present invention relates to the field of train control, and particularly to a method, system, device and storage medium for mapping GPS data to kilometer markers. Background Art

[0002] When a train runs on a track, the position data sent to the ground is usually GPS (Global Positioning System) data. However, the line information of various working conditions on the track is usually marked by kilometer markers, such as tunnels, bridges, and switches on the track line. When the train runs into different working conditions, the vehicle may have faults that affect the operation of the vehicle, such as car body shaking or instability. However, since it is impossible to determine whether the train has the above-mentioned faults due to running into different working conditions based on the GPS data sent by the train, it is impossible to perform stable control on the train before it runs into the corresponding working conditions. Summary of the Invention

[0003] The purpose of the present invention is to provide a method, system, device and storage medium for mapping GPS data to kilometer markers, establish a model for determining the corresponding kilometer marker through GPS data, and then determine the real-time kilometer marker through the real-time GPS data during the train operation, so as to determine whether the train is about to run into the corresponding working condition, and thus perform stability control on the train in advance.

[0004] To solve the above technical problems, the present invention provides a method for mapping GPS data to kilometer markers, including:

[0005] Establishing a kilometer marker-GPS mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each station;

[0006] Substituting the kilometer markers of each working condition into the kilometer marker-GPS mapping prediction model, obtaining the predicted GPS data of each working condition generated by the kilometer marker-GPS mapping prediction model, and determining the mapping relationship between the kilometer markers and predicted GPS data of each working condition;

[0007] Establishing a GPS-kilometer marker mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each station, and the mapping relationship between the kilometer markers and predicted GPS data of each working condition;

[0008] Substituting the real-time GPS data sent by the train into the GPS-kilometer marker mapping prediction model to determine the real-time kilometer marker corresponding to the real-time GPS data.

[0009] Preferably, before establishing the GPS-kilometer marker mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each station, and the mapping relationship between the kilometer markers and predicted GPS data of each working condition, it further includes:

[0010] Obtain each real-time corrected GPS data sent when the train is running on the track line;

[0011] Correct each of the predicted GPS data based on each of the real-time corrected GPS data;

[0012] Determine the mapping relationship between the kilometer markers of each of the corrected working conditions and the predicted GPS data.

[0013] Preferably, correcting each of the predicted GPS data based on each of the real-time corrected GPS data includes:

[0014] Calculate the Euclidean distance between each of the predicted GPS data and each of the real-time corrected GPS data respectively;

[0015] Determine each to-be-corrected real-time GPS data among each of the real-time corrected GPS data whose calculation results with each of the predicted GPS data are the minimum values; the predicted GPS data and the to-be-corrected real-time GPS data are in one-to-one correspondence;

[0016] Correct each of the predicted GPS data based on each of the to-be-corrected real-time GPS data respectively in one-to-one correspondence.

[0017] Preferably, after establishing the GPS-kilometer marker mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each of the stations, and the mapping relationship between the kilometer markers and predicted GPS data of each of the working conditions, it further includes:

[0018] Determine the positioning times of the train sending the real-time corrected GPS data within the preset section, and the positioning quantity of the kilometer markers within the preset section;

[0019] If the positioning times are greater than the positioning quantity, substitute each of the real-time corrected GPS data within the preset section into the GPS-kilometer marker mapping prediction model to generate each interpolated kilometer marker and insert it into the preset section.

[0020] Preferably, after determining the positioning times of the train sending the real-time corrected GPS data within the preset section, and the positioning quantity of the kilometer markers within the preset section, it further includes:

[0021] If the positioning times are less than the positioning quantity, set that multiple GPS data located within the preset section in the GPS-kilometer marker mapping prediction model correspond to one kilometer marker.

[0022] Preferably, after establishing a GPS-kilometer post mapping prediction model based on the mapping relationships between the kilometer posts and GPS data of each of the stations, and between the kilometer posts and predicted GPS data of each of the operating conditions, the method further includes:

[0023] Obtaining each optimized sample GPS data sent when the train travels on the track line;

[0024] Determining the sample kilometer posts respectively corresponding to each of the optimized sample GPS data;

[0025] Performing an optimization process on the GPS-kilometer post mapping prediction model based on the mapping relationship between the optimized sample GPS data and the sample kilometer posts, to generate an optimized GPS-kilometer post mapping prediction model;

[0026] Substituting the real-time GPS data sent by the train into the GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data, including:

[0027] Substituting the real-time GPS data sent by the train into the optimized GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data.

[0028] Preferably, substituting the real-time GPS data sent by the train into the optimized GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data, including:

[0029] Substituting the real-time GPS data sent by the train into the optimized GPS-kilometer post mapping prediction model to determine the first real-time kilometer post corresponding to the real-time GPS data;

[0030] Substituting the real-time GPS data sent by the train into the GPS-kilometer post mapping prediction model to determine the second real-time kilometer post corresponding to the real-time GPS data;

[0031] Determining the real-time kilometer post based on the first kilometer post and the second kilometer post.

[0032] To solve the above technical problems, the present invention provides a GPS data and kilometer post mapping system, including:

[0033] A first establishing unit, configured to establish a kilometer post-GPS mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each station;

[0034] An obtaining unit, configured to substitute the kilometer posts of each operating condition into the kilometer post-GPS mapping prediction model, obtain the predicted GPS data of each of the operating conditions generated by the kilometer post-GPS mapping prediction model, and determine the mapping relationship between the kilometer posts and the predicted GPS data of each operating condition;

[0035] A second establishment unit, configured to establish a GPS-kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each of the stations, and the mapping relationship between the kilometer posts and predicted GPS data of each of the working conditions.

[0036] A determination unit, configured to substitute the real-time GPS data sent by the train into the GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data.

[0037] To solve the above technical problems, the present invention provides a GPS data and kilometer post mapping device, including:

[0038] A memory, configured to store a computer program;

[0039] A processor, configured to implement the steps of the GPS data and kilometer post mapping method as described above when executing the computer program.

[0040] To solve the above technical problems, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the GPS data and kilometer post mapping method as described above are implemented.

[0041] The present application provides a GPS data and kilometer post mapping method, system, device and storage medium, relating to the field of train control. In this solution, first, a kilometer post-GPS mapping prediction model is established based on the mapping relationship between the kilometer posts and GPS data of each station to obtain the mapping relationship between the kilometer posts and predicted GPS data of each working condition generated by the kilometer post-GPS mapping prediction model, and then a GPS-kilometer post mapping prediction model is established, so as to substitute the real-time GPS data sent by the train into the GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data. It can be seen that in the present application, a model for determining the corresponding kilometer post through GPS data is established, and the real-time kilometer post can be determined by the real-time GPS data during the train operation, so as to determine whether the train is about to run into the corresponding working condition, and thus perform stability control on the train in advance. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the prior art and embodiments. Obviously, the drawings described below are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0043] Figure 1Flow schematic diagram of a method for mapping GPS data to kilometer markers provided by the present invention;

[0044] Figure 2 Structural schematic diagram of a system for mapping GPS data to kilometer markers provided by the present invention;

[0045] Figure 3 Structural schematic diagram of a device for mapping GPS data to kilometer markers provided by the present invention. Detailed implementation manners

[0046] The core of the present invention is to provide a method, a system, a device and a storage medium for mapping GPS data to kilometer markers, establish a model for determining the corresponding kilometer markers through GPS data, and then determine the real-time kilometer markers through the real-time GPS data during the train operation, so as to determine whether the train is about to run to the corresponding working conditions, and thus control the stability of the train in advance.

[0047] To make the objectives, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Please refer to Figure 1 , Figure 1 Flow schematic diagram of a method for mapping GPS data to kilometer markers provided by the present invention. The method includes:

[0049] S11: Establish a kilometer marker - GPS mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each station;

[0050] In the prior art, when a train is positioned on a track line, it is positioned through GPS data. However, each position on the track line is usually positioned by kilometer markers. Therefore, after the ground system receives the GPS data sent by the train, it is impossible to determine which position the train is on the track, nor can it determine whether the train is about to run to a certain working condition for prediction, and it is impossible to avoid the train being unable to run stably when it runs to the corresponding working condition. For example, when the train runs onto a bridge, the train body may shake, resulting in a decline in the riding experience of passengers. However, in the prior art, it is impossible to determine in advance whether the train is about to run onto a bridge, nor can it control the train to run stably when it runs onto a bridge.

[0051] To solve the above technical problems, in this application, a kilometer post - GPS mapping model is first established according to the mapping relationship between the kilometer posts of stations and GPS data. The kilometer posts of each station can be obtained from the railway administration, and the GPS data of the stations can be obtained by importing the information of each high - speed railway station in China through Bigmap GIS Office. That is, the mapping relationship between the kilometer posts of the stations and the GPS data is known. After establishing the kilometer post - GPS mapping prediction model based on the known mapping relationship between the kilometer posts of the stations and the GPS data, the GPS data of the stations can be obtained by inputting the kilometer posts of the stations into the kilometer post - GPS mapping prediction model. That is, the kilometer post - GPS mapping prediction model can obtain the corresponding GPS data when the kilometer posts of the stations are known.

[0052] S12: Substitute the kilometer posts of each working condition into the kilometer post - GPS mapping prediction model, obtain the predicted GPS data of each working condition generated by the kilometer post - GPS mapping prediction model, and determine the mapping relationship between the kilometer posts and the predicted GPS data of each working condition;

[0053] After establishing the kilometer post - GPS mapping prediction model, the predicted GPS data corresponding to the kilometer posts of the working conditions can be obtained by substituting the kilometer posts of each working condition into the kilometer post - GPS mapping prediction model. That is, after training the kilometer post - GPS mapping prediction model through the mapping relationship between the kilometer posts and GPS data of the stations, the kilometer posts can be input into the kilometer post - GPS mapping prediction model to obtain the predicted GPS data corresponding to the kilometer posts.

[0054] Correspondingly, the kilometer posts of the working conditions can also be obtained from the railway administration, such as the kilometer posts of working conditions such as bridges, uphill and downhill, tunnels, and turns.

[0055] S13: Establish a GPS - kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each station, and the mapping relationship between the kilometer posts and the predicted GPS data of each working condition;

[0056] After determining the mapping relationship between the kilometer posts and GPS data of the working conditions and already knowing the mapping relationship between the kilometer posts and GPS data of the stations, establish a GPS - kilometer post mapping prediction model. That is, the GPS data can be input to generate a model of kilometer posts.

[0057] Based on this, by training the GPS - kilometer post mapping prediction model through the mapping relationship between the kilometer posts and GPS data of the working conditions and the mapping relationship between the kilometer posts and GPS data of the stations, the kilometer posts corresponding to the known GPS data can be determined through the GPS - kilometer post mapping prediction model.

[0058] S14: Substitute the real-time GPS data sent by the train into the GPS-kilometer marker mapping prediction model to determine the real-time kilometer marker corresponding to the real-time GPS data.

[0059] After training the GPS-kilometer marker mapping prediction model, when the train is running on the track line and sending GPS data, substituting the current real-time GPS data of the train into the GPS-kilometer marker mapping prediction model can determine the kilometer marker of the current location of the train, so as to pre-determine whether the train is about to enter the corresponding working condition and perform stability control on the train in advance.

[0060] For example, after determining the real-time kilometer marker of the train according to the current real-time GPS data of the train and determining that the train is about to enter a bridge, in order to avoid the train jittering when running on the bridge, stability control can be performed on the train in advance according to the running situation of the train on the bridge. For example, closed-loop negative feedback control is performed on the train to ensure that the train can still maintain stability after driving onto the bridge.

[0061] It should be noted that the kilometer marker-GPS mapping prediction model is a model that inputs a kilometer marker and obtains GPS data (including longitude data and latitude data), while the GPS-kilometer marker mapping prediction model is a model that does not input GPS data but obtains the kilometer marker.

[0062] In summary, in this application, a model for determining the corresponding kilometer marker through GPS data is established. Subsequently, the real-time kilometer marker can be determined through the real-time GPS data during the train operation to determine whether the train is about to run into the corresponding working condition, so as to perform stability control on the train in advance.

[0063] Based on the above embodiments:

[0064] As a preferred embodiment, before establishing the GPS-kilometer marker mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each station and the mapping relationship between the kilometer markers and predicted GPS data of each working condition, it further includes:

[0065] Obtain each real-time corrected GPS data sent when the train is running on the track line;

[0066] Correct each predicted GPS data based on each real-time corrected GPS data;

[0067] Determine the mapping relationship between the kilometer markers and predicted GPS data of each working condition after correction.

[0068] In this embodiment, considering that the kilometer post - GPS mapping prediction model is trained based on the mapping relationship between the kilometer posts of stations and GPS data, but there are a large number of working conditions on the track line, the GPS data obtained after substituting the kilometer posts of the working conditions into the kilometer post - GPS mapping prediction model may have errors. For example, the GPS data is before the position of the kilometer post, which will cause the kilometer posts obtained in the subsequently trained GPS - kilometer post mapping prediction model to be after the kilometer posts corresponding to the actual GPS data, resulting in the train entering the stability control in advance and reducing the operating efficiency of the train.

[0069] To solve the above - mentioned technical problems, in this embodiment, the train is controlled to run on the track line and positioned to obtain each real - time corrected GPS data during the train operation, so as to correct each predicted GPS data, make the correspondence between the GPS data and the position of the kilometer post more accurate, and perform stability control more precisely.

[0070] After correcting each predicted GPS data, determine the mapping information between the kilometer posts and the predicted GPS data of each corrected working condition, so as to train a more accurate GPS - kilometer post mapping prediction model and obtain a more accurate kilometer post based on the GPS data of the train.

[0071] As a preferred embodiment, correcting each predicted GPS data based on each real - time corrected GPS data includes:

[0072] Calculate the Euclidean distance between each predicted GPS data and each real - time corrected GPS data respectively;

[0073] Determine each real - time corrected GPS data to be corrected among each real - time corrected GPS data whose calculation results with each predicted GPS data are the minimum values; the predicted GPS data and the real - time corrected GPS data to be corrected are in one - to - one correspondence;

[0074] Correct each predicted GPS data based on each real - time corrected GPS data to be corrected respectively in one - to - one correspondence.

[0075] In this embodiment, when correcting each predicted GPS data, specifically, calculate the Euclidean distance between each predicted GPS data and each real - time corrected GPS data respectively to determine the real - time corrected GPS data to be corrected corresponding to each predicted GPS data, so as to correct the predicted GPS data.

[0076] For example, after a train runs on a track line, 100 real-time corrected GPS data are generated, while there are 10 predicted GPS data. First, the Euclidean distance is calculated between the first predicted GPS data and the 100 real-time corrected GPS data to determine the real-time corrected GPS data with the minimum calculation result among the 100 real-time corrected GPS data and the first predicted GPS data. This real-time corrected GPS data is the real-time GPS data to be corrected corresponding to the first predicted GPS data, and the first predicted GPS data is corrected based on this real-time GPS data to be corrected. Subsequently, the Euclidean distance is calculated between the second predicted GPS data and the 100 real-time corrected GPS data to determine the real-time corrected GPS data with the minimum calculation result among the 100 real-time corrected GPS data and the second predicted GPS data. This real-time corrected GPS data is the real-time GPS data to be corrected corresponding to the second predicted GPS data, and the second predicted GPS data is corrected based on this real-time GPS data to be corrected. And so on, the 10 predicted GPS data are corrected respectively.

[0077] When the train runs on the track line, a real-time corrected GPS data can be generated every preset distance. The smaller the preset distance is, the more accurate the results of correcting each predicted GPS data will be.

[0078] As a preferred embodiment, after establishing a GPS-kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each station and the mapping relationship between the kilometer posts and predicted GPS data of each working condition, it further includes:

[0079] Determine the positioning times of the real-time corrected GPS data sent by the train within a preset section and the positioning quantity of the kilometer posts within the preset section;

[0080] If the positioning times are greater than the positioning quantity, substitute each real-time corrected GPS data within the preset section into the GPS-kilometer post mapping prediction model to generate each interpolated kilometer post and insert it into the preset section.

[0081] Considering that in the prior art, the road conditions within a preset section may be relatively stable and there may be fewer kilometer posts set in this preset section. If the train sends a real-time corrected GPS data every preset distance when running on the track line, but the distance of the preset section is much greater than the preset distance, it is inconvenient to determine the kilometer post corresponding to the GPS data within this preset section, that is, the specific position of the train on the track line cannot be accurately located.

[0082] In this embodiment, to solve the above technical problem, if the positioning times of the real-time corrected GPS generated within the preset section are greater than the positioning quantity of the kilometer posts within the preset section, kilometer posts are inserted into the preset section to correspond to the real-time corrected GPS data.

[0083] Specifically, for example, within a preset section, the number of positioning times for the train to send real-time corrected GPS data is 10 times, while the number of positioning of kilometer markers in this preset section is only two. In this embodiment, the 10 real-time corrected GPS data within the preset section are substituted into the GPS-kilometer marker mapping prediction model to generate corresponding interpolated kilometer markers, which are inserted into the preset section to ensure that the preset section includes kilometer markers corresponding to each real-time corrected GPS data, so as to perform more accurate positioning of the train.

[0084] The interpolated kilometer markers can be set as curves on the track line, etc.

[0085] As a preferred embodiment, after determining the number of positioning times for the train to send real-time corrected GPS data within the preset section and the number of positioning of kilometer markers within the preset section, it further includes:

[0086] If the number of positioning times is less than the number of positioning, then set that multiple GPS data located within the preset section in the GPS-kilometer marker mapping prediction model correspond to one kilometer marker.

[0087] And if the number of positioning times for sending real-time corrected GPS data within this preset section is less than the number of positioning of kilometer markers within the preset section, then multiple GPS data can correspond to one kilometer marker. For example, if the number of positioning times for sending real-time corrected GPS data within the preset section is 10 times and the number of positioning of kilometer markers within the preset section is 20, then the first kilometer marker can correspond to the two real-time corrected GPS data closest to the first kilometer marker, and the second kilometer marker can correspond to the two real-time corrected GPS data closest to the second kilometer marker, realizing that multiple real-time corrected GPS data correspond to one kilometer marker.

[0088] As a preferred embodiment, after establishing the GPS-kilometer marker mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each station and the mapping relationship between the kilometer markers and predicted GPS data of each working condition, it further includes:

[0089] Obtain each optimized sample GPS data sent by the train when it travels on the track line;

[0090] Determine the sample kilometer markers respectively corresponding to each optimized sample GPS data;

[0091] Perform optimization processing on the GPS-kilometer marker mapping prediction model based on the mapping relationship between the optimized sample GPS data and the sample kilometer markers to generate an optimized GPS-kilometer marker mapping prediction model;

[0092] Substitute the real-time GPS data sent by the train into the GPS-kilometer marker mapping prediction model to determine the real-time kilometer marker corresponding to the real-time GPS data, including:

[0093] Substitute the real-time GPS data sent by the train into the optimized GPS-kilometer marker mapping prediction model to determine the real-time kilometer marker corresponding to the real-time GPS data.

[0094] In this embodiment, considering that the GPS-kilometer marker mapping prediction model is trained using the mapping relationship between the kilometer markers and GPS data under working conditions and the mapping relationship between the kilometer markers and GPS data at stations, and the training samples are few, there may also be mapping errors in the GPS-kilometer marker mapping prediction model. To further ensure the accuracy of the real-time kilometer marker of the finally determined real-time GPS data, tuning sample GPS data and the corresponding sample kilometer markers are added to perform tuning processing on the GPS-kilometer marker mapping prediction model to generate an optimized GPS-kilometer marker mapping prediction model. By substituting the real-time GPS data sent by the train into the optimized GPS-kilometer marker mapping prediction model, a more accurate real-time kilometer marker corresponding to the real-time GPS data is determined, realizing more accurate positioning of the train.

[0095] As a preferred embodiment, substituting the real-time GPS data sent by the train into the optimized GPS-kilometer marker mapping prediction model to determine the real-time kilometer marker corresponding to the real-time GPS data includes:

[0096] Substitute the real-time GPS data sent by the train into the optimized GPS-kilometer marker mapping prediction model to determine the first real-time kilometer marker corresponding to the real-time GPS data;

[0097] Substitute the real-time GPS data sent by the train into the GPS-kilometer marker mapping prediction model to determine the second real-time kilometer marker corresponding to the real-time GPS data;

[0098] Determine the real-time kilometer marker based on the first kilometer marker and the second kilometer marker.

[0099] In this embodiment, considering that there is a certain subjectivity when obtaining the tuning sample GPS data, there may also be some errors in all the finally obtained real-time kilometer markers. Therefore, the real-time kilometer marker is determined based on the optimized GPS-kilometer marker mapping prediction model and the GPS-kilometer marker mapping prediction model. For example, the average value of the first kilometer marker and the second kilometer marker is calculated to determine a more accurate real-time kilometer marker corresponding to the real-time GPS data.

[0100] Please refer to Figure 2 , Figure 2 which is a schematic structural diagram of a GPS data and kilometer marker mapping system provided by the present invention, including:

[0101] A first establishing unit 21, configured to establish a kilometer marker-GPS mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each station;

[0102] An acquisition unit 22 is configured to substitute the kilometer markers of each working condition into the kilometer marker - GPS mapping prediction model, obtain the predicted GPS data of each working condition generated by the kilometer marker - GPS mapping prediction model, and determine the mapping relationship between the kilometer markers of each working condition and the predicted GPS data;

[0103] A second establishment unit 23 is configured to establish a GPS - kilometer marker mapping prediction model based on the mapping relationship between the kilometer markers and GPS data of each site, and the mapping relationship between the kilometer markers of each working condition and the predicted GPS data;

[0104] A determination unit 24 is configured to substitute the real - time GPS data sent by the train into the GPS - kilometer marker mapping prediction model to determine the real - time kilometer marker corresponding to the real - time GPS data.

[0105] For the introduction of a GPS data and kilometer marker mapping system provided by the present invention, please refer to the above - mentioned method embodiments, and the present invention will not be elaborated herein.

[0106] Please refer to Figure 3 , Figure 3 FIG. is a schematic structural diagram of a GPS data and kilometer marker mapping device provided by the present invention. The device includes:

[0107] A memory 31 is configured to store a computer program;

[0108] A processor 32 is configured to implement the steps of the GPS data and kilometer marker mapping method as described above when executing the computer program.

[0109] For the introduction of a GPS data and kilometer marker mapping device provided by the present invention, please refer to the above - mentioned method embodiments, and the present invention will not be elaborated herein.

[0110] A computer program is stored on a computer - readable storage medium in the present invention. When the computer program is executed by a processor, the steps of the GPS data and kilometer marker mapping method as described above are implemented.

[0111] For the introduction of the computer - readable storage medium provided by the present invention, please refer to the above - mentioned method embodiments, and the present invention will not be elaborated herein.

[0112] It should also be noted that in this specification, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variation thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0113] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for mapping GPS data to kilometer markers, characterized in that, Including: Establish a kilometer post - GPS mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each site; Substitute the kilometer posts of each working condition into the kilometer post - GPS mapping prediction model, obtain the predicted GPS data of each working condition generated by the kilometer post - GPS mapping prediction model, and determine the mapping relationship between the kilometer posts and the predicted GPS data of each working condition; Establish a GPS - kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each site, and the mapping relationship between the kilometer posts and the predicted GPS data of each working condition; Substitute the real - time GPS data sent by the train into the GPS - kilometer post mapping prediction model to determine the real - time kilometer post corresponding to the real - time GPS data; Before establishing a GPS - kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each site, and the mapping relationship between the kilometer posts and the predicted GPS data of each working condition, it further includes: Obtain each real - time corrected GPS data sent by the train when it travels on the track line; After establishing a GPS - kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each site, and the mapping relationship between the kilometer posts and the predicted GPS data of each working condition, it further includes: Determine the positioning times of the real - time corrected GPS data sent by the train in the preset section, and the positioning quantity of the kilometer posts in the preset section; if the positioning times are greater than the positioning quantity, substitute each real - time corrected GPS data in the preset section into the GPS - kilometer post mapping prediction model to generate each interpolated kilometer post and insert it into the preset section.

2. The method for mapping GPS data and kilometer markers according to claim 1, characterized in that, Before establishing a GPS - kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each site, and the mapping relationship between the kilometer posts and the predicted GPS data of each working condition, it further includes: Correct each predicted GPS data based on each real - time corrected GPS data; Determine the mapping relationship between the kilometer posts and the predicted GPS data of each corrected working condition.

3. The method for mapping GPS data and kilometer markers according to claim 2, characterized in that, Correcting each predicted GPS data based on each real - time corrected GPS data includes: Perform Euclidean distance calculation between each predicted GPS data and each real - time corrected GPS data; Determine each to - be - corrected real - time GPS data in each real - time corrected GPS data whose calculation result with each predicted GPS data is the minimum value; the predicted GPS data and the to - be - corrected real - time GPS data are in one - to - one correspondence; Correct each predicted GPS data based on each to - be - corrected real - time GPS data respectively in one - to - one correspondence.

4. A GPS data and kilometer marker mapping method as claimed in claim 1, wherein, After determining the positioning times of the real - time corrected GPS data sent by the train in the preset section, and the positioning quantity of the kilometer posts in the preset section, it further includes: If the positioning times are less than the positioning quantity, set that multiple GPS data located in the preset section in the GPS - kilometer post mapping prediction model correspond to one kilometer post.

5. A method for mapping GPS data to kilometer markers according to any one of claims 1-4, characterized in that, After establishing the GPS-kilometer post mapping prediction model based on the mapping relationships between the kilometer posts and GPS data of each of the said stations, and the mapping relationships between the kilometer posts and predicted GPS data of each of the said working conditions, the following steps are further included: Obtain each optimized sample GPS data sent when the train is running on the track line; Determine the sample kilometer posts corresponding to each of the said optimized sample GPS data; Perform optimization processing on the GPS-kilometer post mapping prediction model based on the mapping relationship between the optimized sample GPS data and the sample kilometer posts to generate an optimized GPS-kilometer post mapping prediction model; Substitute the real-time GPS data sent by the train into the GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data, including: Substitute the real-time GPS data sent by the train into the optimized GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data.

6. The GPS data and kilometer marker mapping method according to claim 5, characterized in that, Substitute the real-time GPS data sent by the train into the optimized GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data, including: Substitute the real-time GPS data sent by the train into the optimized GPS-kilometer post mapping prediction model to determine the first real-time kilometer post corresponding to the real-time GPS data; Substitute the real-time GPS data sent by the train into the GPS-kilometer post mapping prediction model to determine the second real-time kilometer post corresponding to the real-time GPS data; Determine the real-time kilometer post based on the first real-time kilometer post and the second real-time kilometer post.

7. A GPS data and kilometer marker mapping system, characterized in that It includes: A first establishment unit for establishing a kilometer post-GPS mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each station; An acquisition unit for substituting the kilometer posts of each working condition into the kilometer post-GPS mapping prediction model, obtaining the predicted GPS data of each of the said working conditions generated by the kilometer post-GPS mapping prediction model, and determining the mapping relationship between the kilometer posts and predicted GPS data of each working condition; A second establishment unit for establishing a GPS-kilometer post mapping prediction model based on the mapping relationship between the kilometer posts and GPS data of each of the said stations, and the mapping relationship between the kilometer posts and predicted GPS data of each of the said working conditions; A determination unit for substituting the real-time GPS data sent by the train into the GPS-kilometer post mapping prediction model to determine the real-time kilometer post corresponding to the real-time GPS data; The GPS data and kilometer post mapping system is specifically used for: Obtain each real-time corrected GPS data sent when the train is running on the track line; The GPS data and kilometer post mapping system is specifically used for: Determine the positioning times of the real-time corrected GPS data sent by the train within a preset section, and the positioning quantity of the kilometer posts within the preset section; if the positioning times are greater than the positioning quantity, substitute each of the real-time corrected GPS data within the preset section into the GPS-kilometer post mapping prediction model to generate each interpolated kilometer post and insert it into the preset section.

8. A GPS data and kilometer marker mapping device, characterized in that, It includes: A memory for storing a computer program; A processor, configured to implement the steps of the GPS data and kilometer marker mapping method according to any one of claims 1 to 6 when executing the computer program.

9. A computer-readable storage medium, characterized in that, A computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the GPS data and kilometer marker mapping method according to any one of claims 1 to 6 are implemented.

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