Train position calibration method, device, and medium

Abstract

A train position calibration method, an electronic device, and a computer-readable storage medium. The train position calibration method comprises: acquiring a preset position calibration interval, the preset position calibration interval being determined on the basis of a cumulative distance measurement error of a train speed sensor and a preset train positioning error threshold (S110); acquiring a current cumulative travel distance of a train determined on the basis of the train speed sensor during travelling of the train, the current cumulative travel distance of the train being a distance traveled by the train since the last position calibration position (S120); and when the current cumulative travel distance reaches the preset position calibration interval, by means of virtual balises, calibrating a position determined by the train on the basis of the train speed sensor (S130).

Description

Train calibration method, equipment and medium

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This disclosure claims priority to Chinese patent application number 202311130327.6, filed on August 31, 2023, entitled “Train calibration method, device and medium,” the entire contents of which are incorporated herein by reference. Technical Field

[0003] The embodiments of the present disclosure relate to the field of train operation control, and more specifically, to a train alignment method, an electronic device, and a computer-readable storage medium. Background Art

[0004] Traditional train signaling systems use train speed sensors and physical transponders installed along the train lines to locate, orient, and calibrate the train. After initial positioning, the train uses the speed sensors to accumulate distance measurements, which are then used to determine the train's position based on the initial positioning. The train signaling system uses the physical transponders to correct the train's position as the train passes over them.

[0005] Due to the cost and difficulty of deploying physical balises, a method for correcting train position using virtual balises has emerged. This virtual balise calibration method relies on the accumulated distance measurement results of the speed sensor for intermittent calibration. However, these accumulated distance measurement results often contain errors, resulting in inaccuracies in the train's position.

[0006] Public content

[0007] The disclosed embodiments provide a new train position calibration method, electronic device, and computer-readable storage medium, which can promptly eliminate errors caused by the accumulated ranging of the speed sensor and promptly calibrate the train position.

[0008] In the first aspect, this embodiment provides a train calibration method, including: obtaining a preset calibration interval, which is determined based on the cumulative ranging error of the train speed sensor and a preset train positioning error threshold; obtaining the current cumulative running distance determined based on the train speed sensor during the train's travel, and the current train cumulative running distance is the distance the train has traveled since the previous calibration position; when the current cumulative running distance reaches the preset calibration interval, correcting the train's position determined based on the train speed sensor through a virtual transponder.

[0009] Optionally, before obtaining the preset calibration interval, the method further includes: obtaining the cumulative ranging error of the train speed sensor and the target cumulative running distance determined based on the train speed sensor when the train is traveling on the test section, wherein the target cumulative running distance is the cumulative running distance at the moment when the cumulative ranging error increases to the train positioning error threshold; and determining the target cumulative running distance as the preset calibration interval.

[0010] Optionally, the test section is a section where the satellite positioning accuracy reaches a preset accuracy; obtaining the cumulative ranging error of the train speed sensor when the train travels on the test section includes: obtaining a first cumulative running distance determined based on the train speed sensor and a standard cumulative running distance determined based on satellite positioning when the train travels on the test section; and determining the error between the first cumulative running distance and the standard cumulative running distance as the cumulative ranging error of the train speed sensor.

[0011] Optionally, obtaining the first cumulative running distance determined based on the train speed sensor when the train travels on the test section includes: obtaining multiple first cumulative running distances determined based on the train speed sensor when the train travels on the test section multiple times; determining the error between the first cumulative running distance and the standard cumulative running distance as the cumulative ranging error of the train speed sensor includes: calculating the deviation between each of the first cumulative running distances and the standard cumulative running distance respectively to obtain multiple sets of deviation data; and determining the cumulative ranging error of the train speed sensor based on the multiple sets of deviation data.

[0012] Optionally, determining the cumulative ranging error of the train speed sensor based on the multiple sets of deviations includes: determining a confidence interval of the cumulative ranging error of the train speed sensor based on the multiple sets of deviation data; determining a range of the cumulative ranging error based on the confidence interval; and determining the cumulative ranging error based on the range of the cumulative ranging error.

[0013] Optionally, the correction of the train position determined based on the train speed sensor by the virtual transponder includes: when the train is traveling within the satellite positioning trust area and the current train cumulative running distance reaches the preset calibration interval, obtaining the train position determined based on satellite positioning; when the train is traveling outside the satellite positioning trust area and the current train cumulative running distance reaches the preset calibration interval, obtaining the train position determined based on radar positioning; according to the train position determined based on satellite positioning or the train position determined based on radar positioning, correcting the train position determined based on the train speed sensor by the virtual transponder.

[0014] Optionally, when the train is traveling outside the satellite positioning credible area and the current train's cumulative running distance reaches the preset calibration interval, obtaining the train position determined based on radar positioning includes: when the train is traveling outside the satellite positioning credible area and the current train's cumulative running distance reaches the preset calibration interval, obtaining point cloud data collected by radar; aligning the point cloud data with a point cloud map to obtain the train position determined based on radar positioning; wherein, the point cloud map is a map corrected based on satellite positioning results.

[0015] Optionally, when the train is traveling in a satellite positioning credible area and the current train's cumulative running distance reaches the preset calibration interval, obtaining the train position determined based on satellite positioning includes: when the train is traveling in a satellite positioning credible area and the current train's cumulative running distance reaches the preset calibration interval, obtaining positioning data collected by satellites; and correcting the positioning data collected by satellites based on satellite positioning deviations to obtain the train position determined based on satellite positioning.

[0016] In a second aspect, this embodiment provides an electronic device comprising a memory and a processor, wherein the memory is used to store computer instructions, and the processor is used to call the computer instructions from the memory to execute the train alignment method as described in any one of the first aspects of this disclosure.

[0017] In a third aspect, this embodiment provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the train alignment method as described in any one of the first aspects of this disclosure.

[0018] In this embodiment of the present application, a preset calibration interval is determined based on the cumulative ranging error of the train speed sensor and a preset train positioning error threshold. The current cumulative distance traveled by the train speed sensor is obtained during real-time train travel. When the current cumulative distance reaches the preset calibration interval, the train position determined by the train speed sensor is corrected using a virtual transponder. This allows for timely elimination of errors caused by the cumulative ranging of the speed sensor and for timely correction of the train position.

[0019] Other features and advantages of the present application will become apparent from the following detailed description of exemplary embodiments of the present application with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the application and, together with the description, serve to explain the principles of the application.

[0021] FIG1 is a flow chart of a train alignment method provided in an embodiment of the present application.

[0022] FIG2 is a flow chart of another train alignment method provided in an embodiment of the present application.

[0023] FIG3 is a flow chart of a method for determining a cumulative ranging error of a train speed sensor provided in an embodiment of the present application.

[0024] FIG4 is a flow chart of another method for determining the cumulative ranging error of a train speed sensor provided in an embodiment of the present application.

[0025] FIG5 is a flow chart of another method for determining the cumulative ranging error of a train speed sensor provided in an embodiment of the present application.

[0026] FIG6 is a flow chart of another train alignment method provided in an embodiment of the present application.

[0027] FIG7 is a schematic block diagram of a train calibration system provided in an embodiment of the present application.

[0028] FIG8 is a schematic block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] Various exemplary embodiments of the present application will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangements of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present application.

[0030] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the present disclosure, its application, or uses.

[0031] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0032] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0033] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0034] The present invention discloses a train alignment method. This alignment method is applied to a rail transit train alignment system. To facilitate understanding of the train alignment method provided in the present invention, the train signaling system involved in the present invention is first introduced.

[0035] The train signaling system may include a train positioning system and a train calibration system. The train positioning system may include a train speed sensor positioning system.

[0036] The train speed sensor positioning system locates the train position by measuring the distance using the train axle speed sensor. Based on the train speed sensor positioning system, the preliminary position information of the train can be obtained.

[0037] However, the wheel axle speed sensors have errors in ranging, which leads to cumulative ranging errors during train travel. Consequently, the train position information determined by the train speed sensor positioning system is erroneous. In this case, the train position determined by the train speed sensor positioning system needs to be corrected by the train calibration system.

[0038] Since there is no cumulative error in satellite positioning and lidar positioning, in some embodiments of the present application, the train calibration system may include a GNSS (Global Navigation Satellite System) calibration system, or may include a lidar calibration system, or may include both a GNSS and a lidar calibration system.

[0039] In the embodiment of the present application, the train position determined by the GNSS calibration system can be used to correct the position determined by the train speed sensor. The train position determined by the LiDAR calibration system can also be used to correct the position determined by the train speed sensor.

[0040] Since satellite positioning has high accuracy and good signal quality within the satellite positioning credible area (such as a relatively open location), and outside the satellite positioning credible area (such as a location with dense buildings), there are many lidar point cloud features, high positioning accuracy, and good signal quality, therefore, within the GNSS satellite positioning credible area, the train position determined by the GNSS calibration system can be used to correct the position determined by the train speed sensor; outside the GNSS satellite positioning credible area, the train position determined by the lidar calibration system can be used to correct the position determined by the train speed sensor. This can replace the physical transponder to realize the calibration function and improve the positioning accuracy of the train. At the same time, this can reduce the equipment cost of the system and the labor cost of laying transponders along the line.

[0041] Optionally, the position determined by the train speed sensor may be corrected in real time using the train position determined based on the GNSS calibration system and / or the lidar calibration system.

[0042] Optionally, calibration points where the train's position needs to be corrected can be pre-determined. When a train passes through a calibration point, the train's position, determined by the train positioning system and the train's position, are obtained. Using the train's position determined by the train positioning system, the virtual balise is used to correct the train's position, determined by the train positioning system. Correcting the train's position at a pre-determined calibration point can reduce the problem of frequent position changes. Furthermore, this can, to a certain extent, reduce the operational burden on the train signaling system and minimize resource waste.

[0043] The calibration point for calibrating the train position needs to be determined in advance, and the calibration interval needs to be determined in advance. When the train travels a distance that reaches the calibration interval, it means that the train has reached the calibration point.

[0044] The train alignment method provided by the embodiment of the present application is described in detail below with reference to the accompanying drawings. As shown in FIG1 , the method includes steps S110 to S130.

[0045] Step S110: Obtain a preset calibration interval.

[0046] The preset calibration interval is determined based on the cumulative ranging error of the train speed sensor and a preset train positioning error threshold.

[0047] The cumulative distance measurement error of the train speed sensor is the error caused by the continuous accumulation of distance measurement errors of the wheel axle speed sensors during the train's travel. As the train travels longer or farther, the cumulative distance measurement error of the train speed sensor also increases.

[0048] The train positioning error threshold is determined by the positioning accuracy requirements of the train positioning system. A higher positioning accuracy results in a lower train positioning error threshold. When the cumulative ranging error of the train speed sensor reaches the train positioning error threshold, the train position needs to be corrected.

[0049] The smaller the train positioning error threshold, the smaller the allowed cumulative ranging error of the train speed sensor. In this case, the preset calibration interval is smaller.

[0050] Step S120: obtaining the current accumulated travel distance determined based on the train speed sensor during the train's travel.

[0051] In the embodiment of the present application, the current accumulated travel distance of the train is the distance the train has traveled since the last calibration position.

[0052] In one example, the train speed sensor collects the train speed information in real time from the last calibration position, and determines the current cumulative distance traveled by the train based on the train speed information and travel time.

[0053] It can be understood that the longer the train travels, the greater the current accumulated distance traveled.

[0054] Step S130: When the current accumulated running distance reaches the preset calibration interval, the position of the train determined based on the train speed sensor is corrected by the virtual balise.

[0055] In one example, assuming that the preset calibration interval is 10m, the previous calibration position of the train is 100m away from the starting point of the train. The train starts to move from the 100m position, and the current cumulative running distance determined by the train speed sensor continues to increase. When the current cumulative running distance determined by the train speed sensor increases to 10m, the position determined by the train speed sensor is 110m. Assuming that the running distance determined by the train calibration system is 109.5m, the train calibration system will correct the position of the train determined by the train speed sensor to 109.5m. Then the current cumulative running distance determined by the train speed sensor is cleared to zero, and the new current cumulative running distance determined by the train speed sensor is obtained again.

[0056] In an embodiment of the present application, a preset calibration interval is determined based on the cumulative ranging error of the train speed sensor and a preset train positioning error threshold. The current cumulative distance traveled by the train based on the train speed sensor is obtained during the train's travel. When the current cumulative distance reaches the preset calibration interval, the train's position determined by the train speed sensor is corrected using a virtual transponder. This allows the train calibration system to promptly eliminate the error caused by the cumulative ranging of the speed sensor, promptly correct the positioning results of the train positioning system, and improve the accuracy of train positioning.

[0057] Furthermore, in an embodiment of the present application, when the current cumulative distance traveled reaches a preset calibration interval, the train signal system triggers the train calibration system to correct the train's position, determined based on the train speed sensor, thereby implementing the virtual balise function. Compared to conventional train calibration methods that rely on physical balises, this reduces equipment costs. Furthermore, when the current cumulative distance traveled reaches a preset calibration interval, determining that this is the installation location for the virtual balise reduces installation difficulty and reduces labor costs.

[0058] In the embodiment of the present application, as shown in FIG2 , before step S110 , the train calibration method further includes steps S100 to S102 .

[0059] Step S100: Obtain the cumulative distance measurement error of the train speed sensor and the target cumulative running distance determined based on the train speed sensor when the train travels on the test section.

[0060] In the embodiment of the present application, the target cumulative running distance is the cumulative running distance at the moment when the cumulative ranging error of the train speed sensor increases to the train positioning error threshold.

[0061] In one example of this embodiment, a straight line section of a train route is preselected as a test section. Based on empirical data, a test section of a certain length can be selected so that the cumulative ranging error generated by the train speed sensor when the train travels from the starting point to the end point of the test section is close to the train positioning error threshold.

[0062] In one example of this embodiment, the starting point of the test section can be marked as the initial positioning point. As the train begins to travel from the initial positioning point, a first cumulative distance determined by the train speed sensor and a standard cumulative distance from the initial positioning point are continuously obtained. The error between the first cumulative distance and the standard cumulative distance is determined as the cumulative distance measurement error of the train speed sensor.

[0063] The standard cumulative distance traveled can be manually measured or determined based on a GNSS calibration system. When the standard cumulative distance is determined based on a GNSS calibration system, the test section is a section where the satellite positioning accuracy meets the preset accuracy.

[0064] In this example, as shown in FIG3 , step S100 may include steps S300 to S302 .

[0065] Step S300: obtaining a first cumulative running distance determined based on a train speed sensor and a standard cumulative running distance determined based on satellite positioning when the train travels on a test section.

[0066] In the embodiment of the present application, the first accumulated running distance determined based on the train speed sensor is the distance traveled by the train from the initial positioning of the train.

[0067] It can be understood that, during the process of the train running on the test section, the obtained first cumulative running distance and the standard cumulative running distance both gradually increase.

[0068] Step S302: Determine the error between the first cumulative running distance and the standard cumulative running distance as the cumulative distance measurement error of the train speed sensor.

[0069] It is understood that as the train travels along the test section, the cumulative distance measurement error of the train speed sensor gradually increases. When the cumulative distance measurement error of the train speed sensor increases to the train positioning error threshold, the first cumulative distance determined based on the train speed sensor at this time is used as the target cumulative distance.

[0070] In another example of this embodiment, a first cumulative running distance determined by a train speed sensor when the train travels from the starting point of the test section to the end point can be obtained. Based on the first cumulative running distance and the standard cumulative running distance of the test section, the cumulative ranging error A of the train speed sensor is calculated. When the calculated cumulative ranging error A of the train speed sensor is greater than the train positioning error threshold, the length of the test section is shortened. The above steps are repeated to calculate the cumulative ranging error B of the train speed sensor. When the calculated cumulative ranging error B of the train speed sensor is less than the train positioning error threshold, the length of the test section is increased. Until the calculated cumulative ranging error C of the train speed sensor is equal to the train positioning error threshold, the first cumulative running distance determined based on the train speed sensor is the target cumulative running distance.

[0071] In an example of this embodiment, the method for determining the cumulative ranging error of the train speed sensor, as shown in FIG4 , may include steps S400 to S404 .

[0072] Step S400: obtaining a plurality of first accumulated travel distances determined based on a train speed sensor when the train travels on a test section multiple times.

[0073] In the embodiment of the present application, the test sections can be different sections or the same section, as long as the section distances are the same.

[0074] Preferably, the train travels on different sections of the same distance. A first cumulative travel distance determined based on a train speed sensor each time the train travels the distance is obtained.

[0075] It is understandable that there may be deviations between the multiple first accumulated running distances.

[0076] In one example, the first cumulative running distance is S_PULSE, the standard cumulative running distance is S_GNSS, and the deviation between the first cumulative running distance and the standard cumulative running distance is diff=(S_PULSE-S_GNSS) / S_GNSS.

[0077] Step S402 : Calculate the deviation between each first cumulative running distance and the standard cumulative running distance respectively to obtain multiple sets of deviation data.

[0078] In the embodiment of the present application, due to the interference of random noise, the multiple groups of deviation data between the multiple first cumulative running distances and the standard cumulative running distances obey the normal distribution.

[0079] Step S404: determining the cumulative ranging error of the train speed sensor based on the multiple sets of deviation data.

[0080] In an example of this embodiment, in step S404 , the average values ​​of multiple groups of deviation data may be directly calculated to obtain the cumulative ranging error of the train speed sensor.

[0081] In another example of this embodiment, as shown in FIG5 , step S404 may include steps S500 to S504 .

[0082] Step S500 : determining a confidence interval of the cumulative ranging error of the train speed sensor based on the multiple sets of deviation data.

[0083] In one example of this embodiment, the mean μ and standard deviation σ of the above-mentioned multiple sets of deviation data can be calculated, and the confidence interval determined based on the mean μ and standard deviation σ of the above-mentioned multiple sets of deviation data is (μ-Z*σ, μ+Z*σ). Wherein, Z is an integer. The selection of Z needs to be determined based on the statistical probability required to be achieved. The closer the statistical probability is to 100%, the larger the Z value. For example, when the statistical probability is required to reach 99.73%, the Z value is 3.

[0084] Step S502: Determine the range of the cumulative ranging error of the train speed sensor according to the confidence interval.

[0085] In one example, when the statistical probability requirement reaches 99.73%, the corresponding speed sensor cumulative error range is (μ-3*σ, μ+3*σ).

[0086] Step S504: determining the cumulative ranging error according to the range of the cumulative ranging error.

[0087] Preferably, when the cumulative error range of the speed sensor is (μ-3*σ, μ+3*σ), the cumulative ranging error of the speed sensor can be determined as μ+3*σ. In this way, the preset calibration interval determined based on the cumulative ranging error of the speed sensor and the preset train positioning error threshold is more accurate.

[0088] When the cumulative distance measurement error of the train speed sensor is equal to the train positioning error threshold, the cumulative running distance determined based on the train speed sensor at this time (ie, the target cumulative running distance) is obtained.

[0089] Step S102: determining the target cumulative running distance as a preset calibration interval.

[0090] In one example of this embodiment, the target cumulative travel distance may be determined as a preset calibration interval threshold. To further improve positioning accuracy, a suitable calibration interval may be selected within the preset calibration interval threshold to set the calibration point.

[0091] In this example, a preset calibration interval is pre-determined so that when the train reaches the preset calibration interval, the train signal system promptly triggers the train calibration system to perform calibration operations, thereby increasing controllability. Furthermore, embodiments of the present application can also increase the number of calibration points selected within the preset calibration interval, further improving positioning accuracy without increasing costs.

[0092] In one example of this embodiment, a satellite positioning trust zone can be pre-determined. GNSS data can be collected along the entire route and then solved. The various satellite positioning solution scenarios correspond to different positioning accuracies, with the following corresponding accuracy levels from low to high: zero solution, single-point solution, differential solution, floating-point solution, and fixed solution. These five different solution states serve as the basis for selecting the GNSS trust zone.

[0093] However, if there are only a few discrete points that are fixed solutions for satellite positioning, the positions where the virtual balise needs to be calibrated when the train passes through this section may not be at these discrete points, thus affecting the availability of the virtual balise.

[0094] Therefore, to improve the credibility of the solution, in one example of this embodiment, only when a fixed solution exists for N consecutive satellite positioning cycles can the train section corresponding to these N cycles be considered to be a GNSS trustworthy zone. Where N can be determined based on actual measurement experience.

[0095] In an example of this embodiment, as shown in FIG6 , step S130 may include steps S600 to S620 .

[0096] Step S600: When the train is traveling in a satellite positioning credible area and the current cumulative running distance of the train reaches a preset calibration interval, the train position determined based on satellite positioning is obtained.

[0097] Since the satellite positioning results may also have certain errors, the average deviation of the satellite positioning results within the GNSS trustworthy area can be determined in advance. In one example of this embodiment, the position L calculated as the fixed solution is determined. i The average deviation of the satellite positioning result includes steps S601 to S603.

[0098] Step S601: repeatedly collect GNSS trusted zone data on the route.

[0099] In the GNSS trustworthy area, the satellite positioning results (B ij ,L ij ,H ij ), i, j = 1, 2, ..., n. Among them, B ij ,L ij ,H ijRespectively represent the position L i The latitude, longitude, and altitude information collected at the jth time.

[0100] Step S602: for the same position L i Calculate the average of multiple satellite positioning results

[0101] Step S603, calculate the L i The average deviation of satellite positioning results

[0102] In one example of this embodiment, the average deviation of the satellite positioning results of multiple locations can be calculated to obtain the overall average deviation σ of the satellite positioning. L .

[0103] In this embodiment, step S600 may include steps S605 to S606.

[0104] Step S605: When the train is traveling in a satellite positioning trustworthy area and the current cumulative running distance of the train reaches a preset calibration interval, the positioning data collected by the satellite is obtained.

[0105] In one example of this embodiment, the positioning data of the position Li collected by the satellite is (B i ,L i ,H i ). Among them, B i ,L i ,H i They respectively represent the latitude, longitude, and altitude information collected by the satellite at position Li in real time.

[0106] Step S606: Correct the positioning data collected by the satellite based on the satellite positioning deviation to obtain the train position determined based on the satellite positioning.

[0107] In an example of this embodiment, when the train is traveling in the satellite positioning trust area and the current train cumulative running distance reaches the preset calibration interval, the satellite positioning result obtained is Where i = 1, 2, ..., n.

[0108] In another example of this embodiment, when the train is traveling in the satellite positioning trust area and the current train cumulative running distance reaches the preset calibration interval, the satellite positioning result obtained is Where i = 1, 2, ..., n.

[0109] Step S610: When the train is traveling outside the satellite positioning credible area and the current cumulative running distance of the train reaches the preset calibration interval, the train position determined based on radar positioning is obtained.

[0110] To determine the train location based on radar positioning, a point cloud map needs to be established in advance.

[0111] In one example of this embodiment, the point cloud map can be established by collecting point cloud data of the entire line in advance through a laser radar, and the point cloud map can be established through laser SLAM (Simultaneous Localization And Mapping).

[0112] Because the positioning principles of lidar sensors are different from those of GNSS positioning, GNSS satellite positioning obtains three-dimensional coordinates in the Earth's geocentric coordinate system, while lidar cannot obtain absolute positioning. The initial positioning at each mapping moment is (0,0,0). Therefore, at the initial moment of mapping, GNSS needs to provide the absolute position of the current train to the laser point cloud.

[0113] In one example of this embodiment, the starting point for mapping can be selected within the GNSS satellite positioning trust zone, which can ensure the accuracy of the initial position of the point cloud map.

[0114] In one example of this embodiment, in the laser radar mapping stage, in order to ensure the accuracy of laser point cloud mapping, in the GNSS satellite positioning trust area, the satellite positioning result after removing the deviation can be used to obtain the correct value. Correct the point cloud positioning results.

[0115] In this example, when the train is traveling outside the satellite positioning trust zone and the current train's cumulative travel distance reaches the preset calibration interval, the radar positioning results are obtained in real time, and the point cloud collected by the lidar in real time is aligned with the pre-established point cloud map to determine the train's position.

[0116] The point cloud registration algorithm is not specifically limited, and may be, for example, an ICP (Iterative Closest Point) algorithm or a DNT (Normal Distributions Transform) algorithm.

[0117] Step S620: According to the train position determined based on satellite positioning or the train position determined based on radar positioning, the train position determined based on the train speed sensor is corrected by a virtual transponder.

[0118] In an embodiment of the present application, when the current cumulative running distance of the train reaches the preset calibration interval, if the train is within the GNSS satellite positioning trust zone, the train position determined based on the train speed sensor is corrected by a virtual transponder according to the train position determined based on satellite positioning; if the train is outside the GNSS satellite positioning trust zone, the train position determined based on the train speed sensor is corrected by a virtual transponder according to the train position determined based on radar positioning.

[0119] In this example, the complementary relationship between satellite positioning and lidar positioning allows for accurate train location throughout the entire line. In other words, this embodiment of the application can replace physical transponders with virtual transponders along the entire line, thereby correcting the train's position determination based on speed sensors and improving the train's positioning accuracy along the entire line.

[0120] The embodiment of the present application further provides a train alignment system. As shown in FIG7 , the train alignment system 700 includes a first acquisition device 710 , a second acquisition device 720 , and a correction device 730 .

[0121] The first obtaining means 710 is used to obtain a preset calibration interval, where the preset calibration interval is determined based on the cumulative ranging error of the train speed sensor and a preset maximum allowable error of train positioning.

[0122] The second obtaining device 720 is used to obtain the current cumulative running distance determined based on the train speed sensor during the train running process, and the current train cumulative running distance is the distance the train has traveled since the last calibration position.

[0123] The correction device 730 is used to correct the position of the train determined based on the train speed sensor through a virtual transponder when the cumulative running distance of the current train reaches the preset calibration interval.

[0124] The present application also provides an electronic device. As shown in FIG8 , the electronic device 800 includes a memory 810 and a processor 820. The memory 810 is used to store computer instructions, and the processor 820 is used to call the computer instructions from the memory to execute any of the train alignment methods described in the above embodiments.

[0125] An embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, it implements the train alignment method as described in any one of the above embodiments.

[0126] The present application may be a system, method and / or computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present application.

[0127] A computer-readable storage medium can be a tangible device that can hold and store instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, such as a punch card or a raised structure in a groove on which instructions are stored, and any suitable combination thereof. As used herein, a computer-readable storage medium is not to be construed as a transient signal per se, such as a radio wave or other freely propagating electromagnetic wave, an electromagnetic wave propagating through a waveguide or other transmission medium (e.g., a light pulse through a fiber optic cable), or an electrical signal transmitted through an electrical wire.

[0128] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0129] The computer program instructions for performing the operation of the present application can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-related instructions, microcode, firmware instructions, state setting data or source code or object code written in any combination of one or more programming languages, wherein the programming language includes object-oriented programming languages ​​such as Smalltalk, C++, and conventional procedural programming languages ​​such as "C" language or similar programming languages. Computer-readable program instructions can be executed completely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or executed completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer by any type of network including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (such as by using an Internet service provider to connect to the Internet). In certain embodiments, by utilizing the state information of computer-readable program instructions to personalize electronic circuits, such as programmable logic circuits, field programmable gate arrays (FPGAs) or programmable logic arrays (PLAs), the electronic circuits can execute computer-readable program instructions, thereby realizing various aspects of the present application.

[0130] Various aspects of the present application are described herein with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present application. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0131] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device is generated that implements the functions / actions specified in one or more blocks in the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, where these instructions cause the computer, programmable data processing device, and / or other device to operate in a specific manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0132] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0133] The flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a part of a module, program segment or instruction, and the part of the module, program segment or instruction contains one or more executable instructions for realizing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of the boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, implementation by software, and implementation by a combination of software and hardware are all equivalent.

[0134] The embodiments of the present application have been described above. The above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terms used herein are selected to best explain the principles of the embodiments, practical applications, or technical improvements to technologies in the market, or to enable other persons skilled in the art to understand the embodiments disclosed herein. The scope of this application is defined by the appended claims.

Claims

1. A train calibration method, comprising: Obtaining a preset calibration interval, where the preset calibration interval is determined based on a cumulative ranging error of a train speed sensor and a preset train positioning error threshold; Acquire a current accumulated running distance determined based on a train speed sensor during the running of the train, wherein the current accumulated running distance of the train is the distance the train has traveled since the last calibration position; When the current accumulated running distance reaches the preset calibration interval, the position of the train determined based on the train speed sensor is corrected by the virtual balise.

2. The train calibration method according to claim 1, wherein: Before obtaining the preset calibration interval, the method further includes: Acquire the cumulative distance measurement error of the train speed sensor and the target cumulative running distance determined based on the train speed sensor when the train is traveling on the test section, wherein the target cumulative running distance is the cumulative running distance at the moment when the cumulative distance measurement error increases to the train positioning error threshold; The target accumulated travel distance is determined as the preset calibration interval.

3. The train calibration method according to claim 2, wherein: The test section is a section where the satellite positioning accuracy reaches a preset accuracy; The step of obtaining the accumulated ranging error of the train speed sensor when the train travels on the test section includes: Acquire a first cumulative running distance determined based on a train speed sensor and a standard cumulative running distance determined based on satellite positioning when the train travels on a test section; An error between the first cumulative running distance and the standard cumulative running distance is determined as a cumulative distance measurement error of a train speed sensor.

4. The train calibration method according to claim 3, wherein: The obtaining of a first accumulated running distance determined based on a train speed sensor when the train travels on the test section includes: Acquire a plurality of first accumulated travel distances determined based on a train speed sensor when the train travels on the test section for multiple times; The step of determining the error between the first cumulative running distance and the standard cumulative running distance as the cumulative distance measurement error of the train speed sensor comprises: Calculating the deviation between each of the first cumulative running distances and the standard cumulative running distance respectively to obtain multiple groups of deviation data; The accumulated ranging error of the train speed sensor is determined according to the multiple sets of deviation data.

5. The train calibration method according to claim 4, wherein: Determining the cumulative ranging error of the train speed sensor according to the multiple groups of deviations includes: Determining a confidence interval of a cumulative ranging error of the train speed sensor according to the multiple sets of deviation data; Determining a range of the cumulative ranging error according to the confidence interval; The accumulated ranging error is determined according to a range of the accumulated ranging error.

6. The train alignment method according to any one of claims 1 to 5, wherein: The method of correcting the position of the train determined by the train speed sensor by using the virtual balise comprises: When the train is traveling in the satellite positioning credible area and the current accumulated running distance of the train reaches the preset calibration interval, obtaining the train position determined based on satellite positioning; When the train is traveling outside the satellite positioning credible area and the current accumulated travel distance of the train reaches the preset calibration interval, obtaining the train position determined based on radar positioning; According to the train position determined based on the satellite positioning or the train position determined based on the radar positioning, the train position determined based on the train speed sensor is corrected by a virtual balise.

7. The train calibration method according to claim 6, wherein: The step of obtaining the train position determined based on radar positioning when the train is traveling outside the satellite positioning credible area and the current accumulated travel distance of the train reaches the preset calibration interval includes: When the train is traveling outside the satellite positioning credible area and the current accumulated travel distance of the train reaches the preset calibration interval, acquiring point cloud data collected by the radar; Aligning the point cloud data with the point cloud map to obtain the train position determined based on radar positioning; The point cloud map is a map corrected based on satellite positioning results.

8. The train alignment method according to claim 6 or 7, wherein: The step of obtaining the train position determined based on satellite positioning when the train is traveling in a satellite positioning credible area and the current accumulated travel distance of the train reaches the preset calibration interval includes: When the train is traveling in the satellite positioning credible area and the current accumulated running distance of the train reaches the preset calibration interval, obtaining positioning data collected by the satellite; The positioning data collected by the satellite is corrected based on the satellite positioning deviation to obtain the train position determined based on the satellite positioning.

9. An electronic device comprising a memory and a processor, The memory is used to store computer instructions, and the processor is used to call the computer instructions from the memory to execute the train alignment method as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the train alignment method according to any one of claims 1 to 8.

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