Train positioning method based on sleeper coding

Abstract

A train positioning method based on sleeper codes comprises the following steps that a coding protocol is formulated, and the sleeper codes are drawn on sleepers along a track line according to the coding protocol to serve as positioning targets for train positioning; a point cloud acquisition module is installed on a train body, and all point cloud data in front of the advancing direction of the train are acquired through the point cloud acquisition module and sent to a train-mounted computer; the train-mounted computer extracts sleeper target point cloud data from all the point cloud data by adopting a sleeper extraction algorithm; the train-mounted computer decodes the sleeper target point cloud data and converts the data into absolute position information of a current positioning target of the train, namely absolute position information of a sleeper code; and the train-mounted computer carries out comprehensive calculation to obtain accurate absolute position information of the current train. According to the method, the sleeper is used for bearing coding information, coding protocols in any form are supported, the universality is high, customized design can be achieved according to different line conditions and different user requirements, and transplantation is easy and convenient.

Description

Technical Field

[0001] The invention relates to the technical field of rail transit train positioning, and in particular to a train positioning method based on sleeper coding. Background Art

[0002] Rail transit safety is related to the life and property safety of participants, and has always been the focus of the rail transit industry. Train positioning technology is the basic function of rail transit signal control, and plays an extremely important role in ensuring the safety of train operation and improving operational efficiency. Among them, more accurate and robust positioning methods can not only improve the safety of train travel, but also further improve the operating efficiency of the entire transportation network.

[0003] In the prior art, traditional train positioning technology can be mainly divided into continuous positioning technology and point positioning technology. The continuous positioning includes: cumulative positioning based on vehicle-mounted equipment, positioning based on GNSS, track circuit positioning and positioning based on Simultaneous Localization And Mapping (SLAM), etc.; the point positioning includes: beacon positioning, kilometer mark positioning, ultra-wideband (UWB) positioning and secondary radar positioning, etc.

[0004] However, the above vehicle positioning solutions have the problems of high additional equipment cost, poor versatility, low accuracy, difficulty in eliminating cumulative errors, poor safety, etc. Therefore, it is very necessary to design a train positioning method to overcome the above technical problems.

[0005] It should be understood that the above statements merely provide background technology related to the present invention and do not necessarily constitute prior art. Summary of the invention

[0006] The purpose of the present invention is to provide a train positioning method based on sleeper coding, which is simple to implement and has extremely high positioning accuracy, and can realize autonomous train positioning on the entire line.

[0007] In order to achieve the above-mentioned purpose, the present invention provides a train positioning method based on sleeper coding, comprising the following steps: S1, formulating a coding protocol, and drawing the sleeper coding on the sleeper along the track line according to the coding protocol as a positioning target for train positioning; S2, installing a point cloud acquisition module on the train body, using the point cloud acquisition module to obtain all point cloud data in front of the train, and sending it to the train on-board computer; S3, the train on-board computer uses a sleeper extraction algorithm to extract sleeper target point cloud data from all the point cloud data; S4, the train on-board computer decodes the sleeper target point cloud data and converts it into the absolute position information of the train's current positioning target, that is, the absolute position information of the sleeper coding; S5, the train on-board computer performs comprehensive calculations to obtain the precise absolute position information of the current train.

[0008] Preferably, the encoding protocol adopts binary, ternary, multi-base or pattern.

[0009] Preferably, a plurality of groups of sleeper codes are arranged at intervals on the sleepers along the track line, and each group of sleeper codes is composed of a plurality of adjacent sleepers.

[0010] A plurality of adjacent sleepers carrying sleeper codes constitute a sleeper group, and each sleeper in the sleeper group represents a different coding position of the sleeper code.

[0011] Preferably, in S2, the point cloud acquisition module detects all targets in front of the train by emitting detection signals, obtains distance information of each target, and converts them into position coordinates one by one to constitute the point cloud data of the current detection.

[0012] Preferably, in S2, the point cloud acquisition module uses millimeter wave radar, laser radar or depth camera.

[0013] Preferably, the millimeter wave radar emits electromagnetic wave signals to detect targets, the laser radar emits laser beams to detect targets, and the depth camera emits infrared light or structured light to detect targets.

[0014] Preferably, in S3, the sleeper extraction algorithm clusters the sleeper targets carrying sleeper codes in front of the train from all the point cloud data, separates the sleeper targets from other targets, and extracts the sleeper target point cloud data that only carries the sleeper codes and does not contain other irrelevant point cloud data.

[0015] Preferably, the decoding principle is compatible with the formulated coding protocol, and the train onboard computer decodes the extracted sleeper target point cloud data according to the coding protocol formulated in S1.

[0016] Preferably, in the above S5, the precise absolute position information of the current train = the absolute position information of the sleeper code - the ranging information of the point cloud data.

[0017] Preferably, the absolute position of the sleeper code is the position of the first sleeper of the sleeper group corresponding to the sleeper code that is closest to the train; the ranging information of the point cloud data is the distance between the point cloud acquisition module and the absolute position of the sleeper code.

[0018] Preferably, in said S1, the code is drawn on the sleeper by spraying with a high reflectivity material or a sticker.

[0019] The present invention also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the train positioning method based on sleeper coding is implemented.

[0020] The present invention also provides an electronic device, including a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the train positioning method based on sleeper coding is implemented.

[0021] In summary, compared with the prior art, the train positioning method based on sleeper coding provided by the present invention has at least the following beneficial effects:

[0022] (1) The present invention can realize autonomous train positioning on the entire line, and realize segmented train positioning in any section of the entire line, such as tunnels, elevated roads, turnouts, platforms, etc., without relying on any external equipment or signal support, and can still achieve normal functions when CC, BLS, and GNSS fail;

[0023] (2) The algorithm of the present invention is simple to implement, has low computing power requirements, and can ensure real-time computing;

[0024] (3) The present invention has no cumulative error and high positioning accuracy. The theoretical positioning accuracy only depends on the ranging accuracy of the point cloud;

[0025] (4) The present invention has high repositioning efficiency. When a train loses its position due to anomalies, failures, etc., the train position can be quickly regained at one time by identifying the next sleeper coding information;

[0026] (5) The present invention innovatively uses rail sleepers to carry coding information and supports any form of coding protocols. It is highly versatile and can be customized according to different line conditions and different user needs. For different cities and different lines, the solution is highly reusable and easy to transplant. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of the train positioning method based on sleeper coding in the present invention;

[0028] Figure 2 It is a schematic diagram of the principle of the train positioning method based on sleeper coding in the present invention;

[0029] Figure 3 A sleeper coding embodiment of the train positioning method based on sleeper coding in the present invention;

[0030] Figure 4 This is another sleeper coding embodiment of the train positioning method based on sleeper coding in the present invention. DETAILED DESCRIPTION

[0031] The following is combined with Figures 1 to 4 , the present invention is further explained by describing a preferred specific embodiment in detail.

[0032] It should be noted that the drawings are in a very simplified form and use non-precise proportions. They are only used to conveniently and clearly assist in explaining the embodiments of the present invention, and are not used to limit the conditions for the implementation of the present invention. Therefore, they have no substantive technical significance. Any structural modification, change in proportional relationship or adjustment of size, without affecting the effects and purposes that can be achieved by the present invention, should still fall within the scope of the technical content disclosed by the present invention.

[0033] It should be noted that, in the present invention, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only the elements explicitly listed, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0034] like Figure 1 As shown, the present invention provides a train positioning method based on sleeper coding, comprising the following steps:

[0035] S1. Formulate a coding protocol, and draw the sleeper codes on the sleepers along the track according to the coding protocol as positioning targets for train positioning;

[0036] S2. Install a point cloud acquisition module on the train body, use the point cloud acquisition module to acquire all point cloud data ahead of the train, and send it to the train onboard computer;

[0037] S3, the train onboard computer uses a sleeper extraction algorithm to extract sleeper target point cloud data from all the point cloud data;

[0038] S4, the train onboard computer decodes the sleeper target point cloud data and converts it into the absolute position information of the current positioning target of the train, that is, the absolute position information of the sleeper code;

[0039] S5. The train's onboard computer performs comprehensive calculations to obtain the precise absolute position information of the current train.

[0040] Furthermore, in S1, the coding protocol is a customized rule, which can be expressed in binary, ternary, or multi-base form, or in a special pattern or any other customized coding format that can be used as a special identifier, etc.

[0041] Furthermore, on the sleepers along the track line, several groups of sleeper codes are arranged at intervals, and each group of sleeper codes is composed of multiple adjacent sleepers. Therefore, only when multiple adjacent sleepers work together can a group of sleeper codes be fully displayed; wherein, multiple adjacent sleepers carrying sleeper codes constitute a sleeper group, and each sleeper in the sleeper group represents a different coding position of the sleeper code.

[0042] like Figure 3 As shown, in this embodiment, the coding protocol adopts binary form, and a complete set of sleeper codes includes 1 start bit, 8 sleeper code bits, 1 even parity bit and 1 end bit. It can be understood that in this coding protocol, each set of sleeper codes is composed of 11 (1+8+1+1) sleepers, so these 11 sleepers are called a sleeper group. Figure 4 As shown, in this embodiment, the coding protocol adopts ternary form, and a complete set of sleeper codes only includes 6 sleeper code bits. It can be understood that in this coding protocol, each set of sleeper codes is composed of 6 sleepers, so these 6 sleepers are called a sleeper group.

[0043] It can be understood that, in the embodiment of the present invention, the sleeper code on the sleeper can be used as a reference for train positioning, which is equivalent to the role played by road signs on the highway.

[0044] Furthermore, in S2, the point cloud acquisition module may use a point cloud data detection device such as a millimeter wave radar, a laser radar, a depth camera or any other detector that can collect point cloud data, to detect all targets in front of the train by emitting detection signals, and obtain the distance information of each target, and convert it one by one into point cloud data in a Cartesian coordinate system, that is, all the obtained point cloud data represent the position and shape of each target in the form of three-dimensional coordinates, thereby providing a basis for subsequent processing and analysis. Among them, all targets in front of the train include all detectable targets such as sleepers, buildings, and background environments.

[0045] Among them, the millimeter wave radar emits electromagnetic wave signals to detect targets, the laser radar emits laser beams to detect targets, and the depth camera emits infrared light or structured light to detect targets.

[0046] Furthermore, in S3, the sleeper extraction algorithm can cluster the sleeper targets carrying sleeper codes in front of the train from all the point cloud data, separate the sleeper targets from other targets, and extract separate sleeper target point cloud data that only carries the sleeper codes and does not contain other irrelevant point cloud data.

[0047] Furthermore, in the above S4, the principle of decoding is compatible with the established coding protocol, and the train onboard computer decodes the extracted sleeper target point cloud data according to the coding protocol established in the above S1.

[0048] Furthermore, in the above S5, the precise absolute position information of the current train = the absolute position information of the sleeper code - the ranging information of the point cloud data.

[0049] It is understandable that when decoding, a complete set of sleeper codes needs to be decoded in order to determine whether the sleeper codes are valid. Therefore, after decoding, the position of the first sleeper closest to the train in the sleeper group corresponding to the sleeper codes is the absolute position of the sleeper codes. Figure 2 As shown, the distance measurement information x of the point cloud data is the distance between the point cloud acquisition module and the position of the first sleeper of the sleeper group corresponding to the sleeper code that is closest to the train.

[0050] In one embodiment of the present invention, Figure 3 As shown, first formulate a coding protocol, which adopts a binary form, including 1 start bit, 8 sleeper coding bits, 1 even parity bit and 1 end bit. Secondly, according to the coding protocol, the sleeper code is drawn on the sleeper along the track line using high reflectivity material / sticker to distinguish the start bit, the end bit, the sleeper coding bit 0 and the sleeper coding bit 1. Among them, in this embodiment, the normal sleeper is not sprayed, the start / end bit is all sprayed, the sleeper coding bit 0 is sprayed on the left half in front of the train, and the sleeper coding bit 1 is sprayed on the right half in front of the train. Then, the point cloud acquisition module obtains all the point cloud data in front of the train. It can be understood that the position where the high reflectivity material / sticker is sprayed will have a higher reflectivity, which can be significantly distinguished in the point cloud. Then, the sleeper extraction algorithm can extract a complete sleeper code (1+8+1+1 bit) and perform a parity check. Finally, the train's onboard computer decodes the sleeper code and calculates the precise absolute position information of the current train by combining the ranging information with the point cloud data.

[0051] It should be noted that the materials of the sleepers include wood and concrete, and the number of sleepers generally ranges from 1440 to 1920 per kilometer. In this embodiment, according to 1667 sleepers per kilometer and a 60 cm spacing between every two adjacent sleepers, each complete sleeper code corresponds to 11 sleepers, sleeper code length = 10 × 60 cm = 6m, sleeper code capacity = 2 8 =256, that is, 256 different positions can be represented. It can be understood that for a 40km long route, if the sleeper code positions are evenly distributed, the adjacent interval between every two adjacent sleeper codes = 40km / 256≈156m, and this positioning density is sufficient for the positioning needs of the train.

[0052] If you want to further improve the positioning density, in addition to increasing the number of sleeper code bits, you can also increase the sleeper code depth to increase the sleeper code capacity at the same length.

[0053] In another embodiment of the present invention, Figure 4 As shown, the sleeper coding eliminates the start bit, end bit and parity bit, but changes the coding protocol to 3-bit form, which not only shortens the number of bits required, but also increases the sleeper coding capacity. Specifically, the coding protocol only includes 6 sleeper coding bits, which are also sprayed with high reflectivity materials. Normal sleepers are not sprayed, sleeper coding bit 0 is sprayed on the left half, sleeper coding bit 1 is sprayed on the right half, and sleeper coding bit 2 is sprayed in its entirety. Therefore, for this coding protocol, the sleeper coding length = 5×60cm = 3m, and the sleeper coding capacity = 3 6 =729, that is, 729 different positions can be represented. Similarly, for a 40km long route, if the sleeper code positions are evenly distributed, the adjacent interval between every two adjacent sleeper codes = 40km / 729≈55m. It can be understood that in this embodiment, by shortening the sleeper code length, not only the sleeper code capacity is improved, but also the extraction and decoding efficiency of the sleeper target is improved, and the positioning density of 55m intervals can fully meet the positioning granularity requirements of the train.

[0054] Furthermore, the present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the above-mentioned train positioning method based on sleeper coding is implemented.

[0055] Furthermore, the present invention also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the above-mentioned train positioning method based on sleeper coding is implemented.

[0056] In summary, the train positioning method based on sleeper coding of the present invention can realize autonomous train positioning of the entire line, and realize segmented train positioning of any section of the entire line such as tunnels, elevated roads, turnouts, platforms, etc., without relying on any external equipment or signal support, and can still realize normal functions when CC, BLS, and GNSS fail; the algorithm is simple to implement, and the computing power requirement is low, and the real-time calculation can be guaranteed; there is no cumulative error, and the positioning accuracy is high, and the theoretical positioning accuracy only depends on the ranging accuracy of the point cloud; the repositioning efficiency is high, and when the train loses its positioning due to abnormalities, failures, etc., the next coding information can be identified to quickly regain the positioning of the train at one time; the sleepers are innovatively used to carry coding information, and any form of coding protocols are supported, with high versatility, and can be customized according to different line conditions and different user needs. For different cities and different lines, the solution has high reusability and is easy to transplant.

[0057] Although the content of the present invention has been described in detail through the above preferred embodiments, it should be appreciated that the above description should not be considered as a limitation of the present invention. After reading the above content, it will be apparent to those skilled in the art that various modifications and substitutions of the present invention will occur. Therefore, the protection scope of the present invention should be limited by the appended claims.

Claims

1. A train positioning method based on sleeper coding, characterized in that: The following steps are involved: S1. Formulate a coding protocol, and draw the sleeper codes on the sleepers along the track according to the coding protocol as positioning targets for train positioning; S2. Install a point cloud acquisition module on the train body, use the point cloud acquisition module to acquire all point cloud data ahead of the train, and send it to the train onboard computer; S3, the train onboard computer uses a sleeper extraction algorithm to extract sleeper target point cloud data from all the point cloud data; S4, the train onboard computer decodes the sleeper target point cloud data and converts it into the absolute position information of the current positioning target of the train, that is, the absolute position information of the sleeper code; S5. The train's onboard computer performs comprehensive calculations to obtain the precise absolute position information of the current train.

2. The train positioning method based on sleeper coding according to claim 1, characterized in that: The encoding protocol adopts binary, ternary, multi-base or pattern.

3. The train positioning method based on sleeper coding as claimed in claim 2, characterized in that: On the sleepers along the track line, several groups of sleeper codes are arranged at intervals, and each group of sleeper codes is composed of multiple adjacent sleepers; A plurality of adjacent sleepers carrying sleeper codes constitute a sleeper group, and each sleeper in the sleeper group represents a different coding position of the sleeper code.

4. The train positioning method based on sleeper coding according to claim 1, characterized in that: In S2, the point cloud acquisition module detects all targets in front of the train by emitting detection signals, obtains distance information of each target, and converts them into position coordinates one by one to form the point cloud data of the current detection.

5. The train positioning method based on sleeper coding as claimed in claim 4, characterized in that: In S2, the point cloud acquisition module uses millimeter wave radar, laser radar or depth camera.

6. The train positioning method based on sleeper coding as claimed in claim 5, characterized in that: The millimeter wave radar emits electromagnetic wave signals to detect targets, the laser radar emits laser beams to detect targets, and the depth camera emits infrared light or structured light to detect targets.

7. The train positioning method based on sleeper coding according to claim 1, characterized in that: In S3, the sleeper extraction algorithm clusters the sleeper targets carrying sleeper codes in front of the train from all the point cloud data, separates the sleeper targets from other targets, and extracts the sleeper target point cloud data that only carries the sleeper codes and does not contain other irrelevant point cloud data.

8. The train positioning method based on sleeper coding as claimed in claim 3, characterized in that: The principle of decoding is compatible with the formulated coding protocol, and the train onboard computer decodes the extracted sleeper target point cloud data according to the coding protocol formulated in S1.

9. The train positioning method based on sleeper coding according to claim 1, characterized in that: In the above S5, the precise absolute position information of the current train = the absolute position information of the sleeper code - the distance measurement information of the point cloud data.

10. The train positioning method based on sleeper coding according to claim 9, characterized in that: The absolute position of the sleeper code is the position of the first sleeper of the sleeper group corresponding to the sleeper code that is closest to the train; The distance measurement information of the point cloud data is the distance between the point cloud acquisition module and the absolute position of the sleeper code.

11. The train positioning method based on sleeper coding according to claim 3, characterized in that: In the above-mentioned S1, the code is drawn on the sleeper by spraying with a high reflectivity material or a sticker.

12. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the train positioning method based on sleeper coding according to any one of claims 1 to 11 is implemented.

13. An electronic device, characterized in that: The invention comprises a processor and a memory, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the train positioning method based on sleeper coding according to any one of claims 1 to 11 is implemented.

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