CN110254477B - Automatic train benchmarking method and system based on satellite differential positioning - Google Patents
Automatic train benchmarking method and system based on satellite differential positioning Download PDFInfo
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L23/00—Control, warning or like safety means along the route or between vehicles or trains
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L25/00—Recording or indicating positions or identities of vehicles or trains or setting of track apparatus
- B61L25/02—Indicating or recording positions or identities of vehicles or trains
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Abstract
The invention discloses an automatic train benchmarking method and system based on satellite differential positioning, which improve automation and intellectualization, can avoid operation risks caused by mistaken transmission and departure parameters of a driver, avoid the phenomenon of setting errors of a benchmarking signal machine in a continuous departure station and eliminate distance errors caused by manual benchmarking. The technical scheme is as follows: thereby confirm the accurate coordinate of locomotive automatically and check whether driver's input departure parameter is accurate, avoid because of the operation risk that driver mistake transmission departure parameter leads to, confirm the semaphore serial number in the place ahead, avoid appearing setting for error phenomena to the mark semaphore when the station yard of dispatching a car in succession, reach the automatic alignment mark behind the alignment mark semaphore position, eliminate the distance error that artifical alignment mark leads to.
Description
Technical Field
The invention relates to a train benchmarking technology, in particular to an automatic train benchmarking method and system based on satellite differential positioning.
Background
The conventional train operation monitoring device LKJ basically adopts a manual driving target alignment mode. The train driver sets departure parameters before departure, including information such as a starting station, a departure station track, a running path and the like. The departure signal machine of the starting station is usually used as a departure target point, when the train runs to the departure signal machine position, the train enters a vehicle-mounted data control mode (normal mode) through manual operation of a driver, and the manual departure target point aligning process is completed. After the locomotive enters a normal mode, the LKJ can indicate information such as speed limit, gradient and distance from a signal machine of a current line of the locomotive, and a driver is guided to complete driving operation. However, if the LKJ indication position is inconsistent with the current actual position of the locomotive or the distance error is large, the current information such as the speed limit, the gradient and the distance of the front signal machine is incorrect, and the operation efficiency is affected or even serious consequences are caused.
The reasons for such problems are mainly the following:
1. the departure parameters input by the driver are not consistent with the actual departure station track, or the departure station track is correct, but the set benchmarking signal machine is not consistent with the actual benchmarking signal machine, so that the driving benchmarking data are completely wrong.
2. In addition, the manual benchmarking process has manual operation errors, and the number and the accurate position of the front benchmarking signal machine cannot be confirmed due to the influence of factors such as low weather visibility and the like, so that the benchmarking is advanced or delayed, and distance errors exist.
In summary, it is desirable to obtain a method capable of automatically determining the orientation of a locomotive, automatically identifying a beacon signal machine and automatically starting the train to perform beacon alignment, so as to greatly improve the automation and intelligence level of a train operation monitoring device.
The current driving benchmarking method mainly comprises the following steps:
1. and (3) driving according to the station track and aligning: the mode is the current train benchmarking mode, most road offices adopt the mode to benchmark, the mode can not eliminate the error of manual benchmarking, and can not automatically identify whether the departure parameters input by a driver are in accordance with the actual departure position of a locomotive, including whether a front signal machine is the benchmarking signal machine set in the departure parameters or not.
2. And (3) starting and aligning according to the transponder: and laying transponder point type equipment at the position where the train needs to be driven to align the targets, and executing corresponding operation according to the message content of the transponder when the train passes by. The method is generally used on a CTCS-2 level line, and a CTCS-0 section does not have the condition of the method, and the method cannot automatically recognize whether the departure parameters input by a driver are consistent with the actual departure position of the locomotive before departure, and cannot confirm whether a front signal is a target signal set in the departure parameters.
Disclosure of Invention
The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.
The invention aims to solve the problems and provides an automatic train benchmarking method and system based on satellite differential positioning, which improve automation and intelligence, can avoid operation risks caused by mistaken transmission and departure parameters of a driver, avoid the phenomenon of setting errors of a benchmarking signal machine in a continuous departure station and eliminate distance errors caused by manual benchmarking.
The technical scheme of the invention is as follows: the invention discloses an automatic train benchmarking method based on satellite differential positioning, which comprises the following steps:
step 1: the LKJ reads the satellite positioning information of the current route from the vehicle-mounted data according to the set departure parameters;
step 2: judging whether the satellite positioning information is stable, and entering the next step after the satellite positioning information based on the satellite differential positioning is stable and effective;
and step 3: judging whether the satellite positioning information of the current route is matched with the target route track, and executing the next step after the satellite positioning information of the current route is matched with the target route track;
and 4, step 4: automatically checking the mark, and displaying the name of the front beacon signal machine and the distance between the train and the front beacon signal machine;
and 5: and judging whether the train reaches a front beacon signal machine or not, and if so, automatically switching to enter a normal mode by the LKJ.
According to an embodiment of the automatic benchmarking method for the train based on the satellite differential positioning, in step 3, if not matched, the driver is prompted to check whether the departure parameters are correct.
According to an embodiment of the automatic train benchmarking method based on satellite differential positioning, an LKJ normal mode is a vehicle-mounted data control mode.
According to an embodiment of the automatic benchmarking method for a train based on satellite differential positioning, departure parameters include, but are not limited to, a starting station, a departure track and a running path.
According to an embodiment of the automatic train benchmarking method based on satellite differential positioning, satellite positioning information is added to a part of stations in the vehicle-mounted data in the step 1, and satellite positioning vehicle-mounted data manufacturing is completed through three steps of field collection, field extraction and data import, wherein the satellite positioning information is divided into auxiliary function satellite positioning information and benchmarking signal machine satellite positioning information.
The invention also discloses a train automatic benchmarking system based on satellite differential positioning, which comprises:
a processor; and
a memory configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions,
wherein the series of computer executable instructions, when executed by the processor, cause the processor to perform the method as described above.
Also disclosed is a non-transitory computer readable storage medium having stored thereon a series of computer executable instructions which, when executed by a computing device, cause the computing device to perform the method as described above.
Compared with the prior art, the invention has the following beneficial effects: the method mainly realizes automation (automatically enters a common mode after confirming that the destination is reached without driver operation) and intellectualization (automatically identifies departure station, departure station and destination signal machine, and the driver only needs to confirm work). Compared with the traditional train benchmarking scheme, the automatic benchmarking method can automatically confirm the accurate coordinates of the locomotive so as to check whether the input departure parameters of a driver are accurate or not, avoid the operation risk caused by the mistaken transmission of the departure parameters of the driver, confirm the serial number of a signal machine in front, avoid the phenomenon of setting errors for the benchmarking signal machine when the train is continuously dispatched from a station, automatically benchmarking after the position of the benchmarking signal machine is reached, and eliminate the distance error caused by manual benchmarking.
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The above features and advantages of the present disclosure will be better understood upon reading the detailed description of embodiments of the disclosure in conjunction with the following drawings. In the drawings, components are not necessarily drawn to scale, and components having similar relative characteristics or features may have the same or similar reference numerals.
Fig. 1 shows a schematic diagram of differential positioning.
Fig. 2 shows a schematic diagram of the satellite positioning point data production for a track.
Fig. 3 is a flowchart of an embodiment of the automatic train benchmarking method based on satellite differential positioning according to the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. It is noted that the aspects described below in connection with the figures and the specific embodiments are only exemplary and should not be construed as imposing any limitation on the scope of the present invention.
Fig. 3 shows a flow of an embodiment of the automatic train benchmarking method based on satellite differential positioning according to the present invention. The implementation steps of the method of this embodiment are detailed below.
Step S1: and setting departure parameters, and reading the satellite positioning information of the current route from the vehicle-mounted data by the LKJ according to the departure parameters (including the input information of the station names, the departure station tracks and the like).
The train driver sets departure parameters before departure, and the departure parameters comprise information such as a starting station, a departure station track, a running path and the like.
Satellite positioning information is added to a part of stations in the vehicle-mounted data, and satellite positioning vehicle-mounted data manufacturing is completed through three steps of field acquisition, field extraction and data import, wherein the satellite positioning information is divided into auxiliary function satellite positioning information and beacon signal machine satellite positioning information.
In the present embodiment, the coordinates of the locomotive are obtained according to a differential positioning technique. Fig. 1 shows a differential positioning principle, as shown in fig. 1, a differential reference station (reference station) is installed in each large station yard, the reference station sends an observed value thereof to a ground data center in real time through a 3G/4G network or a railway intranet, the data center calculates a correction value under the current environment according to the received observed value and a known coordinate of the reference station, and simultaneously sends the correction value to each locomotive (mobile station) through a 3G/4G wireless network, each locomotive receives the coordinate correction value through a wireless receiving device, and corrects an original locomotive coordinate acquired by a satellite receiving device on the locomotive by using the correction value, so as to acquire a more accurate locomotive coordinate.
The stock data acquisition comprises three parts of field acquisition, field extraction and data file integration. The field data acquisition is mainly completed by using a laser and panoramic mobile backpack based on GPS and INS assisted positioning. Interior extraction first uses fusion software to generate the original field mapping data into a station three-dimensional scene (point cloud and panorama) with real geographic reference by fusing GPS, INS and laser data for interior data extraction. And integrating data files, namely adding the mapped geographic geometric information (real geographic coordinates) into the existing LKJ vehicle-mounted data according to the one-to-one correspondence of the control names for the subsequent locomotive driving benchmarking.
The vehicle-mounted data creating means creates the acquired satellite positioning data into the vehicle-mounted data. Satellite positioning data points fall into two categories: auxiliary function satellite positioning point
And positioning point of beacon signal machine satellite
As shown in fig. 2. According to the length and the bending degree of the track, the number of the positioning points of the auxiliary function satellite on each track is different, but at least the change trend of the track can be described within an error allowable range and is used for matching with the coordinates of the locomotive.
Step S2: and judging whether the satellite positioning information is stable or not, and entering the next step after the result of the satellite positioning information (namely the locomotive differential positioning coordinate) is stable and effective.
Step S3: and judging whether the satellite positioning information of the current route is matched with the target route track. If the matching is not the case, the step S4 is executed (i.e. the automatic benchmarking process is performed), and if the matching is not the case, the step S7 is executed.
Step S4: and automatically aligning the mark, and displaying the name of the front alignment mark signal machine and the distance from the front alignment mark signal machine.
Step S5: and judging whether the back counting distance of the train is 0 or not, and executing the next step if the back counting distance of the train is 0. That is, the distance value of the display at the rear of the motor train unit decreases with the running distance of the train, and when the distance is 0, it indicates that the locomotive has run to the destination signal machine, and the destination operation should be performed.
Step S6: and (4) automatically switching the LKJ into a normal mode (namely a vehicle-mounted data control mode), and ending the process.
Step S7: and prompting the driver to check whether the departure parameters are correct or not, and ending the process.
In addition, the invention also discloses a train automatic benchmarking system based on satellite differential positioning, which comprises a processor and a memory. The memory is configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions. When executed by a processor, the series of computer-executable instructions cause the processor to perform a method as described in the embodiment of fig. 3. Since the method embodiments have been described in detail in the foregoing, no further description is given here.
Also disclosed is a non-transitory computer readable storage medium having stored thereon a series of computer executable instructions which, when executed by a computing device, cause the computing device to perform a method as described in the embodiment of fig. 3. Since the method embodiments have been described in detail in the foregoing, no further description is given here.
Furthermore, the invention also provides an alternative: and automatically aligning the marks by adopting a point type transponder mode, laying a ground transponder at the departure position of each station track, and automatically driving and aligning the marks according to the received message information after the train passes through the transponders. The alternative scheme can also eliminate the error of manual target alignment, but because the positioning information is received only when the train passes through the transponder, the train departure parameters input by a driver cannot be checked before the train is departed, so that the hidden danger of mistaken transmission of the train departure parameters exists.
While, for purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated that the methodologies are not limited by the order of acts, as some acts may, in accordance with one or more embodiments, occur in different orders and/or concurrently with other acts from that shown and described herein or not shown and described herein, as would be understood by one skilled in the art.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The various illustrative logical blocks, modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The steps of a method or algorithm described in connection with the embodiments disclosed herein may be embodied directly in hardware, in a software module executed by a processor, or in a combination of the two. A software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. An exemplary storage medium is coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC. The ASIC may reside in a user terminal. In the alternative, the processor and the storage medium may reside as discrete components in a user terminal.
In one or more exemplary embodiments, the functions described may be implemented in hardware, software, firmware, or any combination thereof. If implemented in software as a computer program product, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer. Any connection is properly termed a computer-readable medium. For example, if the software is transmitted from a web site, server, or other remote source using a coaxial cable, fiber optic cable, twisted pair, Digital Subscriber Line (DSL), or wireless technologies such as infrared, radio, and microwave, then the coaxial cable, fiber optic cable, twisted pair, DSL, or wireless technologies such as infrared, radio, and microwave are included in the definition of medium. Disk (disk) and disc (disc), as used herein, includes Compact Disc (CD), laser disc, optical disc, Digital Versatile Disc (DVD), floppy disk and blu-ray disc where disks (disks) usually reproduce data magnetically, while discs (discs) reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. A train automatic benchmarking method based on satellite differential positioning is characterized by comprising the following steps:
step 1: the LKJ reads the satellite positioning information of the current route from the vehicle-mounted data according to the set departure parameters;
step 2: judging whether the satellite positioning information is stable, and entering the next step after the satellite positioning information based on the satellite differential positioning is stable and effective;
and step 3: judging whether the satellite positioning information of the current route is matched with the target route track or not, and executing the next step after the satellite positioning information of the current route is matched with the target route track;
and 4, step 4: automatically checking the mark, and displaying the name of the front beacon signal machine and the distance between the train and the front beacon signal machine;
and 5: and judging whether the train reaches the front beacon signal machine according to whether the back counting distance of the train is 0, and automatically switching to a normal mode by the LKJ if the train reaches the front beacon signal machine.
2. The automatic benchmarking method for trains based on satellite differential positioning as claimed in claim 1, wherein in step 3, if not matched, the driver is prompted to check whether the departure parameters are correct.
3. The automatic train calibration method based on satellite differential positioning as claimed in claim 1, wherein the LKJ normal mode is a vehicle-mounted data control mode.
4. The automatic benchmarking method for trains based on satellite differential positioning as claimed in claim 1, wherein the departure parameters include but are not limited to start station, departure track and operation path.
5. The automatic train alignment method based on satellite differential positioning as claimed in claim 1, wherein the satellite positioning information is added to some stations in the vehicle data in step 1, and the satellite positioning vehicle data is manufactured through three steps of field collection, field extraction and data import, wherein the satellite positioning information is divided into satellite positioning information with auxiliary function and satellite positioning information of alignment signal machine.
6. An automatic train calibration system based on satellite differential positioning is characterized by comprising:
a processor; and
a memory configured to store a series of computer-executable instructions and computer-accessible data associated with the series of computer-executable instructions,
wherein the series of computer executable instructions, when executed by the processor, cause the processor to perform the method of any of claims 1 to 5.
7. A non-transitory computer readable storage medium having stored thereon a series of computer executable instructions that, when executed by a computing device, cause the computing device to perform the method of any of claims 1 to 5.
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| CN111086540A (en) * | 2020-03-23 | 2020-05-01 | 北京全路通信信号研究设计院集团有限公司 | Railway message information processing method and system |
| CN114802359B (en) * | 2021-01-27 | 2023-03-24 | 株洲中车时代电气股份有限公司 | Automatic benchmarking parking method, system and device for locomotive |
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