CN113650645B - Method and system for identifying trend of train turnout - Google Patents
Method and system for identifying trend of train turnout Download PDFInfo
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- CN113650645B CN113650645B CN202110948678.2A CN202110948678A CN113650645B CN 113650645 B CN113650645 B CN 113650645B CN 202110948678 A CN202110948678 A CN 202110948678A CN 113650645 B CN113650645 B CN 113650645B
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- 238000007781 pre-processing Methods 0.000 claims description 8
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- 238000002790 cross-validation Methods 0.000 abstract description 3
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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 provides a method and a system for identifying the trend of a train turnout, comprising the following steps: determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map; determining a second trend judgment result based on the obtained turning angle of the train turnout; and carrying out cross verification on the first trend judging result and the second trend judging result to determine a train trend judging result. According to the invention, the rapid identification of the two train trends is realized through the matching of the real-time scanning point cloud and the high-precision electronic map and the integration of the horizontal angular velocity of the IMU, and the reliable detection of the train trend is realized through the cross-validation of the two methods.
Description
Technical Field
The invention relates to the technical field of rail transit, in particular to a method and a system for identifying the trend of a train turnout.
Background
In the current train operation control system, when a train passes through a turnout, the positioning or the reverse position of the train entering the turnout is generally comprehensively confirmed by collecting the state of a switch machine and combining the mileage of the train through ground equipment. The exact trend of the train cannot be known only by the train itself within a period of time after the switch, and the exact trend and position of the train can be known only when the train passes through the nearest transponder, as shown in fig. 1.
For the above situation, if no ground switch state is sent to the train, the train does not know the exact trend of the train in a period of time after passing the switch, and is always in a 'blind-line' state until passing the nearest transponder, the distance is tens of meters or hundreds of meters, and the distance depends on the position of the transponder. For a new generation train active sensing system that does not rely on ground systems, the distance to blind travel after a switch is only longer until an identifiable landmark (e.g., a platform) is encountered. If the exact position of the train is not known, the active sensing system cannot load a proper map, so that the sensing capability is seriously reduced, the train cannot predict the track trend in front, and the obstacle cannot be reliably detected, so that the running safety is more threatened.
Therefore, to overcome the above-mentioned drawbacks, a new method for identifying the track of a train switch is required.
Disclosure of Invention
The invention provides a method and a system for identifying the trend of a train turnout, which are used for solving the defect that the trend of the train turnout needs to depend on ground equipment in the prior art.
In a first aspect, the present invention provides a method of identifying the trend of a train switch, comprising:
determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map;
determining a second trend judgment result based on the obtained turning angle of the train turnout;
and carrying out cross verification on the first trend judging result and the second trend judging result to determine a train trend judging result.
In one embodiment, the determining the first trend determination result based on the real-time scanning point cloud data and the train electronic map includes:
acquiring point cloud data, inertia measurement data and vehicle speed data of a train running full line;
preprocessing the point cloud data to obtain corrected point cloud data;
storing initial data in the corrected point cloud data into an initial train electronic map, and carrying out pose estimation by combining the inertial measurement data and the speed data to obtain initial estimated pose data;
and superposing and storing the subsequent point cloud data in the corrected point cloud data into the initial train electronic map, and carrying out pose estimation by combining the inertia measurement data and the vehicle speed data until all the point cloud data are processed, so as to obtain the train electronic map.
In one embodiment, the determining the first trend determination result based on the real-time scanning point cloud data and the train electronic map further includes:
and acquiring a positioning steering angle and a reverse steering angle of each turnout passing through a preset distance of a turnout point in the whole train running line.
In one embodiment, the determining the first trend determination result based on the real-time scanning point cloud data and the train electronic map includes:
acquiring current scanning point cloud data in train operation, preprocessing the real-time scanning point cloud data, and obtaining corrected current scanning point cloud data;
integrating the vehicle speed data and the inertial measurement angular speed to obtain the current scanning point cloud estimation pose;
based on the current scanning point cloud estimation pose, matching the corrected current scanning point cloud data with the point cloud data in the train electronic map to obtain an accurate train position;
and when the train passes through any turnout, respectively acquiring a first distance between the accurate position of the train and the positioning track and a second distance between the accurate position of the train and the reversing track, and determining the first trend judgment result based on the first distance and the second distance.
In one embodiment, the determining the first trend determination result based on the first distance and the second distance includes:
if the difference of the first distance minus the second distance is greater than a first threshold, determining that the train is located on the reversed track;
and if the difference of the second distance minus the first distance is larger than a second threshold value, determining that the train is positioned on the positioning track.
In one embodiment, the determining the second trend determination result based on acquiring the turning angle of the switch of the train includes:
calculating an inertia measurement horizontal angular velocity integral of the train passing through any turnout, and obtaining a rotation angle in the horizontal direction when the train passes through a preset distance of a turnout point;
and determining the second trend judging result based on the rotation angle, the positioning steering angle and the flip steering angle.
In a second aspect, the present invention also provides a system for identifying the track of a train switch, comprising:
the first determining module is used for determining a first trend judging result based on the real-time scanning point cloud data and the train electronic map;
the second determining module is used for determining a second trend judging result based on the obtained turning angle of the train turnout;
and the verification module is used for carrying out cross verification on the first trend judgment result and the second trend judgment result to determine a train trend judgment result.
In a third aspect, the present invention also provides an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the method of identifying the track of a train switch as described in any one of the preceding claims when the program is executed by the processor.
In a fourth aspect, the present invention also provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of a method of identifying a track of a train switch as described in any of the above.
In a fifth aspect, the invention also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of a method of identifying the track of a train switch as described in any of the above.
According to the method and the system for identifying the trend of the train turnout, the two types of the trend of the train are rapidly identified through matching of the real-time scanning point cloud and the high-precision electronic map and integration of the horizontal angular velocity of the IMU, and reliable detection of the trend of the train is achieved through cross verification of the two types of the method.
Drawings
In order to more clearly illustrate the invention or the technical solutions of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a train operation control system provided in the prior art;
FIG. 2 is a flow chart of a method for identifying the trend of a train switch provided by the invention;
FIG. 3 is a schematic diagram of a train operation control system provided by the present invention;
FIG. 4 is a schematic diagram of a train electronic map generation process provided by the invention;
FIG. 5 is a schematic view of the switch angle of the train provided by the invention;
FIG. 6 is a schematic diagram of a comprehensive train trend identification process provided by the invention;
FIG. 7 is a schematic illustration of a positioning and inversion track trajectory provided by the present invention;
FIG. 8 is a schematic diagram of a system for identifying the track of a train switch according to the present invention;
fig. 9 is a schematic structural diagram of an electronic device provided by the present invention.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is apparent that the described embodiments are some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
In order to overcome the defects in the prior art, the invention provides a method for identifying the trend of a train turnout, as shown in fig. 2, which comprises the following steps:
step S1, determining a first trend judgment result based on real-time scanning point cloud data and a train electronic map;
step S2, determining a second trend judgment result based on acquiring the turning angle of the train turnout;
and S3, performing cross verification on the first trend judging result and the second trend judging result to determine a train trend judging result.
Specifically, firstly, the invention identifies whether the trend of the train is in a positioning track or a reversed track after the train passes through the turnout based on the matching of the real-time scanning point cloud and the high-precision electronic map.
The track positions at which the switch points are divided are defined as follows: the usual travel position of the turnout is positioning, and the unusual travel position is reverse, namely positioning and reverse are relative, and the travel tracks of the turnout in two different directions are presented.
As shown in fig. 3, the track recognition method of the train after passing through the turnout mainly comprises a vehicle-mounted sensor and a vehicle-mounted computer, wherein the vehicle-mounted sensor comprises a laser radar, an IMU (Inertial Measurement Unit, an inertial measurement unit), a millimeter wave radar, a speed sensor and the like; the laser radar scans the front of the train and outputs a real-time scanning point cloud, and the positioning and the environmental perception of the train can be realized based on the point cloud; the IMU outputs the angular speed and acceleration of the train in all directions in real time, and can estimate the position and the gesture of the vehicle by combining the speed information provided by the millimeter wave radar or the speed sensor. The vehicle-mounted computer is internally provided with a high-precision electronic map, the positioning steering angle and the inversion steering angle of each turnout, and the laser radar outputs real-time scanning point cloud to be matched with the high-precision electronic map to realize accurate measurement of the vehicle position, so that the trend of the vehicle after passing through the turnout is identified.
In addition, the steering angle of the train after passing through the turnout can be obtained through integrating the output angular speed of the IMU, and the trend of the train is determined through comparing the steering angles of the positioning and the inversion.
And comprehensively carrying out cross verification on the two train trend judging results to obtain a real-time trend identifying result of the train.
According to the invention, the rapid identification of the two train trends is realized through the matching of the real-time scanning point cloud and the high-precision electronic map and the integration of the horizontal angular velocity of the IMU, and the reliable detection of the train trend is realized through the cross-validation of the two methods.
Based on the above embodiment, the method step S1 includes:
acquiring point cloud data, inertia measurement data and vehicle speed data of a train running full line;
preprocessing the point cloud data to obtain corrected point cloud data;
storing initial data in the corrected point cloud data into an initial train electronic map, and carrying out pose estimation by combining the inertial measurement data and the speed data to obtain initial estimated pose data;
and superposing and storing the subsequent point cloud data in the corrected point cloud data into the initial train electronic map, and carrying out pose estimation by combining the inertia measurement data and the vehicle speed data until all the point cloud data are processed, so as to obtain the train electronic map.
Specifically, a high-precision train electronic map needs to be constructed before the switch identification is performed on the train.
The high-precision electronic map mainly comprises two parts of scene point cloud and track. The scene point cloud is obtained by acquiring a plurality of frames of preprocessed laser radar point clouds in advance, finding out an accurate pose relation through pose estimation and mutual matching, superposing the pose relation together based on the pose relation, and compressing the pose relation through means such as downsampling.
Before the high-precision electronic map is built, laser radar point cloud data, IMU data and vehicle speed data of all lines are required to be collected, wherein the vehicle speed data can be obtained by a self-millimeter wave radar or a self-speed sensor.
During acquisition, no influence of any obstacle in front, such as a vehicle or a pedestrian, is ensured, so that no interference of the obstacle exists in the established high-precision electronic map, then the point cloud is preprocessed, noise is eliminated, and intra-frame correction is performed.
Further, the obtained initial point cloud data, namely the first frame point cloud, is directly added into the electronic map, then the accurate relative pose of the subsequent point cloud and the electronic map is obtained through pose estimation and matching with the electronic map, and the subsequent point cloud is sequentially overlapped into the high-precision electronic map according to the accurate pose until all the point cloud data are processed, wherein the process is shown in fig. 4.
Since the positional relationship between the laser radar and the vehicle body is fixed, and the vehicle body is directly above the track, the position of the center of the track directly below the radar can be converted from the position of the laser radar. In the process of superposing the point clouds on the high-precision electronic map, the coordinate origin (namely the position of the radar) of each frame of point clouds is converted into the position of the track center right below the radar, and the track tracks are formed by summarizing the positions, so that the electronic map of the train for subsequent use is obtained.
According to the invention, accurate data of the running track is obtained by constructing the train electronic map in advance, so that the train trend can be conveniently and subsequently identified, and the identification precision and efficiency are improved.
Based on any of the above embodiments, the method further includes, before step S1:
and acquiring a positioning steering angle and a reverse steering angle of each turnout passing through a preset distance of a turnout point in the whole train running line.
Specifically, before identification, besides building a train electronic map, the positioning and reverse steering angles of each turnout crossing a turnout tip in the running track at a certain distance are recorded, and as shown in fig. 5, the steering angle positioned at a position 20 m away from the turnout tip is assumed to be 0 degree, and the corresponding steering angle is assumed to be 6 degrees.
And (3) completely recording the positioning steering angles and the inversion steering angles corresponding to all the turnouts along the running track for comparison use in the follow-up identification.
According to the invention, the positioning steering angle and the inversion steering angle of the turnout are recorded, so that the positioning and inversion angle data are obtained, and the train trend judgment is carried out by combining the positioning and inversion angle data and the position information, so that the identification precision can be effectively improved.
Based on any of the above embodiments, the method step S1 includes:
acquiring current scanning point cloud data in train operation, preprocessing the real-time scanning point cloud data, and obtaining corrected current scanning point cloud data;
integrating the vehicle speed data and the inertial measurement angular speed to obtain the current scanning point cloud estimation pose;
based on the current scanning point cloud estimation pose, matching the corrected current scanning point cloud data with the point cloud data in the train electronic map to obtain an accurate train position;
and when the train passes through any turnout, respectively acquiring a first distance between the accurate position of the train and the positioning track and a second distance between the accurate position of the train and the reversing track, and determining the first trend judgment result based on the first distance and the second distance.
Wherein the determining the first trend determination result based on the first distance and the second distance includes:
if the difference of the first distance minus the second distance is greater than a first threshold, determining that the train is located on the reversed track;
and if the difference of the second distance minus the first distance is larger than a second threshold value, determining that the train is positioned on the positioning track.
Specifically, the high-precision electronic map obtained in the foregoing embodiment and the switch positioning steering angle and the opposite steering angle are loaded into the vehicle-mounted computer, as shown in fig. 6, during the running process of the vehicle, firstly, the real-time scanning point cloud output by the vehicle-mounted laser radar is preprocessed, noise is eliminated, intra-frame correction is performed, then, the estimated pose of the current scanning point cloud is obtained by integrating the vehicle speed and the IMU angular speed, and on the basis of pose estimation, the scanning point cloud is matched with the scene point cloud in the high-precision electronic map, so that the accurate pose of the vehicle is obtained, wherein the vehicle position is included.
When the vehicle passes through the fork point, the distance between the vehicle position and the track of the positioning track and the track of the opposite track are calculated, when the difference between the two distances exceeds a certain threshold value, the vehicle is judged to be on one track, as shown in fig. 7, the position of the vehicle is determined to be at a point P through the matching of the scanning point cloud and the high-precision electronic map, the distance between the point P and the positioning track is d1, namely the first distance, the distance between the point P and the track of the opposite track is d2, namely the second distance, when the value of d1-d2 is larger than the first threshold value (for example, set to be 2 meters), the train is considered to be on the opposite track, and when the value of d2-d1 is larger than the second threshold value, the train is considered to be on the positioning track.
The invention realizes the rapid identification of the trend of the train after the train passes the turnout by means of the vehicle-mounted equipment, does not depend on ground equipment, solves the problem that the specific trend is not known for a long time after the train passes the turnout, enhances the autonomous perception capability of the train, and obviously improves the intelligent degree of the train.
Based on any of the above embodiments, the method step S2 includes:
calculating an inertia measurement horizontal angular velocity integral of the train passing through any turnout, and obtaining a rotation angle in the horizontal direction when the train passes through a preset distance of a turnout point;
and determining the second trend judging result based on the rotation angle, the positioning steering angle and the flip steering angle.
Specifically, the invention also calculates the angle that the train turns in the horizontal direction when the train runs from the fork point (point O) to the point P through integrating the horizontal angular velocity of the IMU, and as shown in figure 7, if the turning angle is 0 degrees, the train is indicated to be positioned, and if the turning angle is beta, the train is indicated to be in the reverse position.
Finally, cross-verifying the train trend obtained in the embodiment and the train trend obtained in the previous embodiment, and if the train trend is consistent, considering that an accurate trend recognition result of the train is obtained.
According to the invention, the steering angle of the train after passing through the turnout point for a certain distance is calculated through integrating the angular speed output by the IMU, and the track of the train, namely the trend of the train, is identified according to the different steering angles of the inversion and the positioning, so that the identification accuracy is further improved as the identification of supplementary verification, the real-time verification and error correction are realized, and the accurate position of the train can be timely reported to the control center, thereby shortening the driving interval of the train and improving the running efficiency.
The implementation of the invention is illustrated in the following in a complete embodiment:
1) The point cloud, IMU, and vehicle speed data are collected. And acquiring data of a line to be established with the high-precision electronic map through a vehicle-mounted laser radar, an IMU, a millimeter wave radar or a speed sensor.
2) And establishing a high-precision electronic map of the track line. And directly adding the first frame of point cloud into the electronic map, then obtaining the accurate relative pose of the subsequent point cloud and the electronic map through pose estimation and matching with the electronic map, then sequentially adding the subsequent point cloud into the high-precision electronic map according to the accurate pose until all the point cloud data are processed, and finally compressing the electronic map in a downsampling mode and the like, thus completing the map establishment. Wherein the pose estimate is obtained by integrating the angular velocity of the IMU output and the vehicle speed.
3) In the process of superposing the point clouds on the high-precision electronic map, the coordinate origin (namely the position of the radar) of each frame of point clouds is converted into the position of the track center right below the radar, and the positions are collected together to form the track.
4) And recording the positioning and reverse steering angles of each turnout at a certain distance after the turnout point is crossed.
5) And loading the high-precision electronic map and the turnout positioning inversion steering angle into the vehicle-mounted computer.
6) Preprocessing the real-time scanning point cloud, obtaining the estimated pose of the current scanning point cloud through integration of the vehicle speed and the IMU angular speed, and matching the scanning point cloud with the scene point cloud in the high-precision electronic map on the basis of pose estimation to obtain the accurate pose of the vehicle.
7) And after the vehicle passes through the fork point, calculating the distances between the vehicle position and the track of the positioning track and the track of the opposite track respectively, and judging that the vehicle is on one of the tracks when the two distance differences exceed a certain threshold value.
8) Through integrating the horizontal angular velocity of the IMU, the angle of the train rotating in the horizontal direction after moving for a certain distance from the fork point is calculated, and the train is determined to be on one of the tracks through matching with the positioning reverse steering angle.
9) And cross-verifying the train trend obtained by the two methods, and obtaining the determined trend of the train if the train trends are consistent.
The system for identifying the track of the train turnout provided by the invention is described below, and the system for identifying the track of the train turnout and the method for identifying the track of the train turnout described above can be correspondingly referred to each other.
Fig. 8 is a schematic structural diagram of a system for identifying the track of a train switch according to the present invention, as shown in fig. 8, including: a first determination module 81, a second determination module 82, and a verification module 83, wherein:
the first determining module 81 is configured to determine a first trend determination result based on the real-time scanning point cloud data and the train electronic map; the second determining module 82 is configured to determine a second trend determination result based on acquiring the turning angle of the switch of the train; the verification module 83 is configured to cross-verify the first trend determination result and the second trend determination result, and determine a train trend determination result.
According to the invention, the rapid identification of the two train trends is realized through the matching of the real-time scanning point cloud and the high-precision electronic map and the integration of the horizontal angular velocity of the IMU, and the reliable detection of the train trend is realized through the cross-validation of the two methods.
Fig. 9 illustrates a physical schematic diagram of an electronic device, as shown in fig. 9, which may include: processor 910, communication interface (Communications Interface), memory 930, and communication bus 940, wherein processor 910, communication interface 920, and memory 930 communicate with each other via communication bus 940. The processor 910 may invoke logic instructions in the memory 930 to perform a method of identifying the track of a train switch, the method comprising: determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map; determining a second trend judgment result based on the obtained turning angle of the train turnout; and carrying out cross verification on the first trend judging result and the second trend judging result to determine a train trend judging result.
Further, the logic instructions in the memory 930 described above may be implemented in the form of software functional units and may be stored in a computer-readable storage medium when sold or used as a stand-alone product. Based on this understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (RAM, random Access Memory), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, the computer program product comprising a computer program, the computer program being storable on a non-transitory computer readable storage medium, the computer program, when executed by a processor, being capable of executing the method for identifying the track of a train switch provided by the methods described above, the method comprising: determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map; determining a second trend judgment result based on the obtained turning angle of the train turnout; and carrying out cross verification on the first trend judging result and the second trend judging result to determine a train trend judging result.
In yet another aspect, the present invention provides a non-transitory computer readable storage medium having stored thereon a computer program which, when executed by a processor, is implemented to perform the method of identifying the track of a train switch provided by the methods described above, the method comprising: determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map; determining a second trend judgment result based on the obtained turning angle of the train turnout; and carrying out cross verification on the first trend judging result and the second trend judging result to determine a train trend judging result.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A method of identifying the track of a train switch, comprising:
determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map;
determining a second trend judgment result based on the obtained turning angle of the train turnout;
cross-verifying the first trend judgment result and the second trend judgment result to determine a train trend judgment result;
the determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map comprises the following steps:
acquiring current scanning point cloud data in train operation, preprocessing the real-time scanning point cloud data, and obtaining corrected current scanning point cloud data;
integrating the vehicle speed data and the inertial measurement angular speed to obtain the current scanning point cloud estimation pose;
based on the current scanning point cloud estimation pose, matching the corrected current scanning point cloud data with the point cloud data in the train electronic map to obtain an accurate train position;
when the train passes through any turnout, a first distance between the accurate position of the train and a positioning track and a second distance between the accurate position of the train and a reversing track are respectively obtained, and the first trend judgment result is determined based on the first distance and the second distance;
the determining the first trend determination result based on the first distance and the second distance includes:
if the difference of the first distance minus the second distance is greater than a first threshold, determining that the train is located on the reversed track;
and if the difference of the second distance minus the first distance is larger than a second threshold value, determining that the train is positioned on the positioning track.
2. The method for identifying the trend of a train switch according to claim 1, wherein the determining the first trend determination result based on the real-time scanning point cloud data and the train electronic map comprises the following steps:
acquiring point cloud data, inertia measurement data and vehicle speed data of a train running full line;
preprocessing the point cloud data to obtain corrected point cloud data;
storing initial data in the corrected point cloud data into an initial train electronic map, and carrying out pose estimation by combining the inertial measurement data and the speed data to obtain initial estimated pose data;
and superposing and storing the subsequent point cloud data in the corrected point cloud data into the initial train electronic map, and carrying out pose estimation by combining the inertia measurement data and the vehicle speed data until all the point cloud data are processed, so as to obtain the train electronic map.
3. The method for identifying the trend of the train turnout according to claim 1 or 2, wherein the determining the first trend determination result based on the real-time scanning point cloud data and the train electronic map further comprises:
and acquiring a positioning steering angle and a reverse steering angle of each turnout passing through a preset distance of a turnout point in the whole train running line.
4. The method of claim 1, wherein determining the second trend determination result based on obtaining the turning angle of the switch of the train comprises:
calculating an inertia measurement horizontal angular velocity integral of the train passing through any turnout, and obtaining a rotation angle in the horizontal direction when the train passes through a preset distance of a turnout point;
and determining the second trend judging result based on the rotation angle, the positioning steering angle and the flip steering angle.
5. A system for identifying the trend of a train switch, comprising:
the first determining module is used for determining a first trend judging result based on the real-time scanning point cloud data and the train electronic map;
the second determining module is used for determining a second trend judging result based on the obtained turning angle of the train turnout;
the verification module is used for carrying out cross verification on the first trend judgment result and the second trend judgment result to determine a train trend judgment result;
the determining a first trend judgment result based on the real-time scanning point cloud data and the train electronic map comprises the following steps:
acquiring current scanning point cloud data in train operation, preprocessing the real-time scanning point cloud data, and obtaining corrected current scanning point cloud data;
integrating the vehicle speed data and the inertial measurement angular speed to obtain the current scanning point cloud estimation pose;
based on the current scanning point cloud estimation pose, matching the corrected current scanning point cloud data with the point cloud data in the train electronic map to obtain an accurate train position;
when the train passes through any turnout, a first distance between the accurate position of the train and a positioning track and a second distance between the accurate position of the train and a reversing track are respectively obtained, and the first trend judgment result is determined based on the first distance and the second distance;
the determining the first trend determination result based on the first distance and the second distance includes:
if the difference of the first distance minus the second distance is greater than a first threshold, determining that the train is located on the reversed track;
and if the difference of the second distance minus the first distance is larger than a second threshold value, determining that the train is positioned on the positioning track.
6. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method of identifying the track of a train switch as claimed in any one of claims 1 to 4 when the program is executed.
7. A non-transitory computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the method of identifying a train switch strike according to any one of claims 1 to 4.
8. A computer program product comprising a computer program which, when executed by a processor, implements the steps of the method of identifying the track of a train switch as claimed in any one of claims 1 to 4.
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| CN109484435B (en) * | 2018-11-28 | 2021-04-27 | 交控科技股份有限公司 | Train positioning method and device suitable for intelligent rail transit detection system |
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