A trajectory data processing method, device and equipment for a road network map

Abstract

The present disclosure provides a trajectory data processing method, device and equipment of a road network map, belonging to the technical field of computer information processing, solving the problem that the trajectory data of the road network map is prone to appear stuttering phenomenon when displayed in a three-dimensional scene, resulting in poor visualization effect. The method comprises: determining a spatial road network model according to a source file in the road network map; generating a trajectory database according to trajectory data in the road network map; correcting trajectory points in the trajectory database according to the spatial road network model to obtain corrected trajectory point data. The technical scheme of the present disclosure can make the trajectory data of the road network map more clear and smooth when displayed in a three-dimensional scene.

Description

Technical Field

[0001] This disclosure relates to the field of computer information processing technology, and in particular to a method, apparatus and equipment for processing trajectory data of a road network map. Background Technology

[0002] Currently, when displaying 3D scenes based on trajectory data from road network maps, the data quality can easily affect the display, causing stuttering. This is especially true for trajectory data acquired through simulation software, video recognition, and vehicle-mounted units, which often suffer from low data frequency and discontinuity, resulting in poor visualization.

[0003] Public content

[0004] This disclosure provides a method, apparatus, and device for processing trajectory data of road network maps, which solves the problem that trajectory data of road network maps is prone to stuttering when displayed in a three-dimensional scene, resulting in poor visualization effects.

[0005] To solve the above-mentioned technical problems, the technical solution disclosed herein is as follows:

[0006] In a first aspect, embodiments of this disclosure provide a method for processing trajectory data of a road network map, including:

[0007] Determine the spatial road network model based on the source files in the road network map;

[0008] Generate a trajectory database based on trajectory data from the road network map;

[0009] Based on the spatial road network model, the trajectory points in the trajectory database are corrected to obtain corrected trajectory point data.

[0010] Optionally, based on the source files in the road network map, determine the spatial road network model, including:

[0011] Obtain lane data from the source file of the road network map;

[0012] Based on lane data, the road boundaries are determined in a preset coordinate system;

[0013] Each road is divided into triangular faces to obtain the road data corresponding to the triangular faces;

[0014] Based on the road data corresponding to the triangular facets, a spatial road network model is obtained.

[0015] Optionally, a trajectory database is generated based on trajectory data in the road network map, including:

[0016] Obtain trajectory data from the trajectory file of the road network map;

[0017] The trajectory data is sorted according to its timestamp to obtain a trajectory data sequence;

[0018] The trajectory data sequence is processed to obtain a trajectory database.

[0019] Optionally, the trajectory data sequence is processed to obtain a trajectory database, including:

[0020] The trajectory data is processed by frame interpolation and smoothing to obtain a trajectory database.

[0021] Optionally, based on the spatial road network model, the trajectory points in the trajectory database are corrected to obtain corrected trajectory point data, including:

[0022] Retrieve trajectory points from the trajectory database;

[0023] Calculate the height of the intersection point between the ray and the spatial road network model. The ray is a ray that starts from the trajectory point and is perpendicular to the ground.

[0024] The height of the intersection point is corrected to obtain the corrected trajectory point data.

[0025] Optionally, the height of the intersection point is corrected to obtain the corrected trajectory point data, including:

[0026] The number of intersections obtained;

[0027] The height of the corrected trajectory points is obtained based on the number of intersections;

[0028] Based on the height of the trajectory point and the lane data corresponding to the trajectory point, the corrected trajectory point data is obtained.

[0029] Optionally, the height of the corrected trajectory points can be obtained based on the number of intersections, including:

[0030] If the number of intersection points is equal to 1, the height of the intersection point is used as the height of the corrected trajectory point;

[0031] If the number of intersection points is greater than 1, retrieve the trajectory points from the trajectory database again, calculate the height of the intersection point between the ray and the spatial road network model, correct the height of the intersection point, and process the corrected trajectory point data.

[0032] Secondly, embodiments of this disclosure provide a trajectory data processing apparatus for a road network map, comprising:

[0033] The determination module is used to determine the spatial road network model based on the source file in the road network map;

[0034] The generation module is used to generate a trajectory database based on trajectory data in the road network map;

[0035] The correction module is used to correct the trajectory points in the trajectory database based on the spatial road network model, so as to obtain the corrected trajectory point data.

[0036] Optionally, the determination module includes:

[0037] The first determination submodule is used to obtain lane data from the source file in the road network map;

[0038] The second determination submodule is used to determine the road boundary in a preset coordinate system based on lane data;

[0039] The third determination submodule is used to divide each road into triangular faces to obtain the road data corresponding to the triangular faces;

[0040] The fourth determination submodule is used to obtain a spatial road network model based on the road data corresponding to the triangular face.

[0041] Optionally, the generation module includes:

[0042] The first generation submodule is used to obtain trajectory data from the trajectory file of the road network map;

[0043] The second generation submodule is used to sort the trajectory data according to the timestamp of the trajectory data to obtain the trajectory data sequence;

[0044] The third generation submodule is used to process the trajectory data sequence to obtain the trajectory database.

[0045] Optionally, the third generation submodule includes:

[0046] The first generation unit is used to perform frame interpolation and smoothing on the trajectory data to obtain a trajectory database.

[0047] Optionally, the calibration module includes:

[0048] The first correction submodule is used to obtain trajectory points from the trajectory database;

[0049] The second correction submodule is used to calculate the height of the intersection point of the ray and the spatial road network model. The ray is a ray that starts from the trajectory point and is perpendicular to the ground.

[0050] The third correction submodule is used to correct the height of the intersection point to obtain the corrected trajectory point data.

[0051] Optionally, the third correction submodule includes:

[0052] The first correction unit is used to obtain the number of intersection points;

[0053] The second correction unit is used to obtain the height of the corrected trajectory points based on the number of intersections;

[0054] The third correction unit is used to obtain the corrected trajectory point data based on the height of the trajectory point and the lane data corresponding to the trajectory point.

[0055] Optionally, the second correction unit is specifically used for:

[0056] If the number of intersection points is equal to 1, the height of the intersection point is used as the height of the corrected trajectory point;

[0057] If the number of intersection points is greater than 1, retrieve the trajectory points from the trajectory database again, calculate the height of the intersection point between the ray and the spatial road network model, correct the height of the intersection point, and process the corrected trajectory point data.

[0058] Thirdly, embodiments of this disclosure provide a computing device, including: a processor and a memory storing a computer program, wherein the computer program, when run by the processor, performs the method as described in the first aspect.

[0059] Fourthly, embodiments of this disclosure provide a computer-readable storage medium storing instructions that, when executed on a computer, cause the computer to perform the method as described in the first aspect.

[0060] The technical solution disclosed herein includes at least the following effects:

[0061] The disclosed method for processing trajectory data of road network maps involves: determining a spatial road network model based on the source file in the road network map; generating a trajectory database based on the trajectory data in the road network map; and correcting the trajectory points in the trajectory database based on the spatial road network model to obtain corrected trajectory point data. This method can improve the visualization quality of trajectory data in road network maps, making the trajectory data of road network maps clearer and smoother when displayed in a three-dimensional scene. Attached Figure Description

[0062] Figure 1 This is a flowchart of the trajectory data processing method for a road network map provided in this embodiment of the disclosure;

[0063] Figure 2 This is a flowchart of the method for determining a spatial road network model in the trajectory data processing method of a road network map provided in this embodiment of the disclosure;

[0064] Figure 3 This is a flowchart illustrating the generation of a trajectory database in the trajectory data processing method for a road network map provided in this embodiment of the disclosure;

[0065] Figure 4 This is a flowchart illustrating the method for obtaining corrected trajectory point data in the trajectory data processing of a road network map provided in this embodiment of the disclosure;

[0066] Figure 5 This is a flowchart of the method for correcting the height of intersection points in the trajectory data processing method of the road network map provided in this embodiment of the disclosure;

[0067] Figure 6 This is a structural diagram of the trajectory data processing device for a road network map provided in this embodiment of the disclosure;

[0068] Figure 7 This is a schematic diagram of the structure of a computing device provided in an embodiment of this disclosure;

[0069] Figure 8 This is a schematic diagram of the hardware structure of a computing device provided in an embodiment of this disclosure. Detailed Implementation

[0070] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0071] The terms "first," "second," etc., used in this disclosure and in the claims are used to distinguish similar objects and not to describe a specific order or sequence. It should be understood that such use of data can be interchanged where appropriate so that embodiments of this disclosure can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class and the number of objects is not limited; for example, a first object can be one or more. Furthermore, in the specification and claims, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0072] like Figure 1 As shown, embodiments of this disclosure propose a method for processing trajectory data of a road network map, including:

[0073] Step 1: Determine the spatial road network model based on the source file in the road network map;

[0074] It's important to note that a road network map is a map that displays road networks and traffic conditions, typically including urban roads, rural roads, and highways. These maps are usually presented in a high-definition visual format, using lines, colors, and symbols to indicate road direction, location, length, traffic conditions, and other information. In a road network map, the source file refers to the data file or database used to generate the map; this data may include geographic coordinates, road names, lengths, traffic flow, and other information, usually stored in vector or raster format. A spatial road network model is a mathematical model that describes the structure of a road network in geographic space. It uses the concepts of nodes and edges to represent the various components of the road network and the relationships between them. In a spatial road network model, nodes typically represent intersections or junctions, while edges represent roads or paths connecting these nodes.

[0075] Step 2: Generate a trajectory database based on the trajectory data in the road network map;

[0076] Step 3: Based on the spatial road network model, correct the trajectory points in the trajectory database to obtain the corrected trajectory point data.

[0077] In this embodiment, a spatial road network model is determined based on the source file in the road network map; a trajectory database is generated based on the trajectory data in the road network map; and the trajectory points in the trajectory database are corrected based on the spatial road network model to obtain corrected trajectory point data. This improves the visualization quality of the trajectory data in the road network map, making the trajectory data in the road network map clearer and smoother when displayed in a 3D scene.

[0078] like Figure 2 As shown, in an optional embodiment of this disclosure, step 1 may include:

[0079] Step 11: Obtain lane data from the source file in the road network map;

[0080] Step 12: Determine the road boundary in the preset coordinate system based on the lane data;

[0081] Step 13: Divide each road into triangular faces to obtain the road data corresponding to the triangular faces;

[0082] Step 14: Obtain the spatial road network model based on the road data corresponding to the triangular facets.

[0083] In this embodiment, lane data can be obtained from source files in the road network map. This lane data includes information such as lane location, length, and direction. This lane data can be obtained by parsing the FBX or OpenDrive files of the road network model. After obtaining the lane data, a preset coordinate system is defined (such as the ST coordinate system, which typically refers to a space-time coordinate system, where spatial coordinates describe location and time coordinates track changes in location over time). This coordinate system combines the spatial location and temporal information of the road network. Using the obtained lane data, based on the actual size and direction of the lanes, the boundaries of each road are delineated in the ST coordinate system, including the road width and edge lines, as well as possible medians or other structures. Each road is then triangulated. First, the lane outline is identified based on the road boundary, including the left and right edges of the lane. A series of vertices are generated along the lane boundary line, and these vertices are evenly distributed on the lane boundary to ensure uniform division of the triangular faces. Triangles are constructed using these vertices, and the created triangles are made as small as possible to cover the entire lane area. After the initial triangle construction, further subdivision is performed to accommodate the special shapes of the lanes (such as curves, ramps, etc.). Finally, each triangle is associated with its corresponding lane information to ensure that the triangular face represents not only the spatial location but also the lane attributes. After the triangular face division is completed, a quality check is performed to ensure that the triangular faces correctly cover the lane area without overlap or missing parts. Based on the road data corresponding to the triangular faces, all triangular faces are bounded hierarchically. The construction of the Volume Hierarchy (BVH) yields a spatial road network model, including: calculating a bounding box for each triangular facet, where the bounding box is a simple geometric shape (usually a rectangle or cuboid) that completely contains the triangular facet; organizing all triangular faces into a hierarchical tree structure based on their spatial location, dividing the space into smaller regions, and assigning the triangular faces within each region to corresponding tree nodes; further subdividing each node based on the overlap of bounding boxes and spatial density to make the tree more balanced; and storing the tree structure for fast indexing after the tree is constructed, including assigning a unique identifier to each node and storing node information in a fast-access data structure.

[0084] like Figure 3 As shown, in an optional embodiment of this disclosure, step 2 may include:

[0085] Step 21: Obtain trajectory data from the trajectory file of the road network map;

[0086] Step 22: Sort the trajectory data according to the timestamps to obtain the trajectory data sequence;

[0087] Step 23: Process the trajectory data sequence to obtain the trajectory database.

[0088] In this embodiment, trajectory data is obtained from the trajectory file of the road network map and sorted according to the timestamp of the trajectory data. This data typically includes location coordinates (such as latitude and longitude), timestamp, speed, and direction. The lane centerline closest to each trajectory point is identified, and the distance between the trajectory point and each lane centerline is calculated. The closest lane centerline is selected. The trajectory points are mapped to the selected lane centerlines, including adjusting the position of the trajectory points to determine the nearest point and place it on the centerline. To improve the smoothness of the trajectory data, interpolation or filtering methods can be used, such as using a Kalman filter or other smoothing algorithms to reduce noise and random errors in the trajectory data. During the correction process, lane changes of vehicles need to be considered, i.e., when a vehicle moves from one lane to another, the correction algorithm needs to adjust the trajectory points accordingly. To ensure the temporal sequence and continuity of the data, it is necessary to ensure that the timestamp of the corrected trajectory data is consistent with the original data. The corrected trajectory data is verified to ensure that it accurately reflects the actual movement of the vehicle in the lane. Finally, the corrected trajectory data is recorded in the database according to the timestamp of the trajectory data to obtain the trajectory database.

[0089] In an optional embodiment of this disclosure, step 23 may include:

[0090] The trajectory data is processed by frame interpolation and smoothing to obtain a trajectory database.

[0091] In this embodiment, the trajectory data sequence is processed to obtain a trajectory database. The process also includes frame interpolation and smoothing of the trajectory data. Taking three adjacent times A, B, and C as an example, frame interpolation is first performed. If the trajectory points of the same object appear at times A (t=0) and C (t=2), but are missing at time B (t=1), where the object's position at time A is (0,0) with a rotation angle of 0 degrees, and its position at time C is (4,4) with a rotation angle of 90 degrees, polynomial interpolation is applied to the position and rotation data at times A and C to obtain the time... The estimated value for time B is: position (1.5, 1.5) and rotation angle of 33.75 degrees. This means that at time B, the object's position is expected to be near the midpoint between the origin (0,0) and the target position (4,4), and the rotation angle will be the intermediate value between the initial rotation and the target rotation. Interpolation is used to make the object's motion and rotation transition smoothly between the two known times. Finally, the object's position and rotation angle at time B are written back to the database. If the original data frequency is insufficient, the same interpolation method is used to insert data between times AB and BC to meet the frequency requirements.

[0092] like Figure 4 As shown, in an optional embodiment of this disclosure, step 3 may include:

[0093] Step 31: Obtain trajectory points from the trajectory database;

[0094] Step 32: Calculate the height of the intersection point between the ray and the spatial road network model. The ray is a ray that starts from the trajectory point and is perpendicular to the ground.

[0095] Step 33: Correct the height of the intersection point to obtain the corrected trajectory point data.

[0096] In this embodiment, any trajectory point is obtained from the trajectory database, a ray is drawn that passes through the trajectory point and is perpendicular to the ground, the ray intersects with the spatial road network model to generate one or more intersection points, the height of the intersection points is calculated, and the height of the intersection points is corrected to obtain the corrected trajectory point data.

[0097] like Figure 5 As shown, in an optional embodiment of this disclosure, step 33 may include:

[0098] Step 331: Obtain the number of intersections;

[0099] Step 332: Based on the number of intersections, obtain the height of the corrected trajectory points;

[0100] Step 333: Based on the height of the trajectory point and the lane data corresponding to the trajectory point, obtain the corrected trajectory point data.

[0101] In this embodiment, the number of intersections between rays passing through the trajectory points and perpendicular to the ground and the spatial road network model is counted; different correction methods are used to correct the height of the trajectory points according to the number of intersections; the corrected trajectory point data is obtained by combining the corrected height of the trajectory points with the lane data corresponding to the trajectory points.

[0102] In an optional embodiment of this disclosure, step 332 may include:

[0103] If the number of intersection points is equal to 1, the height of the intersection point is used as the height of the corrected trajectory point;

[0104] If the number of intersection points is greater than 1, retrieve the trajectory points from the trajectory database again, calculate the height of the intersection point between the ray and the spatial road network model, correct the height of the intersection point, and process the corrected trajectory point data.

[0105] In this embodiment, if the number of intersection points equals 1, then the height of that intersection point is the corrected height of the trajectory point. If the number of intersection points is greater than 1, it indicates that the exact height of the point cannot be accurately determined based on the current information (e.g., the trajectory point is located on two different road surfaces above and below an overpass). In this case, all possible height values ​​and corresponding road network information are recorded. Historical data of the same trajectory is then examined, especially the data points immediately before and after the trajectory point, as historical data may provide clues about the road surface height where the trajectory is usually located. The vehicle's motion patterns, such as speed, direction, and previous routes, are analyzed to determine which height the vehicle is more likely to be at. If road network structure information near the trajectory point is available, such as overpass design data, this information can be used to infer the most likely height of the trajectory point. Combining all the above information, the most likely height is inferred using data fusion techniques, including statistical analysis or the use of specialized algorithms (such as machine learning models) to evaluate the probability of different heights. Once the most likely height is determined, the height information of the trajectory point is updated and recorded in the database. If any discontinuous or unreasonable height changes are found, a reassessment may be necessary. If a unique height cannot be determined immediately, the above process may need to be iterated, using newly collected data and analysis each time to gradually narrow down the possible height range.

[0106] The above embodiments of this disclosure improve the visualization quality of trajectory data in road network maps by optimizing trajectory points in the trajectory database, making the trajectory data of road network maps clearer and smoother when displayed in a three-dimensional scene.

[0107] like Figure 6 As shown, this embodiment of the disclosure provides a trajectory data processing device 60 for a road network map, including:

[0108] Module 61 is used to determine the spatial road network model based on the source file in the road network map;

[0109] The generation module 62 is used to generate a trajectory database based on trajectory data in the road network map;

[0110] The correction module 63 is used to correct the trajectory points in the trajectory database according to the spatial road network model to obtain the corrected trajectory point data.

[0111] Optionally, the determining module 61 includes:

[0112] The first determination submodule is used to obtain lane data from the source file in the road network map;

[0113] The second determination submodule is used to determine the road boundary in a preset coordinate system based on lane data;

[0114] The third determination submodule is used to divide each road into triangular faces to obtain the road data corresponding to the triangular faces;

[0115] The fourth determination submodule is used to obtain a spatial road network model based on the road data corresponding to the triangular face.

[0116] Optionally, the generation module 62 includes:

[0117] The first generation submodule is used to obtain trajectory data from the trajectory file of the road network map;

[0118] The second generation submodule is used to sort the trajectory data according to the timestamp of the trajectory data to obtain the trajectory data sequence;

[0119] The third generation submodule is used to process the trajectory data sequence to obtain the trajectory database.

[0120] Optionally, the third generation submodule includes:

[0121] The first generation unit is used to perform frame interpolation and smoothing on the trajectory data to obtain a trajectory database.

[0122] Optionally, the calibration module 63 includes:

[0123] The first correction submodule is used to obtain trajectory points from the trajectory database;

[0124] The second correction submodule is used to calculate the height of the intersection point of the ray and the spatial road network model. The ray is a ray that starts from the trajectory point and is perpendicular to the ground.

[0125] The third correction submodule is used to correct the height of the intersection point to obtain the corrected trajectory point data.

[0126] Optionally, the third correction submodule includes:

[0127] The first correction unit is used to obtain the number of intersection points;

[0128] The second correction unit is used to obtain the height of the corrected trajectory points based on the number of intersections;

[0129] The third correction unit is used to obtain the corrected trajectory point data based on the height of the trajectory point and the lane data corresponding to the trajectory point.

[0130] Optionally, the second correction unit is specifically used for:

[0131] If the number of intersection points is equal to 1, the height of the intersection point is used as the height of the corrected trajectory point;

[0132] If the number of intersection points is greater than 1, retrieve the trajectory points from the trajectory database again, calculate the height of the intersection point between the ray and the spatial road network model, correct the height of the intersection point, and process the corrected trajectory point data.

[0133] It should be noted that this device is a device corresponding to the above method. All implementation methods in the above method embodiments are applicable to this embodiment and can achieve the same technical effect.

[0134] like Figure 7 As shown, this disclosure also provides a computing device 70, including a processor 71, a memory 72, and a program or instructions stored in the memory 72 and executable on the processor 71. When executed by the processor 71, the program or instructions implement the various processes of the above-described road network map trajectory data processing method embodiments and achieve the same technical effects. To avoid repetition, further details are omitted here. It should be noted that the computing device in this disclosure includes the aforementioned mobile electronic devices and non-mobile electronic devices.

[0135] Figure 8 A schematic diagram of the hardware structure of a computing device to implement an embodiment of this disclosure.

[0136] The computing device 800 includes, but is not limited to, components such as: radio frequency unit 801, network module 802, audio output unit 803, input unit 804, sensor 805, display unit 806, user input unit 807, interface unit 806, memory 809, and processor 810.

[0137] Those skilled in the art will understand that the computing device 800 may also include a power supply (such as a battery) for supplying power to various components. The power supply may be logically connected to the processor 810 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption through the power management system. Figure 8 The computing device structure shown does not constitute a limitation on the computing device. The computing device may include more or fewer components than shown, or combine certain components, or have different component arrangements, which will not be elaborated here.

[0138] It should be understood that, in this embodiment, the input unit 804 may include a graphics processing unit (GPU) 8041 and a microphone 8042. The GPU 8041 processes image data of still images or videos obtained by an image capture device (such as a camera) in video capture mode or image capture mode. The display unit 806 may include a display panel 8061, which may be configured in the form of a liquid crystal display, an organic light-emitting diode, or the like. The user input unit 807 includes a touch panel 8071 and other input devices 8072. The touch panel 8071 is also called a touch screen. The touch panel 8071 may include a touch detection device and a touch controller. Other input devices 8072 may include, but are not limited to, a physical keyboard, function keys (such as volume control buttons, power buttons, etc.), a trackball, a mouse, and a joystick, which will not be described in detail here. The memory 809 can be used to store software programs and various data, including but not limited to applications and operating systems. Processor 810 can integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the modem processor may also not be integrated into processor 810.

[0139] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this disclosure.

[0140] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0141] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0142] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0143] In addition, the functional units in the various embodiments of this disclosure can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0144] The data is stored in a computer-readable storage medium. Based on this understanding, the technical solution of this disclosure, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this disclosure. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0145] Furthermore, it should be noted that in the apparatus and method of this disclosure, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of this disclosure. Moreover, the steps performing the above series of processes can naturally be executed in the order described, but are not necessarily required to be executed in chronological order; some steps can be executed in parallel or independently of each other. Those skilled in the art will understand that all or any step or component of the method and apparatus of this disclosure can be implemented in any computing device (including processors, storage media, etc.) or network of computing devices, in hardware, firmware, software, or a combination thereof, which can be achieved by those skilled in the art using their basic programming skills after reading the description of this disclosure.

[0146] Therefore, the object of this disclosure can also be achieved by running a program or a set of programs on any computing device. The computing device can be a known general-purpose device. Therefore, the object of this disclosure can also be achieved simply by providing a program product containing program code implementing the method or apparatus. That is, such a program product also constitutes this disclosure, and a storage medium storing such a program product also constitutes this disclosure. Obviously, the storage medium can be any known storage medium or any storage medium developed in the future. It should also be noted that in the apparatus and methods of this disclosure, it is obvious that the components or steps can be decomposed and / or recombined. These decompositions and / or recombinations should be considered equivalent solutions of this disclosure. Furthermore, the steps performing the above series of processes can naturally be performed in the order described and in chronological order, but are not necessarily required to be performed in chronological order. Some steps can be performed in parallel or independently of each other.

[0147] The above are preferred embodiments of this disclosure. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principles of this disclosure, and these improvements and modifications should also be considered within the scope of protection of this disclosure.

Claims

1. A method for processing trajectory data of a road network map, characterized in that, include: Determine the spatial road network model based on the source files in the road network map; Generate a trajectory database based on trajectory data from the road network map; Based on the spatial road network model, the trajectory points in the trajectory database are corrected to obtain corrected trajectory point data; Specifically, based on the spatial road network model, the trajectory points in the trajectory database are corrected to obtain corrected trajectory point data, including: Retrieve trajectory points from the trajectory database; Calculate the height of the intersection point between the ray and the spatial road network model, where the ray is a ray that originates from the trajectory point and is perpendicular to the ground; The height of the intersection point is corrected to obtain the corrected trajectory point data; The process of correcting the height of the intersection points to obtain the corrected trajectory point data includes: Obtain the number of the intersection points; The height of the corrected trajectory point is obtained based on the number of intersection points; The corrected trajectory point data is obtained based on the height of the trajectory point and the lane data corresponding to the trajectory point; The height of the corrected trajectory point is obtained based on the number of intersection points, including: If the number of intersection points is equal to 1, the height of the intersection point is taken as the height of the corrected trajectory point; If the number of intersection points is greater than 1, the trajectory points are retrieved again from the trajectory database, and the height of the intersection point between the ray and the spatial road network model is calculated. The height of the intersection point is then corrected to obtain the corrected trajectory point data.

2. The method for processing trajectory data of a road network map according to claim 1, characterized in that, Based on the source files in the road network map, determine the spatial road network model, including: Obtain lane data from the source file of the road network map; Based on the lane data, the road boundary is determined in a preset coordinate system; Each road is divided into triangular faces to obtain the road data corresponding to the triangular faces; The spatial road network model is obtained based on the road data corresponding to the triangular facets.

3. The method for processing trajectory data of a road network map according to claim 1, characterized in that, Based on trajectory data in the road network map, a trajectory database is generated, including: Obtain trajectory data from the trajectory file of the road network map; The trajectory data is sorted according to the timestamps to obtain a trajectory data sequence; The trajectory data sequence is processed to obtain the trajectory database.

4. The method for processing trajectory data of a road network map according to claim 3, characterized in that, The trajectory data sequence is processed to obtain the trajectory database, including: The trajectory data is subjected to frame interpolation and smoothing processing to obtain the trajectory database.

5. A trajectory data processing device for a road network map, characterized in that, include: The determination module is used to determine the spatial road network model based on the source file in the road network map; The generation module is used to generate a trajectory database based on trajectory data in the road network map; The correction module is used to correct the trajectory points in the trajectory database according to the spatial road network model to obtain corrected trajectory point data; Specifically, based on the spatial road network model, the trajectory points in the trajectory database are corrected to obtain corrected trajectory point data, including: Retrieve trajectory points from the trajectory database; Calculate the height of the intersection point between the ray and the spatial road network model, where the ray is a ray that originates from the trajectory point and is perpendicular to the ground; The height of the intersection point is corrected to obtain the corrected trajectory point data; The process of correcting the height of the intersection points to obtain the corrected trajectory point data includes: Obtain the number of the intersection points; The height of the corrected trajectory point is obtained based on the number of intersection points; The corrected trajectory point data is obtained based on the height of the trajectory point and the lane data corresponding to the trajectory point; The height of the corrected trajectory point is obtained based on the number of intersection points, including: If the number of intersection points is equal to 1, the height of the intersection point is taken as the height of the corrected trajectory point; If the number of intersection points is greater than 1, the trajectory points are retrieved again from the trajectory database, and the height of the intersection point between the ray and the spatial road network model is calculated. The height of the intersection point is then corrected to obtain the corrected trajectory point data.

6. A computing device, characterized in that, include: A processor, a memory storing a computer program, wherein the computer program, when executed by the processor, performs the method as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The system stores instructions that, when executed on a computer, cause the computer to perform the method as described in any one of claims 1 to 4.

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