Positioning optimization method, system, device and storage medium based on grid map

Abstract

The present invention provides a grid-map-based positioning optimization method, system, device, and storage medium. The method comprises the following steps: gridding a target area; collecting reference values ​​corresponding to at least two positioning evaluation methods when at least one vehicle passes through each grid; obtaining a grid positioning performance value based on the reference values ​​for each grid; and modifying the positioning environment of grids whose positioning performance values ​​fall below a preset threshold. The present invention can effectively evaluate the positioning performance of each subdivided area in a port environment and make targeted adjustments and modifications to areas with poor positioning performance.

Description

Technical Field

[0001] The present invention relates to the field of navigation and positioning technology, and in particular to a positioning optimization method, system, device and storage medium based on a grid map. Background Art

[0002] To achieve precise planning and control during autonomous navigation, autonomous vehicles must possess high positioning performance. The unique operating environment of autonomous container trucks in ports places even more stringent positioning requirements. Evaluating the performance of positioning algorithms for autonomous port vehicles in real-world scenarios, and thus enabling targeted optimization and iteration, remains a pressing challenge.

[0003] Existing positioning evaluation methods typically use high-precision measurement equipment to measure the true value of the vehicle's pose. The estimated vehicle pose output by the positioning algorithm is compared with the absolute true value measured by the measurement equipment, and the accuracy of the positioning algorithm is evaluated based on the difference between the two. This method is labor-intensive and can only evaluate positioning accuracy.

[0004] In view of this, the present invention provides a positioning optimization method, system, device and storage medium based on a grid map.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present invention, and therefore may include information that does not constitute prior art known to ordinary technicians in this field. Summary of the Invention

[0006] In response to the problems in the prior art, the purpose of the present invention is to provide a positioning optimization method, system, device and storage medium based on a grid map, which overcomes the difficulties of the prior art, can effectively evaluate the positioning performance of each subdivided area in the port environment, and make targeted adjustments and modifications to areas with poor positioning performance.

[0007] An embodiment of the present invention provides a positioning optimization method based on a grid map, comprising the following steps:

[0008] Gridding the target area;

[0009] Collecting reference values ​​corresponding to at least two positioning evaluation methods when at least one vehicle passes through each grid;

[0010] Obtaining the grid positioning performance value based on each reference value of the grid; and

[0011] For the grid whose positioning performance value is lower than a preset threshold, positioning environment modification is performed on the grid.

[0012] Preferably, gridding the target area includes:

[0013] The target area is meshed according to the preset grid size.

[0014] Preferably, the collecting of reference values ​​corresponding to at least two positioning evaluation methods when at least one vehicle passes through each grid includes:

[0015] Collect driving logs of vehicles operating in the target area;

[0016] Taking each grid as a unit, at least the divergence parameter, positioning accuracy parameter and positioning robustness parameter of the satellite positioning when the vehicle passes through the grid are collected.

[0017] Preferably, the step of collecting at least the divergence parameter, positioning accuracy parameter, and positioning robustness parameter of the satellite positioning when the vehicle passes through each grid as a unit includes:

[0018] The satellite positioning includes a signal convergence state and a signal divergence state, and the percentage of the time period of the signal state divergence to the total time length is obtained as the satellite positioning divergence parameter.

[0019] Preferably, the step of collecting at least the divergence parameter, positioning accuracy parameter, and positioning robustness parameter of the satellite positioning when the vehicle passes through each grid as a unit includes:

[0020] A first positioning result obtained when the satellite positioning is in a signal convergence state;

[0021] a second positioning result output by the positioning algorithm;

[0022] The positioning accuracy parameter is obtained based on an error between the first positioning result and the second positioning result.

[0023] Preferably, the error includes an error in vehicle lateral information, an error in vehicle longitudinal information, and an error in heading angle between the first positioning result and the second positioning result.

[0024] Preferably, the step of collecting at least the divergence parameter, positioning accuracy parameter, and positioning robustness parameter of the satellite positioning when the vehicle passes through each grid as a unit includes:

[0025] Perform polynomial fitting on the trajectory points output by the positioning algorithm to obtain a curve, calculate the variance of the distance from the trajectory point to the fitted curve, and obtain the smoothness of the positioning based on the variance;

[0026] Record the fault coordinates each time a vehicle fails due to positioning problems, and obtain the failure rate based on the density of the fault coordinates in each grid;

[0027] A positioning robustness parameter of the grid is obtained based on at least the smoothness and the failure rate.

[0028] Preferably, obtaining the grid positioning performance value based on each reference value of each grid includes:

[0029] The grid positioning performance value is obtained based on weighted calculation of each reference value of each grid.

[0030] Preferably, for the grid whose positioning performance value is lower than a preset threshold, performing positioning environment modification on the grid includes:

[0031] Obtaining the grid whose positioning performance value is lower than a preset threshold as the target grid;

[0032] Generate positioning marker coordinates on both sides of the road in the electronic map corresponding to the target grid, each positioning marker coordinate having a preset high-precision coordinate;

[0033] An entity location marker is added to the target area based on the location marker coordinates.

[0034] An embodiment of the present invention further provides a grid map-based positioning optimization system for implementing the above-mentioned grid map-based positioning optimization method. The grid map-based positioning optimization system includes:

[0035] Grid planning module, which grids the target area;

[0036] A positioning evaluation module, which collects reference values ​​corresponding to at least two positioning evaluation methods when at least one vehicle passes through each grid;

[0037] a weighted calculation module, which obtains the grid positioning performance value based on weighted calculation of each reference value of each grid; and

[0038] The environment transformation module performs positioning environment transformation on the grid whose positioning performance value is lower than a preset threshold.

[0039] An embodiment of the present invention further provides a positioning optimization device based on a grid map, comprising:

[0040] processor;

[0041] a memory storing executable instructions for the processor;

[0042] The processor is configured to execute the steps of the above-mentioned grid map-based positioning optimization method by executing executable instructions.

[0043] An embodiment of the present invention further provides a computer-readable storage medium for storing a program, which implements the steps of the above-mentioned grid map-based positioning optimization method when executed.

[0044] The grid map-based positioning optimization method, system, device and storage medium of the present invention can effectively evaluate the positioning performance of each subdivided area in a port environment and make targeted adjustments to areas with poor positioning performance. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Other features, objects and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings.

[0046] Figure 1 It is a flow chart of the positioning optimization method based on grid map of the present invention.

[0047] Figure 2 It is a schematic diagram of the steps of an implementation process of the grid map-based positioning optimization method of the present invention.

[0048] Figures 3 to 7 This is a schematic diagram of a scenario for implementing the grid map-based positioning optimization method of the present invention.

[0049] Figure 8 It is a structural diagram of the grid map-based positioning optimization system of the present invention.

[0050] Figure 9 Schematic diagram of the structure of the grid map-based positioning optimization device of the present invention.

[0051] Figure 10 It is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present invention. DETAILED DESCRIPTION

[0052] The following describes the embodiments of the present application through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present application from the content disclosed in the present application. The present application can also be implemented or applied through different specific embodiments. The details in the present application can also be modified or changed according to different viewpoints and application systems without departing from the spirit of the present application. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other unless they conflict.

[0053] The following is a detailed description of the embodiments of the present application with reference to the accompanying drawings so that those skilled in the art can easily implement the present application. The present application can be embodied in many different forms and is not limited to the embodiments described herein.

[0054] In the description of this application, reference to the terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples" means that the specific features, structures, materials, or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of this application. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. In addition, those skilled in the art may combine and integrate different embodiments or examples described in this application, as well as features of different embodiments or examples, unless otherwise contradictory.

[0055] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features being referred to. Thus, a feature identified as "first" or "second" may explicitly or implicitly include at least one such feature. In the context of this application, "plurality" means two or more, unless otherwise specifically defined.

[0056] In order to clearly describe the present application, components not related to the description are omitted, and the same or similar components throughout the specification are given the same reference numerals.

[0057] Throughout this specification, when a device is said to be "connected" to another device, this includes not only "direct connection" but also "indirect connection" with other elements interposed therebetween. Furthermore, when a device is said to "include" a certain component, unless otherwise stated, this does not exclude the inclusion of other components but rather implies that the device may include other components.

[0058] When a device is said to be "on" another device, it may be directly on the other device, but there may also be other devices between it. In contrast, when a device is said to be "directly on" another device, there are no other devices between it.

[0059] Although in some instances the terms first, second, etc. are used to represent various elements in the present invention, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, the first interface and the second interface, etc. are represented. Furthermore, as used in the present invention, the singular forms "one", "an", and "the" are intended to also include the plural forms, unless there is a contrary indication in the context. It should be further understood that the terms "comprise" and "include" indicate the presence of features, steps, operations, elements, components, items, types, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, types, and / or groups. The terms "or" and "and / or" used herein are interpreted as inclusive, or mean any one or any combination. Therefore, "A, B, or C" or "A, B, and / or C" means "any of the following: A; B; C; A and B; A and C; B and C; A, B, and C". An exception to this definition occurs only when a combination of elements, functions, steps, or operations are inherently mutually exclusive in some manner.

[0060] The technical terms used herein are intended only to refer to specific embodiments and are not intended to limit this application. The singular form used herein also includes the plural form unless the statement explicitly indicates otherwise. The term "comprising" as used in this specification is intended to specify specific features, regions, integers, steps, operations, elements, and / or components and does not exclude the presence or addition of other features, regions, integers, steps, operations, elements, and / or components.

[0061] Although not defined differently, all terms used herein, including technical and scientific terms, have the same meanings as those generally understood by those skilled in the art to which this application belongs. Terms defined in commonly used dictionaries are to be interpreted as having meanings consistent with the relevant technical literature and current teachings, and unless otherwise defined, they should not be overly interpreted as ideal or highly formalized meanings.

[0062] Figure 1 Flowchart of the grid map-based positioning optimization method of the present invention. Figure 1 As shown, an embodiment of the present invention provides a positioning optimization method based on a grid map, comprising the following steps:

[0063] S110: Gridding the target area.

[0064] S120 : Collect reference values ​​corresponding to at least two positioning evaluation methods when at least one vehicle passes through each grid.

[0065] S130, obtaining a grid positioning performance value based on each reference value of each grid. And

[0066] S140: For a grid whose positioning performance value is lower than a preset threshold, perform positioning environment modification on the grid.

[0067] This paper proposes a workflow for a comprehensive method for evaluating the positioning performance of unmanned container trucks in ports. This method analyzes positioning performance across multiple evaluation metrics within each subdivided area within a closed scene and visualizes the analysis results. This method not only obtains quantitative positioning performance data but also visually analyzes the distribution of positioning performance within a global map. Based on the analysis results, targeted environmental modifications can be made to areas with weak positioning performance, or algorithmic optimization can be performed on specific positioning metrics to improve the overall performance of the positioning algorithm within the closed port environment.

[0068] In a preferred embodiment, step S110 includes:

[0069] The target area is gridded according to a preset grid size, but is not limited thereto.

[0070] In a preferred embodiment, step S120 includes:

[0071] S121. Collect driving logs of vehicles operating in the target area.

[0072] S122. Taking each grid as a unit, at least collect the divergence parameter, positioning accuracy parameter, and positioning robustness parameter of the satellite positioning when the vehicle passes through the grid, but the present invention is not limited thereto.

[0073] In a preferred embodiment, step S122 includes:

[0074] S1221. Satellite positioning includes a signal convergence state and a signal divergence state. The percentage of the signal divergence period in the total time is obtained as a satellite positioning divergence parameter, but the present invention is not limited thereto.

[0075] In a preferred embodiment, step S122 includes:

[0076] S1222: Obtain a first positioning result when the satellite positioning is in a signal convergence state.

[0077] S1223. The second positioning result output by the positioning algorithm.

[0078] S1224. Obtain a positioning accuracy parameter based on an error between the first positioning result and the second positioning result, but the present invention is not limited thereto.

[0079] In a preferred embodiment, the error includes an error in vehicle lateral information, an error in vehicle longitudinal information, and an error in heading angle between the first positioning result and the second positioning result, but is not limited thereto.

[0080] In a preferred embodiment, step S122 includes:

[0081] S1225 , performing polynomial fitting on the trajectory points output by the positioning algorithm to obtain a curve, calculating the variance of the distance from the trajectory points to the fitted curve, and obtaining the smoothness of the positioning based on the variance.

[0082] S1226. Record the fault coordinates each time a vehicle fails due to a positioning problem, and obtain a failure rate based on the density of the fault coordinates in each grid.

[0083] S1227. Obtain positioning robustness parameters of the grid based at least on the smoothness and the failure rate, but not limited thereto.

[0084] In a preferred embodiment, step S130 includes:

[0085] The grid positioning performance value is obtained based on the weighted calculation of each reference value of each grid, but is not limited thereto.

[0086] In a preferred embodiment, step S140 includes:

[0087] S141. Obtain a grid whose positioning performance value is lower than a preset threshold as a target grid.

[0088] S142: Generate positioning marker coordinates on both sides of the road in the electronic map corresponding to the target grid, each positioning marker coordinate having a preset high-precision coordinate.

[0089] S143: Add an entity positioning marker to the target area based on the positioning marker coordinates, but the present invention is not limited thereto.

[0090] The method described in this paper can grid the scene map and evaluate multiple metrics for each grid, including positioning accuracy, robustness, and GNSS distribution, to assess the positioning performance of each subdivided area in the port environment. Once the analysis report is generated, targeted improvements can be made to specific metrics in areas with poor positioning performance.

[0091] Figure 2 It is a schematic diagram of the steps of an implementation process of the grid map-based positioning optimization method of the present invention. Figures 3 to 7 This is a scene diagram of an implementation process of the grid map-based positioning optimization method of the present invention. Figure 3 As shown, first divide the map of the entire space scene into several grids 2 (see Figure 3 ).

[0092] refer to Figure 4As shown, the positioning performance of vehicles 21, 22, and 23 within each grid is analyzed based on various indicators to determine the positioning performance of the positioning algorithm in different areas. By analyzing the positioning accuracy, positioning robustness, and GNSS status distribution within each grid area, the positioning performance of the positioning algorithm based on various indicators is determined. First, the positioning algorithm is run online in the domain controller during normal vehicle operation. While the algorithm is running, key log data (log data) is collected, such as the positioning trajectory points, GNSS status, and vehicle positioning error information for each frame. A dataset is also collected for offline algorithm operation. After the dataset is downloaded locally, the algorithm can be run offline locally. The offline operation also allows logs to be collected and analyzed. GNSS generally refers to the Global Navigation Satellite System (GNSS), an airborne radio navigation and positioning system that provides information to users. GNSS positioning utilizes observations such as pseudoranges, ephemeris, and satellite launch times from a group of satellites. The user clock error must also be known. GNSS is an airborne radio navigation and positioning system that provides users with all-weather 3D coordinate, velocity, and time information at any location on the Earth's surface or in near-Earth space. Therefore, to put it simply, if you need to know altitude in addition to latitude and longitude, then accurate positioning requires receiving signals from all four satellites. Positioning robustness encompasses both positioning stability robustness (i.e., positioning smoothness) and positioning quality robustness (i.e., positioning failure rate). The robustness of a control system is crucial to its practical application. Therefore, robustness has become a crucial design criterion in modern control system design.

[0093] refer to Figure 5As shown, a positioning performance evaluation standard is proposed, and positioning performance is quantified and visualized. The quantified values ​​of various positioning performance indicators in each grid on the map can be displayed, and the strength of the positioning performance of each grid can be represented by different colors, which can more intuitively show the distribution of positioning performance in different areas within the scene. By constructing a data recovery system, the positioning algorithm evaluation method of the present invention is able to analyze data generated by both online and offline operations. In this embodiment, after obtaining the log data, the analysis is mainly based on three aspects: GNSS status (satellite positioning divergence parameter), positioning accuracy, and positioning robustness (positioning smoothness and positioning failure rate). There are many large-scale mechanical equipment in the port, and the GNSS signal is easily blocked. The ratio of the time when the GNSS state is divergent to the total time is calculated. At the same time, the good and bad GNSS status in the global map is represented by different colors to visualize the distribution of GNSS status. The positioning result when the GNSS signal is good is used as the true value. The true value is compared with the positioning result output by the positioning algorithm to evaluate the vehicle's lateral, longitudinal, and heading angle errors to evaluate the accuracy of the positioning algorithm. The trajectory points output by the positioning algorithm are fitted with a polynomial, and the variance of the distance from the trajectory point to the fitted curve is calculated. This variance is used as the smoothness of the positioning. When the vehicle is in operation, the coordinates of the vehicle are recorded each time it fails due to positioning problems, and the failure rate of the vehicle in each subdivided area is calculated based on this. In this embodiment, (1) satellite positioning includes signal convergence state and signal divergence state, and the percentage of the signal state divergence period in the total time is obtained as the satellite positioning divergence parameter. (2) The first positioning result is obtained when the satellite positioning is in the signal convergence state. The second positioning result is output by the positioning algorithm. The positioning accuracy parameter is obtained based on the error between the first positioning result and the second positioning result. The error includes the error of the vehicle lateral information, the error of the vehicle longitudinal information and the error of the heading angle between the first positioning result and the second positioning result. (3) The trajectory points output by the positioning algorithm are fitted with a polynomial to obtain a curve, and the variance of the distance from the trajectory point to the fitted curve is calculated. The smoothness of the positioning is obtained based on the variance. The fault coordinates of the vehicle are recorded each time it fails due to positioning problems, and the failure rate is obtained based on the density of the fault coordinates in each grid. A positioning robustness parameter of the grid is obtained based on at least the smoothness and the failure rate.

[0094] After calculating the data for each indicator, the global map is rasterized, and the values ​​of each indicator within each grid are calculated. Each indicator is assigned a weight, and the positioning performance value of each grid is calculated. For example, each grid is assigned a different color based on the positioning performance value. This results in a quantitative value and distribution map of positioning performance.

[0095] In this embodiment, the first area where the dot grid 31 in the map is distributed meets the preset positioning performance threshold (greater than or equal to the preset positioning performance threshold), and the second area where the oblique grid 32 is distributed (due to signal obstruction by buildings) does not meet the preset positioning performance threshold (less than the preset positioning performance threshold). Positioning identifier coordinates 41 are generated on both sides of the road in the electronic map corresponding to the oblique grid 32, and each positioning identifier coordinate 41 has a preset high-precision coordinate. Subsequently, this result can be comprehensively analyzed and evaluated to provide algorithm developers with directions for algorithm optimization or environmental modification (for example, increasing the number of fixed road signs in the environment). This improves the overall algorithm performance of the port's driverless car. For example: in this example, a physical positioning identifier 42 is added to the spatial scene based on the positioning identifier coordinates 41, but this is not limited to this. In a preferred embodiment, the positioning marker coordinates 41 can be the center of the diamond block mark, and the physical positioning marker 42 is a high-reflective diamond block pattern. The high-reflective diamond block pattern has a first point a and a second point b located at both ends along the width direction of the road, and a third point c and a fourth point d located at both ends along the length direction of the road; a first connecting line is established based on the first point a and the second point b, and a second connecting line is established based on the third point c and the fourth point d. The intersection e of the first connecting line and the second connecting line is used as the centroid of the point cloud subset, and the positioning information of the centroid corresponds to the position of the positioning marker coordinates 41 in the electronic map.

[0096] The subsequent use of physical positioning marker 42 involves continuously detecting obstacles in the environment through a laser radar during vehicle operation, obtaining relevant point cloud information. Based on the high reflectivity characteristics of the highly reflective diamond pattern, points with high reflectivity are extracted from the point cloud containing ground information. Laser radar collects laser reflection points from the road surface to obtain point cloud information, which includes coordinate information and reflection intensity information in the laser radar coordinate system. Point clouds with reflection intensity information below a preset reflection threshold are filtered out to obtain a point cloud collection.

[0097] After point cloud processing is performed and the highly reflective diamond block pattern information is obtained, it needs to be segmented more accurately to facilitate the subsequent feature extraction. First, based on the reflection intensity of the point cloud, the local point cloud is roughly segmented, and a filtering operation is performed to remove outliers and noise on the surface, so that the local point cloud is as regular and complete as possible. Image segmentation is performed based on the results of point cloud clustering in the point cloud set to obtain several point cloud subsets, thereby obtaining a point cloud subset representing a highly reflective diamond block pattern. In this embodiment, the point cloud subset is identified by an existing point cloud recognition algorithm to obtain a point cloud subset representing a highly reflective diamond block pattern. It is also possible to directly perform point cloud recognition on the point cloud set to segment out a point cloud subset representing each highly reflective diamond block pattern.

[0098] Perform feature extraction, and based on the results of point cloud processing, extract the centroid of the point cloud as the center of the high-reflection diamond block pattern. The above steps realize the laser front-end function. For the point cloud subset, obtain the first point a and the second point b at both ends along the width direction of the road, and obtain the third point c and the fourth point d at both ends along the length direction of the road; establish a first connecting line based on the first point a and the second point b, and establish a second connecting line based on the third point c and the fourth point d, and use the intersection point e of the first connecting line and the second connecting line as the centroid of the point cloud subset, and project the coordinate information corresponding to the centroid in the laser radar coordinate system to the vehicle body coordinate system. Due to the special geometric structure of the high-reflection diamond block pattern, the positions of the four vertices can be easily obtained, and the position of the centroid can be obtained through the intersection point e of the lines connecting the vertices. This greatly saves the amount of calculation compared to the method that requires fitting each circular mark to obtain the centroid.

[0099] Project each centroid to the vehicle body coordinate system, and convert the point cloud information detected by the laser radar to the vehicle body coordinate system based on the external parameters from the laser radar to the vehicle body coordinate system. In closed-loop operation scenarios, such as docks, parks, etc., the characteristics of objects related to the work site are usually collected as prior information. The high-reflection diamond block pattern positioning method proposed in this article already contains its coordinate information in the global map. Subsequent vehicles are positioned using the preset high-precision coordinate information corresponding to these highly reflective diamond blocks to obtain more accurate positioning. Thereby, the second area (oblique grid 32) that does not meet the preset positioning performance threshold is changed into an area that can also be positioned with high precision, eliminating the positioning blind spot. The positioning optimization method based on the grid map of the present invention can effectively evaluate the positioning performance of each subdivided area in the port environment, and make targeted adjustments to areas with poor positioning performance.

[0100] Figure 7 Schematic diagram of the grid map-based positioning optimization system of the present invention. Figure 7 As shown, the grid map-based positioning optimization system 5 of the present invention includes:

[0101] The grid planning module 51 grids the target area.

[0102] The positioning evaluation module 52 collects reference values ​​corresponding to at least two positioning evaluation methods when at least one vehicle passes through each grid.

[0103] The weighted calculation module 53 obtains the grid positioning performance value based on the weighted calculation of each reference value of each grid.

[0104] The environment modification module 54 performs positioning environment modification on the grids whose positioning performance values ​​are lower than a preset threshold.

[0105] In a preferred embodiment, the grid planning module 51 is configured to perform grid division on the target area according to a preset grid size.

[0106] In a preferred embodiment, the positioning assessment module 52 is configured to collect driving logs of vehicles operating in the target area, and collect at least the divergence parameter, positioning accuracy parameter, and positioning robustness parameter of satellite positioning when the vehicle passes through each grid.

[0107] In a preferred embodiment, the positioning assessment module 52 is further configured to obtain the percentage of the signal state divergence period in the total time as the satellite positioning divergence parameter.

[0108] In a preferred embodiment, the positioning assessment module 52 is further configured to obtain a first positioning result when the satellite positioning is in a signal convergence state, obtain a second positioning result output by the positioning algorithm, and obtain a positioning accuracy parameter based on the error between the first positioning result and the second positioning result.

[0109] In a preferred embodiment, the positioning evaluation module 52 is further configured such that the error includes an error in the vehicle lateral information, an error in the vehicle longitudinal information, and an error in the heading angle between the first positioning result and the second positioning result.

[0110] In a preferred embodiment, the positioning assessment module 52 is further configured to perform a polynomial fit on the trajectory points output by the positioning algorithm to obtain a curve, calculate the variance of the distances from the trajectory points to the fitted curve, and determine the smoothness of the positioning based on the variance. The fault coordinates are recorded each time a vehicle fails due to positioning issues, and the failure rate is determined based on the density of the fault coordinates in each grid. A positioning robustness parameter for the grid is determined based on at least the smoothness and failure rate.

[0111] In a preferred embodiment, the weighted calculation module 53 is configured to obtain a grid positioning performance value based on a weighted calculation of each reference value of each grid.

[0112] In a preferred embodiment, the environment modification module 54 is configured to select a grid with a positioning performance value below a preset threshold as a target grid. Positioning marker coordinates are generated on both sides of the road in the electronic map corresponding to the target grid, each with preset high-precision coordinates. A physical location marker is added to the target area based on the positioning marker coordinates.

[0113] The grid map-based positioning optimization system of the present invention can effectively evaluate the positioning performance of each subdivided area in the port environment and make targeted adjustments and modifications to areas with poor positioning performance.

[0114] An embodiment of the present invention further provides a grid map-based positioning optimization device, comprising a processor and a memory storing executable instructions for the processor. The processor is configured to execute the executable instructions to perform the steps of the grid map-based positioning optimization method.

[0115] As described above, the grid map-based positioning optimization device of the present invention can effectively evaluate the positioning performance of each subdivided area in the port environment and make targeted adjustments and modifications to areas with poor positioning performance.

[0116] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods, or program products. Accordingly, various aspects of the present invention may be implemented in the following forms: entirely in hardware, entirely in software (including firmware, microcode, etc.), or in a combination of hardware and software, collectively referred to herein as "circuits," "modules," or "platforms."

[0117] Figure 8 This is a schematic diagram of the structure of the positioning optimization device based on the grid map of the present invention. Figure 8 An electronic device 600 according to this embodiment of the present invention will be described. Figure 8 The electronic device 600 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0118] like Figure 8 As shown, electronic device 600 is implemented as a general-purpose computing device. Components of electronic device 600 may include, but are not limited to, at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different platform components (including storage unit 620 and processing unit 610), and a display unit 640.

[0119] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 executes the steps according to various exemplary embodiments of the present invention described in the electronic prescription circulation processing method section of this specification. For example, the processing unit 610 can execute the following steps: Figure 1 Follow the steps shown in .

[0120] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0121] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0122] Bus 630 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0123] The electronic device 600 can also communicate with one or more external devices 700 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 600, and / or any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 650. Furthermore, the electronic device 600 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 660. The network adapter 660 can communicate with other modules of the electronic device 600 via the bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with the electronic device 600, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0124] An embodiment of the present invention further provides a computer-readable storage medium for storing a program that, when executed, implements the steps of the grid map-based positioning optimization method. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product, which includes program code. When the program product is executed on a terminal device, the program code is used to cause the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the electronic prescription circulation processing method section above.

[0125] As shown above, when the program of the computer-readable storage medium of this embodiment is executed, it can effectively evaluate the positioning performance of each subdivided area in the port environment and make targeted adjustments and modifications to areas with poor positioning performance.

[0126] Figure 9 Schematic diagram of the structure of the computer readable storage medium of the present invention. Figure 9, a program product 800 for implementing the above method according to an embodiment of the present invention is described. The program product 800 may be a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0127] The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0128] Computer-readable storage media may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the readable storage medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination thereof.

[0129] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0130] In summary, the grid map-based positioning optimization method, system, device and storage medium of the present invention can effectively evaluate the positioning performance of each subdivided area in the port environment and make targeted adjustments to areas with poor positioning performance.

[0131] The above is a further detailed description of the present invention in conjunction with specific preferred embodiments, and the specific implementation of the present invention should not be considered to be limited to these descriptions. For those skilled in the art of the present invention, without departing from the concept of the present invention, several simple deductions or substitutions can be made, which should be considered to fall within the scope of protection of the present invention.

Claims

1. A positioning optimization method based on a grid map, characterized in that: The steps include: Gridding the target area; Collecting driving logs of vehicles operating in the target area; collecting, for each grid, at least a divergence parameter, a positioning accuracy parameter, and a positioning robustness parameter of satellite positioning when the vehicle passes through the grid, including: a first positioning result obtained when the satellite positioning is in a signal convergence state; a second positioning result output by the positioning algorithm; and obtaining the positioning accuracy parameter based on an error between the first positioning result and the second positioning result; Obtaining the grid positioning performance value based on weighted calculation of each reference value of each grid; and The grid having a positioning performance value lower than a preset threshold is obtained as a target grid; positioning identifier coordinates are generated on both sides of a road in an electronic map corresponding to the target grid, each of the positioning identifier coordinates having preset high-precision coordinates; and a physical positioning identifier is added to the target area based on the positioning identifier coordinates.

2. The positioning optimization method based on grid map according to claim 1, characterized in that: The gridding of the target area includes: The target area is meshed according to the preset grid size.

3. The positioning optimization method based on grid map according to claim 1, characterized in that: The step of collecting at least a divergence parameter, a positioning accuracy parameter, and a positioning robustness parameter of satellite positioning when the vehicle passes through each grid as a unit includes: The satellite positioning includes a signal convergence state and a signal divergence state, and the percentage of the time period of the signal state divergence to the total time length is obtained as the satellite positioning divergence parameter.

4. The positioning optimization method based on grid map according to claim 1, characterized in that: The error includes an error in vehicle lateral information, an error in vehicle longitudinal information, and an error in heading angle between the first positioning result and the second positioning result.

5. The positioning optimization method based on grid map according to claim 1, characterized in that: The step of collecting at least a divergence parameter, a positioning accuracy parameter, and a positioning robustness parameter of satellite positioning when the vehicle passes through each grid as a unit includes: Perform polynomial fitting on the trajectory points output by the positioning algorithm to obtain a curve, calculate the variance of the distance from the trajectory point to the fitted curve, and obtain the smoothness of the positioning based on the variance; Record the fault coordinates each time a vehicle fails due to positioning problems, and obtain the failure rate based on the density of the fault coordinates in each grid; A positioning robustness parameter of the grid is obtained based on at least the smoothness and the failure rate.

6. A positioning optimization system based on a grid map, characterized in that: The system comprises: Grid planning module, which grids the target area; a positioning evaluation module that collects driving logs of vehicles operating in the target area; collects, for each grid cell, at least a divergence parameter, a positioning accuracy parameter, and a positioning robustness parameter of satellite positioning when the vehicle passes through the grid cell, including: a first positioning result obtained when the satellite positioning is in a signal convergence state; a second positioning result output by the positioning algorithm; and a positioning accuracy parameter obtained based on an error between the first positioning result and the second positioning result; a weighted calculation module, which obtains the grid positioning performance value based on weighted calculation of each reference value of each grid; and The environmental modification module obtains the grid whose positioning performance value is lower than a preset threshold as a target grid; generates positioning identifier coordinates on both sides of the road in the electronic map corresponding to the target grid, each of the positioning identifier coordinates having preset high-precision coordinates; and adds a physical positioning identifier to the target area based on the positioning identifier coordinates.

7. A positioning optimization device based on a grid map, characterized in that: include: processor; a memory storing executable instructions for the processor; The processor is configured to execute the steps of the grid map-based positioning optimization method according to any one of claims 1 to 5 by executing the executable instructions.

8. A computer-readable storage medium for storing a program, characterized in that: When the program is executed, the steps of the grid map-based positioning optimization method according to any one of claims 1 to 5 are implemented.

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