A hierarchical geographic fence generation method and device

Abstract

The embodiments of this specification disclose a hierarchical geo-fence generation method and device, which uses a visual map to generate a first-level geo-fence; projects the first-level geo-fence onto a roadside sensor image and performs map data fusion; starts a real-time fusion video to determine whether the first-level geo-fence matches the actual geographic location on the roadside sensor image; if not, modifies the location of the data point in the first-level geo-fence based on the roadside sensor image; and generates a second-level geo-fence based on the map data fusion result. The hierarchical geo-fence generation method and device provided in the embodiments of this specification can effectively improve the efficiency of geo-fence generation, and can adjust and customize geo-fences in real time for business scenario functions.

Description

Technical Field

[0001] The embodiments of this specification relate to the field of autonomous driving technology, and more particularly to a method and device for generating a hierarchical geo-fence. Background Art

[0002] Geo-fencing is an application of LBS (Location Based Service). It uses a virtual fence to enclose a virtual geographic boundary. When a mobile terminal enters or leaves the virtual geographic boundary, or moves within the virtual geographic boundary, it can receive social services such as automatic notifications or warnings.

[0003] The current methods for generating geofences mainly include those based on autonomous driving vehicle positioning data and those based on road image target recognition training. The main difference between the two is the different data sources. Among them, the method of drawing geofences based on autonomous driving vehicle positioning data is to receive the location data obtained by vehicles on the road through on-board positioning. The method based on road image target recognition training is based on the recognition of vehicle trajectories in a single sensor road image. The geofence is obtained through model training. The main purpose is to standardize the driving route of the autonomous driving vehicle, rather than to optimize the roadside fusion perception results. Therefore, the drawing range may deviate or be omitted from the real road. The training data set itself comes from sensor perception data, so it is not suitable for the optimization of fusion perception results. Summary of the invention

[0004] In view of this, the embodiments of the present specification provide a hierarchical geo-fence generation method and device, which are used to solve the problem in the prior art that the geo-fence range cannot be modified to meet scene requirements during the geo-fence generation process.

[0005] The embodiments of this specification adopt the following technical solutions:

[0006] The embodiment of this specification provides a hierarchical geo-fence generation method, including:

[0007] Generate first-level geofences using visual maps;

[0008] Projecting the primary geo-fence onto a roadside sensor image to perform map data fusion;

[0009] Start the real-time fusion video to determine whether the first-level geo-fence matches the actual geographic location on the roadside sensor image;

[0010] If not, modifying the location of the data point in the primary geo-fence based on the roadside sensor image;

[0011] Based on the map data fusion results, a secondary geo-fence is generated.

[0012] Furthermore, the first-level geographic fence is generated using the visual map, including:

[0013] Analyze high-precision maps and sensor location data to generate visual maps;

[0014] The first-level geo-fence is generated using the visual map.

[0015] Furthermore, the first-level geographic fence is generated using the visual map, including:

[0016] Establish multiple buffer zones using sensor sensing range information as buffer radius;

[0017] Determine the starting and ending points of the first-level geographic fence according to the intersection points of the two adjacent buffer zones and the lane boundary line of the high-precision map;

[0018] Obtaining lane line coordinate data between the starting and ending points;

[0019] The first-level geo-fence is generated based on the lane line coordinate data.

[0020] Further, generating the first-level geo-fence based on the lane line coordinate data includes:

[0021] Get sensor overlap distance information;

[0022] The first-level geo-fence is generated based on the sensor overlap distance information and the lane line coordinate data using a data thinning algorithm.

[0023] Further, projecting the primary geo-fence onto the roadside sensor image to perform map data fusion also includes:

[0024] Projecting the primary geo-fence and the high-precision map onto a roadside sensor image to evaluate a map data fusion result;

[0025] A local map of serialized data is generated based on the projection results of the first-level geographic fence and the high-precision map.

[0026] Further, starting the real-time fusion video and determining whether the first-level geo-fence matches the actual geographic location on the roadside sensor image includes:

[0027] According to the projection result of the high-precision map, start the real-time fusion video;

[0028] Determine a reference position point using the real-time fused video;

[0029] Coordinate matching of the first-level geo-fence and the high-precision map with reference position points on the roadside sensor image to obtain a matching result;

[0030] It is determined based on the matching result whether the first-level geographic fence and the high-precision map match the actual geographic location on the roadside sensor image.

[0031] Further, modifying the position of the data point in the primary geo-fence based on the roadside sensor image includes:

[0032] If the reference position point of the primary geo-fence does not match the actual geographical location of the reference position point on the roadside sensor image, pausing the real-time fused video based on the local map;

[0033] Capture an image containing the reference position point in the real-time fused video;

[0034] The locations of data points in the primary geo-fence are modified based on the image containing the reference location point and the roadside sensor image.

[0035] Furthermore, based on the map data fusion results, a secondary geo-fence is generated, including:

[0036] Obtain map data fusion results within a preset time period;

[0037] Performing kernel density analysis on the map data fusion results within the preset time period to obtain a fusion result distribution heat map;

[0038] Based on the fusion result distribution heat map, the secondary geo-fence is generated.

[0039] Furthermore, obtaining the map data fusion result within a preset time period also includes:

[0040] The map data fusion result within the preset time period is displayed in the visual map.

[0041] The embodiment of the present specification also provides a hierarchical geo-fence generation device, including:

[0042] The first-level generation module generates the first-level geo-fence using the visual map;

[0043] A fusion module projects the first-level geo-fence onto the roadside sensor image to perform map data fusion;

[0044] A matching module, which starts the real-time fusion video and determines whether the first-level geo-fence matches the actual geographic location on the roadside sensor image;

[0045] a modification module, if not, modifying the location of the data point in the primary geo-fence based on the roadside sensor image;

[0046] The secondary generation module generates secondary geo-fences based on the map data fusion results.

[0047] At least one of the above technical solutions adopted in the embodiments of this specification can achieve the following beneficial effects:

[0048] A first-level geofence is generated using a visual map. The first-level geofence is projected onto the roadside sensor image to perform map data fusion. During the fusion process, real-time fusion video is turned on to determine whether the first-level geofence matches the actual geographic location on the roadside sensor image. If not, the position of the data point in the first-level geofence is modified based on the roadside sensor image, and a second-level geofence is generated based on the map data fusion result.

[0049] In this way, in the process of generating geo-fences, by projecting the first-level geo-fence onto the roadside sensor image and matching the actual geographic location, the location of the first-level geo-fence data point can be modified in real time, and the second-level geo-fence can be generated based on the map data fusion result as a reference for the credibility of the fusion result. This can effectively improve the efficiency of geo-fence generation, and the geo-fence can be adjusted and customized in real time according to business scenario functions. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] The drawings described herein are used to provide a further understanding of the embodiments of this specification and constitute a part of the embodiments of this specification. The illustrative embodiments of this specification and their descriptions are used to explain this application and do not constitute an improper limitation on this application. In the drawings:

[0051] Figure 1 A schematic diagram of a system architecture of an exemplary application environment of a hierarchical geo-fence generation method and device provided in an embodiment of this specification;

[0052] Figure 2 A flowchart of a hierarchical geo-fence generation method provided in an embodiment of this specification;

[0053] Figure 3 A schematic diagram of the structure of a hierarchical geographic fence generation device provided in an embodiment of this specification. DETAILED DESCRIPTION

[0054] In the existing technology, in the process of drawing geographic fences, GNSS (Global Navigation Satellite System) is mostly used as the core position reference for data collection, processing and fence judgment. It is impossible to temporarily customize the scope of the geographic fence according to the needs of the actual application scenario functions on the roadside, nor is it suitable for the optimization of fusion perception results.

[0055] Therefore, the embodiments of the present specification provide a hierarchical geo-fence generation method and device. In the process of generating a geo-fence, a first-level geo-fence is generated using a visual map. The first-level geo-fence is projected onto a roadside sensor image to match the actual geographic location, so that the location of the first-level geo-fence data point can be modified in real time. A second-level geo-fence is generated based on the map data fusion result as a reference for the credibility of the fusion result. This can effectively improve the efficiency of geo-fence generation, and can adjust and customize the geo-fence in real time for business scenario functions.

[0056] In order to make the purpose, technical solution and advantages of this application clearer, the technical solution of this application will be clearly and completely described below in conjunction with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0057] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0058] like Figure 1 , which is a schematic diagram of a system architecture of an exemplary application environment to which the embodiments of the present specification can be applied.

[0059] The system architecture may include at least one of the terminal devices 101, the network 102 and the server 103. The network 102 is a medium for providing a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc. The terminal device 101 may be various electronic devices with a display screen, and various APPs or browsers are installed on the terminal device 101.

[0060] The terminal device 101 includes but is not limited to portable computers, smart phones, tablet computers and other devices with display functions. It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. According to the implementation requirements, there may be any number of terminal devices, networks and servers. For example, the server 103 may be a server cluster composed of multiple servers.

[0061] During the actual operation of the terminal device 101 , the server 103 can monitor the process operation status on the terminal device 101 and obtain wireless data information, etc.

[0062] It is easy for those skilled in the art to understand that, in the solution regarding geo-fences provided in the embodiments of this specification, the terminal device 101 belongs to the geo-fence application end, which can deploy automatic wireless signal collection tools and has small batch data storage and processing capabilities; the server 103 can perform big data storage and processing, and can manage and update all geo-fences.

[0063] Based on the above architecture, the solution of this specification is described in detail below.

[0064] like Figure 2 The figure is a flow chart of a hierarchical geo-fence generation method provided in an embodiment of the present specification.

[0065] The hierarchical geo-fence generation method may specifically include the following steps:

[0066] S201: Generate a first-level geographic fence using a visual map;

[0067] S202: Projecting the first-level geo-fence onto the roadside sensor image to perform map data fusion;

[0068] S203: Start the real-time fusion video to determine whether the first-level geo-fence matches the actual geographic location on the roadside sensor image;

[0069] S204: If not, modifying the position of the data point in the primary geo-fence based on the roadside sensor image;

[0070] S205: Generate a secondary geographic fence based on the map data fusion result.

[0071] In the embodiment of this specification, in step S201, generating a first-level geographic fence using a visual map may specifically include:

[0072] Analyze high-precision maps and sensor location data to generate visual maps;

[0073] The first-level geo-fence is generated using the visual map.

[0074] Specifically, GIS auxiliary business software can be used to parse high-precision maps and sensor location data to generate visual maps. Among them, sensor location data can be obtained by RTK measurement, and WGS84 is used as the reference coordinate system in accordance with high-precision map data. The data accuracy of high-precision maps and sensor location data is high, and can be used as a true value reference for map data fusion results.

[0075] GIS (Geographical Information System) is a technology that uses computer technology systems to abstract, store, and visualize geographic space by building geographic models, thereby studying and analyzing real-time or post-event, static or dynamic spatial geographic information.

[0076] RTK (Real-time kinematic) measurement refers to real-time dynamic measurement technology, which is a real-time differential GPS (RTDGPS) technology based on carrier phase observation. It can be composed of three parts: base station receiver, data link, and mobile station receiver.

[0077] In a specific application embodiment, generating a first-level geographic fence using a visual map may include:

[0078] Establish multiple buffer zones using sensor sensing range information as buffer radius;

[0079] Determine the starting and ending points of the first-level geographic fence according to the intersection points of the two adjacent buffer zones and the lane boundary line of the high-precision map;

[0080] Obtaining lane line coordinate data between the starting and ending points;

[0081] The first-level geo-fence is generated based on the lane line coordinate data.

[0082] Among them, the sensor perception range information generally refers to the distance range data that the sensor can perceive, and specifically can be the distance range that the roadside equipment sensor can perceive. In the embodiment of this specification, the deployment location of each sensor is known, and specifically the distance between two adjacent sensors can be used as the sensor perception range information, which is smaller than the actual perception range of the sensor, making the sensor data more accurate.

[0083] Specifically, the location where each sensor is deployed may be a GPS coordinate, which may be converted into a point layer of a high-precision map, generally referred to as an RCU point or pole.

[0084] By using the sensor perception range information as the buffer radius, there is an overlapping range between two adjacent buffers, so that the starting and ending points of the first-level geographic fence can be determined according to the intersection of the two adjacent buffers and the lane boundary line of the high-precision map, and then the lane line coordinate data between the starting and ending points can be obtained, so as to generate a first-level geographic fence.

[0085] In actual application scenarios, there are non-straight areas. In these non-straight areas, if the sensor positions are arranged according to the standards of straight areas, there will be certain deviations in the sensor perception range information. In this case, the density of roadside sensors in non-straight areas can be increased, thereby ensuring that non-straight areas are covered by the perception range of roadside sensors, which can effectively reduce the sensor data error with straight areas.

[0086] Further, generating the first-level geo-fence based on the lane line coordinate data may include:

[0087] Get sensor overlap distance information;

[0088] The first-level geo-fence is generated based on the sensor overlap distance information and the lane line coordinate data using a data thinning algorithm.

[0089] Since the fusion perception between the roadside equipment sensors requires a certain overlap between the two perception areas in order to correct the fusion result, and the sensor has a certain perception blind spot, in the embodiment of this specification, the perception overlap range between two adjacent roadside sensors is used as the overlapping distance information, so that the geographic fences corresponding to adjacent RCU points have a customized overlapping range, and can be optimized and adjusted based on the actual fusion effect.

[0090] The data thinning algorithm may specifically be implemented using the Douglas Peucker algorithm or the vertical distance method.

[0091] In the embodiment of this specification, projecting the primary geo-fence onto the roadside sensor image and performing map data fusion may also include:

[0092] Projecting the primary geo-fence and the high-precision map onto a roadside sensor image to evaluate a map data fusion result;

[0093] A local map of serialized data is generated based on the projection results of the first-level geographic fence and the high-precision map.

[0094] Since data errors may exist in the generation process of the first-level geo-fence, in the embodiment of this specification, the accuracy of the first-level geo-fence is checked by matching the coordinates of the first-level geo-fence with the reference position points on the roadside sensor image.

[0095] Specifically, the first-level geographic fence and the high-precision map can be projected onto the roadside sensor image to perform map data fusion, wherein the high-precision map is projected onto the roadside sensor image to visualize the map data fusion process.

[0096] In the embodiment of the present specification, starting the real-time fusion video and determining whether the first-level geo-fence matches the actual geographic location on the roadside sensor image may include:

[0097] According to the projection result of the high-precision map, start the real-time fusion video;

[0098] Determine a reference position point using the real-time fused video;

[0099] Coordinate matching of the first-level geo-fence and the high-precision map with reference position points on the roadside sensor image to obtain a matching result;

[0100] It is determined based on the matching result whether the first-level geographic fence and the high-precision map match the actual geographic location on the roadside sensor image.

[0101] By projecting the high-precision map onto the roadside sensor image, the map data fusion process can be visualized. In this way, real-time fusion video can be turned on during the map data fusion process to observe in real time whether the location points on the first-level geographic fence and the high-precision map match the actual geographic location on the roadside sensor image.

[0102] In an embodiment of the present specification, the reference location point may be a location point randomly selected based on the real-time fused video. To improve fusion efficiency, a location point on the first-level geographic fence and the high-precision map that does not overlap with the actual geographic location on the roadside sensor image may be selected as a reference location point.

[0103] Furthermore, it is possible to determine whether the first-level geofence and the reference location points on the high-precision map match the actual geographic location on the roadside sensor image by matching the coordinates of the first-level geofence and the reference location points on the high-precision map with the actual geographic location on the roadside sensor image.

[0104] Further, modifying the location of the data point in the primary geo-fence based on the roadside sensor image may include:

[0105] If the reference position point of the primary geo-fence does not match the actual geographical location of the reference position point on the roadside sensor image, pausing the real-time fused video based on the local map;

[0106] Capture an image containing the reference position point in the real-time fused video;

[0107] The locations of data points in the primary geo-fence are modified based on the image containing the reference location point and the roadside sensor image.

[0108] If the reference location points on the first-level geofence and the high-precision map do not match the actual geographic location on the roadside sensor image, the image containing the reference location points in the real-time fusion video can be captured and combined with the roadside sensor image to modify the position of the corresponding data point in the first-level geofence, specifically by modifying the coordinate location data.

[0109] The modified first-level geofence will be stored in the database and the configuration file will be regenerated, and will participate in the subsequent real-time map data fusion.

[0110] In the embodiment of the present specification, generating a secondary geo-fence based on the map data fusion result may include:

[0111] Obtain map data fusion results within a preset time period;

[0112] Performing kernel density analysis on the map data fusion results within the preset time period to obtain a fusion result distribution heat map;

[0113] Based on the fusion result distribution heat map, the secondary geo-fence is generated.

[0114] Kernel density analysis is a method of converting a set of point features (vector data) into raster data. It is mainly used to calculate the density of features in their surrounding neighborhoods. The role of kernel density is to use a kernel function to calculate the value of the unit area based on point or polyline features to fit each point or polyline into a smooth conical surface.

[0115] Based on the fusion result distribution heat map, the secondary geo-fence is generated. Specifically, an appropriate density range is selected based on the fusion result distribution heat map to obtain the secondary geo-fence, which can be provided to the fusion perception algorithm as a reference for the credibility of the vehicle's running trajectory.

[0116] Furthermore, obtaining the map data fusion result within a preset time period may also include:

[0117] The map data fusion result within the preset time period is displayed in the visual map.

[0118] In the embodiments of the present specification, the map data fusion results within a preset time period can be visualized in the GIS tool software.

[0119] A hierarchical geo-fence generation method provided in an embodiment of the present specification utilizes a visualized map to generate a first-level geo-fence, and performs map data fusion by projecting the first-level geo-fence onto a roadside sensor image. During the fusion process, real-time fusion video is turned on to determine whether the first-level geo-fence matches the actual geographic location on the roadside sensor image. If not, the position of the data point in the first-level geo-fence is modified based on the roadside sensor image, and a second-level geo-fence is generated based on the map data fusion result.

[0120] In this way, in the process of generating geo-fences, by projecting the first-level geo-fence onto the roadside sensor image and matching the actual geographic location, the location of the first-level geo-fence data point can be modified in real time, and the second-level geo-fence can be generated based on the map data fusion result as a reference for the credibility of the fusion result. This can effectively improve the efficiency of geo-fence generation, and the geo-fence can be adjusted and customized in real time according to business scenario functions.

[0121] Based on the same inventive concept, the embodiment of this specification provides a hierarchical geographic fence generation device. Figure 3 The figure is a schematic diagram of the structure of the hierarchical geographic fence generation device provided in the embodiment of this specification.

[0122] The hierarchical geo-fence generation device provided in the embodiments of this specification may specifically include:

[0123] A first-level generation module 301 generates a first-level geo-fence using a visual map;

[0124] A fusion module 302 projects the primary geo-fence onto a roadside sensor image to perform map data fusion;

[0125] The matching module 303 starts the real-time fusion video and determines whether the first-level geo-fence matches the actual geographic location on the roadside sensor image;

[0126] The modification module 304 modifies the location of the data point in the primary geo-fence based on the roadside sensor image if no;

[0127] The secondary generation module 305 generates a secondary geographic fence based on the map data fusion result.

[0128] Furthermore, the generation of a first-level geographic fence using a visual map may include:

[0129] Analyze high-precision maps and sensor location data to generate visual maps;

[0130] The first-level geo-fence is generated using the visual map.

[0131] Furthermore, the generation of a first-level geographic fence using a visual map may include:

[0132] Establish multiple buffer zones using sensor sensing range information as buffer radius;

[0133] Determine the starting and ending points of the first-level geographic fence according to the intersection points of the two adjacent buffer zones and the lane boundary line of the high-precision map;

[0134] Obtaining lane line coordinate data between the starting and ending points;

[0135] The first-level geo-fence is generated based on the lane line coordinate data.

[0136] Further, generating the first-level geo-fence based on the lane line coordinate data may include:

[0137] Get sensor overlap distance information;

[0138] The first-level geo-fence is generated based on the sensor overlap distance information and the lane line coordinate data using a data thinning algorithm.

[0139] Furthermore, projecting the primary geo-fence onto the roadside sensor image to perform map data fusion may also include:

[0140] Projecting the primary geo-fence and the high-precision map onto a roadside sensor image to evaluate a map data fusion result;

[0141] A local map of serialized data is generated based on the projection results of the first-level geographic fence and the high-precision map.

[0142] Further, starting the real-time fusion video and determining whether the first-level geo-fence matches the actual geographic location on the roadside sensor image may include:

[0143] According to the projection result of the high-precision map, start the real-time fusion video;

[0144] Determine a reference position point using the real-time fused video;

[0145] Coordinate matching of the first-level geo-fence and the high-precision map with reference position points on the roadside sensor image to obtain a matching result;

[0146] It is determined based on the matching result whether the first-level geographic fence and the high-precision map match the actual geographic location on the roadside sensor image.

[0147] Further, modifying the location of the data point in the primary geo-fence based on the roadside sensor image may include:

[0148] If the reference position point of the primary geo-fence does not match the actual geographical location of the reference position point on the roadside sensor image, pausing the real-time fused video based on the local map;

[0149] Capture an image containing the reference position point in the real-time fused video;

[0150] The locations of data points in the primary geo-fence are modified based on the image containing the reference location point and the roadside sensor image.

[0151] Furthermore, based on the map data fusion result, a secondary geo-fence is generated, which may include:

[0152] Obtain map data fusion results within a preset time period;

[0153] Performing kernel density analysis on the map data fusion results within the preset time period to obtain a fusion result distribution heat map;

[0154] Based on the fusion result distribution heat map, the secondary geo-fence is generated.

[0155] Furthermore, obtaining the map data fusion result within a preset time period may also include:

[0156] The map data fusion result within the preset time period is displayed in the visual map.

[0157] A hierarchical geo-fence generation device provided in an embodiment of the present specification uses a visual map to generate a first-level geo-fence, and performs map data fusion by projecting the first-level geo-fence onto a roadside sensor image. During the fusion process, real-time fusion video is turned on to determine whether the first-level geo-fence matches the actual geographic location on the roadside sensor image. If not, the position of the data point in the first-level geo-fence is modified based on the roadside sensor image, and a second-level geo-fence is generated based on the map data fusion result.

[0158] In this way, in the process of generating geo-fences, by projecting the first-level geo-fence onto the roadside sensor image and matching the actual geographic location, the location of the first-level geo-fence data point can be modified in real time, and the second-level geo-fence can be generated based on the map data fusion result as a reference for the credibility of the fusion result. This can effectively improve the efficiency of geo-fence generation, and the geo-fence can be adjusted and customized in real time according to business scenario functions.

[0159] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0160] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, electronic device, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0161] The apparatus, electronic device, non-volatile computer storage medium and method provided in the embodiments of this specification correspond to each other, and therefore, the apparatus, electronic device and non-volatile computer storage medium also have similar beneficial technical effects as the corresponding method. Since the beneficial technical effects of the method have been described in detail above, the beneficial technical effects of the corresponding apparatus, electronic device and non-volatile computer storage medium will not be repeated here.

[0162] In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (for example, improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with a hardware entity module. For example, a programmable logic device (PLD) (for example, a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0163] The controller can be implemented in any appropriate manner, for example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (such as software or firmware) that can be executed by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art also know that in addition to implementing the controller in a purely computer-readable program code manner, the controller can be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, this controller can be considered as a hardware component, and the devices included therein for implementing various functions can also be regarded as structures within the hardware component. Or even, the devices for implementing various functions can be regarded as both software modules for implementing the method and structures within the hardware component.

[0164] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0165] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing the present application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0166] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0167] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0168] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0169] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0170] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0171] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0172] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0173] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0174] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0175] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0176] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of protection of the claims of the present application.

Claims

1. A hierarchical geo-fence generation method, characterized in that: include: Generate first-level geofences using visual maps; Projecting the primary geo-fence onto a roadside sensor image to perform map data fusion; Start the real-time fusion video to determine whether the first-level geo-fence matches the actual geographic location on the roadside sensor image; If not, modifying the location of the data point in the primary geo-fence based on the roadside sensor image; Generate secondary geo-fences based on the map data fusion results; The method of projecting the first-level geofence onto the roadside sensor image to perform map data fusion also includes: projecting the first-level geofence and the high-precision map onto the roadside sensor image to evaluate the map data fusion result; generating a local map of serialized data based on the projection results of the first-level geofence and the high-precision map; Turn on the real-time fusion video to determine whether the first-level geo-fence matches the actual geographical location on the roadside sensor image, including: turning on the real-time fusion video according to the projection result of the high-precision map; using the real-time fusion video to determine the reference position point; matching the coordinates of the first-level geo-fence and the high-precision map with the reference position point on the roadside sensor image to obtain a matching result; judging whether the first-level geo-fence and the high-precision map match the actual geographical location on the roadside sensor image according to the matching result; Modifying the position of the data point in the first-level geo-fence based on the roadside sensor image includes: if the reference position point of the first-level geo-fence does not match the actual geographical location of the reference position point on the roadside sensor image, pausing the real-time fusion video based on the local map; capturing the image containing the reference position point in the real-time fusion video; and modifying the position of the data point in the first-level geo-fence based on the image containing the reference position point and the roadside sensor image.

2. The method according to claim 1, characterized in that Generate first-level geofences using a visual map, including: Analyze high-precision maps and sensor location data to generate visual maps; The first-level geo-fence is generated using the visual map.

3. The method according to claim 1, characterized in that Generate first-level geofences using a visual map, including: Establish multiple buffer zones using sensor sensing range information as buffer radius; Determine the starting and ending points of the first-level geographic fence according to the intersection points of the two adjacent buffer zones and the lane boundary line of the high-precision map; Obtaining lane line coordinate data between the starting and ending points; The first-level geo-fence is generated based on the lane line coordinate data.

4. The method according to claim 3, characterized in that Generating the first-level geo-fence based on the lane line coordinate data includes: Get sensor overlap distance information; The first-level geo-fence is generated based on the sensor overlap distance information and the lane line coordinate data using a data thinning algorithm.

5. The method according to claim 1, characterized in that Based on the map data fusion results, a secondary geo-fence is generated, including: Obtain map data fusion results within a preset time period; Performing kernel density analysis on the map data fusion results within the preset time period to obtain a fusion result distribution heat map; Based on the fusion result distribution heat map, the secondary geo-fence is generated.

6. The method according to claim 5, characterized in that Obtaining the map data fusion results within a preset time period also includes: The map data fusion result within the preset time period is displayed in the visual map.

7. A hierarchical geo-fence generation device, characterized in that: include: The first-level generation module generates the first-level geo-fence using the visual map; A fusion module projects the first-level geo-fence onto the roadside sensor image to perform map data fusion; A matching module, which starts the real-time fusion video and determines whether the first-level geo-fence matches the actual geographic location on the roadside sensor image; a modification module, if not, modifying the location of the data point in the primary geo-fence based on the roadside sensor image; The secondary generation module generates secondary geo-fences based on the map data fusion results; The method of projecting the first-level geofence onto the roadside sensor image to perform map data fusion also includes: projecting the first-level geofence and the high-precision map onto the roadside sensor image to evaluate the map data fusion result; generating a local map of serialized data based on the projection results of the first-level geofence and the high-precision map; Turn on the real-time fusion video to determine whether the first-level geo-fence matches the actual geographical location on the roadside sensor image, including: turning on the real-time fusion video according to the projection result of the high-precision map; using the real-time fusion video to determine the reference position point; matching the coordinates of the first-level geo-fence and the high-precision map with the reference position point on the roadside sensor image to obtain a matching result; judging whether the first-level geo-fence and the high-precision map match the actual geographical location on the roadside sensor image according to the matching result; Modifying the position of the data point in the first-level geo-fence based on the roadside sensor image includes: if the reference position point of the first-level geo-fence does not match the actual geographical location of the reference position point on the roadside sensor image, pausing the real-time fusion video based on the local map; capturing the image containing the reference position point in the real-time fusion video; and modifying the position of the data point in the first-level geo-fence based on the image containing the reference position point and the roadside sensor image.

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