CN114758083A

CN114758083A - Layered geo-fence generation method and device

Info

Publication number: CN114758083A
Application number: CN202210399096.8A
Authority: CN
Inventors: 于含章; 张丽娟; 陈亚卿; 杨轩
Original assignee: Yunkong Zhixing Technology Co Ltd
Current assignee: Yunkong Zhixing Technology Co Ltd
Priority date: 2022-04-15
Filing date: 2022-04-15
Publication date: 2022-07-15

Abstract

The embodiment of the specification discloses a hierarchical geo-fence generation method and a hierarchical geo-fence generation device, wherein a first-level geo-fence is generated by utilizing a visual map; projecting the primary geo-fence onto a roadside sensor image for map data fusion; starting a real-time fusion video, and judging whether the primary geo-fence is matched with the actual geographic position on the image of the roadside sensor; if not, modifying the position of the data point in the primary geo-fence based on the roadside sensor image; and generating a secondary geo-fence based on the map data fusion result. The method and the device for generating the hierarchical geofence provided by the embodiment of the present specification can effectively improve the generation efficiency of the geofence, and can adjust and customize the geofence in real time according to the service scenario function.

Description

Layered geo-fence generation method and device

Technical Field

The embodiment of the specification relates to the technical field of automatic driving, in particular to a hierarchical geofence generation method and device.

Background

Geo-fencing is an application of Location Based Service (LBS) that uses a virtual fence to enclose a virtual geographic boundary and can receive social services such as automatic notification or warning when a mobile terminal enters or leaves the virtual geographic boundary or is active within the virtual geographic boundary.

The current geo-fence generation methods mainly include methods based on automatic driving vehicle positioning data, target identification training based on road condition images and the like, and the main difference between the methods is that the data sources are different. The method for drawing the geo-fence based on the automatic driving vehicle positioning data comprises the step of receiving position data obtained by vehicle-mounted positioning of vehicles on a road. The object recognition training based on the road condition images is based on vehicle track recognition in the single sensor road condition images, the geo-fences are obtained through model training, the driving route of the automatic driving vehicle is standardized, and optimization of the road side fusion sensing result is not aimed at, so that deviation or omission of the drawing range of the geo-fences relative to a real road may occur, and the training data set is derived from sensor sensing data, so that the geo-fences are not suitable for optimization of the fusion sensing result.

Disclosure of Invention

In view of this, embodiments of the present disclosure provide a method and an apparatus for generating a hierarchical geofence, so as to solve the problem in the prior art that a geofence range cannot be modified in response to a scene requirement in a geofence generation process.

The embodiment of the specification adopts the following technical scheme:

an embodiment of the present specification provides a hierarchical geofence generation method, including:

generating a primary geo-fence using the visual map;

projecting the primary geo-fence onto a roadside sensor image for map data fusion;

starting a real-time fusion video, and judging whether the primary geo-fence is matched with the actual geographic position on the image of the roadside sensor;

if not, modifying the position of the data point in the primary geo-fence based on the roadside sensor image;

and generating a secondary geo-fence based on the map data fusion result.

Further, generating a primary geofence using the visual map, comprising:

analyzing the high-precision map and the sensor position data to generate a visual map;

generating the primary geofence using the visual map.

Further, generating a primary geofence using the visual map, comprising:

establishing a plurality of buffer areas by taking the information of the sensing range of the sensor as the buffer radius;

determining a start point and a stop point of the primary geo-fence according to intersection points of lane boundary lines of two adjacent buffer areas and a high-precision map;

acquiring lane line coordinate data between the start and stop points;

generating the primary geofence based on the lane line coordinate data.

Further, generating the primary geofence based on the lane line coordinate data, comprising:

acquiring overlapping distance information of the sensors;

and generating the primary geo-fence based on the sensor overlapping distance information and the lane line coordinate data by using a data thinning algorithm.

Further, projecting the primary geo-fence onto a roadside sensor image for map data fusion, further comprising:

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

and generating a local map of the serialized data according to the projection results of the primary geo-fence and the high-precision map.

Further, starting a real-time fusion video, and judging whether the primary geo-fence is matched with the actual geographic position on the roadside sensor image, including:

starting a real-time fusion video according to the projection result of the high-precision map;

determining a reference position point by using the real-time fusion video;

coordinate matching is carried out on the primary geo-fence and the high-precision map and a reference position point on the roadside sensor image to obtain a matching result;

and judging whether the primary geo-fence and the high-precision map are matched with the actual geographic position on the roadside sensor image according to the matching result.

Further, modifying the location of data points in the primary geofence based on the roadside sensor image, including:

if the reference position point of the primary geo-fence is not matched with the actual geographic position of the reference position point on the image of the road side sensor, suspending the real-time fusion video based on the local map;

capturing an image containing the reference position point in the real-time fusion video;

modifying the location of the data points in the primary geofence based on the image containing the reference location point and the roadside sensor image.

Further, generating a secondary geo-fence based on the map data fusion result, comprising:

acquiring a map data fusion result in a preset time period;

performing nuclear density analysis on the map data fusion result in the preset time period to obtain a fusion result distribution thermodynamic diagram;

generating the secondary geofence based on the fusion result distribution thermodynamic diagram.

Further, obtaining a map data fusion result in a preset time period further includes:

and displaying the map data fusion result in the preset time period in the visual map.

An embodiment of the present specification further provides a hierarchical geofence generation apparatus, including:

the first-level generation module is used for generating a first-level geographic fence by utilizing the visual map;

the fusion module is used for projecting the primary geo-fence onto a roadside sensor image to perform map data fusion;

the matching module starts the real-time fusion video and judges whether the primary geo-fence is matched with the actual geographic position on the image of the roadside sensor;

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

and the secondary generation module generates a secondary geo-fence based on the map data fusion result.

The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:

the method comprises the steps of generating a primary geo-fence by using a visual map, carrying out map data fusion by projecting the primary geo-fence onto a roadside sensor image, starting a real-time fusion video in the fusion process to judge whether the actual geographic positions of the primary geo-fence and the roadside sensor image are matched, modifying the positions of data points in the primary geo-fence based on the roadside sensor image if the actual geographic positions of the primary geo-fence and the roadside sensor image are not matched, and generating a secondary geo-fence based on a map data fusion result.

Therefore, in the process of generating the geo-fence, the primary geo-fence is projected onto the roadside sensor image to be matched with the actual geo-position, so that the position of the primary geo-fence data point can be modified in real time, the secondary geo-fence is generated based on the map data fusion result and used as a reference for the reliability of the fusion result, the generation efficiency of the geo-fence can be effectively improved, and the geo-fence can be adjusted in real time and customized according to the service scene function.

Drawings

The accompanying drawings, which are included to provide a further understanding of the embodiments of the specification and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the specification and together with the description serve to explain the application and not to limit the application. In the drawings:

fig. 1 is a schematic diagram of a system architecture of an exemplary application environment of a hierarchical geofence generation method and apparatus provided in an embodiment of the present specification;

fig. 2 is a flowchart illustrating a method for generating a hierarchical geofence provided by an embodiment of the present disclosure;

fig. 3 is a schematic structural diagram of a hierarchical geofence generating apparatus provided in an embodiment of this specification.

Detailed Description

In the prior art, in the process of drawing the geofence, a Global Navigation Satellite System (GNSS) is mostly used as a core position reference for data collection, processing and fence judgment, and the range of the geofence cannot be temporarily customized according to the requirement of roadside practical application scene functions, and the method is also not suitable for optimization of fusion perception results.

Therefore, in the process of generating the geo-fence, a primary geo-fence is generated by using a visual map, the primary geo-fence is projected onto a roadside sensor image to match an actual geographic position, so that the position of the data point of the primary geo-fence can be modified in real time, a secondary geo-fence is generated based on a map data fusion result and used as a reference of the reliability of the fusion result, the generation efficiency of the geo-fence can be effectively improved, and the geo-fence can be adjusted in real time and customized according to a service scene function.

In order to make the objects, technical solutions and advantages of the present application more clear, the technical solutions of the present application will be clearly and completely described below with reference to the specific embodiments of the present specification and the accompanying drawings. It is to be understood that the embodiments described are only a few embodiments of the present disclosure, and not all embodiments. All other embodiments obtained by a person skilled in the art based on the embodiments in the present specification without any inventive step are within the scope of the present application.

The technical solutions provided by the embodiments of the present description are described in detail below with reference to the accompanying drawings.

As shown in fig. 1, a schematic diagram of a system architecture of an exemplary application environment to which embodiments of the present specification may be applied is shown.

The system architecture may include, among other things, at least one of terminal devices 101, a network 102, and a server 103. Network 102 is a medium for providing a communication link between terminal device 101 and server 103. Network 102 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few. The terminal device 101 may be various electronic devices having a display screen, and various APPs or browsers are installed on the terminal device 101.

The terminal device 101 includes, but is not limited to, a portable computer, a smart phone, a tablet computer, and other devices having a display function. It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. For example, the server 103 may be a server cluster composed of a plurality of servers.

During the actual operation of the terminal device 101, the server 103 may monitor the process operation condition on the terminal device 101, and obtain the wireless data information and the like.

As will be readily understood by those skilled in the art, in the solution provided in the embodiment of the present disclosure regarding a geofence, the terminal device 101 belongs to a geofence application end, and may deploy an automatic wireless signal acquisition tool, while having a small-batch data storage and processing capability; server 103 can then do big data storage and processing and can manage and update all geofences.

Based on the above-described architecture, the following describes a scheme of the present specification in detail.

Fig. 2 is a schematic flow chart of a hierarchical geofence generation method provided for an embodiment of the present specification.

The hierarchical geofence generation method may specifically include the following steps:

s201: generating a primary geo-fence using the visual map;

s202: projecting the primary geo-fence onto a roadside sensor image for map data fusion;

s203: starting a real-time fusion video, and judging whether the primary geo-fence is matched with the actual geographic position on the image of the roadside sensor;

s204: if not, modifying the position of the data point in the primary geo-fence based on the roadside sensor image;

s205: and generating a secondary geo-fence based on the map data fusion result.

In an embodiment of this specification, in the step S201, generating a primary geo-fence by using a visual map may specifically include:

generating the primary geofence using the visual map.

Specifically, GIS auxiliary service software can be used for analyzing the high-precision map and the sensor position data to generate a visual map. The sensor position data can be obtained by RTK measurement, and is consistent with the high-precision map data, the WGS84 is used as a reference coordinate system, the data precision of the high-precision map and the sensor position data is high, and the sensor position data can be used as a true value reference of a map data fusion result.

A Geographic Information System (GIS) is a technology for abstracting, storing, and visualizing a geographic space by establishing a geographic model through a computer technology System, thereby researching and analyzing real-time or post-trip, static, or dynamic spatial geographic Information.

An RTK (Real-time kinematic) measurement refers to a Real-time dynamic measurement technique, which is a Real-time differential gps (rtdgps) technique based on carrier phase observation, and may be composed of a reference station receiver, a data chain, and a rover receiver.

In a specific application embodiment, generating the primary geo-fence using the visual map may include:

establishing a plurality of buffer areas by taking the sensor sensing range information as a buffer radius;

determining the starting point and the ending point of the primary geo-fence according to the intersection point of the lane boundary lines of two adjacent buffer areas and a high-precision map;

acquiring coordinate data of the lane lines between the start points and the stop points;

generating the primary geofence based on the lane line coordinate data.

In this embodiment of the present specification, the position where each sensor is deployed is known, and specifically, the distance between two adjacent sensors may be used as sensor sensing range information, which is smaller than the actual sensing range of the sensor, so that the sensor data is more accurate.

In particular, the location of each sensor deployment may specifically be GPS coordinates that may be translated into a point map layer of a high precision map, commonly referred to as an RCU point location or pole.

By taking the sensor perception range information as the radius of the buffer areas, the overlapping range is formed between every two adjacent buffer areas, so that the start and stop points of the first-level geo-fence can be determined according to the intersection points of the two adjacent buffer areas and the lane boundary line of the high-precision map, the lane line coordinate data between the start and stop points can be acquired, and the first-level geo-fence can be generated according to the lane line coordinate data.

In an actual application scene, non-straight road regions exist, and in the non-straight road regions, if the sensor positions are arranged according to the standard of the straight road regions, certain deviation exists in the sensor sensing range information.

Further, generating the primary geofence based on the lane line coordinate data may include:

acquiring overlapping distance information of the sensors;

and generating the primary geo-fence based on the sensor overlap distance information and the lane line coordinate data by using a data thinning algorithm.

Because two perception areas of the integration perception demand between the trackside roadside device sensors have certain overlap, thereby revise the integration result, and the sensor has certain perception blind area, so, in this specification embodiment, regard the perception overlap range between two adjacent trackside sensors as overlap distance information, make the geofence that adjacent RCU position is corresponding have a self-defined section of overlap range, and can optimize the adjustment based on the effect of fusing of reality.

The data thinning algorithm may specifically be performed by using a douglas pock algorithm or a sag method.

In an embodiment of this specification, projecting the primary geo-fence onto a roadside sensor image for map data fusion may further include:

Since the primary geofence may have data errors during the generation process, in the embodiments of the present description, the primary geofence is coordinate-matched to a reference location point on the roadside sensor image to determine whether the primary geofence is accurate.

Specifically, the primary geo-fence and the high-precision map may be projected onto the roadside sensor image to perform fusion of the map data, where the projection of the high-precision map onto the roadside sensor image is to perform visualization of the map data fusion process.

In an embodiment of the present description, starting a real-time fusion video, and determining whether the first-stage geo-fence is matched with an actual geographic location on the roadside sensor image may include:

determining a reference position point by using the real-time fusion video;

performing coordinate matching on the primary geo-fence, the high-precision map and a reference position point on the roadside sensor image to obtain a matching result;

The high-precision map is projected onto the roadside sensor image, visualization of the map data fusion process is achieved, and therefore the real-time fusion video can be started in the map data fusion process, and whether the position points on the first-level geo-fence and the high-precision map are matched with the actual geographic position on the roadside sensor image or not can be observed in real time.

In this specification, the reference position point may be a position point randomly selected according to a real-time fusion video, and in order to improve the fusion efficiency, a position point on the primary geo-fence and the high-precision map and a position point on the roadside sensor image that is not coincident with the actual geo-position may be selected as the reference position point.

And further, whether the reference position points on the primary geo-fence and the high-precision map are matched with the actual geographic position on the roadside sensor image or not can be determined by carrying out coordinate matching on the reference position points on the primary geo-fence and the high-precision map and the actual geographic position on the roadside sensor image.

Further, modifying the location of the data points in the primary geofence based on the roadside sensor image may include:

If the reference position point on the primary geo-fence and the high-precision map is not matched with the actual geographic position on the roadside sensor image, an image containing the reference position point in the real-time fusion video can be captured, and the position of the corresponding data point in the primary geo-fence is modified by combining the roadside sensor image, specifically, coordinate position data can be modified.

The modified primary geofence is stored in a database and regenerated into a configuration file, and participates in subsequent real-time map data fusion.

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

acquiring a map data fusion result in a preset time period;

generating the secondary geofence based on the fused result distribution thermodynamic diagram.

Kernel density analysis is a means of transforming a collection of point elements (vector data) into grid data, primarily to calculate the density of the elements in their surrounding neighborhood, where kernel density functions to calculate a measure of unit area from the point or polyline elements using a kernel function to fit individual points or polylines to a smooth pyramidal surface.

And generating the secondary geo-fence based on the fusion result distribution thermodynamic diagram, specifically, selecting an appropriate density range based on the fusion result distribution thermodynamic diagram, obtaining the secondary geo-fence, and providing the secondary geo-fence to a fusion perception algorithm to serve as a reference for the reliability of the vehicle running track.

Further, obtaining a map data fusion result in a preset time period may further include:

In the embodiment of the present specification, the map data fusion result within the preset time period may be visually displayed in the GIS tool software.

In the method for generating a hierarchical geofence provided in the embodiments of the present specification, a first-level geofence is generated by using a visual map, map data fusion is performed by projecting the first-level geofence onto a roadside sensor image, a real-time fusion video is started during the fusion process to determine whether actual geographic positions of the first-level geofence and the roadside sensor image are matched, if not, the position of a data point in the first-level geofence is modified based on the roadside sensor image, and a second-level geofence is generated based on a map data fusion result.

Based on the same inventive concept, the embodiments of the present specification provide a hierarchical geofence generating apparatus. Fig. 3 is a schematic structural diagram of a hierarchical geofence generating device provided for an embodiment of this specification.

The hierarchical geofence generation apparatus provided in the embodiments of this specification may specifically include:

a primary generation module 301, which generates a primary geo-fence using a visual map;

the fusion module 302 is used for projecting the primary geo-fence onto a roadside sensor image to perform map data fusion;

the matching module 303 is used for starting the real-time fusion video and judging whether the primary geo-fence is matched with the actual geographic position on the image of the roadside sensor;

a modifying module 304, if not, modifying the position of the data point in the primary geo-fence based on the roadside sensor image;

the secondary generation module 305 generates a secondary geo-fence based on the map data fusion result.

Further, generating a primary geofence using the visual map may include:

generating the primary geofence using the visual map.

Further, generating the primary geofence using the visual map may include:

generating the primary geofence based on the lane line coordinate data.

acquiring overlapping distance information of the sensors;

Further, projecting the primary geo-fence onto a roadside sensor image for map data fusion, and may further include:

Further, starting the real-time fusion video, and determining whether the primary geo-fence is matched with the actual geographic location on the roadside sensor image may include:

determining a reference position point by using the real-time fusion video;

Further, modifying the location of the data point in the primary geofence based on the roadside sensor image may include:

Further, generating a secondary geo-fence based on the map data fusion result may include:

acquiring a map data fusion result in a preset time period;

and displaying a map data fusion result in the preset time period in the visual map.

The embodiment of the present specification provides a hierarchical geofence generation apparatus, which generates a primary geofence by using a visual map, performs map data fusion by projecting the primary geofence onto a roadside sensor image, starts a real-time fusion video in a fusion process, determines whether actual geographic positions of the primary geofence and the roadside sensor image are matched, modifies positions of data points in the primary geofence based on the roadside sensor image if the actual geographic positions are not matched, and generates a secondary geofence based on a map data fusion result.

Therefore, in the process of generating the geo-fence, the primary geo-fence is projected onto the roadside sensor image to be matched with the actual geo-position, so that the position of the data point of the primary geo-fence can be modified in real time, the secondary geo-fence is generated based on the map data fusion result and used as a reference for the credibility of the fusion result, the generation efficiency of the geo-fence can be effectively improved, and the geo-fence can be adjusted in real time and customized according to the service scene function.

The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the embodiments of the apparatus, the electronic device, and the nonvolatile computer storage medium, since they are substantially similar to the embodiments of the method, the description is simple, and the relevant points can be referred to the partial description of the embodiments of the method.

The apparatus, the electronic device, the nonvolatile computer storage medium and the method provided in the embodiments of the present description correspond to each other, and therefore, the apparatus, the electronic device, and the nonvolatile computer storage medium also have similar advantageous technical effects to the corresponding method.

In the 90 s of the 20 th century, improvements in a technology could clearly distinguish between improvements in hardware (e.g., improvements in circuit structures such as diodes, transistors, switches, etc.) and improvements in software (e.g., improvements in process flow). However, as technology advances, many of today's process flow improvements have been seen as direct improvements in hardware circuit architecture. Designers almost always obtain the corresponding hardware circuit structure by programming an improved method flow into the hardware circuit. Thus, it cannot be said that an improvement in the process flow cannot be realized by hardware physical modules. For example, a Programmable Logic Device (PLD) (e.g., a Field Programmable Gate Array (FPGA)) is an integrated circuit whose Logic functions are determined by a user programming the Device. A digital system is "integrated" on a PLD by the designer's own programming without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Furthermore, nowadays, instead of manually making an Integrated Circuit chip, such Programming is often implemented by "logic compiler" software, which is similar to a software compiler used in program development and writing, but the original code before compiling is also written by a specific Programming Language, which is called Hardware Description Language (HDL), and HDL is not only one but many, such as abel (advanced Boolean Expression Language), ahdl (alternate Hardware Description Language), traffic, pl (core universal Programming Language), HDCal (jhdware Description Language), lang, Lola, HDL, laspam, hardward Description Language (vhr Description Language), vhal (Hardware Description Language), and vhigh-Language, which are currently used in most common. It will also be apparent to those skilled in the art that hardware circuitry for implementing the logical method flows can be readily obtained by a mere need to program the method flows with some of the hardware description languages described above and into an integrated circuit.

The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, an Application Specific Integrated Circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic for the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller as pure computer readable program code, the same functionality can be implemented by logically programming method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers and the like. Such a controller may thus be considered a hardware component, and the means included therein for performing the various functions may also be considered as a structure within the hardware component. Or even means for performing the functions may be regarded as being both a software module for performing the method and a structure within a hardware component.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. One typical implementation device is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smartphone, 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.

For convenience of description, the above devices are described as being divided into various units by function, and are described separately. Of course, the functionality of the various elements may be implemented in the same one or more pieces of software and/or hardware in the practice of the present application.

As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.

The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.

These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.

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

The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.

Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, 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 disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.

It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.

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

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.

The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A hierarchical geofence generation method, comprising:

generating a primary geo-fence using the visual map;

and generating a secondary geo-fence based on the map data fusion result.

2. The method of claim 1, wherein generating a primary geofence using a visual map comprises:

generating the primary geofence using the visual map.

3. The method of claim 1, wherein generating a primary geofence using a visual map comprises:

generating the primary geofence based on the lane line coordinate data.

4. The method of claim 3, wherein generating the primary geofence based on the lane line coordinate data comprises:

acquiring overlapping distance information of the sensors;

5. The method of claim 1, wherein projecting the primary geofence onto a roadside sensor image for map data fusion, further comprising:

6. The method of claim 5, wherein turning on a real-time fusion video to determine whether the primary geofence matches an actual geographic location on the roadside sensor image comprises:

determining a reference position point by using the real-time fusion video;

7. The method of claim 6, wherein modifying the location of data points in the primary geofence based on the roadside sensor image comprises:

if the reference position point of the primary geo-fence is not matched with the actual geo-position of the reference position point on the roadside sensor image, suspending the real-time fusion video based on the local map;

8. The method of claim 1, wherein generating a secondary geofence based on the map data fusion results comprises:

obtaining a map data fusion result in a preset time period;

9. The method of claim 8, wherein obtaining the map data fusion result within a preset time period further comprises:

10. A hierarchical geofence generation apparatus, comprising:

the matching module is used for starting the real-time fusion video and judging whether the primary geo-fence is matched with the actual geographic position on the roadside sensor image or not;