WO2022194008A1

WO2022194008A1 - Map data processing method and apparatus

Info

Publication number: WO2022194008A1
Application number: PCT/CN2022/079965
Authority: WO
Inventors: 刘建琴
Original assignee: 华为技术有限公司
Priority date: 2021-03-18
Filing date: 2022-03-09
Publication date: 2022-09-22
Also published as: CN115146007A

Abstract

The present application provides a map data processing method and apparatus, which can solve the problem of low accuracy of map element evaluation and update caused by relying only on the confidence of a single map element reported by a terminal device, thereby improving the accuracy of map update, and can be applied to an Internet of vehicles communication system. The method comprises: a network side may acquire confidence information of map elements, and determine, according to the confidence information of the map elements, whether to update a map, wherein the confidence information of the map elements may include: confidence information of a target element and reference confidence information, and the reference confidence information may comprises: at least one of confidence information of a reference element, joint confidence information of the target element and the reference element, and conditional confidence information of the target element and the reference element.

Description

Map data processing method and device

This application claims the priority of the Chinese patent application with the application number 202110292905.0 and the application name "Map Data Processing Method and Device", which was submitted to the State Intellectual Property Office on March 18, 2021, the entire contents of which are incorporated into this application by reference .

technical field

The present application relates to the field of maps and Internet of Vehicles, and in particular, to a method and device for processing map data.

Background technique

With the widespread use of electronic maps in daily life, updating maps has become an important part of the process of using electronic maps. The traditional way of updating the map is to lay out a large number of road networks for data collection, maintenance and update. In this way, a lot of manpower, material resources and financial resources are consumed, and the cost of collection and maintenance and update is relatively high. The crowdsourcing collection mode refers to the use of terminal equipment, such as vehicles, or mobile phones, to collect and report the collected data to the cloud, and the cloud updates the map according to the data reported by the terminal equipment to reduce the cost of map update. However, the accuracy of this map update method is insufficient and cannot meet the needs of scenarios that require high map accuracy.

SUMMARY OF THE INVENTION

The embodiments of the present application provide a map data processing method and device, which can solve the technical problem of low accuracy of map update based on crowdsourcing data collection.

To achieve the above object, the application adopts the following technical solutions:

In a first aspect, a map data processing method is provided, which is applied to the network side. The map data processing method may include: acquiring confidence information of map elements, and determining whether to update the map according to the confidence information of the map elements. The map elements may include target elements and reference elements, the confidence information of the map elements may include the confidence information of the target elements and the reference confidence information, and the reference confidence information may include: the confidence information of the reference elements, the target elements and the reference elements. At least one of joint confidence information between elements, and conditional confidence information between a target element and a reference element.

Based on the map data processing method described in the first aspect, the network side can evaluate whether the target element has changed according to the confidence information of the target element reported by the terminal device and the reference confidence information of the reference element associated with the target element, and Update the target element in the map based on the evaluation results. That is to say, based on the relationship between the reference element and the target element, the credibility of the change of the target element can be evaluated, which can reduce the adverse effects of different collection capabilities of different terminal devices on evaluating and updating the target element, thereby improving the map update reliability. accuracy.

In addition, the confidence information of a single map element is also affected by the device error of the terminal device itself, such as the terminal positioning error term, the external parameter calibration error term, and the measurement error term of the sensor. The map data processing method described in the first aspect can also comprehensively evaluate the confidence information of a plurality of map elements reported by the terminal device, so as to reduce the above-mentioned adverse effects on the confidence information of the map elements due to the device error of the terminal device itself, thereby Improve the accuracy of the assessment.

In a possible design solution, there may be multiple reference elements, and the reference confidence level information may further include: joint confidence level information or conditional confidence level information between every two reference elements in the multiple reference elements. In this way, by updating the map in combination with the association relationship between the reference elements and the reference elements, more accurate confidence information can be obtained, thereby further improving the accuracy of map updating.

Optionally, the confidence information of the map elements can be used to determine the confidence covariance matrix. For example, the confidence information of the map element is a confidence covariance matrix, or the confidence information of the map element is used to indicate the confidence covariance matrix, or the confidence information of the map element includes each element in the confidence covariance matrix, to determine the confidence covariance matrix by the receiver. The confidence covariance matrix may include confidences for multiple map elements. The confidence covariance matrix can include the following formula:

Among them, Cov(P _v ) is the confidence covariance matrix, the diagonal element P _v (x) is the confidence of the xth map element, and P _v (x, y) is the relative value of the xth map element to the The joint confidence or conditional confidence of the y-th map element, the joint confidence information between the x-th map element and the y-th map element includes: the joint confidence of the x-th map element relative to the y-th map element , the conditional confidence level information between the xth map element and the yth map element includes: the conditional confidence level of the xth map element relative to the yth map element. Wherein, x=i, i+1,...,i+n; y=i, i+1,...,i+n; i and n are positive integers greater than or equal to 1.

In a possible design scheme, obtaining the confidence information of the map elements may include: the network side obtains the confidence information from multiple terminal devices, and fuses the confidence information of the multiple terminal devices to obtain the fused confidence information. degree information. The fused confidence information is the confidence information of the map element. In this way, by fusing the confidence information of map elements uploaded by multiple terminal devices, such as the confidence information of the target element or the reference confidence information, the adverse effect of a single terminal device, such as a terminal device with a large calculation error, on the confidence can be reduced. , so as to improve the credibility of the fused map elements and further improve the accuracy of the evaluation.

In a possible design solution, the conditional confidence information between the target element and the reference element may be related to the influence factor of the reference element on the target element. In this way, the impact factor can be used to characterize the relationship between the reference element and the target element, so that the conditional confidence information can more accurately reflect the credibility of the target element and improve the accuracy of the evaluation.

In one possible design, the target element can be a map element that changes.

In a possible design solution, the reference element may be a map element whose reference confidence information satisfies a preset condition. In this way, the network side can more accurately evaluate whether the target element has changed when the reference element satisfies the preset condition, thereby further improving the accuracy of map update.

In a second aspect, a map data processing method is provided, which is applied to a terminal device. The map data processing method may include: determining confidence information of a target element, and the target element may be a map element. Determine the reference confidence level information, the reference confidence level information may include at least one of confidence level information of the reference element, joint confidence level information between the target element and the reference element, or conditional confidence level information between the target element and the reference element. Finally, the confidence information of the map element is sent to the network side. The confidence information of the map element includes confidence information of the target element and reference confidence information.

In a possible design solution, there may be multiple reference elements, and the reference confidence level information may further include: joint confidence level information or conditional confidence level information between every two reference elements in the multiple reference elements.

Optionally, the confidence information of the map elements can be used to determine the confidence covariance matrix. For example, the confidence information of the map element is a confidence covariance matrix, or the confidence information of the map element is used to indicate the confidence covariance matrix, or the confidence information of the map element includes each element in the confidence covariance matrix, to determine the confidence covariance matrix by the receiver. The confidence covariance matrix may include confidences of multiple map elements, the multiple map elements include target elements and reference elements, and the confidence covariance matrix may include the following formula:

Among them, Cov(P _v ) is the confidence covariance matrix, the diagonal element P _v (x) is the confidence of the xth map element, and P _v (x, y) is the xth map element relative to the yth map element. The joint confidence or conditional confidence of each map element, the joint confidence information between the xth map element and the yth map element includes: the joint confidence of the xth map element relative to the yth map element, the joint confidence of the xth map element relative to the yth map element, the The conditional confidence level information between the x-th map element and the y-th map element includes: the conditional confidence level of the x-th map element relative to the y-th map element. Wherein, x=i, i+1,...,i+n; y=i, i+1,...,i+n; i and n are positive integers.

In a possible design solution, the method shown in the second aspect may further include: determining a target element and a reference element. The target element is a changed map element, and the reference element is a map element whose confidence information satisfies a preset condition.

In addition, for the technical effect of the map data processing method described in the second aspect, reference may be made to the technical effect of the map data processing method described in the first aspect, which will not be repeated here.

In a third aspect, a map data processing apparatus is provided. The device includes: a processing module and an acquisition module. Among them, the obtaining module can be used to obtain the confidence information of the map element. The map element may include a target element and a reference element, the confidence information may include confidence information of the target element and reference confidence information, and the reference confidence information may include: confidence information of the reference element, the relationship between the target element and the reference element at least one of a joint confidence, and a conditional confidence between the target element and the reference element. The processing module can be used to determine whether to update the map according to the confidence information of the map elements.

Optionally, the confidence information of the map elements can be used to determine the confidence covariance matrix. For example, the confidence information of the map element is a confidence covariance matrix, or the confidence information of the map element is used to indicate the confidence covariance matrix, or the confidence information of the map element includes each element in the confidence covariance matrix, to determine the confidence covariance matrix by the receiver. The confidence covariance matrix may include the confidences of multiple map elements, and the confidence covariance matrix may include the following formula:

In a possible design solution, the acquisition module may also be used to acquire confidence information from multiple terminal devices, and to fuse the confidence information of multiple terminal devices to obtain fused confidence information. The fused confidence information is the confidence information of the map element.

In a possible design solution, the conditional confidence information between the target element and the reference element may be related to the influence factor of the reference element on the target element.

In one possible design, the target element is the map element that changes.

In a possible design solution, the reference element may be a map element whose reference confidence information satisfies a preset condition.

Optionally, the obtaining module may include a transceiver module, and the transceiver module may include a receiving module and a sending module. Wherein, the receiving module and the sending module are respectively used to implement the receiving function and the sending function of the map data processing apparatus described in the third aspect. For example, the receiving module may be configured to receive confidence information from multiple terminal devices.

Optionally, the map data processing apparatus described in the third aspect may further include a storage module, where the storage module stores programs or instructions. When the processing module executes the program or the instruction, the map data processing apparatus described in the third aspect can execute the map data processing method described in the first aspect.

It should be noted that the map data processing apparatus described in the third aspect may be the network side, or may be a chip (system) or other components or components that can be provided in the network side, which is not limited in this application.

In addition, for the technical effect of the map data processing apparatus described in the third aspect, reference may be made to the technical effect of the map data processing method described in the first aspect, which will not be repeated here.

In a fourth aspect, a map data processing apparatus is provided. The apparatus may include: a processing module and a transceiver module. Among them, the processing module is used to determine the confidence information of the target element. The processing module is further configured to determine reference confidence information, where the reference confidence information may include: confidence information of the reference element, joint confidence information between the target element and the reference element, or conditional confidence between the target element and the reference element at least one of the information. The transceiver module is used to send the confidence information of the map element to the network side. The confidence information of the map element includes confidence information of the target element and reference confidence information.

In a possible design solution, the reference confidence level information further includes: joint confidence level information or conditional confidence level information between multiple reference elements.

In a possible design scheme, the processing module can also be used to determine the target element and the reference element. The target element is a map element that has changed, and the reference element is a map element whose reference confidence information satisfies a preset condition.

Optionally, the transceiver module may include a receiving module and a sending module. Wherein, the receiving module and the sending module are respectively used to implement the receiving function and the sending function of the map data processing apparatus described in the fourth aspect.

Optionally, the map data processing apparatus described in the fourth aspect may further include a storage module, where the storage module stores programs or instructions. When the processing module executes the program or instruction, the map data processing apparatus described in the fourth aspect can execute the map data processing method described in the second aspect.

It should be noted that the map data processing apparatus described in the fourth aspect may be a terminal device, or may be a chip, other components or components that can be provided in the terminal device, which is not limited in this application.

In addition, for the technical effect of the map data processing apparatus described in the fourth aspect, reference may be made to the technical effect of the map data processing method described in the first aspect, which will not be repeated here.

In a fifth aspect, a map data processing apparatus is provided. The map data processing apparatus is used for executing the map data processing method described in the first aspect or the second aspect.

In this application, the map data processing apparatus described in the fifth aspect may be the network side described in the first aspect, or the terminal device described in the second aspect, or a chip, other component or components, or apparatuses containing the above-mentioned devices.

It should be understood that the map data processing apparatus described in the fifth aspect includes a corresponding module, unit, or means for implementing the map data processing method described in the first aspect or the second aspect, and the module, unit, or means may be Implemented by hardware, implemented by software, or implemented by hardware executing corresponding software. The hardware or software includes one or more modules or units for performing the functions involved in any of the above-mentioned map data processing methods.

In addition, for the technical effect of the map data processing apparatus described in the fifth aspect, reference may be made to the technical effect of the map data processing method described in the first aspect or the second aspect, which will not be repeated here.

In a sixth aspect, a map data processing apparatus is provided. The map data processing apparatus includes: a processor configured to execute the map data processing method described in the first aspect or the second aspect.

In a possible design solution, the map data processing apparatus described in the sixth aspect may further include a transceiver. The transceiver may be a transceiver circuit or an interface circuit. The transceiver can be used for the map data processing device described in the sixth aspect to communicate with other devices.

In a possible design solution, the map data processing apparatus described in the sixth aspect may further include a memory. The memory can be integrated with the processor, or it can be provided separately. The memory may be used to store the computer program and/or data involved in the map data processing method described in the first aspect or the second aspect.

In this application, the map data processing apparatus described in the sixth aspect may be the network side described in the first aspect, or the terminal device described in the second aspect, or may be provided in chips, other components or components of the above-mentioned devices. , or an apparatus comprising the above apparatus.

In addition, for the technical effect of the map data processing apparatus described in the sixth aspect, reference may be made to the technical effect of the map data processing method described in the first aspect or the second aspect, which will not be repeated here.

In a seventh aspect, a map data processing apparatus is provided. The map data processing apparatus includes: a processor coupled to a memory, the processor is configured to execute a computer program stored in the memory, so that the map data processing apparatus executes the map data processing described in the first aspect or the second aspect method.

In a possible design solution, the map data processing apparatus according to the seventh aspect may further include a transceiver. The transceiver may be a transceiver circuit or an interface circuit. The transceiver can be used for the map data processing apparatus described in the seventh aspect to communicate with other apparatuses.

In this application, the map data processing apparatus described in the seventh aspect may be the network side described in the first aspect, or the terminal device described in the second aspect, or may be provided in chips, other components or components of the above-mentioned devices. , or an apparatus comprising the above apparatus.

In addition, for the technical effect of the map data processing apparatus described in the seventh aspect, reference may be made to the technical effect of the map data processing method described in the first aspect or the second aspect, which will not be repeated here.

In an eighth aspect, a map data processing apparatus is provided, comprising: a processor and a memory; the memory is used to store a computer program or instruction, and when the processor executes the computer program or instruction, the map data processing apparatus executes The map data processing method according to the first aspect or the second aspect.

In a possible design solution, the map data processing apparatus described in the eighth aspect may further include a transceiver. The transceiver may be a transceiver circuit or an interface circuit. The transceiver can be used for the map data processing device described in the eighth aspect to communicate with other devices.

In this application, the map data processing apparatus described in the eighth aspect may be the network side described in the first aspect, or the terminal device described in the second aspect, or may be provided in chips, other components or components of the above-mentioned devices. , or an apparatus comprising the above apparatus.

In addition, for the technical effect of the map data processing apparatus described in the eighth aspect, reference may be made to the technical effect of the map data processing method described in the first aspect or the second aspect, which will not be repeated here.

In a ninth aspect, a map data processing device is provided, comprising: a processor; the processor is configured to be coupled to a memory, and after reading a computer program in the memory, execute the first aspect or the second aspect according to the computer program The described map data processing method.

In a possible design solution, the map data processing apparatus according to the ninth aspect may further include a transceiver. The transceiver may be a transceiver circuit or an interface circuit. The transceiver can be used for the map data processing apparatus described in the ninth aspect to communicate with other apparatuses.

In this application, the map data processing apparatus described in the ninth aspect may be the network side described in the first aspect, or the terminal device described in the second aspect, or may be provided in chips, other components or components of the above devices , or an apparatus comprising the above apparatus.

In addition, for the technical effect of the map data processing apparatus described in the ninth aspect, reference may be made to the technical effect of the map data processing method described in the first aspect or the second aspect, which will not be repeated here.

A tenth aspect provides a processor. The processor is configured to execute the map data processing method described in any possible implementation manner of the first aspect or the second aspect.

An eleventh aspect provides a map data processing system. The map data processing system includes a network side and one or more terminal devices.

A twelfth aspect provides a computer-readable storage medium, comprising: a computer program or instruction; when the computer program or instruction is executed on a processor, the map data processing method described in the first aspect or the second aspect is implement.

A thirteenth aspect provides a computer program product, comprising a computer program or instructions, which, when the computer program or instructions are run on a processor, cause the map data processing method described in the first aspect or the second aspect to be executed.

Description of drawings

1 is a schematic diagram of the architecture of a map data processing system provided by an embodiment of the present application;

2 is a schematic flowchart of a map data processing method provided by an embodiment of the present application;

3 is a schematic diagram of a map element provided by an embodiment of the present application;

FIG. 4 is a schematic structural diagram 1 of a map data processing apparatus provided by an embodiment of the present application;

FIG. 5 is a second schematic structural diagram of a map data processing apparatus provided by an embodiment of the present application;

FIG. 6 is a third schematic structural diagram of a map data processing apparatus according to an embodiment of the present application.

Detailed ways

First, the technical terms involved in the embodiments of the present application are introduced.

1. Crowdsourcing: Crowdsourcing is more and more widely used in different fields, which converts the operations originally carried out by professional companies or institutions into a mode operated by many users. For example, the collection of raw data can be completed by many users while using the device on a daily basis, and serves as the basis for improving user experience.

For example, in the field of maps, data collection is transformed from the original professional collection mode to the crowdsourcing collection mode. The professional collection mode uses professional collection equipment to collect map information, while the crowdsourcing collection mode can use terminal equipment, such as vehicles, or mobile phones, etc. In the process of daily use, map information is collected through the sensors it carries.

During the map update process in the professional collection mode, the network side (such as the cloud) usually receives a notification of changes in map elements in advance, and then uses professional collection equipment to collect the changed map elements in the corresponding area. During the map update process in the crowdsourcing collection mode, if the terminal device detects that a certain map element has changed, it can directly send the collected map element information to the cloud, so as to update the map in time.

Moreover, compared with the professional collection mode, the terminal equipment in the crowdsourcing collection mode can also perform the collection business in the process of performing the daily business, which can solve the problem of insufficient professional collection equipment, and can improve the collection efficiency and the real-time update of map elements. .

2. Confidence: It reflects the possibility that the measured value of the parameter is consistent with the real value, or the possibility that the real value falls within the confidence interval of the measurement result, which can be used to characterize the reliability of the measurement result. Confidence can be expressed in the form of probability, and confidence can be called confidence probability, or simply probability. In this embodiment of the present application, the confidence level may be used to represent the confidence level of the measured map element information.

3. Covariance matrix: Each element in the covariance matrix is the covariance between variables, and the covariance is used to represent the overall error of the two variables, that is, the relative change trend of the two variables. If the changes of the two variables If the trends are the same, the covariance is positive, and if the two variables have opposite trends, the covariance is negative.

For example, an embodiment of the present application provides a joint confidence (or joint probability) covariance matrix, where the diagonal elements of the joint confidence covariance matrix are the confidence (or probability) of a single map element, and the off-diagonal elements The element is the joint confidence (or joint probability) between two map elements, and the joint confidence covariance matrix can represent the overall error between the confidences of the map elements. The confidence of the map elements can also be called probability, such as marginal probability. The off-diagonal element is the joint confidence between two map elements, which may include the joint confidence of the first map element relative to the second map element in the two map elements, or the second map element relative to the first map element. The joint confidence of the elements. Further, the joint confidence between the two map elements on the off-diagonal elements can be replaced by the conditional confidence to obtain the conditional confidence covariance matrix.

4. Diversity computation: In radio communications, after receiving multiple signals carrying the same message, diversity computation can be used to recover the delivered message using selection circuits or combining circuits. Compared with the way of obtaining the message through a single signal, the way of diversity calculation can obtain the message of better quality. In this embodiment of the present application, the network side may integrate the confidence levels of the map elements by means of diversity calculation, so as to improve the confidence levels of the map elements.

5. Maximum Likelihood Estimation (MLE) strategy: It is a common strategy for estimating quasi-conditional probability. The core idea of the MLE strategy is that the event corresponding to the maximum probability is an event that has already occurred. In this embodiment of the present application, the network side may use the MLE strategy to evaluate whether the target element has changed, so as to improve the accuracy of map update.

The technical solutions in the embodiments of the present application will be described below with reference to the accompanying drawings.

The technical solutions of the embodiments of the present application can be applied to various map data processing systems, or various communication systems that need to execute the map data processing method, such as a vehicle-to-everything (V2X) communication system.

This application will present various aspects, embodiments or features around a system that may include a plurality of devices, components, or modules, or the like. It is to be understood and appreciated that the various systems may include additional devices, components, or modules, etc., and/or may not include all of the devices, components, or modules, etc. discussed in connection with the figures. In addition, combinations of these schemes can also be used. In the embodiments of the present application, "a plurality of" refers to two or more. "And/or" describes the association relationship of the associated objects, indicating that there can be three kinds of relationships, for example, H and/or I, which can mean that H exists alone, H and I exist at the same time, and I exists alone. Also, for "at least one of..." means one or any combination of subsequent associated objects, eg "at least one of H, I and J" includes H, I, J , HI, HJ, IJ, or HIJ.

To facilitate understanding of the embodiments of the present application, firstly, a system to which the map data processing method provided by the embodiments of the present application is applied is described by taking the map data processing system shown in FIG. 1 as an example.

Exemplarily, FIG. 1 is a schematic structural diagram of a map data processing system provided by an embodiment of the present application. As shown in FIG. 1 , the map data processing system may include a terminal device and a network side, and the network side is, for example, a cloud, and may include a cloud server and/or a cloud virtual machine. Wherein, there may be one or more terminal devices, and the terminal devices are configured with sensors, and the sensors may be used to collect information of map elements.

In a possible design solution, the terminal device may be a device capable of providing the collected map elements for the network device, and the network side may be a device capable of updating the map according to the reported map elements. It should be understood that when the terminal device detects that the map element (that is, the target element) has changed, it will determine the confidence information of the map element and the reference confidence information of other surrounding map elements (that is, the reference element), and upload it to the network side The confidence information corresponding to the map element and the reference confidence information corresponding to the reference element. The network side and the terminal device can be used to execute the map data processing method shown in FIG. 2 below to determine whether the map element has changed, so as to update the map with the changed map element.

Wherein, the network side of the map data processing system may be a network side device, and the network side of the map data processing system may include a device, a chip or a chip system with a sending and receiving function for performing the steps performed by the network side in the following methods. The network side includes but is not limited to: an application server arranged in the network, such as a map server, or a roadside unit (RSU) with a map update function. The above-mentioned network side can be used to provide map services, such as storing electronic maps, updating electronic maps, or sending electronic maps to terminal devices. For specific implementation methods, refer to the related content shown in FIG. 2 below, which will not be repeated here. In addition, the above-mentioned network side may also be used to provide over-the-air upgrade services, and/or software/algorithm update services, and the like.

Furthermore, the above-mentioned terminal device can communicate with the above-mentioned network side, and the above-mentioned terminal device may be a device, a chip or a chip system having a transceiver function. The terminal equipment may also be referred to as user equipment, access terminal, subscriber unit, remote terminal, mobile device, user terminal, terminal, wireless communication device, user agent, or user equipment. The terminal device in the embodiment of the present application may be a vehicle, a mobile phone, a tablet computer (Pad), a computer, a smart terminal in self-driving, a terminal in transportation safety, a smart terminal Wireless terminals, vehicle-mounted terminals, or RSUs with map information collection functions in a smart city. Among them, the RSU with the function of collecting map information can receive instructions from the network side, focus on the perception of unmatched map elements, and report the perception results to the network side. The terminal device of the present application may also be an on-board module, on-board module, on-board component, on-board chip or on-board unit built into the vehicle as one or more components or units. The above-mentioned terminal device can use the electronic map issued by the network side, and the terminal device can also be used to perceive the surrounding environment, and collect the parameters of map elements that do not match the electronic map and the attribute information of the map elements, such as confidence, and report to the network side. Report the parameter and attribute information of the map element. For a specific implementation manner, reference may be made to the related content shown in FIG. 2 below, which will not be repeated here.

It should be noted that the solutions in the embodiments of the present application can also be applied to other map data processing systems, and the corresponding names can also be replaced by the names of corresponding functions in other map data processing systems.

It should be understood that FIG. 1 is only a simplified schematic diagram for easy understanding, and the map data processing system may also include other network sides and/or other terminal devices, which are not shown in FIG. 1 .

The map data processing method provided by the embodiment of the present application will be described in detail below with reference to FIG. 2 to FIG. 3 .

Exemplarily, FIG. 2 is a schematic flowchart of a map data processing method provided by an embodiment of the present application. The map data processing method can be applied to the map data processing system shown in FIG. 1 . As shown in Figure 2, the map data processing method includes the following steps:

S201, a terminal device determines confidence information of a target element.

Exemplarily, the terminal device may be the vehicle or roadside unit shown in FIG. 1 . The above-mentioned target element may be a map element detected by the terminal device that does not conform to the electronic map, and the element has changed compared with the element in the map, for example, the traversable direction has changed due to road construction. Alternatively, the target element may be an element measured by the terminal device, which is a new element compared with the map, such as a signal light, which is not reflected in the map stored in the terminal. The electronic map may be map data stored locally by the terminal device, and the map data stored locally may be map data pre-stored by the terminal device, or may be the map data previously received by the terminal device from the network side. In the embodiment of the present application, the acquisition method of the electronic map is not limited. The terminal device can use the electronic map to realize the navigation function and/or the automatic driving function. The map element can be any information element in the electronic map. For example, the information element may include geographic information such as location information, road information, or building information, such as: building type, street number where the building is located, traffic signs, or traffic lights. The embodiments of the present application do not limit the specific implementation manner of the map element.

Furthermore, the confidence level information of the target element (also referred to as the first confidence level information) can be used to indicate the confidence level of the target element. For the specific implementation of the confidence level information of the target element, please refer to the specific implementation in S203 below. The implementation method is not repeated here.

S202, the terminal device determines reference confidence information.

Exemplarily, the reference confidence information may be confidence information related to the reference element. The above reference elements may be map elements collected by the terminal device. There is an association between the reference element and the target element. The association rules can be preset in the terminal device, such as elements within a preset distance. For example, if the target element is a newly added traffic light in the north direction at the intersection detected by the terminal device, the reference element can be the traffic light in the south direction, the traffic light in the west direction and/or the traffic light in the east direction at the intersection, or It is the light pole where the traffic light corresponding to the target element is located, and can also be the surrounding buildings corresponding to the intersection. For another example, if the target element is the road section under maintenance detected by the terminal device, the reference element may be the surrounding buildings of the road section, or the traffic signs in the road section. The embodiments of the present application do not limit the specific implementation manner of the association between the reference element and the target element.

Furthermore, the reference confidence information may be used to indicate the reliability of the reference element, or the reference confidence information may be used to indicate the reliability of the first map element relative to the second map element among the two map elements. Wherein, the first map element and the second map element may include one target element and one reference element, or may include two reference elements. For the specific implementation of the confidence level information, reference may be made to the specific implementation in the following step S203, which will not be repeated here.

Optionally, in this embodiment of the present application, the reference element may be a map element whose reference confidence information satisfies a preset condition. For the realization of the above preset condition, reference may be made to the specific implementation manner of the following second preset condition, which will not be repeated here.

It should be noted that, the target elements detected by the terminal device may be one or more, and the reference elements may also be one or more, and the embodiments of the present application do not limit the number of target elements and reference elements. In addition, when there are multiple target elements, the multiple target elements may also be related. For example, the multiple target elements include a first target element and a second target element, the first target element may be a reference element of the second target element, and the second target element may also be a reference element of the first target element.

It can be understood that the association between the above-mentioned target element and the reference element may be configured or preset by the terminal device, or may be set by a protocol. The specific implementation of the association.

S203, the terminal device sends the first confidence level information and the reference confidence level information to the network side. Correspondingly, the network side obtains the confidence information of the map element from at least one terminal device.

The confidence level information of the map element of the terminal device (also referred to as confidence level information of the terminal device) may include first confidence level information and reference confidence level information.

Exemplarily, the network side may be the cloud or server shown in FIG. 1 . The confidence level information of the above-mentioned map elements can be used to represent the confidence level of the map elements. For example, the first confidence level information may be used to represent the confidence level of the target element. The reference confidence level information may be used to indicate the confidence level of the reference element, or the confidence level of the first map element relative to the second map element among the two map elements. Wherein, the first map element and the second map element may include one target element and one reference element, and may also include two reference elements. The confidence information of the map elements (such as the first confidence information and the reference confidence information) can be determined by the terminal device according to the calculation rule, and the calculation rule can be an algorithm configured inside the vehicle terminal or the sensor. The configured algorithm may be different.

The reference confidence information may include one or more of the following: confidence information of the reference element, joint confidence information between the target element and the reference element (also referred to as first joint confidence information), and target element At least one of the conditional confidence information (also referred to as the first conditional confidence information) between the reference element and the reference element.

It should be noted that, in the embodiment of the present application, the above-mentioned first confidence information and the above-mentioned confidence information of the reference element are the possibility that the parameter measurement value of a single map element is a real value, and can be used to indicate the possibility of the corresponding map element. degree of confidence. The joint confidence level information (such as the above-mentioned first joint confidence level information) is the possibility that the parameter measurement values of multiple map elements are real values, and can be used to indicate the joint confidence level of the corresponding multiple map elements. Conditional confidence level information (such as the above-mentioned first conditional confidence level information) is the possibility that when the measured value of a parameter of a certain map element is the true value, the measured value of the parameter of other map elements is the true value, and can be used for Indicates the trustworthiness of other map elements when one map element is trustworthy.

The joint confidence level information and the conditional confidence level information may be calculated by the terminal device according to the confidence level information of the target element and the confidence level information of the reference element. Therefore, the terminal device may only report the confidence information of the target element and the confidence information of the reference element, and the network side determines the joint confidence information or conditional confidence information according to the confidence information of the target element and the confidence information of the reference element. Alternatively, the terminal device can report the confidence information of the target element and the confidence information of the reference element, and further report the joint confidence information or conditional confidence information. In this way, the network side can directly use the confidence information reported by the terminal device to determine whether to update map.

Optionally, when there may be multiple reference elements, the reference confidence information may further include: joint confidence information (also referred to as second joint confidence information) between two reference elements, or two Conditional confidence level information between reference elements (may also be referred to as second conditional confidence level information).

The second joint confidence level information may include: joint confidence level calculated by the terminal device according to confidence level information of multiple reference elements. The second joint confidence level information may be used to represent the joint confidence level between the corresponding two reference elements. The second conditional confidence level information may include: a conditional confidence level calculated by the terminal device according to confidence level information of multiple reference elements. The second conditional confidence level information may be used to indicate the confidence level of another reference element under the condition that a certain reference element is credible. The terminal device may send the reference confidence information to the network side by sending the second joint confidence information or the second conditional confidence information to the network side. The embodiments of the present application do not limit the specific implementation manner in which the terminal device sends the second joint confidence level information or the second conditional confidence level information.

Similarly, when there are multiple target elements, the above-mentioned confidence information may also include: joint confidence information (also referred to as third joint confidence information) between two target elements, or between two target elements The conditional confidence information (also referred to as the third conditional confidence information). The third joint confidence level information may include: a joint confidence level calculated by the terminal device according to the confidence level information of multiple target elements. The third joint confidence level information may be used to represent the joint confidence level of the corresponding two target elements. The third conditional confidence level information may include: the conditional confidence level calculated by the terminal device according to the confidence level information of multiple target elements. The third conditional confidence level information can be used to indicate the confidence level of another target element under the condition that one target element is credible.

It can be understood that, the first confidence information, the confidence information of the reference element, the joint confidence information and the conditional confidence information may all be the confidence information determined by the terminal device according to its own calculation rules, but due to different terminal devices. There may be differences in the calculation rules of the map elements, resulting in different confidence information, joint confidence information or conditional confidence information of the same map element uploaded by different terminal devices, and it is difficult to accurately reflect the credibility of the corresponding map element.

It can be understood that, based on the correlation between the target element and the reference element, there is also a correlation between the credibility of the target element and the credibility of the reference element, and the terminal device can report the confidence information of the target element and the reference element. The reference confidence information for the network side to determine the degree of confidence that the target element changes, that is, the following change confidence degree, thereby reducing the adverse effects of different calculation rules in the terminal device on the reliability degree of the characterizing element, so that the network side can Evaluate whether the target element has changed based on the change confidence. For the specific implementation manner of determining the change confidence level and evaluating the target element by the network side, reference may be made to the following related content of S204, which will not be repeated here.

To sum up, in this embodiment of the present application, the network side can determine the change confidence of the target element based on the correlation between the target element and the reference element, which can more accurately reflect the reliability of the target element. In this way, compared with the method of using the confidence of the target element to evaluate whether the target element has changed, the method of using the reference confidence information of the reference element to evaluate the target element in the embodiment of the present application can reduce the calculation of the confidence between multiple terminal devices. Different rules or different collection capabilities have an impact on evaluating target elements, thereby improving the accuracy of network-side evaluation.

In a possible design solution, the above-mentioned confidence level information can be represented in various forms, for example, the above-mentioned confidence level information may be a confidence level, or information used to indicate a confidence level. For example, the first confidence level information may be: the confidence level of the target element or information indicating the confidence level of the target element. The confidence level information of the reference element may be: the confidence level of the reference element or information indicating the confidence level of the reference element. The joint confidence information may be: the joint confidence between two map elements or information indicating the joint confidence between the two map elements. The conditional confidence level information may be: the conditional confidence level between two map elements or information indicating the conditional confidence level between the two map elements. Among them, the confidence can be expressed by probability, and can also be expressed by numerical value, such as a numerical value with a value interval of [0, 100].

Correspondingly, the confidence level information of the above-mentioned map element may be a set of confidence levels uploaded by the terminal device (hereinafter referred to as the first confidence level set). For example, if the confidence is represented by probabilities, the set of confidences may be a set of probabilities. Optionally, the first set of confidence levels may be a confidence level covariance matrix. For example, if the confidence is expressed in terms of probability, the confidence covariance matrix may be a joint probability covariance matrix or a conditional probability covariance matrix. The diagonal elements of the confidence covariance matrix can be the confidence of a single map element, such as the confidence of the target element and the confidence of the reference element. Correspondingly, the off-diagonal elements of the confidence covariance matrix may be: joint confidence or conditional confidence between any two map elements. The terminal device may upload the confidence covariance matrix to the network side, so that the network side fuses the confidence covariance matrix from at least one terminal device. It should be noted that the confidence level, conditional confidence level and joint confidence level of the map element in the embodiments of the present application are all expressions of the confidence level of the map element.

Exemplarily, the confidence covariance matrix includes the following formula:

It should be noted that, in this embodiment of the present application, the confidence set may also be in other set forms. For example, the set of confidences can be an array where each element is one of the following: the confidence of the target element, the confidence of the reference element, the joint confidence of the xth element relative to the yth element, or the conditional confidence .

FIG. 3 is a schematic diagram of a map element provided by an embodiment of the present application. In the following, with reference to FIG. 3 , a specific implementation manner in which the first confidence set is a joint probability covariance matrix is further described by taking the terminal device as a vehicle terminal carrying a sensor as an example.

If the confidence is represented by probability, the first confidence information may be the first probability. The confidence information of the reference element in the reference confidence information may be the first reference probability, the first joint confidence information may be the first joint probability, the second joint confidence information may be the second joint probability, and the third joint confidence information can be the third joint probability. Wherein, in the joint probability covariance matrix, off-diagonal elements may include: a first joint probability, a second joint probability, and/or a third joint probability.

During the navigation process of the vehicle terminal 1 according to the electronic map, if the vehicle terminal 1 detects that the map element A and the map element B of the intersection are inconsistent with the corresponding map elements on the electronic map, the map element A and map element B as the target element. The vehicle terminal 1 then determines the corresponding map element C and map element D according to the correlation between the target element and the reference element, and uses the map element C and the map element D as reference elements. Then, the vehicle terminal 1 may calculate and obtain the first confidence degree set Cov(P _v1 ) of the vehicle terminal 1 according to the set confidence degree calculation method. The first set of confidence levels may be a joint probability covariance matrix. The first confidence set Cov(P _v1 ) of the vehicle terminal 1 may be:

Among them, Cov(P _v1 ) is the first confidence level set of the vehicle terminal 1, and both P _v1 (A) and P _v1 (B) are the target elements determined by the vehicle terminal 1 (corresponding to map element A and map element B in turn). The first probability, P _v1 (C) and P _v1 (D) are both the first reference probabilities of the reference elements determined by the vehicle terminal 1, and P _v1 (BA) and P _v1 (AB) are both determined by the vehicle terminal 1. The third joint probability between the target elements (map element A and map element B), both P _v1 (DC) and P _v1 (CD) are two reference elements (map element C and map element D) determined by vehicle terminal 1 The second joint probability between, P _v1 (CA), P _v1 (AC), P _v1 (BC), P _v1 (CB), P _v1 (DA), P _v1 (AD), P _v1 (DB), P _v1 (BD) is the first joint probability between the target element and the reference element determined by the vehicle terminal 1 . Wherein, for map element A, map element B may be regarded as a reference element of map element A; similarly, for map element B, map element A may be regarded as a reference element of map element B.

It can be understood that the joint probability covariance matrix may be a symmetric matrix, that is, a matrix with the main diagonal as the symmetry axis, and two elements located at symmetrical positions on both sides of the symmetry axis corresponding to the same matrix. Among them, the joint probability between the same two map elements is equal, such as P _v1 (BA) and P _v1 (AB) are equal, and P _v1 (DC) and P _v1 (CD) are equal.

Optionally, the joint probability covariance matrix may also be an asymmetric matrix, that is, the main diagonal is used as the symmetry axis, and there are matrices whose elements do not correspond to equal. Correspondingly, the joint probability between the same two map elements may not be equal, for example, P _v1 (BA) and P _v1 (AB) are not equal, and P _v1 (DC) and P _v1 (CD) are not equal. This application implements The example does not limit the specific implementation of the joint probability covariance matrix.

It should be noted that the terminal device may not be able to detect all target elements and/or reference elements, and the first confidence sets reported by different terminal devices may be different. Continuing to take the vehicle terminal as an example, if the sensor of the vehicle terminal 2 detects that map element A and map element B are target elements, then the vehicle terminal 2 only detects the corresponding map element D according to the correlation between the target element and the reference element. , the map element D is used as a reference element, and the vehicle terminal 2 can upload the first confidence level set Cov(P _v2 ) of the vehicle terminal 2 to the cloud. The first confidence level set Cov(P _v2 ) of the vehicle terminal 2 may be:

Among them, Cov(P _v2 ) is the first confidence level set of the vehicle terminal 2, P _v2 (A) and P _v2 (B) are the first probabilities of the target element determined by the vehicle terminal 2, and P _v2 (D) are both The first reference probability of the reference element determined by the vehicle terminal 2, P _v2 (BA) and P _v2 (AB) are both the third joint probability between the target elements determined by the vehicle terminal 2, P _v2 (DA), P _v2 ( AD), P _v2 (DB), and P _v2 (BD) are the first joint probability between the target element and the reference element determined by the vehicle terminal 2 . Wherein, for map element A, map element B may be regarded as a reference element of map element A; similarly, for map element B, map element A may be regarded as a reference element of map element B. In this embodiment of the present application, the first set of confidence levels may also be implemented in other ways, and the first joint probability covariance matrix listed above is only used as an example, and does not specifically limit the first set of confidence levels reported by the terminal device to the network side specific implementation.

It can be understood that the above-mentioned first confidence level set may also be a joint probability covariance matrix, or may be one or more probability sets in other forms composed of multiple probabilities as elements, such as multiple sets containing the above joint probability covariance matrix. The set of elements in one or more row vectors or column vectors in the variance matrix, and the embodiment of the present application does not limit the specific implementation of the first confidence set.

It can also be understood that the above-mentioned first set of confidence levels may also be a conditional probability covariance matrix. The diagonal elements of the conditional probability covariance matrix may be the confidence of a single map element, such as the first probability of the target element and the first reference probability of the reference element. Correspondingly, the off-diagonal elements of the conditional probability covariance matrix can be the conditional probabilities of any two map elements, such as the first conditional probability between the target element and the reference element, the difference between every two reference elements in the multiple reference elements. A second conditional probability between and/or a third conditional probability between every two target elements in the plurality of target elements. The terminal device may upload the conditional probability covariance matrix to the network side, so that the network side fuses the conditional probability covariance matrix from at least one terminal device. For a specific implementation manner of the conditional probability covariance matrix, reference may be made to the above-mentioned implementation manner of the joint probability covariance matrix, which will not be repeated here.

In addition, when the terminal device reports the confidence level information of the map element to the network side, the terminal device may report the first confidence level information to the network side, and may also report the reference confidence level information corresponding to the target element to the network side, or only to the network side. The network side reports the first confidence level information, but does not report the corresponding reference confidence level information. The embodiments of the present application do not limit the specific implementation manner in which the terminal device reports map elements to the network side. It can be understood that, in this embodiment of the present application, the terminal device may also report other information related to the target element and/or the reference element when reporting the first confidence level information and/or the reference confidence level information.

It can also be noted that when there are multiple terminal devices, the network side may receive map elements from multiple terminal devices, and the related parameters, such as confidence information, of the same map element reported by different terminal devices may be different. Take the target element as an example, assuming that there are vehicle 1 and vehicle 2, both vehicle 1 and vehicle 2 have reported the target element, and the target element is a traffic light in the north direction newly added at a certain intersection, but the target element reported by vehicle 1 is the same. The parameter is that the newly added traffic light is located 10 meters north of the above-mentioned intersection, and the relevant parameter of the target element reported by vehicle 2 is that the newly-added traffic light is located 20 meters north of the above-mentioned intersection. The embodiments of the present application do not limit the specific implementation manner of the relevant parameters of the map element.

Optionally, the conditional confidence level information between the target element and the reference element is related to the influence factor of the reference element on the target element. Regarding the implementation of the conditional confidence level information, reference may be made to the implementation manner of the fourth conditional confidence level information in the following step S204, which will not be repeated here.

Exemplarily, the above-mentioned network side acquiring the confidence level information of the map element from at least one terminal device may include: the network side acquiring the confidence level information from multiple terminal devices, and fusing the confidence level information of the multiple terminal devices, Get the fused confidence information.

The fused confidence information is the confidence information of the map element.

In this way, by fusing the confidence information of map elements uploaded by multiple terminal devices, such as first confidence information or reference confidence information, the adverse effect of a single terminal device, such as a terminal device with a large calculation error, on the confidence can be reduced. Thereby, the credibility of the fused map elements is improved, and the accuracy of the evaluation is further improved.

Regarding the implementation of the fusion of confidence information, reference may be made to the specific implementation of the fusion of confidence information in the following step S204, which is not repeated here.

S204, the network side determines whether to update the map according to the first confidence level information and the reference confidence level information.

Specifically, the above S204 may include: the network side may determine the change confidence of the target element according to the first confidence information and the reference confidence information, and determine whether to update the map according to the change confidence.

Among them, the change confidence level is used to represent the confidence level of the target element changes. In this way, based on the correlation between the target element and the reference element, there is also correlation between the first confidence level information and the reference confidence level information, so that the network side can determine the change confidence level and use the change confidence level to evaluate whether the target element has occurred. Changes, thereby reducing the adverse effects of different calculation rules in the terminal device on the credibility of the characterization element, and improving the accuracy of the evaluation.

It can be understood that the network side can fuse the confidence information of map elements reported by at least one terminal device (such as the above-mentioned first confidence information and reference confidence information), and then based on the confidence information of the fused map elements, such as fusion. The first confidence level information and the fused reference confidence level information are used to determine the change confidence level of the map element.

In some embodiments, the network side may determine the change confidence level of the target element according to the first confidence level information and the reference confidence level information, which may include: the network side may determine the confidence level of the fused target element according to the first confidence level information. degree information (hereinafter referred to as the second confidence degree information), and the fused reference confidence degree information is determined according to the reference confidence degree information. Finally, the network side can determine the change confidence of the target element according to the second confidence information and the fused reference confidence information.

The fused reference confidence level information may include one or more of the following: confidence level information of the fused reference element, fused first joint confidence level information (also referred to as fourth joint confidence level information), The fused second joint confidence information (which may also be referred to as the fifth joint confidence information), or the fused third joint confidence information (which may also be referred to as the sixth joint confidence information).

It can be understood that, the second confidence level information and the fused reference confidence level information may also have various representation forms, such as probability or numerical value.

Correspondingly, the confidence information of the fused map elements may be a second confidence set, and the second confidence set may be determined by the network side by fusing at least one first confidence set, and the second confidence set may be used for The network side determines the degree of confidence that the target element changes (eg, the change probability of the target element). The first confidence level set may be a confidence level set of map elements reported by at least one terminal device to the network side. For the specific implementation of the first confidence level set, reference may be made to the relevant content in S203 above, which will not be repeated here.

In a possible design solution, the second confidence level set may also be a joint probability covariance matrix. Taking the first confidence level set as the joint probability covariance matrix as an example, the specific implementation manner of the second confidence level set is described in detail.

Exemplarily, the second set of confidence levels may be a joint probability covariance matrix. The fused first confidence information may be the second probability, the confidence information of the fused reference element may be the second reference probability, the fourth joint confidence information may be the fourth joint probability, and the fifth joint confidence The information may be the fifth joint probability, and the sixth joint confidence information may be the sixth joint probability.

The cloud can receive the first confidence level set Cov(P _v1 ) from the vehicle terminal 1, the first confidence level set Cov(P _v2 ) of the vehicle terminal 2, ... and the first confidence level set Cov(P v2 ) of the vehicle terminal n. _vn ), where n is a positive integer. The cloud can integrate the above-mentioned multiple first confidence sets {Cov(P _v1 ), Cov(P _v2 )...Cov(P _vn )} to obtain the second confidence set Cov(P), the second confidence set Cov(P ) can be:

Among them, Cov(P) is the second confidence set, P(A) and P(B) are the second probability of the target element, P(C) and P(D) are the second reference probability of the reference element, P(BA) and P(AB) are the sixth joint probability between target elements after cloud fusion, P(DC) and P(CD) are the fifth joint probability between cloud fusion reference elements, P(CA), P(AC), P(BC), P(CB), P(DA), P(AD), P(DB), P(BD) are the target elements and reference elements after cloud fusion The fourth joint probability of . For a specific implementation manner of the second confidence level set, reference may be made to the above-mentioned specific implementation manner of the first confidence level set, which will not be repeated here.

It should be noted that the fused second confidence level set may include: a second probability, a second reference probability, a fourth joint probability, a fifth joint probability, and a sixth joint probability.

Exemplarily, the second probability in the second confidence level set may be determined according to the first probability of the target element, the second reference probability in the second confidence level set may be determined according to the first reference probability of the reference element, and the second confidence level may be determined according to the first reference probability of the reference element. The fourth joint probability in the set may be determined according to a plurality of first joint probabilities of the reference element and the target element, the fifth joint probability in the second probability set may be determined according to a plurality of second joint probabilities between the reference elements, and the second joint probability The sixth joint probability in the probability set may be determined from a plurality of third joint probabilities among the target elements. The specific implementation manner of the network side fusion is further described below.

First, the network side can integrate the confidence information uploaded by the terminal device by means of diversity calculation, which is described below with reference to several examples.

In a possible design solution, the first confidence level information may be the first probability, and the network side may determine the second confidence level information according to the first confidence level information, which may include: the network side may determine the second confidence level information according to the first probability and the first probability. The preset criterion determines the second probability of the target element. Wherein, the first preset criterion can satisfy:

P(X)=1-[1- _Pv1 (X)]×[1- _Pv2 (X)]×…×[1- _Pvn (X)];

Among them, P _vn (X) is the nth first probability of the target element, n is a positive integer less than or equal to Q ₁ , Q ₁ is the number of first probabilities, and P(X) is the second probability of the target element .

It can be understood that, in this example, the parameter X in the above-mentioned first preset criterion may be the target element. In the diversity calculation, the number of terminal devices reporting the first confidence level set can affect the confidence level of the target element. As the number of terminal devices reporting the first confidence set increases, the number of first probabilities received by the network side will also increase, and the second probability of obtaining the target element after fusion by the network side may also increase accordingly. In this way, by means of diversity calculation in the first preset criterion, it can be ensured that the greater the number of first probabilities fused, the greater the credibility of the target element, thereby improving the accuracy of network-side evaluation.

Similarly, the network side can also fuse the reference confidence information of the reference elements by using the above diversity calculation method.

For example, if the confidence information is a probability, the network side determines the reference confidence information of the fused reference element according to the reference confidence information, which may include: the network side may determine the fused reference element according to the reference confidence information and the first preset criterion. The reference confidence information for the reference element of .

In some examples, the above-mentioned reference confidence information may include confidence information of the reference element, and the confidence information of the reference element may be the first reference probability of the reference element. The parameter X in the above-mentioned first preset criterion may be the reference element, P _vn (X) may be the nth first reference probability of the reference element, n is a positive integer less than or equal to Q ₁ , and Q ₁ is the first reference The number of probabilities, P(X) is the second reference probability of the reference element.

In still other examples, the above-mentioned reference confidence information may include first joint confidence information, such as a first joint probability, of the target element and the reference element. The parameter X in the above-mentioned first preset criterion can be the combination of the target element and the reference element, P _vn (X) can be the nth first joint probability of the target element and the reference element, and n is a positive value less than or equal to Q ₁ . Integer, Q ₁ is the number of the first joint probability, P(X) is the fourth joint probability of the target element and the reference element.

In still other examples, the above-mentioned reference confidence information may include second joint confidence information, such as a second joint probability, between every two reference elements in the plurality of reference elements. The parameter X in the above-mentioned first preset criterion may be a combination of two reference elements in the plurality of reference elements, and P _vn (X) may be the nth between every two reference elements in the plurality of reference elements. Two joint probabilities, n is a positive integer less than or equal to Q ₁ , Q ₁ is the number of second joint probabilities, and P(X) is the fifth joint probability of multiple reference elements.

In still other examples, the parameter X in the above-mentioned first preset criterion may be the combination of any two target elements in the multiple target elements, and P _vn (X) may be the difference between two target elements in the multiple target elements. The nth third joint probability, n is a positive integer less than or equal to Q ₁ , Q ₁ is the number of third joint probabilities, and P(X) is the sixth ratio between two target elements among the multiple target elements Joint probability.

In this way, by means of diversity calculation in the first preset criterion, it can be ensured that the greater the number of fused reference confidence information, the greater the reliability of the reference element, thereby improving the accuracy of the evaluation based on the reference element on the network side. For a specific implementation manner of the first preset criterion, reference may be made to the specific implementation manner of the above-mentioned network-side fusion of the first probability, which will not be repeated here.

Secondly, the network side can also use a simple path to process the fused confidence information. This simple path can characterize the correspondence between target elements and reference elements in graph theory. The following takes the second confidence level information as an example to describe in detail a specific implementation manner in which the network side processes the fused confidence level information according to the simple path.

In a possible design scheme, the network side may determine the change confidence level information of the target element according to the second confidence level information and the fused reference confidence level information, which may include: the network side may determine the change confidence level information of the target element according to the fused reference confidence level information and The number of reference elements is used to determine the third confidence level information of the target element, and the change confidence level of the target element is determined according to the third confidence level information and the fused reference confidence level information.

The following describes how to determine the third confidence information of the target element by taking the second confidence information as an example of the second probability. Correspondingly, the network side may determine the third confidence level information of the target element according to the second preset criterion and the second probability, and in this case, the third confidence level information may be the third probability. Wherein, the second preset criterion can satisfy:

P(X)'=1-[1-P(X)] ^j ;

Among them, P(X) is the second probability of the target element, P(X)' is the third probability of the target element, and j is the number of reference elements corresponding to the target element.

Exemplarily, the number of reference elements may represent the number of correspondences between target elements and reference elements, and in graph theory may represent the number of simple paths between the target elements and the reference elements, that is, the degree of the target elements. In graph theory, the number of simple paths between the target element and the reference element affects the credibility of the target element. The more simple paths between the target element and the reference element, the higher the credibility of the target element. In this way, the network side can increase the reliability of the target element through the number of simple paths between the target element and the reference element, thereby improving the accuracy of the second confidence level information of the target element fused by the network side.

Similarly, the network side can also process the second reference confidence information of the fused reference element by using the above simple path method, that is, the number of simple paths between the target element and the reference element will also affect the reliability of the reference element. Therefore, the confidence level information of the reference element (eg, the second reference confidence level information) can be processed by using the above-mentioned second preset criterion to increase the confidence level of the reference element.

It can be noted that, before fusing the confidence information reported by at least one terminal device, for example, before fusing the confidence information by means of diversity calculation, the network side may use a simple path method to pre-process the confidence information reported by the terminal device ( For example, the first confidence level information, the confidence level information of the reference element), the specific implementation of using the simple path to process the confidence level may refer to the above-mentioned second preset criterion, which will not be repeated here.

Furthermore, the network side can pre-process the confidence information reported by the terminal device by using a simple path, and the terminal device can also pre-process the confidence information of the map element by using the above simple path before reporting, thereby increasing the reliability of the map element. degree of confidence. The embodiment of the present application does not limit the execution subject that pre-processes the confidence information of the map element.

In a possible design solution, the above-mentioned change confidence may be the second confidence information of the target element or the fourth conditional confidence information of the target element.

The fourth conditional confidence level information of the target element is determined according to the fused reference confidence level information and the second confidence level information.

Exemplarily, the above-mentioned change confidence level may be used to represent the confidence level of the change of the target element. The above-mentioned fourth conditional confidence level information may be the possibility that the target element is credible if the reference element is credible.

It can be understood that, after fusing the confidence information of the reported map elements, the network side can determine the change confidence of the target element in the following two ways, which will be described separately below.

In the first manner, the network side can use the second confidence level information of the fused target element as the change confidence level of the target element, and evaluate whether the target element has changed according to the change confidence level.

Taking the above-mentioned second confidence level set as an example, the above-mentioned second confidence level information may be the second probability of the target element, the above-mentioned change confidence level may be the change probability of the target element, and the target element may be the map element A and the map element B, P Both (A) and P(B) are the second probabilities of the target element, and the change probabilities of the target element may be P(A) and P(B). The network side can evaluate whether map element A and map element B have changed according to P(A) and P(B).

In the second manner, the network side may determine the fourth conditional confidence information of the target element according to the fusion confidence information of the reference element and the second confidence information of the target element, and use the fourth conditional confidence information as the target element. , and evaluate whether the target element has changed according to the change confidence.

Exemplarily, the fourth conditional confidence level information may be used to represent the confidence level of the target element under the condition that the reference element is credible. The fourth conditional confidence information of the target element can use the second reference confidence information of the reference element as a reference, and then measure the credibility of the target element, which can reduce the impact of different calculation rules in the terminal device on the credibility of the target element. In this way, the credibility of the target element can be more accurately reflected, thereby improving the accuracy of the network-side evaluation.

Optionally, the fourth conditional confidence level information of the target element is related to the influence factor of the reference element on the target element. In this way, the impact factor can be used to characterize the relationship between the reference element and the target element, so that the confidence level information of the fourth condition can more accurately reflect the reliability of the target element and improve the accuracy of the evaluation.

Further, the fourth conditional confidence information may include two different types of conditional probabilities, such as a third conditional probability and a fourth conditional probability, and the third conditional probability may be the conditional probability of one map element compared to another map element, The fourth conditional probability may be a conditional probability of one map element compared to another plurality of map elements. For example, the conditional probability of map element A compared to map element B refers to the probability that map element A changes under the condition that map element B changes. Similarly, the conditional probability of one map element compared to other multiple map elements may be: the probability that the map element changes under the condition that the other multiple map elements change. In the following, the third conditional probability and the fourth conditional probability of the target element are taken as examples for description.

For the third conditional probability of the target element, the network side may determine the third conditional probability of the target element according to the third preset criterion, the second probability and the second reference probability. Among them, the third preset criterion can satisfy:

P(X|Y)=P(X)+[1-P(X)]×P(Y)×a;

where X is the target element, Y is the reference element, P(X|Y) is the third conditional probability of the target element, P(X) is the second probability of the target element, and P(Y) is the second reference of the reference element Probability, a is the influence factor of the reference element on the target element, a is a real number greater than 0 and less than or equal to 1.

Exemplarily, the third conditional probability of the target element may be the conditional probability of the target element compared to a reference element. For example, when the target elements are map element A and map element B, and the reference element is map element C, the third conditional probability of map element A may include P(A|C), and the third conditional probability of map element B may include P (B|C).

It can be understood that, based on the correlation between the target element and the reference element, the credibility of the reference element can affect the credibility of the target element, that is, the credibility of the reference element increases, and the credibility of the target element also increases with the the improvement. In this way, the third conditional probability of the target element may increase with the increase of the second reference probability of the reference element, so that the third conditional probability of the target element may more accurately reflect the reliability of the target element.

Similarly, when there are multiple target elements, the credibility levels among the multiple target elements will also affect each other. The multiple target elements may include a first target element and a second target element. When calculating the fourth conditional confidence information of the first target element, the second target element may also be used as a reference element of the first target element, so that the network side can According to the influence of the credibility of the second target element on the credibility of the first target element, the fourth conditional confidence information corresponding to the first target element is calculated.

For example, when the target elements are map element A and map element B, the third conditional probability of map element A may further include P(A|B), and the third conditional probability of map element B may further include P(B|A).

Similarly, when there are multiple reference elements, the credibility of multiple reference elements will also affect each other, so the network side can use the above-mentioned third preset criterion to calculate the third conditional probability of the reference element, thereby improving the The confidence level of the third conditional probability of the reference element. For the specific implementation manner of determining the third conditional probability of the reference element by the network side, reference may be made to the specific implementation manner of determining the third conditional probability of the target element above, which will not be repeated here.

The influence factor a may be determined by the network side according to the correlation between the reference element and the target element, and the value of the influence factor may be configured or preset by the network side, or may be set by a protocol. The embodiments of the application do not limit the specific implementation manner of acquiring the impact factor by the network side.

For the above-mentioned fourth conditional probability, the network side may determine it according to the third conditional probability and the fourth joint probability.

Exemplarily, the fourth conditional probability may be the conditional probability of the target element compared to multiple reference elements. For example, when the target elements are map element A and map element B, and the reference elements are map element C, map element D, and map element E, the fourth conditional probability of map element A may include P(A|CD) and P(A |CDE), the fourth conditional probability of map element B may include P(B|CD) and P(B|CDE), and the fourth conditional probability of map element A and map element B may include P(AB|CD) and P (AB|CDE). For a specific implementation manner of the fourth conditional probability, reference may be made to the above-mentioned related content of the third conditional probability, which will not be repeated here.

It can be understood that, based on the correlation between the target element and the reference element, the credibility of multiple reference elements will also affect the credibility of the target element. In this way, when there are multiple reference elements, the network side can determine, according to the above-mentioned third conditional probability, the probability that the target element is credible when multiple reference elements are credible, that is, the fourth conditional probability, so that the network side can follow up on the basis of The third conditional probability and the fourth conditional probability evaluate the target element more accurately and improve the accuracy of map update.

In addition, the network side can calculate and obtain the fourth conditional probability of the target element based on the third conditional probability and the fourth joint probability, using the existing conversion formula of the joint probability and the conditional probability and the conditional joint distribution decomposition formula. Wherein, the number of reference elements compared with the same target element is different, and the manner of determining the fourth conditional probability is also different. For example, the fourth conditional probability of the above-mentioned map element A may include a first sub-probability P(A|CD) and a second sub-probability P(A|CDE), and the network side determines the first sub-probability P(A|CD) and the first sub-probability P(A|CD) The two sub-probabilities P(A|CDE) behave differently. The specific implementation manner of determining the fourth conditional probability by the network side is described in detail below by taking the first sub-probability P(A|CD) and the second sub-probability P(A|CDE) as examples respectively.

For the first sub-probability P(A|CD), if the map element A is the target element, and the map element C and the map element D are the reference elements, the network side can calculate the value of the map element A according to the fourth preset criterion. The first sub-probability P(A|CD). Among them, the fourth preset criterion can satisfy:

where P(A|CD) is the first sub-probability of map element A, the first sub-probability is the fourth conditional probability of map element A compared to map element C and map element D, and P(ACD) is map element A , the joint probability of map element C and map element D, P(CD) is the sixth joint probability of map element C and map element D; P(AC|D) is map element A and map element C compared to map element D , P(D) is the second probability of map element D, P(A|D) is the third conditional probability of map element A compared to map element D, P(C|D) is the phase of map element C Compared to the third conditional probability of map element D.

For the second sub-probability P(A|CDE), if map element A is the target element, and map element C, map element D, and map element E are reference elements, the network side can calculate according to the fifth preset criterion to obtain The second sub-probability P(A|CDE) of map element A. Among them, the fifth preset criterion can satisfy:

where P(A|CDE) is the second sub-probability of map element A, and the second sub-probability is the fourth conditional probability of map element A compared to map element C, map element D, and map element E, P(ACDE) is the joint probability of map element A, map element C, map element D and map element E, P(CDE) is the joint probability of map element C, map element D and map element E, P(AC|DE) is map element A and map element C compared to the conditional probability of map element D and map element E, P(A|DE) is the first sub-probability of map element A, P(C|DE) is the first sub-probability of map element C, Both P(A|DE) and P(C|DE) can be determined according to the above-mentioned fourth preset criterion, P(CD|E) is the conditional probability of map element C and map element D compared to map element E, P( E) is the second probability of map element E, P(C|E) is the third conditional probability of map element C compared to map element E, and P(D|E) is the third conditional probability of map element D compared to map element E The third conditional probability.

It should be noted that the conditional probability may also include a fifth conditional probability of a plurality of map elements compared to another map element, such as the above-mentioned conditional probability P(AC|D of map element A and map element C compared to map element D ). The conditional probability may also include a sixth conditional probability of multiple map elements compared to other multiple map elements, such as the above-mentioned conditional probability P(AC|DE of map element A and map element C compared to map element D and map element E) ). The embodiments of the present application do not limit the specific implementation manner of the conditional probability.

It can be understood that the network side can evaluate whether the target element has changed based on the change confidence of the target element (such as the second probability, the second conditional probability, the third conditional probability, the fourth conditional probability, etc.). The network side can determine the credibility of the target element when the reference element is credible, so as to determine whether the credibility of the change of the target element is acceptable, and then update the map according to the reliable change information of the target element. There are various manners for evaluating the target element on the network side, and the manner for evaluating the target element provided in the embodiment of the present application will be described with reference to two specific implementation manners.

In the first specific implementation manner, there may be multiple reference elements. Correspondingly, the above S204 may include: acquiring second joint confidence information between multiple reference elements, and determining that the target element has changed according to the confidence information, reference confidence information and second joint confidence information of the target element .

Exemplarily, the second joint confidence level information may be used to represent the joint confidence level of the corresponding multiple reference elements. The network side may acquire the second joint confidence level information between multiple reference elements according to the reference confidence level information; the network side may also receive the second joint confidence level information from at least one terminal device. This embodiment of the present application does not limit the specific implementation manner in which the network side obtains the second joint confidence level information.

Specifically, the above-mentioned second joint confidence information may be the second joint probability of multiple reference elements. Correspondingly, the network side may determine the fifth joint probability of the multiple reference elements according to the second joint probability. If the fifth joint probability between the reference elements is greater than the first probability threshold, the network side may determine that the target element has changed.

In this way, when the joint credibility of the reference elements is relatively high, the network side can consider that the credibility of the target element changes is also high based on the correlation between the target element and the reference element, so that the target can be accurately determined. Elements change.

In the second specific implementation manner, there may be multiple change confidence levels, and the network side determines that the target element has changed according to the change confidence levels, which may include: the network side selects from the multiple change confidence levels to satisfy the first preset condition at least one change confidence level, and according to the at least one change confidence level, it is determined that the target element has changed.

Exemplarily, the first preset condition is related to the change confidence of the target element, and the change confidence that satisfies the first preset condition may be used to represent the credibility of the change of the target element when the first preset condition is met, and the network The side can adjust the criterion for evaluating whether the target element has changed by adjusting the first preset condition of the target confidence. In this way, based on the joint confidence information between the reference elements, in the case that the reference elements are credible, the network side can accurately determine which target element has changed according to the confidence information of the target element and the reference confidence information. Improve the accuracy of map updates.

Optionally, the at least one change confidence level that satisfies the first preset condition may be the largest one among multiple change confidence levels. That is to say, the network side can determine which target element has the highest reliability according to the maximum change confidence, so as to accurately determine that the target element has changed, thereby improving the accuracy of map update.

Combining the above two scenarios, the network side may determine that the target element has changed according to the second joint confidence level information between every two reference elements in the multiple reference elements and the change confidence level satisfying the first preset condition. In the following, taking the change confidence as the change probability as an example, a specific implementation manner in which the first preset condition is that the target confidence is the maximum change confidence of the target element will be described in detail.

Specifically, the second joint confidence information may be the second joint probability of multiple reference elements, the first confidence threshold may be the first probability threshold, and the target confidence may be the target probability of the target element. Correspondingly, the network side may determine the fifth joint probability of multiple reference elements according to the second joint probability, and determine the maximum change probability as the target probability. If the fifth joint probability between the reference elements is greater than the first probability threshold, the network side may determine that the target element corresponding to the target probability changes.

Exemplarily, the target probability can be used to characterize the maximum confidence level of the target element. Suppose that map element A is the target element, map element C and map element D are reference elements, and the conditional probability of map element A may include P(A|C), P(A|D) and P(A|CD), Assuming that the target probability is P(A|CD), it means that when the map element C and the map element D are credible, the map element A has the highest degree of reliability. Assuming that the target probability is P(A|C), it means that When map element C is credible, map element A has the highest degree of credibility.

It can be understood that the network side can use the MLE strategy to evaluate the target element, that is, it is considered that the target element corresponding to the maximum change probability is a credible target element, and the target element has changed. Specifically, if the fifth joint probability between the reference elements is greater than or equal to the first probability threshold, the network side can determine that the reference element corresponding to the target element is credible, so that based on the correlation between the reference element and the target element, the network side It can be determined that the credibility of the target element is relatively high, and then the above MLE strategy can be used to determine that the target element corresponding to the target probability is credible, that is, if the target element changes, the network side can update the map according to the change information of the target element.

If the fifth joint probability between the reference elements is less than the first probability threshold, the network side can determine that the reference element corresponding to the target element is unreliable or has a low degree of reliability, so based on the correlation between the reference element and the target element, the network The network side may determine that the reliability of the target element is low or the target element is unreliable, and the network side may not update the map according to the change information of the target element.

Similarly, the above MLE strategy can be applied to Scenario 1 and Scenario 2. Scenario 1 can be a scenario with one target element, and Scenario 2 can be a scenario with multiple target elements. Scenarios 1 and 2 are used as examples for description below.

In scenario 1, there is one target element, and the network side may determine that the target element has changed when the fifth joint probability of the reference element is greater than the first probability threshold. Further, the network side can also determine which target elements are credible according to the target probability. For example, map element A is the target element, map element C, map element D and map element E are reference elements, and the change probability of map element A may include P(A|C), P(A|D), P(A |E), P(A|CD), P(A|CE), P(A|DE) and P(A|CDE), the network side can determine the corresponding probability of multiple change according to the sixth preset criterion The target probability P _max1 is determined, thereby determining that the target element corresponding to the target probability P _max1 changes. The above sixth preset criterion can satisfy:

Among them, P _max1 is the target probability of the target element, P(A|C), P(A|D), P(A|E), P(A|CD), P(A|CE), P(A| DE) and P(A|CDE) are the change probabilities of the target element. In this preset rule, the target probability of the target element is the maximum value among the change probabilities of multiple target elements, and P(CDE) is the change probability of the reference element. The fifth joint probability, P _t1 is a preset or configured first probability threshold.

In this way, when the fifth joint probability P(CDE) is greater than or equal to the first probability threshold P _t1 , the network side can determine that the information of map element C, map element D and map element E is more credible, thereby determining map element A There is a high degree of confidence that a change has occurred. Further, assuming that the target probability P _max1 =P(A|CD), the network side can also determine that the map element A is credible when the map element C and the map element D are credible.

However, when the fifth joint probability P(CDE) is less than the first probability threshold P _t1 , the network side may determine that map element C, map element D and map element E are not credible, and the network side may consider that map element A is not credible Or map element A is less believable.

In scenario 2, there are multiple target elements, and the network side may determine that the target element corresponding to the target probability changes when the fifth joint probability of the reference element is greater than the first probability threshold. For example, map element A and map element B are target elements, map element C, map element D and map element E are reference elements, and the change probability of map element A may include P(A|C), P(A|D) , P(A|E), P(A|CD), P(A|CE), P(A|DE) and P(A|CDE), the change probability of map element B may include P(B|C) , P(B|D), P(B|E), P(B|CD), P(B|CE), P(B|DE), and P(B|CDE), map element A and map element B The change probabilities of can include P(AB|C), P(AB|D), P(AB|E), P(AB|CD), P(AB|CE), P(AB|DE), and P(AB |CDE), the network side may determine the target probability P _max2 corresponding to the multiple conditional probabilities according to the seventh preset criterion, so as to determine that the target element corresponding to the target probability P _max2 changes. The above seventh preset criterion can satisfy:

In this way, when the fifth joint probability P(CDE) is greater than or equal to the first probability threshold P _t2 in scenario 2, the network side can accurately determine that the corresponding target element changes according to the target probability P _max2 .

For example, if the target probability P _max2 =P(A|CE), the network side can determine that the change information of map element A is more credible under the condition that map element C and map element E are credible, so as to determine whether map element A has changed. High reliability. For another example, the target probability P _max2 =P(B|CDE), the network side can determine that the change information of map element B is credible under the condition that map element C, map element D and map element E are credible, so as to determine the map element B changes. For another example, if the target probability P _max2 =P(AB|E), the network side can determine that when the map element E is credible, the change information of the map element A and the map element B are both credible, thereby determining that the map element A and the map element are credible. Map element B is changed.

It should be noted that this embodiment of the present application does not limit the specific number of the fifth joint probability of reference elements. For example, the fifth joint probability may include one or more of the following probabilities: P(CDE), P(CD), P (CE) or P(DE). Correspondingly, the first probability threshold may be one or multiple, and when the first probability threshold is multiple, the first probability thresholds corresponding to different fifth joint probabilities may be the same or different.

Similarly, when there are multiple fifth joint probabilities, the network side may determine that the target element corresponding to the target probability changes when the plurality of fifth joint probabilities satisfy the first condition. The first condition may include one of the following conditions: all fifth joint probabilities are greater than or equal to the first probability threshold, or a fifth joint probability greater than or equal to the first probability threshold exists among the plurality of fifth joint probabilities. The network side may also randomly select a fifth joint probability and compare it with the corresponding first probability threshold. The embodiment of the present application does not limit the specific implementation manner of evaluating the fifth joint probability by the network side.

It should be noted that, the first preset condition of the target confidence may be set according to the MLE strategy, and may also be set according to other strategies, and the embodiment of the present application does not limit the specific implementation of the first preset condition of the target confidence.

In combination with the above-mentioned first specific implementation manner and the second specific implementation manner, the network side can use the MLE strategy to evaluate the target element, and the network side can also use the reference element corresponding to the target element and the change confidence to evaluate the target element. The following third specific implementation manner is described in detail below in conjunction with the reliability of the region where the target element is located.

In a third specific implementation manner, the network side determines that the target element has changed according to the change confidence, which may include: if the change confidence of the target element is greater than or equal to the second confidence threshold, the network side may determine that the target element has changed. Variety.

Exemplarily, the change confidence may be the change probability of the target element, and the change probability may include one or more of the following probabilities: the above-mentioned second probability, or the above-mentioned third conditional probability, or the above-mentioned fourth conditional probability, or the above-mentioned fifth conditional probability. Conditional probability, or the sixth conditional probability above. Correspondingly, the second probability threshold may be one or multiple, and when the second probability threshold is multiple, the second probability thresholds corresponding to different change probabilities may be the same or different. For example, the third conditional probability may correspond to a second probability threshold, and the fourth, fifth and sixth conditional probability may correspond to another second probability threshold.

The network side can determine that the target element corresponding to the change probability greater than or equal to the second confidence threshold is credible through the comparison result between the change confidence and the second confidence threshold, so that the network can determine that the target element has changed, and can Update the map based on this target element. The network side may also determine that the target element corresponding to the change confidence less than the second confidence threshold is untrustworthy or has a low degree of confidence, so that the network side is difficult to determine whether the target element has changed, and the map may not be updated according to the target element.

For example, it is assumed that the change confidence of the target element is the change probability, the second confidence threshold is the second probability threshold, the map elements A and B are the target elements, the map element C is the reference element, and the change of the map element A The probability may include P(A|C), the change probability of map element B may include P(B|C), and the change probability of map element A and map element B may include P(AB|C). If P(A|C) is greater than or equal to the second probability threshold, the network side may determine that the map element A is credible, thereby determining that the map element A has changed. If P(AB|C) is greater than or equal to the second probability threshold, the network side can determine that map element A and map element B are credible, and thus determine that both map element A and map element B have changed. If P(A|C), P(B|C), and P(AB|C) are all less than the second probability threshold, the network side may determine that map element A and map element B are unreliable or have a low degree of reliability.

It can be understood that, when there are multiple change probabilities of the target element, there may be multiple conditions for the network side to evaluate the target element. The network side may determine that the target element has changed when all change probabilities of the target element are greater than or equal to the second probability threshold. The network side may also determine that the target element has changed when there is a change probability greater than or equal to the second probability threshold among the multiple change probabilities of the target element. The network side can also randomly select a change probability and compare it with the second probability threshold, so as to evaluate that the target element changes. The embodiment of the present application does not limit the specific implementation manner of evaluating the target element on the network side.

Optionally, the above-mentioned reference element may be a map element whose reference confidence information satisfies the second preset condition. In other words, the reference confidence information may satisfy the second preset condition. Specifically, the reference confidence information may satisfy the second preset condition, the conditional confidence information may satisfy the second preset condition, or the joint confidence information may satisfy the second preset condition. Correspondingly, the method shown in FIG. 2 may further include: the terminal device determines at least one reference element, where the reference element is a map element whose reference confidence information satisfies the second preset condition.

Exemplarily, the second preset condition may be related to the reference confidence level information, and the confidence level of the reference element is adjusted by adjusting the second preset condition. For example, the second preset condition may be that the fused reference confidence information is greater than or equal to the third confidence threshold, which means that the reliability of the reference element is relatively high, and the second preset condition may also be the reference element and the target. The coordinate distance of the element in the map is less than or equal to the distance threshold, which means that the correlation between the reference element and the target element is high, so the reliability of the reference element is high.

Optionally, the second preset condition may be that the fused reference confidence information is greater than or equal to the third confidence threshold. That is to say, based on the correlation between the reference element and the target element, the reliability of the reference element is high, and the network side can think that the change of the target element has a high degree of reliability, so that it can be accurately determined that the change of the target element is more reliable. information, thereby improving the accuracy of map updates.

Further, the method shown in FIG. 2 may further include: if the number of reference elements satisfying the second preset condition reaches the first number threshold, the network side may determine that the target element has changed.

Exemplarily, based on the correlation between the reference element and the target element, the greater the number of reference elements that meet the second preset condition, it can be understood that the region where the target element is located has a higher degree of reliability, and the second preset condition is satisfied. A region in which the number of reference elements of the condition is greater than or equal to the first number threshold can be considered as a high confidence region. Conversely, the less the number of reference elements that meet the second preset condition, the lower the reliability of the area where the target element is located, and the area where the number of reference elements that meet the second preset condition is less than the first threshold value can be considered as low. confidence zone.

For example, it is assumed that the fused reference confidence information is the second reference probability including the reference element, the third confidence threshold is the third probability threshold, and map element A and map element B are target elements, map element C, map element Element D and map element E are reference elements, the second reference probability of map element C is 0.6, the second reference probability of map element D is 0.7, the second reference probability of map element E is 0.8, and the third probability threshold is 0.7. Therefore, the reference elements that satisfy the second preset condition may be map element D and map element E, and the number of reference elements that satisfy the second preset condition is 2. If the first number threshold is also 2, the map element A is indicated. The area where map element B and map element B are located is a high-confidence area, so the network side can determine that both map element A and map element B are trustworthy, and both map element A and map element B have changed. However, if the number of reference elements that satisfy the second preset condition is less than the first number threshold, the network side may confirm that map element A and map element B have a low or unreliable degree.

Optionally, the network side may evaluate whether the target element has changed in combination with the number of reference elements that satisfy the second preset condition and the change confidence of the target element.

Specifically, the method shown in FIG. 2 may further include: when the number of reference elements that satisfy the second preset condition is greater than or equal to the first number threshold, and the change confidence of the target element is greater than or equal to the second confidence threshold , the network side can determine that the target element has changed. The second preset condition may be that the second reference confidence of the reference element is greater than or equal to the third confidence threshold.

For example, it is assumed that the fused reference confidence information includes the second reference probability of the reference element, the third confidence threshold is the third probability threshold, the change confidence of the target element is the change probability, and the second confidence threshold is the second probability threshold, and map element A and map element B are target elements, map element C, map element D, and map element E are reference elements, the second reference probability of map element C is 0.6, and the second reference probability of map element D is 0.7, the second reference probability of map element E is 0.8, and the third probability threshold is 0.7, then the number of reference elements that satisfy the second preset condition is 2, and if the first number threshold is also 2, it means that map element A is and the area where map element B is located is a high-confidence area. And, if the change probability P(A|CE) of the map element A is greater than or equal to the second probability threshold, the network side may determine that the map element A has changed. If the change probability P(AB|CDE) of map element A and map element B is greater than or equal to the second probability threshold, the network side can determine that both map element A and map element B are credible, and both map element A and map element B occur Variety. However, if the number of reference elements satisfying the second preset condition is less than the first number threshold, or the change probabilities are both less than the second probability threshold, the network side confirms that map element A and map element B have a low degree of reliability or cannot be letter.

In this way, when the area where the target element is located is a high-confidence area, the network side can accurately determine which target element has changed according to the comparison result between the second confidence threshold and the change confidence, thereby improving the accuracy of map update .

It should be noted that the second confidence threshold may be one or multiple. When there are multiple second confidence thresholds, the second confidence thresholds corresponding to different changed confidences may be the same or different. Taking the change confidence as the change probability of the target element and the second confidence threshold as the second probability threshold as an example, the change probability may include the third conditional probability, the fourth conditional probability, the fifth conditional probability and the sixth conditional probability, the target element The third conditional probability and the fourth conditional probability of can correspond to a second probability threshold, and the fifth conditional probability and the sixth conditional probability of the target element can correspond to another second probability threshold. Similarly, the number of reference elements may be one or multiple, and correspondingly, the third probability threshold may be one or multiple. When the third probability threshold is multiple, the reference confidence levels of different reference elements The corresponding third probability thresholds may be the same or different.

It can be noted that the embodiment of the present application does not limit the steps of comparing the number of reference elements and the first number threshold, and the order of comparing the change confidence level and the second confidence level threshold at the network side.

Furthermore, the above-mentioned first confidence threshold, second confidence threshold, third confidence threshold and first quantity threshold may be configured on the network side or preset, or may be set by a protocol. This application implements The example does not limit the specific implementation of the first confidence threshold, the second confidence threshold, the third confidence threshold and the first quantity threshold.

Further, the network side can also determine the change parameter of the target element according to the change confidence of the target element and the relevant parameters of the target element reported by at least one terminal device, and the change parameter of the target element can be used to update the electronic map.

S205, the network side sends the updated electronic map to at least one terminal device. Correspondingly, the terminal device receives the updated electronic map from the network side.

The updated electronic map is determined by the network side according to the changed target element.

Exemplarily, if a credible target element, that is, a changed target element, is determined in the above S204, the network side can update the electronic map according to the changed target element, so that the network side can send the updated electronic map to the terminal device. map, update the electronic map in the terminal device in time, so that the terminal device can accurately realize the navigation function and/or the automatic driving function according to the updated electronic map. If it is determined in the above S204 that the target element is not credible or the degree of credibility is low, the network side may not update the electronic map according to the target element, and will not send the updated electronic map to the terminal device, that is, S205 is an optional step .

It can be understood that, when there are multiple terminal devices, the network side can receive target elements reported from multiple terminal devices. Since the information of the same target element reported by different terminal devices may be different, after determining that the target element has changed, the network side can fuse the information of the same target element reported by multiple terminal devices based on the change confidence of the target element according to the preset fusion rule. A variety of information is obtained, the change parameters of the target element are obtained, and the electronic map is updated with the change parameters.

For example, the preset fusion rule may be to determine the average value of multiple pieces of information of the same target element as the information of the fused target element. Assuming that both vehicle 3 and vehicle 4 have reported the newly added traffic light in the north direction at the same intersection, the information of the target element A reported by vehicle 3 is that the newly added traffic light is located 10 meters north of the above-mentioned intersection, and the target reported by vehicle 4 The information of the element is that the newly added traffic light is located 30 meters north of the above-mentioned intersection, then the network side can determine the change parameter of the target element based on the change confidence of the target element through the preset fusion rule as the newly added traffic light is located above. 20 meters north of the intersection to update the map with the changing parameters of the target element.

There may be one or more preset fusion rules on the network side, and the embodiment of the present application does not limit the specific implementation manner of the preset fusion rules.

It should be noted that the network side can send the updated electronic map to the terminal device by means of incremental update, that is, only the map elements that need to be updated are sent to the terminal device, and the network side can also send the update to the terminal device by changing the update method. The updated electronic map is to send the complete updated electronic map to the terminal device. In addition, the network side can send the updated electronic map to the terminal device by unicast, or can send the updated electronic map by broadcast. The embodiments of the present application do not limit the specific implementation of sending the electronic map by the network side.

Based on the map data processing method shown in FIG. 2 , the network side can evaluate whether the target element has changed according to the first confidence level of the target element reported by the terminal device and the first reference confidence level of the reference element associated with the target element, And update the target element in the map based on the evaluation result. That is to say, based on the relationship between the reference element and the target element, the reliability of the change of the target element can be evaluated, which can reduce the adverse effects of different calculation rules of different terminal devices on evaluating and updating the target element, and can solve the problem of relying only on The problem of low accuracy of map element evaluation and update caused by the confidence of a single element reported by the terminal device, so as to improve the accuracy of map update.

In addition, the confidence of a single map element is also affected by the device error of the terminal device itself, such as the terminal positioning error term, the external parameter calibration error term, and the measurement error term of the sensor. The map data processing method shown in FIG. 2 can also comprehensively evaluate the confidence of multiple map elements reported by the terminal device, so as to reduce the above-mentioned adverse effects on the confidence of the map elements due to the device error of the terminal device itself, thereby improving the evaluation accuracy. accuracy.

It should be understood that any one of the first preset criteria to the seventh preset criteria on the network side in this embodiment of the present application may also be used for the terminal device, which mainly depends on the processing capability of the terminal device. When these preset criteria are used for When a terminal device is used, optionally, the terminal device may report the probability after fusion based on the above criteria to the network side, which is not specifically limited here.

The map data processing method provided by the embodiment of the present application has been described in detail above with reference to FIG. 2 . The apparatus for executing the map data processing method provided by the embodiments of the present application will be described in detail below with reference to FIG. 4 to FIG. 5 .

Exemplarily, FIG. 4 is a first structural schematic diagram of a map data processing apparatus provided by an embodiment of the present application. As shown in FIG. 4 , the map data processing apparatus 400 includes: a processing module 401 and an acquisition module 402 . For convenience of description, FIG. 4 only shows the main components of the map data processing apparatus.

In some embodiments, the map data processing apparatus 400 may be applied to the map data processing system shown in FIG. 1 to perform the functions on the network side in the map data processing method shown in FIG. 2 .

Wherein, the obtaining module 402 can be used to obtain the confidence information of the map element. The map element may include a target element and a reference element, and the confidence information may include confidence information and reference confidence information of the target element. The reference confidence information may include at least one of confidence information of the reference element, joint confidence information of the target element and the reference element, or conditional confidence information of the target element and the reference element.

The processing module 401 may be configured to determine whether to update the map according to the confidence information of the map element.

Optionally, the confidence information of the map elements can be used to determine the confidence covariance matrix. For example, the confidence information of the map element is a confidence covariance matrix, or the confidence information of the map element is used to indicate the confidence covariance matrix, or the confidence information of the map element includes each element in the confidence covariance matrix, to determine the confidence covariance matrix by the receiver. The confidence covariance matrix may include the confidences of multiple map elements, and the multiple map elements may include target elements and reference elements, and the confidence covariance matrix may include the following formula:

Among them, Cov(P _v ) is the confidence covariance matrix, the diagonal element P(x) is the confidence of the xth map element, and P(x,y) is the xth map element relative to the yth map element. The joint confidence or conditional confidence of the element, the joint confidence information between the xth map element and the yth map element includes: the joint confidence of the xth map element relative to the yth map element, the xth map element The conditional confidence level information between the map element and the y-th map element includes: the conditional confidence level of the x-th map element relative to the y-th map element. Wherein, x=i, i+1,...,i+n; y=i, i+1,...,i+n; i and n are positive integers.

In a possible design solution, the acquisition module can also be used to acquire confidence information from multiple terminal devices. And, the confidence information of multiple terminal devices is fused to obtain the fused confidence information. The fused confidence information is the confidence information of the map element.

In one possible design, the target element is the map element that changes.

Optionally, the reference element may be a map element whose reference confidence information satisfies a preset condition.

Optionally, the acquisition module 402 may include a transceiver module (not shown separately in FIG. 4 ). The transceiver module may include a receiving module and a transmitting module (not shown separately in FIG. 4 ). The receiving module and the sending module are respectively used to implement the receiving function and the sending function of the map data processing apparatus 400 .

Optionally, the map data processing apparatus 400 may further include a storage module (not shown separately in FIG. 4 ), and the storage module stores programs or instructions. When the processing module 401 executes the program or instruction, the map data processing apparatus 400 can execute the map data processing method shown in FIG. 2 .

It should be noted that, the map data processing apparatus 400 may be the network side, or may be a chip or other components or components that can be arranged in the network side, which is not limited in this application.

Exemplarily, FIG. 5 is a second schematic structural diagram of a map data processing apparatus provided by an embodiment of the present application. As shown in FIG. 5 , the map data processing apparatus 500 includes: a processing module 501 and a transceiver module 502 . For convenience of explanation, FIG. 5 only shows the main components of the map data processing apparatus.

In some embodiments, the map data processing apparatus 500 can be applied to the map data processing system shown in FIG. 1 to perform the functions of the terminal device in the map data processing method shown in FIG. 2 .

Among them, the processing module 501 is used to determine the confidence information of the target element. The processing module 501 is further configured to determine reference confidence information.

The transceiver module 502 is configured to send confidence information and reference confidence information to the network side.

The reference confidence information may include at least one of: confidence information of the reference element, joint confidence information between the target element and the reference element, or conditional confidence information between the target element and the reference element.

In a possible design solution, the reference confidence level information further includes: joint confidence level information between multiple reference elements.

Further, the processing module 501 can also be used to determine the target element and the reference element. The target element is a map element that has changed, and the reference element is a map element whose reference confidence information satisfies a preset condition.

Optionally, the transceiver module 502 may include a receiving module and a sending module (not shown separately in FIG. 5 ). The receiving module and the sending module are respectively used to implement the receiving function and the sending function of the map data processing apparatus 500 .

Optionally, the map data processing apparatus 500 may further include a storage module (not shown separately in FIG. 5 ), where the storage module stores programs or instructions. When the processing module 501 executes the program or instruction, the map data processing apparatus 500 can execute the map data processing method shown in FIG. 2 .

It should be noted that the map data processing apparatus 500 may be a terminal device, or may be a chip (system) or other components or components that can be provided in the terminal device, which is not limited in this application.

It should be noted that the processing modules involved in each map data processing apparatus 500 shown in FIG. 5 may be implemented by processors or processor-related circuit components, and may be processors or processing units; The module can be implemented by a transceiver or a transceiver-related circuit component, and can be a transceiver or a transceiver unit. The following describes with examples.

Exemplarily, FIG. 6 is a third schematic structural diagram of a map data processing apparatus according to an embodiment of the present application. The map data processing apparatus may be a terminal device or a network side, or may be a chip (system) or other components or assemblies that may be provided on the terminal device or the network side. As shown in FIG. 6 , the map data processing apparatus 600 may include a processor 601 . Optionally, the map data processing apparatus 600 may further include a memory 602 and/or a transceiver 603 . Wherein, the processor 601 is coupled with the memory 602 and the transceiver 603, such as can be connected through a map data processing bus.

Below in conjunction with FIG. 6, each constituent component of the map data processing device 600 will be specifically introduced:

The processor 601 is the control center of the map data processing apparatus 600, which may be one processor, or may be a general term for multiple processing elements. For example, the processor 601 is one or more central processing units (CPUs), may also be a specific integrated circuit (application specific integrated circuit, ASIC), or is configured to implement one or more embodiments of the present application An integrated circuit, such as: one or more microprocessors (digital signal processor, DSP), or, one or more field programmable gate array (field programmable gate array, FPGA).

Optionally, the processor 601 may execute various functions of the map data processing apparatus 600 by running or executing software programs stored in the memory 602 and calling data stored in the memory 602 .

In a specific implementation, as an embodiment, the processor 601 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 6 .

In a specific implementation, as an embodiment, the map data processing apparatus 600 may also include multiple processors, such as the processor 601 and the processor 604 shown in FIG. 2 . Each of these processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU). A processor herein may refer to one or more devices, circuits, and/or processing cores for processing data (eg, computer program instructions).

The memory 602 is used for storing the software program for executing the solution of the present application, and is controlled and executed by the processor 601. For the specific implementation, reference may be made to the above method embodiments, which will not be repeated here.

Optionally, memory 602 may be read-only memory (ROM) or other types of static storage devices that can store static information and instructions, random access memory (RAM), or other types of static storage devices that can store information and instructions. Other types of dynamic storage devices for instructions, which may also be electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM), or other optical disks storage, optical disc storage (including compact disc, laser disc, optical disc, digital versatile disc, blu-ray disc, etc.), magnetic disk storage medium or other magnetic storage device, or capable of carrying or storing desired program code in the form of instructions or data structures and any other medium that can be accessed by a computer, but is not limited thereto. The memory 602 may be integrated with the processor 601, or may exist independently, and be coupled to the processor 601 through an interface circuit (not shown in FIG. 6) of the map data processing apparatus 600, which is not specifically limited in this embodiment of the present application.

The transceiver 603 is used for map data processing with other map data processing devices. For example, the map data processing apparatus 600 is a terminal device, and the transceiver 603 can be used to process map data with the network side, or process map data with another terminal device. For another example, the map data processing apparatus 600 is on the network side, and the transceiver 603 can be used to process map data with a terminal device, or process map data with another network side.

Optionally, the transceiver 603 may include a receiver and a transmitter (not shown separately in FIG. 6 ). Among them, the receiver is used to realize the receiving function, and the transmitter is used to realize the sending function.

Optionally, the transceiver 603 may be integrated with the processor 601, or may exist independently, and be coupled to the processor 601 through an interface circuit (not shown in FIG. 6 ) of the map data processing apparatus 600. This is not specifically limited.

It should be noted that the structure of the map data processing apparatus 600 shown in FIG. 6 does not constitute a limitation of the map data processing apparatus, and the actual map data processing apparatus may include more or less components than those shown in the figure, or Combining certain components, or different component arrangements.

In addition, for the technical effects of the map data processing apparatus 600, reference may be made to the technical effects of the map data processing methods described in the above method embodiments, which will not be repeated here.

An embodiment of the present application further provides a chip system, including: a processor, where the processor is coupled with a memory, the memory is used to store a program or an instruction, and when the program or instruction is executed by the processor, the The chip system implements the method in any of the foregoing method embodiments.

Optionally, the number of processors in the chip system may be one or more. The processor can be implemented by hardware or by software. When implemented in hardware, the processor may be a logic circuit, an integrated circuit, or the like. When implemented in software, the processor may be a general-purpose processor implemented by reading software codes stored in memory.

Optionally, the number of memories in the system-on-chip may also be one or more. The memory may be integrated with the processor, or may be provided separately from the processor, which is not limited in this application. Exemplarily, the memory can be a non-transitory processor, such as a read-only memory ROM, which can be integrated with the processor on the same chip, or can be provided on different chips. The setting method of the processor is not particularly limited.

Exemplarily, the system-on-chip may be a field programmable gate array (FPGA), an application specific integrated circuit (ASIC), or a system on chip (SoC), It can also be a central processing unit (CPU), a network processor (NP), a digital signal processing circuit (DSP), or a microcontroller (microcontroller). controller unit, MCU), it can also be a programmable logic device (PLD) or other integrated chips.

The embodiments of the present application provide a map data processing system. The system includes one or more terminal devices and one or more network sides.

It should be understood that the processor in the embodiments of the present application may be a central processing unit (central processing unit, CPU), and the processor may also be other general-purpose processors, digital signal processors (digital signal processors, DSP), dedicated integrated Circuit (application specific integrated circuit, ASIC), off-the-shelf programmable gate array (field programmable gate array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.

It should also be understood that the memory in the embodiments of the present application may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically programmable Erase programmable read-only memory (electrically EPROM, EEPROM) or flash memory. Volatile memory may be random access memory (RAM), which acts as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (DRAM) Access memory (synchronous DRAM, SDRAM), double data rate synchronous dynamic random access memory (double data rate SDRAM, DDR SDRAM), enhanced synchronous dynamic random access memory (enhanced SDRAM, ESDRAM), synchronous connection dynamic random access memory Fetch memory (synchlink DRAM, SLDRAM) and direct memory bus random access memory (direct rambus RAM, DR RAM).

The above embodiments may be implemented in whole or in part by software, hardware (eg, circuits), firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the processes or functions described in the embodiments of the present application are generated. The computer may be a general purpose computer, special purpose computer, computer network, or other programmable device. The computer instructions may be stored in or transmitted from one computer readable storage medium to another computer readable storage medium, for example, the computer instructions may be downloaded from a website site, computer, server or data center Transmission to another website site, computer, server or data center by wire (eg, infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server, a data center, or the like that contains one or more sets of available media. The usable media may be magnetic media (eg, floppy disks, hard disks, magnetic tapes), optical media (eg, DVDs), or semiconductor media. The semiconductor medium may be a solid state drive.

It should be understood that the term "and/or" in this document is only an association relationship to describe associated objects, indicating that there can be three kinds of relationships, for example, A and/or B, which can mean that A exists alone, and A and B exist at the same time , there are three cases of B alone, where A and B can be singular or plural. In addition, the character "/" in this document generally indicates that the related objects before and after are an "or" relationship, but may also indicate an "and/or" relationship, which can be understood with reference to the context.

In this application, "at least one" means one or more, and "plurality" means two or more. "At least one item(s) below" or similar expressions thereof refer to any combination of these items, including any combination of single item(s) or plural items(s). For example, at least one item (a) of a, b, or c can represent: a, b, c, a-b, a-c, b-c, or a-b-c, where a, b, c may be single or multiple .

It should be understood that, in various embodiments of the present application, the size of the sequence numbers of the above-mentioned processes does not mean the sequence of execution, and the execution sequence of each process should be determined by its functions and internal logic, and should not be dealt with in the embodiments of the present application. implementation constitutes any limitation.

Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Skilled artisans may implement the described functionality using different methods for each particular application, but such implementations should not be considered beyond the scope of this application.

Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described systems, devices and units may refer to the corresponding processes in the foregoing method embodiments, which will not be repeated here.

In the several embodiments provided in this application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are only illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored, or not implemented. On the other hand, the shown or discussed mutual coupling or direct coupling or communication connection may be through some interfaces, indirect coupling or communication connection of devices or units, and may be in electrical, mechanical or other forms.

The units described as separate components may or may not be physically separated, and components displayed as units may or may not be physical units, that is, may be located in one place, or may be distributed to multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution in this embodiment.

In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically alone, or two or more units may be integrated into one unit.

The functions, if implemented in the form of software functional units and sold or used as independent products, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product in essence, or the part that contributes to the prior art or the part of the technical solution. The computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a network side, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program codes .

The above are only specific embodiments of the present application, but the protection scope of the present application is not limited to this. should be covered within the scope of protection of this application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

A map data processing method, characterized in that, applied to a network side, the method comprising:

Obtain confidence information of a map element, where the map element includes a target element and a reference element, the confidence information of the map element includes confidence information of the target element and reference confidence information, and the reference confidence information includes: at least one of confidence information of the reference element, joint confidence information between the target element and the reference element, and conditional confidence information between the target element and the reference element;

Whether to update the map is determined according to the confidence information of the map element.
The method according to claim 1, wherein there are multiple reference elements, and the reference confidence level information further comprises: a joint confidence level between every two reference elements in the multiple reference elements Information or conditional confidence information.
The method according to claim 2, wherein the confidence information of the map elements is a confidence covariance matrix, the confidence covariance matrix includes the confidences of a plurality of map elements, and the confidence covariance The matrix includes the following formula:

Among them, Cov(P v ) is the confidence covariance matrix, the diagonal element P v (x) is the confidence of the xth map element, and P v (x, y) is the relative value of the xth map element to the The joint confidence or conditional confidence of the y-th map element, the joint confidence information between the x-th map element and the y-th map element includes: the joint confidence of the x-th map element relative to the y-th map element , the conditional confidence level information between the xth map element and the yth map element includes: the conditional confidence level of the xth map element relative to the yth map element, where x=i,i+1,..., i+n; y=i, i+1,...,i+n; i and n are positive integers.
The method according to claim 1, wherein the acquiring confidence information of map elements comprises:

Obtain confidence information from multiple terminal devices;

The confidence level information of the multiple terminal devices is fused to obtain the fused confidence level information; wherein the fused confidence level information is the confidence level information of the map element.
The method according to claim 1, wherein the conditional confidence level information between the target element and the reference element is related to the influence factor of the reference element on the target element.
The method according to any one of claims 1-5, wherein the target element is a changed map element.
The method according to any one of claims 1-5, wherein the reference element is a map element whose reference confidence information satisfies a preset condition.
A map data processing method, characterized in that, applied to a terminal device, the method comprising:

Determine the confidence information of the target element;

Determining reference confidence information, wherein the reference confidence information includes: confidence information of a reference element, joint confidence information between the target element and the reference element, and the target element and the reference element at least one of the conditional confidence information between;

The confidence information of the map element is sent to the network side, wherein the confidence information of the map element includes the confidence information of the target element and the reference confidence information.
The method according to claim 8, wherein there are multiple reference elements, and the reference confidence level information further comprises: a joint confidence level between every two reference elements in the multiple reference elements Information or conditional confidence information.
The method according to claim 9, wherein the confidence information of the map element is a confidence covariance matrix, and the confidence covariance matrix includes the confidence of a plurality of map elements, and the plurality of map elements Including the target element and the reference element, the confidence covariance matrix includes the following formula:

Among them, Cov(P v ) is the confidence covariance matrix, the diagonal element P v (x) is the confidence of the xth map element, and P v (x, y) is the relative value of the xth map element to the The joint confidence or conditional confidence of the y-th map element, the joint confidence information between the x-th map element and the y-th map element includes: the joint confidence of the x-th map element relative to the y-th map element , the conditional confidence level information between the xth map element and the yth map element includes: the conditional confidence level of the xth map element relative to the yth map element, where x=i,i+1,..., i+n; y=i, i+1,...,i+n; i and n are positive integers.
The method according to any one of claims 8-10, wherein the method further comprises:

The target element and the reference element are determined; wherein, the target element is a map element that has changed, and the reference element is a map element whose reference confidence information satisfies a preset condition.
A map data processing device, comprising: a processing module and an acquisition module; wherein,

The obtaining module is configured to obtain confidence information of map elements, the map elements include target elements and reference elements, the confidence information includes confidence information and reference confidence information of the target elements, and the reference confidence The degree information includes at least one of: confidence degree information of the reference element, joint confidence degree information between the target element and the reference element, and conditional confidence degree information between the target element and the reference element One;

The processing module is configured to determine whether to update the map according to the confidence information of the map element.
The apparatus according to claim 12, wherein there are multiple reference elements, and the reference confidence information further comprises: joint confidence information between every two reference elements in the multiple reference elements or Conditional confidence information.
The apparatus according to claim 13, wherein the confidence information of the map element is a confidence covariance matrix, the confidence covariance matrix includes confidences of a plurality of map elements, and the confidence covariance The matrix includes the following formula:

Among them, Cov(P v ) is the confidence covariance matrix, the diagonal element P v (x) is the confidence of the xth map element, and P v (x, y) is the relative value of the xth map element to the The joint confidence or conditional confidence of the y-th map element, the joint confidence information between the x-th map element and the y-th map element includes: the joint confidence of the x-th map element relative to the y-th map element , the conditional confidence level information between the xth map element and the yth map element includes: the conditional confidence level of the xth map element relative to the yth map element, where x=i,i+1,..., i+n; y=i, i+1,...,i+n; i and n are positive integers.
The device of claim 12, wherein:

The acquiring module is further configured to acquire confidence information from multiple terminal devices; and,

The confidence level information of the multiple terminal devices is fused to obtain the fused confidence level information; wherein the fused confidence level information is the confidence level information of the map element.
The apparatus according to claim 12, wherein the conditional confidence level information between the target element and the reference element is related to an influence factor of the reference element on the target element.
The device according to any one of claims 12-16, wherein the target element is a map element that changes.
The apparatus according to any one of claims 12-16, wherein the reference element is a map element whose reference confidence information satisfies a preset condition.
A map data processing device, characterized in that the device comprises: a processing module and a transceiver module; wherein,

The processing module is used to determine the confidence information of the target element;

The processing module is further configured to determine reference confidence information, where the reference confidence information includes: confidence information of a reference element, joint confidence information between the target element and the reference element, and the target at least one of the conditional confidence information between the element and the reference element;

The transceiver module is configured to send the confidence level information of the map element to the network side, wherein the confidence level information of the map element includes the confidence level information of the target element and the reference confidence level information.
The apparatus according to claim 19, wherein the reference elements are plural;

The reference confidence level further includes: joint confidence level information or conditional confidence level information between every two reference elements in the plurality of reference elements.
The apparatus according to claim 19, wherein the confidence information of the map element is a confidence covariance matrix, and the confidence covariance matrix includes confidences of a plurality of map elements, and the plurality of map elements Including the target element and the reference element, the confidence covariance matrix includes the following formula:

Among them, Cov(P v ) is the confidence covariance matrix, the diagonal element P v (x) is the confidence of the xth map element, and P v (x, y) is the relative value of the xth map element to the The joint confidence or conditional confidence of the y-th map element, the joint confidence information between the x-th map element and the y-th map element includes: the joint confidence of the x-th map element relative to the y-th map element , the conditional confidence level information between the xth map element and the yth map element includes: the conditional confidence level of the xth map element relative to the yth map element, where x=i,i+1,..., i+n; y=i, i+1,...,i+n; i and n are positive integers.
The device according to any one of claims 19-21, characterized in that,

The processing module is further configured to determine the target element and the reference element; wherein the target element is a changed map element, and the reference element is a map element whose reference confidence information satisfies a preset condition.
A map data processing device, comprising: a processor and a memory; the memory is used to store a computer program or instruction, when the processor executes the computer program or instruction, so that the map data processing device Execute the map data processing method according to any one of claims 1-11.
A computer-readable storage medium, characterized in that the computer-readable storage medium comprises a computer program or instruction, and when the computer program or instruction is executed on a processor, the computer program or instruction is executed as described in any one of claims 1-11. The map data processing method is executed.
A computer program product, characterized by comprising computer instructions that, when executed by a processor, implement the method according to any one of claims 1-11.
A map data processing system, characterized in that it includes a network side device and a terminal device, the network side device is used to execute the method according to any one of claims 1-7, and the terminal device is used to execute the method as claimed in claim 1. The method of any of claims 8-11.