CN116198544A

CN116198544A - Digital twin data processing method and device

Info

Publication number: CN116198544A
Application number: CN202310263824.7A
Authority: CN
Inventors: 浑思琦; 贺伟伟; 潘石尧
Original assignee: Zhidao Network Technology Beijing Co Ltd
Current assignee: Zhidao Network Technology Beijing Co Ltd
Priority date: 2023-03-17
Filing date: 2023-03-17
Publication date: 2023-06-02

Abstract

The application discloses a digital twin data processing method and device, wherein the method comprises the steps of receiving digital twin data; judging the congestion level of the target intersection according to the digital twin data; and if the congestion level of the target intersection reaches the congestion standard, establishing a road surrounding area of each lane in the road driving area in the target intersection. According to the method and the device for displaying the road traffic jam, the influence range of the road traffic jam on the nearby area can be obtained according to the road surrounding area, so that a vehicle end can be served for displaying or calculating the global planning path. The method and the device can be used for digital twin projects in the smart city.

Description

Digital twin data processing method and device

Technical Field

The application relates to the technical field of automatic driving and big data processing, in particular to a digital twin data processing method and device.

Background

The intelligent city is characterized in that key infrastructure components and services formed by cities such as city management, transportation, public utilities and public safety are interconnected, efficient and intelligent through application of intelligent computing technologies such as Internet of things, cloud computing, big data, space geographic information integration and the like.

The digital twin items in the smart city are characterized in that information technologies such as perception, calculation, modeling and the like are comprehensively utilized, and the physical space is described, diagnosed, predicted and decided through software definition, so that the interactive mapping of the physical space and a microblog space (cybertspace) is realized.

In the related art, the congestion condition of the intersection cannot be well estimated, and the influence degree of the congestion of the intersection on traffic cannot be further determined.

Disclosure of Invention

The embodiment of the application provides a digital twin data processing method and device, which are used for calculating road congestion surrounding conditions of an intersection in real time.

The embodiment of the application adopts the following technical scheme:

in a first aspect, an embodiment of the present application provides a digital twin data processing method, where the method includes:

receiving digital twin data;

judging the congestion level of the target intersection according to the digital twin data;

and if the congestion level of the target intersection reaches the congestion standard, establishing a road surrounding area of each lane in the road driving area in the target intersection.

In some embodiments, the determining the congestion level of the target intersection according to the digital twin data includes:

acquiring the average delay time of the vehicle based on the lane level in the target intersection according to the digital twin data;

calculating the maximum vehicle average delay time of a preset running direction in a road passing area according to the vehicle average delay time, and determining the congestion level in the preset running direction;

if the congestion level at the target intersection reaches the congestion standard, establishing a road surrounding area of each lane in the road passing area in the target intersection, including:

if the congestion level of the target intersection reaches the congestion standard, judging the position of the last vehicle of each lane;

and calculating the boundary position of the road surrounding area based on the stop line coordinate position in the target intersection and the position of the last vehicle, wherein the boundary position comprises a plurality of coordinate point positions affecting the corresponding road surrounding area when each lane is congested.

In some embodiments, further comprising: and calculating the influence range of the congestion of the target intersection on the nearby driving area according to the road surrounding area, and displaying the influence range on the nearby driving area at the vehicle end or performing global path planning at the vehicle end.

In some embodiments, before the establishing the road surrounding area of each lane in the road traffic area in the target intersection, the method further includes:

filtering data except the target intersection in the digital twin data, and judging whether abnormal vehicle fusion data exists in the filtered digital twin data;

and if the abnormal vehicle fusion data exists, compensating the abnormal vehicle fusion.

In some embodiments, the establishing a road bounding region for each lane in the road traffic region within the target intersection comprises:

determining data to be processed in a road surrounding area based on a grouping result of a high-precision map on each lane and congestion calculation time, wherein the high-precision map comprises group_ID attribute information and group_num attribute information in an area where a current target intersection is located;

acquiring a corresponding vehicle UUID and a corresponding position of a current time point in the road surrounding area according to the data to be processed;

and calculating the longitude and latitude position of the last vehicle in the road surrounding area according to the UUID of the vehicle and the position of the current time point.

In some embodiments, the establishing a road surrounding area for each lane in the road traffic area within the target intersection further includes:

obtaining an extension line of a position corresponding to the longitude and latitude information according to the longitude and latitude information of the last vehicle;

the same group_num attribute information is correlated to obtain continuous lane lines at two sides of the road;

according to the lane lines on the two sides of the road and the longitude and latitude information of the last vehicle, making a vertical line to an extension line of a position corresponding to the longitude and latitude information, and obtaining a foot drop;

traversing lane lines on two sides of the road to obtain the point positions of the lane lines meeting a preset offset angle;

and obtaining the road surrounding area of each lane according to the position point of the lane line and the position point of the foot drop.

In some embodiments, after obtaining, according to the data to be processed, a corresponding UUID of the vehicle and a location of a corresponding current time point in the road surrounding area, the method further includes:

calculating a preset swing angle according to angles between each point corresponding to the UUID of the vehicle and the center point of the current road;

if the preset swing angle is larger than the preset swing angle, the road is excluded as a reverse point, and the road comprises two lanes, three lanes and four lanes.

In some embodiments, the establishing a road surrounding area of each lane in the road driving area within the target intersection further includes:

if the current lane is within the solid line range of the road, the solid line is connected and then used as the surrounding area of the road.

In some embodiments, the method further comprises:

the twin data is processed based on the flank real-time stream computation framework and transmitted by establishing a message queue MQ.

In a second aspect, embodiments of the present application further provide a twin data processing apparatus, where the apparatus includes:

the receiving module is used for receiving the digital twin data;

the judging module is used for judging the congestion level of the target intersection according to the digital twin data;

the building module is used for building a road surrounding area of each lane in the road running area in the target intersection if the congestion level of the target intersection reaches the congestion standard.

In a third aspect, embodiments of the present application further provide an electronic device, including: a processor; and a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the above method.

In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium storing one or more programs that, when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the above-described method.

The above-mentioned at least one technical scheme that this application embodiment adopted can reach following beneficial effect: and judging the congestion level of the target intersection by receiving the digital twin data and according to the digital twin data, and if the congestion level of the target intersection reaches the congestion standard, establishing a road surrounding area of each lane in a road driving area in the target intersection. And obtaining the influence range of the road congestion on the vicinity according to the road surrounding area, so that a vehicle end can be served for displaying or calculating the global planning path.

Drawings

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

FIG. 1 is a schematic flow chart of a digital twin data processing method in an embodiment of the present application;

FIG. 2 is a schematic diagram of surrounding areas of different roads in a digital twin data processing method according to an embodiment of the present application;

FIG. 3 is a schematic diagram of different road surrounding areas in the digital twin data processing method according to the embodiment of the present application;

FIG. 4 is a diagram showing two different road surrounding areas in the digital twin data processing method according to the embodiment of the present application;

FIG. 5 is a timing chart of a processing flow of different ends in a digital twin data processing method according to an embodiment of the present application;

FIG. 6 is a schematic diagram of a digital twin data processing device in an embodiment of the present application;

FIG. 7 is a flow chart of a method of digital twin data processing in a preferred embodiment of the present application;

fig. 8 is a schematic structural diagram of an electronic device in an embodiment of the present application.

Detailed Description

For the purposes, technical solutions and advantages of the present application, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present application. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are within the scope of the present disclosure.

The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.

The embodiment of the application provides a digital twin data processing method, as shown in fig. 1, and provides a flow chart of the digital twin data processing method in the embodiment of the application, where the method at least includes the following steps S110 to S130:

step S110, digital twin data is received.

The digital twin data is received and further processed by a background service, such as a cloud service. The digital twin data are obtained after being processed based on the digital twin system, the digital twin system can collect image information of each lane at the road side end through cameras deployed at the road junction, and the digital twin system can carry vehicle position information and camera ID (which camera is shot) when reporting, and at the same time, after the road side end receives the digital twin data, the digital twin system processes the image information according to calibration files prestored at the road side end to obtain the digital twin data corresponding to the vehicle in the real scene.

It can be understood that in actual use, if the situation of the same vehicle is captured by a plurality of cameras, the situation is reported after fusion and duplicate removal processing.

And step S120, judging the congestion level of the target intersection according to the digital twin data.

The congestion level is judged according to the national standard of road congestion, and if the congestion level meets the relevant standard, the road is considered to be congested at the target intersection. And in the concrete calculation, firstly, the national standard of road congestion is called, then, the digital twin data is processed according to an intersection congestion level algorithm, and the obtained result is used as the standard for judging the congestion level of the target intersection.

The selection of the target intersection is determined according to the actual service scene, and the north-to-south or the south-to-north at the intersection and different traffic flow driving conditions from west to east or from east to west are required to be considered. Meanwhile, due to the fact that the congestion condition of the target intersection is judged, the area in front of the vehicle stop line of the intersection does not need to be considered, namely, the running direction of the vehicle flow can be the conditions of straight running, right turning, straight running, left turning (left turning waiting) and the like.

Step S130, if the congestion level at the target intersection reaches the congestion standard, establishing a road surrounding area of each lane in the road driving area in the target intersection.

If the congestion level of the target intersection reaches the congestion standard through the calculation of the steps, a road surrounding area of each lane in the lane-level road driving area is established, and the road surrounding area is calculated and then is synchronized with a vehicle end.

The congestion condition of the current road is represented by the road surrounding area, so that the automatic driving vehicle can conveniently conduct road planning and the like in advance or timely synchronize the congestion condition to the vehicle end in the vehicle-road cooperative scene. Meanwhile, the road surrounding area also has a certain influence range, and the previous traffic jam condition can be estimated according to the influence range, or traffic restriction and the like can be performed in advance.

In comparison with the related art, in the cloud service end, whether the road junction is jammed is judged by adopting a vehicle position estimation mode or an image acquired by a road side camera at the road end, and the method can calculate the influence range of the received digital twin data on the nearby lane after the current road junction is jammed in near real time according to the distributed calculation frame.

Further, the method can judge the congestion condition of each lane and synchronize with the vehicle end after timely reporting. The method adopts a distributed real-time stream computing framework, and can ensure the real-time performance of data processing. Meanwhile, if the congestion level at the target intersection reaches the congestion standard, the REDIS cache mode is read to process the digital twin data after congestion occurs one by one, so that low delay of data processing is ensured.

In one embodiment of the present application, the determining, according to the digital twin data, the congestion level of the target intersection includes: acquiring the average delay time of the vehicle based on the lane level in the target intersection according to the digital twin data; calculating the maximum vehicle average delay time of a preset running direction in a road passing area according to the vehicle average delay time, and determining the congestion level in the preset running direction; if the congestion level at the target intersection reaches the congestion standard, establishing a road surrounding area of each lane in the road passing area in the target intersection, including: if the congestion level of the target intersection reaches the congestion standard, judging the position of the last vehicle of each lane; and calculating the boundary position of the road surrounding area based on the stop line coordinate position in the target intersection and the position of the last vehicle, wherein the boundary position comprises a plurality of coordinate point positions affecting the corresponding road surrounding area when each lane is congested.

Referring to fig. 2, for the leftmost lane, the driving direction is left turn, and the road surrounding area includes: A. b, C, D four points. For the rightmost lane, the traveling direction is straight, and the road surrounding area includes: E. i, J, K four points. For the middle lane, the traveling direction is straight, and the road surrounding area includes: B. e, F, G, H area around five points.

Referring to fig. 3, the vehicle uuid1 is located at a queuing turning position from north to south at time t1, and turns left to the east-west lane at time t 1. Similarly, the UUid2 vehicle is located at the north-south queuing straight position at time t3, and continues to travel straight to the north-south lane at time t 4. In consideration of the fact that three lanes may become four lanes due to the irregularity of the road, the situation of the road surrounding area of the corresponding sharp angle or polygon in the middle may be encountered. Fig. 3 shows a three lane situation.

Referring to fig. 4, the vehicle uuid1 is located at a queuing turning position from north to south at time t1, and turns left to the east-west lane at time t 1. Similarly, the UUid2 vehicle is located at the north-south queuing straight position at time t3, and continues to travel straight to the north-south lane at time t 4. In consideration of the fact that three lanes may become four lanes due to the irregularity of the road, the situation of the road surrounding area of the corresponding sharp angle or polygon in the middle may be encountered. Fig. 4 shows a four lane situation.

With continued reference to fig. 3 and 4, it can be seen that the road surrounding area is determined according to the stop line at the target intersection and the position of the last vehicle in the line and the lane lines on both sides.

Illustratively, in fig. 3 or fig. 4, according to the received digital twin data, one road surrounding area composed of 4 points is returned, one road surrounding area composed of 6 points is returned, and one road surrounding area composed of 8 points is returned.

Acquiring the average delay time of the vehicle based on the lane level in the target intersection according to the digital twin data; and calculating the maximum vehicle average delay time of a preset running direction in a road passing area according to the vehicle average delay time, determining the congestion level in the preset running direction, judging the position of the last vehicle of each lane, calculating the boundary position of the surrounding range based on the coordinate point of the stop line and the position of the last vehicle, and obtaining a plurality of coordinate points of each lane affecting the surrounding range.

If the congestion level of the target intersection reaches the congestion standard, judging the position of the last vehicle of each lane; and calculating the boundary position of the road surrounding area based on the stop line coordinate position in the target intersection and the position of the last vehicle, wherein the boundary position comprises a plurality of coordinate point positions affecting the corresponding road surrounding area when each lane is congested, calculating the maximum vehicle average delay time in a certain direction based on the vehicle average delay time of the lane level, and obtaining the congestion level (range) of the vehicle running direction.

In one embodiment of the present application, further comprising: and calculating the influence range of the congestion of the target intersection on the nearby driving area according to the road surrounding area, and displaying the influence range on the nearby driving area at the vehicle end or performing global path planning at the vehicle end.

As shown in fig. 5, the influence range of the congestion of the target intersection on the nearby traveling area is calculated by the road surrounding area, and is transmitted to the vehicle end based on the V2X communication protocol and then displayed on the vehicle end. Or, global path planning is carried out at the vehicle end.

In one embodiment of the present application, before establishing the road surrounding area of each lane in the road traffic area in the target intersection, the method further includes: filtering data except the target intersection in the digital twin data, and judging whether abnormal vehicle fusion data exists in the filtered digital twin data; and if the abnormal vehicle fusion data exists, compensating the abnormal vehicle fusion.

Abnormal vehicle fusion data may be caused when the road side camera collects images, such as when long-range cameras are used to shoot vehicles at an intersection, and vehicle close-up cannot be obtained. Therefore, the loss or abnormality is liable to occur. And filtering out data outside the target intersection in the digital twin data, judging whether abnormal vehicle fusion data exist in the filtered digital twin data, performing data compensation on the digital twin abnormal data, and maximally representing the influence of real-world intersection congestion on the nearby range through a calculation process.

In one embodiment of the present application, the establishing the road surrounding area of each lane in the road traffic area within the target intersection includes: determining data to be processed in a road surrounding area based on a grouping result of a high-precision map on each lane and congestion calculation time, wherein the high-precision map comprises group_ID attribute information and group_num attribute information in an area where a current target intersection is located; acquiring a corresponding vehicle UUID and a corresponding position of a current time point in the road surrounding area according to the data to be processed; and calculating the longitude and latitude position of the last vehicle in the road surrounding area according to the UUID of the vehicle and the position of the current time point.

"high-precision map" refers to a high-precision map loaded on the area of the target intersection. And obtaining grouping results of each lane according to the high-precision map, namely dividing the grouping results into groups of lanes 1, 2 and 3. By "congestion calculation time" is meant the calculation time within one timing period after the congestion level is reached. For example, the last 0.5 seconds in the timing cycle of 5 seconds is taken as the congestion calculation time.

After the data to be processed are determined, the corresponding vehicle UUIDs in the road surrounding area and the corresponding positions of the current time points are acquired from the data to be processed. And calculating the longitude and latitude position of the last vehicle in the road surrounding area according to the UUID of the vehicle and the position of the current time point.

In one embodiment of the present application, the establishing a road surrounding area of each lane in the road traffic area in the target intersection further includes: obtaining an extension line of a position corresponding to the longitude and latitude information according to the longitude and latitude information of the last vehicle; the same group_num attribute information is correlated to obtain continuous lane lines at two sides of the road; according to the lane lines on the two sides of the road and the longitude and latitude information of the last vehicle, making a vertical line to an extension line of a position corresponding to the longitude and latitude information, and obtaining a foot drop; traversing lane lines on two sides of the road to obtain the point positions of the lane lines meeting a preset offset angle; and obtaining the road surrounding area of each lane according to the position point of the lane line and the position point of the foot drop.

The group_id and the group_num are one attribute provided by the high-precision map, and the links link of the same group_num are associated together to calculate in order to be able to connect the roads one by one.

When the road surrounding area is calculated according to the angle, the longitude and latitude positions of the last vehicle on the corresponding road are firstly judged, and the last vehicle is the farthest distance by calculating the distances between the longitude and latitude of all vehicles and the corresponding road stop line. And then making vertical lines to two sides along the negative direction (the driving direction is positive) of the road direction according to the obtained position of the last vehicle. Obtaining the drop foot. And finally, obtaining the information of the corresponding road section to obtain a series of position points. The points of the vertical line and the last vehicle, and the points of all lane lines are calculated. Finally, traversing lane lines on two sides of the road to obtain the point positions of the lane lines meeting the preset offset angle; and obtaining the road surrounding area of each lane according to the position point of the lane line and the position point of the foot drop.

In an embodiment of the present application, after obtaining, according to the data to be processed, a UUID of a corresponding vehicle and a location of a corresponding current time point in the road surrounding area, the method further includes: calculating a preset swing angle according to angles between each point corresponding to the UUID of the vehicle and the center point of the current road; if the preset swing angle is larger than the preset swing angle, the road is excluded as a reverse point, and the road comprises two lanes, three lanes and four lanes.

Due to the irregularity of the road, it is possible to encounter a situation where three lanes become four lanes, and for a situation where the road may be two lanes, three lanes or four lanes, different types of lanes may be obtained when the reverse point is excluded. And calculating a preset swing angle according to angles between each point corresponding to the UUID of the vehicle and the center point of the current road. If the point is a reverse point, the corresponding point in the surrounding area of the road cannot be included.

In one embodiment of the present application, the establishing a road surrounding area of each lane in the road driving area within the target intersection further includes: and if the current lane is in the solid line range of the road, connecting the solid lines and then taking the connected solid lines as the road-taking surrounding area.

When the lane is within the range of the solid line, the solid lines are directly connected together to acquire the closed figure, and the solid line fence can be preferentially constructed because the solid line does not allow lane change.

The embodiment of the present application further provides a digital twin data processing apparatus 600, as shown in fig. 6, and a schematic structural diagram of the digital twin data processing apparatus in the embodiment of the present application is provided, where the twin data processing apparatus 600 at least includes: a receiving module 610, a judging module 620, and a establishing module 630, wherein:

in one embodiment of the present application, the receiving module 610 is specifically configured to: digital twin data is received.

In one embodiment of the present application, the determining module 620 is specifically configured to: and judging the congestion level of the target intersection according to the digital twin data.

In one embodiment of the present application, the establishing module 630 is specifically configured to: and if the congestion level of the target intersection reaches the congestion standard, establishing a road surrounding area of each lane in the road driving area in the target intersection.

It can be understood that the above-mentioned digital twin data processing apparatus can implement the steps of the digital twin data processing method provided in the foregoing embodiments, and the relevant explanation about the digital twin data processing method is applicable to the digital twin data processing apparatus, which is not repeated herein.

Fig. 7 is a schematic flow chart of a digital twin data processing method in the preferred embodiment of the present application, which specifically includes the following flow chart:

and step S710, obtaining KFK data, calculating the congestion level, and transmitting the current data of 5 seconds to the downstream when the congestion level is larger than a fixed value. 5 seconds is only an example, mainly considering the requirement of ensuring real-time. The KFK data refers to digital twin data obtained through a Kaff card queue.

Step S720, filtering data outside the intersection.

And filtering out data outside the target intersection in the digital twin data, and judging whether abnormal vehicle fusion data exists in the filtered digital twin data.

In step S730, the fusion vehicle is compensated.

Step S740, grouping is performed according to the group_id and the group_num.

The high-precision map comprises group_ID attribute information and group_Num attribute information in the area where the current target intersection is located. And determining the data to be processed in the road surrounding area based on the grouping result of the high-precision map on each lane and the congestion calculation time.

Step S750, determining which data after grouping is subjected to surrounding processing.

And acquiring a corresponding vehicle UUID and a corresponding position of the current time point in the road surrounding area according to the data to be processed.

Step S760, acquiring data in the last 0.5 seconds in 5 seconds, and acquiring the corresponding UUID and the position of the last time point.

By "congestion calculation time" is meant the calculation time within one timing period after the congestion level is reached. For example, the last 0.5 seconds in the timing cycle of 5 seconds is taken as the congestion calculation time.

In step S770, a preset swing angle is calculated according to the angles between each point corresponding to the UUID of the vehicle and the center point of the current road, and if the preset swing angle is greater than 100 degrees, the point is considered as a reverse point and needs to be eliminated.

In step S780, the position of the last vehicle is calculated and extended, and the group_num is acquired and correlated together.

Step S790, making a vertical line to an extension line of a position corresponding to the longitude and latitude information according to the lane lines on the two sides of the road and the longitude and latitude information of the last vehicle, and obtaining a foot drop; traversing lane lines on two sides of the road to obtain the point positions of the lane lines meeting a preset offset angle; and obtaining the road surrounding area of each lane according to the position point of the lane line and the position point of the foot drop.

Fig. 8 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 8, at the hardware level, the electronic device includes a processor, and optionally an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.

The processor, network interface, and memory may be interconnected by an internal bus, which may be an ISA (Industry Standard Architecture ) bus, a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 8, but not only one bus or type of bus.

And the memory is used for storing programs. In particular, the program may include program code including computer-operating instructions. The memory may include memory and non-volatile storage and provide instructions and data to the processor.

The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs to form the digital twin data processing device on the logic level. The processor is used for executing the programs stored in the memory and is specifically used for executing the following operations:

receiving digital twin data;

The method performed by the digital twin data processing apparatus disclosed in the embodiment of fig. 1 of the present application may be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.

The electronic device may further execute the method executed by the digital twin data processing apparatus in fig. 1, and implement the functions of the digital twin data processing apparatus in the embodiment shown in fig. 1, which is not described herein.

The present application also proposes a computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device comprising a plurality of application programs, enable the electronic device to perform the method performed by the digital twin data processing apparatus in the embodiment shown in fig. 1, and in particular for performing:

receiving digital twin data;

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

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

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

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

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

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

Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.

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

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

The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims

1. A digital twin data processing method, wherein the method comprises:

receiving digital twin data;

2. The method of claim 1, wherein the step of,

the judging the congestion level of the target intersection according to the digital twin data comprises the following steps:

3. The method of claim 2, further comprising: and calculating the influence range of the congestion of the target intersection on the nearby driving area according to the road surrounding area, and displaying the influence range on the nearby driving area at the vehicle end or performing global path planning at the vehicle end.

4. The method of claim 1, wherein prior to establishing the road bounding region for each lane in the road traffic region within the target intersection, further comprising:

5. The method of claim 4, wherein the establishing a road bounding region for each lane in a road traffic region within the target intersection comprises:

6. The method of claim 5, wherein the establishing a road bounding region for each lane in a road traffic region within the target intersection further comprises:

7. The method of claim 5, wherein after the acquiring, according to the data to be processed, the corresponding UUID of the vehicle and the corresponding position of the current time point in the surrounding area of the road, further comprises:

8. The method of claim 1, wherein the establishing a road bounding region for each lane in a road travel region within the target intersection further comprises:

9. The method of any one of claims 1 to 8, wherein the method further comprises:

10. A twin data processing apparatus, wherein the apparatus comprises:

the receiving module is used for receiving the digital twin data;