Digital twin data processing method and apparatus

Abstract

The application discloses a digital twin data processing method and device. The method comprises receiving digital twin data; judging the congestion level of a target intersection according to the digital twin data; and if the congestion level of the target intersection reaches a congestion standard, establishing a road enclosure area of each lane in a road driving area in the target intersection. The application can obtain the influence range of intersection congestion on the surrounding area according to the road enclosure area, thereby serving the vehicle end to display or calculate a global planning path. The application can be used in digital twin projects in smart cities.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving and big data processing, and particularly relates to a digital twin data processing method and device. BACKGROUND

[0002] A smart city is a city that uses information and communication technology to integrate and improve the management of urban services, such as transportation, utilities, and public safety, to make the city more interconnected, efficient, and intelligent.

[0003] In a smart city, a digital twin project is a project that uses information technology such as perception, computation, and modeling to describe, diagnose, predict, and make decisions about a physical space through software definition, and then realizes the interactive mapping between the physical space and the cyberspace (digital virtual space).

[0004] In related technologies, it is difficult to estimate the congestion situation at an intersection, and it is further difficult to determine the impact of the congestion at the intersection on traffic. SUMMARY

[0005] Embodiments of the present application provide a digital twin data processing method and device to calculate the road congestion situation at an intersection in real time.

[0006] Embodiments of the present application use the following technical solutions:

[0007] In a first aspect, embodiments of the present application provide a digital twin data processing method, which includes:

[0008] receiving digital twin data;

[0009] determining the congestion level of a target intersection according to the digital twin data;

[0010] if the congestion level of the target intersection reaches a congestion standard, establishing a road enclosure area for each lane in a road driving area in the target intersection.

[0011] In some embodiments, determining the congestion level of a target intersection according to the digital twin data includes:

[0012] obtaining the average vehicle delay time based on the lane in the target intersection according to the digital twin data;

[0013] calculating the maximum average vehicle delay time of a preset driving direction in a road traffic area according to the average vehicle delay time, and determining the congestion level of the preset driving direction;

[0014] If the congestion level of the target intersection reaches the congestion standard, a road enclosure area of each lane in a road passing area in the target intersection is established, comprising:

[0015] If the congestion level of the target intersection reaches the congestion standard, the position of the last vehicle of each lane is determined;

[0016] Based on the stop line coordinate position in the target intersection and the position of the last vehicle, the boundary position of the road enclosure area is calculated, wherein the boundary position includes a plurality of coordinate point positions of each lane affecting the corresponding road enclosure area when congested.

[0017] In some embodiments, it further comprises calculating the influence range of congestion of the target intersection on the nearby driving area based on the road enclosure area, for displaying at the vehicle end or for global path planning at the vehicle end.

[0018] In some embodiments, before establishing the road enclosure area of each lane in the road passing area in the target intersection, it further comprises:

[0019] Filtering out data other than the target intersection in the digital twin data, and determining whether there is abnormal vehicle fusion data in the filtered digital twin data;

[0020] If there is abnormal vehicle fusion data, compensate for the abnormal vehicle fusion.

[0021] In some embodiments, the establishment of the road enclosure area of each lane in the road passing area in the target intersection comprises:

[0022] Based on the grouping result of each lane and the congestion calculation time, determine the to-be-processed data in the road enclosure area, wherein the high-precision map includes Group_ID attribute information and Group_Num attribute information in the area where the current target intersection is located;

[0023] According to the to-be-processed data, obtain the vehicle UUID in the road enclosure area and the position at the corresponding current time point;

[0024] According to the vehicle UUID and the position at the corresponding current time point, calculate the latitude and longitude position of the last vehicle in the road enclosure area.

[0025] In some embodiments, the establishment of the road enclosure area of each lane in the road passing area in the target intersection further comprises:

[0026] According to the latitude and longitude information of the last vehicle, obtain the extension line of the position corresponding to the latitude and longitude information.

[0027] The same Group_Num attribute information is associated to obtain continuous road lane lines on both sides of the road;

[0028] According to the road lane lines on both sides of the road and the latitude and longitude information of the last vehicle, a perpendicular line is drawn to the extension line of the position corresponding to the latitude and longitude information, and a foot of the perpendicular is obtained;

[0029] The road lane lines on both sides of the road are traversed to obtain a point of a lane line that satisfies a preset offset angle;

[0030] According to the position point of the lane line and the position point of the foot of the perpendicular, a road enclosing area of each lane is obtained.

[0031] In some embodiments, after obtaining the corresponding vehicle UUID in the road enclosing area and the position of the corresponding current time point, the method further comprises:

[0032] According to the angle between each point corresponding to the vehicle UUID and the center point of the current road, a preset swing angle is calculated.

[0033] If it is greater than the preset swing angle, it is excluded as a reverse point, and the road includes two lanes, three lanes, and four lanes.

[0034] In some embodiments, the method further comprises:

[0035] If the current lane is within the range of the road solid line, the solid line is connected and then used as the road enclosing area.

[0036] In some embodiments, the method further comprises:

[0037] The twin data is processed based on a Flink real-time stream computing framework, and is transmitted through a message queue MQ.

[0038] In a second aspect, the embodiments of the present application also provide a twin data processing device, wherein the device comprises:

[0039] A receiving module is configured to receive digital twin data.

[0040] A judging module is configured to judge a congestion level of a target intersection according to the digital twin data.

[0041] An establishing module is configured to establish a road enclosing area of each lane in a road driving area in the target intersection if the congestion level of the target intersection reaches a congestion standard.

[0042] In a third aspect, the embodiments of the present application further provide an electronic device, comprising: a processor; and a memory arranged to store computer-executable instructions that, when executed, cause the processor to perform the method described above.

[0043] In a fourth aspect, the embodiments of the present application further provide a computer-readable storage medium storing one or more programs, which, when executed by an electronic device comprising a plurality of applications, cause the electronic device to perform the method described above.

[0044] The above at least one technical solution adopted by the embodiments of the present application can achieve the following beneficial effects: by receiving digital twin data and determining the congestion level of the target intersection according to the digital twin data, if the congestion level of the target intersection reaches the congestion standard, a road enclosure area of each lane in the road driving area in the target intersection is established. The influence range of intersection congestion on the nearby area is obtained according to the road enclosure area, thereby serving the vehicle end to display or calculate the global planning path. BRIEF DESCRIPTION OF DRAWINGS

[0045] The accompanying drawings, which are included to provide a further understanding of the present application, constitute a part of the present application and illustrate the illustrative embodiments of the present application and their description serve to explain the present application, and do not constitute improper limitations on the present application. In the drawings:

[0046] Figure 1 It is a flowchart of the digital twin data processing method in the embodiments of the present application;

[0047] Figure 2 It is a schematic diagram of different road enclosure areas in the digital twin data processing method in the embodiments of the present application;

[0048] Figure 3 It is one of the schematic diagrams of different road enclosure areas in the digital twin data processing method in the embodiments of the present application;

[0049] Figure 4 It is the second of the schematic diagrams of different road enclosure areas in the digital twin data processing method in the embodiments of the present application;

[0050] Figure 5 It is a timing diagram of the processing flow of different ends in the digital twin data processing method in the embodiments of the present application;

[0051] Figure 6 It is a structural schematic diagram of the digital twin data processing device in the embodiments of the present application;

[0052] Figure 7 It is a flowchart of the digital twin data processing method in the preferred embodiments of the present application;

[0053] Figure 8 Fig. 1 is a structural schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0054] In order to make the objects, technical solutions and advantages of the present application clearer, the technical solutions of the present application will be described below in detail with the specific embodiments of the present application and the corresponding drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0055] The technical solutions provided by the embodiments of the present application will be described in detail below with reference to the drawings.

[0056] The embodiments of the present application provide a digital twin data processing method, as shown in Fig. 1, a flowchart of the digital twin data processing method in the embodiments of the present application is provided, and the method at least includes the following steps S110 to S130: Figure 1

[0057] Step S110, receiving digital twin data.

[0058] The digital twin data is received and further processed by a background service such as a cloud service. For the digital twin data obtained after processing based on a digital twin system, the digital twin system can collect image information of each lane through a camera deployed at an intersection on a roadside, and the vehicle position information and camera ID (which camera is used for shooting) are carried when reporting. At the same time, after receiving on the roadside, the image information is processed according to the calibration file pre-stored on the roadside to obtain the digital twin data corresponding to the vehicle in the real scene.

[0059] It can be understood that in actual use, if multiple cameras are used to shoot the same vehicle, the fusion deduplication processing will be performed first before reporting.

[0060] Step S120, judging the congestion level of the target intersection according to the digital twin data.

[0061] The congestion level is judged according to the national standard of road congestion, and if it meets the relevant standard, it is considered to be congested at the target intersection. In the specific calculation, the national standard of road congestion is first called, and then the digital twin data is processed according to the intersection congestion level algorithm, and the result is used as the standard for judging the congestion level of the target intersection.

[0062] ​The selection of the target intersection is determined according to the actual business scenario, and the different traffic flow driving conditions from north to south or from south to north, and from west to east or from east to west at the intersection need to be considered. At the same time, since the congestion condition of the target intersection is judged, the area before the vehicle stop line at the intersection does not need to be considered, that is, the driving direction of the traffic flow can be straight, straight right turn or straight left turn (left turn waiting) and the like.

[0063] In step S130, if the congestion level at the target intersection reaches the congestion standard, the road enclosure area of each lane in the road driving area in the target intersection is established.

[0064] After the calculation of the above steps, if the congestion level at the target intersection reaches the congestion standard, the road enclosure area of each lane in the road driving area at the lane level is established, and after the road enclosure area is calculated, it is synchronized with the vehicle end again.

[0065] The road congestion condition of the current road is represented by the road enclosure area, so as to facilitate the road planning of the autonomous vehicle in advance or the timely synchronization of the congestion condition to the vehicle end in the vehicle-road cooperation scene. At the same time, the road enclosure area also has a certain influence range, which can be used to estimate the previous traffic congestion condition or perform traffic flow control in advance.

[0066] Unlike the related art, the vehicle position estimation method is usually used in the cloud service end, or the image collected by the roadside camera at the road end is used to judge whether congestion occurs at the intersection. The above method can calculate the influence range of the nearby lane after the current intersection congestion based on the distributed computing framework and the received digital twin data in near real time.

[0067] Further, the above method can judge the congestion condition of each lane and timely report it to the vehicle end for synchronization. The above method uses a distributed real-time stream computing framework, which can ensure the real-time performance of data processing. At the same time, if the congestion level at the target intersection reaches the congestion standard, the digital twin data after the congestion is processed one by one in the form of reading the REDIS cache, so as to ensure the low delay of data processing.

[0068] In an embodiment of the present application, the congestion level of the target intersection is determined according to the digital twin data, including: obtaining the average vehicle delay time based on the lane level in the target intersection according to the digital twin data; calculating the maximum average vehicle delay time of the preset driving direction in the road traffic area according to the average vehicle delay time, and determining the congestion level of the preset driving direction; if the congestion level of the target intersection reaches the congestion standard, the road containment area of each lane in the road traffic area in the target intersection is established, including: if the congestion level of the target intersection reaches the congestion standard, the position of the last vehicle of each lane is determined; based on the coordinate position of the stop line in the target intersection and the position of the last vehicle, the boundary position of the road containment area is calculated, wherein the boundary position includes a plurality of coordinate point positions of each lane affecting the corresponding road containment area when congested.

[0069] Please refer to Figure 2 For the leftmost lane, the driving direction is left turn, and at this time the road containment area includes the containment area of points A, B, C, and D. For the rightmost lane, the driving direction is straight, and at this time the road containment area includes the containment area of points E, I, J, and K. For the middle lane, the driving direction is straight, and at this time the road containment area includes the containment area of points B, E, F, G, and H.

[0070] Please refer to Figure 3 The vehicle of UUid1 is located at the queuing turn position from south to north at t1, and turns left to the lane from east to west at t1. Similarly, the vehicle of UUid2 is located at the queuing straight position from south to north at t3, and continues to straight to the lane from south to north at t4. Considering the irregularity of the road, it is possible to encounter a three-lane to four-lane situation, which will encounter a corresponding sharp corner or polygon road containment area in the middle. Figure 3 The three-lane situation is shown.

[0071] Please refer to Figure 4 The vehicle of UUid1 is located at the queuing turn position from south to north at t1, and turns left to the lane from east to west at t1. Similarly, the vehicle of UUid2 is located at the queuing straight position from south to north at t3, and continues to straight to the lane from south to north at t4. Considering the irregularity of the road, it is possible to encounter a three-lane to four-lane situation, which will encounter a corresponding sharp corner or polygon road containment area in the middle. Figure 4 The four-lane situation is shown.

[0072] Please refer to Figure 3 and Figure 4It can be seen that, for the road enclosure area, the stop line at the target intersection, the position of the last vehicle in the queue, and the lane lines on both sides are determined.

[0073] Exemplarily, Figure 3 Or Figure 4 In the method, according to the received digital twin data, a road enclosure area composed of 4 point positions is returned, a road enclosure area composed of 6 point positions is returned, and a road enclosure area composed of 8 point positions is returned.

[0074] According to the digital twin data, the average vehicle delay time based on the lane level in the target intersection is obtained; according to the average vehicle delay time, the maximum average vehicle delay time of the preset driving direction in the road passing area is calculated, the congestion level of the preset driving direction is determined, the position of the last vehicle in each lane is judged, the boundary position of the enclosure range is calculated based on the stop line coordinate point and the position of the last vehicle, and multiple coordinate points of each lane affecting the enclosure range are obtained.

[0075] If the congestion level of the target intersection reaches the congestion standard, the position of the last vehicle in each lane is judged; based on the coordinate position of the stop line in the target intersection and the position of the last vehicle, the boundary position of the road enclosure area is calculated, wherein the boundary position includes multiple coordinate point positions of each lane affecting the corresponding road enclosure area when congested. Based on the average vehicle delay time based on the lane level, the maximum average vehicle delay time of a certain direction is calculated, and the congestion level (range) of the vehicle driving direction is obtained.

[0076] In an embodiment of the present application, the influence range of the congestion of the target intersection on the nearby driving area is calculated based on the road enclosure area, and the influence range is displayed at the vehicle end or the global path planning at the vehicle end is performed.

[0077] As Figure 5 shown, the influence range of the congestion of the target intersection on the nearby driving area is calculated based on the road enclosure area, and is sent to the vehicle end based on the V2X communication protocol, and then is displayed at the vehicle end. Alternatively, the global path planning at the vehicle end is performed.

[0078] In an embodiment of the present application, before the road enclosure area of each lane in the road passing area of the target intersection is established, the data of the target intersection in the digital twin data is filtered out, and it is judged whether there is abnormal vehicle fusion data in the filtered digital twin data; if the abnormal vehicle fusion data exists, the abnormal vehicle fusion is compensated.

[0079] The abnormal vehicle fusion data can be caused by the image acquisition of the roadside camera, such as when a long-range camera is used to shoot vehicles at an intersection, the close-up of the vehicle cannot be obtained, and therefore, loss or abnormality can easily occur. In the method, the data of the target intersection is filtered out, and it is determined whether there is abnormal vehicle fusion data in the filtered digital twin data, the digital twin abnormal data is compensated, and the calculation process can maximize the representation of the influence of the real-world intersection congestion on the nearby range.

[0080] In an embodiment of the present application, the establishing of the road enclosure area of each lane in the road passing area in the target intersection comprises: determining the to-be-processed data in the road enclosure area based on the grouping result of each lane and the congestion calculation time of the high-definition map, wherein the high-definition map comprises Group_ID attribute information and Group_Num attribute information in the area where the current target intersection is located; obtaining the corresponding vehicle UUID and the position at the corresponding current time point in the road enclosure area according to the to-be-processed data; and calculating the latitude and longitude position of the last vehicle in the road enclosure area according to the vehicle UUID and the position at the current time point.

[0081] The "high-definition map" refers to the high-definition map loaded in the area of the target intersection. According to the high-definition map, the grouping result of each lane is obtained, that is, it is divided into lane 1, 2 and 3 groups. The "congestion calculation time" refers to the calculation time within a fixed time period after reaching the congestion level. For example, the last 0.5 seconds within 5 seconds as the congestion calculation time.

[0082] After determining the to-be-processed data, the corresponding vehicle UUID and the position at the corresponding current time point in the road enclosure area are obtained in the to-be-processed data. According to the vehicle UUID and the position at the current time point, the latitude and longitude position of the last vehicle in the road enclosure area is calculated.

[0083] In an embodiment of the present application, the establishing of the road enclosure area of each lane in the road passing area in the target intersection further comprises: obtaining an extension line of the latitude and longitude information corresponding position according to the latitude and longitude information of the last vehicle; associating the same Group_Num attribute information to obtain continuous road two-side lane lines; making a perpendicular line to the extension line corresponding to the latitude and longitude information according to the road two-side lane lines and the latitude and longitude information of the last vehicle, and obtaining a foot of the perpendicular line; traversing the road two-side lane lines to obtain a point of the lane line satisfying a preset offset angle; and obtaining the road enclosure area of each lane according to the position point of the lane line and the position point of the foot.

[0084] The Group_ID and the Group_Num are attributes provided by the high-definition map, and the provided is a road segment separated by the Group_Num. In order to connect the road, the road segments of the same Group_Num are associated and calculated.

[0085] In the process of calculating the road closure area according to the angle, firstly, the latitude and longitude position of the last vehicle on the corresponding road is judged, and the distance between the latitude and longitude of all vehicles and the stop line of the corresponding road is calculated. The farthest distance is the last vehicle. Then, the perpendicular lines are drawn in the negative direction of the road direction (the driving direction is the positive direction) according to the position of the last vehicle. The foot points are obtained. Finally, the information of the corresponding road segment is obtained, and a series of position points are obtained. The angle is calculated by calculating the perpendicular line and the point of the last vehicle, and the point of all lane lines. Finally, the lane lines on both sides of the road are traversed to obtain the lane line points that meet the preset offset angle. The road closure area of each lane is obtained according to the position points of the lane line and the position points of the foot point.

[0086] In an embodiment of the present application, after obtaining the corresponding vehicle UUID and the position of the corresponding current time point in the road closure area according to the to-be-processed data, the method further comprises: calculating a preset swing angle according to the angle between each point corresponding to the vehicle UUID and the center point of the current road; if the angle is greater than the preset swing angle, the point is excluded as a reverse point, and the road includes two lanes, three lanes, and four lanes.

[0087] Due to the irregularity of the road, it is possible to encounter a three-lane road becoming a four-lane road. For the case that the road can be two lanes, three lanes, or four lanes, different types of lanes can be obtained after excluding the reverse point. Generally, the position point of the vehicle is the center point of the current road. The preset swing angle is calculated according to the angle between each point corresponding to the vehicle UUID and the center point of the current road. If it is a reverse point, it cannot be included in the corresponding point in the road closure area.

[0088] In an embodiment of the present application, the method of establishing the road closure area of each lane in the road driving area in the target intersection further comprises: if the current lane is within the range of the road solid line, connecting the solid line to obtain the road closure area.

[0089] When the lane is within the range of the solid line, the solid line is directly connected to obtain a closed figure. Because the solid line is not allowed to change lanes, the solid fence can be preferentially constructed.

[0090] The embodiment of the present application also provides a digital twin data processing device 600, which comprises Figure 6As shown, a structural schematic diagram of the digital twin data processing apparatus in the embodiment of the present application is provided, and the digital twin data processing apparatus 600 at least includes a receiving module 610, a judging module 620, and an establishing module 630, wherein:

[0091] In an embodiment of the present application, the receiving module 610 is specifically used for receiving digital twin data.

[0092] The digital twin data is further processed through a background service such as a cloud service. For the digital twin data obtained after processing by a digital twin system, the digital twin system can collect image information of each lane through a camera deployed at an intersection on a roadside end, and the image information is carried with vehicle position information and a camera ID (which camera takes) when being reported. Meanwhile, after being received on the roadside end, the image information is processed according to a pre-stored calibration file on the roadside end to obtain the digital twin data corresponding to the vehicle in a real scene.

[0093] It can be understood that in actual use, if the same vehicle is photographed by multiple cameras, the vehicle will be reported after fusion and deduplication processing.

[0094] In an embodiment of the present application, the judging module 620 is specifically used for judging a congestion level of a target intersection according to the digital twin data.

[0095] The congestion level is judged according to a national standard of road congestion, and if the relevant standard is met, it is considered that the target intersection is congested. In specific calculation, the national standard of road congestion is first called, and then the digital twin data is processed according to an intersection congestion level algorithm, and the result is taken as a standard for judging the congestion level of the target intersection.

[0096] The selection of the target intersection is determined according to an actual business scenario, and different traffic driving conditions from north to south or from south to north, and from west to east or from east to west at the intersection need to be considered. Meanwhile, since the congestion of the target intersection is judged, the area before the vehicle stop line at the intersection does not need to be considered, that is, the driving direction of the traffic can be straight, straight right turn, or straight left turn (left turn waiting), and the like.

[0097] In an embodiment of the present application, the establishing module 630 is specifically used for establishing a road enclosure area of each lane in a road driving area in the target intersection if the congestion level of the target intersection reaches a congestion standard.

[0098] If the congestion level of the target intersection reaches the congestion standard after the calculation of the above steps, the road enclosure area of each lane in the road driving area at the lane level is established, and after the road enclosure area is calculated, it is synchronized with the vehicle end.

[0099] The road enclosure area represents the congestion situation of the current road, so as to facilitate the road planning of the autonomous vehicle in advance or the synchronization of the congestion situation to the vehicle end in time in the vehicle-infrastructure cooperation scene. Meanwhile, the road enclosure area also has a certain influence range, and the previous traffic congestion situation can be estimated or traffic flow can be limited in advance according to the influence range.

[0100] It can be understood that the digital twin data processing device described above can realize each step of the digital twin data processing method provided in the foregoing embodiments, and the related explanations about the digital twin data processing method are all applicable to the digital twin data processing device, which will not be repeated here.

[0101] As shown in Figure 7 , it is a flowchart of the digital twin data processing method in the preferred embodiment of the present application, which specifically includes the following flow:

[0102] Step S710, acquiring KFK data, calculating congestion level, and when the congestion level is greater than a fixed value, passing the current 5-second data downstream. 5 seconds are only for illustration, mainly considering the requirement of ensuring real-time. KFK data refers to the digital twin data obtained through Kafka queue.

[0103] Step S720, filtering data outside the intersection.

[0104] Filtering out data other than the target intersection in the digital twin data, and determining whether there is abnormal vehicle fusion data in the filtered digital twin data.

[0105] Step S730, compensating the fusion vehicle.

[0106] If the abnormal vehicle fusion data exists, the abnormal vehicle fusion is compensated.

[0107] Step S740, grouping according to Group_ID and Group_Num.

[0108] The high-definition map includes Group_ID attribute information and Group_Num attribute information in the area where the current target intersection is located. Based on the grouping result of each lane of the high-definition map and the congestion calculation time, the to-be-processed data in the road enclosure area is determined.

[0109] Step S750, determining which data after grouping is processed by enclosure.

[0110] According to the to-be-processed data, the corresponding vehicle UUID in the road enclosure area and the position at the corresponding current time point are obtained.

[0111] Step S760, obtain the data in the last 0.5 seconds within 5 seconds, obtain the corresponding UUID and the position of the last time point.

[0112] For "congestion calculation time", it refers to the calculation time within a timing period after reaching the congestion level. For example, the last 0.5 seconds within 5 seconds as the congestion calculation time.

[0113] Step S770, according to the angle of each point corresponding to the vehicle UUID and the center point of the current road, calculate the preset swing angle, if the preset swing angle is greater than 100 degrees, it is considered as a reverse point and needs to be excluded.

[0114] Step S780, calculate the position of the last vehicle and extend, obtain Group_Num associated together.

[0115] The Group_ID and the Group_Num are attributes provided by the high-precision map, and the road is separated by segments. In order to connect the road, link the road segments with the same Group_Num together for calculation.

[0116] Step S790, according to the latitude and longitude information of the last vehicle and the lane lines on both sides of the road, make a perpendicular line to the extension line of the corresponding position of the latitude and longitude information, obtain the foot of the perpendicular; traverse the lane lines on both sides of the road to obtain the point position of the lane line that meets the preset offset angle; according to the position point of the lane line and the position point of the foot, obtain the road enclosing area of each lane.

[0117] When calculating the road enclosing area according to the angle, first judge the latitude and longitude position of the last vehicle on the corresponding road, calculate the distance between the latitude and longitude of all vehicles and the stop line of the corresponding road, and the farthest distance is the last vehicle. Then, according to the obtained position of the last vehicle, make a perpendicular line in the negative direction of the road direction (the driving direction is positive). Obtain the foot. Finally, obtain the information of the corresponding road segment to obtain a series of position points. Calculate the angle of the perpendicular line and the point of the last vehicle, and the point of all lane lines. Finally, traverse the lane lines on both sides of the road to obtain the point position of the lane line that meets the preset offset angle; according to the position point of the lane line and the position point of the foot, obtain the road enclosing area of each lane.

[0118] Figure 8 It is a structural schematic diagram of an electronic device according to an embodiment of the present application. Please refer to Figure 8At the hardware level, the electronic device includes a processor, and optionally further includes an internal bus, a network interface, a memory. The memory can include a memory such as a random-access memory (RAM), and can further include a non-volatile memory such as at least one disk memory. Of course, the electronic device can further include other hardware required by the business.

[0119] The processor, the network interface, and the memory can be connected to each other through the internal bus, which can be an industry standard architecture (ISA) bus, a peripheral component interconnect (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one bidirectional arrow is used in the figure, but it does not mean that there is only one bus or only one type of bus.

[0120] The memory is used to store programs. Specifically, the program can include program code including computer operation instructions. The memory can include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0121] The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs, and forms a digital twin data processing apparatus at the logical level. The processor executes the program stored in the memory, and is specifically used to execute the following operations:

[0122] Receive digital twin data;

[0123] According to the digital twin data, determine the congestion level of the target intersection;

[0124] If the congestion level of the target intersection reaches the congestion standard, establish a road enclosure area for each lane in the road driving area in the target intersection.

[0125] The above as described in the present application Figure 1The method performed by the digital twin data processing apparatus disclosed in the embodiments shown can be applied in a processor or implemented by the processor. The processor can be an integrated circuit chip with processing capability of signals. In the implementation process, each step of the above method can be completed by integrated logic circuits in hardware or instructions in the form of software in the processor. The processor mentioned above can be a general processor, including a central processing unit (CPU), a network processor (NP), etc.; or a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. Each method, step and logic block diagram disclosed in the embodiments of the present application can be implemented or executed. The general processor can be a microprocessor or the processor can also be any conventional processor. The steps of the method disclosed in combination with the embodiments of the present application can be directly embodied as a hardware code processor for execution, or a combination of hardware and software modules in the code processor for execution. The software module can be located in a random access memory, a flash memory, a read-only memory, a programmable read-only memory or an electrically erasable programmable memory, a register or other mature storage medium in the art. The storage medium is located in the memory, and the processor reads the information in the memory and combines the hardware to complete the steps of the above method.

[0126] The electronic device can also execute the method performed by the digital twin data processing apparatus in the embodiments shown, and implement the functions of the digital twin data processing apparatus in the embodiments shown. The embodiments of the present application will not be repeated here. Figure 1 The electronic device can also execute the method performed by the digital twin data processing apparatus in the embodiments shown, and implement the functions of the digital twin data processing apparatus in the embodiments shown. The embodiments of the present application will not be repeated here. Figure 1 The electronic device can also execute the method performed by the digital twin data processing apparatus in the embodiments shown, and implement the functions of the digital twin data processing apparatus in the embodiments shown. The embodiments of the present application will not be repeated here.

[0127] The embodiments of the present application also propose a computer readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by an electronic device including a plurality of application programs, can cause the electronic device to execute the method performed by the digital twin data processing apparatus in the embodiments shown, and specifically for executing: Figure 1 The method performed by the digital twin data processing apparatus in the embodiments shown, and specifically for executing:

[0128] receiving digital twin data;

[0129] determining the congestion level of the target intersection according to the digital twin data;

[0130] If the congestion level of the target intersection reaches the congestion criterion, a road enclosure area of each lane in a road driving area in the target intersection is established.

[0131] Those skilled in the art will appreciate that embodiments of the application can be supplied as methods, systems, or computer program products. Accordingly, the application can be embodied in the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the application can be embodied in the form of a computer program product on one or more computer readable storage media (including, but not limited to, disk memory, CD-ROMs, optical storage media, etc.) having computer usable program code embodied therein.

[0132] The present application is described in reference to the flowchart and / or block diagrams of the method, apparatus (system) and computer program product according to embodiments of the application. It should be understood that each flow and / or block in the flowchart and / or block diagrams, and combinations of flows and / or blocks in the flowchart and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can 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 and / or block diagrams block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart and / or block diagram block or blocks.

[0133] These computer program instructions can 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 instructions means which implement the function specified in the flowchart and / or block diagrams block or blocks. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the function specified in the flowchart and / or block diagram block or blocks.

[0134] These computer program instructions can 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 function specified in the flowchart and / or block diagrams block or blocks. Figure 1 one or more flows and / or blocks ​ means for carrying out the function specified in the flowchart and / or block diagram block or blocks.

[0135] In one typical configuration, the computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0136] Memory can include non-persistent memory, Random Access Memory (RAM), and / or non-volatile memory such as read-only memory (ROM) or flash memory, etc. in a computer readable medium. Memory is an example of computer readable media.

[0137] Computer readable media includes permanent and non-permanent, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD), or other optical storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information accessible to a computing device. According to the definition herein, computer readable media does not include transitory media such as modulated data signals and carrier waves.

[0138] It should also be noted that the terms "comprising", "containing", or any other similar term are intended to encompass non-exclusive inclusions such that a process, method, article, or apparatus that comprises a list of elements does not include those elements solely, but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0139] Those skilled in the art will understand that embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer available storage media (including, but not limited to, disk memory, CD-ROM, optical storage, etc.) containing computer usable program code.

[0140] The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes can be made to the present application by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in 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; judging the congestion level of a target intersection according to the digital twin data; if the congestion level of the target intersection reaches the congestion standard, establishing a road enclosure area of each lane in the road travel area within the target intersection; the judgment of the congestion level of the target intersection according to the digital twin data comprises: obtaining the average vehicle delay time based on lane in the target intersection according to the digital twin data; calculating the maximum average vehicle delay time of the preset travel direction in the road traffic area according to the average vehicle delay time, and determining the congestion level of the preset travel direction; if the congestion level of the target intersection reaches the congestion standard, establishing a road enclosure area of each lane in the road travel area within the target intersection, comprising: if the congestion level of the target intersection reaches the congestion standard, judging the position of the last vehicle of each lane; based on the stop line coordinate position in the target intersection and the position of the last vehicle, calculating the boundary position of the road enclosure area, wherein the boundary position comprises a plurality of coordinate point positions of each lane affecting the corresponding road enclosure area when congested; calculating the influence range of the congestion of the target intersection on the nearby travel area according to the road enclosure area, so as to display at the vehicle end or perform global path planning at the vehicle end.

2. The method of claim 1, wherein, Before establishing the road enclosure area of each lane in the road travel area within the target intersection, it further comprises: filtering out the data of the target intersection in the digital twin data, and judging whether there is abnormal vehicle fusion data in the filtered digital twin data; if there is abnormal vehicle fusion data, compensate for the abnormal vehicle fusion.

3. The method of claim 2, wherein, The establishment of the road enclosure area of each lane in the road travel area within the target intersection comprises: based on the grouping result of each lane and the congestion calculation time of high-precision map, determine the to-be-processed data in the road enclosure area, wherein the high-precision map comprises Group_ID attribute information and Group_Num attribute information in the current target intersection area, wherein the Group_ID and the Group_Num are attributes provided by the high-precision map, and the road is separated by the Group_Num, in order to connect the road, the same Group_Num road link can be associated together for calculation; according to the to-be-processed data, obtaining the vehicle UUID corresponding to the road enclosure area and the position corresponding to the current time point; according to the vehicle UUID and the position corresponding to the current time point, calculating the latitude and longitude position of the last vehicle in the road enclosure area.

4. The method of claim 3, wherein, The establishment of the road enclosure area of each lane in the road travel area within the target intersection further comprises: according to the latitude and longitude information of the last vehicle, obtaining the extension line of the position corresponding to the latitude and longitude information; associating the same Group_Num attribute information to obtain the continuous road lane line on both sides of the road; According to the lane lines on both sides of the road and the latitude and longitude information of the last vehicle, a perpendicular line is drawn to the extension line of the position corresponding to the latitude and longitude information, and a foot point is obtained; The lane lines on both sides of the road are traversed to obtain a point position of a lane line that meets a preset offset angle; According to the position point of the lane line and the position point of the foot point, a road bounding area of each lane is obtained.

5. The method of claim 3, wherein, After obtaining the corresponding vehicle UUID and the position of the corresponding current time point in the road bounding area according to the to-be-processed data, the method further includes: According to the angle between each point corresponding to the vehicle UUID and the center point of the current road, a preset swing angle is calculated. If it is greater than the preset swing angle, it is excluded as a reverse point. The road includes two lanes, three lanes, and four lanes.

6. The method of claim 1, wherein, The method further includes: The twin data is processed based on a Flink real-time stream computing framework, and is transmitted by establishing a message queue.

7. The method of any one of claims 1 to 6, wherein, The device includes: A receiving module for receiving digital twin data; 8. A twin data processing apparatus, wherein, A judging module for judging the congestion level of a target intersection according to the digital twin data; An establishing module for establishing a road bounding area of each lane in a road driving area in the target intersection if the congestion level of the target intersection reaches a congestion standard; The method further includes: According to the digital twin data, the average vehicle delay time in the target intersection based on the lane level is obtained. According to the average vehicle delay time, the maximum average vehicle delay time of a preset driving direction in a road passing area is calculated to determine the congestion level of the preset driving direction. The method further includes: If the congestion level of the target intersection reaches the congestion standard, the position of the last vehicle of each lane is judged. Based on the stop line coordinate position in the target intersection and the position of the last vehicle, the boundary position of the road bounding area is calculated, wherein the boundary position includes a plurality of coordinate point positions that affect the corresponding road bounding area when each lane is congested. According to the road bounding area, the influence range of the congestion of the target intersection on the nearby driving area is calculated, which is used for displaying at the vehicle end or performing global path planning at the vehicle end. ​ ​

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