Perception data cloud service system based on vehicle and road cloud and data processing method

Abstract

The invention relates to the technical field of vehicle-road cooperation, in particular to a perception data cloud service system based on vehicle-road cloud and a data processing method. The method comprises the following steps: acquiring a sensing result of each roadside cloud service; integrating all sensing results into the same set; dividing the sensing service area into grids according to intervals; calculating a center point coordinate of each grid, and establishing a null array; traversing and calculating the linear distance between the target in the set and the center point coordinate; filling the null array with the targets whose linear distances are smaller than the spacing; acquiring a sensing request parameter position coordinate and a distance radius sent by the vehicle; calculating the number of the grid closest to the position coordinate according to the position coordinate, summarizing the sensing structures of all grids in the radius range, and sending the summarized sensing structures to the vehicle end; the system comprises a road end, a cloud end and a vehicle end. In this way, the distance range of the vehicle end for obtaining the roadside sensing data is enlarged.

Description

Technical Field

[0001] The present invention relates to the field of vehicle-road collaborative technology, and in particular to a vehicle-road cloud-based perception data cloud service system and a data processing method. Background Art

[0002] Vehicle-road cooperative perception is an emerging technology that integrates information from vehicle-side and roadside perception devices, such as cameras, radars, and lidars, to jointly perceive the traffic environment. Its core lies in the use of vehicle-road cooperative communications (such as C-V2X, DSRC) and multimodal data fusion technology to expand the perception range, make up for the blind spot on one side, and improve the accuracy of target detection and behavior prediction. This technology is widely used in intelligent transportation and autonomous driving scenarios, which helps to improve the safety, stability and traffic efficiency of the system, and provides key support for the realization of intelligent transportation.

[0003] At present, the vehicle-road collaborative perception technology mainly broadcasts the structured perception results of the road side through the PC5 channel of the roadside communication unit RSU. The on-board unit OBU on the vehicle side communicates with the RSU through the PC5 channel to receive the structured perception results broadcast by the road side. After receiving the perception results, the vehicle-side OBU uses them for subsequent perception fusion modules.

[0004] In the above method, the signal broadcast range of the roadside communication unit RSU is several hundred meters. Only when the vehicle drives within the broadcast distance range of the RSU device can it receive the roadside sensing results of the intersection. The vehicle cannot receive roadside sensing results farther away, and the sensing result broadcast range is small. Summary of the invention

[0005] The purpose of the present invention is to provide a perception data cloud service system and data processing method based on vehicle-road cloud, aiming to solve the technical problems in the prior art that the roadside perception results of the intersection can only be received after the vehicle travels within the broadcast distance range, the vehicle cannot receive the roadside perception results farther away, and the perception result broadcast range is small.

[0006] To achieve the above purpose, the present invention adopts a vehicle-road cloud-based perception data cloud service data processing method, which includes the following steps: Obtain the perception results of each roadside cloud service; Integrate all perception results into the same set; Divide the sensing service area into grids according to the spacing; Calculate the coordinates of the center point of each grid and create an empty array; Traverse and calculate the straight-line distance between the target and the center point coordinates in the set; Fill the targets whose straight-line distance is less than the spacing into the empty array; Get the location coordinates and distance radius of the perception request parameters sent by the vehicle; The grid number closest to the position coordinates is calculated, and the perception structures of all grids within the radius are summarized and sent to the vehicle end.

[0007] Among them, in the step of obtaining the perception results of each roadside cloud service: The perception results of each roadside cloud service are used express.

[0008] Among them, in the step of integrating all perception results into the same set: All Integrate into one collection In which: ; The number of perception targets contained in this set is recorded as m indivual; ; in x , y Represents the target position coordinates, heading Represents the target heading, v represents the target speed, length , width , height Represents the length, width and height of the target respectively. type Represents the type of target.

[0009] Among them, in the step of dividing the sensing service area into grids according to the spacing: The service area of ​​the perception data cloud service is divided into h Divide the grid, and each grid number is recorded as , the number of grids in each row is recorded as q indivual.

[0010] Among them, in the steps of calculating the coordinates of the center point of each grid and creating an empty array: Calculate the coordinates of each grid center point , and create an empty array for each grid .

[0011] Among them, in the step of traversing and calculating the straight-line distance between the target and the center point coordinates in the set: Traversal calculation Target and The straight-line distance is: .

[0012] Among them, in the step of filling the targets whose straight-line distance is less than the spacing into the empty array: like Less than h , then Fill in an empty array middle.

[0013] Among them, in the step of obtaining the position coordinates and distance radius of the perception request parameters sent by the vehicle: Obtain the perception request parameters sent by the vehicle in real time, including location coordinate information and distance radius .

[0014] Among them, in the step of calculating the grid number closest to the position coordinates, summarizing the perception structures of all grids within the radius, and sending them to the vehicle end: According to the location coordinates V Calculate the grid number closest to it j , will be numbered j The grid is centered and has a side length of All the perception results within the rectangular range are summarized and sent to the vehicle end, and we get: ; in: .

[0015] The present invention also provides a vehicle-road-cloud-based perception data cloud service system, including a road side, a cloud side and a vehicle side.

[0016] The present invention provides a perception data cloud service system and data processing method based on vehicle-road cloud, which obtains the perception results of each roadside cloud service; integrates all the perception results into the same set; divides the perception service area into grids according to the spacing; calculates the center point coordinates of each grid and establishes an empty array; traverses and calculates the straight-line distance between the targets in the set and the center point coordinates; fills the targets whose straight-line distance is less than the spacing into the empty array; obtains the perception request parameter position coordinates and distance radius sent by the vehicle; calculates the grid number closest to the position coordinates according to the position coordinates, summarizes the perception structures of all grids within the radius, and sends them to the vehicle end, thereby increasing the distance range for the vehicle end to obtain roadside perception data. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0018] Figure 1 It is a step flow chart of the method for processing vehicle-road-cloud-based perception data cloud service data of the present invention.

[0019] Figure 2 It is a flow chart of the vehicle-road-cloud-based perception data cloud service data processing method of the present invention.

[0020] Figure 3 It is a schematic diagram of the grid division of the present invention.

[0021] Figure 4 It is a structural principle diagram of the vehicle-road-cloud-based perception data cloud service system of the present invention. DETAILED DESCRIPTION

[0022] Here, exemplary embodiments are described in detail, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application.

[0023] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0024] It should be understood that although the terms first, second, third, etc. may be used in the present application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish the same type of information from each other. For example, without departing from the scope of the present application, the first information may also be referred to as the second information, and similarly, the second information may also be referred to as the first information. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0025] See also Figure 1~Figure 3 The present invention provides a method for processing perception data cloud service data based on vehicle-road cloud, comprising the following steps: S100: Obtaining perception results of each roadside cloud service.

[0026] In this embodiment, the perception results of each roadside cloud service are obtained, and the perception results of each roadside cloud service are used express.

[0027] S200: Integrate all perception results into the same set.

[0028] In this embodiment, all Integrate into one collection In which: ; The number of perception targets contained in this set is recorded as m indivual; ; in x , y Represents the target position coordinates, heading Represents the target heading, v represents the target speed, length , width , height Represents the length, width and height of the target respectively. type Represents the type of target.

[0029] S300: Divide the sensing service area into grids according to the spacing.

[0030] In this embodiment, if Figure 3 As shown in the figure, the service area of ​​the perception data cloud service is divided into h Divide the grid, and each grid number is recorded as , the number of grids in each row is recorded as q indivual.

[0031] S400: Calculate the coordinates of the center point of each grid and create an empty array.

[0032] In this embodiment, the coordinates of each grid center point are calculated , and create an empty array for each grid .

[0033] S500: Traverse and calculate the straight-line distance between the target in the set and the center point coordinates.

[0034] In this embodiment, the traversal calculation Target and The straight-line distance is: .

[0035] S600: Fill the targets whose straight-line distance is less than the spacing into the empty array.

[0036] In this embodiment, the targets whose straight-line distance is less than the spacing are filled into the empty array. Less than h , then Fill in an empty array Otherwise, repeat S500.

[0037] S700: Obtain the location coordinates and distance radius of the perception request parameters sent by the vehicle.

[0038] In this embodiment, the perception request parameters sent by the vehicle are obtained in real time, including the location coordinate information and distance radius .

[0039] S800: Calculate the grid number closest to the position coordinates, summarize the perception structures of all grids within the radius, and send them to the vehicle end.

[0040] In this embodiment, according to the position coordinates V Calculate the grid number closest to it j , will be numbered j The grid is centered and has a side length of All the perception results within the rectangular range are summarized and sent to the vehicle end, and we get: ; in: .

[0041] In the present invention, firstly, the perception results of each roadside cloud service are obtained; then all the perception results are integrated into the same set; then the perception service area is divided into grids according to the spacing; then the coordinates of the center point of each grid are calculated, and an empty array is established; the straight-line distances between the targets in the calculation set and the center point coordinates are traversed; then the targets whose straight-line distances are less than the spacing are filled into the empty array; then the perception request parameter position coordinates and distance radius sent by the vehicle are obtained; finally, the grid number closest to it is calculated according to the position coordinates, the perception structures of all grids within the radius are summarized, and sent to the vehicle end; this realizes increasing the distance range for the vehicle end to obtain roadside perception data, increasing the ways for the vehicle end to obtain roadside perception data, and improving the utilization efficiency of roadside perception data.

[0042] See also Figure 4 The present invention also provides a perception data cloud service system based on vehicle-road-cloud, including a road side, a cloud side and a vehicle side.

[0043] In this embodiment, the road side is mainly composed of roadside sensing equipment and roadside communication units. Its main task is to upload real-time sensing results to the cloud through 4G / 5G or wired network, and at the same time broadcast the sensing results to the vehicle side through the roadside communication unit RSU.

[0044] The roadside cloud service on the cloud side is responsible for receiving the perception result data uploaded by each intersection. The perception data cloud service on the cloud side is responsible for aggregating the perception data of all roadside cloud services and providing a variety of perception data services to vehicles through different service interfaces.

[0045] The vehicle obtains local perception data broadcast by the roadside communication unit in real time through the PC5 channel, and also obtains global perception data from the perception data cloud service in the cloud in real time through the 4G / 5G mobile network.

[0046] The difference between this architecture and the traditional architecture is that the cloud adds a perception data cloud service, which aggregates the isolated roadside cloud service data and packages the perception data to provide perception data services for vehicles. The advantages of this architecture are as follows: 1. Vehicles are no longer limited to PC5 communication mode, and can use mobile cellular networks to obtain data at the same time. In this way, vehicles without pre-installed on-board communication units (OBUs) can also obtain perception data through existing T-BOXs, greatly expanding the scope of data services; Second, this architecture breaks the data silos of each isolated roadside cloud service and integrates the data. Vehicles do not need to connect to each roadside cloud service separately, but only need to connect to the perception data cloud service once; 3. This architecture breaks the limitation that vehicles can only passively receive RSU broadcast data, and enables vehicles to obtain data as required by their functional applications.

[0047] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the contents disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary technical means in the art that are not disclosed in the present application.

[0048] It will be appreciated that the present application is not limited to the exact construction that has been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof.

Claims

1. A method for processing perception data cloud service data based on vehicle-road cloud, characterized in that: The steps include: Obtain the perception results of each roadside cloud service; Integrate all perception results into the same set; Divide the sensing service area into grids according to the spacing; Calculate the coordinates of the center point of each grid and create an empty array; Traverse and calculate the straight-line distance between the target and the center point coordinates in the set; Fill the targets whose straight-line distance is less than the spacing into the empty array; Get the location coordinates and distance radius of the perception request parameters sent by the vehicle; The grid number closest to the position coordinates is calculated, and the perception structures of all grids within the radius are summarized and sent to the vehicle end.

2. The method for processing perception data cloud service data based on vehicle-road cloud according to claim 1, characterized in that: In the steps of obtaining the perception results of each roadside cloud service: The perception results of each roadside cloud service are used express.

3. The method for processing data of a perception data cloud service based on a vehicle-road cloud as claimed in claim 2, characterized in that: In the step of combining all perception results into the same set: All Integrate into one collection In which: ； The number of perception targets contained in this set is recorded as m indivual; ； in x , y represents the target position coordinates, heading Represents the target heading, v represents the target speed, length , width , height Represents the length, width and height of the target respectively. type Represents the type of target.

4. The method for processing perception data cloud service data based on vehicle-road cloud according to claim 3, characterized in that: In the step of dividing the perception service area into grids according to the spacing: The service area of ​​the perception data cloud service is divided into h Divide the grid, and each grid number is recorded as , the number of grids in each row is recorded as q indivual.

5. The method for processing perception data cloud service data based on vehicle-road cloud according to claim 4, characterized in that: In the steps of calculating the coordinates of the center point of each grid and creating an empty array: Calculate the coordinates of each grid center point , and create an empty array for each grid .

6. The method for processing data of a perception data cloud service based on a vehicle-road cloud as claimed in claim 5, characterized in that: In the step of traversing and calculating the straight-line distance between the target and the center point coordinates in the set: Traversal calculation Target and The straight-line distance is: 。 7. The method for processing perception data cloud service data based on vehicle-road cloud according to claim 6, characterized in that: In the step of filling the empty array with targets whose straight line distance is less than the spacing: like Less than h , then Filling an empty array middle.

8. The method for processing perception data cloud service data based on vehicle-road cloud according to claim 7, characterized in that: In the step of obtaining the location coordinates and distance radius of the perception request parameters sent by the vehicle: Obtain the perception request parameters sent by the vehicle in real time, including location coordinate information and distance radius .

9. The method for processing perception data cloud service data based on vehicle-road cloud as claimed in claim 8, characterized in that: In the step of calculating the nearest grid number according to the position coordinates, summarizing the perception structures of all grids within the radius, and sending them to the vehicle side: According to the location coordinates V Calculate the grid number closest to it j , will be numbered j The grid is centered and has a side length of All the perception results within the rectangular range are summarized and sent to the vehicle end, and we get: ； in: 。 10. A vehicle-road-cloud-based perception data cloud service system, applied to the vehicle-road-cloud-based perception data cloud service data processing method as claimed in claim 1, characterized in that: Including road side, cloud side and vehicle side.

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