Vehicle identity sharing method and system for vehicle infrastructure integration and vehicle identity determination device

Abstract

The application discloses a vehicle identity sharing method and system, a vehicle identity determination device and a computer readable storage medium. The method is applied to the vehicle identity determination device and comprises the following steps: receiving first vehicle identity information of a target vehicle sent by a detector corresponding to the vehicle identity determination device; determining second vehicle identity information of the target vehicle according to the position of the vehicle identity determination device in a road and the first vehicle identity information; and sharing the second vehicle identity information of the target vehicle with a downstream vehicle identity determination device of the vehicle identity determination device through a data central processing unit, wherein the downstream vehicle identity determination device is a vehicle identity determination device adjacent to the vehicle identity determination device and located in a first preset direction of the vehicle identity determination device, and the first preset direction is a driving direction defined by the road. According to the application, the vehicle identity information is shared, so that the vehicle identity determination device in the downstream can obtain relatively accurate vehicle identity information.

Description

Technical Field

[0001] This application belongs to the field of information processing technology, and in particular relates to a vehicle identity sharing method, a vehicle identity sharing system, a vehicle identity determination device, and a computer-readable storage medium for vehicle-road cooperative systems. Background Technology

[0002] To obtain information about vehicle behavior on the road, detectors can currently be installed at various points along the road to detect vehicle identification information and track the vehicles based on this information. However, considering that detectors have a certain degree of error, it is difficult to guarantee the accuracy of the vehicle identification information obtained by the detectors when there are many vehicles on the road. Summary of the Invention

[0003] This application provides a vehicle identity sharing method, a vehicle identity sharing system, a vehicle identity determination device, and a computer-readable storage medium for vehicle-road cooperative systems, which can help obtain relatively accurate vehicle identity information.

[0004] In a first aspect, this application provides a vehicle identity sharing method, which is applied to a vehicle identity determination device, comprising:

[0005] Receive the first vehicle identity information of the target vehicle sent by the detector corresponding to the aforementioned vehicle identity determination device;

[0006] Based on the location of the vehicle identification device on the road and the first vehicle identification information, the second vehicle identification information of the target vehicle is determined.

[0007] The second vehicle identity information of the target vehicle is shared with the downstream vehicle identity determination device of the aforementioned vehicle identity determination device by the data central processor. The downstream vehicle identity determination device is a vehicle identity determination device that is adjacent to the aforementioned vehicle identity determination device and located in a first preset direction of the aforementioned vehicle identity determination device. The first preset direction is the driving direction specified by the aforementioned road.

[0008] Secondly, this application provides a vehicle identification device, which includes:

[0009] The receiving module is used to receive the first vehicle identity information of the target vehicle sent by the detector corresponding to the vehicle identity determination device.

[0010] The determination module is used to determine the second vehicle identity information of the target vehicle based on the location of the vehicle identity determination device on the road and the first vehicle identity information.

[0011] The sharing module is used to share the second vehicle identity information of the target vehicle with the downstream vehicle identity determination device of the vehicle identity determination device through the data central processor. The downstream vehicle identity determination device is a vehicle identity determination device that is adjacent to the vehicle identity determination device and located in a first preset direction of the vehicle identity determination device. The first preset direction is the driving direction specified by the road.

[0012] Thirdly, this application provides a vehicle identity sharing system, which includes at least two vehicle identity determination devices as described in the second aspect above, a detector corresponding to each vehicle identity determination device, and at least one data central processor.

[0013] Fourthly, this application provides a vehicle identification device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described in the first aspect.

[0014] Fifthly, this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the method described in the first aspect above.

[0015] In a sixth aspect, this application provides a computer program product comprising a computer program that, when executed by one or more processors, implements the steps of the method described in the first aspect.

[0016] The beneficial effects of this application compared to the prior art are as follows: Through the solution of this application, the downstream vehicle identification device can not only obtain the vehicle identification information of the target vehicle through its own corresponding detector, but also receive the vehicle identification information of the target vehicle shared by the upstream vehicle identification device. Therefore, even if the detector corresponding to the downstream vehicle identification device experiences data delays or detects too many vehicles, it can still track vehicles traveling on the road using the vehicle identification information shared by the upstream vehicle identification device. It is understood that the beneficial effects of the second to sixth aspects mentioned above can be found in the relevant descriptions in the first aspect above, and will not be repeated here. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is an example diagram illustrating the deployment method of the vehicle identity sharing system provided in this application embodiment;

[0019] Figure 2 This is an example architecture diagram of the vehicle identity sharing system provided in the embodiments of this application;

[0020] Figure 3 This is a schematic diagram illustrating the implementation process of the vehicle identity sharing method provided in this application embodiment;

[0021] Figure 4 These are example diagrams showing overlapping and non-overlapping areas of the road segments covered by the radar provided in this application embodiment;

[0022] Figure 5 This is an example diagram of the trajectory points and detection time of the first and second trajectories in the overlapping area provided in the embodiments of this application;

[0023] Figure 6 This is an example diagram of trajectory correction provided in the embodiments of this application;

[0024] Figure 7 This is a structural block diagram of the vehicle identification device provided in the embodiments of this application;

[0025] Figure 8 This is a schematic diagram of the vehicle identification device provided in the embodiments of this application. Detailed Implementation

[0026] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0027] To illustrate the technical solution proposed in this application, specific embodiments are described below.

[0028] The vehicle identity sharing system proposed in the embodiments of this application will be described below. (See also...) Figure 1 , Figure 1An example of how to deploy this vehicle identity sharing system is given. Figure 1 In the highway application scenario shown, a gantry can be deployed at a preset first distance (e.g., 6 kilometers), and a side pole can be deployed between the gantries at a preset second distance (e.g., 2 kilometers). Based on the above deployment of gantry and side poles, this is merely an example; the deployment methods of each detector and vehicle identification device are as follows... Figure 1 As shown. Based on Figure 1 It is known that the vehicle identity sharing system includes: at least two vehicle identification devices (Intelligent Traffic System Stations, ITS Stations), detectors corresponding to each vehicle identification device (the number of detectors being the same as the number of vehicle identification devices), and at least one data centralization processor (Intelligent Traffic System Station, ITP). It should be noted that... Figure 1 There are no restrictions on the number of vehicle identification devices and data central processors, nor are there any restrictions on the deployment method of each detector.

[0029] Specifically, the detectors include trajectory detectors and identification detectors. Specifically, the trajectory detector can be radar, and the identification detector can be a camera or a roadside unit (RSU). That is, the detector can include both a camera and radar, or it can include both an RSU and radar; the specific composition of the detector is not limited here. As an example, radar is typically installed to achieve full coverage, specifically: one radar is deployed on each gantry facing a first preset direction and another facing a second preset direction. Each radar covers all lanes of the road, where the first preset direction is the prescribed driving direction, and the second preset direction is the opposite direction of the prescribed driving direction. Figure 1 The radar on the gantry shown can cover three lanes. One radar is deployed on each side pole, facing both a first and a second preset direction, with each radar providing lateral coverage of all lanes of the road. Under the gantry and side pole deployment schemes given above, the coverage area (i.e., detection range) of each radar can be at least 1 km.

[0030] As an example only, identification detectors, i.e., RSUs or cameras, will also be deployed on the gantries and side poles. Assuming RSUs are used, then: two RSUs are deployed on each gantry for each lane; one RSU is used to detect the identity of vehicles in the near-field area of ​​the lane, and the other is used to detect the identity of vehicles in the far-field area of ​​the lane. Three RSUs are deployed on each side pole, each detecting the identity of vehicles in a different lane. Assuming cameras are used, then: one camera is deployed on each gantry and side pole; or, similar to radar, one camera is deployed facing a first preset direction and another facing a second preset direction.

[0031] Radar can be used to detect traffic information on the road and generate vehicle trajectories. The RSU (Roadside Unit) can communicate with each vehicle's Onboard Unit (OBU) and / or Compound Pass Card (CPC) to obtain vehicle identification (e.g., license plate number) at a specific location. Cameras can capture images of vehicles on the road at fixed points and perform video or image processing on the captured images to obtain vehicle identification for a specific location. By combining the vehicle trajectories detected by the trajectory detectors and the vehicle identification detected by the identification detectors, the vehicle's identity information for the corresponding road segment can be obtained.

[0032] Each gantry and side pole is equipped with a corresponding vehicle identification device. This device receives and processes vehicle identification information obtained by the detector within its corresponding detection range. It is understood that this vehicle identification device is not necessarily a standalone physical device; that is, it can also be considered a virtual device. For example, when radar and a radar unit (RSU) are combined to form a detector, the RSU can act as the vehicle identification device, performing the various operations related to vehicle identification as described later. Similarly, when radar and a camera are combined to form a detector, a radar-view fusion unit can act as the vehicle identification device, performing the same operations. Through this deployment method, long-distance roads can be divided into multiple segments, each managed by a corresponding identification device and detector.

[0033] All vehicle identification devices can upload the vehicle identification information they obtain to the data central processor. The data central processor can receive and forward the data uploaded by the vehicle identification devices.

[0034] In addition, the vehicle identity sharing system may also include a cloud platform. This data central processor can also upload all data to the cloud platform. The cloud platform can receive all the data uploaded by the data central processor (i.e., vehicle identity information for all vehicles across the entire road segment), thereby enabling the cloud platform to track each vehicle across the entire road segment.

[0035] In some embodiments, after the vehicle identity sharing system is established, it is necessary to perform time synchronization preprocessing and spatial synchronization preprocessing on the vehicle identity sharing system.

[0036] The time synchronization preprocessing operation refers to the following: the vehicle identification device synchronizes its time through the centralized data processor; the detectors synchronize their time through their respective corresponding vehicle identification devices. This ensures that the time of each node in the vehicle identification sharing system remains synchronized.

[0037] The operation of spatial synchronization preprocessing refers to storing the coordinates and detection direction of the radar under its jurisdiction (i.e., the corresponding radar) in the world coordinate system according to the preset world coordinate system (such as latitude and longitude). In this way, during the subsequent operation of the vehicle identity sharing system, the vehicle trajectory of each vehicle detected by the radar in the radar coordinate system can be converted into the vehicle trajectory in the world coordinate system. The radar coordinate system refers to the local coordinate system established by the radar with itself as the origin within its corresponding coverage area.

[0038] Please see Figure 2 , Figure 2 An architectural example of the vehicle identity sharing system is provided. The various nodes of this system have been described previously and will not be repeated here.

[0039] Please see Figure 3 This vehicle identity sharing method is applied to a vehicle identity determination device, and the implementation process of this vehicle identity sharing method is detailed below:

[0040] Step 301: Receive the first vehicle identity information of the target vehicle sent by the detector corresponding to the vehicle identity determination device.

[0041] In this embodiment of the application, the target vehicle can be any vehicle on the road. That is, for each vehicle on the road, its vehicle identity information can be shared through the vehicle identity sharing method proposed in this embodiment of the application.

[0042] The detectors managed by the vehicle identification device can detect the vehicle trajectory and vehicle identification identifier of the target vehicle, and generate vehicle identification information based on the detected vehicle trajectory and vehicle identification identifier, as explained above, and will not be repeated here. For ease of distinction, this vehicle identification information is referred to as the first vehicle identification information; that is, in the embodiments of this application, for a specific vehicle identification device, the first vehicle identification information obtained refers to the vehicle identification information obtained through the detection operation of the corresponding detector.

[0043] Step 302: Determine the second vehicle identity information of the target vehicle based on the location of the vehicle identity determination device on the road and the first vehicle identity information.

[0044] In this embodiment, the location of the vehicle identification device on the road affects the acquisition process of the final vehicle identification information (i.e., the second vehicle identification information) for each vehicle. Specifically, based on the characteristics of highways, vehicle identification devices are initially divided into three categories: The first category is vehicle identification devices at the road entrance. For this type of device, there are no upstream vehicle identification devices, only downstream ones. The second category is vehicle identification devices at locations other than entrances and exits on the road. For this type of device, there are both upstream and downstream vehicle identification devices. The third category is vehicle identification devices at the road exit. For this type of device, there are no downstream vehicle identification devices, only upstream ones.

[0045] The concepts of upstream and downstream given above are determined based on the driving direction specified by the road. It can be understood that upstream refers to the opposite direction of driving, while downstream refers to the direction of driving.

[0046] When a road is long, vehicle identification devices are installed at various points along its length. Therefore, a single vehicle identification device may have multiple upstream and downstream vehicle identification devices. To reduce the computational burden on each device, it can share its vehicle identification information only with the nearest downstream device. Conversely, it can receive only the vehicle identification information shared by the nearest upstream device.

[0047] This leads to the concepts of downstream vehicle identification devices and upstream vehicle identification devices. It can be understood that a downstream vehicle identification device refers to a vehicle identification device adjacent to the current vehicle identification device and located in a first preset direction, which is the driving direction prescribed by the road. An upstream vehicle identification device refers to a vehicle identification device adjacent to the current vehicle identification device and located in a second preset direction, which is the opposite direction to the driving direction prescribed by the road.

[0048] Based on the concepts given above, for the first type of vehicle identification device, since it is located at the entrance of the road, the vehicles it detects are all vehicles that have just entered the road. Therefore, it can only obtain vehicle identification information through the corresponding detector. Based on this, the first vehicle identification information obtained through the corresponding detector can be directly determined as the second vehicle identification information (that is, the final vehicle identification information of the target vehicle determined by the first type of vehicle identification device).

[0049] For vehicle identification devices of types two and three, since they are not located at the road entrance, the detected vehicles have already passed the upstream road section. Therefore, the upstream vehicle identification devices must have already generated the target vehicle's vehicle identification information. To avoid excessive data processing due to too much information, the vehicle identification device only receives the vehicle identification information shared by its upstream vehicle identification devices. For ease of distinction, this vehicle identification information can be referred to as third vehicle identification information; that is, in this embodiment, for a specific vehicle identification device, the third vehicle identification information it obtains refers to the vehicle identification information obtained by the upstream vehicle identification device through a sharing operation.

[0050] In other words, for the second and third types of vehicle identification devices, they can obtain the target vehicle's vehicle identification information (i.e., the first vehicle identification information) through the corresponding detector, and they can also obtain the target vehicle's vehicle identification information (i.e., the third vehicle identification information) through the sharing operation of the upstream vehicle identification device. In response, the second and third types of vehicle identification devices can compare the first vehicle identification information with the third vehicle identification information, and based on the comparison result, determine the second vehicle identification information (i.e., the final vehicle identification information of the target vehicle as determined by the second and third types of vehicle identification devices) from the first and third vehicle identification information.

[0051] Step 303: Share the second vehicle identity information of the target vehicle with the downstream vehicle identity determination device of the vehicle identity determination device through the data central processor.

[0052] In this embodiment, for the first and second type vehicle identification devices, they can upload the second vehicle identification information of the target vehicle they have identified to a data central processor in real time. The data central processor can then share the second vehicle identification information of the target vehicle uploaded by the vehicle identification device, that is, forward it to the corresponding downstream vehicle identification device. Thus, data transmission and sharing between upstream and downstream vehicle identification devices can be realized.

[0053] To facilitate understanding, the following will be combined with Figure 1 The above steps 301-303 will be explained. Assume... Figure 1 The vehicle identification device 1 is located at the road entrance. Therefore, the vehicle identification device 1 can only obtain the vehicle identification information A1 of the target vehicle based on the detection results of the detector 1, and the vehicle identification information A1 will be shared with the vehicle identification device 2 through the data central processor.

[0054] For vehicle identification device 2, it can not only obtain the vehicle identification information A2 of the target vehicle based on the detection results of detector 2, but also obtain the vehicle identification information A1 of the target vehicle shared by vehicle identification device 1 through the data central processor. Vehicle identification device 2 compares vehicle identification information A1 and A2, and selects one vehicle identification information based on the comparison result to share with vehicle identification device 3 through the data central processor. Similarly, the operations of vehicle identification devices 3 and 4 are similar to those of vehicle identification device 2, and will not be described in detail here.

[0055] In some embodiments, for vehicle identification devices of the second and third types, after comparing the first vehicle identification information and the third vehicle identification information, the second vehicle identification information of the target vehicle can be determined by the following operation:

[0056] If the comparison result indicates that the vehicle identification identifier of the first vehicle identification information is the same as that of the third vehicle identification information, then the first vehicle identification information is determined as the second vehicle identification information. That is, if the vehicle identification identifier of the target vehicle detected by its corresponding detector is the same as the vehicle identification identifier of the target vehicle shared by the upstream vehicle identification determination device, then it is determined that the target vehicle has indeed been identified as the same vehicle by its corresponding detector and the upstream vehicle identification determination device. In this case, the vehicle identification information of the target vehicle is essentially free of error. Furthermore, since the vehicle identification identifier of the first vehicle identification information is the same as that of the third vehicle identification information, meaning that the first and third vehicle identification information are essentially equivalent, either vehicle identification information can be selected as the second vehicle identification information.

[0057] If the comparison result indicates that the vehicle identity identifier of the first vehicle identity information is different from the vehicle identity identifier of the third vehicle identity information, then the vehicle identity identifier with higher credibility between the first and third vehicle identity information is determined as the second vehicle identity information. That is, if the vehicle identity identifier of the target vehicle detected by its corresponding detector is different from the vehicle identity identifier of the target vehicle shared by the upstream vehicle identity determination device, then there must be a mismatched vehicle identity identifier between the first and third vehicle identity information. In this case, it is necessary to judge the credibility of the two, and determine the vehicle identity identifier with higher credibility between the first and third vehicle identity information as the second vehicle identity information.

[0058] In some embodiments, in addition to the vehicle identification identifier, the vehicle identity information also includes the following types of data: identity verification level, identity verification mark count, and identity verification confidence level. The identity verification level is used to indicate the number of vehicles on the road when the corresponding vehicle identity information is generated. The identity verification mark count is used to indicate the number of times the vehicle identification identifier in the corresponding vehicle identity information is determined by the vehicle identity determination device. The identity verification confidence level is used to indicate the confidence level of the detector that generates the corresponding vehicle identity information.

[0059] The identity verification level is determined by the total number of vehicles within the detection area when the detector performs its operation. As an example, the identity verification levels can range from level 1 to 10, with level 1 being the highest and level 10 the lowest. It can be understood that the fewer vehicles in the detection area, the more accurate the detector's results are generally. Therefore, the total number of vehicles can be divided into multiple intervals, each interval corresponding to an identity verification level. For example, one vehicle per interval corresponds to level 1; 2-5 vehicles per interval corresponds to level 2; 6-15 vehicles per interval corresponds to level 3, and so on. Further details are omitted here.

[0060] The number of identity verification markers can be determined by the number of times each upstream vehicle identification device identifies the target vehicle. As an example, assuming vehicle 1's actual license plate is A, typically, under correct detection conditions, vehicle 1 will obtain vehicle identification information containing the vehicle identification identifier A each time it passes a vehicle identification device. Then, the identity verification marker count for this vehicle identification information containing the vehicle identification identifier A will increment by 1 for each vehicle identification device, indicating how many upstream vehicle identification devices have confirmed the vehicle identification identifier. Suppose vehicle 1 overtakes vehicle 2, whose actual license plate is B, and reaches the fourth vehicle identification device. Even if the detector corresponding to the fourth vehicle identification device incorrectly identifies vehicle 1's vehicle identification identifier as B, because the number of identity verification markers for vehicle identification information corresponding to vehicle identification identifier A is greater than the number of identity verification markers for vehicle identification information corresponding to vehicle identification identifier B, the final output from the four vehicle identification devices for vehicle 1 will still be license plate A.

[0061] The confidence level for vehicle identification can be determined by the confidence level of the detector that generates the corresponding vehicle identification information. Specifically, the confidence level for the first vehicle identification information is the confidence level of the detector corresponding to the current vehicle identification device, and the confidence level for the third vehicle identification information is the average confidence level of the detectors corresponding to the vehicle identification devices that output the third vehicle identification information in the upstream road segment. Specifically, the detector's confidence level can be determined as follows: Assuming the detector consists of a radar and a Roadside Unit (RSU), the RSU's signal coverage range is set to within 50m. When a vehicle is within this signal coverage range, its On-Board Unit (OBU) will be activated by receiving the signal transmitted by the RSU, thus allowing the RSU to receive the OBU's signal. When the RSU receives this signal, it can determine the confidence level for the corresponding vehicle identification information based on the radar's detection results. For example, if the radar detects that the vehicle is at 50m, the confidence level is 90%; if the radar detects that the vehicle is at 80m, the confidence level is 80%. Of course, other parameters can also be combined to determine the confidence level of identity verification, such as the Received Signal Strength Indication (RSSI) of the signal received by the RSU, the RSU's signal reception time, and the speed and position of the vehicle detected by the radar, etc., which are not limited here. Assuming that the detector consists of radar and a camera, the confidence level of identity verification can be determined by the clarity of the camera's image. Based on the above three concepts, the vehicle identification device can determine more reliable vehicle identity information through the following operations:

[0062] Based on the identity verification level, number of identity verification markers, and identity verification confidence level of the first vehicle identity information, and the identity verification level, number of identity verification markers, and identity verification confidence level of the third vehicle identity information, the vehicle identity information with higher credibility is determined from the first vehicle identity information and the third vehicle identity information. The specific method is as follows: based on the dimensions of identity verification level, identity verification markers, and identity verification confidence level, the values ​​of the first vehicle identity information and the third vehicle identity information are compared to see if they are the same. The comparison stops when a target dimension is detected, where the target dimension is the dimension in which the values ​​of the first vehicle identity information and the third vehicle identity information are different. If the target dimension is detected, the vehicle identity information corresponding to the value that meets the preset condition under the target dimension is determined as the vehicle identity information with higher credibility, where the preset condition is determined based on the target dimension.

[0063] In other words, the vehicle identification device can first compare the identity verification levels of the first vehicle's identity information and the third vehicle's identity information.

[0064] If the identity verification levels of the first and third vehicle identification information are different, then the identity verification level can be determined as the target dimension. Under this target dimension, the preset condition is that the identity verification level is higher. That is, the vehicle identification information with the higher identity verification level between the first and third vehicle identification information is identified as the second vehicle identification information. For example, assuming the identity verification level of the first vehicle identification information is level 1 and the identity verification level of the third vehicle identification information is level 2, then it can be seen that the identity verification level of the first vehicle identification information is higher, meaning that the credibility of the first vehicle identification information is higher, and therefore the first vehicle identification information can be identified as the second vehicle identification information.

[0065] If the identity verification levels of the first vehicle's identity information and the third vehicle's identity information are the same, then it is necessary to continue comparing the number of identity verification markers of the first vehicle's identity information and the third vehicle's identity information.

[0066] If the number of identity verification markers for the first vehicle's identity information and the third vehicle's identity information differs, then the number of identity verification markers can be determined as the target dimension. Under this target dimension, the presupposition condition is that the vehicle with more identity verification markers is identified as the second vehicle's identity information. For example, assuming the first vehicle's identity information has 5 identity verification markers and the third vehicle's identity information has 1, then the first vehicle's identity information has a higher number of identity verification markers, meaning its credibility is higher, and therefore it can be identified as the second vehicle's identity information.

[0067] If the number of identity verification tags for the first vehicle's identity information and the third vehicle's identity information is the same, then it is necessary to continue comparing the confidence levels of the identity verification for the first vehicle's identity information and the third vehicle's identity information.

[0068] If the confidence levels for identity verification of the first vehicle's identity information and the third vehicle's identity information are different, then the confidence level for identity verification can be determined as the target dimension. Under this target dimension, the presupposition condition is that the confidence level for identity verification is higher. That is, the vehicle identity information with the higher confidence level for identity verification between the first and third vehicle identity information is identified as the second vehicle identity information. For example, assuming the confidence level for identity verification of the first vehicle's identity information is 90% and the confidence level for identity verification of the third vehicle's identity information is 70%, then the confidence level for identity verification of the first vehicle's identity information is higher, meaning that the first vehicle identity information is more credible, and therefore, the first vehicle identity information can be identified as the second vehicle identity information.

[0069] If the confidence levels of the first vehicle identity information and the third vehicle identity information are the same, then the vehicle identity information obtained by the current vehicle identity determination device is considered more reliable. In other words, the first vehicle identity information can be identified as the second vehicle identity information.

[0070] The above process can be summarized as follows: First, compare the identity verification level and select the vehicle identity information with the higher verification level as the final vehicle identity information; if the identity verification levels are the same, compare the number of identity verification tags and select the vehicle identity information with more identity verification tags as the final vehicle identity information; if the number of identity verification tags is also the same, compare the identity verification confidence level and select the vehicle identity information with the higher identity verification confidence level as the final vehicle identity information; if the identity verification level, the number of identity verification tags, and the identity verification confidence level are all the same, then the vehicle identity information obtained by the current vehicle identity determination device itself (i.e., the first vehicle identity information) is used as the final vehicle identity information. It can be understood that the final vehicle identity information is the second vehicle identity information.

[0071] It should be noted that in real-world applications, there may be instances where the vehicle identification device assigns the same vehicle identifier to two different vehicles on the road. This is illustrated in Table 1 below.

[0072]

[0073] Table 1

[0074] In response to this situation, after determining the second identity information of the target vehicle, it will be compared with the second identity information of a previously determined preset number of vehicles (e.g., 20 vehicles). If the vehicle identity identifier of the target vehicle's second identity information is the same as the vehicle identity identifier of a previously determined vehicle's second identity information, the identity verification level, identity verification mark number, and identity verification confidence of the two second identity information will be compared. Based on the comparison results, the vehicle identity identifier will be assigned to the optimal vehicle. That is, the optimal vehicle will retain its second identity information, while the second identity information of the other vehicle will be changed.

[0075] Taking Table 1 as an example, assuming the target vehicle is vehicle 2, comparing its first and third vehicle identity information reveals that the first vehicle identity information is confirmed as the second vehicle identity information of vehicle 2 due to its higher credibility. However, after comparing it with the second identity information of the previously identified 20 vehicles, it is found that the vehicle identity identifier of vehicle 2's second identity information is the same as that of vehicle 1's second identity information. At this point, the second vehicle identity information of vehicle 1 and vehicle 2 can be compared sequentially based on three dimensions: identity verification level, number of identity verification markers, and identity verification confidence level. The comparison reveals that while the identity verification level and number of identity verification markers are the same in the second identity information of vehicle 1 and vehicle 2, the identity verification confidence level in vehicle 1's second identity information is higher than that in vehicle 2's second identity information. At this point, the vehicle identification identifier "License Plate A" is assigned to vehicle 1, meaning that vehicle 1's second vehicle identification information remains unchanged. However, for vehicle 2, its first vehicle identification information can no longer be used as its second identification information; instead, its third vehicle identification information is used to avoid conflict with the vehicle identification identifier assigned to vehicle 1. The adjusted second identification information for vehicle 1 and vehicle 2 is shown in Table 2 below:

[0076]

[0077] Table 2

[0078] In some embodiments, considering that multiple vehicles may be traveling on the road, the upstream vehicle identification device may actually share vehicle identification information of two or more vehicles. Therefore, the vehicle identification device should first identify the target vehicle among these two or more vehicles to reduce subsequent matching errors. Specifically, since vehicle identification information includes vehicle trajectories, when the upstream vehicle identification device shares vehicle identification information of two or more vehicles, the target vehicle can be identified among these two or more vehicles based on the vehicle trajectories in the vehicle identification information of the two or more vehicles and the vehicle trajectories in the first vehicle identification information. In this way, the vehicle identification information of the target vehicle shared by the upstream vehicle identification device can be subsequently identified as the third vehicle identification information of the target vehicle.

[0079] The following section defines the vehicle trajectory from the first vehicle identity information of the target vehicle as the first trajectory, and the vehicle trajectory from any vehicle identity information shared by the upstream vehicle identity determination device as the second trajectory. The process of determining whether the first trajectory and the second trajectory are generated by the same vehicle (i.e., the target vehicle) is explained and illustrated:

[0080] A1. Detect whether there is an overlapping area between the trajectory area corresponding to the first trajectory and the trajectory area corresponding to the second trajectory, and obtain the detection result.

[0081] The vehicle identification device can equate the trajectory area corresponding to the first trajectory to the road segment covered by the first trajectory detector (i.e., the detection range of the first trajectory detector), which is the trajectory detector among the detectors corresponding to the vehicle identification device. Similarly, the second trajectory detector is the trajectory detector among the detectors corresponding to the upstream vehicle identification device. The vehicle identification device can first detect whether the road segment covered by the first trajectory detector overlaps with the road segment covered by the second trajectory detector. Please refer to [link / reference]. Figure 4 Taking radar as an example of a trajectory detector, Figure 4 Examples of overlapping and non-overlapping areas covered by radar are given.

[0082] The existence of overlapping regions can be detected based on the trajectory point in the second trajectory that is closest to the first trajectory detector (usually the last trajectory point in the second trajectory, i.e., the trajectory point with the latest detection time in the second trajectory) and the trajectory point in the first trajectory that is closest to the second trajectory detector (usually the first trajectory point in the first trajectory, i.e., the trajectory point with the earliest detection time in the first trajectory). Specifically:

[0083] If the distance between the last trajectory point in the second trajectory and the first trajectory detector is less than the distance between the first trajectory point in the first trajectory and the first trajectory detector; and / or, if the distance between the first trajectory point in the first trajectory and the second trajectory detector is less than the distance between the last trajectory point in the second trajectory and the second trajectory detector, then an overlapping region is considered to exist.

[0084] A2. Based on the detection results, select the corresponding trajectory judgment method to determine whether the first trajectory and the second trajectory are generated by the same vehicle (i.e., the target vehicle).

[0085] Two trajectory determination methods are proposed to address the presence or absence of overlapping areas. The vehicle identification device can select the corresponding trajectory determination method based on the detection results of overlapping areas to determine whether the first trajectory and the second trajectory are generated by the same vehicle (i.e., the target vehicle).

[0086] In one application scenario, for cases where there is no overlapping area, that is, if the detection result indicates that there is no overlapping area, it can be determined whether the first trajectory and the second trajectory are generated by the same vehicle based on the position of the first trajectory in the trajectory area corresponding to the first trajectory and the position of the second trajectory in the trajectory area corresponding to the second trajectory.

[0087] As an example, assuming the second trajectory detector detects multiple vehicles traveling side-by-side, it can determine the relative position of each vehicle corresponding to a second trajectory within these vehicles. After these vehicles enter the road segment covered by the first trajectory detector, the first trajectory detector will also detect multiple vehicles traveling side-by-side and can determine the relative position of each vehicle corresponding to a first trajectory within these vehicles. By default, in areas not covered by either of these trajectory detectors, vehicles do not change lanes during travel (i.e., their relative positions do not change). In this case, the second and first trajectories with the same relative position can be directly identified as trajectories generated by the same vehicle.

[0088] As an example, suppose the second trajectory detector detects the second trajectories of three vehicles traveling side by side, corresponding to the left lane, middle lane, and right lane respectively on the road; and suppose the first trajectory detector subsequently detects the first trajectories of the three vehicles traveling side by side, corresponding to the left lane, middle lane, and right lane respectively on the road. Then it is confirmed that the second trajectory in the left lane and the first trajectory are generated by the same vehicle, the second trajectory in the middle lane and the first trajectory are generated by the same vehicle, and the second trajectory in the right lane and the first trajectory are generated by the same vehicle. This is how the determination of whether the second trajectory and the first trajectory are generated by the same vehicle is achieved.

[0089] In another application scenario, for cases with overlapping areas, that is, if the detection results indicate the existence of overlapping areas, the distance between the first and second trajectories within the overlapping area can be used to determine whether the first and second trajectories are generated by the same vehicle (i.e., the target vehicle). It can be assumed that when the distance between the trajectories is sufficiently small, the first and second trajectories are relatively close, and can be preliminarily confirmed as being generated by the same vehicle (i.e., the target vehicle).

[0090] Specifically, the distance between these trajectories is calculated as follows:

[0091] B1. Calculate the number of probe data frames corresponding to the overlapping area.

[0092] Since the time of the first and second trajectory detectors is synchronized, meaning they will perform detection operations at the same detection time, the number of detection data frames can be regarded as the number of times the first and second trajectory detectors perform detection operations in the overlapping area. The detection operation performed by the two at the same detection time is considered as one detection operation; that is, at the same detection time, the detection operation is counted only once, and the result of the count is the number of detection data frames.

[0093] Specifically, the detection data frame can be calculated as follows: obtain the detection time of the first trajectory point in the overlapping area of ​​the first trajectory, denoted as the first detection time t.a ; Obtain the detection time of the last trajectory point in the overlapping region of the first trajectory, and denote it as the second detection time t'. a ; Obtain the detection time of the first trajectory point in the overlapping region of the second trajectory, denoted as the third detection time t. b ; Obtain the detection time of the last trajectory point of the second trajectory in the overlapping region, denoted as the fourth detection time t'. b Based on the first detection time, the second detection time, the third detection time, the fourth detection time, and the preset detection interval τ, the number of detection data frames p can be calculated. Specifically, the formula for calculating the number of detection data frames p is as follows:

[0094]

[0095] Please see Figure 5 , Figure 5 Examples of trajectory points and their detection times in the overlapping region of the first and second trajectories are given. Solid squares represent the trajectory points of the first trajectory; solid circles represent the trajectory points of the second trajectory; and so on. Figure 5 We can deduce that the first detection time is t2, the second detection time is t5, the third detection time is t1, and the fourth detection time is t4. Substituting these values ​​into the formula for calculating the number of detection data frames, we can obtain t. ab Let t1, t a’b’ If it is t5, then based on Figure 3 Number of obtained detection data frames

[0096] B2. Based on the number of detection data frames, the coordinates of the trajectory points of the first trajectory that are not null within the overlapping area, and the coordinates of the trajectory points of the second trajectory that are not null within the overlapping area, the distance between the trajectories is calculated.

[0097] Assume a i Let b be the coordinates of the trajectory point in the overlapping region at the i-th detection time (i.e., the i-th frame of detection data). i Let a be the coordinates of the trajectory point of the second trajectory at the i-th detection time in the overlapping region. i and b i Let be the coordinates of the corresponding trajectory points (trajectory points under the same detection time). Where 1 ≤ i ≤ p, and i is an integer. When a i or b i When the value is null, it indicates that there is no comparison point at this time, and the coordinates of the trajectory points corresponding to this detection time need to be discarded when calculating the distance. Based on this, it can be recorded that the coordinates of the corresponding trajectory points are not null values ​​under q detection times. Specifically, the formula for calculating the distance D between trajectories is as follows:

[0098] Still with Figure 5 For example, it can be seen that in the first detection time, there are only the coordinates of the trajectory points of the second trajectory, and in the fifth detection time, there are only the coordinates of the trajectory points of the first trajectory. These coordinates will be discarded in the calculation. Therefore, in practice, only the average distance between the corresponding trajectory points in the second, third and fourth detection times is considered as the final distance between trajectories, and the value of q is 3.

[0099] It is understandable that the coordinates of a trajectory point can include not only the coordinates of the trajectory point in the world coordinate system, but also multi-dimensional information such as the vehicle's speed at that trajectory point; this is not limited here.

[0100] B3. If the distance between the trajectories is less than the preset distance threshold between trajectories, then the first trajectory and the second trajectory are determined to be trajectories generated by the same vehicle.

[0101] As described earlier, when the distance between trajectories is small, the first and second trajectories can be considered to be generated by the same vehicle. To address this, the vehicle identification device can pre-set a distance threshold between trajectories and compare the calculated distance between trajectories with this threshold. If the comparison finds that the distance between trajectories is less than the threshold, it can be determined that the first and second trajectories were generated by the same vehicle. By comparing the first trajectory with each of the second trajectories, it is possible to determine which second trajectory was generated by the target vehicle.

[0102] In some embodiments, after determining that the first trajectory and a certain second trajectory are trajectories generated by the same vehicle (target vehicle), the first trajectory and the second trajectory are spliced ​​together.

[0103] If there is no overlapping area, and it is determined that the first trajectory and the second trajectory are generated by the same vehicle, then the first trajectory point of the first trajectory can be directly connected to the last trajectory point of the second trajectory to achieve the splicing of the first trajectory and the second trajectory.

[0104] When there is an overlapping area, if it is determined that the first trajectory and the second trajectory are generated by the same vehicle, then the first trajectory and the second trajectory in the overlapping area need to be merged to obtain a new trajectory in the overlapping area. Then, the endpoints of the new trajectory are connected to the first trajectory and the second trajectory outside the overlapping area respectively. Specifically, the first trajectory point of the new trajectory is connected to the first trajectory point of the first trajectory outside the overlapping area, and the last trajectory point of the new trajectory is connected to the last trajectory point of the second trajectory outside the overlapping area. This ensures that the trajectory of the target vehicle will not be interrupted.

[0105] In some embodiments, the trajectory fusion operation performed within the overlapping region may specifically include:

[0106] C1. Calculate the confidence of the first trajectory detector and the second trajectory detector in each group of trajectory points to be fused in the overlapping region.

[0107] For ease of explanation, the trajectory points of the first and second trajectories within the overlapping region at the same detection time can be considered as a group of trajectory points. For each group of trajectory points, the confidence levels of the first and second trajectory detectors for that group can be calculated separately. The higher the confidence level, the higher the trust in the corresponding trajectory detector. This confidence level can be understood as a concept of weight.

[0108] It can be understood that the sum of the confidence level of the first trajectory detector for a set of trajectory points and the confidence level of the second trajectory detector for the same set of trajectory points is 1. That is, assuming the confidence level of the first trajectory detector for the set of trajectory points at the i-th detection time is k... i Then the confidence level of the second trajectory detector for this set of trajectory points is 1-k. i .

[0109] Specifically, assuming that the first trajectory detector and the second trajectory detector have the same distance resolution and angular resolution, the confidence level k of the first trajectory detector for the trajectory point group at the i-th detection time can be calculated as follows: i Based on the coordinates of two trajectory points in the trajectory point group, calculate the first distance x between the trajectory point group and the first trajectory detector, and the second distance y between the trajectory point group and the second trajectory detector. Then, based on the first distance x, the second distance y, the preset detector distance resolution m, and the preset detector angular resolution n, calculate the confidence level k using the following formula. i :

[0110]

[0111] As an example only, the distance between the center point of two trajectory points in a trajectory point group and the first trajectory detector can be directly used as the first distance between the trajectory point group and the first trajectory detector, and the distance between the center point and the second trajectory detector can be used as the second distance between the trajectory point group and the second trajectory detector, so as to calculate the confidence of the first and second trajectory detectors in the trajectory point group.

[0112] C2. Based on the confidence level and the coordinates of the two trajectory points in each trajectory point group, calculate the coordinates of the new trajectory point corresponding to each trajectory point group.

[0113] C3. Generate a new trajectory based on the coordinates of the new trajectory points corresponding to each trajectory point group.

[0114] Let the new trajectory be denoted as c, then each trajectory point c in the new trajectory c... iThe coordinates can be obtained using the following coordinate fusion calculation formula:

[0115]

[0116] That is, when the second trajectory is in the overlapping region at the i-th detection time, the coordinates b of the trajectory point... i When the value is empty, the coordinates c of the corresponding new trajectory point i That is, the coordinates a of the trajectory point at the i-th detection time in the overlapping region of the first trajectory. i Conversely, the same applies only when coordinate a i and coordinates b i Only when all values ​​are non-nullable can the coordinates c of the corresponding new trajectory point be calculated based on the corresponding confidence level (weight). i .

[0117] In some embodiments, trajectory correction can be performed through the following process to further eliminate errors: After the trajectory fusion of the first trajectory and the second trajectory in the overlapping area is completed, the distance between the new trajectory point on the fused new trajectory and other trajectory points detected by the trajectory detector with lower accuracy at the same detection time in the overlapping area can be calculated, wherein the trajectory detector with lower accuracy refers to the trajectory detector that is farther away from the new trajectory point among the first trajectory detector and the second trajectory detector. If calculations reveal that the less precise trajectory detector, within the overlapping area and under the same detection time, detects other trajectory points (i.e., neither the first nor the second trajectory) that are closer to the new trajectory point (which can be denoted as target trajectory points), then it's possible that a single trajectory detector made a mistake. The trajectory points detected by the less precise trajectory detector can be corrected. Specifically: if the less precise trajectory detector is the first trajectory detector, then the trajectory points detected in the first trajectory under the same detection time are changed to target trajectory points (i.e., the trajectory points in the first trajectory under the same detection time are replaced with target trajectory points); if the less precise trajectory detector is the second trajectory detector, then the trajectory points detected in the second trajectory under the same detection time are changed to target trajectory points (i.e., the trajectory points in the second trajectory under the same detection time are replaced with target trajectory points). After trajectory correction, trajectory fusion operations are performed again in the overlapping area based on the corrected trajectories.

[0118] Please see Figure 6 , Figure 6 An example of trajectory correction is given. Figure 6In the above steps, trajectory a1 detected by the second trajectory detector and trajectory a2 detected by the first trajectory detector are considered to be trajectories generated by the same vehicle. Therefore, the vehicle identification device can fuse trajectories a1 and a2 within the overlapping area. Assume that at the i-th detection time in the overlapping area, the trajectory point of trajectory a1 is a1. i The trajectory point of trajectory a2 is a2 i Through trajectory fusion, the corresponding new trajectory point c was obtained. i And through trajectory point a1 i and trajectory point a2 i Based on their positions, the first trajectory detector is farther away from them, meaning that for this set of trajectory points, the first trajectory detector is a less accurate one. Through detection, it was found that at the i-th detection time, the first trajectory detector detected trajectory point b in trajectory b. i Distance from the new trajectory point c i If it's closer, then it's assumed that the first trajectory detector made a mistake, and the trajectory point b... i If it belongs to trajectory a2, then trajectory point b... i Replace trajectory point a2 i That is, at the i-th detection time, the trajectory point of trajectory a2 is b. i The trajectory point of trajectory b is a2. i Then, based on the trajectory point a1 in trajectory a1 at the i-th detection time... i Trajectory point b in trajectory a2 i The fusion yields the corresponding new trajectory point c. i '.

[0119] In some embodiments, if the number of targets detected by the first trajectory detector and the second trajectory detector is different, when sharing vehicle identity information, if the second trajectory detector detects more targets, the extra detected targets will have their trajectories disappear; if the first trajectory detector detects more targets, the extra detected targets will have their trajectories generated.

[0120] In some embodiments, the cloud platform can also visualize the received vehicle identity information, and the visualization effect is as follows:

[0121] Trajectory tracking is achieved based on trajectory detectors. According to the data detected by the trajectory detectors at different detection times, the trajectory lines of each vehicle on the entire road segment are generated. Furthermore, the length of the trajectory residual in the visualization interface at certain time periods can be adjusted by setting time parameters, thereby forming a traffic information collection interface based on vehicle movement across the entire road segment.

[0122] As an example, different colors can be used to distinguish the tracks in the stitched parts. For example, the track detected by a single track detector (i.e., the track that is not in the overlapping area) can be displayed in black; the track in the overlapping area can be displayed in dark gray (or in the case of no overlapping area, two tracks belonging to the same vehicle can be directly connected by light gray tracks).

[0123] As an example only, under each road segment, the preset position of its trajectory (such as the front or above) may carry the vehicle identity information finally confirmed by that road segment (that is, the second vehicle identity information of the vehicle corresponding to the trajectory finally confirmed by the vehicle identity determination device of that road segment). The accuracy of the vehicle identity information can be distinguished by color, and the identity confirmation level, identity confirmation mark number and identity confirmation confidence level of the vehicle identity information can also be displayed as optional outputs in the traffic information collection interface.

[0124] As can be seen from the above, through the embodiments of this application, the downstream vehicle identification device can not only obtain the vehicle identification information of the target vehicle through its own corresponding detector, but also receive the vehicle identification information of the target vehicle shared by the upstream vehicle identification device. In this way, even if the detector corresponding to the downstream vehicle identification device experiences data delay or detects too many vehicles, it can still track vehicles traveling on the road through the vehicle identification information shared by the upstream vehicle identification device.

[0125] Corresponding to the vehicle identity sharing method provided above, the vehicle identity determination device 700 in the vehicle identity sharing system includes:

[0126] The receiving module 701 is used to receive the first vehicle identity information of the target vehicle sent by the detector corresponding to the vehicle identity determination device.

[0127] The determination module 702 is used to determine the second vehicle identity information of the target vehicle based on the location of the vehicle identity determination device on the road and the first vehicle identity information.

[0128] The sharing module 703 is used to share the second vehicle identity information of the target vehicle with the downstream vehicle identity determination device of the vehicle identity determination device through the data central processor. The downstream vehicle identity determination device is a vehicle identity determination device that is adjacent to the vehicle identity determination device and located in a first preset direction of the vehicle identity determination device. The first preset direction is the driving direction specified by the road.

[0129] Optionally, the determining module 702 includes:

[0130] The first determining unit is used to determine the first vehicle identity information as the second vehicle identity information if the vehicle identity determining device is located at the entrance of the road.

[0131] The information acquisition unit is used to acquire, through the data central processor, the third vehicle identity information of the target vehicle shared by the upstream vehicle identity determination device of the vehicle identity determination device if the vehicle identity determination device is not located at the entrance of the road. The upstream vehicle identity determination device is a vehicle identity determination device that is adjacent to the vehicle identity determination device and located in the second preset direction of the vehicle identity determination device. The second preset direction is the opposite direction of the driving direction specified by the road.

[0132] The information comparison unit is used to compare the first vehicle identity information with the third vehicle identity information.

[0133] The second determining unit is used to determine the second vehicle identity information from the first vehicle identity information and the third vehicle identity information based on the comparison result.

[0134] Optionally, the information acquisition unit mentioned above includes:

[0135] The target vehicle determination subunit is used to determine the target vehicle among the two or more vehicles based on the vehicle trajectory in the vehicle identity information of the two or more vehicles and the vehicle trajectory in the first vehicle identity information if the upstream vehicle identity determination device shares the vehicle identity information of two or more vehicles.

[0136] The third vehicle identity information determination subunit is used to determine the vehicle identity information of the target vehicle shared by the upstream vehicle identity determination device as the third vehicle identity information of the target vehicle.

[0137] Optionally, both the first vehicle identity information and the third vehicle identity information mentioned above include a vehicle identification identifier; the second determining unit includes:

[0138] The first determining subunit is configured to determine the first vehicle identity information as the second vehicle identity information if the comparison result indicates that the vehicle identity identifier of the first vehicle identity information is the same as the vehicle identity identifier of the third vehicle identity information.

[0139] The second determining subunit is used to determine the more reliable vehicle identity information between the first vehicle identity information and the third vehicle identity information as the second vehicle identity information if the comparison result indicates that the vehicle identity identifier of the first vehicle identity information is different from the vehicle identity identifier of the third vehicle identity information.

[0140] Optionally, the aforementioned first vehicle identity information and the aforementioned third vehicle identity information further include an identity verification level, an identity verification marker count, and an identity verification confidence level. The identity verification level indicates the number of vehicles on the road when the corresponding vehicle identity information is generated. The identity verification marker count indicates the number of times the vehicle identity identifier in the corresponding vehicle identity information is determined by the vehicle identity determination device. The identity verification confidence level indicates the confidence level of the detector that generates the corresponding vehicle identity information. The aforementioned second determination subunit includes:

[0141] The third determining subunit is used to determine the vehicle identity information with higher credibility among the first vehicle identity information and the third vehicle identity information based on the identity verification level, identity verification mark number and identity verification confidence level of the first vehicle identity information, and the identity verification level, identity verification mark number and identity verification confidence level of the third vehicle identity information.

[0142] The fourth determining subunit is used to determine the vehicle identity information with higher credibility as the second vehicle identity information.

[0143] Optionally, the aforementioned third determining subunit includes:

[0144] The information comparison subunit is used to compare whether the values ​​of the first vehicle identity information and the third vehicle identity information are the same in the corresponding dimensions based on the dimensions of the identity verification level, the dimensions of the number of identity verification markers, and the dimensions of the identity verification confidence level, and to stop the comparison when a target dimension is detected, wherein the target dimension is the dimension in which the values ​​of the first vehicle identity information and the third vehicle identity information are different.

[0145] The fifth determining subunit is used to determine the vehicle identity information corresponding to the value that meets the preset conditions under the above target dimension as the vehicle identity information with higher credibility if the above target dimension is detected, wherein the above preset conditions are determined based on the above target dimension.

[0146] Optionally, the vehicle identification device 700 further includes:

[0147] The upload module is used to upload the second vehicle identity information of the target vehicle to a preset cloud platform through the aforementioned data central processor, so that the cloud platform can track the target vehicle across the entire road segment.

[0148] Corresponding to the vehicle identity sharing method provided above, this application also provides a vehicle identity determination device. Please refer to... Figure 8 The vehicle identification device 8 in this embodiment includes: a memory 801, and one or more processors 802. Figure 8Only one is shown in the diagram, along with a computer program stored in memory 801 and executable on the processor. Memory 801 stores software programs and units. The processor 802 executes various functional applications and diagnostics by running the software programs and units stored in memory 801 to obtain resources corresponding to the aforementioned preset events. Specifically, when the processor 802 executes the aforementioned computer program, it implements the steps in various embodiments of the aforementioned vehicle identity sharing method, for example... Figure 3 The numbers 301 to 303 shown are not described in detail here.

[0149] It should be understood that, in the embodiments of this application, the processor 802 may be a central processing unit (CPU), but it may also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor.

[0150] Memory 801 may include read-only memory and random access memory, and provides instructions and data to processor 802. Some or all of memory 801 may also include non-volatile random access memory. For example, memory 801 may also store device class information.

[0151] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the above device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0152] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of external device software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0153] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For instance, the division of modules or units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or units through some interfaces, and may be electrical, mechanical, or other forms.

[0154] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0155] If the integrated units described above are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing associated hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer-readable storage device, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc. It should be noted that the contents of the aforementioned computer-readable storage media may be appropriately added to or subtracted from the contents according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable storage media may not include electrical carrier signals and telecommunication signals.

[0156] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A vehicle identity sharing method, characterized by, Applied to vehicle identification devices, including: Receive the first vehicle identity information of the target vehicle sent by the detector corresponding to the vehicle identity determination device; Based on the location of the vehicle identification device on the road and the first vehicle identification information, the second vehicle identification information of the target vehicle is determined; The second vehicle identity information of the target vehicle is shared with the downstream vehicle identity determination device of the vehicle identity determination device through the data central processor. The downstream vehicle identity determination device is a vehicle identity determination device that is adjacent to the vehicle identity determination device and located in a first preset direction of the vehicle identity determination device. The first preset direction is the driving direction specified by the road. The step of determining the second vehicle identity information of the target vehicle based on the location of the vehicle identity determination device on the road and the first vehicle identity information includes: Based on the dimensions of identity verification level, identity verification mark number, and identity verification confidence, the values ​​of the first vehicle identity information and the third vehicle identity information are compared to see if they are the same in the corresponding dimensions. The comparison stops when a target dimension is detected. The target dimension is the dimension in which the values ​​of the first vehicle identity information and the third vehicle identity information are different. If the target dimension is detected, the vehicle identity information corresponding to the value that meets the preset conditions under the target dimension is determined as the vehicle identity information with higher credibility; wherein, the preset conditions are determined based on the target dimension, the third vehicle identity information is the vehicle identity information of the target vehicle shared by the upstream vehicle identity determination device of the vehicle identity determination device, the first vehicle identity information and the third vehicle identity information both include the identity confirmation level, the identity confirmation mark count and the identity confirmation confidence level, the identity confirmation level is used to indicate the number of vehicles on the road when the corresponding vehicle identity information is generated, the identity confirmation mark count is used to indicate the number of times the vehicle identity identifier in the corresponding vehicle identity information is determined by the vehicle identity determination device, and the identity confirmation confidence level is used to indicate the confidence level of the detector that generates the corresponding vehicle identity information, and the downstream and upstream are determined based on the driving direction specified by the road; the vehicle identity information with higher credibility is determined as the second vehicle identity information.

2. The vehicle identity sharing method of claim 1, wherein, The step of determining the second vehicle identity information of the target vehicle based on the location of the vehicle identity determination device on the road and the first vehicle identity information includes: If the vehicle identification device is located at the entrance of the road, the first vehicle identification information is identified as the second vehicle identification information; If the vehicle identification device is not located at the entrance of the road, the third vehicle identification information of the target vehicle shared by the upstream vehicle identification device is obtained through the data central processor. The upstream vehicle identification device is a vehicle identification device that is adjacent to the vehicle identification device and located in the second preset direction of the vehicle identification device. The second preset direction is the opposite direction of the driving direction specified by the road. The identity information of the first vehicle is compared with the identity information of the third vehicle; Based on the comparison results, the second vehicle identity information is determined from the first vehicle identity information and the third vehicle identity information.

3. The vehicle identity sharing method of claim 2, wherein, Both the first vehicle identity information and the third vehicle identity information include vehicle trajectory; the step of obtaining the third vehicle identity information of the target vehicle shared by the upstream vehicle identity determination device of the vehicle identity determination device through the data central processor includes: If the upstream vehicle identity determination device shares the vehicle identity information of two or more vehicles, then based on the vehicle trajectory in the vehicle identity information of the two or more vehicles and the vehicle trajectory in the first vehicle identity information, the target vehicle is determined among the two or more vehicles. The vehicle identity information of the target vehicle shared by the upstream vehicle identity determination device is determined as the third vehicle identity information of the target vehicle.

4. The vehicle identity sharing method of claim 2, wherein, Both the first vehicle identity information and the third vehicle identity information include a vehicle identity identifier; the step of determining the second vehicle identity information from the first vehicle identity information and the third vehicle identity information based on the comparison result includes: If the comparison result indicates that the vehicle identity identifier of the first vehicle identity information is the same as the vehicle identity identifier of the third vehicle identity information, then the first vehicle identity information is determined to be the second vehicle identity information. If the comparison result indicates that the vehicle identity identifier of the first vehicle identity information is different from the vehicle identity identifier of the third vehicle identity information, then the vehicle identity information with higher credibility among the first vehicle identity information and the third vehicle identity information is determined as the second vehicle identity information.

5. The vehicle identity sharing method as described in claim 1, characterized in that, The vehicle identity sharing method also includes: The data processing unit uploads the second vehicle identity information of the target vehicle to a preset cloud platform, enabling the cloud platform to track the target vehicle across the entire road segment.

6. A vehicle identity sharing system, characterized in that, The vehicle identity sharing system includes at least two vehicle identity determination devices, a detector corresponding to each vehicle identity determination device, and at least one data centralization processor; wherein, each vehicle identity determination device includes: The receiving module is used to receive the first vehicle identity information of the target vehicle sent by the detector corresponding to the vehicle identity determination device. The determination module is used to determine the second vehicle identity information of the target vehicle based on the location of the vehicle identity determination device on the road and the first vehicle identity information; A sharing module is used to share the second vehicle identity information of the target vehicle with a downstream vehicle identity determination device through a data central processor, wherein the downstream vehicle identity determination device is a vehicle identity determination device that is adjacent to the vehicle identity determination device and located in a first preset direction of the vehicle identity determination device, and the first preset direction is the driving direction specified by the road. The determining module is specifically used for: Based on the dimensions of identity verification level, identity verification mark number, and identity verification confidence, the values ​​of the first vehicle identity information and the third vehicle identity information are compared to see if they are the same in the corresponding dimensions. The comparison stops when a target dimension is detected. The target dimension is the dimension in which the values ​​of the first vehicle identity information and the third vehicle identity information are different. If the target dimension is detected, the vehicle identity information corresponding to the value that meets the preset conditions under the target dimension is determined as the vehicle identity information with higher credibility; wherein, the preset conditions are determined based on the target dimension, the third vehicle identity information is the vehicle identity information of the target vehicle shared by the upstream vehicle identity determination device of the vehicle identity determination device, the first vehicle identity information and the third vehicle identity information both include identity confirmation level, identity confirmation mark number and identity confirmation confidence level, the identity confirmation level is used to indicate the number of vehicles on the road when the corresponding vehicle identity information is generated, the identity confirmation mark number is used to indicate the number of times the vehicle identity identifier in the corresponding vehicle identity information is determined by the vehicle identity determination device, and the identity confirmation confidence level is used to indicate the confidence level of the detector that generates the corresponding vehicle identity information, and the downstream and upstream are determined based on the driving direction specified by the road; The vehicle identity information with higher credibility is identified as the second vehicle identity information.

7. A vehicle identification device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 5.

8. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 5.

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