Vehicle tracking method, apparatus, terminal device, and computer program product

Abstract

This application relates to the field of automotive technology and provides a vehicle tracking method, device, terminal equipment, and computer program product. The method includes: when a target vehicle is detected entering a ramp entrance, acquiring first vehicle information collected by a first radar and a first camera device located at the ramp entrance; after the target vehicle enters the ramp's perception blind zone, obtaining simulated driving data of a simulated vehicle corresponding to the target vehicle within the ramp's perception blind zone based on the first vehicle information; acquiring second vehicle information of each vehicle collected by a second radar and a second camera device located at the ramp exit; determining the target vehicle information from the second vehicle information; and adjusting the simulated driving data based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area. This application not only reduces costs but also avoids the influence of height differences within the ramp area on radar signals, improving perception accuracy and thus enhancing vehicle tracking capabilities.

Description

Technical Field

[0001] This application belongs to the field of automotive technology, and in particular relates to a vehicle tracking method, device, terminal equipment, and computer program product. Background Technology

[0002] In practical applications, ramps, also known as approach roads, typically refer to short sections of road that provide access to and from main roads (such as highways, elevated roads, bridges, and tunnels) and adjacent auxiliary roads, or overpasses / rapid ramps / approach roads connecting to other main roads, as well as collector-distributor roads. Ramps are a major traffic infrastructure component of road interchanges, providing vehicles with access to and from main roads and alleviating traffic congestion on those main roads.

[0003] Currently, to achieve full-range vehicle tracking from the divergence direction to the merging direction of a ramp, existing technologies typically achieve full-range coverage of the entire ramp area using millimeter-wave radar or lidar. This enables full-range perception from the divergence direction to the merging direction, thereby achieving full-range vehicle tracking. However, achieving radar coverage of the entire ramp area is costly, and the height difference within the ramp area affects the propagation and reflection of radar signals, reducing perception accuracy and thus decreasing the vehicle tracking capability. Summary of the Invention

[0004] This application provides a vehicle tracking method, device, terminal equipment, and computer program product to address the problems in the prior art where achieving radar coverage of the entire ramp area is costly, and the height difference within the ramp area affects the propagation and reflection of radar signals, reducing perception accuracy and thus reducing the ability to track vehicles.

[0005] In a first aspect, embodiments of this application provide a vehicle tracking method, including:

[0006] When a target vehicle is detected entering the ramp entrance, the first vehicle information collected by the first radar and the first camera device set at the ramp entrance is acquired;

[0007] After the target vehicle enters the ramp perception blind zone, the target vehicle is simulated based on the first vehicle information to obtain the simulated driving data of the simulated vehicle corresponding to the target vehicle within the ramp perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where there are no radar and camera devices.

[0008] Acquire second vehicle information of each vehicle from the second radar and second camera devices installed at the exit of the ramp;

[0009] Determine the target vehicle information that matches the first vehicle information from each of the second vehicle information;

[0010] The simulated driving data is adjusted based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind spot, and the ramp exit.

[0011] Optionally, the first vehicle information includes a first vehicle type, a first license plate number, a first vehicle speed, a first driving direction, and the first lane in which the target vehicle is located; the step of simulating the target vehicle based on the first vehicle information to obtain simulated driving data of the simulated vehicle corresponding to the target vehicle within the ramp perception blind spot includes:

[0012] Based on the first vehicle model and the first license plate number, the target vehicle is simulated to obtain the simulated vehicle;

[0013] Based on the first vehicle speed, the first driving direction, and the first lane, the trajectory of the target vehicle in the blind spot of the ramp is predicted to obtain the simulated driving data.

[0014] Optionally, the step of predicting the trajectory of the target vehicle in the ramp's blind spot based on the first vehicle speed, the first driving direction, and the first lane to obtain the simulated driving data includes:

[0015] The first driving direction and the first lane are input into the trained path prediction model for processing to obtain the simulated driving path of the simulated vehicle.

[0016] The simulated driving data is determined based on the first vehicle speed and the simulated driving path.

[0017] Optionally, the first vehicle information includes a first driving direction and the first lane where the target vehicle is located; the step of simulating the target vehicle based on the first vehicle information to obtain simulated driving data of the simulated vehicle corresponding to the target vehicle within the ramp perception blind spot includes:

[0018] Obtain historical driving data of each historical vehicle that passed through the exit of the ramp within a historical time period; each historical vehicle refers to a vehicle whose historical driving direction at the ramp entrance is the same as the first driving direction and whose historical lane at the ramp entrance is the same as the first lane.

[0019] The simulated driving data is determined based on the historical driving data.

[0020] Optionally, the target vehicle information includes vehicle position, second speed, second direction of travel, and the second lane in which the target vehicle is located; the simulated driving data includes the simulated vehicle position at the end of the simulation; adjusting the simulated driving data based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area includes:

[0021] The degree of difference between the vehicle position and the simulated vehicle position is calculated;

[0022] If the difference is greater than or equal to a set threshold, the simulated driving data is adjusted based on the second vehicle speed, the second driving direction, and the second lane to obtain the target driving data of the target vehicle in the ramp perception blind zone.

[0023] The tracking trajectory is generated based on the first vehicle information, the target vehicle information, and the target driving data;

[0024] After calculating the difference between the vehicle position and the simulated vehicle position, the method further includes:

[0025] If the difference is less than the set threshold, the tracking trajectory is generated based on the first vehicle information, the target vehicle information, and the simulated driving data.

[0026] Optionally, the simulated driving data further includes simulated vehicle speed and simulated driving path; the first vehicle information includes a first vehicle speed, a first driving direction, and the first lane in which the target vehicle is located; adjusting the simulated driving data based on the second vehicle speed, the second driving direction, and the second lane to obtain the target driving data of the target vehicle in the ramp's blind spot includes:

[0027] The simulated driving path is adjusted based on the second driving direction, the second lane, the first driving direction, and the first lane to obtain the target driving path;

[0028] The simulated vehicle speed is adjusted based on the second vehicle speed to obtain the target vehicle speed;

[0029] The target driving data is obtained based on the target vehicle speed and the target driving path.

[0030] Optionally, the first radar and the second radar include millimeter-wave radar or lidar; the first camera device and the second camera device include a bayonet camera.

[0031] Secondly, embodiments of this application provide a vehicle tracking device, comprising:

[0032] The first acquisition unit is used to acquire first vehicle information collected by the first radar and the first camera device set at the ramp entrance when the target vehicle is detected to enter the ramp entrance;

[0033] The first simulation unit is used to simulate the target vehicle based on the first vehicle information after the target vehicle enters the ramp perception blind zone, and obtain the simulation driving data of the simulated vehicle corresponding to the target vehicle in the ramp perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where there are no radar and camera devices.

[0034] The second acquisition unit is used to acquire second vehicle information of each vehicle collected by the second radar and the second camera device set at the exit of the ramp.

[0035] The first determining unit is configured to determine target vehicle information that matches the first vehicle information from each of the second vehicle information;

[0036] The first adjustment unit is used to adjust the simulated driving data based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind spot and the ramp exit.

[0037] Thirdly, embodiments of this application provide a terminal device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the vehicle tracking method as described in any one of the first aspects above.

[0038] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the vehicle tracking method as described in any one of the first aspects above.

[0039] Fifthly, embodiments of this application provide a computer program product that, when run on a terminal device, enables the terminal device to execute the vehicle tracking method described in any one of the first aspects.

[0040] The beneficial effects of the embodiments in this application compared with the prior art are:

[0041] This application provides a vehicle tracking method that, upon detecting a target vehicle entering a ramp entrance, acquires first vehicle information collected by a first radar and a first camera device located at the ramp entrance; after the target vehicle enters the ramp's perception blind zone, it simulates the target vehicle based on the first vehicle information to obtain simulated driving data of the simulated vehicle within the ramp's perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where no radar or camera device exists; second vehicle information is acquired by a second radar and a second camera device located at the ramp exit for each vehicle; target vehicle information matching the first vehicle information is determined from the second vehicle information; the simulated driving data is adjusted based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind zone, and the ramp exit. Compared with existing technologies, this application only requires radar and camera devices to be installed at the ramp entrance and ramp exit, eliminating the need for full radar coverage of the entire ramp area. This not only reduces costs but also avoids the influence of height differences within the ramp area on radar signals, improving perception accuracy. Meanwhile, by simulating vehicle movement in the ramp's blind spot and adjusting the simulated data based on target vehicle information at the ramp exit, accurate vehicle tracking in the ramp area can be achieved, improving tracking capabilities. This ensures effective perception and tracking of vehicles throughout the entire ramp area and enhances the overall understanding of ramp traffic conditions, contributing to more intelligent traffic management and control. Attached Figure Description

[0042] 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.

[0043] Figure 1 This is a schematic diagram of a ramp area provided in one embodiment of this application;

[0044] Figure 2 This is a flowchart illustrating the implementation of a vehicle tracking method according to an embodiment of this application;

[0045] Figure 3 This is a flowchart illustrating the implementation of a vehicle tracking method according to another embodiment of this application;

[0046] Figure 4 This is a flowchart illustrating the implementation of a vehicle tracking method according to another embodiment of this application;

[0047] Figure 5This is a schematic diagram of the structure of a vehicle tracking device provided in one embodiment of this application;

[0048] Figure 6 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Detailed Implementation

[0049] 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.

[0050] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0051] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0052] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if detected [the described condition or event]" may be interpreted, depending on the context, as meaning "once determined," "in response to determination," "once detected [the described condition or event]," or "in response to detection [the described condition or event]."

[0053] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0054] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0055] In practical applications, ramps, also known as approach roads, typically refer to short sections of road that provide access to and from main roads (such as highways, elevated roads, bridges, and tunnels) and adjacent auxiliary roads, or overpasses / rapid ramps / approach roads connecting to other main roads, as well as collector-distributor roads. Ramps are a major traffic infrastructure component of road interchanges, providing vehicles with access to and from main roads and alleviating traffic congestion on those main roads.

[0056] Currently, to achieve full-range vehicle tracking from the divergence direction to the merging direction of a ramp, existing technologies typically achieve full-range coverage of the entire ramp area using millimeter-wave radar or lidar. This enables full-range perception from the divergence direction to the merging direction, thereby achieving full-range vehicle tracking. However, achieving radar coverage of the entire ramp area is costly, and the height difference within the ramp area affects the propagation and reflection of radar signals, reducing perception accuracy and thus decreasing the vehicle tracking capability.

[0057] Please see Figure 1 , Figure 1 This is a schematic diagram of a ramp area provided in one embodiment of this application. Figure 1 As shown, the ramp area Z consists of areas A, B, and C. Area A is the ramp entrance, area B is the ramp perception blind spot, and area C is the ramp exit.

[0058] Therefore, this application proposes a vehicle tracking method that can reduce costs and improve vehicle tracking capabilities. The vehicle tracking method will be described in detail below with specific embodiments.

[0059] Please see Figure 2 , Figure 2 This is a flowchart illustrating the implementation of a vehicle tracking method according to an embodiment of this application. In this embodiment, the vehicle tracking method is executed by a terminal device. The terminal device includes, but is not limited to, laptops, desktop computers, and other similar devices.

[0060] like Figure 2As shown, a vehicle tracking method provided in one embodiment of this application may include steps S101 to S105, which are detailed below:

[0061] In S101, when a target vehicle is detected to enter the ramp entrance, the first vehicle information collected by the first radar and the first camera device set at the ramp entrance is obtained.

[0062] In this embodiment of the application, a first radar installed at the entrance of the ramp senses any vehicle within its detection range in real time, and a first camera installed at the entrance of the ramp captures any vehicle within its shooting range in real time.

[0063] It should be noted that the detection range and the shooting range mentioned above can be exactly the same, or they can overlap.

[0064] In some possible embodiments, in order to improve the accuracy of perception of any vehicle and accurately obtain the vehicle information, the first radar can be a lidar or millimeter-wave radar, and the first camera device can be a bayonet camera.

[0065] In this embodiment of the application, when the terminal device detects that the target vehicle has entered the detection range of the ramp entrance (including the detection range and the shooting range mentioned above), it can determine that the target vehicle is at the ramp entrance. Therefore, the terminal device can obtain the first vehicle information of the target vehicle in real time through the first radar and the first camera device that are wirelessly connected to it.

[0066] It should be noted that the first vehicle information includes, but is not limited to: the first vehicle model, the first license plate number, the first vehicle speed, the first direction of travel, the first location, and the first lane in which the target vehicle is located. The first vehicle model includes the vehicle's length, width, and height.

[0067] In one implementation of this application, the terminal device can obtain the first vehicle model, first vehicle speed, first driving direction, and first position in real time through a first radar wirelessly connected to it.

[0068] In another implementation of this application, the terminal device can obtain the first license plate number and the first lane in real time through a first camera device wirelessly connected to it.

[0069] In this embodiment of the application, after obtaining the first vehicle information of the target vehicle, the terminal device can store the first vehicle information.

[0070] In S102, after the target vehicle enters the ramp perception blind zone, the target vehicle is simulated based on the first vehicle information to obtain the simulated driving data of the simulated vehicle corresponding to the target vehicle in the ramp perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where there are no radar and camera devices.

[0071] In this embodiment, after the terminal device detects that the target vehicle has entered the ramp perception blind zone, since there are no radar and camera devices in the ramp perception blind zone, the terminal device cannot obtain the actual vehicle information of the target vehicle. Therefore, in order to achieve the tracking capability after the target vehicle enters the ramp perception blind zone, the terminal device can simulate the simulated vehicle corresponding to the target vehicle in the simulation software based on the first vehicle information, and control the simulated vehicle to simulate the driving process of the target vehicle in the ramp perception blind zone, thereby obtaining the simulated driving data of the simulated vehicle corresponding to the target vehicle in the ramp perception blind zone.

[0072] It should be noted that the simulated driving data includes, but is not limited to: the simulated vehicle speed and the simulated driving path.

[0073] In one embodiment of this application, when the first vehicle information includes a first driving direction and the first lane where the target vehicle is located, in order to improve the working efficiency of the terminal device, the terminal device can obtain simulated driving data according to the following steps, detailed below:

[0074] Obtain historical driving data of each historical vehicle that passed through the exit of the ramp within a historical time period; each historical vehicle refers to a vehicle whose historical driving direction at the ramp entrance is the same as the first driving direction and whose historical lane at the ramp entrance is the same as the first lane.

[0075] The simulated driving data is determined based on the historical driving data.

[0076] It should be noted that the historical time period can be determined according to actual needs, and there are no restrictions here.

[0077] Historical driving data includes, but is not limited to: the third direction of travel, the third lane, and the third speed at the ramp exit.

[0078] In this embodiment, the terminal device can count the number of occurrences of different third driving directions, different third lanes, and different third speeds within a historical time period. Then, the terminal device can directly determine the most frequently occurring third driving direction as the simulated driving direction of the simulated vehicle, the most frequently occurring third lane as the simulated lane of the simulated vehicle, and the most frequently occurring third speed as the simulated speed.

[0079] Afterwards, the terminal device can generate a simulated driving path for the simulated lane based on the simulated driving direction and the simulated lane.

[0080] In another embodiment of this application, when the first vehicle information includes a first vehicle model, a first license plate number, a first vehicle speed, a first driving direction, and the first lane where the target vehicle is located, in order to improve the simulation accuracy and achieve effective tracking of the target vehicle in the ramp perception blind spot, the terminal device can specifically achieve this by means of... Figure 3 The simulation driving data obtained through steps S201 to S202 are detailed below:

[0081] In S201, the target vehicle is simulated based on the first vehicle model and the first license plate number to obtain the simulated vehicle.

[0082] In S202, the trajectory of the target vehicle in the blind spot of the ramp is predicted based on the first vehicle speed, the first driving direction, and the first lane to obtain the simulated driving data.

[0083] In this embodiment, the terminal device can simulate a vehicle corresponding to the target vehicle based on the first vehicle model and the first license plate number in the first vehicle information.

[0084] Then, the terminal device can input the first vehicle speed, the first driving direction, and the first lane into the trained prediction model for prediction, that is, to predict the trajectory of the target vehicle in the blind spot of the ramp perception, thereby obtaining simulated driving data.

[0085] It should be noted that the prediction model can be obtained by training a pre-built neural network model based on a preset sample set. Each sample data point in the preset sample set includes sample information (sample vehicle speed, sample driving direction, and sample lane) and the corresponding sample driving data. When training the pre-built neural network model, the sample information from each sample data point is used as the input to the neural network model, and the corresponding sample driving data is used as the output. Through training, the neural network model can learn the correspondence between all possible sample information and sample driving data, and the trained neural network model becomes the prediction model.

[0086] In one embodiment of this application, the terminal device can predict simulated driving data according to the following steps, detailed below:

[0087] The first driving direction and the first lane are input into the trained path prediction model for processing to obtain the simulated driving path of the simulated vehicle.

[0088] The simulated driving data is determined based on the first vehicle speed and the simulated driving path.

[0089] In this embodiment, in order to improve work efficiency, the terminal device can directly determine the first vehicle speed as the simulated vehicle speed in the simulated driving data.

[0090] In this embodiment, in order to improve the accuracy of determining the simulated driving path, the terminal device can input the first driving direction and the first lane into the trained path prediction model for processing to obtain the simulated driving path of the simulated vehicle.

[0091] It should be noted that the path prediction model can be obtained by training a pre-built deep learning model based on a preset sample set. Each sample data point in the preset sample set includes sample information (sample driving direction and sample lane) and the corresponding sample driving data. When training the pre-built deep learning model, the sample information from each sample data point is used as the input to the deep learning model, and the corresponding sample driving data is used as the output. Through training, the deep learning model can learn the correspondence between all possible sample information and sample driving data, and the trained neural network model becomes the path prediction model.

[0092] In S103, the second vehicle information of each vehicle is acquired by the second radar and the second camera device set at the exit of the ramp.

[0093] In this embodiment of the application, a second radar installed at the exit of the ramp senses any vehicle within its detection range in real time, and a second camera installed at the exit of the ramp captures any vehicle within its shooting range in real time.

[0094] It should be noted that the detection range and the shooting range mentioned above can be exactly the same, or they can overlap.

[0095] In some possible embodiments, in order to improve the accuracy of perception of any vehicle and accurately obtain vehicle information, the second radar can be a lidar or millimeter-wave radar, and the second camera device can be a bayonet camera.

[0096] In this embodiment of the application, when the terminal device detects that any vehicle has entered the detection range of the ramp exit (including the detection range and the shooting range mentioned above), it can determine that the vehicle is at the ramp exit. Therefore, the terminal device can obtain the second vehicle information of the vehicle in real time through the second radar and the second camera device that are wirelessly connected to it.

[0097] Based on this, the terminal device can obtain second vehicle information for each vehicle passing through the ramp exit.

[0098] It should be noted that the secondary vehicle information for each vehicle includes, but is not limited to: vehicle model, license plate number, speed, direction of travel, position, and lane. The vehicle model information includes the vehicle's length, width, and height.

[0099] In one implementation of this application, the terminal device can obtain the vehicle type, speed, direction of travel, and position of each vehicle in real time through a second radar wirelessly connected to it.

[0100] In another implementation of this application, the terminal device can obtain the license plate number of each vehicle and the lane where each vehicle is located in real time through a second camera device that is wirelessly connected to it.

[0101] In S104, target vehicle information that matches the first vehicle information is determined from each of the second vehicle information.

[0102] In this embodiment of the application, since the second vehicle information of each vehicle includes the license plate number of each vehicle, and the first vehicle information includes the first license plate number of the target vehicle, the terminal device can compare the first license plate number with the license plate numbers of each of the above vehicles in sequence to determine the vehicle with the same license plate number as the first license plate number, and determine the second vehicle information with the same license plate number as the first license plate number as the target vehicle information, that is, the vehicle information of the target vehicle at the ramp exit.

[0103] In S105, the simulated driving data is adjusted based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind spot, and the ramp exit.

[0104] In this embodiment of the application, in order to improve the tracking capability of vehicles in the ramp area and achieve effective perception and tracking of vehicles in the ramp area, the terminal device can adjust the simulated driving data of the target vehicle in the ramp perception blind spot based on the target vehicle information to obtain more accurate simulated driving data.

[0105] Subsequently, the terminal device can determine the target vehicle's tracking trajectory in the ramp area by combining the first vehicle information at the ramp entrance, the adjusted simulated driving data, and the target vehicle information. The ramp area consists of the ramp entrance, the ramp perception blind spot, and the ramp exit.

[0106] In one embodiment of this application, in order to improve the accuracy of adjusting simulated driving data and obtain a more accurate tracking trajectory, the terminal device can specifically achieve the following: Figure 4 The tracking trajectory is obtained through steps S301 to S303, as detailed below:

[0107] In S301, the degree of difference between the vehicle position and the simulated vehicle position is calculated.

[0108] It should be noted that the simulation end time specifically refers to the time when the target vehicle arrives at the ramp exit.

[0109] In this embodiment, since the simulated driving data includes the simulated vehicle position at the end of the simulation, and the target vehicle information includes the vehicle position, second speed, second driving direction, and the second lane where the target vehicle is located, the terminal device can calculate the distance between the target vehicle's position at the ramp exit and the simulated vehicle's position at the ramp exit, i.e., the difference, based on the simulated vehicle position and the vehicle position.

[0110] The terminal device can then compare this difference with a set threshold. The set threshold can be determined based on actual needs and is not restricted here.

[0111] In one embodiment of this application, when the terminal device detects a difference greater than or equal to a set threshold, it may execute steps S302 to S303.

[0112] In another embodiment of this application, when the terminal device detects a difference less than a set threshold, it can perform the following: Figure 4 Step S304 is shown.

[0113] In S302, if the difference is greater than or equal to a set threshold, the simulated driving data is adjusted based on the second vehicle speed, the second driving direction, and the second lane to obtain the target driving data of the target vehicle in the ramp perception blind zone.

[0114] In this embodiment, when the terminal device detects a difference greater than or equal to a set threshold, it indicates that the accuracy of the terminal device's simulation of the target vehicle's driving process within the ramp sensing area is low, and the simulated driving data needs to be adjusted. Therefore, in order to make the simulated driving data closer to the target vehicle information at the ramp exit, the terminal device can adjust the simulated driving data based on the second vehicle speed, the second driving direction, and the second lane to obtain the target driving data of the target vehicle in the ramp sensing blind zone.

[0115] In one embodiment of this application, when the simulated driving data also includes simulated vehicle speed and simulated driving path, and the first vehicle information includes a first vehicle speed, a first driving direction, and the first lane where the target vehicle is located, in order to further improve the adjustment accuracy, the terminal device can adjust the simulated driving data according to the following steps, detailed below:

[0116] The simulated driving path is adjusted based on the second driving direction, the second lane, the first driving direction, and the first lane to obtain the target driving path;

[0117] The simulated vehicle speed is adjusted based on the second vehicle speed to obtain the target vehicle speed;

[0118] The target driving data is obtained based on the target vehicle speed and the target driving path.

[0119] In this embodiment, the terminal device can determine the first driving direction and the first lane as the driving direction and lane of the target vehicle at the starting point of the ramp sensing area. The terminal device can also determine the second driving direction and the second lane as the driving direction and lane of the target vehicle at the ending point of the ramp sensing area. Then, the terminal device can adjust the starting point and ending point of the simulated driving path according to the driving direction and lane at the starting point and the driving direction and lane at the ending point, thereby obtaining the target driving path.

[0120] To make the simulated driving data closer to the target vehicle information at the ramp exit, the terminal device can directly adjust the simulated vehicle speed based on the second vehicle speed, that is, adjust the simulated vehicle speed to the second vehicle speed, thereby obtaining the target vehicle speed.

[0121] In this embodiment, the terminal device can directly determine the target vehicle speed and target driving path as the target driving data of the target vehicle.

[0122] In S303, the tracking trajectory is generated based on the first vehicle information, the target vehicle information, and the target driving data.

[0123] In this embodiment, the terminal device can directly determine the first vehicle information, target driving data and target vehicle information at the ramp entrance as the tracking trajectory of the target vehicle in the ramp area.

[0124] In S304, if the difference is less than the set threshold, the tracking trajectory is generated based on the first vehicle information, the target vehicle information, and the simulated driving data.

[0125] In this embodiment, when the terminal device detects that the difference is less than a set threshold, it indicates that the terminal device has a high accuracy rate in simulating the driving process of the target vehicle in the ramp perception area. There is no need to adjust the simulated driving data. Therefore, the terminal device can directly determine the first vehicle information, the target vehicle information, and the simulated driving data as the tracking trajectory.

[0126] As can be seen from the above, the vehicle tracking method provided in this application involves acquiring first vehicle information collected by a first radar and a first camera device located at the ramp entrance when a target vehicle is detected entering the ramp entrance; simulating the target vehicle based on the first vehicle information after the target vehicle enters the ramp perception blind zone to obtain simulated driving data of the simulated vehicle corresponding to the target vehicle within the ramp perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where no radar or camera device exists; acquiring second vehicle information collected by a second radar and a second camera device located at the ramp exit; determining the target vehicle information matching the first vehicle information from the second vehicle information; and adjusting the simulated driving data based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind zone, and the ramp exit. Compared with the prior art, this application only requires radar and camera devices to be set up at the ramp entrance and ramp exit, eliminating the need for full radar coverage of the entire ramp area. This not only reduces costs but also avoids the influence of height differences within the ramp area on radar signals, improving perception accuracy. Meanwhile, by simulating vehicle movement in the ramp's blind spot and adjusting the simulated data based on target vehicle information at the ramp exit, accurate vehicle tracking in the ramp area can be achieved, improving tracking capabilities. This ensures effective perception and tracking of vehicles throughout the entire ramp area and enhances the overall understanding of ramp traffic conditions, contributing to more intelligent traffic management and control.

[0127] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0128] Corresponding to the vehicle tracking method described in the above embodiments, Figure 5 A schematic diagram of a vehicle tracking device according to an embodiment of this application is shown. For ease of explanation, only the parts relevant to the embodiment of this application are shown. (Refer to...) Figure 5 The vehicle tracking device 400 includes: a first acquisition unit 41, a first simulation unit 42, a second acquisition unit 43, a first determination unit 44, and a first adjustment unit 45. Wherein:

[0129] The first acquisition unit 41 is used to acquire first vehicle information collected by the first radar and the first camera device set at the ramp entrance when a target vehicle is detected to enter the ramp entrance.

[0130] The first simulation unit 42 is used to simulate the target vehicle based on the first vehicle information after the target vehicle enters the ramp perception blind zone, and obtain the simulation driving data of the simulated vehicle corresponding to the target vehicle in the ramp perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where there are no radar and camera devices.

[0131] The second acquisition unit 43 is used to acquire the second vehicle information of each vehicle collected by the second radar and the second camera device set at the exit of the ramp.

[0132] The first determining unit 44 is used to determine the target vehicle information that matches the first vehicle information from each of the second vehicle information.

[0133] The first adjustment unit 45 is used to adjust the simulated driving data based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind spot and the ramp exit.

[0134] In one embodiment of this application, the first vehicle information includes a first vehicle type, a first license plate number, a first vehicle speed, a first driving direction, and the first lane in which the target vehicle is located; the first simulation unit 42 specifically includes a second simulation unit and a prediction unit. Wherein:

[0135] The second simulation unit is used to simulate the target vehicle based on the first vehicle model and the first license plate number to obtain the simulated vehicle.

[0136] The prediction unit is used to predict the trajectory of the target vehicle in the blind spot of the ramp based on the first vehicle speed, the first driving direction and the first lane, so as to obtain the simulated driving data.

[0137] In one embodiment of this application, the prediction unit specifically includes: a processing unit and a second determining unit. Wherein:

[0138] The processing unit is used to input the first driving direction and the first lane into the trained path prediction model for processing, so as to obtain the simulated driving path of the simulated vehicle.

[0139] The second determining unit is used to determine the simulated driving data based on the first vehicle speed and the simulated driving path.

[0140] In one embodiment of this application, the first vehicle information includes a first driving direction and the first lane in which the target vehicle is located; the first simulation unit 42 specifically includes: a third acquisition unit and a third determination unit. Wherein:

[0141] The third acquisition unit is used to acquire the historical driving data of each historical vehicle that passed through the exit of the ramp within a historical time period; each historical vehicle refers to a vehicle whose historical driving direction at the ramp entrance is the same as the first driving direction and whose historical lane at the ramp entrance is the same as the first lane.

[0142] The third determining unit is used to determine the simulated driving data based on the historical driving data.

[0143] In one embodiment of this application, the target vehicle information includes vehicle position, second vehicle speed, second driving direction, and the second lane in which the target vehicle is located; the first adjustment unit 45 specifically includes: a calculation unit, a second adjustment unit, and a generation unit; correspondingly, the vehicle tracking device 400 further includes: an output unit. Wherein:

[0144] The calculation unit is used to calculate the degree of difference between the vehicle position and the simulated vehicle position.

[0145] The second adjustment unit is used to adjust the simulated driving data based on the second vehicle speed, the second driving direction, and the second lane if the difference is greater than or equal to a set threshold, so as to obtain the target driving data of the target vehicle in the ramp perception blind zone.

[0146] The generation unit is used to generate the tracking trajectory based on the first vehicle information, the target vehicle information, and the target driving data.

[0147] The output unit is used to generate the tracking trajectory based on the first vehicle information, the target vehicle information, and the simulated driving data if the difference is less than the set threshold.

[0148] In one embodiment of this application, the simulated driving data further includes simulated vehicle speed and simulated driving path; the first vehicle information includes a first vehicle speed, a first driving direction, and the first lane where the target vehicle is located; the second adjustment unit specifically includes: a third adjustment unit, a fourth adjustment unit, and a fourth determination unit. Wherein:

[0149] The third adjustment unit is used to adjust the simulated driving path based on the second driving direction, the second lane, the first driving direction, and the first lane to obtain the target driving path.

[0150] The fourth adjustment unit is used to adjust the simulated vehicle speed based on the second vehicle speed to obtain the target vehicle speed.

[0151] The fourth determining unit is used to obtain the target driving data based on the target vehicle speed and the target driving path.

[0152] In one embodiment of this application, the first radar and the second radar include millimeter-wave radar or lidar; the first camera device and the second camera device include a bayonet camera.

[0153] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0154] 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 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.

[0155] Figure 6 This is a schematic diagram of the structure of a terminal device provided in an embodiment of this application. Figure 6 As shown, the terminal device 5 in this embodiment includes: at least one processor 50 ( Figure 6 (Only one is shown in the diagram), memory 51, and computer program 52 stored in said memory 51 and executable on said at least one processor 50, which, when executed, implements the steps in any of the above vehicle tracking method embodiments.

[0156] The terminal device may include, but is not limited to, a processor 50 and a memory 51. Those skilled in the art will understand that... Figure 6 This is merely an example of terminal device 5 and does not constitute a limitation on terminal device 5. It may include more or fewer components than shown in the figure, or combine certain components, or different components, such as input / output devices, network access devices, etc.

[0157] The processor 50 may be a Central Processing Unit (CPU), or it may 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. A general-purpose processor may be a microprocessor or any conventional processor.

[0158] In some embodiments, the memory 51 may be an internal storage unit of the terminal device 5, such as the RAM of the terminal device 5. In other embodiments, the memory 51 may be an external storage device of the terminal device 5, such as a plug-in hard drive, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the terminal device 5. Furthermore, the memory 51 may include both internal and external storage units of the terminal device 5. The memory 51 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 51 can also be used to temporarily store data that has been output or will be output.

[0159] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0160] This application provides a computer program product that, when run on a terminal device, enables the terminal device to implement the steps described in the various method embodiments above.

[0161] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it 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 of this application can be implemented by a computer program instructing related 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 medium can include at least: any entity or device capable of carrying computer program code to a terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0162] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0163] The above-described 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 tracking method, characterized in that, include: When a target vehicle is detected entering the ramp entrance, the first vehicle information collected by the first radar and the first camera device set at the ramp entrance is acquired; After the target vehicle enters the ramp perception blind zone, the target vehicle is simulated based on the first vehicle information to obtain the simulated driving data of the simulated vehicle corresponding to the target vehicle within the ramp perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where there are no radar and camera devices. Acquire second vehicle information of each vehicle from the second radar and second camera devices installed at the exit of the ramp; Determine the target vehicle information that matches the first vehicle information from each of the second vehicle information; The simulated driving data is adjusted based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind spot, and the ramp exit.

2. The vehicle tracking method as described in claim 1, characterized in that, The first vehicle information includes a first vehicle type, a first license plate number, a first vehicle speed, a first driving direction, and the first lane in which the target vehicle is located; the step of simulating the target vehicle based on the first vehicle information to obtain simulated driving data of the simulated vehicle corresponding to the target vehicle within the perception blind spot of the ramp includes: Based on the first vehicle model and the first license plate number, the target vehicle is simulated to obtain the simulated vehicle; Based on the first vehicle speed, the first driving direction, and the first lane, the trajectory of the target vehicle in the blind spot of the ramp is predicted to obtain the simulated driving data.

3. The vehicle tracking method as described in claim 2, characterized in that, The simulation driving data is obtained by predicting the trajectory of the target vehicle in the blind spot of the ramp based on the first vehicle speed, the first driving direction, and the first lane, including: The first driving direction and the first lane are input into the trained path prediction model for processing to obtain the simulated driving path of the simulated vehicle. The simulated driving data is determined based on the first vehicle speed and the simulated driving path.

4. The vehicle tracking method as described in claim 1, characterized in that, The first vehicle information includes a first driving direction and the first lane in which the target vehicle is located; the step of simulating the target vehicle based on the first vehicle information to obtain simulated driving data of the simulated vehicle corresponding to the target vehicle within the perception blind spot of the ramp includes: Obtain historical driving data of each historical vehicle that passed through the exit of the ramp within a historical time period; each historical vehicle refers to a vehicle whose historical driving direction at the ramp entrance is the same as the first driving direction and whose historical lane at the ramp entrance is the same as the first lane. The simulated driving data is determined based on the historical driving data.

5. The vehicle tracking method as described in claim 1, characterized in that, The target vehicle information includes vehicle position, second speed, second driving direction, and the second lane in which the target vehicle is located; the simulated driving data includes the simulated vehicle position at the end of the simulation; adjusting the simulated driving data based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area includes: The degree of difference between the vehicle position and the simulated vehicle position is calculated; If the difference is greater than or equal to a set threshold, the simulated driving data is adjusted based on the second vehicle speed, the second driving direction, and the second lane to obtain the target driving data of the target vehicle in the ramp perception blind zone. The tracking trajectory is generated based on the first vehicle information, the target vehicle information, and the target driving data; After calculating the difference between the vehicle position and the simulated vehicle position, the method further includes: If the difference is less than the set threshold, the tracking trajectory is generated based on the first vehicle information, the target vehicle information, and the simulated driving data.

6. The vehicle tracking method as described in claim 5, characterized in that, The simulated driving data also includes simulated vehicle speed and simulated driving path; the first vehicle information includes a first vehicle speed, a first driving direction, and the first lane where the target vehicle is located; adjusting the simulated driving data based on the second vehicle speed, the second driving direction, and the second lane to obtain the target driving data of the target vehicle in the ramp's blind spot includes: The simulated driving path is adjusted based on the second driving direction, the second lane, the first driving direction, and the first lane to obtain the target driving path; The simulated vehicle speed is adjusted based on the second vehicle speed to obtain the target vehicle speed; The target driving data is obtained based on the target vehicle speed and the target driving path.

7. The vehicle tracking method according to any one of claims 1-6, characterized in that, The first radar and the second radar include millimeter-wave radar or lidar; the first camera device and the second camera device include a bayonet camera.

8. A vehicle tracking device, characterized in that, include: The first acquisition unit is used to acquire first vehicle information collected by the first radar and the first camera device set at the ramp entrance when the target vehicle is detected to enter the ramp entrance; The first simulation unit is used to simulate the target vehicle based on the first vehicle information after the target vehicle enters the ramp perception blind zone, and obtain the simulation driving data of the simulated vehicle corresponding to the target vehicle in the ramp perception blind zone; the ramp perception blind zone refers to the area from the ramp entrance to the ramp exit where there are no radar and camera devices. The second acquisition unit is used to acquire second vehicle information of each vehicle collected by the second radar and the second camera device set at the exit of the ramp. The first determining unit is configured to determine target vehicle information that matches the first vehicle information from each of the second vehicle information; The first adjustment unit is used to adjust the simulated driving data based on the target vehicle information to obtain the tracking trajectory of the target vehicle in the ramp area; the ramp area includes the ramp entrance, the ramp perception blind spot and the ramp exit.

9. A terminal 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 vehicle tracking method as described in any one of claims 1 to 7.

10. A computer program product, characterized in that, It includes a computer program that, when run, implements the vehicle tracking method as described in any one of claims 1 to 7.

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