CN114460598A - Target identification method, device, equipment and storage medium - Google Patents
Target identification method, device, equipment and storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a target identification method, a device, equipment and a storage medium, wherein the method comprises the following steps: in the running process of the vehicle, acquiring a plurality of preset sensor targets and millimeter wave radar static targets, and performing association judgment on each millimeter wave radar static target and each preset sensor target; and then determining a related target successfully related to at least one preset sensor target in each millimeter wave radar static target according to the related judgment result, and tracking and managing the related target in the life cycle of the target. According to the technical scheme of the embodiment of the invention, the millimeter wave radar static target is subjected to correlation judgment by utilizing each preset sensor target, so that the stability of the millimeter wave radar in identifying the static target is enhanced, the target identification performance of the millimeter wave radar on the preset sensor under a specific scene is supplemented, and the robustness of the automatic driving system is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of automatic driving, in particular to a target identification method, a target identification device, target identification equipment and a storage medium.
Background
With the high-speed development of the automatic driving technology, the driving environment is automatically sensed by the automatic driving sensing technology, and vehicle driving assistance is carried out according to an environment sensing result, so that the method has important significance in reducing the traffic jam degree and improving the traffic efficiency.
At present, in the existing automatic driving perception technology, an intelligent vision sensor and a laser radar sensor are mainly used for target perception, and correspondingly, the intelligent vision sensor and the laser radar sensor are mainly adopted for fusion of an automatic driving perception fusion scheme for target perception. However, in some specific scenarios, for example, the vision of the vehicle is blocked or a target which is stationary for a long time is identified, the existing automatic driving perception technology cannot realize accurate perception of the target, and the robustness of the automatic driving system is reduced.
Disclosure of Invention
The embodiment of the invention provides a target identification method, a device, equipment and a storage medium, which can enhance the stability of a millimeter wave radar in identifying a static target, realize the target identification performance supplement of the millimeter wave radar to a preset sensor in a specific scene and improve the robustness of an automatic driving system.
In a first aspect, an embodiment of the present invention provides a target identification method, including:
acquiring at least one preset sensor target and a millimeter wave radar static target in the running process of a vehicle;
performing association judgment on each millimeter wave radar static target and each preset sensor target;
and according to the association judgment result, determining an associated target successfully associated with at least one preset sensor target in the millimeter wave radar static targets, and tracking and managing the associated target in the target life cycle.
In a second aspect, an embodiment of the present invention further provides a target identification apparatus, including:
the target acquisition module is used for acquiring at least one preset sensor target and a millimeter wave radar static target in the running process of the vehicle;
the correlation judgment module is used for performing correlation judgment on each millimeter wave radar static target and each preset sensor target;
and the associated target determining module is used for determining an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target according to the association judgment result, and tracking and managing the associated target in the life cycle of the target.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
storage means for storing one or more computer programs;
the object recognition method provided by any embodiment of the present invention is implemented when the one or more computer programs are executed by the one or more processors, so that the one or more processors execute the computer programs.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the storage medium, and when the computer program is executed by a processor, the computer program implements the object identification method provided in any embodiment of the present invention.
According to the technical scheme provided by the embodiment of the invention, a plurality of preset sensor targets and millimeter wave radar static targets are obtained in the running process of the vehicle, and correlation judgment is carried out on each millimeter wave radar static target and each preset sensor target; further determining a correlation target successfully correlated with at least one preset sensor target in each millimeter wave radar static target according to the correlation judgment result, and tracking and managing the correlation target in the target life cycle; the millimeter wave radar static target is subjected to correlation judgment by utilizing each preset sensor target, so that the stability of the millimeter wave radar in recognizing the static target is enhanced, the target recognition performance of the millimeter wave radar on the preset sensor under a specific scene is supplemented, and the robustness of the automatic driving system is improved.
Drawings
FIG. 1A is a flow chart of a method of object recognition in an embodiment of the invention;
FIG. 1B is a flowchart illustrating a target recognition method according to an embodiment of the invention;
FIG. 2A is a flow chart of a method of object recognition in another embodiment of the present invention;
FIG. 2B is a flowchart illustrating a target recognition method according to another embodiment of the invention;
FIG. 3A is a flow chart of a method of object recognition in another embodiment of the present invention;
FIG. 3B is a flowchart illustrating a target recognition method according to another embodiment of the invention;
FIG. 4 is a schematic structural diagram of an object recognition device according to another embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device in another embodiment of the invention.
Detailed Description
Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present invention are shown in the drawings, it should be understood that the present invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for a more complete and thorough understanding of the present invention. It should be understood that the drawings and the embodiments of the present invention are illustrative only and are not intended to limit the scope of the present invention.
Fig. 1A is a flowchart of a target identification method according to an embodiment of the present invention, where the embodiment of the present invention is applicable to association determination of millimeter wave radar static targets by using preset sensor targets, so as to obtain accurately identified associated targets from the millimeter wave radar static targets; the method may be performed by an object recognition apparatus, which may be composed of hardware and/or software, and may be generally integrated in an electronic device, and typically, may be integrated in a car machine device. As shown in fig. 1A, the method specifically includes the following steps:
and S110, acquiring at least one preset sensor target and a millimeter wave radar static target in the running process of the vehicle.
In this embodiment, the preset sensor target may include a single lidar target, a single vision target, and at least one of a lidar and a vision fusion target. The single laser radar target refers to a target which is only detected and identified by a laser radar; a mono-vision target, which refers to a target that is detected and recognized only by a vision sensor; correspondingly, the laser radar and the vision fusion target refer to targets detected and recognized by the laser radar and the vision sensor together. The target may be a vehicle, a pedestrian, a road facility, or the like, and the type of the target is not particularly limited in this embodiment.
The laser radar mainly comprises a transmitter, a receiver, a measurement control unit and a power supply; when the target detection is carried out, a laser beam is firstly emitted to a detected target, and then parameters such as time for reflected or scattered light to reach a transmitter, signal intensity, frequency change and the like are measured so as to determine the distance, the movement speed and the direction of the detected target, thereby realizing the environmental perception in the automatic driving process. The vision sensor is mainly used for detecting roads and detecting and identifying vehicles, signal lamps, traffic signs and the like in the field of automatic driving; the vision sensor may include a monocular camera, a binocular camera, a panoramic camera, an infrared camera, and the like.
The millimeter wave radar static target is a static target which is detected and identified by the millimeter wave radar; millimeter wave radar, i.e. radar equipment with millimeter wave (wavelength of 1-10 mm) as detection wave. It should be noted that, the identification of the millimeter wave radar to the static target is indiscriminate, so that, for the garbage bin, the flagpole, the well lid, the iron fence and the like on the roadside, as long as within the radar detection range, the static target can be successfully identified. In addition, for the attributes of such static objects, such as the transverse and longitudinal distances, there are problems that the identification is not accurate or the jump is easy. Therefore, if the millimeter wave radar static target is directly used for automatic driving control, target error identification is easy to cause, so that the stability of an automatic driving system is reduced, and the automatic driving safety is influenced.
In this embodiment, during the automatic driving of the vehicle, environmental sensing may be performed by using preset sensors (e.g., a laser sensor and a vision sensor) and the millimeter wave radar together to obtain a plurality of preset sensor targets and a millimeter wave radar static target.
And S120, performing correlation judgment on each millimeter wave radar static target and each preset sensor target.
In this embodiment, for the above-mentioned problem of the static target of millimeter wave radar, the target recognition result of the preset sensor may be adopted to perform association judgment on the static target of millimeter wave radar so as to obtain a stable and effective static target of millimeter wave radar by screening in the static target of millimeter wave radar. And then regard the static target of millimeter wave radar who selects as the replenishment of presetting the sensor target, can be under some specific scenes, for example, vision is sheltered from or heavy fog weather etc. when presetting the sensor and appearing the target perception unusual, carry out autopilot control based on the static target of millimeter wave radar who selects, can promote autopilot system's robustness.
The correlation judgment between the millimeter wave radar static targets and the preset sensor targets can be carried out by calculating the similarity between the millimeter wave radar static targets and the preset sensor targets; specifically, if it is detected that the similarity between a certain millimeter wave radar static target and a preset sensor target is greater than a preset similarity threshold, it may be determined that the detected millimeter wave radar static target is successfully associated with the preset sensor target; and if the similarity is smaller than or equal to the preset similarity threshold, determining that the detected millimeter wave radar static target is in failed association with the preset sensor target. The Euclidean distance between each millimeter wave radar static target and each preset sensor target can be respectively calculated to serve as the similarity; in this embodiment, the method of association determination is not particularly limited.
In an optional implementation manner of this embodiment, the determining the association between each millimeter wave radar static target and each preset sensor target may include: respectively calculating the Mahalanobis distance between each millimeter wave radar static target and each preset sensor target, and determining each similar preset sensor target with the minimum Mahalanobis distance between each millimeter wave radar static target and each preset sensor target;
correspondingly, if the minimum mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is smaller than the preset distance threshold value, determining that the detected millimeter wave radar static target is successfully associated with the corresponding similar preset sensor target; and if the fact that the minimum Mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is larger than or equal to the preset distance threshold value is detected, determining that the detected millimeter wave radar static target is in failed association with the corresponding similar preset sensor target.
In this embodiment, mahalanobis distances between the millimeter wave radar static targets and the preset sensor targets may be calculated respectively to serve as similarities between the millimeter wave radar static targets and the preset sensor targets. The Mahalanobis distance (Mahalanobis distance) represents a covariance distance of two data, and can effectively calculate a similarity between two unknown sample sets. Different from the Euclidean distance, the Mahalanobis distance can comprehensively consider the connection among various characteristics and is independent of the measurement scale; through the Mahalanobis distance, the position and the speed of the target can be comprehensively considered, and the accurate evaluation of the similarity between the millimeter wave radar static target and the preset sensor target is realized.
Specifically, mahalanobis distances between each millimeter wave radar static target and each preset sensor target may be calculated respectively, and then the preset sensor target having the smallest mahalanobis distance with the millimeter wave radar static target may be used as the similar preset sensor target; therefore, similar preset sensor targets corresponding to the millimeter wave radar static targets can be obtained. The smaller the mahalanobis distance is, the higher the similarity between the corresponding millimeter wave radar static target and the preset sensor target is.
Further, comparing the minimum mahalanobis distance between each millimeter wave radar static target and the corresponding similar preset sensor target with a preset distance threshold, and if the minimum mahalanobis distance is smaller than the preset distance threshold, determining that the millimeter wave radar static target corresponding to the minimum mahalanobis distance is successfully associated with the similar preset sensor target; correspondingly, if the minimum mahalanobis distance is greater than or equal to the preset distance threshold, it may be determined that the millimeter wave radar static target corresponding to the minimum mahalanobis distance is associated with a similar preset sensor target in a failure.
The calculating the mahalanobis distance between each millimeter wave radar static target and each preset sensor target may include: according to the formula:
calculating the Mahalanobis distance D between each millimeter wave radar static target and each preset sensor target;
wherein X represents the preset sensor target coordinate, Y represents the millimeter wave radar static target coordinate, and W represents the sum matrix of the covariance matrix of the millimeter wave radar static target coordinate and the covariance matrix of the preset sensor target coordinate.
It should be noted that X may further include a speed of a preset sensor target, and correspondingly, Y may include a speed of a millimeter wave radar static target; by comprehensively considering the position and the speed of the target, whether the preset sensor target is associated with the millimeter wave radar static target or not is judged, and the accuracy of association judgment can be further improved.
In an optional implementation manner of this embodiment, before performing association determination on each millimeter wave radar static target and each preset sensor target, the method may further include: filtering the preset sensor target through a preset filtering algorithm to obtain an effective preset sensor target; correspondingly, the association judgment of each millimeter wave radar static target and each preset sensor target may include: and performing association judgment on each millimeter wave radar static target and each effective preset sensor target. The preset filtering algorithm may include a kalman filtering algorithm, a particle filtering algorithm, and the like.
It is understood that some preset sensor targets may jump or be temporarily lost during the continuous tracking detection of the preset sensor targets, and at this time, such preset sensor targets may be determined as misrecognized targets. For such a misrecognized target, it is not necessary to perform association determination with the millimeter wave radar static target. Therefore, the preset sensor target is screened in advance through the preset filtering algorithm to obtain the effective preset sensor target, the effective preset sensor target and the millimeter wave radar static target are subjected to association judgment, and the association judgment efficiency can be improved.
S130, according to the association judgment result, determining an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target, and tracking and managing the associated target in the life cycle of the target.
In this embodiment, after the association determination of the millimeter wave radar static target and the preset sensor target is completed; and selecting the millimeter wave radar static target successfully associated with the preset sensor target as an associated target, and continuously tracking and managing each associated target until the life cycle of the associated target is finished, namely the associated target cannot be detected any more.
According to the technical scheme provided by the embodiment of the invention, a plurality of preset sensor targets and millimeter wave radar static targets are obtained in the running process of a vehicle, and correlation judgment is carried out on each millimeter wave radar static target and each preset sensor target; determining a correlation target successfully correlated with at least one preset sensor target in each millimeter wave radar static target according to the correlation judgment result, and tracking and managing the correlation target in the life cycle of the target; the millimeter wave radar static target is subjected to correlation judgment by utilizing each preset sensor target, so that the stability of the millimeter wave radar in recognizing the static target is enhanced, the target recognition performance of the millimeter wave radar on the preset sensor under a specific scene is supplemented, and the robustness of the automatic driving system is improved.
In a specific implementation manner of this embodiment, as shown in fig. 1B, the laser radar and the visual fusion target are first obtained, and the obtained targets are screened through a preset filtering algorithm to obtain an effective laser radar and a visual fusion target. And then respectively carrying out association judgment on the millimeter wave radar static target and the effective laser radar and the visual fusion target, if the millimeter wave radar static target and the effective laser radar and the visual fusion target are determined to be successfully associated, marking the millimeter wave radar static target and the corresponding effective laser radar and visual fusion target as associated targets, and carrying out tracking management on the associated targets in the life cycle of the targets.
If the millimeter wave radar static target is determined to be failed to be associated with each effective laser radar and visual fusion target, acquiring a single laser radar target, screening the effective single laser radar target, and further performing association judgment on the millimeter wave radar static target and the effective single laser radar target; and if the successful association is determined, marking the millimeter wave radar static target and the corresponding effective single laser radar target as an associated target, and tracking and managing the associated target in the life cycle of the target.
Further, if the correlation still fails, obtaining a single vision target, screening effective single vision targets, and further performing correlation judgment on the millimeter wave radar static target and the effective single vision targets; and if the successful association is determined, marking the millimeter wave radar static target and the corresponding effective single-vision target as an associated target, and tracking and managing the associated target in the life cycle of the target. Otherwise, ending the target identification process.
In this embodiment, the correlation determination may be performed on the millimeter wave radar static target and each type of preset sensor target at the same time, or may be performed sequentially; in this embodiment, the association determination sequence between the millimeter wave radar static target and each type of preset sensor target is not specifically limited.
Fig. 2A is a flowchart of a target identification method according to yet another embodiment of the present invention, where the present embodiment is based on the foregoing technical solution, in this embodiment, when an abnormal preset sensor target with abnormal identification is detected, a millimeter wave radar static target successfully associated with the abnormal preset sensor target is determined, and when it is determined that a target confidence corresponding to the millimeter wave radar static target is greater than or equal to a preset confidence threshold, vehicle driving control is performed according to the millimeter wave radar static target; as shown in fig. 2A, the method specifically includes:
s210, in the running process of the vehicle, at least one preset sensor target and a millimeter wave radar static target are obtained.
S220, respectively calculating the Mahalanobis distance between each millimeter wave radar static target and each preset sensor target, and determining each similar preset sensor target with the minimum Mahalanobis distance between each millimeter wave radar static target and each preset sensor target.
And S230, if the minimum Mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is smaller than a preset distance threshold value, determining that the detected millimeter wave radar static target is successfully associated with the corresponding similar preset sensor target.
S240, if the minimum Mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is detected to be larger than or equal to the preset distance threshold, determining that the detected millimeter wave radar static target is in failed association with the corresponding similar preset sensor target.
And S250, determining a related target successfully related to at least one preset sensor target in each millimeter wave radar static target according to the related judgment result.
S260, configuring a target confidence for the associated target according to the target type of the similar preset sensor target successfully associated with the associated target.
In this embodiment, after determining the associated target, a corresponding target confidence may be configured for the associated target based on the target type of the similar preset sensor target successfully associated with the associated target. It can be appreciated that the lidar and the vision fusion target are more trustworthy due to their co-determination by the lidar and the vision sensor, and correspondingly, the single lidar target and the single vision target are less trustworthy. Thus, a higher target confidence (e.g., 0.9) may be configured for associated targets successfully associated with the lidar and the visual fusion target, and a lower target confidence (e.g., 0.7) may be configured for associated targets successfully associated with the single lidar target or the single visual target.
S270, when the abnormal preset sensor target with abnormal recognition is detected, whether the millimeter wave radar static target successfully associated with the abnormal preset sensor target exists or not is judged.
The identification exception may include target jump, unstable target attribute identification, transient target loss, and the like.
In this embodiment, when it is detected that the preset sensor target has an identification abnormality, the preset sensor target may be determined as an abnormal preset sensor target, and it is determined whether a millimeter wave radar static target successfully associated with the abnormal preset sensor target exists.
And S280, if so, carrying out vehicle running control according to the millimeter wave radar static target when the target confidence corresponding to the millimeter wave radar static target is determined to be greater than or equal to a preset confidence threshold value.
At this time, if the millimeter wave radar static target successfully associated with the abnormal preset sensor target is detected, whether the target confidence of the millimeter wave radar static target successfully associated at present is greater than or equal to a preset confidence threshold value or not can be further judged; if so, the current millimeter wave radar static target is used as a target stability basis to control vehicle running, so that the robustness of the automatic driving system can be improved.
Different preset confidence threshold values can be set for different scenes; for example, when the abnormal preset sensor target is a lidar and a vision fusion target, a higher preset confidence threshold may be set; alternatively, a lower preset confidence threshold may be set when the anomalous preset sensor target is a single lidar target or a single vision target.
Optionally, the usable time of the millimeter wave radar static target may also be determined according to the target type and the target confidence degree of the millimeter wave radar static target successfully associated with the target; for example, if the target type successfully associated with the millimeter wave radar static target is a laser radar and visual fusion target, and has a higher target confidence, a longer usable time may be set; if the target type successfully associated with the millimeter wave radar static target is a single laser radar target or a single visual target and has a low target confidence coefficient, a short usable time can be set.
In one scenario, for a static target, in an initial short time, the laser radar is unstable in identifying the speed attribute of the target, and a large deviation is easy to occur. For the above problem, when a single laser radar is used for target detection, multiple filtering is required, or other target attributes are introduced for calculation, so as to stably identify the speed attribute of the target. In addition, when the lidar is affected by environmental factors (e.g., fog or rain, etc.), and target hopping occurs simultaneously in target identification, a more complex fault-tolerant processing mechanism is required for processing.
Under the condition, a millimeter wave radar static target successfully associated with the current single laser radar target can be obtained; if the target is continuously and stably tracked by the millimeter wave radar, stable identification of the speed attribute of the target can be realized based on the millimeter wave radar, the calculation force can be saved, and meanwhile, the problem of target jump of the single laser radar can be solved.
In another scenario, for a long-time stationary target, the visual sensor may have occasional target class jumps or transient target losses; in order to solve the above problems, the training of the visual sensor on the target needs to be enhanced to improve the recognition accuracy of the single-vision target. Therefore, a large number of training samples need to be obtained, and a large amount of manpower and material resources need to be invested. By the method provided by the embodiment, the millimeter wave radar static target successfully associated with the single vision target can be obtained, and the identification result of the millimeter wave radar on the static target is used as the basis for automatic driving. In this embodiment, by adding the associable millimeter wave radar static target, stable identification of the visual sensor to the full-scene full target can be realized under different development budgets and development periods, and the robustness of the automatic driving system can be improved.
In another scene, when transient visual occlusion occurs in the automatic driving process, the visual perception capability of the visual sensor is greatly influenced, and transient target loss or jump occurs; in this case, for the single vision sensor, the whole sensor configuration needs to be improved, and the other vision sensors are used for complementation, so as to solve the above problem. In the embodiment, the problem of sporadic occurrence can be solved by adding the associable millimeter wave radar static target, the cost of the automatic driving system is reduced, and the calculation force is saved.
According to the technical scheme provided by the embodiment of the invention, after the associated target successfully associated with at least one preset sensor target is determined in each millimeter wave radar static target according to the association judgment result, the target confidence coefficient is configured for the associated target according to the target type of the similar preset sensor target successfully associated with the associated target, and when the abnormal preset sensor target with abnormal identification is detected, whether the millimeter wave radar static target successfully associated with the abnormal preset sensor target exists or not is judged; if the target confidence degree corresponding to the millimeter wave radar static target is larger than or equal to the preset confidence degree threshold value, vehicle running control is carried out according to the millimeter wave radar static target, and when the preset sensor target is identified abnormally, the millimeter wave radar static target successfully associated with the preset sensor is used as a target stable tracking basis, so that the cost of the automatic driving system can be reduced, the calculation power is saved, and the robustness of the automatic driving system can be improved.
In a specific implementation manner of this embodiment, as shown in fig. 2B, when the recognition of the single lidar target, the single vision target, and the lidar and vision fusion target is abnormal, it is determined whether there is a successfully associated millimeter wave radar static target; if yes, when the millimeter wave radar static target is determined to be stably tracked, whether the target confidence degree corresponding to the millimeter wave radar static target meets a preset confidence degree threshold value in the current scene is further judged. And when the target confidence coefficient is determined to meet the preset confidence coefficient threshold, taking the millimeter wave radar static target as a main judgment condition to avoid transient sensing abnormal conditions of other sensors.
Fig. 3A is a flowchart of a target identification method according to another embodiment of the present invention, where the present embodiment is based on the above technical solution, and in the present embodiment, an alarm of vehicle automatic driving abnormality is performed based on a millimeter wave radar static target associated with a corresponding similar preset sensor failure; as shown in fig. 3A, the method specifically includes:
s310, in the running process of the vehicle, at least one preset sensor target and a millimeter wave radar static target are obtained.
And S320, respectively calculating the Mahalanobis distance between each millimeter wave radar static target and each preset sensor target, and determining each similar preset sensor target with the minimum Mahalanobis distance between each millimeter wave radar static target and each preset sensor target.
S330, if the minimum Mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is smaller than a preset distance threshold value, the fact that the detected millimeter wave radar static target is successfully associated with the corresponding similar preset sensor target is determined.
S340, if the minimum Mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is detected to be larger than or equal to the preset distance threshold, determining that the detected millimeter wave radar static target is in failed association with the corresponding similar preset sensor target.
And S350, according to the association judgment result, determining an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target, and tracking and managing the associated target in the life cycle of the target.
And S360, screening the millimeter wave radar static targets related to the vehicle driving safety from the millimeter wave radar static targets related to the failure of the corresponding similar preset sensors, and carrying out tracking management on the temporary millimeter wave radar static targets.
And S370, in a preset time range, if the temporary millimeter wave radar static target is detected to be stably identified, generating alarm information corresponding to the temporary millimeter wave radar static target and sending the alarm information to a vehicle driver.
It should be noted that, for a millimeter wave radar static target associated with a corresponding similar preset sensor failure, it indicates that no other sensor stably identifies the target at present; in general, such objects often belong to misrecognized objects. However, in some specific scenarios, such targets may correspond to specific targets, such as a white indicator board appearing on the road, or a truck parked laterally, etc.; by further analyzing and judging the targets, the target under a special scene can be prevented from being missed to be reported.
In this embodiment, the millimeter wave radar static targets that are associated with the corresponding similar preset sensor failures may be first screened to retain the unassociated millimeter wave radar static targets on the driving path; and then, temporary millimeter wave radar static targets related to vehicle driving safety are further screened out from the unassociated millimeter wave radar static targets, for example, targets such as advertising boards and the like can be removed. Then, continuously tracking and managing the screened temporary millimeter wave radar static target; wherein the target attributes (e.g., position, speed, etc.) of the temporary millimeter wave radar static target can be continuously tracked and managed. The vehicle travel path may be determined from navigation information of the vehicle or manually selected by a user.
Further, if the temporary millimeter wave radar static target is not subjected to target hopping, transient target loss or target attribute hopping and other abnormalities within the preset time range, that is, is stably tracked within the preset time range, it indicates that the temporary millimeter wave radar static target may endanger the automatic driving safety. At this time, the warning information corresponding to the temporary millimeter wave radar static target may be generated and sent to the vehicle driver, and the vehicle driver determines whether to exit the automatic driving state and take over the vehicle, or continue to maintain the automatic driving state.
The preset time range can be set according to the working condition and the vehicle state. The warning information may include information such as the position, speed and category of the temporary millimeter wave radar static target; the content and form of the warning information are not particularly limited in this embodiment.
According to the technical scheme provided by the embodiment of the invention, when the static targets of the detected millimeter wave radar are determined to be in failure association with the corresponding similar preset sensor targets, temporary millimeter wave radar static targets related to the running safety of the vehicle are obtained by screening the millimeter wave radar static targets associated with the corresponding similar preset sensor failures, and the temporary millimeter wave radar static targets are tracked and managed; within a preset time range, if the temporary millimeter wave radar static target is detected to be stably identified, generating alarm information corresponding to the temporary millimeter wave radar static target and sending the alarm information to a vehicle driver; by further analyzing and judging the millimeter wave radar static target which is associated with the failure, the target under a special scene can be prevented from being missed, the accuracy of target identification can be improved, and the robustness of an automatic driving system can be further improved.
In a specific implementation manner of this embodiment, as shown in fig. 3B, a millimeter wave radar static target that is associated with a failure is subjected to a screening process to obtain a millimeter wave radar static target on a driving path, and when it is determined that the screened millimeter wave radar static target is related to driving safety, the millimeter wave radar static target is subjected to tracking management in a life cycle. Further, in a specific time, if the millimeter wave radar static target is continuously and stably tracked, corresponding warning information is generated and fed back to the vehicle owner.
Fig. 4 is a schematic structural diagram of a target identification apparatus according to another embodiment of the present invention. As shown in fig. 4, the apparatus includes: an object acquisition module 410, an association determination module 420, and an association object determination module 430. Wherein the content of the first and second substances,
the target acquisition module 410 is used for acquiring at least one preset sensor target and a millimeter wave radar static target in the running process of the vehicle;
the association judgment module 420 is configured to perform association judgment on each millimeter wave radar static target and each preset sensor target;
and the associated target determining module 430 is configured to determine, according to the association determination result, an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target, and perform tracking management on the associated target in a target life cycle.
According to the technical scheme provided by the embodiment of the invention, a plurality of preset sensor targets and millimeter wave radar static targets are obtained in the running process of the vehicle, and correlation judgment is carried out on each millimeter wave radar static target and each preset sensor target; determining a correlation target successfully correlated with at least one preset sensor target in each millimeter wave radar static target according to the correlation judgment result, and tracking and managing the correlation target in the life cycle of the target; the millimeter wave radar static target is subjected to correlation judgment by utilizing each preset sensor target, so that the stability of the millimeter wave radar in recognizing the static target is enhanced, the target recognition performance of the millimeter wave radar on the preset sensor under a specific scene is supplemented, and the robustness of the automatic driving system is improved.
Optionally, on the basis of the above technical scheme, the preset sensor target includes a single laser radar target, a single vision target, and at least one of a laser radar and a vision fusion target.
Optionally, on the basis of the foregoing technical solution, the association determining module 420 includes:
the distance calculation unit is used for calculating the Mahalanobis distance between each millimeter wave radar static target and each preset sensor target respectively, and determining each similar preset sensor target with the minimum Mahalanobis distance between each millimeter wave radar static target and each preset sensor target;
the successful association determining unit is used for determining that the detected millimeter wave radar static target is successfully associated with the corresponding similar preset sensor target if the minimum Mahalanobis distance between the detected millimeter wave radar static target and the corresponding similar preset sensor target is smaller than a preset distance threshold;
and the failure association determining unit is used for determining that the detected millimeter wave radar static target is in failure association with the corresponding similar preset sensor target if the minimum mahalanobis distance between the detected millimeter wave radar static target and the corresponding similar preset sensor target is greater than or equal to a preset distance threshold.
Optionally, on the basis of the above technical solution, the distance calculating unit is specifically configured to:
calculating the Mahalanobis distance D between each millimeter wave radar static target and each preset sensor target;
wherein X represents the preset sensor target coordinate, Y represents the millimeter wave radar static target coordinate, and W represents the sum matrix of the covariance matrix of the millimeter wave radar static target coordinate and the covariance matrix of the preset sensor target coordinate.
Optionally, on the basis of the above technical solution, the object recognition apparatus further includes:
and the confidence coefficient configuration module is used for configuring a target confidence coefficient for the associated target according to the target type of the similar preset sensor target successfully associated with the associated target.
Optionally, on the basis of the above technical solution, the object recognition apparatus further includes:
the abnormal preset sensor target detection module is used for judging whether a millimeter wave radar static target which is successfully associated exists in the abnormal preset sensor target when the abnormal preset sensor target which is identified abnormally is detected;
and the target confidence judgment module is used for controlling vehicle running according to the millimeter wave radar static target when the target confidence corresponding to the millimeter wave radar static target is determined to be greater than or equal to a preset confidence threshold value if the target confidence is determined to be greater than or equal to the preset confidence threshold value.
Optionally, on the basis of the above technical solution, the object recognition apparatus further includes:
the temporary millimeter wave radar static target screening module is used for screening a millimeter wave radar static target related to vehicle driving safety from the millimeter wave radar static targets related to failure of the corresponding similar preset sensor, and tracking and managing the temporary millimeter wave radar static target;
and the warning information generating module is used for generating warning information corresponding to the temporary millimeter wave radar static target and sending the warning information to a vehicle driver if the temporary millimeter wave radar static target is detected to be stably identified within a preset time range.
The device can execute the target identification method provided by the embodiment of the invention, and has corresponding functional modules and beneficial effects for executing the method. For technical details that are not described in detail in the embodiments of the present invention, reference may be made to the target identification method provided in the foregoing embodiments of the present invention.
Fig. 5 is a schematic structural diagram of an electronic device according to another embodiment of the present invention, as shown in fig. 5, the electronic device includes a processor 510, a memory 520, an input device 530, and an output device 540; the number of the processors 510 in the electronic device may be one or more, and one processor 510 is taken as an example in fig. 5; the processor 510, the memory 520, the input device 530 and the output device 540 in the electronic apparatus may be connected by a bus or other means, and the connection by the bus is exemplified in fig. 5. The memory 520 may be used as a computer-readable storage medium for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to an object recognition method in any embodiment of the present invention (e.g., the object obtaining module 410, the association judging module 420, and the association object determining module 430 in an object recognition apparatus). The processor 510 executes various functional applications and data processing of the electronic device by executing software programs, instructions and modules stored in the memory 520, so as to implement one of the object recognition methods described above.
That is, the program when executed by the processor implements:
in the running process of a vehicle, at least one preset sensor target and a millimeter wave radar static target are obtained;
performing association judgment on each millimeter wave radar static target and each preset sensor target;
and according to the association judgment result, determining an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target, and tracking and managing the associated target in the life cycle of the target.
The memory 520 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the memory 520 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, memory 520 may further include memory located remotely from processor 510, which may be connected to an electronic device through a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 530 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic apparatus, and may include a keyboard, a mouse, and the like. The output device 540 may include a display device such as a display screen.
Embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method according to any of the embodiments of the present invention. Of course, the embodiment of the present invention provides a computer-readable storage medium, which can perform related operations in a target identification method provided in any embodiment of the present invention. That is, the program when executed by the processor implements:
acquiring at least one preset sensor target and a millimeter wave radar static target in the running process of a vehicle;
performing association judgment on each millimeter wave radar static target and each preset sensor target;
and according to the association judgment result, determining an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target, and tracking and managing the associated target in the life cycle of the target.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes instructions for enabling an electronic device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the object recognition apparatus, the included units and modules are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A method of object recognition, comprising:
acquiring at least one preset sensor target and a millimeter wave radar static target in the running process of a vehicle;
performing association judgment on each millimeter wave radar static target and each preset sensor target;
and according to the association judgment result, determining an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target, and tracking and managing the associated target in the life cycle of the target.
2. The method of claim 1, wherein the pre-set sensor targets include a single lidar target, a single vision target, and at least one of a lidar and a vision fusion target.
3. The method of claim 1, wherein the association determination of each millimeter wave radar static target with each preset sensor target comprises:
respectively calculating the Mahalanobis distance between each millimeter wave radar static target and each preset sensor target, and determining each similar preset sensor target with the minimum Mahalanobis distance between each millimeter wave radar static target and each preset sensor target;
if the minimum Mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is smaller than a preset distance threshold value, determining that the detected millimeter wave radar static target is successfully associated with the corresponding similar preset sensor target;
and if the fact that the minimum Mahalanobis distance between one millimeter wave radar static target and the corresponding similar preset sensor target is larger than or equal to the preset distance threshold value is detected, determining that the detected millimeter wave radar static target is in failed association with the corresponding similar preset sensor target.
4. The method of claim 3, wherein calculating the Mahalanobis distance between each millimeter wave radar static target and each preset sensor target respectively comprises:
according to the formula:
calculating the Mahalanobis distance D between each millimeter wave radar static target and each preset sensor target;
wherein X represents the preset sensor target coordinate, Y represents the millimeter wave radar static target coordinate, and W represents the sum matrix of the covariance matrix of the millimeter wave radar static target coordinate and the covariance matrix of the preset sensor target coordinate.
5. The method according to claim 3, further comprising, after determining, in the millimeter wave radar static targets, an associated target that is successfully associated with at least one preset sensor target according to the association determination result:
and configuring a target confidence for the associated target according to the target type of the similar preset sensor target successfully associated with the associated target.
6. The method of claim 5, further comprising:
when the abnormal preset sensor target with abnormal recognition is detected, judging whether the abnormal preset sensor target has a millimeter wave radar static target which is successfully associated;
and if so, carrying out vehicle running control according to the millimeter wave radar static target when the target confidence corresponding to the millimeter wave radar static target is determined to be greater than or equal to a preset confidence threshold.
7. The method of claim 3, further comprising:
screening a temporary millimeter wave radar static target related to vehicle running safety from the millimeter wave radar static targets related to failure of corresponding similar preset sensors, and carrying out tracking management on the temporary millimeter wave radar static target;
and in a preset time range, if the temporary millimeter wave radar static target is detected to be stably identified, generating alarm information corresponding to the temporary millimeter wave radar static target and sending the alarm information to a vehicle driver.
8. An object recognition apparatus, comprising:
the target acquisition module is used for acquiring at least one preset sensor target and a millimeter wave radar static target in the running process of the vehicle;
the correlation judgment module is used for performing correlation judgment on each millimeter wave radar static target and each preset sensor target;
and the associated target determining module is used for determining an associated target successfully associated with at least one preset sensor target in each millimeter wave radar static target according to the association judgment result, and tracking and managing the associated target in the life cycle of the target.
9. An electronic device, comprising:
one or more processors;
storage means for storing one or more computer programs;
the object recognition method as claimed in any one of claims 1-7, when the one or more computer programs are executed by the one or more processors such that the one or more processors execute the computer programs.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the object recognition method of any one of claims 1 to 7.
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