CN114003613A - High-precision map lane line updating method and device, electronic equipment and storage medium - Google Patents
High-precision map lane line updating method and device, electronic equipment and storage medium Download PDFInfo
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Abstract
The disclosure provides a high-precision map lane line updating method and device, electronic equipment and a storage medium, and relates to the technical field of computers, in particular to the fields of automatic driving, intelligent transportation and big data. The specific implementation scheme is as follows: determining at least one matching pair meeting a preset condition from at least one first vector point corresponding to the acquired lane line data and at least one second vector point corresponding to the historical lane line data, wherein each matching pair comprises one first vector point and one second vector point; calculating, for each matching pair, an evaluation value corresponding to the matching pair; determining a target matching pair according to the evaluation value; and updating the historical lane line data according to the first vector point in the target matching pair.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for updating a lane line of a high-precision map, an electronic device, and a storage medium.
Background
The high-precision map is used as a scarce resource in the field of unmanned driving and is just needed, plays a core role in the whole field, can help an unmanned vehicle to sense complex road information such as gradient, curvature, course and the like in advance, and is an indispensable data source for unmanned vehicle driving by combining with intelligent path planning to make a correct decision for the unmanned vehicle. The unmanned vehicle can be ensured to be safely driven to a destination only by comparing the information collected by the sensor with the stored high-precision map and judging the position and the direction. Therefore, the accuracy of high-precision map data acquisition is very critical for unmanned driving.
Disclosure of Invention
The disclosure provides a high-precision map lane line updating method and device, electronic equipment and a storage medium.
According to an aspect of the present disclosure, there is provided a high-precision map lane line updating method, including: determining at least one matching pair meeting a preset condition from at least one first vector point corresponding to the acquired lane line data and at least one second vector point corresponding to the historical lane line data, wherein each matching pair comprises one first vector point and one second vector point; calculating, for each of the matching pairs, an evaluation value corresponding to the matching pair; determining a target matching pair according to the evaluation value; and updating the historical lane line data according to the first vector point in the target matching pair.
According to another aspect of the present disclosure, there is provided a high-precision map lane line updating apparatus including: the system comprises a first determining module, a second determining module and a judging module, wherein the first determining module is used for determining at least one matching pair meeting a preset condition from at least one first vector point corresponding to collected lane line data and at least one second vector point corresponding to historical lane line data, and each matching pair comprises one first vector point and one second vector point; a calculation module configured to calculate, for each of the matching pairs, an evaluation value corresponding to the matching pair; the second determining module is used for determining a target matching pair according to the evaluation value; and the first updating module is used for updating the historical lane line data according to the first vector point in the target matching pair.
According to another aspect of the present disclosure, there is provided an electronic device including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the high precision map lane line updating method as described above.
According to another aspect of the present disclosure, there is provided a non-transitory computer readable storage medium storing computer instructions for causing the computer to execute the high-precision map lane line updating method as described above.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements a high-precision map lane line updating method as described above.
It should be understood that the statements in this section do not necessarily identify key or critical features of the embodiments of the present disclosure, nor do they limit the scope of the present disclosure. Other features of the present disclosure will become apparent from the following description.
Drawings
The drawings are included to provide a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 schematically illustrates an exemplary system architecture to which the high-precision map lane line updating method and apparatus may be applied, according to an embodiment of the present disclosure;
FIG. 2 schematically illustrates a flow chart of a high precision map lane line update method according to an embodiment of the present disclosure;
FIG. 3 schematically illustrates an overall flow chart of a high-precision map lane line update method according to an embodiment of the present disclosure;
FIG. 4 schematically illustrates a block diagram of a high-precision map lane line update apparatus according to an embodiment of the present disclosure; and
FIG. 5 illustrates a schematic block diagram of an example electronic device that can be used to implement embodiments of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below with reference to the accompanying drawings, in which various details of the embodiments of the disclosure are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
In the technical scheme of the disclosure, the collection, storage, use, processing, transmission, provision, disclosure and other processing of the personal information of the related user are all in accordance with the regulations of related laws and regulations, necessary security measures are taken, and the customs of the public order is not violated.
High-precision maps play an important role in autonomous driving of automobiles. Especially, the timeliness of data in a high-precision map is significant to automatic driving. The data updating production mode of the high-precision map is mainly that after various sensor data of road information are regularly acquired by a professional acquisition vehicle, the data change points are found and updated in an automatic algorithm and manual marking mode. The sensor data mainly includes IMU (Inertial Measurement Unit) trajectory data, laser point cloud data, and high-speed camera image data. By applying the marking mode based on the original data to the production line in a large scale and researching and developing an automatic marking algorithm, the operation time of marking personnel can be greatly saved, the marking efficiency is improved, and the production cost is reduced.
The inventor finds that in the process of realizing the concept disclosed by the invention, the original data are subjected to certain data processing to generate visual labeling data, including 2/3-dimensional point cloud views, image views, track data and the like. The marking personnel refers to the data on a customized marking tool and compares the existing master database data to find and update lane line change points. The main elements of the labeling include lane line geometry, lane line topology and lane line attributes. The following pain points are mainly present: the automatic labeling algorithm faces a plurality of scenes, which easily causes recognition errors, such as non-recall caused by road abrasion and road shielding, unstable acquisition quality caused by the influence of various factors, and error recognition caused by environment and system reasons. The lane line change point finding efficiency is low, and the marking personnel can find the change point only after rechecking the full-image data, so the cost is high. The labeling efficiency is low, and the labeling personnel need to manually delete, update, add and the like according to the data of the change point. The requirement on the quality of the marking personnel is high, the high-precision map has certain requirements on the data precision, and the marking personnel can be competent for the work after long-time training, so that the labor input cost is increased.
In view of this, the present disclosure provides a method for updating a lane line of a high-precision map, including: determining at least one matching pair satisfying a preset condition from at least one first vector point corresponding to the collected lane line data and at least one second vector point corresponding to the historical lane line data. Each matching pair includes a first vector point and a second vector point. For each matching pair, an evaluation value corresponding to the matching pair is calculated. And determining a target matching pair according to the evaluation value. And updating the historical lane line data according to the first vector point in the target matching pair.
Fig. 1 schematically illustrates an exemplary system architecture to which the high-precision map lane line updating method and apparatus may be applied, according to an embodiment of the present disclosure.
It should be noted that fig. 1 is only an example of a system architecture to which the embodiments of the present disclosure may be applied to help those skilled in the art understand the technical content of the present disclosure, and does not mean that the embodiments of the present disclosure may not be applied to other devices, systems, environments or scenarios. For example, in another embodiment, an exemplary system architecture to which the high-precision map lane line updating method and apparatus may be applied may include a terminal device, but the terminal device may implement the high-precision map lane line updating method and apparatus provided by the embodiments of the present disclosure without interacting with a server.
As shown in fig. 1, the system architecture 100 according to this embodiment may include terminal devices 101, 102, 103, a network 104 and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired and/or wireless communication links, and so forth.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as a knowledge reading application, a web browser application, a search application, an instant messaging tool, a mailbox client, and/or social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for content browsed by the user using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device. The Server may be a cloud Server, which is also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service extensibility in a traditional physical host and a VPS service ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed system, or a server incorporating a blockchain.
It should be noted that the high-precision map lane line updating method provided by the embodiment of the present disclosure may be generally executed by the terminal device 101, 102, or 103. Accordingly, the high-precision map lane line updating device provided by the embodiment of the present disclosure may also be provided in the terminal device 101, 102, or 103.
Alternatively, the high-precision map lane line updating method provided by the embodiment of the present disclosure may also be generally executed by the server 105. Accordingly, the high-precision map lane line updating device provided by the embodiment of the present disclosure may be generally disposed in the server 105. The high-precision map lane line updating method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the high-precision map lane line updating device provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster that is different from the server 105 and is capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
For example, when it is necessary to update lane line data, the terminal devices 101, 102, 103 may acquire the acquired lane line data and the historical lane line data, and then transmit the acquired lane line data and the historical lane line data to the server 105, determine, by the server 105, at least one matching pair that satisfies a preset condition from among at least one first vector point corresponding to the acquired lane line data and at least one second vector point corresponding to the historical lane line data, each matching pair including one first vector point and one second vector point, calculate, for each matching pair, an evaluation value corresponding to the matching pair, determine a target matching pair according to the evaluation value, and update the historical lane line data according to the first vector point in the target matching pair. Or by a server or server cluster capable of communicating with the terminal devices 101, 102, 103 and/or the server 105, analyzing the collected lane line data and the historical lane line data and enabling updating of the historical lane line data.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Fig. 2 schematically shows a flowchart of a high-precision map lane line updating method according to an embodiment of the present disclosure.
As shown in fig. 2, the method includes operations S210 to S240.
In operation S210, at least one matching pair satisfying a preset condition is determined from at least one first vector point corresponding to the collected lane line data and at least one second vector point corresponding to the historical lane line data, each matching pair including one first vector point and one second vector point.
In operation S220, for each matching pair, an evaluation value corresponding to the matching pair is calculated.
In operation S230, a target matching pair is determined according to the evaluation values.
In operation S240, the historical lane line data is updated according to the first vector point in the target matching pair.
According to an embodiment of the present disclosure, the acquired lane line data may include bounding box data including lane line features newly acquired at a current time or within a preset time period, and the bounding box data may include lane line features within a preset three-dimensional space range centered on a current acquisition point. The lane line feature may include at least one of position data, image data, point cloud data, and the like of the lane line. By vectorized modeling of newly acquired bounding box data, lane line features characterized by the bounding box data can be converted into a representation of vector points. The historical lane line data may include road network data for characterizing lane line characteristics of the historical lane lines that has been stored in a road network database. The road network data may be stored in the road network database in the form of vector points. The point information of the vector point may indicate position information corresponding to the point, and the direction information of the vector point may be determined based on the route of the lane line or the allowable vehicle traveling direction of the lane line. The acquired lane line data may include lane line characteristics acquired for each area lane line without limiting the range. The current time and the preset time period for collecting the lane line data are both later than the storage time of the historical lane line data.
According to the embodiment of the present disclosure, by uniformly sampling the bounding box data and the road network data expressed in the form of vector points given a predetermined sampling step, a first vector point and a second vector point can be obtained, respectively. During sampling, spatial relationship information such as predecessor successors, left-right relationships and the like among sampling points can be determined by adopting a Kdtree (K-dimension tree) according to the physical spatial relationship of the sampling points.
According to an embodiment of the present disclosure, the preset condition may include: the two vector points are contained in the same area range with the predefined size, and the result of the matching difference of the two vector points meets at least one of the preset matching formulas. The step of matching the two vector points with the difference satisfying the preset matching formula may include: the distance and the direction included angle between the two vector points both meet corresponding preset ranges, and the normal distance between the two vector points meets at least one of the corresponding preset ranges. In case at least one of the aforementioned conditions is fulfilled, the respective first and second vector points may be determined as one matching pair.
According to the embodiment of the present disclosure, the evaluation value calculation formula may be constructed from at least one of the position information and the direction information of each of the two vector points in the matching pair, the distance information and the direction angle information between the two vector points, and the position information and the direction information of the other vector points having a relationship of predecessor, successor, left, right, and the like with any one vector point. For each matching pair, a corresponding evaluation value may be calculated based on the evaluation value calculation formula.
According to the embodiment of the present disclosure, according to the target matching pair determined by the evaluation value, new lane line data in which there is a change compared to the history lane line data, that is, the first vector point in the target matching pair, can be further obtained from the matching pair. The manner of determining the target matching pair according to the evaluation value may include: a preset range may be defined in advance, and a matching pair corresponding to the evaluation value within the preset range may be determined as a target matching pair. Or sorting according to the evaluation values to obtain a sorting result, and then determining the matching pairs corresponding to the preset evaluation values with larger values as the target matching peers according to the sorting result. It should be noted that, the manner of determining the target matching pair is not limited herein, and any other feasible determination manner may also be included in other embodiments of the present disclosure.
According to the embodiment of the disclosure, after the target matching pair is determined, the lane line data to be added may be determined according to the first vector point in the target matching pair. Then, the lane line data to be added may be added to the historical lane line data, and the update of the historical lane line data is completed.
Through the embodiment of the disclosure, the target matching pair is determined according to the evaluation value, the first vector point which is possibly changed compared with the historical lane line data can be further determined from the first vector point and the second vector point which are matched as the matching pair, and then automatic updating is carried out, so that the calling-ready rate of automatic marking is improved, the manual marking investment can be effectively reduced, the accuracy and the integrity of the change point discovery can be effectively improved, and the updating efficiency of the high-precision map is improved.
The method shown in fig. 2 is further described below with reference to specific embodiments.
According to an embodiment of the present disclosure, determining at least one matching pair satisfying a preset condition from among at least one first vector point corresponding to the collected lane line data and at least one second vector point corresponding to the historical lane line data may include: and respectively calculating the distance and the direction included angle between the first vector point and each second vector point aiming at each first vector point. And determining a matching pair meeting the preset condition according to the first vector point and the second vector point, wherein the distance is less than or equal to a second preset threshold value, and the direction included angle is less than or equal to a third preset threshold value.
According to an embodiment of the present disclosure, the second preset threshold may be less than or equal to the sampling step. The preset condition may include a preset matching formula (1) as follows:
d∈[0，wd]&&θ∈[0，wθ] (1)
where d may represent a distance between the first vector point and the second vector point, which may include, for example, a euclidean distance, a manhattan distance, a chebyshev distance, or the like. w is adA predefined maximum value for the distance, i.e. the second preset threshold mentioned above, may be represented. θ may represent a directional angle between the first vector point and the second vector point. w is aθA predefined maximum value for the direction angle, i.e. the third preset threshold, may be indicated.
According to an embodiment of the present disclosure, formula (1) is matched based on the above-mentioned preset. For example, the euclidean distance d between a first vector point and a second vector point may be first calculated1And angle theta of direction1. Then, according to the preset matching formula (1), d will be satisfied1∈[0，wd]&&θ1∈[0，wθ]Is determined as a matching pair.
Through the embodiment of the disclosure, at least one first vector point and at least one second vector point can be converted into the matching pair, and subsequent calculation is performed according to the matching pair, so that the calculation amount is effectively reduced, and the updating efficiency of the high-precision map is improved.
According to the embodiment of the present disclosure, determining the matching pair meeting the preset condition according to the first vector point and the second vector point, where the distance is less than or equal to the second preset threshold and the direction included angle is less than or equal to the third preset threshold, may include: and calculating the normal distance between the first vector point and the second vector point, wherein the distance is less than or equal to a second preset threshold value, and the direction included angle is less than or equal to a third preset threshold value. And determining the first vector point and the second vector point of which the normal distance is greater than or equal to a fourth preset threshold value as a matching pair.
According to embodiments of the present disclosure, the normal distance may represent a perpendicular distance of a point to a vector. For example, in this embodiment, the normal distance between the first vector point and the second vector point may include at least one of a first perpendicular distance from a point characterized by the first vector point to a vector characterized by the second vector point, and a second perpendicular distance from a point characterized by the second vector point to a vector characterized by the first vector point. The normal distance being greater than or equal to the fourth preset threshold may include at least one of the first vertical distance being greater than or equal to the fourth preset threshold, the second vertical distance being greater than or equal to the fourth preset threshold, and the like.
According to the embodiment of the disclosure, for the first vector point and the second vector point, the distance of which is less than or equal to the second preset threshold and the direction included angle of which is less than or equal to the third preset threshold, only the first vertical distance is greater than or equal to the fourth preset threshold, or the second vertical distance is greater than or equal to the fourth preset threshold, or both the first vector point and the second vector point, of which the first vertical distance and the second vertical distance are greater than or equal to the fourth preset threshold, are determined as the matching pair according to the relationship between the normal distance between the two vector points and the fourth preset threshold. And determining the first vector point and the second vector point of which the first vertical distance and the second vertical distance are both smaller than a fourth preset threshold as invalid change points.
Through the embodiment of the disclosure, the calculation of the normal distance between the first vector point and the second vector point is introduced, and the screening is performed according to the relation between the normal distance and the fourth preset threshold, so that the matching pairs with less data volume and higher effective change point occupation ratio are determined for subsequent calculation from the first vector point and the second vector point with the distance less than or equal to the second preset threshold and the direction included angle less than or equal to the third preset threshold, the calculation amount is effectively reduced, and the updating efficiency of the high-precision map is improved.
According to an embodiment of the present disclosure, calculating the evaluation value corresponding to the matching pair may include: at least one of a distance, a distance variance, and a directional angle between a first vector point and a second vector point in the matched pair is determined. An evaluation value corresponding to the matching pair is calculated based on at least one of the distance, the distance variance, and the direction angle.
According to an embodiment of the present disclosure, the distance variance may characterize a variance of distances of a plurality of predecessor successor matching pairs determined from predecessor successor vector points respectively associated with a first vector point and a second vector point of a matching pair, within a preset range from the first vector point and the second vector point constituting the matching pair.
According to the embodiment of the present disclosure, the evaluation value may be calculated from any at least one of the distance, the distance variance, and the direction angle between the first vector point and the second vector point in the matching pair. For example, the distance between a first vector point and a second vector point in a matching pair may be represented by d, the distance variance may be represented by w, and the included angle of direction may be represented by θ. The calculation manner of the evaluation value Score may include the following formula (2):
it should be noted that the calculation manner of the evaluation value may not be limited to that shown in formula (2), and other feasible formulas may be constructed according to at least any one of the distance, the distance variance and the direction angle between the first vector point and the second vector point in the matching pair, as long as the formula logic conforms to d, w, and Score is larger as θ is larger.
Through the embodiments of the present disclosure, a reliable evaluation value calculation manner is provided, and by combining parameters such as a distance between a first vector point and a second vector point in a matching pair, a distance variance, and a direction included angle, an evaluation value corresponding to the matching pair is calculated, so that accuracy of determining target matching according to the evaluation value can be improved, and update accuracy of a high-precision map can be improved.
According to an embodiment of the present disclosure, calculating the evaluation value corresponding to the matching pair according to at least one of the distance, the distance variance, and the direction angle may include: a distance correlation coefficient, a distance variance correlation coefficient, and a direction included angle correlation coefficient associated with at least one of the distance, the distance variance, and the direction included angle are determined, respectively. And calculating an evaluation value corresponding to the matching pair based on at least one of the distance correlation coefficient, the distance variance correlation coefficient, and the direction angle correlation coefficient.
According to an embodiment of the present disclosure, for example, a distance correlation coefficient may be determined from the distance d
The distance variance correlation coefficient can be determined from the distance variance w
The correlation coefficient of the direction included angle can be determined according to the direction included angle theta
The calculation manner of the evaluation value Score may further include the followingFormula (3) shows:
through the embodiment of the disclosure, another reliable evaluation value calculation mode is provided, and the evaluation value corresponding to the matching pair is calculated by combining the normalization coefficients related to the parameters such as the distance between the first vector point and the second vector point in the matching pair, the distance variance and the direction included angle, so that the accuracy of determining the target matching according to the evaluation value can be improved, and the updating precision of the high-precision map can be improved.
According to an embodiment of the present disclosure, determining the target matching pair according to the evaluation value may include: in the case where the evaluation value is greater than or equal to the first preset threshold value, a matching pair corresponding to the evaluation value is determined as a target matching pair.
According to the embodiment of the present disclosure, a first preset threshold may be predefined and used as a basis for distinguishing whether the first vector point in the matching pair is a change point. For example, in a case where the evaluation value calculated for a certain matching pair is smaller than a first preset threshold value, it may be determined that the first vector point in the matching pair does not belong to the change point, and the matching pair may not be regarded as the target matching pair. In the case where the evaluation value calculated for a certain matching pair is greater than or equal to the first preset threshold value, it may be determined that the first vector point in the matching pair belongs to the change point, and the matching pair may be regarded as a target matching pair. Therefore, the historical lane line data can be updated according to the first vector point in the target matching pair and the related lane line data thereof.
Through the embodiment of the disclosure, a mode of determining the target matching pair according to the evaluation value is provided, and on the basis of reasonably utilizing the evaluation value, the accuracy and the integrity of determining the change point are improved, so that the high-precision map is updated more accurately.
According to the embodiment of the disclosure, the first vector point and the second vector point outside the matching pair can be used as effective change points to update the lane lines in the high-precision map. In this case, the high-precision map lane line updating method may further include: at least one target first vector point and at least one target second vector point included in the at least one matching pair are determined. From the at least one first vector point, other first vector points than the target first vector point are determined. From the at least one second vector point, other second vector points than the target second vector point are determined. And updating the historical lane line data according to the other first vector points and the other second vector points.
According to the embodiments of the present disclosure, when matching a first vector point sampled for bounding box data and a second vector point sampled for road network data, there may be a case where matching is not possible with each other. For example, at least one of the second vector point not matching the first vector point, i.e. the other first vector points exist, and the first vector point not matching the second vector point, i.e. the other second vector points exist, may be included. Under the condition that any first vector point and any second vector point which are matched with each other do not exist, the other independent first vector points and other independent second vector points can be determined as effective change points because the other independent first vector points and other independent second vector points are not matched with the historical lane line data and the collected lane line data respectively, and the historical lane line data can be updated according to the other independent first vector points and other independent second vector points.
Through the embodiment of the disclosure, the lane line data can be updated according to the first vector point and the second vector point except the matching pair, the updating integrity of the lane line can be further improved, and the accuracy of the high-precision map is improved.
According to an embodiment of the present disclosure, updating the historical lane line data according to the other first vector points and the other second vector points may include: and determining the lane line data to be added according to other first vector points. In the history lane line data, data related to lane line data to be added is added. And determining the lane line data to be deleted according to other second vector points. And deleting data related to the lane line data to be deleted in the historical lane line data.
According to an embodiment of the present disclosure, the lane line change may include a new road, a lane line re-brushing, an extension, a reduction, and other change modes. These changing modes are all operations such as adding, modifying, deleting and the like at the lane line level. For all operations of adding, modifying, deleting and the like, the modes of adding, deleting and the like can be unified when the historical lane credit data is updated.
For example, in a case where a new lane line or the like is performed with respect to the historical lane line data, the collected lane line data may include the new lane line data, and the at least one first vector point determined according to the collected lane line data may include a first vector point representing the new lane line data. When the first vector point and the second vector point are matched, other first vector points that do not match the historical lane line data may appear. In this case, the other first vector points are newly added points with respect to each point in the history lane line data. Therefore, it is possible to determine the lane line data corresponding to the other first vector points as the lane line data to be added. In the process of updating the historical lane line data, the updating of the historical lane line data can be realized by adding the lane line data to be added.
For example, when an operation such as deleting a lane line is performed on the history lane line data, the collected lane line data does not include the deleted lane line data. When the first vector point and the second vector point are matched, other second vector points that do not match the acquired lane line data may appear. In this case, the other second vector points are redundant points with respect to the respective points in the acquired lane line data. Therefore, it is possible to determine the lane line data corresponding to the other second vector points as the lane line data to be deleted. In the process of updating the historical lane line data, the historical lane line data can be updated in a mode of deleting the lane line data to be deleted.
According to the embodiment of the disclosure, the modification operation performed on the historical lane line data may include at least one of adding a new lane line, deleting an existing lane line, and the like. For the corresponding modification mode, the implementation scheme corresponding to the adding operation and the deleting operation can be adopted to update the historical lane line data.
Through the embodiment of the disclosure, the updating operation for the lane line can be simplified into the operations of adding, deleting and the like for the historical lane line data, the scene complexity is simplified, and the updating efficiency is improved.
Fig. 3 schematically shows an overall flowchart of a high-precision map lane line updating method according to an embodiment of the present disclosure.
As shown in fig. 3, the method includes operations S301 to S312.
In operation S301, bounding box data is sampled to obtain at least one first vector point.
In operation S302, the road network data is sampled to obtain at least one second vector point.
In operation S303, a one-to-one matching is performed on the first vector point and the second vector point, and a distance d, a direction angle θ, and a normal distance d between the first vector point and the second vector point are calculated⊥And defining a first preset threshold value1A second preset threshold value2A third preset threshold value3And a fourth preset threshold value4。
In operation S304, it is judged that d is less than or equal to value2And θ is less than or equal to value3Whether or not both are true. If so, operations S305 or S306 to S308 are performed, and if not, operations S311 to S312 are performed.
In operation S305, d is judged⊥Whether greater than or equal to value4. If yes, executing operations S306-S308; if not, operation S310 is performed.
In operation S306, the first vector point and the second vector point are determined as a matching pair.
In operation S307, an evaluation value score corresponding to the matching pair is calculated.
In operation S308, it is determined whether score is greater than or equal to value1. If yes, perform operation S309; if not, operation S310 is performed.
In operation S309, the road network data is updated according to the first vector point.
In operation S310, it is determined that the first vector point and the second vector point are both invalid change points.
In operation S311, it is determined that the first vector point and the second vector point are both valid change points.
In operation S312, the lane line data associated with the first vector point is added to the road network data, and the lane line data associated with the second vector point in the road network data is deleted.
Through the embodiment of the disclosure, the evaluation value is calculated for the matching pair, and the effective change point can be further determined from the first vector point and the second vector point which are matched as the matching pair, so that the accuracy and the integrity of finding the effective change point are improved. The automatic updating operation is combined, the calling-in rate of automatic labeling is improved, the manual labeling investment can be effectively reduced, and the updating efficiency of the high-precision map is improved. In addition, the updating operation aiming at the lane line data is unified into an adding mode and a deleting mode, and the scene complexity is simplified.
Fig. 4 schematically shows a block diagram of a high-precision map lane line updating apparatus according to an embodiment of the present disclosure.
As shown in fig. 4, the high-precision map lane line updating apparatus 400 includes a first determining module 410, a calculating module 420, a second determining module 430, and a first updating module 440.
The first determining module 410 is configured to determine at least one matching pair satisfying a preset condition from at least one first vector point corresponding to the collected lane line data and at least one second vector point corresponding to the historical lane line data. Each matching pair includes a first vector point and a second vector point.
A calculating module 420 for calculating, for each matching pair, an evaluation value corresponding to the matching pair.
And a second determining module 430, configured to determine the target matching pair according to the evaluation value.
And a first updating module 440, configured to update the historical lane line data according to the first vector point in the target matching pair.
According to an embodiment of the present disclosure, a calculation module includes a first determination unit and a first calculation unit.
And the first determining unit is used for determining at least one of the distance, the distance variance and the direction included angle between the first vector point and the second vector point in the matched pair.
A first calculation unit for calculating an evaluation value corresponding to the matching pair based on at least one of the distance, the distance variance, and the direction angle.
According to an embodiment of the present disclosure, the first calculation unit includes a first determination subunit and a first calculation subunit.
A first determining subunit for determining a distance correlation coefficient, a distance variance correlation coefficient, and a direction included angle correlation coefficient, respectively, with respect to at least one of a distance, a distance variance, and a direction included angle.
And a first calculating subunit, configured to calculate an evaluation value corresponding to the matching pair according to at least one of the distance correlation coefficient, the distance variance correlation coefficient, and the direction angle correlation coefficient.
According to an embodiment of the present disclosure, the second determination module includes a second determination unit.
A second determining unit configured to determine a matching pair corresponding to the evaluation value as a target matching pair in a case where the evaluation value is greater than or equal to a first preset threshold value.
According to an embodiment of the present disclosure, the first determination module includes a second calculation unit and a third determination unit.
And the second calculating unit is used for respectively calculating the distance and the direction included angle between the first vector point and each second vector point aiming at each first vector point.
And the third determining unit is used for determining the matching pair meeting the preset condition according to the first vector point and the second vector point, wherein the distance is less than or equal to the second preset threshold value, and the direction included angle is less than or equal to the third preset threshold value.
According to an embodiment of the present disclosure, the third determination unit includes a second calculation subunit and a second determination subunit.
And the second calculating subunit is used for calculating the normal distance between the first vector point and the second vector point, wherein the distance is less than or equal to a second preset threshold value, and the direction included angle is less than or equal to a third preset threshold value.
And the second determining subunit is used for determining the first vector point and the second vector point of which the normal distance is greater than or equal to a fourth preset threshold value as a matching pair.
According to the embodiment of the disclosure, the high-precision map lane line updating device further comprises a third determining module, a fourth determining module, a fifth determining module and a second updating module.
A third determining module for determining at least one target first vector point and at least one target second vector point comprised in the at least one matching pair.
And the fourth determining module is used for determining other first vector points except the target first vector point from the at least one first vector point.
And the fifth determining module is used for determining other second vector points except the target second vector point from the at least one second vector point.
And the second updating module is used for updating the historical lane line data according to the other first vector points and the other second vector points.
According to an embodiment of the present disclosure, the second update module includes a fourth determination unit, an addition unit, a fifth determination unit, and a deletion unit.
And the fourth determining unit is used for determining the lane line data to be added according to other first vector points.
And the adding unit is used for adding data related to the lane line data to be added in the historical lane line data.
And the fifth determining unit is used for determining the lane line data to be deleted according to other second vector points.
And the deleting unit is used for deleting data related to the lane line data to be deleted in the historical lane line data.
The present disclosure also provides an electronic device, a readable storage medium, and a computer program product according to embodiments of the present disclosure.
According to an embodiment of the present disclosure, an electronic device includes: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the high precision map lane line updating method as described above.
According to an embodiment of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the high-precision map lane line updating method as described above.
According to an embodiment of the present disclosure, a computer program product comprising a computer program which, when executed by a processor, implements a high-precision map lane line updating method as described above.
FIG. 5 illustrates a schematic block diagram of an example electronic device 500 that can be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 5, the apparatus 500 comprises a computing unit 501 which may perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)502 or a computer program loaded from a storage unit 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the device 500 can also be stored. The calculation unit 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
A number of components in the device 500 are connected to the I/O interface 505, including: an input unit 506 such as a keyboard, a mouse, or the like; an output unit 507 such as various types of displays, speakers, and the like; a storage unit 508, such as a magnetic disk, optical disk, or the like; and a communication unit 509 such as a network card, modem, wireless communication transceiver, etc. The communication unit 509 allows the device 500 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 501 may be a variety of general-purpose and/or special-purpose processing components having processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The calculation unit 501 executes the respective methods and processes described above, such as the high-precision map lane line update method. For example, in some embodiments, the high-precision map lane line update method may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 508. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 500 via the ROM 502 and/or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the high-precision map lane line updating method described above may be performed. Alternatively, in other embodiments, the computing unit 501 may be configured to perform the high-precision map lane line update method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), Complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server with a combined blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made in accordance with design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (19)
1. A high-precision map lane line updating method comprises the following steps:
determining at least one matching pair meeting a preset condition from at least one first vector point corresponding to the acquired lane line data and at least one second vector point corresponding to the historical lane line data, wherein each matching pair comprises one first vector point and one second vector point;
calculating, for each of the matching pairs, an evaluation value corresponding to the matching pair;
determining a target matching pair according to the evaluation value; and
and updating the historical lane line data according to the first vector point in the target matching pair.
2. The method of claim 1, wherein the calculating the evaluation value corresponding to the matched pair comprises:
determining at least one of a distance, a distance variance and a direction included angle between a first vector point and a second vector point in the matched pair;
and calculating an evaluation value corresponding to the matching pair according to at least one of the distance, the distance variance and the direction included angle.
3. The method of claim 2, wherein said calculating an evaluation value corresponding to said matched pair based on at least one of said distance, distance variance and included direction angle comprises:
respectively determining a distance correlation coefficient, a distance variance correlation coefficient and a direction included angle correlation coefficient which are related to at least one of the distance, the distance variance and the direction included angle; and
and calculating an evaluation value corresponding to the matching pair according to at least one of the distance correlation coefficient, the distance variance correlation coefficient and the direction included angle correlation coefficient.
4. The method of claim 1, wherein the determining a target matching pair according to the evaluation value comprises:
determining a matching pair corresponding to the evaluation value as the target matching pair in a case where the evaluation value is greater than or equal to a first preset threshold value.
5. The method of claim 1, wherein the determining at least one matching pair that satisfies a preset condition from among at least one first vector point corresponding to the collected lane line data and at least one second vector point corresponding to the historical lane line data comprises:
respectively calculating the distance and the direction included angle between each first vector point and each second vector point aiming at each first vector point; and
and determining a matching pair meeting the preset condition according to the first vector point and the second vector point, wherein the distance is less than or equal to a second preset threshold value, and the direction included angle is less than or equal to a third preset threshold value.
6. The method according to claim 5, wherein the determining, according to the first vector point and the second vector point of which the distance is less than or equal to a second preset threshold and the direction included angle is less than or equal to a third preset threshold, the matching pair meeting the preset condition comprises:
calculating the normal distance between a first vector point and a second vector point, wherein the distance is less than or equal to a second preset threshold value, and the direction included angle is less than or equal to a third preset threshold value; and
and determining the first vector point and the second vector point of which the normal distance is greater than or equal to a fourth preset threshold value as the matching pair.
7. The method of any of claims 1 to 6, further comprising:
determining at least one target first vector point and at least one target second vector point included in the at least one matching pair;
determining other first vector points except the target first vector point from the at least one first vector point;
determining second vector points other than the target second vector point from the at least one second vector point; and
and updating the historical lane line data according to the other first vector points and the other second vector points.
8. The method of claim 7, the updating the historical lane line data based on the other first vector points and the other second vector points comprising:
determining lane line data to be added according to the other first vector points;
adding data related to the lane line data to be added in the historical lane line data;
determining lane line data to be deleted according to the other second vector points; and
and deleting data related to the lane line data to be deleted in the historical lane line data.
9. A high-precision map lane line updating device comprising:
the system comprises a first determining module, a second determining module and a judging module, wherein the first determining module is used for determining at least one matching pair meeting a preset condition from at least one first vector point corresponding to collected lane line data and at least one second vector point corresponding to historical lane line data, and each matching pair comprises one first vector point and one second vector point;
a calculation module configured to calculate, for each of the matching pairs, an evaluation value corresponding to the matching pair;
the second determining module is used for determining a target matching pair according to the evaluation value; and
and the first updating module is used for updating the historical lane line data according to the first vector point in the target matching pair.
10. The apparatus of claim 9, wherein the computing module comprises:
the first determining unit is used for determining at least one of the distance, the distance variance and the direction included angle between a first vector point and a second vector point in the matched pair;
and the first calculation unit is used for calculating the evaluation value corresponding to the matching pair according to at least one of the distance, the distance variance and the direction included angle.
11. The apparatus of claim 10, wherein the first computing unit comprises:
a first determining subunit, configured to determine a distance correlation coefficient, a distance variance correlation coefficient, and a direction included angle correlation coefficient, which are related to at least one of the distance, the distance variance, and the direction included angle, respectively; and
and the first calculating subunit is used for calculating the evaluation value corresponding to the matching pair according to at least one of the distance correlation coefficient, the distance variance correlation coefficient and the direction included angle correlation coefficient.
12. The apparatus of claim 9, wherein the second determining means comprises:
a second determination unit configured to determine a matching pair corresponding to the evaluation value as the target matching pair in a case where the evaluation value is greater than or equal to a first preset threshold value.
13. The apparatus of claim 9, wherein the first determining means comprises:
the second calculation unit is used for calculating the distance and the direction included angle between each first vector point and each second vector point respectively aiming at each first vector point; and
and the third determining unit is used for determining the matching pair meeting the preset condition according to the first vector point and the second vector point, wherein the distance is less than or equal to a second preset threshold value, and the direction included angle is less than or equal to a third preset threshold value.
14. The apparatus of claim 13, wherein the third determining unit comprises:
the second calculating subunit is used for calculating the normal distance between the first vector point and the second vector point, wherein the distance is smaller than or equal to a second preset threshold value, and the direction included angle is smaller than or equal to a third preset threshold value; and
and the second determining subunit is configured to determine the first vector point and the second vector point, of which the normal distance is greater than or equal to a fourth preset threshold, as the matching pair.
15. The apparatus of any of claims 9 to 14, further comprising:
a third determining module for determining at least one target first vector point and at least one target second vector point included in the at least one matching pair;
a fourth determining module, configured to determine, from the at least one first vector point, other first vector points except the target first vector point;
a fifth determining module, configured to determine, from the at least one second vector point, other second vector points except the target second vector point; and
and the second updating module is used for updating the historical lane line data according to the other first vector points and the other second vector points.
16. The apparatus of claim 15, the second update module comprising:
the fourth determining unit is used for determining lane line data to be added according to the other first vector points;
the increasing unit is used for increasing data related to the lane line data to be increased in the historical lane line data;
a fifth determining unit, configured to determine, according to the other second vector points, lane line data to be deleted; and
and the deleting unit is used for deleting data related to the lane line data to be deleted in the historical lane line data.
17. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
18. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.
19. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-8.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114581667A (en) * | 2022-03-04 | 2022-06-03 | 北京百度网讯科技有限公司 | Map data processing method and device, electronic equipment and storage medium |
| CN114677570A (en) * | 2022-03-14 | 2022-06-28 | 北京百度网讯科技有限公司 | Road information updating method, device, electronic equipment and storage medium |
| CN115223118A (en) * | 2022-06-09 | 2022-10-21 | 广东省智能网联汽车创新中心有限公司 | High-precision map confidence judgment method and system and vehicle |
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2021
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114581667A (en) * | 2022-03-04 | 2022-06-03 | 北京百度网讯科技有限公司 | Map data processing method and device, electronic equipment and storage medium |
| CN114677570A (en) * | 2022-03-14 | 2022-06-28 | 北京百度网讯科技有限公司 | Road information updating method, device, electronic equipment and storage medium |
| CN115223118A (en) * | 2022-06-09 | 2022-10-21 | 广东省智能网联汽车创新中心有限公司 | High-precision map confidence judgment method and system and vehicle |
| CN115223118B (en) * | 2022-06-09 | 2024-03-01 | 广东省智能网联汽车创新中心有限公司 | High-precision map confidence judging method, system and vehicle |
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