CN113743344A

CN113743344A - Road information determination method and device and electronic equipment

Info

Publication number: CN113743344A
Application number: CN202111064516.9A
Authority: CN
Inventors: 马桥
Original assignee: Beijing Elite Road Technology Co ltd
Current assignee: Beijing Elite Road Technology Co ltd
Priority date: 2021-09-10
Filing date: 2021-09-10
Publication date: 2021-12-03

Abstract

The invention provides a method and a device for determining road information and electronic equipment, and relates to the technical field of artificial intelligence such as image video processing, intelligent parking and unmanned driving. The specific implementation scheme is as follows: when the lane direction in the road to be detected is determined, the straight line segment detection can be firstly carried out on the image of the road to be detected, and a plurality of spatial blanking points in the image are determined according to the detected line segment; in view of the fact that the spatial blanking point with the highest confidence degree in the road image is usually the spatial blanking point in the lane direction of the road, the line segment corresponding to the target spatial blanking point with the highest confidence degree in the plurality of spatial blanking points can be subjected to straight line fitting, the lane direction of the road to be detected is determined according to the directions indicated by the plurality of target line segments obtained through straight line fitting, and the accuracy of the determined lane direction is improved.

Description

Road information determination method and device and electronic equipment

Technical Field

The present disclosure relates to the field of image processing technologies, and in particular, to a method and an apparatus for determining road information, and an electronic device, and in particular, to the technical fields of image video processing, smart parking, unmanned driving, and other artificial intelligence.

Background

Determining road information is crucial to the safe driving of the vehicle. At present, under certain scenes, road information is shielded, and the like, so that the road information cannot be accurately determined.

Therefore, how to accurately determine the road information in the road is a problem that needs to be solved by those skilled in the art.

Disclosure of Invention

The disclosure provides a method and a device for determining road information and electronic equipment, which can accurately determine the road information in a road and improve the accuracy of the determined road information.

According to a first aspect of the present disclosure, there is provided a method of determining road information, which may include:

the method comprises the steps of detecting straight line segments of an image of a road to be detected, and determining a plurality of spatial blanking points in the image according to the detected straight line segments.

And performing straight line fitting on the line segment corresponding to the spatial blanking point with the maximum confidence level to obtain a plurality of target line segments.

And determining the lane direction of the road to be detected according to the directions indicated by the target line segments.

According to a second aspect of the present disclosure, there is provided a method of determining road information, which may include:

And determining an area corresponding to the parking space in the road to be detected according to the target line segments and the detected line segments.

According to a third aspect of the present disclosure, there is provided a road information determination device that may include:

the detection unit is used for detecting straight line segments of the image of the road to be detected and determining a plurality of spatial blanking points in the image according to the detected straight line segments.

And the fitting unit is used for performing linear fitting on the line segment corresponding to the spatial blanking point with the maximum reliability to obtain a plurality of target line segments.

And the determining unit is used for determining the lane direction of the road to be detected according to the directions indicated by the target line segments.

According to a fourth aspect of the present disclosure, there is provided a road information determination device that may include:

And the determining unit is used for determining the area corresponding to the parking space in the road to be detected according to the target line segments and the detected line segments.

According to a fifth aspect of the present disclosure, there is provided an electronic apparatus, which may include:

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 determining road information of the first aspect; or, the at least one processor may be enabled to execute the method for determining road information according to the second aspect.

According to a sixth aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method for determining road information of the first aspect; alternatively, the computer instructions are for causing the computer to execute the method of determining road information according to the second aspect described above.

According to a seventh aspect of the present disclosure, there is provided a computer program product comprising: a computer program stored in a readable storage medium, from which at least one processor of an electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to execute the method of determining road information according to the first aspect; alternatively, the at least one processor executes the computer program to cause an electronic device to execute the determination method of road information according to the second aspect.

According to the technical scheme, the road information in the road can be accurately determined, and the accuracy of the determined road information is improved.

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 is a schematic flowchart of a road information determination method provided according to a first embodiment of the present disclosure;

fig. 2 is a schematic diagram of an image of a road to be detected according to an embodiment of the disclosure;

fig. 3 is a schematic diagram of a detection result obtained by performing a straight-line segment detection on an image according to an embodiment of the present disclosure;

fig. 4 is a schematic diagram of an image of another road to be detected according to the embodiment of the disclosure;

FIG. 5 is a schematic diagram of a target line segment provided by an embodiment of the present disclosure;

fig. 6 is a flowchart illustrating a road information determination method according to a second embodiment of the present disclosure;

fig. 7 is a flowchart illustrating a road information determination method according to a third embodiment of the present disclosure;

fig. 8 is a schematic view of an area corresponding to a parking space on a road to be detected according to an embodiment of the present disclosure;

FIG. 9 is a schematic diagram of an image of a road collected in a practical application scenario according to an embodiment of the present disclosure;

FIG. 10 is a schematic diagram of a lane-to-lane position detected in a practical application scenario according to an embodiment of the present disclosure;

fig. 11 is a flowchart illustrating a road information determination method according to a fourth embodiment of the present disclosure;

fig. 12 is a schematic structural diagram of a road information determination device provided according to a fifth embodiment of the present disclosure;

fig. 13 is a schematic structural diagram of a road information determination device provided according to a sixth embodiment of the present disclosure;

fig. 14 is a schematic block diagram of an electronic device provided by an embodiment of the 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 embodiments of the present disclosure, "at least one" means one or more, "a plurality" means two or more. "and/or" describes the access relationship of the associated object, meaning that there may be three relationships, e.g., A and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone, wherein A and B can be singular or plural. In the description of the text of the present disclosure, the character "/" generally indicates that the former and latter associated objects are in an "or" relationship. In addition, in the embodiments of the present disclosure, "first", "second", "third", "fourth", "fifth", and "sixth" are only used to distinguish the contents of different objects, and have no other special meaning.

The technical scheme provided by the embodiment of the disclosure can be applied to the scene of parking space line detection. The parking spaces in the road can be accurately determined by detecting the parking space lines so as to effectively manage the parking spaces in the road. The parking space refers to a rectangular area which is planned in a road and used for parking vehicles, and the parking space line refers to a line segment used for marking the edge of the parking space area. In general, a parking space line comprises a lateral parking space line and a parking space dividing line; the lateral position lines are position lines parallel to the lane direction in the position lines, and the position dividing lines are position lines perpendicular to the lane direction in the position lines.

When determining a parking space area in a road, it is necessary to rely on road information in the road, such as a lane direction or a vehicle line, and therefore, in order to effectively manage the parking space in the road, the road information in the road may be determined first. At present, under certain scenes, road information is shielded, and the like, so that the road information cannot be accurately determined.

When the road information is in a lane direction, in order to accurately determine the road information in the road, it is considered that the spatial blanking point with the highest confidence degree in the road image is usually the spatial blanking point in the lane direction of the road according to the priori knowledge, therefore, when the lane direction in the road to be detected is determined, the spatial blanking point with the highest confidence degree corresponding to the image of the road to be detected can be determined, the line segment corresponding to the target spatial blanking point with the highest confidence degree is subjected to straight line fitting, the lane direction of the road to be detected is determined according to the direction indicated by a plurality of target line segments obtained by fitting, so that the road information, namely the lane direction, can be accurately determined, and the accuracy of the determined road information is improved.

Based on the technical concept, the embodiments of the present disclosure provide a method for determining road information, and the method for determining road information provided by the present disclosure will be described in detail by specific embodiments. It is to be understood that the following detailed description may be combined with other embodiments, and that the same or similar concepts or processes may not be repeated in some embodiments.

Example one

Fig. 1 is a flowchart illustrating a road information determining method provided according to a first embodiment of the present disclosure, where the road information determining method may be performed by software and/or a hardware device, for example, the hardware device may be a terminal or a server. For example, referring to fig. 1, the method for determining the road information may include:

s101, carrying out straight line segment detection on the image of the road to be detected, and determining a plurality of spatial blanking points in the image according to the detected line segments.

For example, when acquiring an image of a road to be detected, the image of the road to be detected may be acquired by road side equipment, or the image of the road to be detected sent by other electronic equipment may also be received, and the setting may be specifically performed according to actual needs.

After the image of the road to be detected is acquired, the image of the road to be detected can be subjected to straight line segment detection by adopting an lsd straight line segment detection method, or the image of the road to be detected can be subjected to straight line segment detection by adopting other straight line segment detection methods, such as a hough transform straight line segment detection method, and the method can be specifically set according to actual needs. In view of the fact that the lsd straight-line segment detection method is high in detection speed, does not need parameter adjustment, has good scene adaptability, and can improve the accuracy of straight-line detection, for example, in the embodiment of the present disclosure, the lsd straight-line segment detection method can be adopted to perform straight-line segment detection on the image of the road to be detected.

The lsd straight line segment detection method generally calculates the gradient size and direction of all points in an image, then uses the points with small gradient direction change and adjacent points as a connected domain, judges whether the points need to be disconnected according to rules according to the rectangularity of each domain to form a plurality of domains with larger rectangularity, then improves and screens all generated domains, and reserves the domains meeting conditions, wherein the domains meeting the conditions are the final straight line detection result.

For example, please refer to fig. 2, where fig. 2 is a schematic diagram of an image of a road to be detected according to an embodiment of the present disclosure, and it can be seen that the image shown in fig. 2 includes the road to be detected, and the road to be detected includes a plurality of parking spaces, and since a vehicle is parked in a part of the parking spaces, a part of the parking space lines in the acquired image is blocked. After an image of a road to be detected is obtained, an lsd straight-line segment detection method may be adopted to perform straight-line segment detection on the image to obtain a detection result, for example, please refer to fig. 3, where fig. 3 is a schematic diagram of a detection result obtained by performing straight-line segment detection on an image according to an embodiment of the present disclosure, it can be seen that the straight-line segment detection result shown in fig. 3 includes a line segment detected from the image, and the line segments of the plurality of line segments are different in length.

After straight line segment detection is performed on an image of a road to be detected to obtain a corresponding detection result, considering that a spatial blanking point with the highest confidence degree in the road image is generally a spatial blanking point in a lane direction of the road according to prior knowledge, therefore, a plurality of spatial blanking points corresponding to the image can be further determined according to the detection result, so that the spatial blanking point with the highest confidence degree can be marked as a target spatial blanking point according to the confidence degree corresponding to each spatial blanking point, and a corresponding line segment is subjected to straight line fitting to determine the lane direction in the road to be detected, that is, the following S102 is performed:

s102, performing straight line fitting on the line segment corresponding to the target space blanking point with the maximum reliability to obtain a plurality of target line segments.

The line segment corresponding to the spatial blanking point can be understood as a line segment corresponding to all intersection points used for calculating the spatial blanking point. In general, the intersection points of the line segments may be clustered, the center of each cluster may be recorded as a spatial blanking point, and the line segments corresponding to the spatial blanking point may be understood as the line segments corresponding to all the intersection points included in the cluster to which the line segments belong.

For example, when a line segment corresponding to the target spatial blanking point with the highest confidence level is subjected to linear fitting, a linear fitting technique may be adopted to perform linear fitting on the line segment corresponding to the target spatial blanking point with the highest confidence level, and the obtained plurality of target line segments are a plurality of target line segments which are parallel to each other. For example, the plurality of target line segments may include lane lines and/or lane edge lines in addition to the lateral lane lines in the road to be detected, and may be specifically set according to actual needs.

After the target spatial blanking point with the maximum confidence coefficient is determined, considering that the spatial blanking point with the maximum confidence coefficient in the road image is usually the spatial blanking point in the lane direction of the road, in order to determine the lane direction in the road to be detected, a straight line fitting may be performed on a line segment corresponding to the target spatial blanking point with the maximum confidence coefficient, so that the lane direction in the road to be detected may be determined according to a plurality of target line segments obtained by the fitting, that is, the following S103 is performed:

s103, determining the lane direction of the road to be detected according to the directions indicated by the target line segments.

The direction indicated by the target line segment may be understood as an extending direction of the target line segment. For example, if the extending direction of the target line segment is the east-west direction, the direction indicated by the target line segment is the east-west direction; the extending direction of the target line segment is the north-south direction, and the direction indicated by the target line segment is the north-south direction.

For example, the lane direction may be an east-west direction or a north-south direction, and may be specifically set according to actual needs, and herein, the embodiment of the present disclosure is not specifically limited.

For example, as shown in fig. 4, it is assumed that fig. 4 is a schematic view of another image of a road to be detected provided by the embodiment of the present disclosure, and by adopting the technical scheme provided by the embodiment of the present disclosure, after the road to be detected described in fig. 4 is processed, three target line segments in the detected road can be obtained, for example, as shown in fig. 5, fig. 5 is a schematic view of a target line segment provided by the embodiment of the present disclosure, and in fig. 5, three line segments that are thicker and parallel to a green belt are determined as three target line segments, and it can be seen that directions indicated by the three target line segments are lane directions.

When the lane direction of the road to be detected is determined according to the directions indicated by the target line segments, the direction indicated by the target line segments can be directly determined as the lane direction of the road to be detected, in view of the fact that the target line segments are obtained by performing straight line fitting on the line segment corresponding to the target spatial blanking point with the maximum confidence coefficient, and the spatial blanking point with the maximum confidence coefficient in the road image is usually the spatial blanking point in the lane direction of the road.

It can be seen that, in the embodiment of the present disclosure, when determining the lane direction in the road to be detected, the straight line segment detection may be performed on the image of the road to be detected first, and a plurality of spatial blanking points in the image may be determined according to the detected line segment; in view of the fact that the spatial blanking point with the highest confidence degree in the road image is usually the spatial blanking point in the lane direction of the road, the line segment corresponding to the target spatial blanking point with the highest confidence degree in the plurality of spatial blanking points can be subjected to straight line fitting, the lane direction of the road to be detected is determined according to the directions indicated by the plurality of target line segments obtained through straight line fitting, and the accuracy of the determined lane direction is improved.

Based on the embodiment shown in fig. 1, it is known from a priori knowledge that the lengths of the lines corresponding to the lane line, the lateral vehicle-side line, the drive-side edge line, and the like are long, for example, when determining the plurality of spatial blanking points in the image according to the detection result in S101, in order to avoid processing the short-length line segments to reduce the data processing amount, a plurality of first line segments with the line length greater than a first threshold value may be determined from the detected line segments, and a plurality of spatial blanking points may be determined according to the plurality of first line segments, so that the plurality of spatial blanking points may be determined based on the long-length line segments in the detection result in a targeted manner, the data processing amount is reduced, and the data processing efficiency is improved. The value of the first threshold may be set according to actual needs, and the embodiment of the present disclosure does not further limit the value of the first threshold.

In order to facilitate understanding of how to determine the plurality of spatial blanking points according to the plurality of first line segments with the segment lengths larger than the first threshold value in the embodiment of the present disclosure, the following will be described in detail through an embodiment two shown in fig. 4.

Example two

Fig. 6 is a flowchart illustrating a road information determining method according to a second embodiment of the disclosure, where the road information determining method may be implemented by software and/or a hardware device, for example, the hardware device may be a terminal or a server. For example, referring to fig. 6, the method for determining the road information may include:

s601, respectively determining intersection points between any two first line segments in the plurality of first line segments, and clustering the obtained plurality of intersection points to obtain a plurality of first clusters; and the central point of each first cluster is an initial spatial blanking point.

It should be noted that, in the embodiment of the present disclosure, when determining an intersection point between any two first segments, if the lengths of any two first segments are sufficient to generate an intersection point, the generated intersection point may be determined as the intersection point between any two first segments; on the contrary, if the lengths of the any two first segments are not enough to generate the intersection point, the intersection point generated by the extension lines of the any two first segments may be determined as the intersection point between the any two first segments, and may be specifically set according to actual needs.

For example, when clustering the obtained multiple intersection points, clustering the multiple sites by using a DBSCAN clustering algorithm may be performed, or clustering the multiple sites by using another clustering algorithm, for example, a K-Means clustering algorithm or a mean shift clustering algorithm, which may be specifically set according to actual needs, and herein, the embodiment of the present disclosure is not limited specifically.

By clustering the obtained multiple intersection points, the multiple intersection points can be divided into different clusters to obtain multiple clusters, and in order to distinguish the clusters from subsequent segmentations, in the embodiment of the present disclosure, the cluster corresponding to the intersection point can be marked as a first cluster. Each cluster has a central point, and the central point of the cluster is marked as an initial spatial blanking point.

After the plurality of initial spatial blanking points are obtained in this way, in view of the fact that there may be an unreliable spatial blanking point in the plurality of initial spatial blanking points, the confidence degree corresponding to each initial spatial blanking point may be determined, so as to determine an reliable spatial blanking point from the plurality of initial spatial blanking points according to the confidence degree corresponding to each initial spatial blanking point, so as to participate in the determination of the subsequent lane direction, that is, to execute the following S602 and S603.

S602, determining the confidence corresponding to each initial spatial blanking point according to the number of the first line segments corresponding to each initial spatial blanking point and the average length of the line segments.

The average length of the line segment corresponding to the initial spatial blanking point can be understood as the average length between all the first line segments corresponding to the initial spatial blanking point.

For example, when the confidence corresponding to the initial spatial blanking point is determined according to the number of the first line segments corresponding to the initial spatial blanking point and the average length of the line segments, in a general case, the value of the confidence corresponding to the initial spatial blanking point is in a direct proportional relationship with the number of the first line segments corresponding to the initial spatial blanking point and the average length of the line segments, that is, the greater the number of the first line segments corresponding to the initial spatial blanking point, the longer the average length of the line segments, the greater the value of the corresponding confidence; conversely, the smaller the number of the first line segments corresponding to the initial spatial blanking point is, the shorter the average length of the line segments is, and the smaller the value of the corresponding confidence coefficient is.

After the confidence corresponding to each initial spatial blanking point is determined according to the number of the first line segments corresponding to each initial spatial blanking point and the average length of the line segments, the incredible spatial blanking points can be removed according to the confidence corresponding to each initial spatial blanking point, and a plurality of initial spatial blanking points with the confidence higher than a second threshold are determined as a plurality of spatial blanking points, so as to determine the credible spatial blanking points from the plurality of initial spatial blanking points, that is, the following S603 is executed:

and S603, determining a plurality of initial spatial blanking points with the confidence degrees larger than a second threshold value as a plurality of spatial blanking points.

The value of the second threshold may be set according to actual needs, and the embodiment of the present disclosure does not further limit the value of the second threshold.

In general, the higher the confidence corresponding to the spatial blanking point, the higher the confidence level thereof; conversely, the lower the confidence level of the spatial blanking point corresponds to, the lower the confidence level thereof is.

It can be seen that, in the embodiment of the present disclosure, when determining a plurality of spatial blanking points corresponding to an image according to a plurality of first segments, an intersection point between any two first segments may be determined, and a clustering process is performed on the obtained plurality of intersection points to obtain a plurality of first clusters, where a central point of each first cluster is an initial spatial blanking point; determining the confidence corresponding to each initial spatial blanking point according to the number of first line segments corresponding to each initial spatial blanking point and the average length of the line segments; and then according to the confidence corresponding to each initial spatial blanking point, removing the incredible spatial blanking points, and determining the plurality of initial spatial blanking points with the confidence higher than a second threshold value as the credible plurality of spatial blanking points, so that the lane direction can be determined based on the credible plurality of spatial blanking points subsequently, and the accuracy of the determined lane direction is improved.

Based on the embodiment shown in fig. 1 or fig. 6, after the lane direction in the road to be detected is determined, in order to further realize centralized management of roadside parking spaces in the road to be detected, an area corresponding to the roadside parking spaces in the road to be detected may be further determined based on a plurality of target line segments obtained by fitting, so that centralized management of the roadside parking spaces in the road to be detected may be performed based on the area corresponding to the determined parking spaces.

When determining the region corresponding to the roadside parking space in the road to be detected, in view of the fact that the line segment corresponding to the target space blanking point with the maximum confidence degree is subjected to straight line fitting, the lateral vehicle position line in the road to be detected, and possibly a lane line and/or a lane edge line are obtained from a plurality of target line segments, in order to determine the region corresponding to the roadside parking space in the road to be detected, the lateral vehicle position line in the road to be detected needs to be screened from the plurality of target line segments, and the corresponding parking space dividing line is fitted, so that the region corresponding to the roadside parking space in the road to be detected can be further determined according to the lateral vehicle position line in the road to be detected and the corresponding parking space dividing line.

As to how to screen the lateral parking space lines in the road to be detected from the multiple target line segments and fit the corresponding parking space dividing lines, the area corresponding to the roadside parking spaces in the road to be detected is determined according to the lateral parking space lines and the corresponding parking space dividing lines in the road to be detected, which will be described in detail through the following embodiment three shown in fig. 7.

EXAMPLE III

Fig. 7 is a flowchart illustrating a road information determining method according to a third embodiment of the disclosure, where the road information determining method may be implemented by software and/or a hardware device, for example, the hardware device may be a terminal or a server. For example, referring to fig. 7, the method for determining the road information may include:

s701, determining a plurality of second line segments intersected with the target line segment and a plurality of third line segments, wherein the intersection points of the extension lines and the target line segment are intersected, and the distance between the intersection points and the end points of the intersection points is smaller than a third threshold value, from the detected line segments; and determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segment.

For example, when the lateral parking space line in the road to be detected is screened from the plurality of target line segments and the corresponding parking space dividing lines are fitted, the plurality of dividing lines corresponding to each target line segment in the plurality of target line segments can be determined respectively. It can be understood that, when determining a plurality of target line segments and a plurality of dividing lines corresponding to each target line segment respectively, in view of the similarity of the determination methods of the plurality of dividing lines corresponding to each target line segment, for avoiding redundancy, how to determine a plurality of dividing lines corresponding to any one target line segment in the plurality of target line segments will be taken as an example, and how to determine a plurality of dividing lines corresponding to each target line segment in the plurality of target line segments in the embodiment of the present disclosure will be described.

For example, when determining a plurality of segmentation lines corresponding to any one of a plurality of target line segments, all line segments parallel to the lane direction, including line segments having a small included angle with the lane direction, may be removed from the plurality of line segments in the detection result, and line segments intersecting with the target line segments are determined from the remaining plurality of line segments, which may be recorded as a second line segment in the present disclosure, and a plurality of line segments in which extension lines of the line segments intersect with the target line segment and the distances between the intersection points and end points of the line segments are smaller than a third threshold, which may be recorded as a third line segment in the present disclosure; after a plurality of second line segments and a plurality of third line segments corresponding to the target line segment are determined; clustering the plurality of second line segments and the plurality of third line segments according to the respective positions and angles of the plurality of second line segments and the plurality of third line segments corresponding to the target line segment to obtain a plurality of second clusters; and respectively performing straight line fitting on the line segments in the second clustering to obtain a plurality of segmentation lines corresponding to the target line segment.

And a second cluster can be correspondingly fitted with a parting line. It is to be understood that only the second line segment or only the third line segment may be included in the second cluster, and that the second line segment and the third line segment may also be included in the second cluster, that is, the second line segment and/or the third line segment may be included in the second cluster. The value of the third threshold may be set according to actual needs, and the embodiment of the present disclosure is not further limited to the value of the third threshold.

By combining the above description, a plurality of dividing lines corresponding to each target line segment in the plurality of target line segments can be respectively determined; after determining the plurality of dividing lines corresponding to each target line segment, determining an area corresponding to a parking space in the road to be detected according to each target line segment and the plurality of corresponding dividing lines, namely executing the following step S702:

s702, determining an area corresponding to a parking space in the road to be detected according to the target line segment and the corresponding plurality of dividing lines.

For example, when determining an area corresponding to a parking space in a road to be detected according to each target line segment and a plurality of corresponding dividing lines, for each target line segment and the plurality of corresponding dividing lines, the confidence degrees corresponding to the target line segment and the plurality of corresponding dividing lines can be determined according to the target line segment and the plurality of corresponding dividing lines; determining a target line segment corresponding to the maximum confidence as a lateral parking space line in the road to be detected, and determining a plurality of parting lines corresponding to the maximum confidence as parking space parting lines in the road to be detected; after the lateral position line and the parking space dividing line are determined, the area corresponding to the parking space in the road to be detected can be determined according to the lateral position line and the parking space dividing line.

For example, when determining the confidence degrees corresponding to the target line segment and the corresponding multiple segmentation lines according to the target line segment and the corresponding multiple segmentation lines, a first confidence degree corresponding to the target line segment may be determined according to the segment length of the target line segment and the number of first line segments included in the target line segment; determining a second confidence corresponding to each segmentation line according to the line segment length of each segmentation line in the plurality of segmentation lines and the line segment number included by each segmentation line; and carrying out weighted average on the first confidence coefficient and the plurality of second confidence coefficients to obtain the confidence coefficients corresponding to the target line segment and the plurality of corresponding segmentation lines.

When a first confidence coefficient corresponding to a target line segment is determined according to the length of the target line segment and the number of first line segments included in the target line segment, under normal conditions, the value of the first confidence coefficient corresponding to the target line segment is in direct proportion to both the length of the target line segment and the number of the first line segments included in the target line segment, that is, the longer the length of the target line segment is, the more the number of the first line segments included in the target line segment is, the larger the value of the corresponding first confidence coefficient is; conversely, the shorter the segment length of the target segment is, the smaller the number of the first segments included in the target segment is, and the smaller the value of the corresponding first confidence coefficient is.

When a second confidence coefficient corresponding to the segmentation line is determined according to the line segment length of the segmentation line and the number of the line segments included in the segmentation line, under normal conditions, the value of the second confidence coefficient corresponding to the segmentation line is in direct proportion to both the line segment length of the segmentation line and the number of the line segments included in the segmentation line, namely, the longer the line segment length of the segmentation line is, the more the number of the line segments included in the segmentation line is, the larger the value of the corresponding second confidence coefficient is; conversely, the shorter the segment length of the segmentation line is, the smaller the number of segments included in the segmentation line is, and the smaller the value of the corresponding second confidence coefficient is.

For example, in combination with the image shown in fig. 4, a lateral position line and a parking space dividing line of the road to be detected in the image are determined, as shown in fig. 8, fig. 8 is a schematic diagram of an area corresponding to a parking space in the road to be detected provided by the embodiment of the disclosure, the area is thicker in fig. 8, a line segment parallel to the green belt is the determined lateral position line, nine line segments connected to the lateral position line and perpendicular to the lateral position line are the determined parking space dividing lines, and it can be seen that the areas corresponding to the eight parking spaces in the road to be detected can be accurately determined according to the lateral position line and the parking space dividing lines.

It can be seen that, in the embodiment of the present disclosure, when determining the area corresponding to the parking space in the road to be detected, a plurality of dividing lines corresponding to each target line segment in a plurality of target line segments may be determined first; and determining the area corresponding to the parking space in the road to be detected according to each target line segment and the corresponding plurality of dividing lines, so that the area corresponding to the parking space in the road to be detected can be accurately determined, and then carrying out centralized management on roadside parking spaces in the road to be detected based on the determined area corresponding to the parking space.

In an actual application process, for example, please refer to fig. 9, where fig. 9 is a schematic view of an image of a road collected in an actual application scene provided by the embodiment of the present disclosure, and by using the technical solution provided by the embodiment of the present disclosure, the image of the road shown in fig. 9 is processed, so that a lateral parking space line and a parking space dividing line of the road can be determined, a parking space line formed by the lateral parking space line and the parking space dividing line can be determined as shown in fig. 10, and fig. 10 is a schematic view of a parking space line in a road detected in an actual application scene provided by the embodiment of the present disclosure.

When the road information is an area corresponding to a parking space in the road, the area corresponding to the parking space may be determined, so that based on the determined area corresponding to the parking space, centralized management of roadside parking spaces in the road to be detected may be implemented, as shown in the following fourth embodiment shown in fig. 11.

Example four

Fig. 11 is a flowchart illustrating a road information determining method according to a fourth embodiment of the disclosure, where the road information determining method may be implemented by software and/or a hardware device, for example, the hardware device may be a terminal or a server. For example, referring to fig. 11, the method for determining the road information may include:

s1101, carrying out straight line segment detection on the image of the road to be detected, and determining a plurality of spatial blanking points in the image according to the detected straight line segments.

It should be noted that, in S1101, the straight-line segment detection is performed on the image of the road to be detected, and the implementation manner of the multiple spatial blanking points in the image is determined according to the detected line segment, which is similar to the implementation manner of the straight-line segment detection performed on the image of the road to be detected in S101 and the multiple spatial blanking points in the image is determined according to the detected line segment, reference may be made to the straight-line segment detection performed on the image of the road to be detected in S101, and the relevant description of the multiple spatial blanking points in the image is determined according to the detected line segment, which is not described herein again in this disclosure.

And S1102, performing straight line fitting on the line segment corresponding to the spatial blanking point with the maximum confidence level to obtain a plurality of target line segments.

It should be noted that, in S1102, a line segment corresponding to the spatial blanking point with the highest confidence level is subjected to straight line fitting to obtain an implementation manner of a plurality of target line segments, which is similar to the implementation manner of the line segment corresponding to the spatial blanking point with the highest confidence level in S102, and the implementation manner of the plurality of target line segments is obtained, reference may be made to the implementation manner of the line segment corresponding to the spatial blanking point with the highest confidence level in S102 to perform straight line fitting to obtain a description of the plurality of target line segments, and here, the embodiment of the present disclosure is not described in detail again.

S1103, determining an area corresponding to the parking space in the road to be detected according to the plurality of target line segments and the detected line segments.

It can be seen that, in the embodiment of the present disclosure, when determining the area corresponding to the parking space in the road to be detected, the straight line segment detection may be performed on the image of the road to be detected first, and a plurality of spatial blanking points in the image may be determined according to the detected straight line segment; performing linear fitting on the line segment corresponding to the spatial blanking point with the maximum reliability to obtain a plurality of target line segments; and then determining the area corresponding to the parking space in the road to be detected according to the plurality of target line segments and the detected line segments, so that the area corresponding to the parking space in the road can be accurately determined, and the accuracy of the determined area corresponding to the parking space is improved.

Based on the embodiment shown in fig. 11, in S1101, when determining a plurality of spatial blanking points in the image according to the detected line segments, similarly, in order to avoid processing the line segments with shorter lengths to reduce the data processing amount, a plurality of first line segments with length greater than a first threshold value may be determined from the detected line segments, and a plurality of spatial blanking points may be determined according to the plurality of first line segments, so that a plurality of spatial blanking points may be determined based on the line segments with longer lengths in the detection result in a targeted manner, thereby reducing the data processing amount, and improving the data processing efficiency. The value of the first threshold may be set according to actual needs, and the embodiment of the present disclosure does not further limit the value of the first threshold.

For example, when a plurality of spatial blanking points are determined according to a plurality of first segments, an intersection point between any two first segments in the plurality of first segments may be determined, and the obtained plurality of intersection points are clustered to obtain a plurality of first clusters; the central point of each first cluster is an initial spatial blanking point; determining the confidence corresponding to each initial spatial blanking point according to the number of first line segments corresponding to each initial spatial blanking point and the average length of the line segments; and then according to the confidence corresponding to each initial spatial blanking point, removing the incredible spatial blanking points, and determining the plurality of initial spatial blanking points with the confidence higher than a second threshold value as the credible plurality of spatial blanking points, so that the lane direction can be determined based on the credible plurality of spatial blanking points subsequently, and the accuracy of the determined lane direction is improved.

It should be noted that, in the embodiment of the present disclosure, an implementation manner of determining a plurality of spatial blanking points according to a plurality of first segments is similar to the implementation manner of determining a plurality of spatial blanking points according to a plurality of first segments in the embodiment shown in fig. 6, and reference may be made to related description of determining a plurality of spatial blanking points according to a plurality of first segments in the embodiment shown in fig. 6, and here, details of the embodiment of the present disclosure are not repeated.

Based on the embodiment shown in fig. 11, in the step S1103, when determining the area corresponding to the parking space in the road to be detected according to the plurality of target line segments and the detected line segments, for example, a plurality of second line segments intersecting with the target line segments and a plurality of third line segments, of which the extension lines intersect with the target line segments and the distances between the intersection points and the end points are smaller than the third threshold value, may be determined from the detected line segments; determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segment; and determining the area corresponding to the parking space in the road to be detected according to the target line segment and the corresponding plurality of dividing lines, so that the roadside parking space in the road to be detected is subjected to centralized management based on the determined area corresponding to the parking space.

For example, when determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segments, clustering the plurality of second line segments and the plurality of third line segments according to respective positions and angles of the plurality of second line segments and the plurality of third line segments to obtain a plurality of second clusters; and respectively performing straight line fitting on the line segments in the second clustering to obtain a plurality of segmentation lines corresponding to the target line segment.

It should be noted that, in the embodiment of the present disclosure, the implementation manner of the multiple dividing lines corresponding to the target line segment is determined according to the multiple second line segments and the multiple third line segments, which is similar to the implementation manner of determining the multiple dividing lines corresponding to the target line segment according to the multiple second line segments and the multiple third line segments in the above S701, reference may be made to the related description of determining the multiple dividing lines corresponding to the target line segment according to the multiple second line segments and the multiple third line segments in the above S701, and here, the embodiment of the present disclosure is not described again.

Based on any one of the above embodiments, it can be understood that, when roadside parking spaces in a road to be detected are centrally managed based on an area corresponding to the parking spaces determined by the above embodiments, a position relationship between a vehicle and the parking spaces in the road to be detected needs to be detected, and the roadside parking spaces in the road to be detected are centrally managed based on the position relationship.

For example, when determining the position relationship between the parking spaces and the parking spaces in the road to be detected, the intersection area and the union area of the area corresponding to the vehicle and the area corresponding to the parking spaces in the road to be detected may be determined respectively; and determining the position relation between the vehicle and the parking space according to the ratio of the intersection area to the union area. For example, if the ratio of the intersection area to the union area is greater than or equal to the set threshold, it indicates that the vehicle is in the parking space; on the contrary, if the ratio of the intersection area to the union area is smaller than the set threshold, it indicates that the vehicle is located outside the parking space, so as to perform centralized management on roadside parking spaces in the road to be detected. The value of the set threshold may be set according to actual needs, and the embodiment of the present disclosure is not particularly limited to the value of the set threshold.

In addition, in view of prior art, when carrying out parking stall line detection, usually based on high-order video equipment, roadside device gathers the image of waiting to detect the road promptly, and operating personnel marks the side direction parking stall line in each parking stall in the roadside parking monitored control system according to the image of waiting to detect the road, can mark as initial side direction parking stall line to judge that the vehicle gets into and leaves the parking stall based on the initial side direction parking stall line of this mark, thereby carry out centralized management to the parking stall. However, when the roadside apparatus is deviated from the preset position and angle, the previously marked initial lateral parking space line becomes an invalid lateral parking space line, and it is impossible to determine whether the vehicle enters or leaves the parking space based on the previously marked initial lateral parking space line, and thus it is impossible to manage the parking space. For example, the high-order video device may be installed in a same-side installation manner, may also be installed in a side-to-side installation manner, may also be installed in a vertical installation manner, and may be specifically set according to actual needs.

Therefore, in a general situation, before the parking spaces are managed in a centralized manner through the pre-marked initial parking space lines, the pre-marked initial lateral parking space lines can be checked, so that whether the position of the road side equipment is shifted or not can be determined through the checking result. For example, the pre-marked initial lateral position line may be verified based on the determined lateral position line in the road to be detected in the embodiment of the present disclosure, so as to determine whether the position of the roadside device is shifted according to the verification result.

For example, when the pre-marked initial lateral position line is verified by the lateral position line in the road to be detected determined according to the embodiment of the disclosure, so as to determine whether the position of the roadside device is shifted according to the verification result, the determined lateral position line in the road to be detected can be matched with the pre-marked initial lateral position line of the roadside device; and determining whether the position of the road side equipment is shifted or not according to the matching result. For example, if the lateral parking space line approximately coincides with the initial lateral parking space line, it is determined that the position of the roadside device is not shifted; if the lateral vehicle position line and the initial lateral vehicle position line are not approximately overlapped, the position of the road side equipment is determined to be shifted, whether the position of the road side equipment is shifted or not can be accurately determined, the situation that the parking space cannot be accurately managed due to the fact that the position of the road side equipment is shifted is avoided, and therefore the accuracy of managing the parking space is improved.

It can be understood that when the determined lateral position line in the road to be detected is matched with the initial lateral position line marked in advance by the roadside device, in an ideal state, an operator completely fits the actual lateral position line through the initial lateral position line marked in advance by the roadside device, and by the technical scheme provided by the embodiment of the disclosure, the determined lateral position line is also completely accurate, so that the initial lateral position line marked in advance by the roadside device can be completely overlapped with the lateral position line; however, in the actual operation process, it is difficult to ensure that the initial lateral position line marked in advance by the roadside device by the operator completely fits the actual lateral position line, and the determined lateral position line cannot be completely accurate through the technical scheme provided by the embodiment of the disclosure, so that a deviation range within a certain degree can be tolerated during matching, and if the matching result is within the deviation range, the initial lateral position line and the lateral position line are approximately coincident; on the contrary, if the matching result is not within the deviation range, it is understood that the initial lateral lane and the lateral lane do not approximately coincide with each other. The value of the deviation range may be set according to actual needs, and the embodiment of the present disclosure is not particularly limited to the value of the deviation range.

EXAMPLE five

Fig. 12 is a schematic structural diagram of a road information determining apparatus 120 according to a fifth embodiment of the disclosure, for example, please refer to fig. 12, the road information determining apparatus 120 may include:

the detecting unit 1201 is configured to perform straight-line segment detection on an image of a road to be detected, and determine a plurality of spatial blanking points in the image according to the detected straight-line segment.

The fitting unit 1202 is configured to perform linear fitting on the line segment corresponding to the spatial blanking point with the highest confidence level to obtain a plurality of target line segments.

A first determining unit 1203 is configured to determine a lane direction of the road to be detected according to the directions indicated by the plurality of target line segments.

Optionally, the detection unit 1201 includes a first detection module.

The first detection module is used for determining a plurality of spatial blanking points according to a plurality of first line segments of which the line segment lengths are larger than a first threshold value.

Optionally, the first detection module includes a first detection submodule, a second detection submodule, and a third detection submodule.

The first detection submodule is used for respectively determining an intersection point between any two first line segments in the plurality of first line segments and clustering the plurality of obtained intersection points to obtain a plurality of first clusters; and the central point of each first cluster is an initial spatial blanking point.

And the second detection submodule is used for determining the confidence corresponding to each initial spatial blanking point according to the number of the first line segments corresponding to each initial spatial blanking point and the average length of the line segments.

And the third detection submodule is used for determining a plurality of initial spatial blanking points with the confidence degrees larger than the second threshold value as a plurality of spatial blanking points.

Optionally, the determining device 120 of the road information further includes a second determining unit and a third determining unit.

A second determination unit configured to determine, from the detected line segments, a plurality of second line segments intersecting the target line segment, and a plurality of third line segments in which the extension line intersects the target line segment and the distance between the intersection point and the end point thereof is smaller than a third threshold; and determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segment.

And the third determining unit is used for determining the area corresponding to the parking space in the road to be detected according to the target line segment and the corresponding plurality of dividing lines.

Optionally, the second determining unit includes a first determining module and a second determining module.

And the first determining module is used for clustering the plurality of second line segments and the plurality of third line segments according to the respective positions and angles of the plurality of second line segments and the plurality of third line segments to obtain a plurality of second clusters.

And the second determining module is used for respectively performing straight line fitting on the line segments in the second clustering to obtain a plurality of dividing lines corresponding to the target line segment.

Optionally, the third determining unit includes a third determining module, a fourth determining module, and a fifth determining module.

And the third determining module is used for determining the confidence degrees corresponding to the target line segment and the corresponding multiple segmentation lines according to the target line segment and the corresponding multiple segmentation lines.

And the fourth determination module is used for determining the target line segment corresponding to the maximum confidence coefficient as a lateral parking space line in the road to be detected, and determining the plurality of division lines corresponding to the maximum confidence coefficient as parking space division lines in the road to be detected.

And the fifth determining module is used for determining the area corresponding to the parking space in the road to be detected according to the lateral parking space line and the parking space dividing line.

Optionally, the third determining module includes a first determining sub-module, a second determining sub-module, and a third determining sub-module.

And the first determining submodule is used for determining a first confidence corresponding to the target line segment according to the length of the target line segment and the number of the first line segments included in the target line segment.

And the second determining submodule is used for determining a second confidence coefficient corresponding to each partition line according to the line segment length of each partition line in the plurality of partition lines and the number of the second line segments and/or the third line segments included in each partition line.

And the third determining submodule is used for carrying out weighted average on the first confidence coefficient and the plurality of second confidence coefficients to obtain the confidence coefficients corresponding to the target line segment and the plurality of corresponding segmentation lines.

Optionally, the determining device 120 of road information further includes a fourth determining unit and a fifth determining unit.

And the fourth determining unit is used for respectively determining the areas corresponding to the vehicles in the road to be detected, and the intersection area and the union area of the areas corresponding to the parking spaces.

And the fifth determining unit is used for determining the position relation between the vehicle and the parking space according to the ratio of the intersection area to the union area.

Optionally, the determining device 120 of the road information further includes a matching unit and a sixth determining unit.

And the matching unit is used for matching the lateral position line with the initial lateral position line marked in advance by the road side equipment.

And a sixth determining unit, configured to determine whether the position of the roadside device is shifted according to the matching result.

Optionally, the sixth determining unit includes a sixth determining module and a seventh determining module.

And the sixth determining module is used for determining that the position of the road side equipment is not shifted if the lateral parking space line is approximately coincident with the initial lateral parking space line.

And the seventh determining module is used for determining that the position of the road side equipment is shifted if the lateral position line and the initial lateral position line are not approximately overlapped.

The road information determining apparatus 120 provided in the embodiment of the present disclosure may implement the technical solution of the road information determining method shown in the above embodiment, and its implementation principle and beneficial effect are similar to those of the road information determining method, and reference may be made to the implementation principle and beneficial effect of the road information determining method, which is not described herein again.

EXAMPLE six

Fig. 13 is a schematic structural diagram of a road information determining device 130 according to a sixth embodiment of the disclosure, for example, please refer to fig. 13, where the road information determining device 130 may include:

the detection unit 1301 is configured to perform straight line segment detection on an image of a road to be detected, and determine a plurality of spatial blanking points in the image according to the detected straight line segment.

The fitting unit 1302 is configured to perform linear fitting on the line segment corresponding to the spatial blanking point with the highest confidence level to obtain a plurality of target line segments.

The first determining unit 1303 is configured to determine, according to the multiple target line segments and the detected line segments, an area corresponding to a parking space in the road to be detected.

Optionally, the detection unit 1301 includes a first detection module.

Optionally, the first determining unit 1303 includes a first determining module and a second determining module.

The first determining module is used for determining a plurality of second line segments intersected with the target line segment and a plurality of third line segments, wherein the extension lines are intersected with the target line segment, and the distance between the intersection points and the end points of the intersection points is smaller than a third threshold value; and determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segment.

And the second determining module is used for determining the area corresponding to the parking space in the road to be detected according to the target line segment and the corresponding plurality of dividing lines.

Optionally, the first determining module includes a first determining submodule and a second determining submodule.

And the first determining submodule is used for clustering the plurality of second line segments and the plurality of third line segments according to the respective positions and angles of the plurality of second line segments and the plurality of third line segments to obtain a plurality of second clusters.

And the second determining submodule is used for respectively performing straight line fitting on the line segments in the second clustering to obtain a plurality of dividing lines corresponding to the target line segment.

Optionally, the second determining module includes a third determining submodule, a fourth determining submodule and a fifth determining submodule.

And the fourth determining module is used for determining the target line segment corresponding to the maximum confidence coefficient as a lateral parking space line in the road to be detected, and determining a plurality of dividing lines corresponding to the maximum confidence coefficient as parking space dividing lines in the road to be detected.

Optionally, the third determining module is specifically configured to determine a first confidence corresponding to the target line segment according to the length of the target line segment and the number of the first line segments included in the target line segment; determining a second confidence corresponding to each partition line according to the line segment length of each partition line in the plurality of partition lines and the number of second line segments and/or third line segments included in each partition line; and carrying out weighted average on the first confidence coefficient and the plurality of second confidence coefficients to obtain the confidence coefficients corresponding to the target line segment and the plurality of corresponding segmentation lines.

Optionally, the determining device 130 of road information further includes a second determining unit and a third determining unit.

And the second determining unit is used for respectively determining the areas corresponding to the vehicles in the road to be detected, and the intersection area and the union area of the areas corresponding to the parking spaces.

And the third determining unit is used for determining the position relation between the vehicle and the parking space according to the ratio of the intersection area to the union area.

Optionally, the determining device 130 of road information further includes a matching unit and a fourth determining unit.

And the fourth determination unit is used for determining whether the position of the road side equipment is shifted or not according to the matching result.

Optionally, the fourth determining unit includes a third determining module and a fourth determining module.

And the third determining module is used for determining that the position of the road side equipment is not shifted if the lateral parking space line is approximately coincident with the initial lateral parking space line.

And the fourth determination module is used for determining that the position of the road side equipment is shifted if the lateral position line and the initial lateral position line are not approximately overlapped.

The road information determining apparatus 130 provided in the embodiment of the present disclosure may implement the technical solution of the road information determining method shown in the above embodiment, and its implementation principle and beneficial effect are similar to those of the road information determining method, and reference may be made to the implementation principle and beneficial effect of the road information determining method, which is not described herein again.

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, the present disclosure also provides a computer program product comprising: a computer program, stored in a readable storage medium, from which at least one processor of the electronic device can read the computer program, the at least one processor executing the computer program causing the electronic device to perform the solution provided by any of the embodiments described above.

Fig. 14 is a schematic block diagram of an electronic device provided by an embodiment of the 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. 14, the device 140 includes a computing unit 1401 that can perform various appropriate actions and processes in accordance with a computer program stored in a Read Only Memory (ROM)1402 or a computer program loaded from a storage unit 1408 into a Random Access Memory (RAM) 1403. In the RAM1403, various programs and data necessary for the operation of the device 140 can also be stored. The calculation unit 1401, the ROM1402, and the RAM1403 are connected to each other via a bus 1404. An input/output (I/O) interface 1405 is also connected to bus 1404.

A number of components in the device 140 are connected to the I/O interface 1405, including: an input unit 1406 such as a keyboard, a mouse, or the like; an output unit 1407 such as various types of displays, speakers, and the like; a storage unit 1408 such as a magnetic disk, optical disk, or the like; and a communication unit 1409 such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 1409 allows the device 140 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

The computing unit 1401 may be a variety of general purpose and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 1401 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized 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 the like. The calculation unit 1401 executes the respective methods and processes described above, such as the determination method of road information. For example, in some embodiments, the determination of road information may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 1408. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 140 via the ROM1402 and/or the communication unit 1409. When a computer program is loaded into the RAM1403 and executed by the computing unit 1401, one or more steps of the determination method of road information described above may be performed. Alternatively, in other embodiments, the computing unit 1401 may be configured to perform the determination method of the road information 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), load 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 can be a cloud Server, 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 expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a 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

1. A method of determining road information, comprising:

carrying out straight line segment detection on an image of a road to be detected, and determining a plurality of spatial blanking points in the image according to the detected line segments;

performing linear fitting on the line segment corresponding to the spatial blanking point with the maximum reliability to obtain a plurality of target line segments;

2. The method of claim 1, wherein said determining a plurality of spatial blanking points in the image from the detected line segments comprises:

and determining the plurality of spatial blanking points according to a plurality of first line segments of which the line segment lengths are larger than a first threshold value in the detected line segments.

3. The method of claim 2, wherein determining the plurality of spatial blanking points from the plurality of first segments comprises:

respectively determining intersection points between any two first line segments in the plurality of first line segments, and clustering the obtained plurality of intersection points to obtain a plurality of first clusters; the central point of each first cluster is an initial spatial blanking point;

determining the confidence corresponding to each initial spatial blanking point according to the number of first line segments corresponding to each initial spatial blanking point and the average length of the line segments;

determining a plurality of initial spatial blanking points with confidence degrees greater than a second threshold as the plurality of spatial blanking points.

4. The method of any of claims 1-3, further comprising:

determining a plurality of second line segments intersecting the target line segment and a plurality of third line segments of which the distance between the intersection points and the end points of the intersection points is less than a third threshold from the detected line segments; determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segment;

and determining an area corresponding to the parking space in the road to be detected according to the target line segment and the corresponding plurality of dividing lines.

5. The method of claim 4, wherein said determining a plurality of split lines to which the target line segment corresponds based on the plurality of second line segments and the third line segment comprises:

clustering the plurality of second line segments and the plurality of third line segments according to the respective positions and angles of the plurality of second line segments and the plurality of third line segments to obtain a plurality of second clusters;

and respectively performing straight line fitting on the line segments in the second clustering to obtain the plurality of segmentation lines corresponding to the target line segment.

6. The method according to claim 4 or 5, wherein the determining, according to the target line segment and the corresponding plurality of dividing lines, the area corresponding to the parking space in the road to be detected comprises:

determining the confidence degrees corresponding to the target line segment and the corresponding multiple segmentation lines according to the target line segment and the corresponding multiple segmentation lines;

determining a target line segment corresponding to the maximum confidence as a lateral parking space line in the road to be detected, and determining a plurality of dividing lines corresponding to the maximum confidence as parking space dividing lines in the road to be detected;

and determining the area corresponding to the parking space in the road to be detected according to the lateral parking space line and the parking space dividing line.

7. The method of claim 6, wherein said determining a confidence level that the target line segment corresponds to the corresponding plurality of segmentation lines based on the target line segment and the corresponding plurality of segmentation lines comprises:

determining a first confidence corresponding to the target line segment according to the length of the target line segment and the number of first line segments included in the target line segment;

determining a second confidence corresponding to each segmentation line according to the line segment length of each segmentation line in the plurality of segmentation lines and the number of second line segments and/or third line segments included in each segmentation line;

and carrying out weighted average on the first confidence coefficient and the plurality of second confidence coefficients to obtain the confidence coefficients corresponding to the target line segment and the plurality of corresponding segmentation lines.

8. The method according to any one of claims 4-7, further comprising:

respectively determining an intersection area and a union area of areas corresponding to the vehicles in the road to be detected and the parking spaces;

and determining the position relation between the vehicle and the parking space according to the ratio of the intersection area to the union area.

9. The method of claim 6 or 7, further comprising:

matching the lateral position line with an initial lateral position line marked in advance by road side equipment;

and determining whether the position of the road side equipment is shifted or not according to the matching result.

10. The method of claim 9, wherein the determining whether the position of the roadside device is offset according to the matching result comprises:

if the lateral parking space line is approximately coincident with the initial lateral parking space line, determining that the position of the road side equipment is not shifted;

and if the lateral position line and the initial lateral position line are not approximately overlapped, determining that the position of the road side equipment is shifted.

11. A method of determining road information, comprising:

12. The method of claim 11, wherein said determining a plurality of spatial blanking points in the image from the detected line segments comprises:

13. The method of claim 12, wherein determining the plurality of spatial blanking points from the plurality of first segments comprises:

14. The method according to any one of claims 11 to 13, wherein the determining, from the plurality of target line segments and the detected line segment, an area corresponding to a parking space in the road to be detected comprises:

15. The method of claim 14, wherein said determining a plurality of split lines to which the target line segment corresponds based on the plurality of second line segments and the third line segment comprises:

16. The method according to claim 14 or 15, wherein the determining, according to the target line segment and the corresponding plurality of dividing lines, an area corresponding to a parking space in the road to be detected comprises:

17. The method of claim 16, wherein said determining a confidence level that the target line segment corresponds to the corresponding plurality of segmentation lines based on the target line segment and the corresponding plurality of segmentation lines comprises:

18. The method according to any one of claims 11-17, further comprising:

19. The method of claim 16 or 17, further comprising:

20. The method of claim 19, wherein the determining whether the position of the roadside device is offset according to the matching result comprises:

21. An apparatus for determining road information, comprising:

the detection unit is used for detecting straight line segments of an image of a road to be detected and determining a plurality of spatial blanking points in the image according to the detected straight line segments;

the fitting unit is used for performing linear fitting on the line segment corresponding to the spatial blanking point with the maximum reliability to obtain a plurality of target line segments;

and the first determining unit is used for determining the lane direction of the road to be detected according to the directions indicated by the target line segments.

22. The apparatus of claim 21, wherein the detection unit comprises a first detection module;

the first detection module is used for determining the plurality of spatial blanking points according to a plurality of first line segments of which the line segment lengths are larger than a first threshold value.

23. The apparatus of claim 22, wherein the first detection module comprises a first detection submodule, a second detection submodule, and a third detection submodule;

the first detection submodule is used for respectively determining an intersection point between any two first line segments in the plurality of first line segments and clustering the plurality of obtained intersection points to obtain a plurality of first clusters; the central point of each first cluster is an initial spatial blanking point;

the second detection submodule is used for determining the confidence corresponding to each initial spatial blanking point according to the number of the first line segments corresponding to each initial spatial blanking point and the average length of the line segments;

the third detection submodule is used for determining a plurality of initial spatial blanking points with confidence degrees larger than a second threshold value as the plurality of spatial blanking points.

24. The apparatus according to any of claims 21-23, further comprising a second determining unit and a third determining unit;

the second determining unit is used for determining a plurality of second line segments intersected with the target line segment and a plurality of third line segments, wherein the extended lines of the second line segments are intersected with the target line segment, and the distance between the intersection points and the end points of the third line segments is smaller than a third threshold value; determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segment;

25. The apparatus of claim 24, wherein the second determining means comprises a first determining module and a second determining module;

the first determining module is configured to perform clustering processing on the plurality of second line segments and the plurality of third line segments according to respective positions and angles of the plurality of second line segments and the plurality of third line segments to obtain a plurality of second clusters;

and the second determining module is used for respectively performing straight line fitting on the line segments in the second clustering to obtain the plurality of segmentation lines corresponding to the target line segment.

26. The apparatus of claim 24 or 25, wherein the third determining means comprises a third determining means, a fourth determining means, and a fifth determining means;

the third determining module is used for determining the confidence degrees corresponding to the target line segment and the corresponding multiple segmentation lines according to the target line segment and the corresponding multiple segmentation lines;

the fourth determining module is configured to determine a target line segment corresponding to the maximum confidence as a lateral parking space line in the road to be detected, and determine a plurality of dividing lines corresponding to the maximum confidence as parking space dividing lines in the road to be detected;

27. The apparatus of claim 26, wherein the third determination module comprises a first determination submodule, a second determination submodule, and a third determination submodule;

the first determining submodule is used for determining a first confidence corresponding to the target line segment according to the length of the target line segment and the number of first line segments included in the target line segment;

the second determining submodule is used for determining a second confidence corresponding to each segmentation line according to the line segment length of each segmentation line in the plurality of segmentation lines and the number of second line segments and/or third line segments included in each segmentation line;

28. The apparatus according to any of claims 24-27, further comprising a fourth determination unit and a fifth determination unit;

the fourth determining unit is used for respectively determining an area corresponding to a vehicle in the road to be detected, and an intersection area and a union area of the areas corresponding to the parking spaces;

the fifth determining unit is configured to determine a positional relationship between the vehicle and the parking space according to a ratio of the intersection area to the union area.

29. The apparatus according to claim 26 or 27, further comprising a matching unit and a sixth determining unit;

the matching unit is used for matching the lateral position line with an initial lateral position line marked in advance by road side equipment;

the sixth determining unit is configured to determine whether the position of the roadside apparatus is shifted according to the matching result.

30. The apparatus of claim 29, wherein the sixth determining means comprises a sixth determining means and a seventh determining means;

the sixth determining module is configured to determine that the position of the roadside device is not shifted if the lateral parking space line is approximately coincident with the initial lateral parking space line;

the seventh determining module is configured to determine that the position of the roadside device is shifted if the lateral lane line and the initial lateral lane line do not approximately coincide.

31. An apparatus for determining road information, comprising:

and the first determining unit is used for determining the area corresponding to the parking space in the road to be detected according to the plurality of target line segments and the detected line segments.

32. The apparatus of claim 31, wherein the detection unit comprises a first detection module;

33. The apparatus of claim 32, wherein the first detection module comprises a first detection submodule, a second detection submodule, and a third detection submodule;

34. The apparatus according to any of claims 31-33, wherein the first determining unit comprises a first determining module and a second determining module;

the first determining module is used for determining a plurality of second line segments intersected with the target line segment and a plurality of third line segments, wherein the extended lines of the second line segments are intersected with the target line segment, and the distance between the intersection points and the end points of the third line segments is smaller than a third threshold value; determining a plurality of dividing lines corresponding to the target line segment according to the plurality of second line segments and the third line segment;

35. The apparatus of claim 34, wherein the first determination module comprises a first determination submodule and a second determination submodule;

the first determining submodule is configured to perform clustering processing on the plurality of second line segments and the plurality of third line segments according to respective positions and angles of the plurality of second line segments and the plurality of third line segments to obtain a plurality of second clusters;

and the second determining submodule is used for respectively performing straight line fitting on the line segments in the second clustering to obtain the plurality of segmentation lines corresponding to the target line segment.

36. The apparatus of claim 34 or 35, wherein the second determination module comprises a third determination submodule, a fourth determination submodule, and a fifth determination submodule;

the third determining module is configured to determine confidence degrees corresponding to the target line segment and the corresponding multiple dividing lines according to the target line segment and the corresponding multiple dividing lines;

37. The apparatus of claim 36, wherein,

the third determining module is specifically configured to determine a first confidence corresponding to the target line segment according to the length of the target line segment and the number of first line segments included in the target line segment; determining a second confidence corresponding to each segmentation line according to the line segment length of each segmentation line in the plurality of segmentation lines and the number of second line segments and/or third line segments included in each segmentation line; and carrying out weighted average on the first confidence coefficient and the plurality of second confidence coefficients to obtain the confidence coefficients corresponding to the target line segment and the plurality of corresponding segmentation lines.

38. The apparatus according to any of claims 31-37, further comprising a second determining unit and a third determining unit;

the second determining unit is used for respectively determining an area corresponding to a vehicle in the road to be detected, and an intersection area and a union area of the areas corresponding to the parking spaces;

the third determining unit is configured to determine a positional relationship between the vehicle and the parking space according to a ratio of the intersection area to the union area.

39. The apparatus according to claim 36 or 37, further comprising a matching unit and a fourth determining unit;

the fourth determination unit is configured to determine whether the position of the roadside apparatus is shifted according to a matching result.

40. The apparatus of claim 39, wherein the fourth determination unit comprises a third determination module and a fourth determination module;

the third determining module is configured to determine that the position of the roadside device is not shifted if the lateral parking space line is approximately coincident with the initial lateral parking space line;

the fourth determining module is configured to determine that the position of the roadside device is shifted if the lateral lane line and the initial lateral lane line do not approximately coincide.

41. An electronic device, comprising:

at least one processor; and

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a method of determining road information as claimed in any one of claims 1 to 10; or to enable the at least one processor to perform the method of determining road information of any of claims 11-20.

42. A non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the determination method of road information according to any one of claims 1 to 10; alternatively, the computer instructions are for causing the computer to execute the determination method of road information according to any one of claims 11 to 20.

43. A computer program product comprising a computer program which, when being executed by a processor, carries out the steps of the method of determining road information according to any one of claims 1 to 10; alternatively, the computer program realizes the steps of the determination method of road information according to any one of claims 11 to 20 when executed by a processor.