CN113886511B - High-precision map generation method, system, electronic device, computer equipment and storage medium - Google Patents

Abstract

The application relates to a method, a system, an electronic device, computer equipment and a storage medium for generating a high-precision map, wherein the method comprises the following steps: acquiring data of a road sealing area; matching the acquired road sealing area data with map original data; splitting the map original data according to the matching result; detecting the road sealing state of the lanes in each region after segmentation according to the matching result; and re-creating a topological relation for the lanes with the detection result of non-road sealing, and generating a high-precision map after the topological relation of all the non-road sealing lanes is created. By analyzing the road sealing area data, the area road of the road sealing area is segmented for each closed area, then the road sealing state of the internal lanes of the segmented area is detected, the non-road sealing lanes are re-established into the topological relation, and when all the non-road sealing lanes refresh the topological relation, a more accurate high-precision map for the road sealing area is generated, so that the closed lanes can be used more effectively, and the path planning efficiency is improved.

Description

High-precision map generation method, system, electronic device, computer equipment and storage medium

Technical field

This application relates to the field of autonomous driving technology, and in particular to high-precision map generation methods, systems, electronic devices, computer equipment and storage media.

Background technique

Automated horizontal transportation is one of the key components of the "green", "intelligent" and "unmanned" port. It has very strict requirements for the ability of self-driving bicycles, which means it needs to be completed under various weather and working conditions. 24/7 port operations. Automated horizontal transportation can solve the current problems of labor difficulty and high labor cost faced by the logistics industry. It can also further reduce accidents and improve the safety index.

In autonomous driving scenarios in ports, we often encounter situations where roads are occupied by containers, and intersections are occupied by gantry cranes in the yard. At this time, the occupied road needs to be closed, so that the map engine can avoid the closed road during path planning, so as to realize the function of avoiding the closed road during the operation of the self-driving vehicle.

To sum up, the existing technology of high-precision maps cannot achieve accurate road closure: for example, the middle part of a certain lane line is closed to traffic at both ends of the road. If the entire lane line is closed, the unsealed part of the road cannot be fully used. .

Contents of the invention

Embodiments of the present application provide a high-precision map generation method, system, electronic device, computer equipment, and storage medium to at least solve the problem in related technologies that the unsealed portion of the road cannot be fully used.

In the first aspect, embodiments of the present application provide a method for generating a high-precision map, which includes the following steps:

Get road closure area data;

Match the obtained road closure area data with the original map data;

Segment the original map data according to the matching results;

Based on the matching results, the road closure status of the lanes in each area after segmentation is detected;

Re-create topological relationships for lanes whose detection results are unsealed. When the topological relationships of all unsealed lanes are created, a high-precision map is generated.

In some embodiments, the method for generating a high-precision map further includes the following steps:

Divide the boundary difference of the road closure area into a list of points;

Match each point with the lane in the road closure area, record the index position of each matched lane, and record it as the matching lane index range.

In some embodiments, segmenting the original map data according to the matching results specifically includes the following steps:

The matching lane index range corresponding to all lanes in the statistical area road is sorted according to its index position;

Obtain several segmentation points based on the sorting information;

The roads in the area are divided according to the dividing points to obtain multiple continuous divided sub-regions.

In some embodiments, detecting the road closure status of lanes in each area after segmentation based on the matching results specifically includes the following steps:

The road closure status of each lane in the segmented sub-region is determined based on the matching lane index range of each lane and the segmentation position information of the road closure area data.

In some embodiments, the detection results are used to re-create topological relationships for unsealed lanes. After the topological relationships of all unsealed lanes are created, a high-precision map is generated, which specifically includes the following steps:

Obtain the road closure status information of all lanes in all sub-regions within the regional road;

If the lane in the divided sub-region is in a road-blocking state, no topological relationship is created between the lane and the lanes connected to it. Lanes create topological relationships;

When the topological relationships of all unsealed lanes are created, a high-precision map is generated.

In the second aspect, embodiments of the present application provide a high-precision map generation system, including an acquisition unit, a matching unit, a segmentation unit, a detection unit and a generation unit;

The acquisition unit is used to acquire road closure area data;

The matching unit is used to match the obtained road closure area data with the original map data;

The segmentation unit is used to segment the original map data according to the matching results;

The detection unit is used to detect the road closure status of the lanes in each area after segmentation based on the matching results;

The generating unit is used to re-create topological relationships for lanes whose detection results are unsealed, and generate high-precision maps after the topological relationships of all unsealed lanes are created.

In a third aspect, embodiments of the present application provide an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to perform the above-described first aspect. The method for generating high-precision maps described above.

In a fourth aspect, embodiments of the present application provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program Steps to implement the method for generating a high-precision map as described in the first aspect above.

In a fifth aspect, embodiments of the present application provide a storage medium on which a computer program is stored. When the program is executed by a processor, the method for generating a high-precision map as described in the first aspect is implemented.

Compared with related technologies, embodiments of the present application provide high-precision map generation methods, systems, electronic devices, computer equipment, and storage media to obtain road closure area data; and match the obtained road closure area data with the original map data. ; Segment the original map data according to the matching results; detect the road closure status of the lanes in each area after segmentation based on the matching results; re-create topological relationships for lanes whose detection results are unsealed. When all unsealed lanes After the topological relationship is created, a high-precision map is generated. By parsing the road closure area data, for each closed area, the regional roads in the road closure area are segmented, and then the road closure status of the internal lanes in the segmented area is detected, and the topological relationship of the unsealed lanes is re-created. When all After the topological relationship of the unsealed lanes is refreshed, a more accurate high-precision map of the closed roads can be generated, which can make the closed lanes more effective and improve the efficiency of path planning.

The details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more concise and understandable.

Description of the drawings

The drawings described here are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation of the present application. In the attached picture:

Figure 1 is a hardware structure block diagram of a terminal of a high-precision map generation method in the related art;

Figure 2 is a flow chart of the method for generating a high-precision map in this embodiment;

Figure 3 is a schematic diagram of regional roads of the high-precision map generation method in this embodiment;

Figure 4 is a schematic structural diagram of the high-precision map generation system in this embodiment.

Detailed ways

In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be described and illustrated below in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application. Based on the embodiments provided in this application, all other embodiments obtained by those of ordinary skill in the art without any creative work shall fall within the scope of protection of this application. In addition, it will also be appreciated that, although such development efforts may be complex and lengthy, the technology disclosed in this application will be readily apparent to those of ordinary skill in the art relevant to the disclosure of this application. Some design, manufacturing or production changes based on the content are only conventional technical means and should not be understood as insufficient content disclosed in this application.

Reference in this application to "an embodiment" means that a particular feature, structure or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearances of this phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by those of ordinary skill in the art that the embodiments described in this application may be combined with other embodiments without conflict.

Unless otherwise defined, the technical terms or scientific terms involved in this application shall have the usual meanings understood by those with ordinary skills in the technical field to which this application belongs. "A", "an", "a", "the" and other similar words used in this application do not indicate a quantitative limit and may indicate singular or plural numbers. The terms "include", "comprises", "having" and any variations thereof involved in this application are intended to cover non-exclusive inclusion; for example, a process, method, system, product or product that includes a series of steps or modules (units). The equipment is not limited to the listed steps or units, but may also include steps or units that are not listed, or may further include other steps or units inherent to these processes, methods, products or equipment. Words such as "connected", "connected", "coupled" and the like mentioned in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "plurality" mentioned in this application means greater than or equal to two. "And/or" describes the relationship between related objects, indicating that three relationships can exist. For example, "A and/or B" can mean: A alone exists, A and B exist simultaneously, and B exists alone. The terms “first”, “second”, “third”, etc. used in this application are only used to distinguish similar objects and do not represent a specific ordering of the objects.

The method embodiments provided in this embodiment can be executed in a terminal, computer, or similar computing device. Taking running on a terminal as an example, FIG. 1 is a hardware structure block diagram of a terminal for a high-precision map generation method according to an embodiment of the present invention. As shown in Figure 1, the terminal 10 may include one or more (only one is shown in Figure 1) processors 102 (the processor 102 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the above-mentioned terminal may also include a transmission device 106 and an input and output device 108 for communication functions. Persons of ordinary skill in the art can understand that the structure shown in Figure 1 is only illustrative, and it does not limit the structure of the above-mentioned terminal. For example, terminal 10 may also include more or fewer components than shown in FIG. 1 , or have a different configuration than shown in FIG. 1 .

The memory 104 can be used to store computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the high-precision map generation method in the embodiment of the present invention. The processor 102 runs the computer program stored in the memory 104, Thereby executing various functional applications and data processing, that is, realizing the above method. Memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 may further include memory located remotely relative to the processor 102, and these remote memories may be connected to the terminal 10 through a network. Examples of the above-mentioned networks include but are not limited to the Internet, intranets, local area networks, mobile communication networks and combinations thereof.

Transmission device 106 is used to receive or send data via a network. The above-mentioned specific examples of the network may include a wireless network provided by the communication provider of the terminal 10 . In one example, the transmission device 106 includes a network adapter (Network Interface Controller, NIC for short), which can be connected to other network devices through a base station to communicate with the Internet. In one example, the transmission device 106 may be a radio frequency (Radio Frequency, RF for short) module, which is used to communicate with the Internet wirelessly.

This embodiment provides a method for generating a high-precision map. Figure 2 is a flow chart of a method for generating a high-precision map according to an embodiment of the present application. As shown in Figure 2, the process includes the following steps:

S100: Obtain road closure area data;

The road closure area data is set in the cloud. At the same time, the road closure area data is forwarded to the map service through the cloud road closure service. The map service then responds to the path planning request of the external service and feeds back the path planning results based on the generated high-precision map.

S200: Match the obtained road closure area data with the original map data;

S300: Segment the original map data according to the matching results;

S400: Detect the road closure status of the lanes in each area after segmentation based on the matching results;

S500: Re-create topological relationships for lanes whose detection results are unsealed, and generate high-precision maps after the topological relationships of all unsealed lanes are created.

The above steps S300 to S500 are all operations on the same road closure area. If multiple road closure areas are generated by analysis, step S300 can be repeated for each road closure area.

Through the above steps S100 to S500, the road closure area data is obtained; the obtained road closure area data is matched with the original map data; the original map data is segmented according to the matching results; and each segmented area is detected based on the matching results. The road closure status of the inner lane; re-create the topological relationship for the lanes whose detection results are unsealed, and generate a high-precision map after the topological relationships of all unsealed lanes are created. By parsing the road closure area data, for each closed area, the regional roads in the road closure area are segmented, and then the road closure status of the internal lanes in the segmented area is detected, and the topological relationship of the unsealed lanes is re-created. When all After the topological relationship of the unsealed lanes is refreshed, a more accurate high-precision map of the closed roads can be generated, which can make the closed lanes more effective and improve the efficiency of path planning.

In addition to the above steps, the operation of a road closure area also includes the following steps:

S600: Divide the boundary difference of the road closure area into a list of points;

S700: Match each point with the lane in the road closure area, record the index position of each matched lane, and record it as the matching lane index range.

Among them, step S300: segment the original map data according to the matching results, specifically including the following steps:

S310: The matching lane index ranges corresponding to all lanes in the statistical area are sorted according to their index positions;

S320: Obtain several segmentation points based on the sorting information;

S330: Segment the roads in the area according to the segmentation points to obtain multiple continuous segmented sub-regions.

In this embodiment, in the process of the above-mentioned steps S310 to S330, the rules for sorting range sizes are not limited, because once the sorting rules are changed, the rules for obtaining several segmentation points based on the sorting information only need to be modified accordingly. Can.

Step S400: Detect the road closure status of the lanes in each segmented area based on the matching results, which specifically includes the following steps:

The road closure status of each lane in the segmented sub-region is determined based on the matching lane index range of each lane and the segmentation position information of the road closure area data.

In one embodiment, the road closure status of a range of lanes in the current segmented road is determined based on the road, the lanes subordinate to the road, the matching lane index range of the segmented lanes, and the segmentation location information in the road closure area data.

Step S500: Re-create topological relationships for lanes whose detection results are unsealed. After the topological relationships of all unsealed lanes are created, a high-precision map is generated, which specifically includes the following steps:

S510: Obtain the road closure status information of all lanes in all sub-regions within the regional road;

In one embodiment, based on step S400, step S510 mainly obtains the road closure status of each lane within the segmented sub-region.

S520: If the lane in the cut sub-area is in a road closure state, create a topological relationship between the lane and the lanes connected to it. The lanes of the road create topological relationships;

S530: Generate a high-precision map after the topological relationships of all unsealed lanes are created.

In addition to the above steps, the topological relationship between the first and last ends of the segmented road and adjacent roads needs to be transplanted from the original map data.

In step S530, several above-mentioned lane topology creation operations need to be completed repeatedly, because the road closure area data may sometimes be more than one, and each road closure area data contains n roads, and each road will include m lanes. For each road closure area data, Divide a road into i sub-areas. At this time, the number of road closure states determined for each lane increases i times compared with before the segmentation. Based on the detection and re-detection of the road closure status of each lane after segmentation, the road is divided into i sub-areas. For refreshing topological relationships for unsealed lanes, in this way, the lanes are segmented and then the road closure status is detected, which can more accurately detect the road closure location. At the same time, the road closure lanes are deleted (this does not mean deleting the data, it only does not delete the data). Create a topological relationship with the lanes connected before and after the lane), and only create a topological relationship with the unsealed lanes, which can generate a higher-precision high-precision map, which is more conducive to path planning.

For the matching, segmentation and creation of topological relationships of regional roads, explanations are now provided, as shown in Figure 3. In the figure, the horizontal solid lines are lane lines, the horizontal dotted lines are lane center lines, and the geometric figures of the solid lines in the road are seals. Road area, original steps S300~S500, specifically include the following steps:

For example, a regional road has three lanes, namely lane 0, lane 1, and lane 2;

(1) Divide the road closure area boundary difference obtained from the road closure area data into a list of points;

(2) Match each point with the original map data, record the index range of each matched lane, and record it as the matching lane index range. At this time, the range of matched lane 0 is (a, b), The range matching to lane 1 is (d, e), and the range matching to lane 2 is (c, e);

(3) Sort all matching index ranges in the order of points in the same extension direction of the lane, that is, a, b, c, d, e, and determine whether the sequence contains the starting point. If it does not, If the starting point is the starting point, add the starting point, and after deduplication, you will get a list of split points of 0, a, b, c, d, e, t; if the sequence contains a starting point, for example, when point a is the starting point, you will get 0 after deduplication. , b, c, d, e, t list of split points. The following steps are illustrated with a sequence that does not include a starting point;

(4) Segment the regional roads based on the obtained segmentation points, and obtain six consecutive segmented sub-regions A, B, C, D, E, and F;

(5) Detect the road closure status of the three lanes in each sub-area;

(6) The detection results of the road closure status information of all lanes in the six sub-areas are: the sub-area B of lane 0 is in a road closure state, the sub-area E of lane 1 is in a road closure state, and the sub-area E of lane 2 is in a road closure state. The D-cut sub-area of the lane is in a road closure state;

(7). At this time, the topological relationship for creating lane 0 is A, C->D->E->F, and the topological relationship for creating lane 1 is A->B->C->D, F. Create The topological relationship of Lane 2 is A->B->C, E->F. The topological relationship between the A-cut subregion and F-cut subregion of the above three lanes and the adjacent roads is directly transplanted from the corresponding area of the original map data. topological relationship.

It should be noted that the steps shown in the above process or the flow chart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical sequence is shown in the flow chart, in the In some cases, the steps shown or described may be performed in a different order than here.

This embodiment also provides a high-precision map generation system, which is used to implement the above embodiments and preferred implementations. What has already been explained will not be described again. As used below, the terms "module", "unit", "sub-unit", etc. may be a combination of software and/or hardware that implements a predetermined function. Although the systems described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.

Figure 4 is a structural block diagram of a high-precision map generation system according to an embodiment of the present application. As shown in Figure 4, a high-precision map generation system includes an acquisition unit 10, a matching unit 20, a segmentation unit 30, and a detection unit. 40 and generation unit 50;

The acquisition unit 10 is used to acquire road closure area data;

The matching unit 20 is used to match the obtained road closure area data with the original map data;

The segmentation unit 30 is used to segment the original map data according to the matching results;

The detection unit 40 is used to detect the road closure status of the lanes in each area after segmentation based on the matching results;

The generating unit 50 is used to re-create topological relationships for lanes whose detection results are unsealed, and generate a high-precision map after the topological relationships of all unsealed lanes are created.

The above-mentioned high-precision map generation system obtains road closure area data; matches the obtained road closure area data with the original map data; segments the original map data according to the matching results; and detects each segmented segment based on the matching results. The road closure status of the lanes in the area; re-create the topological relationship for the lanes whose detection results are unsealed, and generate a high-precision map after the topological relationships of all unsealed lanes are created. By parsing the road closure area data, for each closed area, the regional roads in the road closure area are segmented, and then the road closure status of the internal lanes in the segmented area is detected, and the topological relationship of the unsealed lanes is re-created. When all After the topological relationship of the unsealed lanes is refreshed, a more accurate high-precision map of the closed roads can be generated, which can make the closed lanes more effective and improve the efficiency of path planning.

This embodiment also provides an electronic device, including a memory and a processor. A computer program is stored in the memory, and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

Optionally, the above-mentioned electronic device may further include a transmission device and an input-output device, wherein the transmission device is connected to the above-mentioned processor, and the input-output device is connected to the above-mentioned processor.

Optionally, in this embodiment, the above-mentioned processor may be configured to perform the following steps through a computer program:

S100: Obtain road closure area data;

S200: Match the obtained road closure area data with the original map data;

S300: Segment the original map data according to the matching results;

S400: Detect the road closure status of the lanes in each area after segmentation based on the matching results;

S500: Re-create topological relationships for lanes whose detection results are unsealed, and generate high-precision maps after the topological relationships of all unsealed lanes are created.

It should be noted that for specific examples in this embodiment, reference may be made to the examples described in the above-mentioned embodiments and optional implementations, and the details of this embodiment will not be repeated here.

In one embodiment, a computer device is provided, which may be a terminal. The computer equipment includes a processor, memory, network interface, display screen and input device connected by a system bus. Wherein, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes non-volatile storage media and internal memory. The non-volatile storage medium stores operating systems and computer programs. This internal memory provides an environment for the execution of operating systems and computer programs in non-volatile storage media. The network interface of the computer device is used to communicate with external terminals through a network connection. When the computer program is executed by the processor, a method for generating a high-precision map is implemented. The display screen of the computer device may be a liquid crystal display or an electronic ink display. The input device of the computer device may be a touch layer covered on the display screen, or may be a button, trackball or touch pad provided on the computer device shell. , it can also be an external keyboard, trackpad or mouse, etc.

Those skilled in the art can understand that the above structures are only block diagrams of partial structures related to the solution of the present application, and do not constitute a limitation on the computer equipment to which the solution of the present application is applied. Specific computer equipment may include more than the above or Have fewer parts, or combine certain parts, or have different parts arrangements.

In addition, combined with the high-precision map generation method in the above embodiments, embodiments of the present application may provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by the processor, any one of the high-precision map generation methods in the above embodiments is implemented.

Those skilled in the art should understand that the technical features of the above-described embodiments can be combined in any way. To simplify the description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as these If there is no contradiction in the combination of technical features, they should be considered to be within the scope of this specification.

The above-mentioned embodiments only express several implementation modes of the present application, and their descriptions are relatively specific and detailed, but they should not be understood as limiting the scope of the invention patent. It should be noted that, for those of ordinary skill in the art, several modifications and improvements can be made without departing from the concept of the present application, and these all fall within the protection scope of the present application. Therefore, the scope of protection of this patent application should be determined by the appended claims.

Claims (5)

1. A method for generating high-precision maps, which is characterized by including the following steps: Get road closure area data; Match the obtained road closure area data with the original map data; Divide the boundary difference of the road closure area into a list of points; Match each point with the lane in the road closure area, record the index position of each matched lane, and record it as the matching lane index range; The matching lane index ranges corresponding to all lanes in the statistical area are sorted according to their index positions, and the sorting is arranged in the order of points in the same extension direction of the lane; Obtain several segmentation points based on the sorting information; Segment the roads in the area based on the segmentation points to obtain multiple consecutive segmented sub-regions; Determine the road closure status of each lane in the segmented sub-region based on the matching lane index range of each lane and the segmented location information of the road closure area data; Obtain the road closure status information of all lanes in all sub-regions within the regional road; If the lane in the divided sub-region is in a road-blocking state, no topological relationship is created between the lane and the lanes connected to it. Lanes create topological relationships; When the topological relationships of all unsealed lanes are created, a high-precision map is generated. 2. A high-precision map generation system, characterized by including an acquisition unit, a matching unit, a segmentation unit, a detection unit and a generation unit; The acquisition unit is used to acquire road closure area data; The matching unit is used to match the obtained road closure area data with the original map data; divide the road closure area boundary difference into a list of points; match each point with the lane in the road closure area, and record each matched The index position of the lane is recorded as the matching lane index range; The segmentation unit counts the matching lane index ranges corresponding to all lanes in the regional road, and sorts them according to their index positions. The sorting is arranged in the order of points in the same extension direction of the lane; several segmentation points are obtained according to the sorting information; based on The segmentation points segment the roads in the area to obtain multiple continuous segmented sub-regions; The detection unit is used to determine the road closure status of each lane in the segmented sub-region based on the matching lane index range of each lane and the segmentation position information of the road closure area data; The generation unit is used to obtain the road closure status information of all lanes in all sub-areas within the regional road; if the lane in the sub-area is in road closure, create a topological relationship for the lane that is not connected to the lanes before and after it; if If the lanes in the segmented sub-region are in an unsealed state, a topological relationship is created between the lane and the unsealed lanes connected to it before and after it. When the topological relationships of all unsealed lanes are created, a high-precision map is generated. 3. An electronic device, comprising a memory and a processor, characterized in that a computer program is stored in the memory, and the processor is configured to run the computer program to execute the high-precision map described in claim 1 generation method. 4. A computer device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that when the processor executes the computer program, the method described in claim 1 is implemented Steps of generating high-precision maps. 5. A computer-readable storage medium on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the method for generating a high-precision map described in claim 1 are implemented.