Estimation Method, Device and Driverless Vehicle for Passable Areas in High-Definition Maps

Abstract

An embodiment of the present invention relates to the field of driverless technology, and discloses a method for estimating a passable area in a high-precision map, including: obtaining a high-precision map; determining the road on which the target vehicle is currently driving and the current position; extracting road data of the road from the high-precision map; according to the road data, and starting from the current position, searching for a passable area within a preset search range of the target vehicle on the road; along the traffic direction of the road, sequentially obtaining adjacent passable areas on the road from the searched passable areas; along the traffic direction of the road, sequentially merging the adjacent passable areas on the road. Through the above steps, the embodiment of the present invention can obtain a complete passable area, which is convenient for the driving of driverless vehicles.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of driverless technology, and in particular, to a method and device for estimating passable areas in a high-precision map and a driverless vehicle. Background Art

[0002] Path planning is an important part of driverless driving. Its purpose is to find one or more passable routes. When performing path planning, it is necessary to pre-give some road information of the current passable areas, so that the driverless vehicle knows which routes are passable in the path planning program, or predicts the driving routes of other vehicles.

[0003] The inventors of the embodiments of the present invention found in the process of implementing the embodiments of the present invention that the information of two passable areas is independently separated and there is no overall information, which is not conducive to the autonomous driving of the driverless vehicle. Summary of the Invention

[0004] The main technical problem to be solved by the embodiments of the present invention is to provide a method for estimating passable areas in a high-precision map, which can combine the independently separated passable areas.

[0005] To solve the above technical problem, a technical solution adopted by the embodiments of the present invention is: to provide a method for estimating passable areas in a high-precision map, including: obtaining a high-precision map; determining the road on which the target vehicle is currently driving and the current position; extracting the road data of the road from the high-precision map; according to the road data, and starting from the current position, searching for passable areas within a preset search range of the target vehicle on the road; along the traffic direction of the road, obtaining adjacent passable areas on the road from the searched passable areas; along the traffic direction of the road, merging the adjacent passable areas on the road.

[0006] Optionally, the adjacent passable areas include a first passable area and a second passable area. Along the traffic direction of the road, the second passable area is located in front of the first passable area.

[0007] Optionally, both the first passable area and the second passable area store their respective nodes in a linked list data structure. The steps of connecting the left endpoint of the ending boundary and the left endpoint of the starting boundary, and connecting the right endpoint of the ending boundary and the right endpoint of the starting boundary, and deleting the ending boundary and the starting boundary specifically include: according to the characteristics of the linked list data structure, obtaining the connection order of the left endpoint of the ending boundary and the left endpoint of the starting boundary, and the connection order of the right endpoint of the ending boundary and the right endpoint of the starting boundary; connecting an edge from the left endpoint of the starting boundary to the left endpoint of the ending boundary, and deleting the ending boundary; connecting an edge from the right endpoint of the ending boundary to the right endpoint of the starting boundary, and deleting the starting boundary.

[0008] Optionally, when there are multiple driving directions in the first passable area, there are multiple ending boundaries in the first passable area, and the number of second passable areas is multiple; connecting the left endpoint of the ending boundary and the left endpoint of the starting boundary; connecting the left endpoint of the ending boundary and the left endpoints of the starting boundaries of each second passable area, and connecting the right endpoint of the ending boundary and the right endpoints of the starting boundaries of each second passable area.

[0009] Optionally, the ending boundary of the first passable area and the starting boundary of the second passable area are in the same driving direction.

[0010] Optionally, starting from the current position, along the driving direction of the road, sequentially determine whether the distance between two adjacent passable areas obtained by search is greater than a preset threshold; if so, determine that the two adjacent passable areas are adjacent passable areas.

[0011] To solve the above technical problems, another technical solution adopted in the embodiments of the present invention is: to provide a device for dynamically loading passable areas, including: a first acquisition module for acquiring a high-precision map; a determination module for determining the road on which the target vehicle is currently driving and the current position; an extraction module for extracting road data of the road from the high-precision map; a search module for searching for passable areas within a preset search range of the target vehicle on the road according to the road data and starting from the current position; a second acquisition module for obtaining adjacent passable areas on the road from the passable areas obtained by search along the driving direction of the road; a fitting module for merging the adjacent passable areas on the road along the driving direction of the road.

[0012] Optionally, the adjacent passable areas include a first passable area and a second passable area. Along the traffic direction of the road, the second passable area is located in front of the first passable area. The fitting module is specifically configured to determine the ending boundary of the first passable area and the starting boundary of the second passable area in the adjacent passable areas, connect the left endpoint of the ending boundary and the left endpoint of the starting boundary, connect the right endpoint of the ending boundary and the right endpoint of the starting boundary, and delete the ending boundary and the starting boundary.

[0013] Optionally, when there are multiple traffic directions in the first passable area, there are multiple ending boundaries of the first passable area and multiple second passable areas. The steps for the fitting module to specifically connect the left endpoint of the ending boundary and the left endpoint of the starting boundary, and connect the right endpoint of the ending boundary and the right endpoint of the starting boundary further include: connecting the left endpoint of the ending boundary and the left endpoints of the starting boundaries of the second passable areas, and connecting the right endpoint of the ending boundary and the right endpoints of the starting boundaries of the second passable areas.

[0014] Optionally, a driverless vehicle includes: at least one processor; and a memory communicatively connected to the at least one processor. The memory stores instructions executable by the at least one processor, and when the instructions are executed by the at least one processor, the at least one processor is enabled to execute the method as described in any one of the above.

[0015] Optionally, a computer-readable storage medium includes: a computer-readable storage medium storing computer-executable instructions for causing a computer to execute the method as described in any one of the above.

[0016] The beneficial effects of the embodiments of the present invention are as follows: Different from the prior art, the embodiments of the present invention obtain a high-precision map, determine the road and the current position where the target vehicle is currently driving in the map, extract the road data of the road from the high-precision map, and then, based on the road data and starting from the current position, search for the passable areas within the preset search range of the target vehicle on the road. Then, along the traffic direction of the road, obtain the adjacent passable areas on the road from the searched passable areas, and finally, along the traffic direction of the road, merge the adjacent passable areas on the road to obtain a complete passable area, which facilitates the driving of the driverless vehicle. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] To more clearly illustrate the technical solutions in the specific embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the specific embodiments or the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0018] Figure 1 is a schematic diagram of the application environment for dynamically loading passable areas in an embodiment of the present invention;

[0019] Figure 2 is a flowchart of a method for estimating passable areas in a high-precision map in an embodiment of the present invention;

[0020] Figure 3 is another flowchart of step S105 of the method for estimating passable areas in a high-precision map in an embodiment of the present invention;

[0021] Figure 4 is a schematic diagram of the environment for estimating passable areas in a high-precision map in an embodiment of the present invention;

[0022] Figure 5 is a schematic diagram of three independent adjacent passable areas in an embodiment of the present invention;

[0023] Figure 6 is a further flowchart of the step of merging adjacent passable areas in the method for estimating passable areas in a high-precision map in an embodiment of the present invention;

[0024] Figure 7 is a further flowchart of step S1062 in the method for estimating passable areas in a high-precision map in an embodiment of the present invention;

[0025] Figure 8 is another schematic diagram of three independent adjacent passable areas in an embodiment of the present invention;

[0026] Figure 9 is a block diagram of the device for estimating passable areas in a high-precision map in an embodiment of the present invention;

[0027] Figure 10 is a schematic diagram of the hardware structure of the controller of a driverless vehicle in an embodiment of the present invention; Specific Embodiment

[0028] For the convenience of understanding the present invention, the present invention will be described in more detail below with reference to the accompanying drawings and specific embodiments. It should be noted that when an element is expressed as "fixed to" another element, it can be directly on the other element, or there can be one or more intermediate elements therebetween. When an element is expressed as "connected to" another element, it can be directly connected to the other element, or there can be one or more intermediate elements therebetween. The orientation or positional relationship indicated by the terms "upper", "lower", "inner", "outer", "vertical", "horizontal", etc. used in this specification is based on the orientation or positional relationship shown in the accompanying drawings, and is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, the terms "first", "second", etc. are only used for descriptive purposes and cannot be construed as indicating or implying relative importance.

[0029] Unless otherwise defined, all technical and scientific terms used in this specification have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs. The terms used in the description of the present invention are only for the purpose of describing specific embodiments and are not used to limit the present invention. The term "and / or" used in this specification includes any and all combinations of one or more of the related listed items.

[0030] In addition, the technical features involved in different embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0031] Please refer to Figure 1 , Figure 1 which is the structure of an embodiment of the driverless vehicle 1 of the present invention. The driverless vehicle 1 includes a vehicle body 10, a controller 20, a driving component 30, and a detection component 40. The driving component 30 is installed on the vehicle body 10, and the driving component 30 is used to drive the vehicle body to move. The controller 20 is installed on the vehicle body 10, and the controller 20 is connected to the driving component 30. The controller 20 is used to control the driving component 30. The detection component 40 is installed on the vehicle body 10, and the detection component 40 is connected to the controller 20. The detection component 40 is used to detect the environmental information around the driverless vehicle 1, and then drive according to the environmental information in combination with the high-precision map. Among them, the detection component 40 can be a camera, a radar, or a combination of a camera and a radar. The driverless vehicle captures the environmental images around the vehicle body through the camera and identifies the environmental information according to the environmental images, or detects the environmental information through the radar. The high-precision map is a map of the roads in the area where the driverless vehicle travels that has been pre-detected.

[0032] Please refer to Figure 2, an embodiment of the present invention provides a method for estimating a passable area in a high-precision map, which is applied to the above-mentioned driverless vehicle. The method includes:

[0033] Step S101: Obtain a high-precision map;

[0034] The high-precision map is a pre-collected map, which includes road data. The road data includes road names, traffic directions, positions of roads, geographical locations (longitude and latitude) of discrete points on the road lines that make up the road, and so on. The high-precision map can be collected by a third-party company and directly loaded by the driverless vehicle from the database of the third-party company. Or, the high-precision map can also be constructed by the company developing the driverless vehicle after collecting road data through a specific map construction tool.

[0035] Furthermore, in order to facilitate the driving of the driverless vehicle, several passable areas (also known as convex hulls) for the driverless vehicle to drive freely are constructed in the high-precision map according to the road data, and the driverless vehicle can drive in the passable areas.

[0036] Step S102: Determine the road on which the target vehicle is currently driving and the current position;

[0037] The current position is the geographical location where the target vehicle is currently located. According to this geographical location, the road where the target vehicle is located can be identified.

[0038] Step S103: Extract the road data of the road from the high-precision map;

[0039] Among them, the road data includes road names, traffic directions, positions of roads, geographical locations (longitude and latitude) of discrete points on the road lines that make up the road, and so on.

[0040] Step S104: According to the road data, and starting from the current position, search for the passable areas in the road within the preset search range of the target vehicle;

[0041] The preset search range is a predefined range, which can be set according to the actual situation. This range should not be too large or too small. If it is too large, the amount of data that the target vehicle needs to process will be too large, which will affect the normal driving of the target vehicle. If it is too small, the target vehicle will frequently merge passable areas.

[0042] In some embodiments, since the roads in the high-precision map often intersect, and the target vehicle has a destination when driving, and the target vehicle plans a driving route based on the destination and in combination with the high-precision map, the main way to search for the passable areas within the preset search range of the target vehicle on the road is as follows: According to the driving direction of the target vehicle, search for the passable areas in front of the target vehicle and within the driving route and the preset search range, and only process the passable areas on the driving route, which is beneficial to reducing the processed data and improving the processing efficiency.

[0043] Of course, in some other embodiments, the preset search range can be a range enclosed by a preset radius centered on the target vehicle for searching. In this way, the passable areas obtained by the search will include the passable areas around the target vehicle, and the amount of data processing will increase.

[0044] Step S105: Along the traffic direction of the road, sequentially obtain the adjacent passable areas on the road from the passable areas obtained by the search;

[0045] The traffic direction of the road refers to the driving direction allowed by the road. Only one traffic direction is allowed on the same road. Of course, the same highway can include two roads, and the traffic directions of the two roads are opposite. The two roads on the same highway can be distinguished by solid lines or by a median strip. And the same road can include multiple lanes.

[0046] Adjacent passable areas refer to two adjacent passable areas along the traffic direction of the road. For the convenience of description, the following two adjacent passable areas are represented by the first passable area and the second passable area. Along the traffic direction of the road, the second passable area is in front of the first passable area. In some embodiments, it can also be defined that the minimum distance between two adjacent passable areas needs to meet a predetermined distance to be determined as two adjacent passable areas.

[0047] Please refer to Figure 3 , step S105 further includes:

[0048] Step S1051: Starting from the current position, along the driving direction of the road, sequentially determine whether the distance between two adjacent passable areas obtained by the search is greater than a preset threshold;

[0049] Step S1052: If so, determine the two adjacent passable areas as adjacent passable areas.

[0050] The preset threshold is a predefined value, and the specific value of this value can be set according to the actual situation.

[0051] Step S106: Merge the adjacent passable areas in the road in sequence along the traffic direction of the road.

[0052] Merging the adjacent passable areas in the road in sequence means: along the traffic direction of the road, merging two adjacent passable areas one by one. For example, as Figure 4 shown, along the traffic direction of the road, there are a first passable area 60, a second passable area 70, and a third passable area 80 on the road where the target vehicle is located. The first passable area 60, the second passable area 70, and the third passable area 80 are separated and independent in the high-precision map. The first passable area 60 and the second passable area 70 are adjacent, and the second passable area 70 and the third passable area 80 are adjacent. First, merge the first passable area 60 and the second passable area 70, and then merge the second passable area 70 and the third passable area 80. The first passable area 60, the second passable area 70, and the third passable area 80 are merged into a large passable area, as Figure 5 shown.

[0053] It should be noted that: after merging the adjacent passable areas in the road in sequence to obtain a new passable area, the new passable area can be updated to the high-precision map so that when the target vehicle travels on this road again, it can directly travel according to the new passable area.

[0054] In some embodiments, as Figure 6 shown, the step of merging the adjacent passable areas in the road further includes:

[0055] Step S1061: Determine the ending boundary of the first passable area and the starting boundary of the second passable area among the adjacent passable areas;

[0056] The ending boundary is the boundary of the first passable area along the traffic direction of the road and opposite to the second passable area, and the starting boundary is the boundary of the second passable area along the traffic direction of the road and opposite to the first passable area.

[0057] Step S1062: Connect the left endpoint of the ending boundary and the left endpoint of the starting boundary, and connect the right endpoint of the ending boundary and the right endpoint of the starting boundary, and delete the ending boundary and the starting boundary.

[0058] The left endpoint of the ending boundary is the leftmost boundary of the first passable area along the road traffic direction, and the right endpoint of the ending boundary is the rightmost of the first passable area along the road traffic direction. The left endpoint of the starting boundary is the leftmost of the second passable area along the road traffic direction relative to the first passable area, and the left endpoint of the starting boundary is the rightmost of the second passable area. Deleting the ending boundary and the starting boundary refers to the original boundaries that are irrelevant in the passable area adjacent to the current target.

[0059] In some embodiments, when there are fork roads in the road, that is, when there are multiple second passable areas adjacent to the first passable area, the first passable area can be merged with the multiple second passable areas simultaneously, and both the first passable area and the second passable area store their respective nodes in a linked list data structure. Please refer to Figure 7 , the step S1062 further includes:

[0060] Step S10621: According to the characteristics of the linked list data structure, obtain the connection order of the left endpoints of the ending boundary and the starting boundary, and the connection order of the right endpoints of the ending boundary and the starting boundary;

[0061] Step S10622: Connect an edge from the left endpoint of the starting boundary to the left endpoint of the ending boundary, and delete the ending boundary;

[0062] Step S10623: Connect an edge from the right endpoint of the ending boundary to the right endpoint of the starting boundary, and delete the starting boundary.

[0063] As Figure 8 shown, there are two second passable areas, namely B1 and B2 respectively. The first passable area is A, and A is adjacent to both B1 and B2. B1 and B2 are fork roads, and after B1 and B2 fork and then merge, B1 merges with A, and B2 merges with A.

[0064] It should be noted that: the first passable area and the second passable area can be one-way passable areas or multi-directional passable areas. When the first passable area and the second passable area are multi-directional passable areas, during merging, the ending boundary of the first passable area and the starting boundary of the second passable area are in the same passing direction. Among them, the data linked list structure is a non-continuous and non-sequential storage structure on physical storage units in a computer. The logical order of its respective nodes on the first passable area and the second passable area is realized through the pointer linking order in the linked list. The linked list consists of a series of nodes (each element in the linked list is called a node), and the nodes can be dynamically generated during runtime. Each node includes two parts: one is the data field for storing data elements, and the other is the pointer field for storing the address of the next node. The beneficial effects of the embodiments of the present invention are: different from the prior art, the embodiments of the present invention obtain a high-precision map, determine the road and the current position where the target vehicle is currently driving in the map, extract the road data of the road from the high-precision map, and then according to the road data, with the current position as the starting point, search for the passable areas in the preset search range of the target vehicle on the road, and then along the passing direction of the road, obtain the adjacent passable areas on the road from the searched passable areas, and finally along the passing direction of the road, merge the adjacent passable areas on the road to obtain a complete passable area, which is convenient for the driving of driverless vehicles.

[0065] The embodiments of the present invention also provide an embodiment of the estimation device 50 for the passable area in the high-precision map. Please refer to Figure 9 , the device 50 includes: a first acquisition module 51, a determination module 52, an extraction module 53, a search module 54, a second acquisition module 55, and a fitting module 56. Among them, the first acquisition module 51 is used to acquire a high-precision map; the determination module 52 is used to extract the road data of the road from the high-precision map; the search module 54 is used to search for the passable areas in the preset search range of the target vehicle on the road according to the road data and with the current position as the starting point; the second acquisition module 55: is used to obtain the adjacent passable areas on the road from the searched passable areas along the passing direction of the road; the fitting module 56 is used to merge the adjacent passable areas on the road along the passing direction of the road.

[0066] In some embodiments, the adjacent passable areas include a first passable area and a second passable area. Along the driving direction of the road, the second passable area is located in front of the first passable area. Wherein, the fitting module is specifically configured to determine the ending boundary of the first passable area in the adjacent passable areas, and the starting boundary of the second passable area, and connect the left endpoint of the ending boundary and the left endpoint of the starting boundary, and connect the right endpoint of the ending boundary and the right endpoint of the starting boundary, and delete the ending boundary and the starting boundary.

[0067] The beneficial effects of the embodiments of the present invention are as follows: Different from the prior art, the embodiments of the present invention provide an estimation device for passable areas in a high-precision map, including a first acquisition module for acquiring a high-precision map; a determination module for determining the road and the current position where the target vehicle is currently driving; an extraction module for extracting road data of the road from the high-precision map; a search module for searching for passable areas within a preset search range of the target vehicle on the road according to the road data and starting from the current position; a second acquisition module for acquiring adjacent passable areas on the road from the passable areas obtained by the search along the driving direction of the road; a fitting module for merging the adjacent passable areas on the road along the driving direction of the road. Through the above method, a complete passable area is obtained, which is convenient for the driving of driverless vehicles.

[0068] Please refer to Figure 10 , Figure 10 which is a schematic diagram of the hardware structure of a controller of a driverless vehicle provided by an embodiment of the present invention. As Figure 10 shown, the controller 20 includes:

[0069] One or more processors 201 and a memory 202. Figure 9 Taking a processor 501 as an example in

[0070] The processor 201 and the memory 202 can be connected through a bus or other means. Figure 9 Taking connection through a bus as an example in

[0071] The memory 202, as a non-volatile computer-readable storage medium, can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions / modules corresponding to the method for generating expert influence in the embodiments of the present invention (for example, attached Figure 9The first acquisition module, the second acquisition module, the first generation module, the update module, and the second generation module shown). The processor 201 executes various functional applications and data processing of the server by running the non-volatile software programs, instructions, and modules stored in the memory 202, that is, implements the method for generating expert influence and the method for expert recommendation in the above method embodiments.

[0072] The memory 202 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the expert influence generation device and the expert recommendation device, etc. In addition, the memory 202 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some embodiments, the memory 202 may optionally include a memory remotely provided with respect to the processor 201, and these remote memories can be connected to the expert influence generation device and the expert recommendation device through a network. Examples of the above network include but are not limited to the Internet, an enterprise intranet, a local area network, a mobile communication network, and combinations thereof.

[0073] The one or more modules are stored in the memory 202 and, when executed by the one or more processors 201, execute the methods in any of the above method embodiments. For example, execute the Figure 2 method steps S101 to step S106 in the above, Figure 3 method steps S1051 to step S1052 in the above, Figure 6 method steps S1061 to step S1062 in the above, Figure 7 step S10621 in the above, and implement Figure 9 the functions of modules 51-56 in the above.

[0074] The above product can execute the method provided by the embodiments of the present invention and has the corresponding functional modules and beneficial effects of the execution method. For technical details not described in detail in this embodiment, reference can be made to the method provided by the embodiments of the present invention.

[0075] The electronic device in the embodiments of the present invention exists in various forms, including but not limited to:

[0076] (1) Mobile communication devices: These devices are characterized by having mobile communication functions and mainly aim to provide voice and data communication. Such terminals include: smart phones (such as iPhone), multimedia phones, functional phones, and low-end phones, etc.

[0077] (2) Ultra-mobile personal computer devices: This type of device belongs to the category of personal computers, has computing and processing capabilities, and generally also has the feature of mobile Internet access. Such terminals include: PDA, MID, and UMPC devices, etc., such as the iPad.

[0078] (3) Servers: Devices that provide computing services. The composition of a server includes a processor, hard disk, memory, system bus, etc. Servers are similar to general computer architectures, but due to the need to provide highly reliable services, they have higher requirements in terms of processing power, stability, reliability, security, scalability, and manageability.

[0079] (4) Other electronic devices with data interaction functions.

[0080] Embodiments of the present invention provide a non-volatile computer-readable storage medium, and the non-volatile computer-readable storage medium stores computer-executable instructions. These computer-executable instructions are executed by an electronic device to perform the methods in any of the above method embodiments. For example, to execute the method steps S101 to S105 described above Figure 1 in, Figure 2 the method steps S1011 to S1014 in, Figure 3 the method steps S201 to S210 in, to implement Figure 7 the modules 301 - 305 in, Figure 8 the functions of the modules 401 - 410 in.

[0081] Embodiments of the present invention provide a computer program product, including a computing program stored on a non-volatile computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer is made to execute the methods in any of the above method embodiments. For example, to execute the method steps S101 to S105 described above Figure 1 in, Figure 2 the method steps S1011 to S1014 in, Figure 3 the method steps S201 to S210 in, to implement Figure 7 the modules 301 - 305 in, Figure 8 the functions of the modules 401 - 410 in.

[0082] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated. The components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0083] Through the description of the above embodiments, those of ordinary skill in the art can clearly understand that each embodiment can be implemented by means of software plus a general hardware platform, and of course, it can also be implemented by hardware. Those of ordinary skill in the art can understand that all or part of the processes in the above-described method for implementing the embodiments can be completed by instructing relevant hardware through a computer program. The program can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the above-described method embodiments. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM), etc.

[0084] The above are only the embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the content of the specification and drawings of the present invention, or directly or indirectly applied to other related technical fields, shall be equally included in the patent protection scope of the present invention.

Claims

1. A method for estimating a passable area in a high-precision map, characterized in that The method includes: Determining the road on which the target vehicle is currently traveling and its current position; Extracting the road data of the road from the high-precision map, where the road data includes the position information and connection relationships of each section of the road in the high-precision map; According to the road data, and starting from the current position, along the traffic direction of the road, searching for the passable sections within the preset search range of the target vehicle on the road; According to the connection relationships of the passable sections, sequentially merging the adjacent passable sections on the road to obtain a passable area; The adjacent passable areas include a first passable area and a second passable area. Along the traffic direction of the road, the second passable area is located in front of the first passable area. The step of merging the adjacent passable areas on the road further includes: Determining the ending boundary of the first passable area and the starting boundary of the second passable area among the adjacent passable areas; Connecting the left endpoint of the ending boundary and the left endpoint of the starting boundary, and connecting the right endpoint of the ending boundary and the right endpoint of the starting boundary, and deleting the ending boundary and the starting boundary; Both the first passable area and the second passable area store their respective nodes in a linked list data structure. The step of connecting the left endpoint of the ending boundary and the left endpoint of the starting boundary, and connecting the right endpoint of the ending boundary and the right endpoint of the starting boundary, and deleting the ending boundary and the starting boundary specifically includes: According to the characteristics of the linked list data structure, obtaining the connection order of the left endpoint of the ending boundary and the left endpoint of the starting boundary, and the connection order of the right endpoint of the ending boundary and the right endpoint of the starting boundary; Connecting an edge from the left endpoint of the starting boundary to the left endpoint of the ending boundary, and deleting the ending boundary; Connecting an edge from the right endpoint of the ending boundary to the right endpoint of the starting boundary, and deleting the starting boundary.

2. The method according to claim 1, wherein The ending boundary of the first passable area and the starting boundary of the second passable area are in the same traffic direction.

3. The method according to claim 1 or 2, characterized in that, The step of obtaining the adjacent passable areas on the road from the searched passable areas along the traffic direction of the road further includes: Starting from the current position, along the driving direction of the road, sequentially determining whether the distance between two adjacent passable areas in the searched passable areas is greater than a preset threshold; If so, determining the two adjacent passable areas as adjacent passable areas.

4. An estimation device for passable areas in a high-precision map, characterized in that, Applied to an autonomous vehicle, the device includes: A first acquisition module for acquiring a high-precision map; A determination module for determining the road on which the target vehicle is currently traveling and its current position; An extraction module for extracting the road data of the road from the high-precision map; A search module for searching for a passable area within the preset search range of the target vehicle on the road according to the road data and starting from the current position; A second acquisition module, configured to acquire adjacent passable areas in the road from the searched passable areas along the traffic direction of the road; A fitting module, configured to merge the adjacent passable areas in the road along the traffic direction of the road; The adjacent passable areas include a first passable area and a second passable area. Along the traffic direction of the road, the second passable area is located in front of the first passable area; Specifically, the fitting module is configured to determine an ending boundary of the first passable area and a starting boundary of the second passable area in the adjacent passable areas, and connect a left endpoint of the ending boundary and a left endpoint of the starting boundary, and connect a right endpoint of the ending boundary and a right endpoint of the starting boundary, and delete the ending boundary and the starting boundary; When there are multiple traffic directions of the first passable area, there are multiple ending boundaries of the first passable area and multiple second passable areas; The step that the fitting module specifically connects the left endpoint of the ending boundary and the left endpoint of the starting boundary, and connects the right endpoint of the ending boundary and the right endpoint of the starting boundary further includes: connecting the left endpoint of the ending boundary and the left endpoints of the starting boundaries of the second passable areas, and connecting the right endpoint of the ending boundary and the right endpoints of the starting boundaries of the second passable areas.

5. A driverless vehicle, characterized in that, Comprising: At least one processor; And a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions for causing a computer to execute the method according to any one of claims 1-3.

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