Navigation map data set generation method and device, vehicle and storage medium

Abstract

The invention relates to the technical field of navigation, in particular to a navigation map data set generation method and device, a vehicle and a storage medium. The vehicle machine on the vehicle end sends the target road on which the vehicle is running or is about to run to the cloud end, and the cloud end preselects and stores the basic data of all the roads, so that once the cloud end receives the target road requested by the vehicle machine, the cloud end sends the basic data of the target road to the vehicle machine; meanwhile, a sensing system of the vehicle-mounted terminal can sense traffic information of roads around the vehicle-mounted terminal in real time. And the vehicle machine integrates the road traffic information and the basic data to form a navigation map data set so as to navigate the driving of the vehicle. In conclusion, the navigation map data set provided by the invention not only meets the requirements of real-time performance, but also meets the requirements of data accuracy, so that the quality of the navigation map data set is improved.

Description

Technical Field

[0001] This application relates to the technical field of navigation, and specifically relates to a method, device, vehicle, and storage medium for generating a navigation map data set. Background Art

[0002] The navigation map data set is used to assist a driving vehicle. The vehicle can obtain its surrounding environment data, road data, and traffic data in real time through its own perception system. The vehicle uses its own computing resources to fuse the surrounding environment data, road data, and traffic data into a navigation map data set. Since all the data for forming the map comes from the vehicle's real-time acquisition, it excessively occupies the vehicle's computing resources, resulting in insufficient or unstable remaining computing power of the vehicle, which will directly affect the map generation quality.

[0003] In summary, the navigation map data set generated by the prior art reduces the data quality.

[0004] Therefore, the prior art still needs to be improved and enhanced. Summary of the Invention

[0005] This application provides a method, device, vehicle, and storage medium for generating a navigation map data set to solve the technical problem that the navigation map data set generated by the prior art in the related technology reduces the data quality.

[0006] To achieve the above object, this application adopts the following technical solutions:

[0007] The first aspect embodiment of this application provides a method for generating a navigation map data set, including the following steps:

[0008] Obtain the basic data stored for the target road;

[0009] Perceive the road traffic information of the target road in real time;

[0010] Overlay the basic data and the road traffic information to obtain the navigation map data set of the target road.

[0011] According to the above technical means, the basic data of this application is road data with low requirements for real-time performance, that is, the basic data will not change with time. Even if the basic data is collected and saved in advance, it will not affect the accuracy of the basic data. Therefore, the basic data can be collected in advance to be saved. And the road traffic information is data that is prone to change with time. Therefore, it is necessary to use the perception system on the vehicle to sense the road traffic information in real time to ensure the accuracy of the obtained road traffic data. Since this application saves the road basic data with low requirements for real-time performance in advance, it is not necessary to occupy the computing resources of the vehicle computer to collect and construct the basic data. The above computing resources saved by using the vehicle computer can be used to better collect the road traffic information in real time, thereby ensuring the accuracy of the collected road traffic information. In summary, the navigation map data set of the present invention meets both the real-time performance and the requirements of data accuracy, thereby improving the quality of the navigation map data set.

[0012] Optionally, in an embodiment of this application, the obtaining of the basic data stored for the target road includes:

[0013] Perceive the identification road sign and parse the identification road sign to obtain on-site identification information;

[0014] Send the on-site identification information to the cloud;

[0015] Receive the basic data of the target road sent by the cloud and matching the on-site identification information.

[0016] According to the above technical means, in the embodiment of this application, the on-site identification information of the road is obtained through the identification road sign. Since the vehicle arrives at the identification road sign before entering the target road, that is, the identification information contained in the identification road sign of the target road can be sent to the cloud before the vehicle travels to the target road. After receiving the identification information, the cloud knows which road or which section of the road the vehicle needs to obtain the basic data for, so that the cloud can send the data to the vehicle computer before the vehicle travels to the target road, that is, the basic data of the road has been obtained before the vehicle travels to the target road. Therefore, even though it takes time for the cloud to transmit the basic data to the vehicle computer, since the vehicle computer can obtain the basic data sent by the cloud in advance before it travels to the target road, the time required for data transmission can be compensated, so as not to affect the vehicle computer from using the basic data to navigate the vehicle on the target road.

[0017] Optionally, in an embodiment of this application, the obtaining of the basic data stored for the target road includes:

[0018] Read the current position of the vehicle body;

[0019] Send the current position to the cloud;

[0020] Receive the basic data of the target road sent by the cloud, where the target road is in front of the vehicle body.

[0021] According to the above technical means, before the vehicle-mounted device of the embodiment of the present application travels to the target road, it sends the current position of the vehicle to the cloud, allowing the cloud to analyze several target roads existing in the road that the vehicle is about to travel according to the current position. The so-called target road can be a tunnel or a bridge, and the cloud sends the basic data of the parsed target road to the vehicle-mounted device. The vehicle-mounted device can obtain more basic data of the target road at one time by using the current position of the vehicle, thereby reducing the number of data transmissions and saving the network resources of the vehicle-mounted device.

[0022] Optionally, in an embodiment of the present application, the real-time perception of the road traffic information of the target road includes:

[0023] Perceive the road scene image of the target road through the image acquisition device on the vehicle body, where the target road is in front of the vehicle body;

[0024] Analyze the road scene image to obtain the real-time traffic data and / or the real-time road surface information of the target road, and use the real-time traffic data and / or the real-time road surface information as the road traffic information.

[0025] According to the above technical means, the basic data in the embodiment of the present application covers vector data and attribute data, and the road traffic information covers traffic data and road surface data, thus enriching the data volume and data types, so that the subsequent constructed navigation map data set is more refined, and further improving the quality of the navigation map data set.

[0026] Optionally, in an embodiment of the present application, the superimposing the basic data and the road traffic information to obtain the navigation map data set of the target road includes:

[0027] Receive the cloud identification information corresponding to the basic data, where the basic data and the cloud identification information both come from the cloud;

[0028] Perceive the on-site identification information of the target road;

[0029] When the on-site identification information matches the cloud identification information, superimpose the basic data and the road traffic information to obtain the navigation map data set of the target road.

[0030] According to the above technical means, the vehicle-mounted device of the embodiment of the present application verifies the cloud identification information sent by the cloud to verify whether the basic data sent by the cloud is the data of the target road that the vehicle is about to travel, thereby further improving the accuracy of the subsequent navigation map data set.

[0031] Optionally, in an embodiment of the present application, the superimposing the basic data and the real-time data to obtain the navigation map data set of the target road includes:

[0032] Obtain a first coordinate corresponding to the cloud identification information on a first map and a second coordinate corresponding to the cloud identification information on a second map, where both the first map and the second map cover the target road, and the accuracy of the first map is greater than that of the second map;

[0033] Obtain a conversion relationship between the first map and the second map according to the difference between the first coordinate and the second coordinate;

[0034] Superimpose the basic data on the first map and the road traffic information on the second map on the second map according to the conversion relationship to obtain the navigation map data set of the target road.

[0035] According to the above technical means, the basic data stored in the cloud in the embodiment of the present application is established on the first map, and only the cloud identification information is established on both the second map and the first map, that is, the cloud identification information is established on both the first map and the second map. The reason for using the first map is to improve the accuracy of the road coordinates corresponding to the basic data, and the road traffic information and on-site identification information sensed by the vehicle-mounted device are established on the second map. Therefore, using the cloud identification information and on-site identification information can superimpose the basic data on the second map, so as to facilitate the fusion of the basic data and the road traffic information on the second map to form a navigation map data set.

[0036] Optionally, in an embodiment of the present application, a method for generating a navigation map data set includes the following steps:

[0037] Receive a request message sent by the vehicle-mounted device;

[0038] Parse the request message to obtain the target road in front of the vehicle body;

[0039] Extract the basic data of the target road and send the basic data to the vehicle-mounted device, where the basic data is used to be superimposed on the road traffic information of the target road on the vehicle-mounted device to obtain a navigation map data set.

[0040] According to the above technical means, in the embodiment of the present application, the cloud provides the basic data and the vehicle-mounted device provides the road traffic information, so that the cloud shares the computing pressure of the vehicle-mounted device, thereby saving the computing resources of the vehicle-mounted device.

[0041] Optionally, in an embodiment of the present application, parsing the request information to obtain a target road in front of the vehicle body includes:

[0042] Parsing the request information to obtain registration information, on-site identification information, and the current position of the vehicle body;

[0043] Verifying the registration information;

[0044] When the registration information is verified, screening out the target road from each typical road according to the on-site identification information and the current position of the vehicle body, where the typical road is a section with a driving difficulty greater than a set difficulty.

[0045] According to the above technical means, the cloud in the present application does not feedback the basic data of the target road for the request information of all vehicles, but only gives feedback to the vehicles that pass the verification, thereby improving the data security. In addition, in the embodiment of the present application, only the basic data of the typical roads with large driving difficulties is sent to the in-vehicle computer. This is because even if the in-vehicle computer does not have specific road data for ordinary roads with small driving difficulties, the vehicle can still drive normally. Therefore, the cloud only sends the data of the typical roads, which can not only ensure the safe driving of the vehicle but also save the computing resources of the in-vehicle computer on the vehicle.

[0046] An embodiment of the second aspect of the present application provides a navigation map dataset generation device, including:

[0047] An acquisition module, configured to acquire the basic data stored for the target road;

[0048] A perception receiving module, configured to perceive the road traffic information of the target road in real time;

[0049] A map generation module, configured to superimpose the basic data and the road traffic information to obtain a navigation map dataset of the target road.

[0050] An embodiment of the third aspect of the present application provides a vehicle, where the vehicle includes a memory, a processor, and a navigation map dataset generation program stored in the memory and executable on the processor. When the processor executes the navigation map dataset generation program, the steps of the above-mentioned navigation map dataset generation method are implemented; or, the steps of the above-mentioned navigation map dataset generation method are implemented.

[0051] An embodiment of the fourth aspect of the present application provides a computer-readable storage medium, on which a navigation map dataset generation program is stored. When the navigation map dataset generation program is executed by a processor, the steps of the above-mentioned navigation map dataset generation method are implemented; or, the steps of the above-mentioned navigation map dataset generation method are implemented.

[0052] Advantages of the present application:

[0053] (1) The basic data of the present application is road data with low real-time requirements, that is, the basic data does not change with time. Even if the basic data is collected and saved in advance, it will not affect the accuracy of the basic data. Therefore, the basic data can be collected and saved in advance. And the road traffic information is data that is prone to change with time. Therefore, it is necessary to use the perception system on the vehicle to sense the road traffic information in real time to ensure the accuracy of the obtained road traffic data. Since the present application has saved the road basic data with low real-time requirements in advance, there is no need to occupy the computing resources of the vehicle computer to collect and construct the basic data. The above computing resources saved by the vehicle computer can be used to better collect the road traffic information in real time, so as to ensure the accuracy of the collected road traffic information. In summary, the navigation map data set of the present invention meets both the real-time requirement and the data accuracy requirement, thus improving the quality of the navigation map data set.

[0054] (2) In the embodiment of the present application, the road sign is identified to obtain the on-site identification information of the road. Since the vehicle enters the target road after reaching the road sign, that is, the identification information contained in the road sign of the target road can be sent to the cloud before the vehicle travels to the target road. When the cloud receives the identification information, it knows which road or which section of the road the vehicle needs to obtain the basic data for, so that the cloud can send the data to the vehicle computer before the vehicle travels to the target road, that is, the basic data of the road has been obtained before the vehicle travels to the target road. Therefore, even though it takes time for the cloud to transmit the basic data to the vehicle computer, since the vehicle computer can obtain the basic data sent by the cloud in advance before it travels to the target road, the time required for data transmission can be compensated, thus not affecting the vehicle computer from using the basic data to navigate the vehicle on the target road.

[0055] (3) Before the vehicle computer of the embodiment of the present application travels to the target road, it sends the current position of the vehicle to the cloud, allowing the cloud to analyze several target roads existing in the road that the vehicle is about to travel based on the current position. The so-called target roads can be tunnels or bridges, and the cloud sends the basic data of the parsed target roads to the vehicle computer. The vehicle computer can obtain the basic data of more target roads at one time by using the current position of the vehicle, thereby reducing the number of data transmissions and saving the network resources of the vehicle computer.

[0056] Additional aspects and advantages of the present application will be given in part in the following description, will become apparent in part from the following description, or will be understood through the practice of the present application. Brief Description of the Drawings

[0057] The above and / or additional aspects and advantages of the present application will become apparent and be readily understood from the following description of embodiments in conjunction with the accompanying drawings, where:

[0058] Figure 1 is the overall flowchart of the present application;

[0059] Figure 2 is the interaction schematic diagram between the vehicle end and the cloud end in the embodiment of the present application;

[0060] Figure 3 is the road schematic diagram in the embodiment of the present application;

[0061] Figure 4 is for the present application Figure 3 partial enlarged view;

[0062] Figure 5 is the flowchart of the vehicle end compiling the map in the embodiment of the present application;

[0063] Figure 6 is the structural schematic diagram of the navigation map data set generation device in the embodiment of the present application;

[0064] Figure 7 is the internal structure principle block diagram of the vehicle provided in the embodiment of the present application. Detailed Embodiments

[0065] The embodiments of the present application will be described in detail below. Examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present application and should not be construed as limiting the present application.

[0066] A navigation map data set generation method, device, vehicle, and storage medium according to an embodiment of the present application will be described below with reference to the accompanying drawings. In view of

[0067] the problem that the generated navigation map data set mentioned in the above background technology reduces the mapping quality, the present application provides a navigation map data set generation method. In this method, the vehicle computer obtains the basic data stored for the target road; the vehicle computer real-time senses the road traffic information of the target road; the vehicle computer superimposes the basic data and the road traffic information to obtain the navigation map data set of the target road.

[0068] For example, existing driverless technologies collect road images through the perception system on the vehicle. The in-vehicle computer of the vehicle obtains the road traffic information and basic data of the road by analyzing the road images. Among them, the basic data includes the number of lanes on the road, the width of the road, the inflection point coordinates of the road, etc. That is, the basic data does not change in a short period of time, that is, the basic data has low requirements for real-time performance. The road traffic data includes the traffic flow on the road, the distance between vehicles, temporary roadblocks on the road, etc. That is, the road traffic data changes in a short period of time, that is, the road traffic data has high requirements for real-time performance. In the existing above-mentioned driverless technologies, all data processing falls on the in-vehicle computer, thus occupying the computing resources of the in-vehicle computer. In the present invention, the basic data with low requirements for real-time performance is placed on the cloud. When the in-vehicle computer needs the basic data, it can directly obtain this part of the data from the cloud, thus saving the computing resources of the in-vehicle computer. And the road traffic data with high requirements for real-time performance is collected in real time through the perception system of the in-vehicle computer, so that the collected road traffic information is more accurate. In summary, the present invention not only saves the computing resources of the in-vehicle computer but also improves the accuracy of the road traffic information required for constructing the navigation map dataset.

[0069] Specifically, Figure 1 is a schematic flowchart of a method for generating a navigation map dataset provided by an embodiment of the present application.

[0070] As Figure 1 shown, the method for generating the navigation map dataset includes the following steps:

[0071] S100, obtaining the basic data stored for the target road.

[0072] The target road can be a section with a large flow of people and vehicles, or a typical section. Signage can be set for both sections with a large flow of people and vehicles and typical sections. Among them, typical sections include complex intersections, complex interchanges, tunnels, uphill / downhill, continuous curves, sharp curves, merging / splitting sections, etc. Typical sections are sections with greater driving difficulty.

[0073] The target road can also be the upcoming section that the vehicle is about to drive on.

[0074] That is, the in-vehicle computer sends a request message to the cloud. The in-vehicle computer is the computer or in-vehicle computer on the vehicle. The cloud can be a server, and this server can store data and process data. That is, the cloud pre-stores the basic data of all roads. When the cloud receives the request message, it will judge which section of the basic data the in-vehicle computer needs to obtain according to the request message. That is, after the in-vehicle computer sends the request message to the cloud, the cloud will send the basic data requested by the in-vehicle computer to the in-vehicle computer.

[0075] S200, perceiving the road traffic information of the target road in real time.

[0076] At the same time, the vehicle computer will also use the perception system on the vehicle to perceive road traffic information. The perception system may include a camera and an image processor for processing image data collected by the camera.

[0077] S300: superimpose the basic data and the road traffic information to obtain a navigation map data set of the target road.

[0078] The navigation map data set includes both the location data of the road and the basic data and road traffic information. The unmanned vehicle can drive safely on the road using the navigation map data set. If the navigation map data set obtained by the present invention is displayed on the vehicle display in a graphical manner, the driver can drive the vehicle more safely according to the basic data and road traffic information displayed on the navigation map data set.

[0079] In one embodiment, step S100 includes the following specific steps S101a, S102a, and S103a:

[0080] S101a, sensing a signpost, and analyzing the signpost to obtain on-site sign information.

[0081] The signpost is located in front of the vehicle's direction of travel. The vehicle reaches the signpost first before reaching the target road. The signpost is usually attached to a corner of the roadside notice board. Through the signpost, the vehicle can send information requesting the target road data to the cloud before reaching the target road.

[0082] The vehicle computer collects images of road signs through cameras. Figure 2 The roadside information code unit in the camera is Figure 2 The vehicle-side sensing unit in the vehicle-side sensing unit collects the image of the roadside information code unit and transmits it to the vehicle-side processing unit. The vehicle-side processing unit of the vehicle computer analyzes the image to obtain the on-site identification information of the target road. The on-site identification information can be the name of the target road.

[0083] S102a, sending the site identification information to the cloud.

[0084] The vehicle computer sends the parsed site identification information to Figure 2 The cloud control unit in the cloud determines which road the vehicle computer requests based on the on-site identification information. That is, the cloud receives the on-site identification information and can know which road the vehicle computer needs to obtain data on by combining it with the second map.

[0085] S103a, receiving basic data of the target road that matches the on-site identification information and is sent by the cloud.

[0086] The cloud sends the basic data to the in-vehicle unit, and the in-vehicle unit receives the basic data. Among them, the basic data stored in the cloud comes from the data surveyed on-site by the surveying party or the basic data collected by the surveying party. The basic data includes vector data, attribute data, and anchor point coordinates. The anchor point coordinates are the coordinates where the above-mentioned identification road signs are located. For example, Figure 5 As shown, the surveying party will deploy the identification road signs in the form of information codes on one side of the road. Among them, the vector data is the road data with coordinate positions. The vector data includes the coordinate points of the road edge feature points, curve parameters, number of lanes, slope, and curvature data. The coordinate points of the road edge feature points include the end point coordinates, midpoint coordinates, and inflection point coordinates on both sides of the road. The curve parameters include the radius of curvature and radian of the road curve segment, etc. The number of lanes is the number of lanes on the road and the coordinates of each lane; the attribute data is the data independent of the position coordinates, including speed limit, traffic restriction, and Figure 3 information such as the traffic direction indicated by the arrow in Figure 3 The figure composed of a large circle enclosing a small circle in Figure 4 is used to mark the feature points, and the anchor points are as shown in

[0087] In another embodiment, step S100 includes the following specific steps S101b, S102b, and S103b:

[0088] S101b, read the current position of the vehicle body.

[0089] S102b, send the current position to the cloud.

[0090] S103b, receive the basic data of the target road sent by the cloud, and the target road is in front of the vehicle body.

[0091] The in-vehicle unit sends the current position of the vehicle body, that is, the vehicle, to the cloud. The cloud uses the second map as the working base map. After receiving the current position, the cloud divides the first map where the current position is located. For example, the electronic base map is a map of a certain province, and the first map is a map of a certain urban area in that province. After the cloud identifies the typical road sections around the current position on the first map, that is, after identifying the target road, it sends the basic data of the typical road sections to the in-vehicle unit.

[0092] In one embodiment, the request information includes not only the on-site identification information but also the registration information. The vehicle head unit sends the on-site identification information and the registration information to the cloud. The cloud does not give feedback on all the on-site identification information. Instead, the cloud verifies the registration information sent by the vehicle head unit. Only when the verification passes will the cloud parse the request information to obtain the basic data of the specific typical road that the vehicle head unit needs. The registration information includes the vehicle owner's driving license and the owner's identity information, the driving license of the driver who often drives the vehicle, and the driver's identity information. It also includes whether the owner accepts the data security agreement and whether the owner accepts the new vehicle security agreement.

[0093] In one embodiment, based on steps S101a to S103a, step S200 includes the following specific steps S201 and S202:

[0094] S201, use the image acquisition device on the vehicle body to sense the road scene image of the target road, where the target road is in front of the vehicle body.

[0095] S202, parse the road scene image to obtain the real-time traffic data and / or the real-time road surface information of the target road, and use the real-time traffic data and / or the real-time road surface information as the road traffic information.

[0096] The real-time road surface information includes information such as whether there are roadblocks on the road, the coordinate positions of the roadblocks, and whether the road surface is uneven.

[0097] In one embodiment, the vehicle head unit in step S300 does not directly use all the basic data sent by the cloud to construct the navigation map dataset. It starts to construct the navigation map dataset only after meeting the conditions. This embodiment specifically includes the following steps: receive the cloud identification information corresponding to the basic data, where both the basic data and the cloud identification information come from the cloud; sense the on-site identification information of the target road; when the on-site identification information matches the cloud identification information, superimpose the basic data and the road traffic information to obtain the navigation map dataset of the target road.

[0098] The cloud not only sends the basic data to the vehicle head unit but also sends the information code corresponding to the basic data, that is, the cloud identification information, to the vehicle head unit. The cloud identification information is the information used by the cloud to mark which road the basic data belongs to. The vehicle head unit will judge whether the cloud identification information is consistent with the on-site identification information. If they are consistent, it means that the basic data sent by the cloud is exactly the data needed by the vehicle head unit. Therefore, the basic data can be used to construct the navigation map dataset. If they are not consistent, the vehicle head unit does not use the basic data sent by the cloud to construct the navigation map dataset but directly uses its own second map to export the vehicle.

[0099] Based on the above embodiments, step S300 includes the following specific steps S301, S302, and S303:

[0100] S301, obtain a first coordinate corresponding to the cloud identification information on a first map and a second coordinate corresponding to the cloud identification information on a second map, where both the first map and the second map cover the target road, and the accuracy of the first map is greater than the accuracy of the second map.

[0101] That is, the identification road sign where the cloud identification information is located has corresponding coordinates in the coordinate system of the first map and also has corresponding coordinates in the coordinate system of the second map.

[0102] S302, obtain a conversion relationship between the first map and the second map based on the difference between the first coordinate and the second coordinate.

[0103] If the same identification road sign has different coordinates on the first map and the second map, it indicates that there is a difference between the two maps. Through the different coordinates of the same identification road sign on the two maps, the conversion relationship between the two maps can be calculated.

[0104] S303, based on the conversion relationship, superimpose the basic data on the first map and the road traffic information on the second map on the second map to obtain a navigation map dataset of the target road.

[0105] The basic data sent by the cloud is only established on the first map, not on the second map with lower accuracy, and the car machine stores the second map, that is, the electronic map. For example, the basic data of a typical road is the road width. There is a typical road on the first map in the cloud, and the distance between the corresponding coordinates on both sides of the typical road is the road width.

[0106] The car machine uses the second map as the working map, that is, the road traffic information collected by the car machine through its own perception system is established on the second map. According to the conversion relationship between the first map and the second map, the basic data on the first map can be added to the corresponding positions on the second map. For example, the basic data includes the above-mentioned vector data and attribute data. The vector data includes the endpoint coordinates, midpoint coordinates, and inflection point coordinates on both sides of the road. According to the conversion relationship between the two maps, the endpoint coordinates, midpoint coordinates, and inflection point coordinates are converted into the corresponding coordinates on the second map, so as to add the endpoint coordinates, midpoint coordinates, and inflection point coordinates to the second map to fuse the original road traffic information on the second map to obtain a navigation map dataset of the target road. The specific process of superimposing the attribute data on the second map is as follows:

[0107] The attribute data includes information such as speed limits, traffic restrictions, and traffic directions. Coordinates of the roads corresponding to the speed limits, traffic restrictions, and traffic directions are matched on the first map, and the coordinates are converted into coordinates on the second map according to the conversion relationship, that is, the areas where the above roads are located are demarcated on the second map. Then, the speed limits, traffic restrictions, and traffic directions are added to the areas on the second map to complete the overlay of the basic data and the road traffic information on the second map.

[0108] After the vehicle has traveled a typical section and before reaching the next typical section, a request message is sent to the cloud again. The cloud will send a data detection instruction to the in-vehicle computer, as Figure 5 shown, to detect whether the in-vehicle computer has cleared and released the basic data obtained last time. If it has been cleared, the cloud will send data to the in-vehicle computer again, thus preventing the data from being stored on the in-vehicle computer for a long time and ensuring data security.

[0109] In summary, the present invention starts from the lightweighting of the autonomous driving map and data security, follows the idea that in ordinary scenarios, the self-vehicle perception is mainly relied on, and in difficult scenarios, the map over-the-horizon perception and the self-vehicle perception are combined, to obtain a better autonomous driving experience, aiming to improve the passing performance of autonomous driving on typical sections and enhance driving safety and data security. Moreover, based on the road vector data and attribute data provided by the information code, the mapping difficulty and computing power requirements at the vehicle end can be reduced, and the mapping reliability can be improved; in addition, the compiled navigation map data set can directly serve the planning and control of autonomous driving vehicles.

[0110] Next, a navigation map data set generation device according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0111] As Figure 6 shown, the navigation map data set generation device 10 includes: an acquisition module 100, a perception receiving module 200, and a map generation module 300.

[0112] Specifically, the acquisition module 100 is configured to acquire the basic data stored for the target road.

[0113] The perception receiving module 200 is configured to perceive the road traffic information of the target road in real time.

[0114] The map generation module 300 is configured to overlay the basic data and the road traffic information to obtain the navigation map data set of the target road.

[0115] It should be noted that the foregoing explanation of the embodiment of the navigation map data set generation method also applies to the navigation map data set generation device of this embodiment, and will not be repeated here.

[0116] Figure 7Schematic diagram of the structure of the vehicle provided by the embodiment of the present application. The vehicle may include:

[0117] A memory 501, a processor 502, and a computer program stored on the memory 501 and executable on the processor 502.

[0118] When the processor 502 executes the program, it implements the navigation map data set generation method provided in the above embodiment.

[0119] Furthermore, the vehicle further includes:

[0120] A communication interface 503 for communication between the memory 501 and the processor 502.

[0121] The memory 501 is used to store a computer program executable on the processor 502.

[0122] The memory 501 may include a high-speed RAM memory, and may also include non-volatile memory, such as at least one disk memory.

[0123] If the memory 501, the processor 502, and the communication interface 503 are implemented independently, the communication interface 503, the memory 501, and the processor 502 can be interconnected through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 7 only a thick line is shown in the figure, but it does not mean that there is only one bus or one type of bus.

[0124] Optionally, in a specific implementation, if the memory 501, the processor 502, and the communication interface 503 are integrated on a chip, the memory 501, the processor 502, and the communication interface 503 can communicate with each other through an internal interface.

[0125] The processor 502 may be a Central Processing Unit (CPU), or an Application Specific Integrated Circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0126] This embodiment also provides a computer-readable storage medium, on which a computer program is stored. When the program is executed by a processor, the above-described method for generating a navigation map data set is implemented.

[0127] In the description of this specification, the descriptions with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples", etc. mean that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms are not necessarily directed to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any one or N embodiments or examples in a suitable manner. In addition, without conflict, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0128] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of the present application, the meaning of "N" is at least two, such as two, three, etc., unless otherwise specifically and clearly defined.

[0129] Any process or method description in the flowchart or described in other ways herein can be understood to represent a module, segment, or part of code including one or N executable instructions for implementing a customized logic function or process. The scope of the preferred embodiments of the present application includes additional implementations, where the functions may be executed in a substantially simultaneous manner or in a reverse order according to the functions involved, rather than in the order shown or discussed, which should be understood by those skilled in the art to which the embodiments of the present application pertain.

[0130] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other systems that can read and execute instructions from the instruction execution system, apparatus, or device), or in conjunction with these instruction execution systems, apparatuses, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection part (electronic device) having one or N wirings, a portable computer disk cartridge (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which a program can be printed, because the program can be obtained electronically by optically scanning the paper or other media, followed by editing, interpretation, or otherwise processing it as appropriate, and then storing it in a computer memory.

[0131] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware, or a combination thereof. In the above-described embodiments, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits having logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits having appropriate combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), and the like.

[0132] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by a program instructing relevant hardware. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0133] In addition, each functional unit in various embodiments of the present application may be integrated into one processing module, may exist separately physically for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0134] The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present application. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for generating a navigation map data set, characterized in that, Including the following steps: Obtain the basic data stored for the target road; Perceive the road traffic information of the target road in real time; Overlay the basic data and the road traffic information to obtain the navigation map dataset of the target road.

2. The method for generating a navigation map data set according to claim 1, characterized in that, The obtaining of the basic data stored for the target road includes: Perceive the identification road signs and parse the identification road signs to obtain on-site identification information; Send the on-site identification information to the cloud; Receive the basic data of the target road that matches the on-site identification information sent by the cloud.

3. The method for generating a navigation map data set according to claim 1, characterized in that, The obtaining of the basic data stored for the target road includes: Read the current position of the vehicle body; Send the current position to the cloud; Receive the basic data of the target road sent by the cloud, and the target road is in front of the vehicle body.

4. The method for generating a navigation map data set according to claim 1, characterized in that, The real-time perception of the road traffic information of the target road includes: Perceive the road scene image of the target road through the image acquisition device on the vehicle body, and the target road is in front of the vehicle body; Parse the road scene image to obtain the real-time traffic data and / or the real-time road surface information of the target road, and use the real-time traffic data and / or the real-time road surface information as the road traffic information.

5. The method for generating a navigation map data set according to claim 1, characterized in that, The overlaying of the basic data and the road traffic information to obtain the navigation map dataset of the target road includes: Receive the cloud identification information corresponding to the basic data, and both the basic data and the cloud identification information come from the cloud; Perceive the on-site identification information of the target road; When the on-site identification information and the cloud identification information match, overlay the basic data and the road traffic information to obtain the navigation map dataset of the target road.

6. The method for generating a navigation map data set according to claim 5, characterized in that, The step of when the on-site identification information and the cloud identification information match, overlay the basic data and the road traffic information to obtain the navigation map dataset of the target road includes: Obtain the first coordinate corresponding to the cloud identification information on the first map and the second coordinate corresponding to the cloud identification information on the second map. Both the first map and the second map cover the target road, and the accuracy of the first map is greater than that of the second map; Obtain the conversion relationship between the first map and the second map based on the difference between the first coordinate and the second coordinate; According to the conversion relationship, overlay the basic data on the first map and the road traffic information on the second map on the second map to obtain the navigation map dataset of the target road.

7. A method for generating a navigation map data set, characterized in that, Including the following steps: Receive the request information sent by the car machine; Parse the request information to obtain the target road in front of the vehicle body; Extract the basic data of the target road and send the basic data to the car machine. The basic data is used to overlay with the road traffic information of the target road on the car machine to obtain the navigation map dataset.

8. The method for generating a navigation map data set according to claim 7, characterized in that, The parsing of the request information to obtain the target road in front of the vehicle body includes: Parse the request information to obtain the registration information and the on-site identification information and / or the current position of the vehicle body; Verify the registration information; When the registration information is verified successfully, a target road is selected from various typical roads based on the on-site identification information and the current position of the vehicle body, where the typical road is a section with a driving difficulty greater than a set difficulty.

9. A navigation map data set generation device, characterized in that It includes: An acquisition module for acquiring the basic data stored for the target road; A perception and reception module for real-time perceiving the road traffic information of the target road; A map generation module for superimposing the basic data and the road traffic information to obtain the navigation map data set of the target road.

10. A vehicle, characterized in that The vehicle includes a memory, a processor, and a navigation map data set generation program stored in the memory and executable on the processor. When the processor executes the navigation map data set generation program, the steps of the navigation map data set generation method according to any one of claims 1-6 are implemented; or, the steps of the navigation map data set generation method according to any one of claims 7-8 are implemented.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a navigation map data set generation program. When the navigation map data set generation program is executed by a processor, the steps of the navigation map data set generation method according to any one of claims 1-6 are implemented; or, the steps of the navigation map data set generation method according to any one of claims 7-8 are implemented.

Images