Full-amount navigation path generation method and device, vehicle and storage medium

Abstract

The invention discloses a full-amount navigation path generation method and device, a vehicle and a storage medium, and relates to the technical field of automatic driving. The method comprises the steps that driving track data and first path data corresponding to a target journey are acquired, the driving track data are used for determining a vehicle driving track corresponding to the target journey in a manual driving mode, and the first path data comprise navigation data corresponding to a full navigation path of the target journey; the full navigation path is planned according to the starting position and the ending position of the target travel; performing matching analysis on the driving track data and the first path data to obtain a matching result; performing data clipping on the driving track data and the first path data according to a matching result to obtain a target clipping result; and generating a target navigation path based on the target clipping result. The technical problem that the navigation path generation accuracy is poor due to the fact that a navigation path generation method provided in the related technology is difficult to adapt to personalized driving is solved.

Description

Technical Field

[0001] The present application relates to the field of autonomous driving technology, and more specifically, to a method, device, vehicle and storage medium for generating a full navigation path. Background Art

[0002] In the autonomous driving scenario, a navigation path from the departure point to the destination is usually set for the vehicle. However, the user may manually intervene in the vehicle due to personalized driving route requirements, which triggers the reset of the navigation path when the vehicle deviates from the course. Based on this, after multiple autonomous driving completes a certain trip (that is, multiple trips with the same set of departure points and destinations), the vehicle side may save multiple navigation paths, which may have repeated paths or be inconsistent with the user's actual driving trajectory. Therefore, how to generate a navigation path with complete information and consistent with the user's driving trajectory has become one of the important technical issues in the relevant technical field.

[0003] To address the above-mentioned problems, no effective solution has been proposed yet. Summary of the invention

[0004] The embodiments of the present application provide a method, device, vehicle and storage medium for generating a full navigation path, so as to at least solve the technical problem that the navigation path generation method provided in the related art is difficult to adapt to personalized driving, resulting in poor accuracy of navigation path generation.

[0005] According to one aspect of an embodiment of the present application, a navigation path generation method is provided, including: obtaining driving trajectory data and first path data corresponding to a target trip, wherein the driving trajectory data is used to determine a vehicle driving trajectory corresponding to the target trip in a manual driving mode, and the first path data includes navigation data corresponding to a full navigation path of the target trip, and the full navigation path is planned according to a starting position and an end position of the target trip; performing matching analysis on the driving trajectory data and the first path data to obtain a matching result; performing data trimming on the driving trajectory data and the first path data according to the matching result to obtain a target trimming result; and generating a target navigation path based on the target trimming result.

[0006] Optionally, associating and matching the driving trajectory data and the first path data to obtain a matching result includes: based on the driving trajectory data, performing data removal processing on the first path data to obtain second path data; and associating and matching the driving trajectory data and the second path data to obtain a matching result.

[0007] Optionally, based on the driving trajectory data, the first path data is subjected to data removal processing to obtain the second path data, including: calculating the distance information between the trajectory points on the vehicle's driving trajectory and the line points on the full navigation path based on the driving trajectory data and the first path data; based on the distance information, determining the first confluence point and the second confluence point on the full navigation path, wherein the first confluence point corresponds to the starting point position and the second confluence point corresponds to the end point position; based on the first confluence point and the second confluence point, determining the navigation deviation data to be removed in the first path data; removing the navigation deviation data in the first path data to obtain the second path data.

[0008] Optionally, the first path data includes multiple groups of first data corresponding to multiple full navigation paths, the multiple full navigation paths are generated by triggering multiple driving deviation events in the target itinerary, and the second path data includes multiple groups of second data corresponding to the multiple groups of first data; the full navigation path generation method also includes: performing path comparison on the multiple full navigation paths along the direction from the starting position to the end position to determine multiple navigation convergence points; based on the positions of the multiple navigation convergence points, determining the navigation duplicate data to be removed from the multiple groups of first data; removing the navigation duplicate data from the multiple groups of first data to obtain multiple groups of second data, or removing the navigation duplicate data from the multiple groups of second data to update the multiple groups of second data.

[0009] Optionally, the second path data includes multiple groups of second data corresponding to multiple navigation sections; the driving trajectory data and the second path data are associated and matched to obtain matching results including: using the trajectory point positions corresponding to the driving trajectory data and the line point positions corresponding to the second path data to determine multiple matching point pairs corresponding to the multiple navigation sections, wherein each matching point pair includes a starting line point of a navigation section and a trajectory point on the vehicle's driving trajectory corresponding to the starting line point; based on the driving trajectory data, the second path data and the multiple matching point pairs, the matching results are determined, wherein the matching results are used to determine the same-road intervals and different-road intervals between the driving trajectory data and the second path data.

[0010] Optionally, based on the driving trajectory data, the second path data and multiple matching point pairs, determining the matching result includes: for any target matching point pair among the multiple matching point pairs, determining the distance information, mileage information and direction angle information of the target navigation section corresponding to the target matching point pair based on the driving trajectory data and the second path data; determining the same-road interval and different-road interval in the target navigation section according to the distance information, mileage information and direction angle information; determining the matching result based on the same-road interval and different-road interval corresponding to each navigation section among the multiple navigation sections.

[0011] Optionally, the target trimming result includes a first trimming result and a second trimming result; the driving trajectory data and the first path data are trimmed according to the matching result, and the target trimming result includes: determining the same-road section and the different-road section based on the matching result; trimming the driving trajectory data according to the different-road section to obtain the first trimming result; trimming the first path data according to the same-road section to obtain the second trimming result.

[0012] Optionally, based on the target clipping result, generating the target navigation path includes: performing splicing processing on the first clipping result and the second clipping result to obtain the target navigation path.

[0013] Optionally, splicing the first clipping result and the second clipping result to obtain the target navigation path includes: converting the format of the first clipping result to obtain different-route navigation data; and sequentially splicing the second clipping result and the different-route navigation data according to mileage information corresponding to the target trip to obtain the target navigation path.

[0014] Optionally, the full navigation path generation method also includes at least one of the following: utilizing the road semantic information corresponding to the first path data and the different-path navigation data to perform semantic splicing adjustments on the target navigation path and update the target navigation path; utilizing the road structure information corresponding to the first path data and the different-path navigation data to perform structural splicing adjustments on the partial navigation path in the target navigation path corresponding to the different-path navigation data and update the target navigation path.

[0015] According to another aspect of an embodiment of the present application, a navigation path generating device is also provided, including: an acquisition module, used to acquire driving trajectory data and first path data corresponding to a target trip, wherein the driving trajectory data is used to determine the vehicle driving trajectory corresponding to the target trip in a manual driving mode, and the first path data includes navigation data corresponding to the full navigation path of the target trip, and the full navigation path is planned according to the starting position and the end position of the target trip; a matching module, used to perform matching analysis on the driving trajectory data and the first path data to obtain a matching result; a trimming module, used to perform data trimming on the driving trajectory data and the first path data according to the matching result to obtain a target trimming result; and a generation module, used to generate a target navigation path based on the target trimming result.

[0016] According to another aspect of an embodiment of the present application, a vehicle is also provided, including an on-board memory and an on-board processor, wherein a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to execute any one of the above-mentioned navigation path generation methods.

[0017] According to another aspect of an embodiment of the present application, a computer-readable storage medium is further provided, the computer-readable storage medium including a stored executable program, wherein when the executable program is running, the device where the storage medium is located is controlled to execute any one of the above-mentioned navigation path generation methods.

[0018] According to another aspect of an embodiment of the present application, a computer program product is also provided, including a computer program, and when the computer program is executed by a processor, the navigation path generation method according to any one of the above items is implemented.

[0019] In an embodiment of the present application, firstly, the driving trajectory data and the first path data corresponding to the target trip are obtained, wherein the driving trajectory data is used to determine the vehicle driving trajectory corresponding to the target trip in the manual driving mode, and the first path data includes the navigation data corresponding to the full navigation path of the target trip, and the full navigation path is obtained according to the starting position and the end position of the target trip; further, the driving trajectory data and the first path data are matched and analyzed to obtain a matching result; the driving trajectory data and the first path data are data-cut according to the matching result to obtain a target cutting result; and based on the target cutting result, the target navigation path is generated. Thus, the present application achieves the purpose of cutting and merging the vehicle driving trajectory and the full navigation path to generate the target navigation path, thereby achieving the technical effect of improving the accuracy of the navigation path and the adaptability of the navigation path to the user's personalized driving path, thereby solving the technical problem that the navigation path generation method provided in the related art is difficult to adapt to personalized driving, resulting in poor accuracy of navigation path generation. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and the related descriptions of the embodiments are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0021] Figure 1 is a hardware structure block diagram of an optional computing terminal for implementing a navigation path generation method according to an embodiment of the present application;

[0022] Figure 2 is a flowchart of a navigation path generation method according to an embodiment of the present application;

[0023] Figure 3 is a schematic diagram of an optional vehicle driving trajectory according to an embodiment of the present application;

[0024] Figure 4 is a schematic diagram of an optional full navigation path according to an embodiment of the present application;

[0025] Figure 5is a schematic diagram of another optional full navigation path according to an embodiment of the present application;

[0026] Figure 6 is a schematic diagram of an optional data removal method according to an embodiment of the present application;

[0027] Figure 7 is a schematic diagram of another optional data removal method according to an embodiment of the present application;

[0028] Figure 8 is a schematic diagram of an optional association matching method according to an embodiment of the present application;

[0029] Fig. 9 It is a structural schematic diagram of a navigation path generating device according to an embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments only include a part of the embodiments of the present application, rather than all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0031] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0032] According to an embodiment of the present application, a method embodiment of a navigation path generation method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0033] First, the operating environment of the above method embodiment is exemplarily described. Figure 1is a hardware structure block diagram of a computing terminal for implementing a navigation path generation method according to an embodiment of the present application, such as Figure 1 As shown, a computing terminal 10 (for example, a computer terminal, a mobile smart terminal, a vehicle terminal, or a cloud computing virtual terminal, etc.) may include: one or more processors 102, a memory 104 for storing data, and a transmission device 106 for implementing a communication function, wherein each processor 102 may include but is not limited to a processing component such as a microprocessor (Microcontroller Unit, referred to as MCU) or a programmable logic device (Field Programmable Gate Array, referred to as FPGA).

[0034] The computing terminal 10 may further include: a display device 110, an input / output device 108, a Universal Serial Bus (USB) port (the USB port may be used as one of the ports of a computer bus, not shown in the figure), a network interface (not shown in the figure), a power supply (not shown in the figure) and a camera (not shown in the figure). A person skilled in the art may understand that Figure 1 The structure of the computing terminal 10 shown is only for illustration and does not impose a strict limitation on the structure of the computing terminal 10. For example, the computing terminal 10 may also include Figure 1 More or fewer components than those shown in FIG. 1 , or computing terminal 10 may have the same components as those shown in FIG. Figure 1 Different categories of components are shown.

[0035] It should be noted that the one or more processors 102 and / or other data processing circuits in the computing terminal 10 described above may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. In addition, the data processing circuit may be a single independent processing module, or may be incorporated in whole or in part into any of the other components in the computing terminal 10 (or mobile device).

[0036] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the navigation path generation method in the embodiment of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizing the above-mentioned navigation path generation method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the computing terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0037] The transmission device 106 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the computing terminal 10. In one example, the transmission device 106 includes a network adapter (Network Interface Controller, referred to as NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (Radio Frequency, referred to as RF) module, which is used to communicate with the Internet wirelessly.

[0038] Under the above operating environment, the embodiment of the present application provides the following Figure 2 The navigation path generation method shown, Figure 2 is a flowchart of a navigation path generation method according to an embodiment of the present application. Figure 2 As shown, the method includes the following implementation steps:

[0039] Step S201, obtaining driving trajectory data and first path data corresponding to the target trip, wherein the driving trajectory data is used to determine the vehicle driving trajectory corresponding to the target trip in the manual driving mode, and the first path data includes navigation data corresponding to the full navigation path of the target trip, and the full navigation path is planned according to the starting position and the end position of the target trip;

[0040] Step S202, performing matching analysis on the driving trajectory data and the first path data to obtain a matching result;

[0041] Step S203, performing data trimming on the driving trajectory data and the first path data according to the matching result to obtain a target trimming result;

[0042] Step S204: generating a target navigation path based on the target clipping result.

[0043] The target trip is a vehicle driving trip determined by a preset starting point and an end point. In the application scenario, the user can drive the vehicle at least once in the manual driving mode to complete the target trip, or can control the vehicle at least once in the automatic driving mode to complete the target trip.

[0044] The above driving trajectory data is the vehicle driving trajectory determined by the user in the manual driving mode when driving the vehicle to the target trip. The vehicle driving trajectory may include personalized driving routes corresponding to the user's personalized needs. These personalized driving routes may be inconsistent with the navigation path of the pre-generated target trip. These inconsistent partial personalized driving routes can also be regarded as the user's active deviation route.

[0045] The first path data may include navigation data corresponding to a full navigation path pre-planned based on the target trip. In particular, the first path data may include multiple sets of navigation data corresponding to multiple full navigation paths, where the multiple full navigation paths are obtained by performing multiple path planning for the starting position and the end position of the target trip.

[0046] The above matching results are used to characterize the same path part and different path part between the driving trajectory data and the first path data. The same path part is the partial data where the full navigation path matches the vehicle driving trajectory, and the different path part is the partial data where the full navigation path does not match the vehicle driving trajectory.

[0047] The driving trajectory data and the first path data can be stored in a continuous data format, respectively. The target clipping result includes multiple segments of data obtained by clipping the driving trajectory data according to the matching result and multiple segments of data obtained by clipping the first path data according to the matching result. Based on this, the driving trajectory data and the first path data can be used differently for the same path part and the different path parts, thereby obtaining the target navigation path. For example, a data segment in the first path data is selected in the same path part, and a data segment in the driving trajectory data is selected in the different path parts, and then the selected data segments are spliced ​​to obtain the target navigation path.

[0048] Since the full navigation data can contain richer and more comprehensive navigation-related information, and the driving trajectory data can represent the personalized needs of users when making a target trip, in the above-mentioned real-time steps of the embodiment of the present application, when generating a target navigation path, the full navigation data and the driving trajectory data are comprehensively considered according to the matching results, so that the generated target navigation path can provide a target navigation path that not only better meets the user's personalized driving needs, but also has more comprehensive data. This improves the intelligence level of vehicle autonomous driving, enhances user experience, and improves vehicle safety.

[0049] Through the technical solutions provided by the above steps S201 to S204, the present application achieves the purpose of clipping and merging the vehicle driving trajectory and the full navigation path to generate a target navigation path, thereby achieving the technical effect of improving the accuracy of the navigation path and the adaptability of the navigation path to the user's personalized driving path, and further solves the technical problem that the navigation path generation method provided in the related art is difficult to adapt to personalized driving, resulting in poor accuracy of navigation path generation.

[0050] The above implementation steps provided in the embodiment of the present application are mainly applicable to the field of autonomous driving technology, and can play an important role in the task of establishing cloud navigation maps in specific application scenarios. In the process of establishing a cloud navigation map, the cloud server obtains the vehicle driving trajectory corresponding to the target trip in the manual driving mode to determine the personalized needs of the user in the target trip, and obtains the navigation data corresponding to the full navigation path given by the navigation system in the process of the vehicle completing the target trip multiple times in the driving history. Further, the cloud server matches, trims and splices the vehicle driving trajectory and multiple full navigation paths according to the scheme provided in the embodiment of the present application, generates a target navigation path corresponding to the target trip, and then stores the target navigation path corresponding to the target trip in the cloud navigation map. The above target navigation path is a complete full navigation path corresponding to the target trip, which keeps the same route as the above vehicle driving trajectory, meets the personalized needs of the user, and can also contain as much full navigation data as possible. After the cloud navigation map is established, when the vehicle needs to perform automatic driving for the target trip again, the cloud will send the target navigation path to the vehicle, so that the vehicle can provide the full navigation information to the user through the central control display, and can also help the vehicle make more accurate and more user-friendly automatic driving decisions. The above specific application scenarios can be, but are not limited to, the following application scenarios.

[0051] In the artificial intelligence (AI) driving service scenario, the above method steps can generate a full navigation path with complete information and in line with the user's driving trajectory based on the personalized driving habits and preferences of the user in the learning stage, ensuring that the AI ​​driving process can follow the customer's specific route requirements and improve customer satisfaction.

[0052] In the path planning scenarios of autonomous driving vehicles, especially in complex urban environments or specific scenarios (such as industrial parks, residential areas, etc.), the above method steps can generate a full navigation path that is more in line with actual road conditions and user preferences by analyzing the user's actual driving trajectory, thereby improving the safety and user experience of autonomous driving.

[0053] In the map data update and optimization scenario, for map service providers, the above method steps can optimize and update the full amount of navigation paths in the map by analyzing the actual driving trajectories of a large number of users, remove unnecessary duplicate path information, and improve the accuracy and practicality of map data.

[0054] In the vehicle navigation system upgrade scenario, the above method steps can help vehicle manufacturers and navigation system providers upgrade existing vehicle navigation systems, enabling the vehicle navigation system to dynamically generate a full navigation path based on the user's personalized needs, thereby enhancing the intelligence and flexibility of the vehicle navigation system.

[0055] In the application scenario of Intelligent Transportation System (ITS), the above method and steps can be used to optimize the driving route of vehicles, especially in situations such as traffic congestion or road construction, by analyzing historical driving trajectories and generating full navigation paths to plan a more reasonable and efficient driving route for the vehicle. In the management and dispatching scenario of fleets (such as logistics transport fleets, taxi fleets, etc.), the above method and steps can generate full navigation paths based on the actual driving habits of drivers, provide optimized driving routes for vehicles in the fleet, improve the operating efficiency of the fleet, and reduce unnecessary fuel consumption and time waste.

[0056] The following uses the AI ​​​​designated driving application scenario as an example to further illustrate other optional implementation methods of the above method provided in the embodiment of the present application.

[0057] AI driving is a service that uses artificial intelligence technology to achieve automatic driving of vehicles. Through the artificial intelligence system installed in the vehicle, the vehicle can automatically drive, avoid obstacles, and comply with traffic rules. AI driving technology can reduce traffic accidents caused by human factors and improve driving safety and efficiency. AI driving can also provide convenient and safe vehicle driving services for people who have difficulty driving (such as the elderly, the disabled, or drunk drivers).

[0058] AI driving can be a function provided by an autonomous driving vehicle equipped with an AI driving system. The AI ​​driving system continuously optimizes its own driving route during the route learning stage, and improves driving skills and planning capabilities through practice and feedback. First, the AI ​​driving system uses maps and road conditions information to plan the navigation route to be used, and then collects surrounding environment data (such as road conditions, traffic conditions, pedestrian information, and vehicle information, etc.) in actual driving to adjust and optimize the navigation route to ensure vehicle safety and efficient driving. In addition, the AI ​​driving system improves route planning capabilities based on feedback information during actual driving. For example, driving behavior is analyzed based on driving records and event data during driving to achieve improvements. The executor of the above-mentioned method steps provided in the embodiment of the present application can be the above-mentioned autonomous driving vehicle or the above-mentioned AI driving system.

[0059] In the AI ​​chauffeur application scenario, according to the above-mentioned full navigation path generation method, the navigation path generation is achieved by cutting and splicing the full navigation path and the driving trajectory of the user's learning stage. Specifically, referring to the user's personalized driving trajectory in the learning stage, multiple full navigation paths are cut, processed and spliced ​​to obtain a user-customized navigation path that conforms to the driving trajectory and has complete navigation information.

[0060] As an optional implementation, in the above step S202, the driving trajectory data and the first path data are associated and matched to obtain a matching result, which may also include the following execution steps:

[0061] Step S221, based on the driving trajectory data, performing data removal processing on the first path data to obtain second path data;

[0062] Step S222: performing association matching on the driving trajectory data and the second path data to obtain a matching result.

[0063] In the application scenario, in a part of the target journey, even if there may be a large error between the first path data and the driving trajectory data, the association and matching of the driving trajectory data and the first path data in this part of the journey can be ignored. For example, in the interval when the target journey just begins or is about to end, the driving conditions of the vehicle are usually more complicated, and the user's driving needs will also vary a lot. Therefore, the part of the data corresponding to the beginning and end of the full navigation path in the first path data is removed to obtain the second path data. Furthermore, the second path data after the data is removed is associated and matched with the driving trajectory data to obtain a matching result.

[0064] Through the technical solution provided by the above steps S221 to S222, the embodiment of the present application removes part of the data in the full navigation data before performing association matching, thereby avoiding the influence of this part of the data on the association matching, ensuring that the matching results obtained can accurately represent the same-road intervals and different-road intervals, and further ensuring the accuracy of clipping and splicing in the full navigation path generation method.

[0065] As an optional implementation, in the above step S221, based on the driving trajectory data, the first path data is subjected to data removal processing to obtain the second path data, which may further include the following execution steps:

[0066] Step S2211, calculating the distance information between the track point on the vehicle driving track and the line point on the full navigation path according to the driving track data and the first path data;

[0067] Step S2212, based on the distance information, determining a first meeting point and a second meeting point on the full navigation path, wherein the first meeting point corresponds to the starting point, and the second meeting point corresponds to the ending point;

[0068] Step S2213, determining navigation deviation data to be removed from the first path data based on the first confluence point and the second confluence point;

[0069] Step S2214: remove the navigation deviation data in the first path data to obtain the second path data.

[0070] When the distance between a track point on the vehicle's driving track and a line point on the full navigation path is less than a preset threshold, the vehicle's driving track is considered to merge with the full navigation path, and the line point can be considered to be successfully matched with the track point, and the line point is regarded as a convergence point. There may be multiple convergence points on the full navigation path, the first convergence point is the convergence point closest to the starting point among the multiple convergence points, and the second convergence point is the convergence point closest to the end point among the multiple convergence points.

[0071] Furthermore, the portion of the full navigation path from the starting point to the first meeting point is determined as the starting interval, the portion of the full navigation path from the second meeting point to the end point is determined as the ending interval, and partial data in the first path data corresponding to the starting interval and the ending interval are determined as navigation deviation data, and these navigation deviation data are removed from the first path data to obtain second path data.

[0072] Through the technical solution provided by the above steps S2211 to S2214, the embodiment of the present application determines the navigation deviation data to be removed from the first path data by determining the meeting point positions near the starting point position and the end point position before associating and matching the driving trajectory data and the first path data, thereby avoiding the influence of yaw at the beginning and end of the target journey on the path generation and improving the accuracy of the target navigation path generation.

[0073] As an optional implementation, the first path data includes multiple groups of first data corresponding to multiple full navigation paths, the multiple full navigation paths are generated by triggering multiple driving deviation events in the target trip, and the second path data includes multiple groups of second data corresponding to the multiple groups of first data; the above navigation path generation method may also include the following execution steps:

[0074] Step S251, performing path comparison on a plurality of full navigation paths along the direction from the starting position to the end position, and determining a plurality of navigation convergence points;

[0075] Step S252, determining the navigation duplicate data to be removed from the multiple sets of first data based on the positions of the multiple navigation convergence points;

[0076] Step S253: remove the repeated navigation data from the multiple sets of first data to obtain multiple sets of second data, or remove the repeated navigation data from the multiple sets of second data to update the multiple sets of second data.

[0077] The navigation convergence point is a convergence point between multiple full navigation paths. For example, if multiple full navigation paths are consistent in a certain section, then multiple points in this section are navigation convergence points, and the navigation data corresponding to this section in multiple sets of first data is determined as navigation duplicate data.

[0078] Through the technical solutions provided by the above steps S251 to S253, in the process of associating and matching the driving trajectory data and the first path data, the embodiment of the present application can consider multiple full navigation paths, and remove the duplicate navigation data between these full navigation path data, so that these duplicate navigation data are ignored in the second path data, and subsequent associative matching is performed based on the differences between the multiple full navigation paths, thereby achieving further reduction of path generation calculation amount and improving efficiency while ensuring that the generated target navigation path is consistent with the vehicle's driving trajectory.

[0079] Taking the AI ​​driving application scenario as an example, the vehicle driving trajectory recorded by the user completing the target trip in manual driving mode is as follows: Figure 3 As shown, when a user's driving deviation event triggers path planning, the first full navigation path obtained for the target trip planning is as follows: Figure 4 As shown, when another user's driving deviation event triggers path planning, the second full navigation path obtained for the target trip planning is as follows: Figure 5 The first path data includes first initial navigation data (ie, a set of first data) corresponding to the first full navigation path and second initial navigation data (ie, another set of first data) corresponding to the second full navigation path.

[0080] like Figure 3 , Figure 4 and Figure 5 As shown, within the range close to the starting position and the end position of the target trip, both the first full navigation path and the second navigation path are inconsistent with the vehicle's driving trajectory. At this time, part of the initial navigation data corresponding to the range close to the starting position and the end position in the first initial navigation data can be removed to obtain first intermediate navigation data (that is, a group of second data), and part of the initial navigation data corresponding to the range close to the starting position and the end position in the second initial navigation data can be removed to obtain second intermediate navigation data (that is, another group of second data).

[0081] Specifically, for each section of the full navigation path, the line point closest to the vehicle's driving trajectory on the full navigation path is searched from the starting position as the first convergence point. The specific implementation method of the above search can be: starting from the starting position, traversing the line points, for each line point, calculating the minimum Euclidean distance between the line point and the trajectory point on the vehicle's driving trajectory, calculating the angle between the navigation direction of the line point on the full navigation trajectory and the formal direction of the corresponding trajectory point on the vehicle's driving trajectory, and determining the first convergence point from multiple line points based on the minimum Euclidean distance and angle information of each line point. The distance between the first convergence point and the corresponding trajectory point (that is, the trajectory point with the smallest Euclidean distance from the first convergence point among multiple trajectory points) is less than a preset distance threshold and the corresponding angle is less than a preset angle threshold. Similarly, for each section of the full navigation path, starting from the end position, the line point closest to the vehicle's driving trajectory on the full navigation path is searched as the second convergence point.

[0082] Further, as Figure 4 Take the first full navigation path shown as an example, follow the Figure 6 The first full navigation path is processed in a data removal manner. The navigation path data corresponding to the section from the starting point to the first meeting point on the first full navigation path is determined as a part of the navigation deviation data to be removed in the first initial navigation data, and the navigation path data corresponding to the section from the second meeting point to the end point on the first full navigation path is determined as another part of the navigation deviation data to be removed in the first initial navigation data. Then, these navigation deviation data are removed from the first initial navigation data to obtain the first intermediate navigation data, which is the navigation data corresponding to the first full navigation path after removing the head and tail. Similarly, the corresponding navigation deviation data is removed from the second initial navigation data to obtain the second intermediate navigation data, which is the navigation data corresponding to the second full navigation path after removing the head and tail.

[0083] Further, according to Figure 7 The data removal method shown processes the first full navigation path (or the first full navigation path after removing the head and tail) and the second full navigation path (or the second full navigation path after removing the head and tail). Figure 4 and Figure 5 Compare the two full navigation paths shown in the figure to determine multiple navigation convergence points ( Figure 7After that, the part of the first full navigation path that is identical to the second full navigation path is further determined to obtain a navigation duplicate section. The navigation duplicate data corresponding to the navigation duplicate section is deleted from the first initial navigation data (which can also be the first intermediate navigation data) to obtain first target navigation data, which corresponds to the first full navigation path after deduplication. The first target navigation data can be used as a set of second data in the second path data. Similarly, the navigation duplicate data corresponding to the navigation duplicate section is deleted from the second initial navigation data (which can also be the second intermediate navigation data) to obtain second target navigation data, which corresponds to the second full navigation path after deduplication. The second target navigation data can be used as another set of second data in the second path data.

[0084] Through the above Figure 6 and / or Figure 7 The data removal method shown preprocesses multiple groups of first data corresponding to multiple full navigation paths in the first path data to obtain second path data, that is, completes the preprocessing process of the first path data, which not only avoids the influence of inconsistency between the full navigation path and the vehicle driving trajectory within the range of the beginning and the end of the target journey, but also solves the path duplication problem between multiple full navigation paths.

[0085] As an optional implementation, the second path data includes multiple sets of second data corresponding to multiple navigation sections; in the above step S222, the driving trajectory data and the second path data are associated and matched to obtain a matching result, and the following execution steps may also be included:

[0086] Step S2221, using the track point position corresponding to the driving track data and the line point position corresponding to the second path data, determining a plurality of matching point pairs corresponding to the plurality of navigation sections, wherein each matching point pair includes a starting line point of a navigation section and a track point on the vehicle driving track corresponding to the starting line point;

[0087] Step S2222: determining a matching result based on the driving trajectory data, the second path data and a plurality of matching point pairs, wherein the matching result is used to determine a same-road section and a different-road section between the driving trajectory data and the second path data.

[0088] The driving trajectory data includes trajectory information and driving information corresponding to multiple trajectory points on the vehicle's driving trajectory, for example, the trajectory information includes the location of the trajectory point, and the driving information includes the mileage and driving direction corresponding to the trajectory point. The second path data includes navigation information and path information corresponding to multiple travel points on the full navigation path, for example, the navigation information includes the navigation direction, navigation mileage, etc., and the path information includes the location of the travel point, etc. Further, using the driving trajectory data and the second path data, multiple matching point pairs corresponding to multiple navigation sections are determined. Using each matching point pair and the driving trajectory data and the second path data, the same-road interval and the different-road interval in each navigation section can be determined, the same-road interval indicates that the full navigation path in the navigation section is consistent with the vehicle's driving trajectory route (or the deviation is less than a preset threshold), and the different-road interval indicates that the full navigation path in the navigation section is inconsistent with the vehicle's driving trajectory route (or the deviation exceeds a preset threshold).

[0089] Through the technical solution provided by the above steps S2221 to S2222, in the process of associating and matching the driving trajectory data and the first path data, the embodiment of the present application determines the same-road intervals and different-road intervals corresponding to the vehicle driving trajectory and the full navigation path by matching the trajectory points on the vehicle driving trajectory with the line points on the full navigation path, so that in the process of generating the target navigation path, the same-road intervals and different-road intervals can be processed differently and targetedly to ensure the information integrity and trajectory consistency of the target navigation path.

[0090] As an optional implementation, in the above step S2222, determining the matching result based on the driving trajectory data, the second path data and the plurality of matching point pairs may further include the following execution steps:

[0091] Step S2223, for any one target matching point pair among the multiple matching point pairs, based on the driving trajectory data and the second path data, determining the distance information, mileage information and direction angle information of the target navigation section corresponding to the target matching point pair;

[0092] Step S2224, determining the same-road section and the different-road section in the target navigation section according to the distance information, the mileage information and the direction angle information;

[0093] Step S2225: determining a matching result based on the same-road section and the different-road section corresponding to each of the multiple navigation sections.

[0094] In the AI ​​driving application scenario, the following specific implementation method can be adopted to achieve the determination of the matching result based on the driving trajectory data, the second path data and multiple matching point pairs. The above-mentioned multiple navigation sections can be multiple full navigation paths after removing the head and tail data and / or removing duplicate data from the second path data obtained by the aforementioned preprocessing. For each navigation section, first, find the trajectory point with the smallest Euclidean distance between the starting point of the navigation section (that is, the starting line point) on the vehicle driving trajectory, and establish a matching relationship between the starting line point and the trajectory point. Then, on the navigation section, the line point traversal is performed from the starting line point to the end point of the navigation section (that is, the ending line point). For each line point in the traversal, the line point distance information between the line point and the next line point is calculated, and the distance information is accumulated with the distance information of multiple line points traversed on the navigation section to obtain the cumulative navigation mileage. Similarly, the trajectory point matched by each line point in the traversal is calculated to obtain the trajectory point distance information corresponding to the trajectory point, and the cumulative trajectory mileage is accumulated. Furthermore, for the current row point in the traversal, if the distance between the current row point and the matched trajectory point is less than a first threshold value (for example, 3 meters), the difference between the cumulative navigation mileage corresponding to the current row point and the cumulative trajectory mileage corresponding to the matched trajectory point is less than a second threshold value (for example, 30 meters), and the angle between the navigation direction corresponding to the current row point and the trajectory direction corresponding to the matched trajectory point is less than a third threshold value (for example, 10°), then it can be determined that the path subsegment between the current row point and the next row point belongs to the same road interval; otherwise, the path subsegment is considered to belong to a different road interval, that is, the full navigation path and the vehicle driving trajectory are forked.

[0095] Specifically, in the above application scenario, taking the second full navigation path after deduplication as an example, according to the following Figure 8 The associative matching method shown is used to determine the matching result. The second full navigation path after deduplication is compared with the vehicle driving trajectory to determine the same-road interval and the different-road interval in the second full navigation path after deduplication. The above matching results are used to determine the data range corresponding to the same-road interval and the different-road interval in the second path data. Furthermore, the bifurcation line point between the same-road interval and the different-road interval is determined in the second full navigation path after deduplication, and a matching relationship is established between multiple line points in the same-road interval and the corresponding trajectory points.

[0096] Further, after the full navigation path and the vehicle driving track are bifurcated, the position on the full navigation path where the vehicle driving track is reunited is searched. For example, the line points after the bifurcated line point on the full navigation path are traversed. When it is found that the distance between the current line point and the corresponding track point on the vehicle driving track is less than the first threshold value (such as 3 meters) and the direction angle between the current line point and the track point is less than the third threshold value (such as 10°), the current line point can be determined as the position of reunion, and the current line point is used as the starting line point of the next section of the same road interval. The above scheme for determining the same road interval is repeated, that is, the line points are traversed until the next bifurcated line point is found, the next section of the same road interval is determined, and the next reunion position is started. In this way, multiple converging points and multiple bifurcating points on the full navigation path can be recorded. In order, the first converging point to the first bifurcating point is the first same road interval, the first bifurcating point to the second converging point is the first different road interval, and so on.

[0097] Through the technical solutions provided by the above steps S2223 to S2225, in the process of position matching the track points on the vehicle's driving track with the line points on the full navigation path, the embodiment of the present application takes into account the distance between the track points and the line points, the mileage of the target trip corresponding to the track points and the line points, and the direction angle information corresponding to the track points and the line points in a relatively comprehensive manner, and can relatively accurately establish a matching relationship between the track points and the line points, thereby ensuring the accuracy of the determined same-road sections and different-road sections.

[0098] As an optional implementation, the target clipping result includes a first clipping result and a second clipping result; in the above step S203, the driving trajectory data and the first path data are clipped according to the matching result to obtain the target clipping result, and the following execution steps may also be included:

[0099] Step S231, determining the same-path section and the different-path section based on the matching result;

[0100] Step S232, cutting the driving trajectory data according to the different road section to obtain a first cutting result;

[0101] Step S233, trimming the first path data according to the same path section to obtain a second trimming result.

[0102] In the application scenario, still taking the second full navigation path as an example, according to the different road sections on the second full navigation path, the driving trajectory data corresponding to the vehicle driving trajectory is clipped to obtain partial trajectory data corresponding to the above different road sections, and obtain a first clipping result. According to the same road section on the second full navigation path, the first path data (which can also be the second path data obtained by preprocessing) corresponding to the second full navigation path data is clipped to obtain partial path data corresponding to the above same road section, and obtain a second clipping result.

[0103] Through the technical solution provided by the above steps S231 to S233, in the process of data trimming of the driving trajectory data and the first path data, the embodiment of the present application takes into account the same-road interval and different-road interval determined by matching the driving trajectory data and the first path data, and trims and obtains the partial data corresponding to the driving trajectory data in the different-road interval (that is, the first trimming result), and trims and obtains the partial data corresponding to the first path data in the same-road interval (that is, the second trimming result), thereby ensuring that more comprehensive full navigation path data in the first path data is obtained in the same-road interval, and driving trajectory data that is closer to the user's personalized driving needs is obtained in the different-road interval. Based on this, the target navigation path generated according to the first trimming result and the second trimming result can take into account both information comprehensiveness and trajectory consistency.

[0104] As an optional implementation, in the above step S204, generating a target navigation path based on the target clipping result may further include the following execution steps:

[0105] Step S241, splicing the first clipping result and the second clipping result to obtain a target navigation path.

[0106] In the application scenario, still taking the second full navigation path as an example, according to the mileage information corresponding to the target trip, the partial track data in the first trimming result and the partial path data in the second trimming result are sorted, and then the first trimming result and the second trimming result are spliced ​​to obtain the target navigation path. Specifically, the partial track data and the partial path data are spliced ​​in the order of mileage to obtain the target navigation data, and the target navigation data is used to determine the target navigation path.

[0107] Through the technical solution provided by the above step S241, the embodiment of the present application splices the first clipping result and the second clipping result to obtain a complete target navigation path corresponding to the target trip. The target navigation path navigation is used to provide navigation for the vehicle for the target trip, which can take into account the user's personalized driving trajectory requirements and the vehicle safety requirements guaranteed by complete and comprehensive navigation data.

[0108] As an optional implementation, in the above step S241, the first clipping result and the second clipping result are spliced ​​to obtain the target navigation path, which may also include the following execution steps:

[0109] Step S242, converting the format of the first clipping result to obtain different-route navigation data;

[0110] Step S243: sequentially splicing the second clipping result and the different-route navigation data according to the mileage information corresponding to the target journey to obtain the target navigation route.

[0111] In the application scenario, when generating a target navigation path, it is necessary to obtain target navigation data that is consistent with the vehicle's driving trajectory route. The target navigation data includes same-route navigation data and different-route navigation data. The partial path data in the second clipping result can be used as same-route navigation data, and the different-route navigation data is obtained by format conversion of the partial trajectory data in the first clipping result. Specifically, the partial trajectory data is converted into the full navigation data format, and the full navigation path data that is consistent with the vehicle's driving trajectory route corresponding to the partial trajectory data is obtained as different-route navigation data. Based on this, the same-route navigation data and the different-route navigation data are sequentially spliced ​​to obtain the target navigation data, and the target navigation path is generated based on the target navigation data.

[0112] It should be noted that the partial path data in the second clipping result may contain multiple full navigation sections. Before these full navigation sections are sorted according to mileage information, these full navigation sections can be deduplicated. Furthermore, after these full navigation sections are arranged in order, the different road section between the end point of a full navigation section (corresponding to a same road section) and the start point of the next full navigation section (corresponding to the next same road section) can be used as the part that needs to be supplemented with vehicle driving trajectory, that is, the different road section.

[0113] It should be noted that the first path data corresponding to the above-mentioned full navigation path at least includes the road structure information and road semantic information corresponding to the target journey, and may also include other interactive information related to navigation. The driving trajectory data corresponding to the vehicle driving trajectory at least includes the trajectory point location information, and the data comprehensiveness of the driving trajectory data is usually lower than the data comprehensiveness of the first path data. Based on this, in the process of converting the first clipping result into the different-road navigation data, the road structure information and road semantic information corresponding to the different-road interval are added to the first clipping result.

[0114] Furthermore, in addition to obtaining the off-road navigation data through data format conversion, the full navigation data corresponding to the target itinerary stored in the database may be used to search for a full navigation segment that matches the partial driving trajectory of the off-road section, and use the full navigation segment as the off-road navigation data corresponding to the partial driving trajectory. For example, it is required that the distance between the navigation path corresponding to the matching full navigation segment and the partial driving trajectory is less than 5 meters and the direction angle is less than 10°. Furthermore, the road semantic information and road structure information of the full navigation segment are added to the data corresponding to the partial driving trajectory in the first clipping result to obtain the off-road navigation data corresponding to the partial driving trajectory. In other words, the off-road navigation data may include a first portion of data obtained by converting the vehicle driving trajectory through the data format, and may also include a second portion of data selected from the full navigation database based on the partial driving trajectory.

[0115] It should be noted that in order to ensure that the off-road navigation data contains more comprehensive full navigation information as much as possible, after generating the target navigation path, the full navigation database can be further searched for a matching full navigation fragment in the first part of the data in the off-road navigation data. If the full navigation fragment corresponding to the first part of the data is found, the full navigation fragment is used to replace the first part of the data.

[0116] Through the technical solution provided by the above steps S242 to S243, in the process of splicing the first trimmed result and the second trimmed result, the embodiment of the present application converts part of the driving trajectory data in the first trimmed result into off-road navigation data with more comprehensive information, and also makes the off-road navigation data and part of the full navigation path data in the second trimmed result have the same splicing dimension, and then sequentially splices the second trimmed result and the off-road navigation data according to the mileage information, thereby ensuring the sequential correctness of the target navigation path.

[0117] As an optional implementation, the navigation path generation method may further include at least one of the following execution steps:

[0118] Step S261, using the first path data and the road semantic information corresponding to the different-road navigation data, semantically splicing and adjusting the target navigation path, and updating the target navigation path;

[0119] Step S262: Using the road structure information corresponding to the first path data and the different-route navigation data, structural splicing and adjustment are performed on the partial navigation path corresponding to the different-route navigation data in the target navigation path, so as to update the target navigation path.

[0120] In the above application scenario, after the target navigation path is generated, the target navigation data corresponding to the target navigation path is semantically spliced ​​and verified according to the road semantic information contained in the same-route navigation data in the first path data and the road semantic information obtained by format conversion in the different-route navigation data, and a semantic verification result is obtained. According to the semantic verification result, the target navigation data is semantically spliced ​​and adjusted, and the target navigation path is regenerated and updated using the adjusted target navigation data. Similarly, the target navigation path can be verified and updated according to the road structure information.

[0121] Through the technical solutions provided by the above steps S261 to S264, after generating the target navigation path, the embodiment of the present application also verifies, adjusts and replaces the target navigation path according to the road semantic information and the road structure information, so that the updated target navigation path is more accurate.

[0122] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0123] It should be noted that, for the above method embodiments, for the sake of simplicity, the technical solutions in the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of actions in the described action combinations, because according to the present application, some of the above steps can be performed in other orders or simultaneously. In addition, those skilled in the art should also be aware that the embodiments described in the specification of this application belong to preferred embodiments, and the actions and modules involved are not necessarily necessary to implement the technical solutions of the present application.

[0124] According to an embodiment of the present invention, a device embodiment of a navigation path generation device is also provided, and the navigation path generation device is used to implement the above method embodiment and various optional implementation methods of the method embodiment, and the technical content that has been described in the previous text is no longer repeated in the device embodiment. It should be noted that in the following related descriptions of the device embodiment, a "module" can be software, hardware, or a combination of software and hardware for implementing a specified function.

[0125] Fig. 9 is a structural diagram of a navigation path generating device according to an embodiment of the present application, such as Fig. 9As shown, the device includes: an acquisition module 901, which is used to acquire driving trajectory data and first path data corresponding to the target trip, wherein the driving trajectory data is used to determine the vehicle driving trajectory corresponding to the target trip in the manual driving mode, and the first path data includes navigation data corresponding to the full navigation path of the target trip, and the full navigation path is planned according to the starting position and the end position of the target trip; a matching module 902, which is used to match and analyze the driving trajectory data and the first path data to obtain a matching result; a trimming module 903, which is used to perform data trimming on the driving trajectory data and the first path data according to the matching result to obtain a target trimming result; a generation module 904, which is used to generate a target navigation path based on the target trimming result.

[0126] Optionally, the matching module 902 is further used to: based on the driving trajectory data, perform data removal processing on the first path data to obtain second path data; and perform association matching on the driving trajectory data and the second path data to obtain a matching result.

[0127] Optionally, the matching module 902 is also used to: calculate the distance information between the trajectory points on the vehicle's driving trajectory and the line points on the full navigation path based on the driving trajectory data and the first path data; determine the first confluence point and the second confluence point on the full navigation path based on the distance information, wherein the first confluence point corresponds to the starting point position and the second confluence point corresponds to the end point position; determine the navigation deviation data to be removed in the first path data based on the first confluence point and the second confluence point; remove the navigation deviation data in the first path data to obtain the second path data.

[0128] Optionally, the first path data includes multiple groups of first data corresponding to multiple full navigation paths, and the multiple full navigation paths are generated by triggering multiple driving deviation events in the target itinerary; the second path data includes multiple groups of second data corresponding to the multiple groups of first data; the above-mentioned navigation path generation device includes, in addition to all the above-mentioned modules, further comprising: a deduplication module (not shown in the figure), which is used to perform path comparison on the multiple full navigation paths along the direction from the starting position to the end position, determine multiple navigation convergence points, determine the navigation duplicate data to be removed from the multiple groups of first data based on the positions of the multiple navigation convergence points, and remove the navigation duplicate data from the multiple groups of first data to obtain multiple groups of second data, or remove the navigation duplicate data from the multiple groups of second data to update the multiple groups of second data.

[0129] Optionally, the second path data includes multiple groups of second data corresponding to multiple navigation sections; the above-mentioned matching module 902 is also used to: use the trajectory point positions corresponding to the driving trajectory data and the line point positions corresponding to the second path data to determine multiple matching point pairs corresponding to the multiple navigation sections, wherein each matching point pair includes a starting line point of a navigation section and a trajectory point on the vehicle driving trajectory corresponding to the starting line point; based on the driving trajectory data, the second path data and the multiple matching point pairs, determine the matching result, wherein the matching result is used to determine the same-road interval and different-road interval between the driving trajectory data and the second path data.

[0130] Optionally, the above-mentioned matching module 902 is also used to: determine the distance information, mileage information and direction angle information of the target navigation section corresponding to the target matching point pair for any one target matching point pair among the multiple matching point pairs based on the driving trajectory data and the second path data; determine the same-road interval and different-road interval in the target navigation section according to the distance information, mileage information and direction angle information; determine the matching result based on the same-road interval and different-road interval corresponding to each navigation section among the multiple navigation sections.

[0131] Optionally, the target trimming result includes a first trimming result and a second trimming result; the above-mentioned trimming module 903 is also used to: determine the same-road section and the different-road section based on the matching result; trim the driving trajectory data according to the different-road section to obtain the first trimming result; trim the first path data according to the same-road section to obtain the second trimming result.

[0132] Optionally, the generating module 904 is further configured to: perform splicing processing on the first clipping result and the second clipping result to obtain a target navigation path.

[0133] Optionally, the generation module 904 is further used to: convert the format of the first clipping result to obtain the different-route navigation data; and sequentially splice the second clipping result and the different-route navigation data according to the mileage information corresponding to the target trip to obtain the target navigation path.

[0134] Optionally, in addition to all the above-mentioned modules, the above-mentioned navigation path generating device also includes: an updating module (not shown in the figure), which is used to: utilize the road semantic information corresponding to the first path data and the different-road navigation data to perform semantic splicing adjustment on the target navigation path, and update the target navigation path; and utilize the road structure information corresponding to the first path data and the different-road navigation data to perform structural splicing adjustment on the part of the navigation path in the target navigation path corresponding to the different-road navigation data, and update the target navigation path.

[0135] It should be noted that the above-mentioned acquisition module 901, matching module 902, trimming module 903 and generation module 904 correspond to steps S201 to S204 in the method embodiment. The four modules are the same as the instances and application scenarios implemented by the corresponding steps, but are not limited to the contents disclosed in the above-mentioned method embodiment.

[0136] It should be noted that the various modules mentioned in the above device embodiments can be implemented by software, hardware, or a combination of software and hardware. For example, when hardware is used to implement the above modules, the various modules can be set in the same processor, or the various modules can be set in different processors in any combination. For another example, the above modules can be hardware components or software components stored in a memory and processed by one or more processors, or the above modules can also be run as part of the device on a processor such as a processor. Figure 1 In the computing terminal 10 shown.

[0137] According to an embodiment of the present invention, there is also provided an embodiment of a vehicle, which includes an on-board memory and an on-board processor, wherein a computer program is stored in the on-board memory, and the on-board processor is configured to run the computer program to implement the above-mentioned navigation path generation method.

[0138] According to an embodiment of the present invention, a computer-readable storage medium is further provided. The computer-readable storage medium includes a stored program, wherein when the program is executed, the device where the computer-readable storage medium is located is controlled to implement the above-mentioned navigation path generation method.

[0139] Optionally, the above-mentioned computer storage media may include but are not limited to: hard disk drive (HDD), solid state drive (SSD), USB flash drive, optical disk, memory card, cloud storage media and network storage device (NAS).

[0140] Optionally, the computer-readable storage medium may be configured to store a computer program for executing the following steps: obtaining driving trajectory data and first path data corresponding to a target trip, wherein the driving trajectory data is used to determine a vehicle driving trajectory corresponding to the target trip in a manual driving mode, and the first path data includes navigation data corresponding to a full navigation path of the target trip, and the full navigation path is planned based on a starting position and an end position of the target trip; performing matching analysis on the driving trajectory data and the first path data to obtain a matching result; performing data trimming on the driving trajectory data and the first path data according to the matching result to obtain a target trimming result; and generating a target navigation path based on the target trimming result.

[0141] According to an embodiment of the present invention, a computer program product is also provided. The computer program product includes a computer program, and when the computer program is executed by a processor, the above navigation path generation method can be implemented.

[0142] Optionally, the computer program product may provide a navigation path generation service based on the navigation path generation method.

[0143] Optionally, in this embodiment, the computer program product may be a set of instructions and codes pre-written according to the navigation path generation method. The computer program product may run on various computer platforms, including personal computers, servers, mobile devices, etc.

[0144] Optionally, in this embodiment, the instructions and codes corresponding to the computer program product are used to implement the following method steps: obtaining driving trajectory data and first path data corresponding to the target trip, wherein the driving trajectory data is used to determine the vehicle driving trajectory corresponding to the target trip in the manual driving mode, and the first path data includes navigation data corresponding to the full navigation path of the target trip, and the full navigation path is planned according to the starting position and the end position of the target trip; matching and analyzing the driving trajectory data and the first path data to obtain a matching result; data trimming the driving trajectory data and the first path data according to the matching result to obtain a target trimming result; and generating a target navigation path based on the target trimming result.

[0145] In the above-mentioned multiple embodiments of the present application, the description of each embodiment has different emphases. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0146] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of multiple modules can be a logical function division, and there can be any other possible division methods when actually implemented in the application scenario; for another example, multiple modules (or units or components in the modules) can be combined with each other and can be integrated into another system. For example, some features of the method embodiments described above can be ignored or skipped.

[0147] It should be noted that in the above-mentioned embodiments, the modules, components or units described as separate parts can be physically separated or physically integrated. The parts displayed as modules or units can be physical modules or physical units, or virtual modules or virtual units, that is, multiple modules or multiple units can be in the same position, or distributed in multiple positions or multiple spaces. In the application scenario, according to the actual needs of the scenario, some or all of the multiple modules or multiple units can be selected to implement the technical solutions of the embodiments of the present application, thereby achieving the corresponding technical objectives.

[0148] In particular, for an integrated functional module or functional unit, if it is implemented in the form of a software functional unit and sold or used as an independent product, the module or functional unit can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can essentially or in other words, the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application.

[0149] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.

Claims

1. A method for generating a full navigation path, characterized in that: include: Acquire driving trajectory data and first path data corresponding to the target trip, wherein the driving trajectory data is used to determine the vehicle driving trajectory corresponding to the target trip in the manual driving mode, and the first path data includes navigation data corresponding to the full navigation path of the target trip, and the full navigation path is planned according to the starting position and the end position of the target trip; Performing matching analysis on the driving trajectory data and the first path data to obtain a matching result; Performing data trimming on the driving trajectory data and the first path data according to the matching result to obtain a target trimming result; Based on the target clipping result, a target navigation path is generated.

2. The method for generating a full navigation path according to claim 1, characterized in that: The driving trajectory data and the first path data are associated and matched to obtain the matching result, including: Based on the driving trajectory data, performing data removal processing on the first path data to obtain second path data; The driving trajectory data and the second path data are associated and matched to obtain the matching result.

3. The method for generating a full navigation path according to claim 2, characterized in that: Based on the driving trajectory data, performing data removal processing on the first path data to obtain the second path data includes: Calculating distance information between a track point on the vehicle's driving track and a line point on the full navigation path according to the driving track data and the first path data; Based on the distance information, determining a first merging point and a second merging point on the full navigation path, wherein the first merging point corresponds to the starting point position, and the second merging point corresponds to the ending point position; Determining navigation deviation data to be removed from the first path data based on the first merging point and the second merging point; The navigation deviation data in the first path data is removed to obtain the second path data.

4. The method for generating a full navigation path according to claim 2 or 3, characterized in that: The first path data includes multiple groups of first data corresponding to multiple full navigation paths, wherein the multiple full navigation paths are generated by triggering multiple driving deviation events in the target trip, and the second path data includes multiple groups of second data corresponding to the multiple groups of first data; The method for generating a full navigation path also includes: Comparing the plurality of full navigation paths along the direction from the starting position to the end position to determine a plurality of navigation convergence points; Based on the positions of the plurality of navigation convergence points, determining the navigation duplicate data to be removed from the plurality of sets of first data; The repeated navigation data in the multiple groups of first data are removed to obtain the multiple groups of second data, or the repeated navigation data in the multiple groups of second data are removed to update the multiple groups of second data.

5. The method for generating a full navigation path according to claim 2, characterized in that: The second path data includes multiple groups of second data corresponding to multiple navigation sections; The driving trajectory data and the second path data are associated and matched to obtain the matching result, including: Determine a plurality of matching point pairs corresponding to the plurality of navigation sections by using the track point positions corresponding to the driving track data and the line point positions corresponding to the second path data, wherein each matching point pair includes a starting line point of a navigation section and a track point on the vehicle driving track corresponding to the starting line point; The matching result is determined based on the driving trajectory data, the second path data and the plurality of matching point pairs, wherein the matching result is used to determine the same-road section and the different-road section between the driving trajectory data and the second path data.

6. The method for generating a full navigation path according to claim 5, characterized in that: Determining the matching result based on the driving trajectory data, the second path data, and the plurality of matching point pairs includes: For any one target matching point pair among the multiple matching point pairs, based on the driving trajectory data and the second path data, determine the distance information, mileage information and direction angle information of the target navigation section corresponding to the target matching point pair; Determine the same road section and the different road section in the target navigation section according to the distance information, the mileage information and the direction angle information; A matching result is determined based on the same-road section and the different-road section corresponding to each of the multiple navigation sections.

7. The method for generating a full navigation path according to claim 1, characterized in that: The target clipping result includes a first clipping result and a second clipping result; The driving trajectory data and the first path data are clipped according to the matching result to obtain a target clipping result including: Determine the same-route section and the different-route section based on the matching result; trimming the driving trajectory data according to the different road section to obtain the first trimming result; The first path data is trimmed according to the same-path section to obtain the second trimming result.

8. The method for generating a full navigation path according to claim 7, characterized in that: Based on the target clipping result, generating a target navigation path includes: The first clipping result and the second clipping result are spliced ​​to obtain a target navigation path.

9. The method for generating a full navigation path according to claim 8, characterized in that: The first clipping result and the second clipping result are spliced ​​to obtain the target navigation path, including: Performing format conversion on the first clipping result to obtain different-route navigation data; According to the mileage information corresponding to the target journey, the second clipping result and the different-route navigation data are sequentially spliced ​​to obtain the target navigation path.

10. The method for generating a full navigation path according to claim 9, characterized in that: The method for generating a full navigation path further includes at least one of the following: Using the first path data and the road semantic information corresponding to the different-road navigation data, semantically splicing and adjusting the target navigation path, and updating the target navigation path; The road structure information corresponding to the first path data and the different-route navigation data is used to perform structural splicing adjustment on a portion of the navigation path corresponding to the different-route navigation data in the target navigation path, and the target navigation path is updated.

11. A navigation path generating device, characterized in that: include: an acquisition module, configured to acquire driving trajectory data and first path data corresponding to a target trip, wherein the driving trajectory data is used to determine a vehicle driving trajectory corresponding to the target trip in a manual driving mode, and the first path data includes navigation data corresponding to a full navigation path of the target trip, and the full navigation path is planned according to a starting position and an end position of the target trip; A matching module, used for performing matching analysis on the driving trajectory data and the first path data to obtain a matching result; A trimming module, used for trimming the driving trajectory data and the first path data according to the matching result to obtain a target trimming result; A generating module is used to generate a target navigation path based on the target clipping result.

12. A vehicle, characterized in that: It includes an on-board memory and an on-board processor, wherein the on-board memory stores a computer program, and the on-board processor is configured to run the computer program to execute the full navigation path generation method described in any one of claims 1 to 10.

13. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored executable program, wherein when the executable program is running, the device where the computer-readable storage medium is located is controlled to execute the full navigation path generation method described in any one of claims 1 to 10.

14. A computer program product, characterized in that It comprises a computer program, which, when executed by a processor, implements the method for generating a full navigation path according to any one of claims 1 to 10.

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