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

Abstract

The application discloses a full-quantity 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 following steps: obtaining driving track data corresponding to a target trip and first path data, wherein the driving track data is used to determine a vehicle driving track corresponding to the target trip in a manual driving mode, the first path data comprises navigation data corresponding to a full-quantity navigation path of the target trip, and the full-quantity navigation path is planned according to a starting point position and an end point position of the target trip; 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 the matching result to obtain a target clipping result; and generating a target navigation path based on the target clipping result. The application solves the technical problem that the navigation path generation method provided in the related art is difficult to adapt to individual driving and thus has poor navigation path generation accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of automatic driving, in particular to a full-quantity navigation path generation method and device, a vehicle and a storage medium. BACKGROUND

[0002] In an automatic driving scenario, a navigation path from a starting point to a destination is usually set for a vehicle. However, a user may manually intervene in the vehicle due to individual driving route requirements, which causes the vehicle to deviate from the navigation path and triggers the resetting of the navigation path. Based on this, after multiple automatic driving of a certain trip (i.e., multiple trips of the same set of starting point and destination), the vehicle side may save multiple navigation paths, and these navigation paths may have repeated paths or do not conform to the actual driving trajectory of the user. Therefore, how to generate a navigation path with complete information and conforming to the driving trajectory of the user has become one of the important technical problems in the related technical field.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] Embodiments of the present application provide a full-quantity navigation path generation method, device, vehicle and storage medium, to at least solve the technical problem that the navigation path generation method provided in the related art is difficult to adapt to individual driving and causes poor accuracy of the generated navigation path.

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

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

[0007] Optionally, the data removal processing on the first path data based on the driving trajectory data comprises: calculating distance information between a trajectory point on the driving trajectory of the vehicle and a link point on the full-quantity navigation path according to the driving trajectory data and the first path data; determining a first merging point and a second merging point on the full-quantity navigation path based on the distance information, wherein the first merging point corresponds to the start point position, and the second merging point corresponds to the end point position; determining navigation deviation data to be removed in the first path data based on the first merging point and the second merging point; and removing the navigation deviation data in the first path data to obtain the second path data.

[0008] Optionally, the first path data comprises a plurality of groups of first data corresponding to a plurality of full-quantity navigation paths triggered and generated by a plurality of driving deviation events in the target trip, and the second path data comprises a plurality of groups of second data corresponding to the plurality of groups of first data; the full-quantity navigation path generation method further comprises: performing path comparison on the plurality of full-quantity navigation paths along the direction from the start point position to the end point position to determine a plurality of navigation merging points; determining navigation repeated data to be removed in the plurality of groups of first data based on the positions of the plurality of navigation merging points; and removing the navigation repeated data in the plurality of groups of first data to obtain the plurality of groups of second data, or removing the navigation repeated data in the plurality of groups of second data to update the plurality of groups of second data.

[0009] Optionally, the second path data comprises a plurality of groups of second data corresponding to a plurality of navigation links; and the association matching of the driving trajectory data and the second path data to obtain the matching result comprises: determining a plurality of matching point pairs corresponding to the plurality of navigation links by using the trajectory point positions corresponding to the driving trajectory data and the link point positions corresponding to the second path data, wherein each matching point pair comprises a starting link point of a navigation link and a trajectory point on the driving trajectory of the vehicle corresponding to the starting link point; and determining the matching result 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 interval and the different road interval between the driving trajectory data and the second path data.

[0010] Optionally, the determination of the matching result based on the driving trajectory data, the second path data, and the plurality of matching point pairs comprises: for any one target matching point pair in the plurality of matching point pairs, determining distance information, mileage information, and direction angle information of a target navigation link corresponding to the target matching point pair based on the driving trajectory data and the second path data; determining the same road interval and the different road interval in the target navigation link according to the distance information, the mileage information, and the direction angle information; and determining the matching result based on the same road interval and the different road interval of each navigation link in the plurality of navigation links.

[0011] Optionally, the target clipping result comprises a first clipping result and a second clipping result; the data clipping of the driving track data and the first path data according to the matching result to obtain the target clipping result comprises: determining a same-road section and a different-road section based on the matching result; clipping the driving track data according to the different-road section to obtain the first clipping result; and clipping the first path data according to the same-road section to obtain the second clipping result.

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

[0013] Optionally, the splicing processing on the first clipping result and the second clipping result to obtain the target navigation path comprises: performing format conversion on the first clipping result to obtain different-road navigation data; and performing sequential splicing on the second clipping result and the different-road navigation data according to the mileage information corresponding to the target trip to obtain the target navigation path.

[0014] Optionally, the full-navigation-path generation method further comprises at least one of the following: using 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 using road structure information corresponding to the first path data and the different-road navigation data to perform structure splicing adjustment on a part of the navigation path corresponding to the different-road navigation data in the target navigation path and update the target navigation path.

[0015] According to another aspect of the embodiments of the present application, a navigation path generation device is also provided, comprising: an acquisition module configured to acquire driving track data corresponding to a target trip and first path data, wherein the driving track data is used to determine a vehicle driving track corresponding to the target trip in a manual driving mode, the first path data comprises navigation data corresponding to a full-navigation-path of the target trip, and the full-navigation-path is planned according to a starting point position and an ending point position of the target trip; a matching module configured to perform matching analysis on the driving track data and the first path data to obtain a matching result; a clipping module configured to perform data clipping of the driving track data and the first path data according to the matching result to obtain a target clipping result; and a generation module configured to generate a target navigation path based on the target clipping result.

[0016] According to another aspect of the embodiments of the present application, a vehicle is also provided, comprising an on-board memory and an on-board processor, the on-board memory stores a computer program, and the on-board processor is configured to run the computer program to execute the navigation path generation method of any one of the above.

[0017] According to another aspect of the embodiments of the present application, a computer readable storage medium is also provided, which includes a stored executable program, wherein the executable program controls the device where the storage medium is located to perform the navigation path generation method of any one of the above when the executable program is executed.

[0018] According to another aspect of the embodiments of the present application, a computer program product is also provided, which includes a computer program, and the computer program implements the navigation path generation method of any one of the above when executed by a processor.

[0019] In the embodiments of the present application, first, driving track data corresponding to the target trip and first path data are acquired, wherein the driving track data is used to determine the vehicle driving track corresponding to the target trip in the manual driving mode, and the first path data includes navigation data corresponding to the full-quantity navigation path of the target trip, and the full-quantity navigation path is planned according to the starting point position and the end point position of the target trip; further, the driving track data and the first path data are matched and analyzed to obtain a matching result; the driving track data and the first path data are data-cropped according to the matching result to obtain a target cropping result; and the target navigation path is generated based on the target cropping result. Thus, the present application achieves the purpose of cropping and merging the vehicle driving track and the full-quantity navigation path to generate the target navigation path, thereby realizing the technical effect of improving the accuracy of the navigation path and the adaptability of the navigation path to the individualized driving path of the user, and further solving the technical problem that the navigation path generation method provided in the related art is difficult to adapt to the individualized driving and leads to poor accuracy of the generated navigation path. BRIEF DESCRIPTION OF DRAWINGS

[0020] The accompanying drawings, which are included to provide a further understanding of the present application and constitute a part of this application, illustrate certain illustrative embodiments of the present application and related descriptions of the embodiments, and do not constitute improper limitations to the present application. In the drawings:

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

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

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

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

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

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

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

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

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

[0030] In order to make the personnel in the technical field better understand the present application scheme, the technical scheme in the present application embodiment will be described clearly and completely in combination with the drawings in the present application embodiment. Obviously, the described embodiments only include part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by the person skilled in the art without creative labor should belong to the scope of protection of the present application.

[0031] It should be noted that the terms "first", "second" and the like in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0032] According to the embodiments 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 drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that herein.

[0033] First, the running environment of the above-mentioned method embodiment is exemplarily described. Figure 1This is a hardware structure block diagram of an optional computing terminal for implementing a navigation path generation method according to an embodiment of this application, such as... Figure 1 As shown, the computing terminal 10 (e.g., a computer terminal, a mobile smart terminal, a vehicle terminal, or a cloud computing virtual terminal) may include: one or more processors 102, a memory 104 for storing data, and a transmission device 106 for implementing communication functions. Each processor 102 may include, but is not limited to, a processing component such as a microprocessor (MCU) or a field programmable gate array (FPGA).

[0034] The aforementioned computing terminal 10 may further include: a display device 110, an input / output device 108, a Universal Serial Bus (USB) port (which can 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). Those skilled in the art will understand that... Figure 1 The structure of the computing terminal 10 shown is for illustrative purposes only and does not impose strict limitations on the structure of the computing terminal 10 described above. For example, the computing terminal 10 may also include components that are larger than... Figure 1 The more or fewer components shown, or the computing terminal 10 may have the same Figure 1 The components are shown in different categories.

[0035] It should be noted that one or more processors 102 and / or other data processing circuits in the aforementioned computing terminal 10 may be wholly or partially embodied in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be wholly or partially integrated into any other element 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 this embodiment. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the above-mentioned navigation path generation method. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computing terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0037] The transmission device 106 is configured to receive or send data via a network. The network can include a wireless network provided by a communication provider of the computing terminal 10. In one example, the transmission device 106 includes a network interface controller (NIC) configured to connect to other network devices via a base station to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module configured to communicate with the Internet via a wireless manner.

[0038] In the above operating environment, the embodiments of the present application provide a navigation path generation method as shown in Figure 2 Figure 2 is a flowchart of a navigation path generation method according to an embodiment of the present application, as shown in Figure 2 The method includes the following implementation steps:

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

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

[0041] Step S203, performing data clipping on the driving track data and the first path data according to the matching result to obtain a target clipping 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 position and an end point position. In an application scenario, a user can drive a vehicle at least once to complete the target trip in a manual driving mode, or can control the vehicle at least once to complete the target trip in an automatic driving mode.

[0044] The driving track data is a vehicle driving track determined by the user in the process of driving the vehicle to perform the target trip in the manual driving mode. The vehicle driving track can include personalized driving routes corresponding to personalized requirements of the user, and the personalized driving routes can be inconsistent with a navigation path of the target trip generated in advance. The inconsistent personalized driving routes can also be regarded as active deviation routes of the user. ​

[0045] The first path data can include navigation data corresponding to a full-quantity navigation path planned in advance based on the target trip. In particular, the first path data can include a plurality of sets of navigation data corresponding to a plurality of full-quantity navigation paths obtained by performing path planning a plurality of times for a start point and an end point of the target trip.

[0046] The matching result is used to represent the same path part and the different path part between the driving trajectory data and the first path data. The same path part is part data that matches the full-quantity navigation path and the vehicle driving trajectory, and the different path part is part data that does not match the full-quantity navigation path and the vehicle driving trajectory.

[0047] The driving trajectory data and the first path data can be stored in a continuous data format, respectively, and the target clipping result includes a plurality of data segments obtained by clipping the driving trajectory data according to the matching result and a plurality of data segments 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 part, and the target navigation path is obtained. For example, a data segment in the first path data is selected in the same path part, a data segment in the driving trajectory data is selected in the different path part, and the selected data segments are spliced to obtain the target navigation path.

[0048] Since the full-quantity navigation data can contain more comprehensive navigation-related information, and the driving trajectory data can represent the personalized needs of the user when performing the target trip, in the real-time step, the full-quantity navigation data and the driving trajectory data are comprehensively considered according to the matching result when the target navigation path is generated, so that the generated target navigation path can provide a target navigation path that not only conforms to the personalized driving needs of the user, but also has more comprehensive data. Thereby, the intelligent level of vehicle automatic driving is improved, the user experience is enhanced, and the safety of the vehicle is improved.

[0049] Through the technical solutions provided by the steps S201 to S204, the present application achieves the purpose of clipping and merging the vehicle driving trajectory and the full-quantity navigation path to generate the target navigation path, thereby realizing the technical effect of improving the accuracy of the navigation path and the adaptability of the navigation path to the personalized driving path of the user, and further 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 the generated navigation path.

[0050] The above implementation steps provided by the embodiments of the present application are mainly applicable to the field of automatic driving technology, and can play an important role in the task of establishing a cloud navigation map in a specific application scenario. In the process of establishing a cloud navigation map, the cloud server obtains a vehicle driving track corresponding to a target trip of a vehicle in a manual driving mode to determine the personalized needs of a user in the target trip, and obtains navigation data corresponding to a full navigation path given by a navigation system in the process of the vehicle completing the target trip multiple times in a driving history. Further, the cloud server matches the vehicle driving track and the multiple full navigation paths, data clips and data splicing according to the scheme provided by the embodiments 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. The target navigation path keeps the same route as the above vehicle driving track, meets the personalized needs of the user, and can contain as much full navigation data as possible. After the establishment of the cloud navigation map is completed, when the vehicle needs to perform automatic driving of the target trip again, the cloud will issue the above target navigation path to the vehicle end, so that the vehicle end provides the full navigation information to the user through the center control display screen, and can also help the vehicle to make more accurate and more user demand-oriented automatic driving decisions. The above specific application scenario can be, but is 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 track according to the user's personalized driving habits and preferences in the learning stage, to ensure that the AI driving process can follow the specific route requirements of the customer and improve customer satisfaction.

[0052] In the path planning scenario of an automatic driving vehicle, 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 the actual road conditions and user preferences by analyzing the user's actual driving track, to improve the safety and user experience of automatic driving.

[0053] In the map data updating and optimization scenario, for a map service provider, the above method steps can optimize and update the full navigation path in the map by analyzing a large number of real driving tracks of users, to remove unnecessary repeated path information and improve the accuracy and practicality of the 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, so that the vehicle navigation system can dynamically generate a full navigation path according to the personalized needs of the user, to enhance the intelligence and flexibility of the vehicle navigation system.

[0055] In the intelligent transportation system (ITS) application scenario, the above method steps can be used to optimize the driving route of a vehicle, especially in the case of traffic congestion or road construction, by analyzing the historical driving trajectory, and by generating a full navigation path to plan a more reasonable and efficient driving path for the vehicle. In the vehicle fleet (such as logistics transportation fleet, taxi fleet, etc.) management and scheduling scenario, the above method steps can generate a full navigation path according to the actual driving habits of the driver, provide an optimized driving route for the vehicles in the fleet, improve the operation efficiency of the fleet, and reduce unnecessary fuel consumption and time waste.

[0056] The following takes the AI chauffeur application scenario as an example to further illustrate other optional implementations of the above method provided by the embodiments of the present application.

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

[0058] AI chauffeur can be a function provided by an autonomous vehicle equipped with an AI chauffeur system. The AI chauffeur system continuously optimizes its driving route during the route learning phase and improves driving skills and planning capabilities through practice and feedback. First, the AI chauffeur system uses map and road condition information to plan a navigation route to be used, and then collects surrounding environment data (such as road conditions, traffic conditions, pedestrian information, and vehicle information, etc.) during actual driving to adjust and optimize the navigation route to ensure safe and efficient driving of the vehicle. In addition, the AI chauffeur system improves route planning capabilities based on feedback information during actual driving. For example, based on driving records and event data during driving to analyze driving behavior and improve it. The execution subject of the above method steps provided by the embodiments of the present application can be the above autonomous vehicle or the above AI chauffeur system.

[0059] In the AI chauffeur application scenario, according to the above full navigation path generation method, the full navigation path and the user's driving trajectory in the learning phase are cut and spliced to generate a navigation path. Specifically, the personalized driving trajectory of the user in the learning phase is used to cut, process and splice multiple full navigation paths, and then a user customized navigation path that conforms to the driving trajectory and has complete navigation information is obtained.

[0060] As an optional implementation, the step S202 of associatively matching the driving track data and the first path data to obtain a matching result can further include the following execution steps:

[0061] In step S221, the first path data is processed by data removal based on the driving track data to obtain second path data.

[0062] In step S222, the driving track data and the second path data are associatively matched to obtain a matching result.

[0063] In the application scenario, even if there is a large error between the first path data and the driving track data in a part of the target trip, the associatively matching of the driving track data and the first path data in this part can be ignored. For example, in the part of the target trip at the beginning or at the end, the driving condition of the vehicle is usually complex, and the driving demand of the user also has many changes. Therefore, the part of the data in the first path data corresponding to the beginning and end of the full navigation path is removed to obtain the second path data. Further, the second path data after data removal is associatively matched with the driving track data to obtain a matching result.

[0064] Through the technical solutions provided in steps S221 to S222, the embodiments of the present application remove part of the data in the full navigation data before associatively matching, avoid the influence of this part of data on the associatively matching, and ensure that the obtained matching result can accurately represent the same road section and different road sections, further ensuring the accuracy of the clipping and splicing in the full navigation path generation method.

[0065] As an optional implementation, the step S221 of processing the first path data by data removal based on the driving track data to obtain the second path data can further include the following execution steps:

[0066] In step S2211, the distance information between the track points on the driving track of the vehicle and the road points on the full navigation path is calculated according to the driving track data and the first path data.

[0067] In step S2212, the first merging point and the second merging point are determined on the full navigation path based on the distance information, wherein the first merging point corresponds to the start point position, and the second merging point corresponds to the end point position.

[0068] In step S2213, the navigation deviation data to be removed in the first path data is determined based on the first merging point and the second merging point.

[0069] In step S2214, the navigation deviation data in the first path data is removed to obtain the second path data.

[0070] When the distance between the track point on the vehicle driving track and the line point on the full-quantity navigation path is less than a preset threshold, it is considered that the vehicle driving track converges with the full-quantity navigation path, and at this time, the line point can be considered as successfully matched with the track point, and the line point is regarded as a convergence point. There can be multiple convergence points on the full-quantity navigation path, the first convergence point is the convergence point closest to the start point position among the multiple convergence points, and the second convergence point is the convergence point closest to the end point position among the multiple convergence points.

[0071] Further, a part of the full-quantity navigation path from the start point position to the first convergence point position is determined as a start interval, a part of the full-quantity navigation path from the second convergence point position to the end point position is determined as an end interval, the part of the first path data corresponding to the start interval and the end interval is determined as navigation deviation data, and the navigation deviation data is removed from the first path data to obtain the second path data.

[0072] Through the technical solutions provided in steps S2211 to S2214, before the driving track data and the first path data are associated and matched, the convergence point positions near the start point position and the end point position are determined, the navigation deviation data to be removed is determined from the first path data, the influence of the deviation at the beginning and the end of the target trip on the path generation is avoided, and the accuracy of the target navigation path generation is improved.

[0073] As an optional implementation, the first path data includes multiple groups of first data corresponding to multiple full-quantity navigation paths, the multiple full-quantity navigation paths are generated by 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 navigation path generation method can further include the following execution steps:

[0074] Step S251, path comparison is performed on the multiple full-quantity navigation paths in the direction from the start point position to the end point position, and multiple navigation convergence points are determined.

[0075] Step S252, based on the positions of the multiple navigation convergence points, navigation repeated data to be removed in the multiple groups of first data is determined.

[0076] Step S253, the navigation repeated data in the multiple groups of first data is removed to obtain the multiple groups of second data, or the navigation repeated data in the multiple groups of second data is removed to update the multiple groups of second data.

[0077] The navigation convergence point is a convergence point between the multiple full-quantity navigation paths. For example, in a certain road section, the multiple full-quantity navigation paths are consistent, and the multiple line points in the road section are navigation convergence points. The navigation data corresponding to the multiple groups of first data in the road section is determined as navigation repeated data.

[0078] By the technical solutions provided by steps S251 to S253, in the process of associating and matching the driving track data and the first path data, the embodiment of the present application can consider multiple full-quantity navigation paths, remove the navigation repeated data between these full-quantity navigation path data, so that the navigation repeated data is ignored in the second path data, and subsequent association and matching is performed according to the differences between the multiple full-quantity navigation paths, thereby realizing the reduction of the path generation calculation amount while ensuring that the generated target navigation path is consistent with the vehicle driving track, and improving the efficiency.

[0079] Taking the AI chauffeur application scenario as an example, the vehicle driving track of the user completing the target trip record in the manual driving mode is as shown in Figure 3 , when the path planning is triggered by the user's driving deviation event, the first full-quantity navigation path obtained by planning the target trip is as shown in Figure 4 , when the path planning is triggered by the user's driving deviation event, the second full-quantity navigation path obtained by planning the target trip is as shown in Figure 5 . The first path data includes the first initial navigation data (i.e., a first set of data) corresponding to the first full-quantity navigation path and the second initial navigation data (i.e., another first set of data) corresponding to the second full-quantity navigation path.

[0080] As shown in Figure 3 , Figure 4 and Figure 5 , in the range close to the start point and the end point of the target trip, the first full-quantity navigation path and the second navigation path are inconsistent with the vehicle driving track, at this time, the part of the initial navigation data corresponding to the range close to the start point and the end point of the first initial navigation data can be removed to obtain the first intermediate navigation data (i.e., a second set of data), and the part of the initial navigation data corresponding to the range close to the start point and the end point of the second initial navigation data can be removed to obtain the second intermediate navigation data (i.e., another second set of data).

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

[0082] Further, taking the first full quantity navigation path as shown in Figure 4 , the first full quantity navigation path is processed according to the data removal mode as shown in Figure 6 . The navigation path data corresponding to the road section between the start position and the first merging point on the first full quantity 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 road section between the second merging point and the end position on the first full quantity navigation path is determined as another part of the navigation deviation data to be removed in the first initial navigation data. Further, the navigation deviation data is removed from the first initial navigation data to obtain the first intermediate navigation data, which is the navigation data corresponding to the first full quantity 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 quantity navigation path after removing the head and tail.

[0083] Further, the first full quantity navigation path (which can also be the first full quantity navigation path after removing the head and tail) and the second full quantity navigation path (which can also be the second full quantity navigation path after removing the head and tail) are processed according to the data removal mode as shown in Figure 7 . The two full quantity navigation paths as shown in Figure 4 and Figure 5 are compared to determine a plurality of navigation merging points Figure 7After the two navigation junctions are shown (as shown in FIG. 2), the part where the first full navigation path and the second full navigation path are determined to be the same is obtained as a navigation repeated section. The navigation repeated data corresponding to the navigation repeated section is deleted from the first initial navigation data (or the first intermediate navigation data), and the first target navigation data corresponding to the deduplicated first full navigation path is obtained. The first target navigation data can be used as a group of second data in the second path data. Similarly, the navigation repeated data corresponding to the navigation repeated section is deleted from the second initial navigation data (or the second intermediate navigation data), and the second target navigation data corresponding to the deduplicated second full navigation path is obtained. The second target navigation data can be used as another group of second data in the second path data.

[0084] By the above-described Figure 6 and / or Figure 7 The data removal manner shown in the above-described

[0085] As an optional implementation, the second path data includes a plurality of groups of second data corresponding to a plurality of navigation sections. In the step S222, the matching between the driving trajectory data and the second path data is performed to obtain a matching result, and the step S222 can further include the following execution steps.

[0086] In step S2221, a plurality of matching point pairs corresponding to a plurality of navigation sections are determined by using the track point positions corresponding to the driving trajectory data and the line point positions corresponding to the second path data. Each matching point pair includes a starting line point of a navigation section and a track point on the driving trajectory corresponding to the starting line point.

[0087] In step S2222, a matching result is determined based on the driving trajectory data, the second path data, and the plurality of matching point pairs. 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.

[0088] The driving track data includes track information corresponding to a plurality of track points on a vehicle driving track and driving information, such as track point positions, driving distances, driving directions, and the like. The second path data includes navigation information corresponding to a plurality of track points on a full navigation path and path information, such as navigation directions, navigation distances, and the like. Further, the plurality of matching point pairs corresponding to a plurality of navigation segments are determined by using the driving track data and the second path data. By using each matching point pair, the driving track data, and the second path data, the same road section and the different road section in each navigation segment can be determined. The same road section indicates that the full navigation path and the vehicle driving track route are consistent (or the deviation is less than a preset threshold) in the navigation segment, and the different road section indicates that the full navigation path and the vehicle driving track route are inconsistent (or the deviation exceeds the preset threshold) in the navigation segment.

[0089] By the technical solutions provided in steps S2221 to S2222, in the process of associating and matching the driving track data and the first path data, the same road section and the different road section corresponding to the vehicle driving track and the full navigation path are determined by matching the track points on the vehicle driving track with the track points on the full navigation path, so that the same road section and the different road section can be distinguished and processed in the process of generating the target navigation path, and the information integrity and the track consistency of the target navigation path are ensured.

[0090] As an optional implementation, in step S2222, the matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the step can further include the following execution steps:

[0091] In step S2223, distance information, mileage information, and direction angle information of a target navigation segment corresponding to a target matching point pair in the plurality of matching point pairs are determined based on the driving track data and the second path data.

[0092] In step S2224, the same road section and the different road section in the target navigation segment are determined according to the distance information, the mileage information, and the direction angle information.

[0093] In step S2225, the matching result is determined based on the same road section and the different road section corresponding to each navigation segment in the plurality of navigation segments.

[0094] In the AI chauffeur application scenario, the following specific implementation manners can be adopted to determine the matching result based on the driving trajectory data, the second path data, and the plurality of matching point pairs. The plurality of navigation segments can be the plurality of full-quantity navigation paths obtained by removing the head and tail data and / or removing the duplicate data from the second path data obtained by the aforementioned preprocessing. For each navigation segment, first, find the trajectory point with the minimum Euclidean distance between the starting point (i.e., the starting point) of the navigation segment and the starting point on the vehicle driving trajectory, and establish the matching relationship between the starting point and the trajectory point. Then, starting from the starting point, traverse the points on the navigation segment towards the terminal point (i.e., the terminal point) of the navigation segment, and for each point in the traversal, calculate the point distance information between the point and the next point, and accumulate the distance information of the plurality of points traversed on the navigation segment to obtain the cumulative navigation mileage. Similarly, for each point in the traversal, calculate the trajectory point distance information corresponding to the matching trajectory point, and accumulate to obtain the cumulative trajectory mileage. Further, for the current point in the traversal, if the distance between the current point and the matching trajectory point is less than a first threshold (e.g., 3 meters), the difference between the cumulative navigation mileage corresponding to the current point and the cumulative trajectory mileage corresponding to the matching trajectory point is less than a second threshold (e.g., 30 meters), and the included angle between the navigation direction corresponding to the current point and the trajectory direction corresponding to the matching trajectory point is less than a third threshold (e.g., 10°), it can be determined that the path sub-segment between the current point and the next point belongs to the same road interval, otherwise, it is considered that the path sub-segment belongs to the different road interval, i.e., the full-quantity navigation path and the vehicle driving trajectory appear to diverge.

[0095] Specifically, in the above application scenario, taking the second full-quantity navigation path after deduplication as an example, the matching result is determined according to the association matching mode as shown in Figure 8 . The second full-quantity 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-quantity navigation path after deduplication. The matching result is used to determine the data range corresponding to the same road interval and the different road interval in the second path data. Further, the diverging point between the same road interval and the different road interval in the second full-quantity navigation path after deduplication is determined, and the matching relationship between the plurality of points in the same road interval and the corresponding trajectory points is established.

[0096] Further, after the full-quantity navigation path and the vehicle driving track diverge, a position where the full-quantity navigation path and the vehicle driving track converge again is searched. For example, the points on the full-quantity navigation path after the diverging point are traversed, and when it is found that the distance between the current point and the corresponding track point on the vehicle driving track is less than the first threshold (for example, 3 meters) and the direction angle between the current point and the track point is less than the third threshold (for example, 10°), it can be determined that the current point is the position of the convergence again, the current point is taken as the starting point of the next same-road section, the above scheme of determining the same-road section is repeated, that is, the points are traversed until the next diverging point is found, the next same-road section is determined, and the next convergence position is searched. In this way, multiple convergence points and multiple diverging points on the full-quantity navigation path can be recorded, and in order, the first same-road section is between the first convergence point and the first diverging point, the first different-road section is between the first diverging point and the second convergence point, and so on.

[0097] Through the technical solutions provided in steps S2223 to S2225, in the process of matching the track point on the vehicle driving track with the point on the full-quantity navigation path, the distance between the track point and the point, the travel mileage of the target journey corresponding to the track point and the point, and the direction angle information corresponding to the track point and the point are comprehensively considered, the matching relationship between the track point and the point can be accurately established, and the accuracy of the determined same-road section and different-road section is ensured.

[0098] As an optional implementation, the target clipping result includes a first clipping result and a second clipping result; in step S203, the driving track data and the first path data are clipped according to the matching result to obtain the target clipping result, and the step can further include the following execution steps:

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

[0100] Step S232, clipping the driving track data according to the different-road section to obtain the first clipping result;

[0101] Step S233, clipping the first path data according to the same-road section to obtain the second clipping result.

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

[0103] Through the technical solutions provided in steps S231 to S233, in the process of clipping the driving trajectory data and the first path data, the same road section and the different road section matched and determined between the driving trajectory data and the first path data are considered, the partial data of the driving trajectory data in the different road section (that is, the first clipping result) is obtained by clipping, and the partial data of the first path data in the same road section (that is, the second clipping result) is obtained by clipping. Therefore, more comprehensive full navigation path data in the first path data in the same road section is ensured, and the driving trajectory data closer to the personalized driving demand of the user in the different road section is ensured. Based on this, the target navigation path generated according to the first clipping result and the second clipping result can take into account the information comprehensiveness and the trajectory consistency.

[0104] As an optional implementation, in step S204, based on the target clipping result, the target navigation path is generated, which can further include the following execution steps:

[0105] In step S241, the first clipping result and the second clipping result are spliced to obtain the 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 journey, the partial trajectory data in the first clipping result and the partial path data in the second clipping result are sorted, and then the first clipping result and the second clipping result are spliced to obtain the target navigation path. Specifically, the partial trajectory data and the partial path data are spliced in the order of the mileage to obtain target navigation data, and the target navigation data is used to determine the target navigation path.

[0107] Through the technical solutions provided in step S241, the first clipping result and the second clipping result are spliced to obtain the complete target navigation path corresponding to the target journey. The target navigation path is used to provide navigation for the vehicle in the target journey, and can take into account the personalized driving trajectory demand of the user and the safety demand of the vehicle ensured by the complete and comprehensive navigation data.

[0108] As an optional implementation, the splicing the first clipping result and the second clipping result to obtain the target navigation path in step S241 can further include the following execution steps:

[0109] In step S242, the first clipping result is converted in format to obtain the off-road navigation data.

[0110] In step S243, the second clipping result and the off-road navigation data are sequentially spliced according to the mileage information corresponding to the target trip to obtain the target navigation path.

[0111] In the application scenario, when the target navigation path is generated, the target navigation data consistent with the vehicle driving trajectory route is obtained, which includes the on-road navigation data and the off-road navigation data. The part of the path data in the second clipping result can be used as the on-road navigation data, and the off-road navigation data is obtained by converting part of the trajectory data in the first clipping result in format. Specifically, the part of the trajectory data is converted into the full-amount navigation data format to obtain the full-amount navigation path data consistent with the vehicle driving trajectory route corresponding to the part of the trajectory data as the off-road navigation data. Based on this, the on-road navigation data and the off-road 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 part of the path data in the second clipping result can contain multiple full-amount navigation segments. Before these full-amount navigation segments are sorted according to the mileage information, these full-amount navigation segments can be de-duplicated. Further, after these full-amount navigation segments are arranged in order, the off-road interval between the terminal point of a full-amount navigation segment (corresponding to a same road interval) and the starting point of the next full-amount navigation segment (corresponding to the next same road interval) can be used as the part that needs to be completed by using the vehicle driving trajectory information, that is, the off-road interval.

[0113] It should be noted that the first path data corresponding to the full-amount navigation path at least contains the road structure information and the road semantic information corresponding to the target trip, and can also contain other interactive information related to navigation. The driving trajectory data corresponding to the vehicle driving trajectory at least contains the trajectory point position information, and the data comprehensiveness of the driving trajectory data is usually lower than that of the first path data. Based on this, in the process of converting the first clipping result into off-road navigation data, the road structure information and the road semantic information corresponding to the off-road interval are added to the first clipping result.

[0114] Further, in addition to the data format conversion to obtain the off-road navigation data, the full navigation data corresponding to the target route stored in the database can be searched for a full navigation segment matching the partial driving track of the off-road section, and the full navigation segment is used as the off-road navigation data corresponding to the partial driving track. For example, the distance between the navigation path corresponding to the full navigation segment to be matched and the partial driving track is less than 5 meters and the direction angle is less than 10°. Further, the road semantic information and road structure information of the full navigation segment are added to the data corresponding to the partial driving track in the first clipping result to obtain the off-road navigation data corresponding to the partial driving track. That is, the off-road navigation data can include the first partial data obtained by the vehicle driving track through data format conversion, and can also include the second partial data selected from the full navigation database according to the partial driving track.

[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 the target navigation path is generated, the first partial data in the off-road navigation data can be continuously searched for a full navigation segment that can be matched in the full navigation database, and if the full navigation segment corresponding to the first partial data is found, the full navigation segment is used to replace the first partial data.

[0116] Through the technical solutions provided by the above steps S242 to S243, in the process of splicing the first clipping result and the second clipping result, the partial driving track data in the first clipping result is converted into off-road navigation data with more comprehensive information, and the off-road navigation data and the partial full navigation path data in the second clipping result have the same splicing dimension, and then the second clipping result and the off-road navigation data are sequentially spliced according to the mileage information, so as to ensure the order correctness of the target navigation path.

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

[0118] Step S261, using the road semantic information corresponding to the first path data and the off-road navigation data to perform semantic splicing adjustment on 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 off-road navigation data to perform structure splicing adjustment on the partial navigation path corresponding to the off-road navigation data in the target navigation path, and updating the target navigation path.

[0120] In the application scenarios, after the target navigation path is generated, the target navigation data corresponding to the target navigation path is verified in semantics according to the road semantic information contained in the same-path navigation data in the first path data and the road semantic information converted from the different-path navigation data, a semantic verification result is obtained, the target navigation data is adjusted in semantics according to the semantic verification result, and the target navigation path is regenerated and updated by using the adjusted target navigation data. Similarly, the target navigation path can be verified and updated according to the road structure information.

[0121] By the technical solutions provided in steps S261 to S264, the embodiments of the application further verify, adjust and replace the target navigation path according to the road semantic information and the road structure information after the target navigation path is generated, 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 equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation portal for user to choose authorization or refusal.

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

[0124] According to the embodiments of the application, a device embodiment of a navigation path generation device is also provided, which is used to implement the method embodiments and various optional implementation manners of the method embodiments, and the technical contents described above will not be repeated here. It should be noted that in the following related description of the device embodiment, the "module" can be software, hardware or a combination of software and hardware for realizing the specified function.

[0125] Figure 9 is a structural schematic diagram of a navigation path generation device according to an embodiment of the application, as shown in Figure 9As shown, the apparatus comprises: an acquisition module 901, configured to acquire driving track data corresponding to a target trip and first path data, wherein the driving track data is used to determine a vehicle driving track corresponding to the target trip in a manual driving mode, the first path data comprises navigation data corresponding to a full-quantity navigation path of the target trip, and the full-quantity navigation path is planned according to a starting point position and an end point position of the target trip; a matching module 902, configured to perform matching analysis on the driving track data and the first path data to obtain a matching result; a clipping module 903, configured to perform data clipping on the driving track data and the first path data according to the matching result to obtain a target clipping result; and a generation module 904, configured to generate a target navigation path based on the target clipping result.

[0126] Optionally, the matching module 902 is further configured to perform data removal processing on the first path data based on the driving track data to obtain second path data, and perform associated matching on the driving track data and the second path data to obtain the matching result.

[0127] Optionally, the matching module 902 is further configured to calculate distance information between a track point on the vehicle driving track and a line point on the full-quantity navigation path according to the driving track data and the first path data, determine a first merging point and a second merging point on the full-quantity navigation path based on the distance information, wherein the first merging point corresponds to the starting point position and the second merging point corresponds to the end point position, determine navigation deviation data to be removed in the first path data based on the first merging point and the second merging point, and remove the navigation deviation data in the first path data to obtain the second path data.

[0128] Optionally, the first path data comprises a plurality of groups of first data corresponding to a plurality of full-quantity navigation paths, the plurality of full-quantity navigation paths are generated by a plurality of driving deviation events in the target trip, and the second path data comprises a plurality of groups of second data corresponding to the plurality of groups of first data. In addition to all the above modules, the navigation path generation apparatus further comprises a deduplication module (not shown in the figure), configured to perform path comparison on the plurality of full-quantity navigation paths in a direction from the starting point position to the end point position, determine a plurality of navigation merging points, determine navigation repeated data to be removed in the plurality of groups of first data based on positions of the plurality of navigation merging points, remove the navigation repeated data in the plurality of groups of first data to obtain the plurality of groups of second data, or remove the navigation repeated data in the plurality of groups of second data and update the plurality of groups of second data.

[0129] Optionally, the second path data includes a plurality of sets of second data corresponding to the plurality of navigation segments; the matching module 902 is further configured to: determine a plurality of matching point pairs corresponding to the plurality of navigation segments, by using the track point positions corresponding to the driving track data and the link point positions corresponding to the second path data, wherein each matching point pair includes a starting link point of a navigation segment and a track point on the driving track corresponding to the starting link point; and determine the matching result based on the driving track data, the second path data, and the plurality of matching point pairs, wherein the matching result is used to determine the same-path section and the different-path section between the driving track data and the second path data.

[0130] Optionally, the matching module 902 is further configured to: for any target matching point pair in the plurality of matching point pairs, determine distance information, mileage information, and direction angle information of a target navigation segment corresponding to the target matching point pair, based on the driving track data and the second path data; determine the same-path section and the different-path section in the target navigation segment according to the distance information, the mileage information, and the direction angle information; and determine the matching result based on the same-path section and the different-path section of each navigation segment in the plurality of navigation segments.

[0131] Optionally, the target clipping result includes a first clipping result and a second clipping result; and the clipping module 903 is further configured to: determine the same-path section and the different-path section based on the matching result; clip the driving track data according to the different-path section to obtain the first clipping result; and clip the first path data according to the same-path section to obtain the second clipping result.

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

[0133] Optionally, the generation module 904 is further configured to: perform format conversion on the first clipping result to obtain different-path navigation data; and perform sequential splicing on the second clipping result and the different-path 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 modules, the navigation path generation apparatus further includes an updating module (not shown in the figure), configured to: perform semantic splicing adjustment on the target navigation path by using road semantic information corresponding to the first path data and the different-path navigation data, update the target navigation path, and perform structure splicing adjustment on a part of the navigation path in the target navigation path corresponding to the different-path navigation data by using road structure information corresponding to the first path data and the different-path navigation data, and update the target navigation path.

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

[0136] It should be noted that each module mentioned in the above device embodiment can be realized by software, hardware or a combination of software and hardware. For example, when the above modules are realized by hardware, each module can be arranged in the same processor, or each module can be arranged 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, and the above modules can also run in the computing terminal 10 as shown in the device as part of the device. Figure 1

[0137] According to an embodiment of the present application, a vehicle is also provided, which comprises an on-board memory and an on-board processor, the on-board memory stores a computer program, and the on-board processor is configured to run the computer program to implement the above navigation path generation method.

[0138] According to an embodiment of the present application, a computer readable storage medium is also provided, which comprises a stored program, wherein the program controls the device where the computer readable storage medium is located to implement the above navigation path generation method when the program is running.

[0139] Optionally, the above computer storage medium can include but is not limited to: a hard disk drive (HDD), a solid state drive (SSD), a USB flash drive, an optical disc, a memory card, a cloud storage medium and a network storage device (NAS) and the like.

[0140] Optionally, the above computer readable storage medium can be configured to store a computer program for performing the following steps: acquiring driving track data corresponding to a target trip and first path data, wherein the driving track data is used to determine the driving track of the vehicle in the manual driving mode corresponding to the target trip, the first path data comprises navigation data corresponding to the full navigation path of the target trip, and the full navigation path is planned according to the starting point and the ending point of the target trip; 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 the matching result to obtain a target clipping result; and generating a target navigation path based on the target clipping result.

[0141] ​According to the embodiment of the present application, a computer program product is also provided. The computer program product comprises a computer program which, when executed by a processor, is capable of implementing the navigation path generation method described above.

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

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

[0144] Optionally, in the embodiment, the instructions and codes corresponding to the computer program product are used to implement the following method steps: obtaining driving track data and first path data corresponding to a target trip, wherein the driving track data is used to determine the driving track of the vehicle in the manual driving mode corresponding to the target trip, and the first path data comprises navigation data corresponding to the full-quantity navigation path of the target trip, and the full-quantity navigation path is planned according to the starting point and the ending point of the target trip; 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 the matching result to obtain a target clipping result; and generating a target navigation path based on the target clipping result.

[0145] In the above-mentioned multiple embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0146] In the several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. For example, the above-described device embodiments are only schematic, and the division of the modules can be a logical function division, and in actual implementation, other arbitrary division can be used; for example, the modules (or units or components) can be combined with each other, or integrated into another system. For example, some features of the above-described method embodiments can be omitted or skipped.

[0147] It should be noted that in each of the above embodiments, the modules, components or units described as separate can be physically integrated, or can be physically separated. The components displayed as modules or units can be physical or virtual, that is, they can be located in the same position or distributed over multiple positions or multiple spaces. In the application scenario, according to the actual needs of the scene, part or all of the modules or units can be selected from the plurality of modules or units to implement the technical solutions of the embodiments of the present application, and then the corresponding technical purposes are achieved.

[0148] In particular, for the integrated functional modules or functional units, if they are implemented in the form of software functional units and sold or used as independent products, the modules or functional units can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes a number of instructions for causing 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 methods described in the embodiments of the present application.

[0149] The above only describes the preferred embodiments of the present application. It should be noted that for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which should also be considered as the protection scope of the present application.

Claims

1. A full navigation path generation method characterized by, The method comprises: obtaining driving track data corresponding to a target trip and first path data, wherein the driving track data is used to determine a vehicle driving track corresponding to the target trip in a manual driving mode, the first path data comprises a plurality of sets of navigation data corresponding to a plurality of full-quantity navigation paths of the target trip, the full-quantity navigation paths are planned according to a starting point position and an ending point position of the target trip, and the plurality of full-quantity navigation paths are triggered and generated by a plurality of driving deviation events in the target trip; 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 the matching result to obtain a target clipping result; generating a target navigation path based on the target clipping result; performing associated matching on the driving track data and the first path data to obtain the matching result, comprising: performing data removal processing on the first path data based on the driving track data to obtain second path data, wherein the second path data is determined based on a first merging point and a second merging point, the first merging point corresponds to the starting point position, the second merging point corresponds to the ending point position, the first merging point and the second merging point are determined on the full-quantity navigation path based on distance information between a track point on the vehicle driving track and a link point on the full-quantity navigation path, and the distance information is calculated according to the driving track data and the first path data; and performing associated matching on the driving track data and the second path data to obtain the matching result.

2. The full-quantity navigation path generation method according to claim 1, characterized by, performing data removal processing on the first path data based on the driving track data to obtain the second path data, comprising: calculating the distance information between the track point on the vehicle driving track and the link point on the full-quantity navigation path according to the driving track data and the first path data; determining the first merging point and the second merging point on the full-quantity navigation path based on the distance information, 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 in the first path data based on the first merging point and the second merging point; removing the navigation deviation data in the first path data to obtain the second path data.

3. The full navigation path generation method according to claim 2, characterized by, The first path data comprises a plurality of sets of first data corresponding to a plurality of full-quantity navigation paths, and the second path data comprises a plurality of sets of second data corresponding to the plurality of sets of first data; and the full-quantity navigation path generation method further comprises: performing path comparison on the plurality of full-quantity navigation paths in a direction from the starting point position to the ending point position to determine a plurality of navigation merging points; determining navigation repetitive data to be removed in the plurality of sets of first data based on positions of the plurality of navigation merging points; removing the navigation repetitive data in the plurality of sets of first data to obtain the plurality of sets of second data, or removing the navigation repetitive data in the plurality of sets of second data to update the plurality of sets of second data.

4. The full-quantity navigation path generation method according to claim 3, characterized by, The second path data includes a plurality of groups of second data corresponding to a plurality of navigation segments; The matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the matching result is used to determine same-path intervals and different-path intervals between the driving track data and the second path data. The matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the matching result is used to determine same-path intervals and different-path intervals between the driving track data and the second path data. The matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the matching result is used to determine same-path intervals and different-path intervals between the driving track data and the second path data.

5. The full-quantity navigation path generation method according to claim 4, characterized by, The matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the matching result is used to determine same-path intervals and different-path intervals between the driving track data and the second path data. The matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the matching result is used to determine same-path intervals and different-path intervals between the driving track data and the second path data. The matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the matching result is used to determine same-path intervals and different-path intervals between the driving track data and the second path data. The matching result is determined based on the driving track data, the second path data, and the plurality of matching point pairs, and the matching result is used to determine same-path intervals and different-path intervals between the driving track data and the second path data.

6. The full-quantity navigation path generation method according to claim 1, characterized by, The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result.

7. The full-quantity navigation path generation method according to claim 6, characterized by, The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result.

8. The full-quantity navigation path generation method according to claim 7, characterized by, The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result.

9. The full navigation path generation method according to claim 8, characterized by, The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result.

10. A navigation route generation device characterized by comprising: The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a first clipping result and a second clipping result. The target clipping result includes a An acquisition module is configured to acquire driving track data corresponding to a target trip and first path data, wherein the driving track data is used to determine a vehicle driving track corresponding to the target trip in a manual driving mode, and the first path data includes a plurality of sets of navigation data corresponding to a plurality of full-quantity navigation paths of the target trip, the full-quantity navigation paths being planned according to a starting point position and an ending point position of the target trip, and the full-quantity navigation paths being triggered and generated by a plurality of driving deviation events in the target trip. A matching module is configured to perform matching analysis on the driving track data and the first path data to obtain a matching result. A clipping module is configured to perform data clipping on the driving track data and the first path data according to the matching result to obtain a target clipping result. A generation module is configured to generate a target navigation path based on the target clipping result. The matching module is further configured to perform data removal processing on the first path data based on the driving track data to obtain second path data, wherein the second path data is determined based on a first merging point and a second merging point, the first merging point corresponding to the starting point position, the second merging point corresponding to the ending point position, the first merging point and the second merging point being determined on the full-quantity navigation path based on distance information between a track point on the vehicle driving track and a line point on the full-quantity navigation path, the distance information being calculated according to the driving track data and the first path data, and the matching result being obtained by performing associated matching on the driving track data and the second path data.

11. A vehicle characterized by comprising: A vehicle-mounted memory and a vehicle-mounted processor are included, the vehicle-mounted memory stores a computer program, and the vehicle-mounted processor is configured to run the computer program to execute the full-quantity navigation path generation method of any one of claims 1 to 9.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein the executable program controls a device where the computer-readable storage medium is located to execute the full-quantity navigation path generation method of any one of claims 1 to 9 when the executable program is running.

13. A computer program product, characterised in that, The computer program is implemented when executed by a processor to realize the full-quantity navigation path generation method of any one of claims 1 to 9.

Images