Navigation route planning method and device, electronic equipment and medium

Abstract

The invention provides a navigation route planning method and device, electronic equipment and a medium, and relates to the technical field of image processing, in particular to the technical field of image segmentation and image recognition. According to the implementation scheme, a first tree image and first position information are obtained, the collection time of the first tree image is before the current moment, the first tree image at least comprises a first tree area beside a first road area, and the first position information indicates the geographic position of the first road area; image processing is carried out on the first tree image to obtain tree form information, and the tree form information indicates the contour and the height of a tree in the first tree area; acquiring sun position information at the current moment; according to the first position information, the tree form information and the sun position information, determining a shadow area, projected into the first road area at the current moment, of trees in the first tree area; and determining whether the first road area is to be planned into the navigation route according to the shadow area.

Description

Technical Field

[0001] The present disclosure relates to the field of image processing technology, in particular to the field of image segmentation and image recognition technology, and specifically to a navigation route planning method, device, electronic device, computer-readable storage medium and computer program product. Background Art

[0002] For environmental protection reasons, green and low-carbon transportation methods such as walking and cycling have gradually become people's first choice for travel. However, in the hot summer season, walking or cycling under the sun is undoubtedly a test for users. Relatively speaking, users are more likely to give up walking and cycling and choose to take a taxi instead.

[0003] Based on satellite images, tree blocks can be identified and road networks can be matched on trees on both sides of the road to obtain the tree distribution density around the road and predict whether there may be tree shadows on the road.

[0004] The methods described in this section are not necessarily methods that have been previously conceived or employed. Unless otherwise indicated, it should not be assumed that any method described in this section is considered to be prior art simply because it is included in this section. Similarly, unless otherwise indicated, the issues mentioned in this section should not be considered to have been recognized in any prior art. Summary of the invention

[0005] The present disclosure provides a navigation route planning method, device, electronic device, computer-readable storage medium and computer program product.

[0006] According to one aspect of the present disclosure, a method for planning a navigation route is provided, comprising: acquiring a first tree image and first position information, wherein the acquisition time of the first tree image falls within a first time period before a current moment, the first tree image includes at least a first tree area beside a first road area, and the first position information indicates a geographical location of the first road area; performing image processing on the first tree image to obtain tree morphological information, wherein the tree morphological information indicates the outline and height of trees in the first tree area; acquiring sun position information at the current moment; determining a shadow area cast by the trees in the first tree area onto the first road area at the current moment based on the first position information, the tree morphological information and the sun position information; and determining whether the first road area will be planned into the navigation route based on the shadow area.

[0007] According to another aspect of the present disclosure, a navigation route planning device is provided, comprising: a first acquisition module, configured to acquire a first tree image and first position information, wherein the acquisition time of the first tree image falls within a first time period before a current moment, the first tree image includes at least a first tree area beside a first road area, and the first position information indicates a geographical location of the first road area; a processing module, configured to perform image processing on the first tree image to obtain tree morphological information, wherein the tree morphological information indicates the outline and height of the trees in the first tree area; a second acquisition module, configured to acquire the sun position information at the current moment; a first determination module, configured to determine a shadow area cast by the trees in the first tree area onto the first road area at the current moment according to the first position information, the tree morphological information and the sun position information; and a second determination module, configured to determine whether the first road area will be planned into the navigation route according to the shadow area.

[0008] According to another aspect of the present disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the above method.

[0009] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute the above method.

[0010] According to another aspect of the present disclosure, a computer program product is provided, comprising a computer program, wherein the computer program implements the above method when executed by a processor.

[0011] According to one or more embodiments of the present disclosure, a method for planning a navigation route is provided. The tree shapes are identified by collecting images of trees beside the road, and the sun's position information at the current moment is introduced according to the rising and setting of the sun. The shadow area formed by the trees in a specific road area at the current moment can be accurately determined, so as to plan a more timely and cool navigation route for the user.

[0012] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The accompanying drawings exemplarily illustrate the embodiments and constitute a part of the specification, and together with the text description of the specification, are used to explain the exemplary implementation of the embodiments. The embodiments shown are for illustrative purposes only and do not limit the scope of the claims. In all drawings, the same reference numerals refer to similar but not necessarily identical elements.

[0014] Figure 1 is a schematic diagram illustrating an example system in which the various methods described herein may be implemented according to an exemplary embodiment;

[0015] Figure 2 A flowchart of a method for planning a navigation route according to an embodiment of the present disclosure is shown;

[0016] Figure 3 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown;

[0017] Figure 4 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown;

[0018] Figure 5 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown;

[0019] Figure 6 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown;

[0020] Figure 7 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown;

[0021] Figure 8 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown;

[0022] Fig. 9 A schematic diagram showing a method of determining a shadow area by using geometric calculation according to an embodiment of the present disclosure is shown;

[0023] Fig.10 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown;

[0024] Fig.11 A structural block diagram of a navigation route planning device according to an embodiment of the present disclosure is shown; and

[0025] Fig.12 A structural block diagram of an exemplary electronic device that can be used to implement the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0026] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0027] In the present disclosure, unless otherwise specified, the use of the terms "first", "second", etc. to describe various elements is not intended to limit the positional relationship, temporal relationship, or importance relationship of these elements, and such terms are only used to distinguish one element from another element. In some examples, the first element and the second element may refer to the same instance of the element, and in some cases, based on the description of the context, they may also refer to different instances.

[0028] The terms used in the description of various examples in this disclosure are only for the purpose of describing specific examples and are not intended to be limiting. Unless the context clearly indicates otherwise, if the number of elements is not specifically limited, the element can be one or more. In addition, the term "and / or" used in this disclosure covers any one of the listed items and all possible combinations.

[0029] In the related technology, it is proposed to identify tree blocks and match the road network based on satellite images to obtain the tree distribution density around the road to predict whether there may be tree shadows on the road. However, due to the low frequency of satellite image updates, the identified road network tree conditions are usually quite different from the actual ones, and the shadow coverage of the navigation route is ultimately less accurate, resulting in a poor user experience.

[0030] To solve the above problems, the present disclosure provides a navigation route planning method, which identifies the shape contours of trees by collecting images of trees beside the road, and introduces the sun's position information at the current moment according to the rising and setting of the sun. It can accurately determine the shadow area formed by the trees in a specific road area at the current moment, and plan a more timely and cool navigation route for users.

[0031] The embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings.

[0032] Figure 1 FIG. 1 is a schematic diagram of an exemplary system 100 in which various methods and apparatuses described herein may be implemented according to an embodiment of the present disclosure. Figure 1, the system 100 includes one or more client devices 101, 102, 103, 104, 105, and 106, a server 120, and one or more communication networks 110 coupling the one or more client devices to the server 120. The client devices 101, 102, 103, 104, 105, and 106 may be configured to execute one or more applications.

[0033] In an embodiment of the present disclosure, the server 120 may run one or more services or software applications that enable the method for planning a navigation route to be executed.

[0034] In some embodiments, server 120 may also provide other services or software applications that may include non-virtualized environments and virtualized environments. In some embodiments, these services may be provided as web-based services or cloud services, such as provided to users of client devices 101, 102, 103, 104, 105, and / or 106 under a software as a service (SaaS) model.

[0035] exist Figure 1 In the configuration shown, the server 120 may include one or more components that implement the functions performed by the server 120. These components may include software components, hardware components, or a combination thereof that can be executed by one or more processors. Users operating client devices 101, 102, 103, 104, 105, and / or 106 may in turn utilize one or more client applications to interact with the server 120 to utilize the services provided by these components. It should be understood that a variety of different system configurations are possible, which may differ from the system 100. Therefore, Figure 1 is an example of a system for implementing the navigation route planning method described herein and is not intended to be limiting.

[0036] The user may use client devices 101, 102, 103, 104, 105 and / or 106 to perform the method of planning a navigation route. The client device may provide an interface that enables the user of the client device to interact with the client device. The client device may also output information to the user via the interface. Figure 1 Only six client devices are depicted, but one skilled in the art will appreciate that the present disclosure may support any number of client devices.

[0037] Client devices 101, 102, 103, 104, 105 and / or 106 may include various types of computer devices, such as portable handheld devices, general-purpose computers (such as personal computers and laptop computers), workstation computers, wearable devices, smart screen devices, self-service terminal devices, service robots, game systems, thin clients, various messaging devices, sensors or other sensing devices, etc. These computer devices may run various types and versions of software applications and operating systems, such as MICROSOFT Windows, APPLE iOS, UNIX-like operating systems, Linux or Linux-like operating systems (such as GOOGLE Chrome OS); or include various mobile operating systems, such as MICROSOFT Windows Mobile OS, iOS, Windows Phone, Android. Portable handheld devices may include cellular phones, smart phones, tablet computers, personal digital assistants (PDAs), etc. Wearable devices may include head-mounted displays (such as smart glasses) and other devices. Game systems may include various handheld game devices, Internet-enabled game devices, etc. Client devices are capable of executing various different applications, such as various Internet-related applications, communication applications (such as email applications), short message service (SMS) applications, and may use various communication protocols.

[0038] The network 110 may be any type of network known to those skilled in the art that may support data communications using any of a variety of available protocols, including but not limited to TCP / IP, SNA, IPX, etc. By way of example only, the one or more networks 110 may be a local area network (LAN), an Ethernet-based network, a token ring, a wide area network (WAN), the Internet, a virtual network, a virtual private network (VPN), an intranet, an extranet, a public switched telephone network (PSTN), an infrared network, a wireless network (e.g., Bluetooth, WIFI), and / or any combination of these and / or other networks.

[0039] Server 120 may include one or more general purpose computers, dedicated server computers (e.g., PC (personal computer) servers, UNIX servers, mid-range servers), blade servers, mainframe computers, server clusters, or any other suitable arrangement and / or combination. Server 120 may include one or more virtual machines running virtual operating systems, or other computing architectures involving virtualization (e.g., one or more flexible pools of logical storage devices that may be virtualized to maintain a server's virtual storage device). In various embodiments, server 120 may run one or more services or software applications that provide the functionality described below.

[0040] The computing units in the server 120 may run one or more operating systems including any of the above operating systems and any commercially available server operating systems. The server 120 may also run any of a variety of additional server applications and / or middle-tier applications, including HTTP servers, FTP servers, CGI servers, JAVA servers, database servers, etc.

[0041] In some implementations, server 120 may include one or more applications to analyze and consolidate data feeds and / or event updates received from users of client devices 101, 102, 103, 104, 105, and 106. Server 120 may also include one or more applications to display data feeds and / or real-time events via one or more display devices of client devices 101, 102, 103, 104, 105, and 106.

[0042] In some embodiments, the server 120 may be a server of a distributed system, or a server combined with a blockchain. The server 120 may also be a cloud server, or an intelligent cloud computing server or intelligent cloud host with artificial intelligence technology. A cloud server is a host product in a cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and virtual private servers (VPS) services.

[0043] The system 100 may also include one or more databases 130. In some embodiments, these databases may be used to store image information, road network information, and other information. For example, one or more of the databases 130 may be used to store images of trees collected and road network information for navigation route planning. The databases 130 may reside in various locations. For example, the database used by the server 120 may be local to the server 120, or may be remote from the server 120 and may communicate with the server 120 via a network-based or dedicated connection. The databases 130 may be of different types. In some embodiments, the database used by the server 120 may be, for example, a relational database. One or more of these databases may store, update, and retrieve data from the database in response to a command.

[0044] In some embodiments, one or more of the databases 130 may also be used by applications to store application data. The databases used by the applications may be different types of databases, such as a key-value store, an object store, or a conventional store backed by a file system.

[0045] Figure 1The system 100 may be configured and operated in various ways to enable the application of various methods and apparatuses described in the present disclosure.

[0046] Figure 2 A flowchart of a method for planning a navigation route according to an embodiment of the present disclosure is shown.

[0047] like Figure 2 As shown, the navigation route planning method 200 includes:

[0048] Step 210: Acquire a first tree image and first location information, wherein the acquisition time of the first tree image falls within a first time period before the current moment, the first tree image at least includes a first tree area beside a first road area, and the first location information indicates a geographical location of the first road area;

[0049] Step 220: performing image processing on the first tree image to obtain tree morphology information, wherein the tree morphology information indicates the outline and height of the trees in the first tree area;

[0050] Step 230, obtaining the sun position information at the current moment;

[0051] Step 240, determining the shadow area cast by the trees in the first tree area on the first road area at the current moment according to the first position information, the tree shape information and the sun position information; and

[0052] Step 250: Determine whether the first road area will be planned into the navigation route according to the shadow area.

[0053] Based on this, the tree shape outlines are identified by collecting images of trees beside the road, and the current sun position information is introduced according to the rising and setting of the sun. The shadow area formed by the trees in the specific road area at the current moment can be accurately determined, and a more timely navigation route can be planned for users.

[0054] In addition, the morphology of trees will change significantly due to time factors such as seasons and growing years, so identifying the specific outline morphology of trees rather than geographical distribution density further improves the accuracy of the shadow coverage determined thereby. For example, evergreen trees have many leaves that can cast shadows in both summer and winter, while deciduous trees only have trunks left in winter, and their shadow coverage is significantly reduced at this time. As a result, it is possible to plan shady navigation routes with high shadow coverage for users in summer, and sunny navigation routes with low shadow coverage for users in winter, thereby improving the user's navigation experience.

[0055] In the navigation engine, the road network is fitted based on the linear model. The road linear model usually uses links and nodes to represent the topological structure of the entire road network. Specifically, a link indicates a section of road and is the basic unit of the road model in the navigation system. A node is the endpoint of a link or the intersection between two links.

[0056] In step 210, illustratively, the first road area may correspond to one or more links, and the first location information may include one or more link data, so that a navigation route is subsequently generated based on the one or more link data. In another example, the first location information may also include the latitude and longitude coordinates of the first road area to better determine the local tree type and sunlight conditions.

[0057] In step 210, the first tree area may be a tree area on the left and / or right side of the first road area according to the road condition (e.g., road width) of the first road area and the direction of travel of the user. For example, in countries or regions where people travel on the right side of the road, the first tree area usually considers the tree area on the right side of the road along the direction of travel of the user. However, for some narrow roads, the trees on the left side of the road may also provide shade for the user at a certain time, so the first tree area may also include tree areas on both sides of the road.

[0058] In step 210, the distance between the first time period and the current moment should not be too long, so that the first tree image collected can fully reflect the morphological characteristics of the tree at the current moment. In an example, the first time period can be one minute before the current moment, so that a tree image with a more real-time outline morphology can be obtained; in another example, since the growth rate of trees is slow, the first time period can also be one month before the current moment during the non-seasonal period, so as to reduce the frequency of image collection and reduce costs while avoiding the impact of seasonal changes on tree morphology.

[0059] Figure 3 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown.

[0060] like Figure 3 As shown, according to some embodiments, step 210 includes:

[0061] Step 311: In response to a navigation request instruction from a user, determine a geographical location of a first road area and generate first location information; and

[0062] Step 312: Acquire an image including a first tree area, which is collected by a vehicle-mounted camera at a geographical location of a first road area within a first time period, as a first tree image.

[0063] Therefore, compared with using satellite images, collecting tree images in the first road area through the on-board camera is more timely and convenient to obtain, and can provide clearer multi-angle tree images, which helps to improve the recognition of details of tree contours and make the determined shadow areas more real-time and accurate.

[0064] In step 312 , illustratively, multiple initial tree images may be acquired based on the Internet of Vehicles, and then images meeting the conditions may be screened out based on acquisition locations and acquisition times as the first tree images.

[0065] In many cases, the first tree image collected also includes a second tree area that will not form a shadow on the first road area. Figure 4 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown.

[0066] like Figure 4 As shown, according to some embodiments, before step 220, method 200 further includes:

[0067] Step 410, in response to determining that the first tree image includes a second tree region beside the second road region in addition to the first tree region, cropping the first tree image to obtain a cropped image including only the first tree region; and

[0068] Step 420: Use the cropped image to update the first tree image.

[0069] By cutting out the irrelevant tree area in the first tree image in advance, the difficulty of subsequently identifying the tree outlines in the first tree area is effectively reduced, and the image processing efficiency is improved.

[0070] In step 410, the position boundary of the first tree area and the second tree area may change according to the current time. For example, for any tree near the boundary of the first road area and the second road area, according to the sun's angle at different times, the tree may form a shadow on the first road area at the first time in the morning and form a shadow on the second road area at the second time in the afternoon.

[0071] Therefore, in one or more embodiments, in addition to the user's traveling direction and road conditions, the sun's position information at the current moment may be used as a distinguishing condition between the first tree area and the second tree area in the first tree image to increase the correlation between the trees in the first tree area and the shadow area of ​​the first road area. Furthermore, the formation of the shadow area may also be affected by the height of the trees, so the height of the trees may also be considered as a distinguishing condition between the first tree area and the second tree area.

[0072] In step 220 , the image processing may be, for example, image segmentation and image recognition. Figure 5 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown.

[0073] like Figure 5 As shown, according to some embodiments, step 220 includes:

[0074] Step 521: Use the image segmentation model to perform image segmentation processing on the first tree image to obtain a tree region mask, wherein the tree region mask indicates the outlines of the trees in the first tree region;

[0075] Step 522: Use the first image recognition model to perform image recognition processing on the tree mask to obtain a tree detection frame, wherein the tree detection frame indicates the outline of the tree in the first tree area;

[0076] Step 523, performing mapping calculation on the tree detection frame to obtain tree height information; and

[0077] Step 524: Generate tree morphology information based on the tree detection frame and tree height information.

[0078] The image segmentation model and the image recognition model are used to process the first tree image at the same time. The detection results of the two are complementary, which greatly enriches the detailed information of the tree outline and makes the detected tree outline more accurate. In addition, the image recognition processing also provides tree height information, which can help to realize the subsequent tree projection mapping calculation based on sunlight.

[0079] According to some embodiments, the first tree area includes a plurality of trees. In this case, if a projection mapping is performed based on determining a specific height of each tree, a lot of time and resources are required. Figure 6 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown.

[0080] like Figure 6 As shown, step 523 includes:

[0081] Step 6231: perform mapping calculation on the tree detection frame to obtain the height of each tree among the multiple trees; and

[0082] Step 6232: Calculate the average of the height of each tree among the multiple trees, and generate tree height information based on the result of the average calculation.

[0083] The heights of trees on the same side of the road are often not much different, so replacing the heights of all trees with their average height can improve processing efficiency and reduce implementation difficulty.

[0084] Figure 7A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown.

[0085] According to some embodiments, Figure 7 As shown, in addition to the above steps 521 to 524, step 220 also includes:

[0086] Step 725: Use the second image recognition model to perform image recognition processing on the tree mask to obtain a tree crown detection frame, wherein the tree crown detection frame indicates the tree crown area within the first tree area; and

[0087] Step 726: Generate tree morphology information based on the tree crown detection frame and tree height information.

[0088] Generally speaking, most of the shade is formed by the crown of the tree, that is, whether the crown of the tree is densely covered with branches and leaves determines its shading effect. Based on this, image recognition can be performed only on the crown area of ​​the trees in the first tree area, so as to exclude some bare trees, so as to simplify the processing process while ensuring that the confirmed shadow coverage is effective.

[0089] In step 230, illustratively, the sun position information may be calculated based on the current time, or may be directly obtained through an observatory or similar platform.

[0090] Figure 8 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown.

[0091] According to some embodiments, Figure 8 As shown, step 240 includes:

[0092] Step 841, determining the light rays formed by the sunlight irradiating the first road area at the current moment according to the first position information and the sun position information;

[0093] Step 842: determining the relative position relationship between the trees in the first tree area and the first road area according to the first position information and the tree morphology information; and

[0094] Step 843: Determine the shadow area using geometric calculations based on the light rays and the relative position relationship.

[0095] In step 841, specifically, after determining the first position information and the sun position information, the sun's rays at the corresponding moment may be directly acquired based on an observatory or a similar platform, and the sun's rays may include, for example, the sun's altitude angle and the irradiation direction for the first road area.

[0096] In step 842 , illustratively, the relative position relationship includes but is not limited to the distance (eg, vertical distance and horizontal distance) of each point in the boundary contour of the first tree region relative to the first road region.

[0097] Fig. 9 A schematic diagram showing a method of determining a shadow area by using geometric calculation according to an embodiment of the present disclosure is shown.

[0098] See also Fig. 9 , point A is any point of the boundary contour of the first tree area. At this time, the height of the point relative to the first road area (tree height) and the sun altitude angle are known, and the position of point B can be calculated based on trigonometric functions as the corresponding shadow area contour point. By analogy, the shadow area in step 843 can be determined.

[0099] Therefore, by means of geometric calculation, the first tree area can be projected onto the first road area in a relatively simple manner to determine the shadow area formed at the current moment.

[0100] According to some embodiments, step 250 includes: in response to the current moment falling within a second time period of the year, and in response to the ratio of the area of ​​the shadow area to the area of ​​the first road area being greater than a second threshold, determining that the first road area will be planned into the navigation route; and in response to the current moment falling within a third time period of the year, and in response to the ratio of the area of ​​the shadow area to the area of ​​the first road area being less than a fourth threshold, determining that the first road area will be planned into the navigation route.

[0101] Furthermore, the target road area includes a plurality of first road areas, and the method 200 further includes: step 260, in response to determining that the number of first road areas to be planned into the navigation route is greater than a third threshold value among the plurality of first road areas included in the target road area, and taking the target road area as the target navigation route.

[0102] In one or more embodiments, if the user wishes to travel on a cool route in the summer, a route with a higher coverage of shadow areas may be selected as the navigation route. At this time, in step 250, the second time period indicates the summer of the year (e.g., June to August), and in response to the current time being summer and the ratio of the area of ​​the shadow area to the area of ​​the first road area being greater than the second threshold, it is determined that the first road area will be planned into the navigation route.

[0103] In one or more embodiments, if the user wishes to travel on a sunny route in winter, a route with a low coverage of shadow areas may be selected as the navigation route. At this time, in step 250, the third time period indicates the winter season of the year (e.g., December to February of the following year), and in response to the current time being winter, and in response to the ratio of the area of ​​the shadow area to the area of ​​the first road area being less than the fourth threshold, it is determined that the first road area will be planned into the navigation route.

[0104] In an example, the second threshold may be 30%, 50% or 70%, the fourth threshold may be 30%, 50% or 70%, and the second threshold and the fourth threshold may be the same or different, without limitation.

[0105] As a result, users can obtain ideal travel navigation routes in a variety of scenarios, improving the user experience.

[0106] In step 260, the first road area only indicates a link of the road network, and the complete navigation route planned for the user may need to be composed of multiple links. In this case, a single first road area can be used as a basic unit to screen out a combination of multiple first road areas between the user's starting point and end point that can be combined and whose shadow area coverage meets the requirements, thereby generating a final navigation route.

[0107] In an example, the third threshold may be 10, 50, 100, or 500, without limitation.

[0108] Fig.10 A partial flow chart of another navigation route planning method according to an embodiment of the present disclosure is shown.

[0109] According to some embodiments, the first road area includes a left road area and a right road area, such as Fig.10 As shown, step 250 includes:

[0110] Step 1051: Determine the direction of travel of the user in the first road area according to the navigation starting point and the navigation end point input by the user;

[0111] Step 1052: in response to determining according to the traveling direction that the user needs to travel in the left road area, determining according to the intersection of the shadow area and the left road area whether the first road area is to be planned into the navigation route; and

[0112] Step 1053: In response to determining that the user needs to travel in the right road area according to the traveling direction, determine whether the first road area will be planned into the navigation route according to the intersection of the shadow area and the right road area.

[0113] For two-way roads, depending on the user's direction of travel, only the shadow coverage of one side of the road can be considered, thereby saving costs and improving the efficiency of navigation route planning.

[0114] Fig.11 A structural block diagram of a navigation route planning device according to an embodiment of the present disclosure is shown.

[0115] According to another aspect of the present disclosure, a data quantization device of an optimizer is provided. Fig.11 As shown, the navigation route planning device 1100 includes: a first acquisition module 1110, configured to acquire a first tree image and first position information, wherein the acquisition time of the first tree image falls within a first time period before the current moment, the first tree image at least includes a first tree area beside a first road area, and the first position information indicates the geographical location of the first road area; a processing module 1120, configured to perform image processing on the first tree image to obtain tree morphological information, wherein the tree morphological information indicates the outline and height of the trees in the first tree area; a second acquisition module 1130, configured to acquire the sun position information at the current moment; a first determination module 1140, configured to determine the shadow area projected by the trees in the first tree area into the first road area at the current moment according to the first position information, the tree morphological information and the sun position information; and a second determination module 1150, configured to determine whether the first road area will be planned into the navigation route according to the shadow area.

[0116] According to another aspect of the present disclosure, an electronic device is also provided, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the aforementioned method.

[0117] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is further provided, wherein the computer instructions are used to enable the computer to execute the aforementioned method.

[0118] According to another aspect of the present disclosure, a computer program product is also provided, including a computer program, wherein the computer program implements the aforementioned method when executed by a processor.

[0119] like Fig.12As shown, the electronic device 1200 includes a computing unit 1201, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1202 or a computer program loaded from a storage unit 1208 into a random access memory (RAM) 1203. In the RAM 1203, various programs and data required for the operation of the electronic device 1200 can also be stored. The computing unit 1201, the ROM 1202, and the RAM 1203 are connected to each other via a bus 1204. An input / output (I / O) interface 1205 is also connected to the bus 1204.

[0120] Multiple components in the electronic device 1200 are connected to the I / O interface 1205, including: an input unit 1206, an output unit 1207, a storage unit 1208, and a communication unit 1209. The input unit 1206 can be any type of device that can input information to the electronic device 1200. The input unit 1206 can receive input digital or character information and generate key signal input related to user settings and / or function control of the electronic device, and can include but is not limited to a mouse, a keyboard, a touch screen, a trackpad, a trackball, a joystick, a microphone and / or a remote control. The output unit 1207 can be any type of device that can present information, and can include but is not limited to a display, a speaker, a video / audio output terminal, a vibrator and / or a printer. The storage unit 1208 can include but is not limited to a disk and an optical disk. The communication unit 1209 allows the electronic device 1200 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks, and can include but is not limited to a modem, a network card, an infrared communication device, a wireless communication transceiver and / or a chipset, such as Bluetooth TM devices, 802.11 devices, WiFi devices, WiMax devices, cellular communication devices, and / or the like.

[0121] The computing unit 1201 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1201 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1201 performs the various methods and processes described above, such as a matrix calculation method based on a GPU. For example, in some embodiments, a matrix calculation method based on a GPU may be implemented as a computer software program, which is tangibly included in a machine-readable medium, such as a storage unit 1208. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 1200 via the ROM 1202 and / or the communication unit 1209. When the computer program is loaded into the RAM 1203 and executed by the computing unit 1201, one or more steps of the matrix calculation method based on the GPU described above may be performed. Alternatively, in other embodiments, the computing unit 1201 may be configured to execute a GPU-based matrix calculation method in any other appropriate manner (eg, by means of firmware).

[0122] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0123] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0124] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0125] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0126] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0127] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0128] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps described in this disclosure can be performed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0129] Although the embodiments or examples of the present disclosure have been described with reference to the accompanying drawings, it should be understood that the above-mentioned methods, systems and devices are merely exemplary embodiments or examples, and the scope of the present invention is not limited by these embodiments or examples, but only by the claims after authorization and their equivalent scope. Various elements in the embodiments or examples can be omitted or replaced by their equivalent elements. In addition, each step can be performed in an order different from that described in the present disclosure. Further, the various elements in the embodiments or examples can be combined in various ways. It is important that with the evolution of technology, many elements described herein can be replaced by equivalent elements that appear after the present disclosure.

Claims

1. A method for planning a navigation route, comprising: Acquire a first tree image and first position information, wherein the acquisition time of the first tree image falls within a first time period before the current moment, the first tree image at least includes a first tree area beside a first road area, and the first position information indicates a geographical location of the first road area; Performing image processing on the first tree image to obtain tree morphology information, wherein the tree morphology information indicates the outline and height of the trees in the first tree area; Obtaining the sun position information at the current moment; Determine, based on the first position information, the tree shape information, and the sun position information, a shadow area cast by the trees in the first tree area in the first road area at the current moment; and It is determined whether the first road area is to be planned into a navigation route according to the shadow area.

2. The method according to claim 1, wherein: The obtaining of the first tree image and the first position information includes: In response to a navigation request instruction from a user, determining a geographical location of the first road area and generating the first location information; and An image including the first tree area, which is collected by a vehicle-mounted camera at a geographical location of the first road area within the first time period, is acquired as the first tree image.

3. The method according to claim 1 or 2, before performing image processing on the first tree image to obtain tree morphological information, further comprising: In response to determining that the first tree image includes a second tree area beside a second road area except the first tree area, cropping the first tree image to obtain a cropped image including only the first tree area; as well as The first tree image is updated using the cropped image.

4. The method according to any one of claims 1 to 3, wherein: The performing image processing on the first tree image to obtain tree morphological information includes: Using an image segmentation model to perform image segmentation processing on the first tree image to obtain a tree region mask, wherein the tree region mask indicates the outlines of trees in the first tree region; Using a first image recognition model to perform image recognition processing on the tree mask to obtain a tree detection frame, wherein the tree detection frame indicates the outline of the tree in the first tree area; Performing mapping calculation on the tree detection frame to obtain tree height information; and The tree morphology information is generated according to the tree detection frame and the tree height information.

5. The method according to claim 4, wherein: The first tree area includes a plurality of trees, and wherein the mapping calculation is performed on the tree detection frame to obtain tree height information, including: Performing mapping calculation on the tree detection frame to obtain the height of each tree in the plurality of trees; and The height of each of the plurality of trees is averaged, and the tree height information is generated based on a result of the average calculation.

6. The method according to claim 4 or 5, wherein: The performing image processing on the first tree image to obtain tree morphological information further includes: Using a second image recognition model to perform image recognition processing on the tree mask to obtain a tree crown detection frame, wherein the tree crown detection frame indicates a tree crown region within the first tree region; and The tree morphology information is generated according to the tree crown detection frame and the tree height information.

7. The method according to any one of claims 1 to 6, wherein: The determining, according to the first position information, the tree shape information and the sun position information, a shadow area cast by the trees in the first tree area in the first road area at the current moment comprises: Determine, according to the first position information and the sun position information, a ray of light formed by the sun's rays irradiating the first road area at the current moment; Determining a relative position relationship between trees in the first tree area and the first road area according to the first position information and the tree morphology information; and The shadow area is determined by geometric calculation according to the light ray and the relative position relationship.

8. The method according to any one of claims 1 to 7, wherein: The determining, according to the shadow area, whether the first road area is to be planned into the navigation route comprises: In response to the current moment falling within a second time period of the year, and in response to a ratio of an area of ​​the shadow area to an area of ​​the first road area being greater than a second threshold, determining that the first road area is to be planned into the navigation route; and In response to the current moment falling within a third time period of the year, and in response to the ratio of the area of ​​the shadow area to the area of ​​the first road area being less than a fourth threshold, determining that the first road area is to be planned into the navigation route; And wherein the target road area includes a plurality of the first road areas, the method further comprises: In response to determining that, among the plurality of first road areas included in the target road area, the number of the first road areas to be planned into the navigation route is greater than a third threshold, the target road area is used as a target navigation route.

9. The method according to any one of claims 1 to 8, wherein: The first road area includes a left road area and a right road area, and wherein determining whether the first road area is to be planned into the navigation route according to the shadow area includes: Determining a travel direction of the user in the first road area according to the navigation start point and the navigation end point input by the user; In response to determining, according to the traveling direction, that the user needs to travel in the left road area, determining, according to an intersection of the shadow area and the left road area, whether the first road area is to be planned into a navigation route; and In response to determining, according to the traveling direction, that the user needs to travel in the right road area, determining, according to an intersection of the shadow area and the right road area, whether the first road area will be planned into a navigation route.

10. A navigation route planning device, comprising: A first acquisition module is configured to acquire a first tree image and first position information, wherein the acquisition time of the first tree image falls within a first time period before a current moment, the first tree image at least includes a first tree area beside a first road area, and the first position information indicates a geographical location of the first road area; a processing module configured to perform image processing on the first tree image to obtain tree morphology information, wherein the tree morphology information indicates the outline and height of the trees in the first tree area; A second acquisition module is configured to acquire the sun position information at the current moment; A first determining module is configured to determine a shadow area cast by trees in the first tree area in the first road area at the current moment according to the first position information, the tree morphology information and the sun position information; and The second determination module is configured to determine whether the first road area will be planned into the navigation route according to the shadow area.

11. The device according to claim 10, wherein: The first acquisition module includes: A first generating submodule is configured to determine the geographical location of the first road area and generate the first location information in response to a navigation request instruction of a user; and The acquisition submodule is configured to acquire an image including the first tree area, which is collected by a vehicle-mounted camera at a geographical location of the first road area within the first time period, as the first tree image.

12. The device according to claim 10 or 11, wherein: The device also includes: a cropping module configured to, in response to determining that the first tree image includes a second tree area beside a second road area in addition to the first tree area, crop the first tree image to obtain a cropped image including only the first tree area; and An updating module is configured to update the first tree image using the cropped image.

13. The device according to any one of claims 10 to 12, wherein: The image processing module comprises: a segmentation submodule, configured to perform image segmentation processing on the first tree image using an image segmentation model to obtain a tree region mask, wherein the tree region mask indicates the outlines of trees in the first tree region; a first recognition submodule configured to perform image recognition processing on the tree mask using a first image recognition model to obtain a tree detection frame, wherein the tree detection frame indicates the outline of the tree in the first tree area; A first mapping submodule is configured to perform mapping calculation on the tree detection frame to obtain tree height information; and The second generating submodule is configured to generate the tree morphology information according to the tree detection frame and the tree height information.

14. The device according to claim 13, wherein: The first tree area includes a plurality of trees, and wherein the first mapping submodule is configured to: Performing mapping calculation on the tree detection frame to obtain the height of each tree in the plurality of trees; and The height of each of the plurality of trees is averaged, and the tree height information is generated based on a result of the average calculation.

15. The device according to claim 13 or 14, wherein: The image processing module also includes: a second recognition submodule configured to perform image recognition processing on the tree mask using a second image recognition model to obtain a tree crown detection frame, wherein the tree crown detection frame indicates a tree crown region within the first tree region; and The third generating submodule is configured to generate the tree morphology information according to the tree crown detection frame and the tree height information.

16. The device according to any one of claims 10 to 15, wherein: The first determining module comprises: A first determination submodule is configured to determine, according to the first position information and the sun position information, a light ray formed by the sun's rays irradiating the first road area at the current moment; A second determining submodule is configured to determine a relative position relationship between trees in the first tree area and the first road area according to the first position information and the tree morphology information; and The third determination submodule is configured to determine the shadow area by using geometric calculation according to the light ray and the relative position relationship.

17. The device according to any one of claims 10 to 16, wherein: The second determining module comprises: a fourth determination submodule, configured to determine that the first road area will be planned into the navigation route in response to the current moment falling within a second time period of the year and in response to a ratio of an area of ​​the shadow area to an area of ​​the first road area being greater than a second threshold; and a fifth determination submodule, configured to determine that the first road area will be planned into the navigation route in response to the current moment falling within a third time period of the year and in response to a ratio of an area of ​​the shadow area to an area of ​​the first road area being less than a fourth threshold; And wherein the target road area includes a plurality of the first road areas, the device further includes: The third determination module is configured to determine, in response to a determination that the number of the first road areas to be planned into the navigation route among the multiple first road areas included in the target road area is greater than a third threshold, to use the target road area as a target navigation route.

18. The device according to any one of claims 10 to 17, wherein: The first road area includes a left road area and a right road area, and wherein the second determining module includes: a sixth determination submodule, configured to determine a travel direction of the user in the first road area according to a navigation start point and a navigation end point input by the user; a seventh determination submodule, configured to, in response to determining according to the traveling direction that the user needs to travel in the left road area, determine whether the first road area is to be planned into a navigation route according to an intersection of the shadow area and the left road area; and The eighth determination submodule is configured to determine whether the first road area will be planned into the navigation route according to the intersection of the shadow area and the right road area in response to determining that the user needs to travel in the right road area according to the traveling direction.

19. An electronic device comprising: at least one processor; as well as a memory communicatively coupled to the at least one processor; in The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 9.

20. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-9.

21. A computer program product comprising a computer program, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 9 is implemented.

Images