Route planning method, electronic device and storage medium

Abstract

The embodiment of the present application discloses a route planning method, an electronic device and a storage medium, including: obtaining an order task and a historical order record, wherein the order task includes an order starting point and an order end point, and the historical order record includes multiple historical order routes; constructing a planned route from the order end point to the order starting point; obtaining candidate routes corresponding to multiple candidate order tasks; and planning a target route from the order end point to the order starting point based on a first similarity between the candidate route and the planned route and the historical order route. This solution can avoid the situation where the return vehicle runs empty, thereby reducing the waste of vehicle resources.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and in particular to a route planning method, an electronic device, and a storage medium. Background Art

[0002] With the development of smart devices and mobile Internet technology, new modes of travel combined with the Internet have also flourished. In order to better meet the needs of users, accurately identifying the destination that users want to go to is crucial for route planning.

[0003] Current route planning solutions are applied in many scenarios. In the freight scenario, the navigation route is planned according to the starting point and destination set by the user. However, the existing freight order acceptance scenario only provides freight navigation routes from the starting point to the destination. Therefore, the return vehicle may run empty (i.e. no goods are delivered), resulting in a waste of vehicle resources. Summary of the invention

[0004] The embodiments of the present application provide a route planning method, an electronic device, and a storage medium, which can avoid the situation where a return vehicle runs empty, thereby reducing the waste of vehicle resources.

[0005] The present application provides a route planning method, including:

[0006] Obtaining an order task and a historical order record, wherein the order task includes an order starting point and an order end point, and the historical order record includes multiple historical order routes;

[0007] Constructing a planned route from the order end point to the order start point;

[0008] Obtain candidate routes corresponding to multiple candidate order tasks;

[0009] According to the first similarity between the candidate route and the planned route and the historical order route, a target route from the order end point to the order start point is planned.

[0010] Optionally, in some embodiments, planning a target route from the order end point to the order start point according to the first similarity between the candidate route and the planned route and the historical order route includes:

[0011] Calculating a first similarity between the candidate route and the planned route;

[0012] Determine the candidate route whose first similarity is greater than a first preset value as a first reference route;

[0013] Calculating a second similarity between the historical order route and the planned route;

[0014] Determine the historical order route where the second similarity is greater than a second preset value as a second reference route;

[0015] Based on the first reference route and the second reference route, a target route from the order end point to the order start point is planned.

[0016] Optionally, in some embodiments, planning a target route from the order destination to the order start point based on the first reference route and the second reference route includes:

[0017] Calculating the route overlap between the first reference route and the second reference route;

[0018] The first reference route whose route overlap degree is greater than a third preset value is determined as the target route from the order end point to the order start point.

[0019] Optionally, in some embodiments, calculating the route overlap between the first reference route and the second reference route includes:

[0020] Splitting the first reference route and the second reference route to obtain a first section corresponding to the first reference route and a second section corresponding to the second reference route;

[0021] Calculating a matching degree between the first road segment and the second road segment;

[0022] According to the calculation result, the route overlap between the first reference route and the second reference route is output.

[0023] Optionally, in some embodiments, the method further includes:

[0024] Detecting whether a first similarity corresponding to the first reference route meets a preset condition;

[0025] When it is detected that the first similarity corresponding to the first reference route meets a preset condition, the first reference route is determined as a target route from the order end point to the order start point.

[0026] Optionally, in some embodiments, obtaining candidate routes corresponding to multiple candidate order tasks includes:

[0027] Get multiple candidate order tasks;

[0028] Extracting candidate route information from the candidate order tasks;

[0029] The candidate route information is split to obtain candidate routes corresponding to the candidate order tasks.

[0030] Optionally, in some embodiments, obtaining historical order records includes:

[0031] Get historical order data within a preset range;

[0032] The historical order data is characterized to obtain historical order records.

[0033] Optionally, in some embodiments, after planning a target route from the order end point to the order start point according to the first similarity between the candidate route and the planned route and the historical order route, the method further includes:

[0034] The target route is displayed.

[0035] Correspondingly, the present application also provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the steps of any of the above methods when executing the program.

[0036] The present application also provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0037] The route planning scheme provided in the embodiment of the present application, after obtaining the order task and the historical order record, the order task includes the order starting point and the order end point, and the historical order record includes multiple historical order routes, a planned route from the order end point to the order starting point is constructed, and then, the candidate routes corresponding to the multiple candidate order tasks are obtained, and finally, according to the first similarity between the candidate route and the planned route and the historical order route, the target route from the order end point to the order starting point is planned. In the route planning scheme provided in the present application, the target route from the order end point to the order starting point is planned in combination with the candidate route, the planned route and the historical order route, which can avoid the situation where the return vehicle runs empty, thereby reducing the waste of vehicle resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0039] Figure 1 It is a flowchart of a route planning method provided in an embodiment of the present application;

[0040] Figure 2 It is a schematic diagram of the KNN algorithm;

[0041] Figure 3is a schematic diagram of the structure of a route planning device provided in an embodiment of the present application;

[0042] Figure 4 It is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0044] Embodiments of the present application provide a route planning method, device, electronic device, and storage medium.

[0045] The route planning device may be specifically integrated in a server or a terminal. The server may include an independently operated server or a distributed server, or may include a server cluster composed of multiple servers. The terminal may include a mobile phone, a tablet computer or a personal computer (PC).

[0046] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0047] A route planning method comprises: obtaining an order task and historical order records, constructing a planned route from an order end point to an order start point, obtaining candidate routes corresponding to a plurality of candidate order tasks, and planning a target route from an order end point to an order start point according to a first similarity between the candidate routes and the planned route and the historical order routes.

[0048] See also Figure 1 , Figure 1 A schematic diagram of a route planning method provided in an embodiment of the present application. The specific process of the route planning method may be as follows:

[0049] 101. Get order tasks and historical order records.

[0050] Optionally, the order task includes an order starting point and an order end point, and may also include an order initiation time and an order completion time corresponding to the order task. The historical order record includes multiple historical order routes.

[0051] The order task may be a task stored locally or obtained by accessing a network interface, and the historical order record may be a task obtained by accessing a network interface, depending on the actual situation.

[0052] Optionally, in order to facilitate the subsequent implementation of return route planning, in some embodiments, after obtaining the historical order data, the historical order data is processed to obtain the historical order route, that is, the step of "obtaining historical order records" may specifically include:

[0053] (11) Obtain historical order data within a preset range;

[0054] (12) Perform characterization processing on historical order data to obtain historical order records.

[0055] For example, obtain user delivery requests within a radius of 5 kilometers (including loading and unloading / picking and picking up point information) and match them against the historical order database, and look for historical order data with similar loading and unloading information, where the historical order data includes road network fragment information, road name information, and historical order route information. Then, perform characterization processing on the historical order data, such as converting the historical order data into numerical values ​​to obtain historical order records.

[0056] 102. Build a planned route from the order end point to the order start point.

[0057] In step 102, a planned route from the order end point to the order start point may be constructed according to a preset route construction rule. For example, if the route construction rule is: shortest time, then a route with the shortest time from the order end point to the order start point is constructed; for another example, if the route construction rule is: shortest distance, then a route with the shortest distance from the order end point to the order start point is constructed. The specific configuration may be based on actual conditions and will not be described in detail here.

[0058] 103. Obtain candidate routes corresponding to multiple candidate order tasks.

[0059] For example, according to the concurrent request navigation interface of user delivery requests within a radius of 5 kilometers, the route of the loading and unloading place of each request (user order) can be obtained, and split into road network fragment information (short road segment data with identification) for subsequent aggregation and calculation, that is, optionally, the step of "obtaining candidate routes corresponding to multiple candidate order tasks" specifically includes:

[0060] (21) Obtain multiple candidate order tasks;

[0061] (22) extracting candidate route information from the candidate order tasks;

[0062] (23) Split the candidate route information to obtain the candidate routes corresponding to the candidate order tasks.

[0063] 104. Plan a target route from the order end point to the order start point based on the first similarity between the candidate route and the planned route and the historical order route.

[0064] Among them, the first similarity between the candidate route and the planned route can be calculated, and the first similarity can be the graphic similarity between the candidate route and the planned route. The graphic similarity between the candidate route and the planned route can be calculated by a convolutional neural network, and then, the candidate route with a first similarity greater than a first preset value is determined as the first reference route, and based on the first reference route and the historical order route, the target route from the order end point to the order starting point is planned.

[0065] Optionally, in some embodiments, the step of “planning a target route from the order end point to the order start point according to the first similarity between the candidate route and the planned route and the historical order route” may specifically include:

[0066] (31) calculating a first similarity between the candidate route and the planned route;

[0067] (32) determining the candidate route with a first similarity greater than a first preset value as a first reference route;

[0068] (33) calculating a second similarity between the historical order route and the planned route;

[0069] (34) determining the historical order route with a second similarity greater than a second preset value as a second reference route;

[0070] (35) Based on the first reference route and the second reference route, plan a target route from the order end point to the order start point.

[0071] Optionally, the first similarity between the candidate route and the planned route and the second similarity between the historical order route and the planned route can be calculated based on the K-Nearest Neighbor (KNN) algorithm. The so-called K-nearest neighbor means K nearest neighbors, which means that each sample can be represented by its closest K neighboring values. The nearest neighbor algorithm is a method of classifying each record in a data set.

[0072] Alternatively, the essence of KNN is to calculate the distance between two vectors in the feature space (also known as similarity) and return the closest (most similar) object. By analogy, the distance between two points in the physical space refers to the Euclidean distance between longitude and latitude. The distance calculated in KNN is the Euclidean distance between feature vectors, and the vector most similar to the target (request) is found.

[0073] See also Figure 2 ,like Figure 2As shown in the figure, triangle S and rectangle J are pre-labeled data, representing different categories respectively, and circle T is the data to be classified. If K=3, then there are 2 triangles and 1 square among the K points closest to circle T, and the proportion of triangle S accounts for 2 / 3, so the point to be classified in circle T belongs to the category corresponding to triangle S; if K=5, then there are 2 triangles and 3 squares among the K points closest to circle T, and the proportion of rectangle J accounts for 3 / 5, so the point to be classified in circle T belongs to the category corresponding to rectangle J. It should be noted that the distance d can be the Euclidean distance, of course, it can also be other distances, and it should be selected according to the actual situation.

[0074] It should be noted that the first reference route is not necessarily the best choice, because, in the time dimension, the first reference route and the planned route may not be completely matched, so a second aggregation is required. Therefore, in the present application, the nearest calculation is performed on the historical order route. The purpose of this aggregation is to determine the historical order route (i.e., the second reference route) that is most similar to the planned route in the historical order route. In this aggregation, the current location information is used. The current location information is one of the inputs of the KNN algorithm, so the target route determined subsequently will not deviate too much from the current location. Finally, the route overlap between the first reference route and the second reference route is calculated, and the first reference route with a route overlap greater than the third preset value is determined as the target route from the order end point to the order starting point, that is, optionally, the step of "planning the target route from the order end point to the order starting point based on the first reference route and the second reference route" can specifically include:

[0075] (41) calculating the route overlap between the first reference route and the second reference route;

[0076] (42) A first reference route whose route overlap is greater than a third preset value is determined as a target route from the order end point to the order start point.

[0077] For example, the first reference route and the second reference route are segmented to obtain corresponding first sections and second sections, and then, according to the matching degree between the first section and the second section, the route overlap between the first reference route and the second reference route is determined. That is, optionally, in some embodiments, the step of “calculating the route overlap between the first reference route and the second reference route” includes:

[0078] (51) splitting the first reference route and the second reference route to obtain a first section corresponding to the first reference route and a second section corresponding to the second reference route;

[0079] (52) calculating the matching degree between the first road segment and the second road segment;

[0080] (53) Based on the calculation result, the route overlap between the first reference route and the second reference route is output.

[0081] For example, based on the position of the first section in the first reference route, the position of the second section in the second reference route, and the section similarity between the first section and the second section, the matching degree between the first section and the second section is output; finally, based on the calculation result, the route overlap degree between the first reference route and the second reference route is output.

[0082] Furthermore, in order to improve the accuracy of the calculation results, the direction corresponding to the first section and the direction corresponding to the second section can also be obtained. Based on the position of the first section in the first reference route, the position of the second section in the second reference route, the section similarity between the first section and the second section, and the obtained direction, the matching degree between the first section and the second section is output. Of course, other section information corresponding to the first section and the second section, such as section length and other information, can also be obtained to improve the accuracy of the calculation results. The specific selection can be made according to the actual situation and will not be repeated here.

[0083] The overlap calculation is an operation in which the online service recalculates the overlap of the path with all the routes in the order pool, with the purpose of finding orders with routes that are as similar as possible from routes with different starting and ending points, and finally recommending orders with overlap greater than a threshold to be displayed to the driver. That is, optionally, in some embodiments, step 104 may further include: displaying the target route.

[0084] Optionally, in some embodiments, when the first similarity of the first reference route meets certain conditions, the first reference route is determined as the target route, that is, the method of the present application may further include:

[0085] (61) detecting whether a first similarity corresponding to the first reference route satisfies a preset condition;

[0086] (62) When it is detected that the first similarity corresponding to the first reference route meets the preset condition, the first reference route is determined as the target route from the order end point to the order start point.

[0087] For example, if the preset condition is that the similarity is 100% and the order time is the same, the first reference route is determined as the target route from the order end point to the order starting point; for another example, if the preset condition is that the similarity is 100% and the order time is within 10 minutes, the first reference route is determined as the target route from the order end point to the order starting point. The specific settings can be made according to the actual situation and will not be repeated here.

[0088] After obtaining the order task and the historical order record, the embodiment of the present application constructs a planned route from the order end point to the order starting point after the order task and the historical order record are obtained. The order task includes the order starting point and the order end point, and the historical order record includes multiple historical order routes. Then, the candidate routes corresponding to the multiple candidate order tasks are obtained. Finally, according to the first similarity between the candidate route and the planned route and the historical order route, the target route from the order end point to the order starting point is planned. In the route planning scheme provided by the present application, the target route from the order end point to the order starting point is planned in combination with the candidate route, the planned route and the historical order route, which can avoid the situation where the return vehicle runs empty, thereby reducing the waste of vehicle resources.

[0089] In order to facilitate better implementation of the route planning method of the embodiment of the present application, the embodiment of the present application also provides a route planning device based on the above (hereinafter referred to as the planning device). The meaning of the terms is the same as in the above route planning method, and the specific implementation details can refer to the description in the method embodiment.

[0090] See also Figure 3 , Figure 3 A schematic diagram of the structure of a route planning device provided in an embodiment of the present application, wherein the planning device may include a first acquisition module 201, a construction module 202, a second acquisition module 203 and a planning module 204, which may be specifically as follows:

[0091] The first acquisition module 201 is used to acquire order tasks and historical order records.

[0092] Optionally, the order task includes an order starting point and an order end point, and may also include an order initiation time and an order completion time corresponding to the order task. The historical order record includes multiple historical order routes.

[0093] The order task may be a task stored locally or obtained by accessing a network interface, and the historical order record may be a task obtained by accessing a network interface, depending on the actual situation.

[0094] Optionally, in order to facilitate the subsequent implementation of return route planning, in some embodiments, after obtaining the historical order data, the historical order data is processed to obtain the historical order route.

[0095] Optionally, in some embodiments, the first acquisition module 201 may be specifically used to: acquire historical order data within a preset range, perform characterization processing on the historical order data, and obtain historical order records.

[0096] The construction module 202 is used to construct a planned route from the order end point to the order start point.

[0097] For example, the construction module 202 can construct a planned route from the order end point to the order starting point according to a preset route construction rule. For example, if the route construction rule is: shortest time, then the route with the shortest time from the order end point to the order starting point is constructed; for another example, if the route construction rule is: shortest distance, then the route with the shortest distance from the order end point to the order starting point is constructed.

[0098] The second acquisition module 203 is used to acquire candidate routes corresponding to multiple candidate order tasks.

[0099] For example, the second acquisition module 203 can concurrently request the navigation interface based on user delivery requests within a radius of 5 kilometers, obtain the route of the loading and unloading location for each request (user order), and split it into road network fragment information (identified short section data) for subsequent aggregation and calculation.

[0100] The planning module 204 is used to plan a target route from the order end point to the order start point according to the first similarity between the candidate route and the planned route and the historical order route.

[0101] Among them, the first similarity between the candidate route and the planned route can be calculated, and the first similarity can be the graphic similarity between the candidate route and the planned route. The graphic similarity between the candidate route and the planned route can be calculated by a convolutional neural network, and then, the candidate route with a first similarity greater than a first preset value is determined as the first reference route, and based on the first reference route and the historical order route, the target route from the order end point to the order starting point is planned.

[0102] Optionally, in some embodiments, the planning module 204 may specifically include:

[0103] A first calculation unit, used to calculate a first similarity between the candidate route and the planned route;

[0104] A first determining unit, configured to determine a candidate route whose first similarity is greater than a first preset value as a first reference route;

[0105] A second calculation unit, used to calculate a second similarity between the historical order route and the planned route;

[0106] A second determining unit, configured to determine a historical order route whose second similarity is greater than a second preset value as a second reference route;

[0107] The planning unit is used to plan a target route from an order end point to an order start point based on a first reference route and a second reference route.

[0108] Optionally, in some embodiments, the planning unit may specifically include:

[0109] A calculation subunit, used to calculate the route overlap between the first reference route and the second reference route;

[0110] The determination subunit is used to determine a first reference route whose route overlap is greater than a third preset value as a target route from an order end point to an order start point.

[0111] Optionally, in some embodiments, the calculation subunit can be specifically used to: divide the first reference route and the second reference route to obtain a first section corresponding to the first reference route and a second section corresponding to the second reference route; calculate the matching degree between the first section and the second section; and output the route overlap degree between the first reference route and the second reference route based on the calculation result.

[0112] Optionally, in some embodiments, the planning module 204 may also be used to display the target route.

[0113] After the first acquisition module 201 of the embodiment of the present application acquires the order task and the historical order record, the order task includes the order starting point and the order end point, and the historical order record includes multiple historical order routes. The construction module 202 constructs a planned route from the order end point to the order starting point, and then the second acquisition module 203 acquires the candidate routes corresponding to the multiple candidate order tasks. Finally, the planning module 204 plans the target route from the order end point to the order starting point according to the first similarity between the candidate route and the planned route and the historical order route. In the route planning scheme provided in the present application, the target route from the order end point to the order starting point is planned in combination with the candidate route, the planned route and the historical order route, which can avoid the situation where the return vehicle runs empty, thereby reducing the waste of vehicle resources.

[0114] In addition, the present application also provides an electronic device, such as Figure 4 As shown, it shows a schematic diagram of the structure of the electronic device involved in the embodiment of the present application, specifically:

[0115] The electronic device may include components such as a processor 301 with one or more processing cores, a memory 302 with one or more computer-readable storage media, a power supply 303, and an input unit 304. Those skilled in the art will appreciate that Figure 4 The electronic device structure shown in the figure does not constitute a limitation on the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0116] The processor 301 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 302, and calling data stored in the memory 302, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. Optionally, the processor 301 may include one or more processing cores; preferably, the processor 301 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 301.

[0117] The memory 302 can be used to store software programs and modules. The processor 301 executes various functional applications and route planning by running the software programs and modules stored in the memory 302. The memory 302 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area may store data created according to the use of the electronic device, etc. In addition, the memory 302 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices. Accordingly, the memory 302 may also include a memory controller to provide the processor 301 with access to the memory 302.

[0118] The electronic device also includes a power supply 303 for supplying power to each component. Preferably, the power supply 303 can be logically connected to the processor 301 through a power management system, so that the power management system can manage charging, discharging, power consumption and other functions. The power supply 303 can also include one or more DC or AC power supplies, recharging systems, power failure detection circuits, power converters or inverters, power status indicators and other arbitrary components.

[0119] The electronic device may further include an input unit 304, which may be used to receive input digital or character information and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0120] Although not shown, the electronic device may further include a display unit, etc., which will not be described in detail herein. Specifically in this embodiment, the processor 301 in the electronic device will load the executable files corresponding to the processes of one or more application programs into the memory 302 according to the following instructions, and the processor 301 will run the application programs stored in the memory 302, thereby realizing various functions, as follows:

[0121] Acquire the text to be searched; perform entity segmentation on the text to be searched to obtain at least one entity corresponding to the text to be searched; determine the entity identifier corresponding to each entity in the text to be searched according to a preset association relationship; and output the target location corresponding to the text to be searched based on the entity identifier corresponding to each entity and the identifier type corresponding to the entity identifier.

[0122] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0123] After obtaining the text to be searched, the embodiment of the present application performs entity segmentation on the text to be searched to obtain at least one entity corresponding to the text to be searched, and then, based on the preset association relationship, determines the entity identifier corresponding to each entity in the text to be searched, and finally, based on the entity identifier corresponding to each entity and the identifier type corresponding to the entity identifier, outputs the target location corresponding to the text to be searched. The route planning solution provided by the present application can perform entity segmentation on the text to be searched to reduce the impact of meaningless words on the search results, and outputs the target location corresponding to the text to be searched based on the entity identifier corresponding to each entity and the identifier type corresponding to the entity identifier, thereby not only improving the locations recalled during route planning, but also improving the accuracy of route planning.

[0124] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0125] To this end, an embodiment of the present application provides a storage medium in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the steps in any route planning method provided in the embodiment of the present application. For example, the instructions can execute the following steps:

[0126] Acquire the text to be searched; perform entity segmentation on the text to be searched to obtain at least one entity corresponding to the text to be searched; determine the entity identifier corresponding to each entity in the text to be searched according to a preset association relationship; and output the target location corresponding to the text to be searched based on the entity identifier corresponding to each entity and the identifier type corresponding to the entity identifier.

[0127] The specific implementation of the above operations can be found in the previous embodiments, which will not be described in detail here.

[0128] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0129] Since the instructions stored in the storage medium can execute the steps in any route planning method provided in the embodiments of the present application, the beneficial effects that can be achieved by any route planning method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0130] The route planning method, device, electronic device and storage medium provided in the embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A route planning method, characterized in that: include: Obtaining an order task and a historical order record, wherein the order task includes an order starting point and an order end point, and the historical order record includes multiple historical order routes; Constructing a planned route from the order end point to the order start point; Obtain candidate routes corresponding to multiple candidate order tasks; Planning a target route from the order end point to the order start point according to the first similarity between the candidate route and the planned route and the historical order route, specifically comprising: Calculating a first similarity between the candidate route and the planned route; Determine the candidate route whose first similarity is greater than a first preset value as a first reference route; Calculating a second similarity between the historical order route and the planned route; Determine the historical order route where the second similarity is greater than a second preset value as a second reference route; Planning a target route from the order end point to the order start point based on the first reference route and the second reference route; The obtaining of historical order records includes: Get historical order data within a preset range; The historical order data is characterized to obtain historical order records.

2. The method according to claim 1, characterized in that The planning of a target route from the order end point to the order start point based on the first reference route and the second reference route includes: Calculating the route overlap between the first reference route and the second reference route; The first reference route whose route overlap degree is greater than a third preset value is determined as the target route from the order end point to the order start point.

3. The method according to claim 2, characterized in that The calculating the route overlap between the first reference route and the second reference route includes: Splitting the first reference route and the second reference route to obtain a first section corresponding to the first reference route and a second section corresponding to the second reference route; Calculating a matching degree between the first road segment and the second road segment; According to the calculation result, the route overlap between the first reference route and the second reference route is output.

4. The method according to claim 1, characterized in that: Also includes: Detecting whether a first similarity corresponding to the first reference route meets a preset condition; When it is detected that the first similarity corresponding to the first reference route meets a preset condition, the first reference route is determined as a target route from the order end point to the order start point.

5. The method according to any one of claims 1 to 4, characterized in that: The step of obtaining candidate routes corresponding to multiple candidate order tasks includes: Get multiple candidate order tasks; Extracting candidate route information from the candidate order tasks; The candidate route information is split to obtain candidate routes corresponding to the candidate order tasks.

6. The method according to any one of claims 1 to 4, characterized in that: After planning a target route from the order end point to the order start point according to the first similarity between the candidate route and the planned route and the historical order route, the method further includes: The target route is displayed.

7. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the steps of the route planning method according to any one of claims 1 to 6 are implemented.

8. A computer-readable storage medium, characterized in that: A computer program is stored thereon, wherein when the computer program is executed by a processor, the steps of the route planning method according to any one of claims 1 to 6 are implemented.

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