Map-based path state processing method and device

Abstract

The application provides a map-based path state processing method and device, electronic equipment and a computer readable storage medium; the method comprises: displaying a target path in a map page; displaying a query condition setting area for the target path in the map page; in response to a query condition setting operation received in the query condition setting area, displaying a query condition set for the target path by the query condition setting operation; wherein the query condition at least comprises a departure date interval; in the map page, display the arrival duration corresponding to at least one departure time in the departure date interval; wherein the arrival duration is the time consumption of traveling along the target path. Through the application, intelligent travel path planning service can be realized.

Description

Technical Field

[0001] This application relates to artificial intelligence and transportation technology, and in particular to a map-based path status processing method, apparatus, electronic device, and computer-readable storage medium. Background Technology

[0002] Artificial intelligence (AI) is the theory, methods, technology, and application system that uses digital computers or machines controlled by digital computers to simulate, extend, and expand human intelligence, perceive the environment, acquire knowledge, and use that knowledge to obtain optimal results.

[0003] Artificial intelligence-based smart transportation technologies are being widely applied, especially as urbanization accelerates and traffic congestion becomes a significant factor hindering urban development and impacting people's travel quality. To avoid traffic congestion and reduce travel time, people are accustomed to choosing routes and deciding departure times based on road information (such as traffic conditions) provided by their devices. However, the road information provided by these technologies is relatively limited and lacks reliable reference value. Summary of the Invention

[0004] This application provides a map-based route status processing method, apparatus, electronic device, and computer-readable storage medium, which can achieve intelligent travel decision-making by providing the departure time and arrival time of the route.

[0005] The technical solution of this application embodiment is implemented as follows:

[0006] This application provides a map-based path status processing method, including:

[0007] Display the target path on the map page;

[0008] The map page displays a query criteria setting area for the target path;

[0009] In response to a query condition setting operation received in the query condition setting area, display the query conditions set by the query condition setting operation for the target path;

[0010] The query criteria include at least a departure date range;

[0011] The map page displays the arrival time corresponding to at least one departure time within the departure date range;

[0012] The arrival time is the time taken to travel along the target path.

[0013] This application provides a map-based path status processing device, including:

[0014] The display module is configured to display a target path on a map page; further configured to display a query condition setting area for the target path on the map page; further configured to display the query conditions set by the query condition setting operation for the target path in response to a query condition setting operation received in the query condition setting area; wherein the query conditions include at least a departure date range; and further configured to display the arrival time corresponding to at least one departure time in the departure date range on the map page; wherein the arrival time is the time taken to travel along the target path.

[0015] In the above scheme, the query condition setting area includes a date selection area; the display module is further used for:

[0016] In response to the query condition setting operation received in the date selection area for setting at least one endpoint date, the departure date range corresponding to the set at least one endpoint date is displayed.

[0017] In the above scheme, the query condition setting area also includes a time selection area; the display module is further used for:

[0018] In response to the query condition setting operation received in the time selection area for setting the departure time, at least one selected time is displayed as the departure time.

[0019] In the above scheme, when the start date and end date of the departure date range are different departure dates, the display module is further configured to:

[0020] Perform at least one of the following operations:

[0021] For each departure date in the range of departure dates, display the first arrival time corresponding to the departure time set by the query condition setting area;

[0022] Wherein, when the departure date is a historical date, the first arrival time is the actual arrival time from the departure time; when the departure date is a current date or a future date, the first arrival time is the predicted arrival time from the departure time.

[0023] For each departure date in the range of departure dates, display the target departure time and the corresponding second arrival time for each departure date;

[0024] Wherein, when the departure date is a historical date, the target departure time is the actual departure time with the shortest travel time, and the second arrival time is the actual arrival time with the shortest travel time; when the departure date is a current date or a future date, the target departure time is the predicted departure time with the shortest travel time, and the second arrival time is the predicted arrival time with the shortest travel time.

[0025] In the above scheme, when the start date and end date of the departure date range are the same departure date, the display module is further configured to:

[0026] Perform at least one of the following operations:

[0027] For each departure date within the given departure date range, a third arrival time is displayed that corresponds one-to-one with the multiple departure times included in the departure date range.

[0028] Wherein, when the departure time is of historical time type, the third arrival time is the actual arrival time from the departure time; when the departure time is of current time or future time type, the third arrival time is the predicted arrival time from the departure time.

[0029] For the departure dates within the given departure date range, display the target departure time among multiple departure times included in the departure date range, and the corresponding fourth arrival time;

[0030] The target departure time is the actual departure time or the predicted departure time with the shortest travel time, and the corresponding fourth arrival time is the actual predicted arrival time or the predicted arrival time with the shortest travel time.

[0031] In the above scheme, the predicted departure time and the predicted arrival time are obtained by sending a prediction request to the server. The map-based path status processing device further includes a prediction module, used for:

[0032] Based on the historical and real-time traffic data of the target route, a machine learning model is invoked for prediction processing to obtain the predicted departure time and the predicted arrival time output by the machine learning model.

[0033] The historical traffic data and the real-time traffic data both include the following types of data: road conditions and population mobility data.

[0034] In the above solution, the display module is further used for:

[0035] A progress bar corresponding to the departure date range is displayed on the map page;

[0036] In response to a movement operation of a sliding button in the progress bar, the road conditions corresponding to the departure date or departure time are displayed for the departure date or departure time corresponding to the sliding button.

[0037] In the above solution, the display module is further used for:

[0038] Based on the set start and end points, multiple candidate paths are displayed, and the selected candidate path is displayed as the target path;

[0039] Displays the real-time status of the target path.

[0040] In the above solution, the display module is further used for:

[0041] Display the historical status entry for the target path on the map page;

[0042] In response to a triggered operation for the historical status entry, a query condition setting area for the target path is displayed on the map page.

[0043] This application provides an electronic device, including:

[0044] Memory, used to store executable instructions;

[0045] The processor, when executing executable instructions stored in the memory, implements the map-based path state processing method provided in the embodiments of this application.

[0046] This application provides a computer-readable storage medium storing executable instructions for inducing a processor to execute and implement the map-based path status processing method provided in this application.

[0047] The embodiments of this application have the following beneficial effects:

[0048] After receiving the query condition setting operation in the query condition setting area of ​​the map page, the system displays the query conditions and the arrival time corresponding to at least one departure time in the departure date range. In this way, it can provide users with departure time and arrival time for reference, realizing intelligent travel route planning services. Attached Figure Description

[0049] Figure 1A This is a schematic diagram of the path query results display page provided by the relevant technology;

[0050] Figure 1B This is a schematic diagram of the path query result details page provided in an embodiment of this application;

[0051] Figure 2AThis is a schematic diagram of the architecture of the map query system 10 provided in this application embodiment;

[0052] Figure 2B This is a schematic diagram of the architecture of the map query system 10 provided in this application embodiment;

[0053] Figure 3 This is a schematic diagram of the structure of the terminal 400 provided in the embodiments of this application;

[0054] Figure 4 This is a schematic flowchart of the map-based path status processing method provided in the embodiments of this application;

[0055] Figure 5A This is a schematic diagram of the query condition display page provided in an embodiment of this application;

[0056] Figure 5B This is a schematic diagram illustrating the historical traffic viewing method provided in this application embodiment;

[0057] Figure 5C This is a schematic diagram of the date setting page provided in an embodiment of this application;

[0058] Figure 5D This is a schematic diagram of the query condition display page provided in an embodiment of this application;

[0059] Figure 5E This is a schematic diagram of the time setting page provided in an embodiment of this application;

[0060] Figure 5F This is a schematic diagram of the date setting page provided in an embodiment of this application;

[0061] Figure 5G This is a schematic diagram of the query condition display page provided in an embodiment of this application;

[0062] Figure 5H This is a schematic diagram of the date setting page provided in an embodiment of this application;

[0063] Figure 6A This is a schematic diagram illustrating the historical data analysis and recommendations provided in the embodiments of this application;

[0064] Figure 6B This is a schematic diagram illustrating the historical data analysis and recommendations provided in the embodiments of this application;

[0065] Figure 7 This is a schematic diagram of the interaction flow of the map-based path status processing method provided in the embodiments of this application;

[0066] Figure 8 This is an interactive schematic diagram of the map-based path status processing method provided in the embodiments of this application. Detailed Implementation

[0067] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. The described embodiments should not be regarded as limitations on this application. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0068] In the following description, references are made to “some embodiments,” which describe a subset of all possible embodiments. However, it is understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0069] If the application documents contain similar descriptions such as "first / second", the following explanation shall be added: In the following description, the terms "first / second / third" are used only to distinguish similar objects and do not represent a specific order of objects. It is understood that "first / second / third" may be interchanged in a specific order or sequence where permitted, so that the embodiments of this application described herein can be implemented in an order other than that illustrated or described herein.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0071] In the implementation of this application, the collection and processing of relevant data should strictly comply with the requirements of relevant laws and regulations, obtain the informed consent or separate consent of the personal information subject, and carry out subsequent data use and processing within the scope of laws and regulations and the authorization of the personal information subject.

[0072] 1) Departure Date: The date when the user travels by car or other means. It can be a past, present, or future date; it can be a specific date or date range, such as 2020.5.1-2020.5.7.

[0073] 2) Departure time: The time when the user travels by car or other means, which can be the past, present or future time; it can be a point in time or a time interval, such as 1:30 pm to 3:30 pm.

[0074] See Figure 1A , Figure 1A This is a schematic diagram of the path query results display page provided by the relevant technology. Figure 1AIt can only display the current real-time road congestion situation. For example, in a driving route from Shenzhen to Guangzhou, different colors are used to show the congestion status of different road sections. However, the technology does not present historical road congestion data from different times, nor does it show the arrival times corresponding to different departure times. Consequently, users cannot use historical road congestion data to plan future trips.

[0075] To address the technical problem that related technologies cannot provide users with historical road congestion information and arrival times corresponding to different departure times, embodiments of this application provide a map-based path status processing method, apparatus, electronic device, and computer-readable storage medium that can provide users with historical congestion information and arrival times corresponding to different departure times, helping users to plan their trips.

[0076] The map-based path status processing method provided in this application can be implemented by various electronic devices. For example, it can be implemented by a terminal alone, or by a server and a terminal working together. For example, the terminal executes the map-based path status processing method described below on its own, or the terminal and a server work together to execute the map-based path status processing method described below. For example, the terminal sends a query request to the server carrying the target path, departure date, and departure time. The server determines the arrival time corresponding to the departure date and departure time based on the query request and returns the arrival time to the terminal.

[0077] The electronic device for path state processing provided in this application embodiment can be various types of terminal devices or servers. The server can be an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, etc., but is not limited to these. The terminal and server can be directly or indirectly connected via wired or wireless communication, and this application embodiment does not impose any restrictions on this.

[0078] Taking servers as an example, such as server clusters deployed in the cloud, AI as a Service (AIaaS) is provided to users. The AIaaS platform breaks down several common AI services and provides them as independent or packaged services in the cloud. This service model is similar to an AI-themed marketplace, where all users can access and use one or more AI services provided by the AIaaS platform through application programming interfaces.

[0079] For example, one type of AI cloud service could be a path status processing service, whereby a server in the cloud encapsulates the path status processing program provided in this application embodiment. In response to a query condition setting operation, the terminal invokes the path status processing service in the cloud service, causing the server deployed in the cloud to call the encapsulated path status processing program. Based on the target path, endpoint date, and departure time, the program determines the corresponding arrival time and returns it to the terminal for display on the terminal's map page.

[0080] The following description uses the example of a server and terminal collaboratively implementing the map-based path status processing method provided in this application. See also... Figure 2A , Figure 2A This is a schematic diagram of the architecture of the map query system 10 provided in this application embodiment. The terminal 400 is connected to the server 200 through the network 300, which can be a wide area network, a local area network, or a combination of both.

[0081] In some embodiments, in response to a trigger operation on the query condition setting area entry in the map page, the terminal 400 displays a query condition setting area for the target path in the map page; and in response to a query condition setting operation received in the query condition setting area, sends a query request carrying the target path, departure date, and departure time to the server 200. The server 200 determines the arrival time corresponding to the target path, departure date, and departure time based on the query request, and returns the arrival time to the terminal 400 for display in the map page.

[0082] This application's embodiments can also be implemented using blockchain technology; see [link to relevant documentation]. Figure 2B , Figure 2BThis is a schematic diagram of the architecture of the map query system 10 provided in this application embodiment. After each navigation cycle, the terminal 400 sends the corresponding location data (time and location) to the blockchain network 500 (nodes 510-1, 510-2, and 510-3 of the blockchain network 500 are shown as an example), or sends the location data to the blockchain network 500 at fixed intervals. When the location data in the blockchain network 500 reaches a certain scale, the location data is sent to the server 200. The server 200 trains a machine learning model based on the received location data and deploys the trained machine learning model online. When the server 200 receives a query request from the terminal 400, it can determine the arrival time corresponding to the target path, departure date, and departure time in the query request based on the received location data and related traffic data, and return the arrival time to the terminal 400. When the server 200 receives a prediction request from the terminal 400, it can determine the predicted departure time and predicted arrival time through the machine learning model and return the predicted departure time and predicted arrival time to the terminal 400. In addition, the blockchain network 500 can periodically send the new location data it receives to the server 200. The server 200 can perform incremental learning based on the new location data, continue to train the existing machine learning model, and continuously update the machine learning model.

[0083] In some embodiments, taking the electronic device 400 provided in this application as an example, the terminal 400 implements the map-based path status processing method provided in this application by running a computer program. The computer program can be a native program or software module in the operating system; it can be a native application (APP), that is, a program that needs to be installed in the operating system to run, such as an electronic map client; it can also be a browser, which displays map pages in the form of web pages; or it can be a navigation applet that can be embedded in any APP. In short, the above-mentioned computer program can be any form of application, module or plugin.

[0084] The following description uses the terminal 400 described above as an example of the electronic device provided in this application embodiment. See also... Figure 3 , Figure 3 This is a schematic diagram of the structure of the terminal 400 provided in the embodiment of this application. Figure 3 The terminal 400 shown includes at least one processor 410, a memory 450, at least one network interface 420, and a user interface 430. The various components in the terminal 400 are coupled together via a bus system 440. It is understood that the bus system 440 is used to implement communication between these components. In addition to a data bus, the bus system 440 also includes a power bus, a control bus, and a status signal bus. However, for clarity, ... Figure 3 All buses are labeled as Bus System 440.

[0085] Processor 410 can be an integrated circuit chip with signal processing capabilities, such as a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or any conventional processor, etc.

[0086] User interface 430 includes one or more output devices 431 that enable the presentation of media content, including one or more speakers and / or one or more visual displays. User interface 430 also includes one or more input devices 432, including user interface components that facilitate user input, such as a keyboard, mouse, microphone, touch screen display, camera, other input buttons and controls.

[0087] The memory 450 may be removable, non-removable, or a combination thereof. Exemplary hardware devices include solid-state storage, hard disk drives, optical disk drives, etc. The memory 450 may optionally include one or more storage devices physically located away from the processor 410.

[0088] The memory 450 may include volatile memory or non-volatile memory, or both. The non-volatile memory may be read-only memory (ROM), and the volatile memory may be random access memory (RAM). The memory 450 described in this application embodiment is intended to include any suitable type of memory.

[0089] In some embodiments, memory 450 is capable of storing data to support various operations, examples of which include programs, modules, and data structures or subsets or supersets thereof, as illustrated below.

[0090] Operating system 451 includes system programs for handling various basic system services and performing hardware-related tasks, such as the framework layer, core library layer, driver layer, etc., for implementing various basic business functions and handling hardware-based tasks;

[0091] The network communication module 452 is used to reach other computing devices via one or more (wired or wireless) network interfaces 420, exemplary network interfaces 420 including: Bluetooth, WiFi, and Universal Serial Bus (USB), etc.

[0092] Presentation module 453 is configured to enable the presentation of information (e.g., a user interface for operating peripheral devices and displaying content and information) via one or more output devices 431 associated with user interface 430 (e.g., a display screen, a speaker, etc.).

[0093] The input processing module 454 is used to detect and translate one or more user inputs or interactions from one or more input devices 432.

[0094] In some embodiments, the map-based path status processing device provided in this application can be implemented in software. Figure 3 A map-based path status processing device 455 stored in memory 450 is shown. This device can be software in the form of programs and plug-ins, and includes the following software modules: a display module 4551 and a prediction module 4552. These modules are logically linked and can therefore be arbitrarily combined or further separated according to their implemented functions. The functions of each module will be described below.

[0095] The map-based path status processing method provided in this application embodiment will be described below with reference to the accompanying drawings. The execution subject of the map-based path status processing method described below can be a terminal, specifically, it can be implemented by the terminal running the various computer programs mentioned above. Of course, based on the understanding of the following text, it is not difficult to see that the map-based path status processing method provided in this application embodiment can also be implemented by the terminal and the server in collaboration.

[0096] See Figure 4 , Figure 4 This is a flowchart illustrating the map-based path status processing method provided in this application embodiment, which will be combined with... Figure 4 The steps shown are explained.

[0097] In step 101, the target path is displayed on the map page.

[0098] In some embodiments, on the map page of a map client or navigation app, after the user selects the starting point (e.g., Shenzhen), destination (e.g., Guangzhou), and mode of travel (e.g., driving), the following will be displayed: Figure 1A The page showing the path search results. Figure 1A In the map, there are three candidate routes from Shenzhen to Guangzhou. The highlighted route is the default target route, but users can also select other routes as their target route by clicking or other methods. The target route can be displayed on the map page by obscuring a portion of the map page (e.g., ...). Figure 1A The floating layer where the target path is located can also be displayed by occupying part of the display area on the map page.

[0099] The real-time status of the target route will be displayed on the route search results page. For example, red indicates congested sections of the target route, yellow indicates slow-moving sections, and green indicates unobstructed sections.

[0100] In step 102, the query criteria setting area for the target path is displayed on the map page.

[0101] In some embodiments, the query condition setting area may be displayed by default on the map page, or it may be displayed in response to a user's triggering action (such as clicking anywhere on the map page), or it may be displayed on the map page as a historical status entry for the target path in response to a user's triggering action; in response to a triggering action on the historical status entry, the query condition setting area for the target path may be displayed on the map page.

[0102] For example, in Figure 1A As shown in the path search results display page, after the user clicks or double-clicks anywhere on the page, multiple floating layers will appear in different locations, such as... Figure 1B As shown, Figure 1B This is a schematic diagram of the path query result details page provided in the embodiments of this application. Figure 1B In the example, the floating layer on the right side of the path query results details page is a toolbar, and the "History 110" in the toolbar is the historical status entry. Users can click on "History 110" to trigger the historical status entry and enter the query condition display page. On the query condition display page, the query condition setting area 210 is displayed as a floating layer at the bottom of the page, and includes a date selection area 220. The date selection area 220 defaults to displaying a date range from n days before the current date to the day before the current date, where n is a positive integer greater than or equal to 2. For example, the default displayed date range could be one week before the current date. If the current date is May 8, 2020, then the default start date displayed in the date selection area 220 would be May 1, 2020, and the default end date would be May 7, 2020. The default displayed date could also be one month, three months, six months before the current date, etc., and this embodiment does not impose any limitations on this.

[0103] In some possible examples, query condition setting area 210 may also include time selection area 230. Time selection area 230 displays the current time by default. For example, if the current time is 3:30 PM, then PM 3:30 will be displayed in the time selection area. Figure 5A As shown, Figure 5AThis is a schematic diagram of the query condition display page provided in the embodiments of this application. The query condition setting area 210 may also include a start and end point display area, a progress bar 240, and a sliding button on the progress bar 240.

[0104] The dates at both ends of progress bar 240 correspond to the same date selection area, for example, both being the time period from May 1, 2020 to May 7, 2020. Figure 5B As shown, Figure 5B This is a schematic diagram of viewing historical traffic conditions provided in an embodiment of this application. In the query condition display page that shows the default date and default departure time, when the user drags the slider button along the progress bar 240 to a certain date (such as May 2, 2020), the map above the query condition setting area 210 will display the traffic conditions for the corresponding date and default departure time (3:30 pm on May 2, 2020).

[0105] In step 103, in response to the query condition setting operation received in the query condition setting area, the query conditions set by the query condition setting operation for the target path are displayed.

[0106] In some embodiments, in response to a query condition setting operation received in the query condition setting area, displaying the query conditions set by the query condition setting operation for the target path can be implemented in the following manner: in response to a query condition setting operation received in the date selection area for setting at least one endpoint date, displaying the departure date range corresponding to the at least one endpoint date set.

[0107] In some possible examples, query criteria include a start date, an end date, and a departure date range (composed of endpoint dates). The endpoint dates include both the start date and the end date. The default start and end dates in date selection range 220 can be reset. The reset start and end dates can be in the form of "past date + past date," for example, if the current date is May 1, 2020, set the start date to April 25, 2020, and the end date to April 28, 2020. The start and end dates can also be in the form of "past date + current date," "current date + current date," "current date + future date," or "future date + future date." When the dates in "past date + past date", "current date + future date", or "future date + future date" are the same, only that same date will be displayed in date selection area 220. For example, if both the start date and end date are 2020.5.1, then only 2020.5.1 will be displayed in date selection area 220. When the user first selects a future date, the earliest selectable start date is the current date; when the user first selects a past date, the latest selectable end date is the current date.

[0108] In some possible examples, when a user clicks on the start date / end date in the date selection area 220, a time selection pop-up window 250 will appear on the query display page. For example... Figure 5C As shown, Figure 5C This is a schematic diagram of the date setting page provided in this application embodiment. The time selection pop-up window 250 is located below the query condition setting area 210, and may also occupy the entire page. The date highlighted (largest font, bold, etc.) on the left side of the time selection pop-up window 250 is the default end date (May 7, 2020), while the times highlighted in the middle and right side are the current time by default. Figure 5C In this example, the user did not change the default start date (May 1, 2020) but needs to change the default end date (May 7, 2020). After the user clicks to select the end date, the end date is selected (highlighted or bolded). At this point, the user can scroll up and down through the dates on the left and the departure times on the right of the time selection pop-up window 250 to reselect the end date and departure time. For example, if the user reselects the end date to May 6, 2020, and does not change the departure time, after clicking the "OK" button in the upper right corner of the time selection pop-up window 250, the time selection pop-up window 250 disappears, and the following will be displayed: Figure 5D The query criteria display page is shown below. Figure 5D The departure date range is from May 1, 2020 to May 6, 2010.

[0109] In some possible examples, after the user selects a start date / end date, the destination date / start date will be automatically determined based on the selected start date / end date and a preset-length date range, and the departure date range including the start date and end date will be displayed. For example, if the preset-length date range is 3 days and the current date is May 10, 2020, when the user selects a start date of May 1, 2020, the destination date will be automatically determined as May 3, 2020. When the user selects a destination date of May 15, 2020, the start date will be automatically determined as May 17, 2020. It should be noted that if the start date is before the current date, and the destination date determined based on the start date and the preset-length date range is after the current date, the destination date will be determined as the day before the current date; if the destination date is after the current date, and the start date determined based on the destination date and the preset-length date range is before the current date, the start date will be determined as the day after the current date. For example, if the preset date range is 3 days, the current date is May 10, 2020, the start date is May 8, 2020, then the end date is May 9, 2020; if the end date is May 12, 2020, then the start date is May 11, 2020.

[0110] In some embodiments, the query criteria include origin and destination, departure date range, and departure time. The departure time in the time selection area 230 is displayed as the current time by default and can be adjusted. When the user adjusts the departure time, the terminal responds to the query criteria setting operation received in the time selection area for setting the departure time and displays at least one selected time as the departure time.

[0111] In some possible examples, Figure 5D The query criteria display page, as shown, will display the following after the user clicks to select the time selection area 230: Figure 5E As shown, Figure 5E This is a schematic diagram of the time setting page provided in an embodiment of this application. Users can... Figure 5E In the time selection pop-up window 250, the departure time is selected on the right. At this time, the date on the left is fixed and cannot be selected; the date can only be selected through the date selection area 230. In some possible examples, the time selection pop-up window 250 may also be... Figure 5F As shown, only AM, PM, and selectable departure times are displayed; the date is not shown. This application embodiment does not limit the specific form of the time selection pop-up. After the user selects a departure time and clicks the "OK" button in the upper right corner of the time selection pop-up 250, the time selection pop-up 250 disappears, and the updated query conditions display page is shown.

[0112] In some possible examples, when the user selects the same start and end date, such as both being May 9, 2020, ... Figure 5G As shown, the time selection area on the query display page will show the default start time 260 and end time 270, which are the two endpoints of the time interval from the start time. The end time 270 is the current time, and the start time 260 is the time obtained by looking back at the current time for a preset duration, such as 3 hours, 6 hours, or 12 hours. For example, if the current time is 1:30 PM, the start time is 7:30 AM. At this time, the times at both ends of the progress bar 240 are consistent with the start time 260 and end time 270 in the time selection area. Users can drag the slider along the progress bar 240 to the corresponding time, such as 9:30 AM (ante meridiem). Figure 5G The map on the query page will display the road conditions for the corresponding date and time (9:30 AM on May 9, 2020).

[0113] Users can set the start / end time by clicking on the selected time area and choosing the start / end time. For example... Figure 5HAs shown, after the user clicks to select the starting time AM7:30, AM7:30 is highlighted, and the default time displayed in the time selection pop-up window 250 is 7:30 AM. At this time, the user can scroll up and down in the time selection pop-up window 250 to reselect the starting time.

[0114] In some possible examples, the start date, end date, and departure time can also be determined by filling in blanks, selecting from a calendar, or voice input. This application embodiment does not limit the method of determining the start date, end date, and departure time.

[0115] In step 104, the arrival time corresponding to at least one departure time in the departure date range is displayed on the map page.

[0116] In some embodiments, arrival time is the time taken to travel along the target path. When the start date and end date of the departure date interval are different departure dates, the arrival time corresponding to at least one departure time in the departure date interval is displayed on the map page, which can be achieved by performing at least one of the following steps 1041 and 1042.

[0117] In step 1041, for each of the multiple departure dates in the departure date range, the first arrival time corresponding to the departure time set by the query condition setting area is displayed.

[0118] In some possible examples, when the departure date type is "historical date," the first arrival time is the actual arrival time from the departure time. For example, the current date is May 10, 2020, the departure date is a historical date, the origin date is May 1, 2020, the destination date is May 7, 2020, and the departure time set in the query condition settings area is 3:30 PM. When the user clicks "Road Historical Data Analysis and Recommendation" at the bottom of the query condition display page, they will be switched to... Figure 6A The page shown, Figure 6A This is a schematic diagram illustrating the historical data analysis and recommendations provided in the embodiments of this application. Figure 6A There are two graphs. The first graph, 601, shows the travel time required to travel along the target route starting at 3:30 PM each day from May 1st to May 7th, 2020, i.e., the actual arrival time. The graph shows that the longest arrival time was 2 hours and 40 minutes when departing at 3:30 PM on May 1st, and the shortest was 1 hour and 45 minutes when departing at 3:30 PM on May 6th. Therefore, users can refer to the arrival times corresponding to departures at 3:30 PM on the dates shown in graph 601 to determine which day of the week departs at 3:30 PM for the shortest travel time.

[0119] In some possible examples, when the departure date is of type current date or future date, the first arrival time is the predicted arrival time from the departure time.

[0120] For example, if the current date is May 10, 2020, and the departure date is either the current date or a future date, with the start date being May 10, 2020, and the destination date being May 17, 2020, and the departure time set in the query criteria is 3:30 PM, then we need to predict the estimated arrival time for departures at 3:30 PM each day from May 10 to May 17, 2020. Figure 6A The first graph 601 shows the predicted arrival times. Therefore, this embodiment not only provides users with analysis of historical road data, i.e., the arrival times corresponding to the same departure time on historical dates, but also provides users with predicted arrival times corresponding to departure times on future dates.

[0121] In step 1042, for each departure date in the multiple departure dates within the departure date range, the target departure time and the corresponding second arrival time for each departure date are displayed.

[0122] In some possible examples, when the departure date type is historical date, the target departure time is the actual departure time with the shortest travel time, and the second arrival time is the actual arrival time with the shortest travel time. For example... Figure 6A As shown in the second curve 602, the departure date range set in the query condition setting area is from May 1, 2020 to May 7, 2020, with a departure time of 3:30 PM. In order to determine the target departure time with the shortest arrival time within the above departure date range, and to avoid the target departure time deviating significantly from the expected departure time (3:30 PM), i.e., to avoid invalid recommendations, a time period (1 PM to 6 PM) is selected as the center of the departure time set in the query condition setting area for filtering, thus obtaining the target departure time corresponding to each day within the departure date range.

[0123] from Figure 6A As shown in the second curve (602), the shortest second arrival time is when departing at 1:30 PM on May 1st, making 1:30 PM the target departure time for May 1st. The longest second arrival time is at 3:30 PM on May 2nd, indicating relatively heavy traffic on May 2nd. The shortest second arrival time is at 5:30 PM on May 7th, at 1 hour and 45 minutes, indicating relatively smooth traffic on May 7th. Therefore, the most suitable time to travel from May 1st to May 7th is 5:30 PM on May 7th, with the shortest second arrival time. Users can refer to this information. Figure 6A The two graphs in the middle reflect the traffic situation of this week, allowing you to plan your future driving trips.

[0124] In some possible examples, when the departure date type is current date or future date, the target departure time is the shortest predicted departure time, and the second arrival time is the shortest predicted arrival time. In this case, Figure 6A The target departure time shown below the second curve 602 and the arrival time shown on the left side of the curve are both prediction results.

[0125] In some possible examples, the user can drag... Figure 6A By sliding the slider to a specific position on the progress bar 240, a specific time period can be selected. At this time, the date range displayed on the horizontal axis of the two graphs below the progress bar 240 will change accordingly, effectively enlarging the graphs for easier viewing. For example, if the user drags the slider to 2020 / 05 / 02, they select the date range 2020 / 05 / 02-2020 / 05 / 07. The first graph will display the arrival time corresponding to departures at 3:30 PM each day from 2020 / 05 / 02 to 2020 / 05 / 07, while the second graph will display the arrival time corresponding to the target departure time for each day within the 2020 / 05 / 02-2020 / 05 / 07 period.

[0126] As can be seen, when the departure date type is historical date, users can clearly see the shortest and longest departure times for each departure date, thus determining the approximate range of arrival times for the target route and providing a reference for future travel planning. When the departure date type is current date or future date, users can choose the departure time of the departure date with the shortest predicted arrival time from all departure dates as their own departure time, thereby avoiding traffic congestion and reducing travel time.

[0127] In some embodiments, when the start date and end date of the departure date interval are the same departure date, the arrival time corresponding to at least one departure time in the departure date interval is displayed on the map page, which can be achieved by performing at least one of the following steps 1043 and 1044.

[0128] In step 1043, for each departure date in the departure date range, a third arrival time corresponding to each of the multiple departure times included in the departure date is displayed.

[0129] In some possible examples, when the departure time type is historical time, the third arrival time is the actual arrival time from the departure time. For example, the current date is May 10, 2020, the departure date is May 9, 2020, and the departure time is from 7:30 AM to 1:30 PM. When the user clicks "Road Historical Data Analysis and Recommendation" at the bottom of the query display page, they will be switched to... Figure 6B The page shown. By Figure 6B As shown in graph 603, the third arrival times correspond to various departure times between 7:30 AM and 1:30 PM on May 9, 2020. From... Figure 6B As can be seen from the curve 603, the traffic congestion situation between 7:30 am and 1:30 pm shows that the traffic is smoothest at 12:30 am. Therefore, the third arrival time corresponding to the departure time of 12:30 am is the shortest, which is 1 hour and 45 minutes.

[0130] In some possible examples, when the departure time is classified as current time or future time, the third arrival time is the predicted arrival time from the departure time. For example, if the current time is 7:30 AM and the departure time is between 7:30 AM and 1:30 PM on the same day as the current time, then... Figure 6B The arrival times in the curve 603 are all predicted results.

[0131] In step 1044, for the departure date within the departure date range, the target departure time and the corresponding fourth arrival time are displayed among the multiple departure times included in the departure date range.

[0132] In some possible examples, the target departure time is the actual departure time or the predicted departure time with the shortest travel time, and the corresponding fourth arrival time is the actual predicted arrival time or the predicted arrival time with the shortest travel time. For example... Figure 6B As shown, below the curve 603, the text "Recommended departure time is 12:30 am, with the shortest arrival time (1 hour and 45 minutes)" is displayed, thus clearly informing users of the target departure time with the shortest travel time between 7:30 am and 1:30 pm and the corresponding fourth arrival time.

[0133] As can be seen, when a user needs to view the traffic conditions of a past day, they can clearly understand the arrival times corresponding to departure times at different times on that day from graph 603, thus determining the periods of traffic congestion and smooth traffic. When a user needs to view the traffic conditions of a future day, they can also know the predicted departure time with the shortest travel time from the arrival times corresponding to departure times at different times on that day displayed in graph 603 or from the text displayed therein, thus rationally planning their future travel time.

[0134] In some embodiments, the actual departure time and actual arrival time in steps 1042 and 1044 are obtained by the terminal by sending a query request to the server. The query request carries the target path, departure date and departure time. Based on the query request, the server obtains the arrival time corresponding to at least one departure time in the departure date range from the database and returns the arrival time corresponding to the departure time to the terminal.

[0135] In some embodiments, the predicted departure time and predicted arrival time in steps 1042 and 1044 are obtained by the terminal by sending a prediction request to the server. The prediction request carries the target path, departure date, and expected departure time. For example, the target path in the prediction request could be "Guangzhou-Shenzhen", the departure date could be May 1, 2020 - May 7, 2010, and the expected departure time could be 3:30 PM; when the target path is "Guangzhou-Shenzhen", the departure date could also be May 7, 2010, and the expected departure time could be between 7:30 AM and 1:30 PM.

[0136] After receiving a prediction request, the server preprocesses the target path, departure date, and expected departure time carried in the request (one-hot encoding and normalization) to obtain the first input feature. This first input feature is then input into a first machine learning model for prediction, yielding the corresponding predicted departure time. Next, the first input feature and the preprocessed predicted departure time are used as the second input feature in a second machine learning model for prediction, resulting in the predicted arrival time. Finally, the predicted departure time and predicted arrival time are returned to the terminal.

[0137] In some possible examples, the first machine learning model is trained using historical and real-time traffic data of the target route as the training set, with the actual departure time as the label. The second machine learning model is trained using the same historical and real-time traffic data as the training set, with the actual arrival time as the label. Both historical and real-time traffic data include road conditions, population mobility data, weather, and holiday information. The population mobility data is obtained by the server through analysis of pedestrian heatmaps. Both the first and second machine learning models can be Long Short-Term Memory (LSTM) models, Gate Recurrent Unit (GRU) models, etc.

[0138] Because the machine learning model used to predict departure and arrival times is trained on historical and real-time traffic data and is continuously updated based on real-time traffic data, the prediction results are more accurate than those of traditional methods.

[0139] In some possible examples, after receiving a forecast request, the server determines the weather corresponding to the departure date in the forecast request, and identifies the traffic data with the highest match between the historical and real-time traffic data related to the target route and the departure date, expected departure time, and weather in the forecast request. Based on the traffic data with the highest match, the server determines the predicted departure date and arrival time. For example, if the current date is May 10, 2020, the departure date is May 17, 2020 (Sunday), and the expected departure time is 3 PM, and the server determines through the network that the predicted weather for May 17, 2020 is light rain, then it determines the traffic data with light rain and a departure time between 1 PM and 5 PM on Sunday from the historical traffic data (such as traffic data within 3 months) and real-time traffic data of the target route (such as Guangzhou-Shenzhen). If the requirements are met on May 3, 2020 and April 26, 2020, and the actual departure times for the shortest travel time between 1 PM and 5 PM on these two days are determined to be 2 PM and 4 PM respectively, with corresponding actual arrival times of 2 hours and 2 hours and 20 minutes, then the average of these two actual departure times is taken to obtain a predicted departure time of 3 PM, and the average of these two actual arrival times is taken to obtain a predicted arrival time of 2 hours and 10 minutes. The predicted departure time of 3 PM on May 17, 2020, and the predicted arrival time of 2 hours and 10 minutes are returned to the terminal.

[0140] As can be seen, in this embodiment of the application, after receiving the query condition setting operation in the query condition setting area of ​​the map page, the query condition and the arrival time corresponding to at least one departure time in the departure date range are displayed. In this way, departure time and arrival time can be provided for users to refer to, realizing intelligent travel route planning services.

[0141] See Figure 7 , Figure 7 This is a schematic diagram of the interaction flow of the map-based path status processing method provided in the embodiments of this application. The following will combine... Figure 7 Steps 201 to 207 describe the process by which the terminal and the server collaboratively implement the map-based path status processing method provided in the embodiments of this application.

[0142] Step 201: The terminal displays the target path on the map page.

[0143] Step 202: The terminal displays the query condition setting area for the target path on the map page.

[0144] Step 203: In response to the query condition setting operation received in the query condition setting area, the terminal displays the query conditions set for the target path by the query condition setting operation.

[0145] The query conditions include a departure date range and at least one departure time within the departure date range. The departure date in the departure date range is of type future date, or the departure date is of type current date, and at least one departure time within the current date is a future time.

[0146] Step 204: The terminal sends a prediction request to the server.

[0147] The prediction request includes the target path, departure date, and expected departure time.

[0148] Step 205: Based on the historical and real-time traffic data of the target route, the server calls a machine learning model to perform prediction processing to obtain the predicted departure time and predicted arrival time output by the machine learning model.

[0149] The historical and real-time traffic data include road conditions, population mobility data, weather, and holiday information.

[0150] Step 206: The server sends the predicted departure time and predicted arrival time to the terminal.

[0151] Step 207: On the map page, the terminal displays the arrival time corresponding to at least one departure time in the departure date range.

[0152] The arrival time is the time taken to travel along the target path.

[0153] It should be noted that the above steps have been described in detail above, and will not be repeated here.

[0154] As can be seen in this embodiment, when it is necessary to predict the departure time and arrival time of a future trip, the terminal can call a machine learning model through the server to perform prediction processing, thereby obtaining the predicted departure time and predicted arrival time, providing users with reliable predicted departure time and predicted arrival time for their future trips.

[0155] The following will describe an exemplary application of the embodiments of this application in a real-world application scenario.

[0156] In the terminal's map client, after the user selects the starting point (Shenzhen), destination (Guangzhou), and mode of transportation (driving), the following will be displayed: Figure 1A The path search results page shown below. After the user selects a target path, the real-time status of that path will be displayed on the path search results page, for example, using different colors to indicate congestion.

[0157] At this point, the user can bring up the display by clicking or double-clicking any position on the page. Figure 1B The path search results details page is shown. Figure 1BThe history section in the right-hand overlay is the entry point for historical status information. When the history status entry point receives a trigger operation (such as a click), it will be displayed. Figure 5A The search criteria display page is shown below. Users can modify the default departure date range by clicking the date selection area on the search criteria display page, and modify the default departure time by clicking the time selection area. Users can also slide the slider on the progress bar at the bottom of the search criteria display page to display the traffic congestion situation for the departure time of the date corresponding to the slider on the map above.

[0158] When a user clicks on a date selection area or a time selection area, such as clicking on the end date in the date selection area, the page will display the following: Figure 5C As shown, users can select the destination date and departure time in the time selection pop-up window. Similarly, users can click on the start date in the date selection area to set the start date. After selecting the departure date (May 1, 2020 - May 7, 2020) and departure time (3:30 PM), the departure date and departure time in the query display page will be updated accordingly.

[0159] Afterwards, the user clicks on "Road Historical Data Analysis and Recommendation" at the bottom of the search criteria display page, and the page will then display as follows: Figure 6A As shown, two graphs are displayed. The first graph shows the arrival time for departures at 3:30 PM daily from May 1st to May 7th, 2020. The second graph shows the shortest departure time and corresponding arrival time for departures between 1 PM and 6 PM daily from May 1st to May 7th, 2020. Figure 6A It can be seen that on May 1st, the best departure time is 1:30 PM, when the arrival time is shortest; on May 2nd, traffic congestion will be prevalent throughout the day, resulting in longer arrival times than average; the best departure times from May 3rd to May 6th are between 2:30 PM and 3:30 PM; and the best departure time on May 7th is 5:30 PM. Users can refer to... Figure 6A The two graphs shown provide an analysis of traffic conditions over the past week, allowing for reasonable planning for future driving trips.

[0160] When the user selects the same end date and start date, such as Figure 5G As shown, the user selects May 9, 2020 as the departure date and 7:30 AM to 1:30 PM as the departure time. The user can then drag the slider to track traffic congestion along the target route between 7:30 AM and 1:30 PM on May 9, 2020. When the user clicks "Road Historical Data Analysis and Recommendation," the page will display as shown... Figure 6B As shown. Figure 6BThe graph shows the arrival times for different departure times between 7:30 AM and 1:30 PM on May 9, 2020. It can be seen that 7:30 AM to 9:30 AM is the morning rush hour for the target route; around 10:30 AM, the morning rush hour gradually ends, and the roads become clear. Therefore, it can be determined that the morning rush hour on this road is concentrated between 7:30 AM and 9:30 AM, and traveling on this section during the morning rush hour will take approximately 2 hours. If you depart after 10:30 AM, avoiding the morning rush hour, the travel time will be reduced to less than 2 hours.

[0161] As can be seen, the embodiments of this application can display the congestion situation of the target route, the best departure time, and the corresponding arrival time over a period of time. Furthermore, when a user... Figure 5C When the selected departure date / time is a future date / time, it can return the predicted departure time and corresponding arrival time within the selected departure date range.

[0162] The prediction process will be explained below.

[0163] See Figure 8 , Figure 8 This is an interactive schematic diagram of the map-based path state processing method provided in an embodiment of this application. For example... Figure 8 As shown, traffic data needs to be collected before prediction. When a user uses a terminal for navigation, the terminal sends the acquired location data to the server's database through the server's access layer. The database correlates the location data of a large number of users on the same road segment at the same time based on the location data, thereby obtaining the road conditions of different road segments and at different times. Traffic data such as road conditions, population mobility data, weather, and holiday information are stored in the database. When the traffic data stored in the database reaches a certain scale, it is sent to the server's AI layer. The AI ​​layer trains a machine learning model based on the traffic data and updates the trained machine learning model synchronously based on the updated traffic data periodically sent by the database.

[0164] Subsequently, in response to the user's query settings, the terminal generates a prediction request and sends it to the server's AI layer. The AI ​​layer then uses a machine learning model to make a prediction, obtaining the predicted departure time and predicted arrival time. This predicted departure time and predicted arrival time are then returned to the terminal via the access layer. The user can then plan future trips based on the predicted departure time and predicted arrival time displayed on the terminal.

[0165] The following description continues to illustrate the exemplary structure of the map-based path status processing device 455 provided in this application embodiment as a software module. In some embodiments, such as... Figure 3As shown, the software module stored in the map-based path status processing device 455 in the memory 450 may include: a display module 4551, configured to display the target path on a map page; further configured to display a query condition setting area for the target path on the map page; further configured to display the query conditions set for the target path by the query condition setting operation in response to a query condition setting operation received in the query condition setting area; wherein the query conditions include at least a departure date range; and further configured to display the arrival time corresponding to at least one departure time in the departure date range on the map page; wherein the arrival time is the time spent traveling along the target path.

[0166] In some embodiments, the query condition setting area includes a date selection area; the display module 4551 is further configured to: in response to a query condition setting operation received in the date selection area for setting at least one endpoint date, display a departure date range corresponding to the set at least one endpoint date.

[0167] In some embodiments, the query condition setting area further includes a time selection area; the display module 4551 is further configured to: in response to a query condition setting operation for setting a departure time received in the time selection area, display at least one selected time as a departure time.

[0168] In some embodiments, when the start date and end date of the departure date interval are different departure dates, the display module 4551 is further configured to: perform at least one of the following operations: for each departure date among the plurality of departure dates in the departure date interval, display a first arrival time corresponding to the departure time set by the query condition setting area; wherein, when the departure date type is a historical date, the first arrival time is the actual arrival time from the departure time; when the departure date type is a current date or a future date, the first arrival time is the predicted arrival time from the departure time; for each departure date among the plurality of departure dates in the departure date interval, display a target departure time corresponding to each departure date and a corresponding second arrival time; wherein, when the departure date type is a historical date, the target departure time is the actual departure time with the shortest travel time, and the second arrival time is the actual arrival time with the shortest travel time; when the departure date type is a current date or a future date, the target departure time is the predicted departure time with the shortest travel time, and the second arrival time is the predicted arrival time with the shortest travel time.

[0169] In some embodiments, when the start date and end date of the departure date interval are the same departure date, the display module 4551 is further configured to: perform at least one of the following operations: for the departure date of the departure date interval, display a third arrival duration corresponding one-to-one with a plurality of departure times included in the departure date; wherein, when the departure time type is historical time, the third arrival duration is the actual arrival duration from the departure time; when the departure time type is current time or future time, the third arrival duration is the predicted arrival duration from the departure time; for the departure date of the departure date interval, display a target departure time among a plurality of departure times included in the departure date interval, and a corresponding fourth arrival duration; wherein, the target departure time is the actual departure time or predicted departure time with the shortest travel time, and the corresponding fourth arrival duration is the actual predicted duration or predicted arrival duration with the shortest travel time.

[0170] In some embodiments, the predicted departure time and predicted arrival time are obtained by sending a prediction request to the server. The map-based path status processing device further includes a prediction module 4552, which is used to: call a machine learning model to perform prediction processing based on historical traffic data and real-time traffic data of the target path, so as to obtain the predicted departure time and predicted arrival time output by the machine learning model; wherein, both historical traffic data and real-time traffic data include the following types of data: road conditions and population mobility data.

[0171] In some embodiments, the display module 4551 is further configured to: display a progress bar for the corresponding departure date range on the map page; and, in response to a movement operation of a sliding button in the progress bar, display the road conditions corresponding to the departure date or departure time for the departure date or departure time corresponding to the sliding button.

[0172] In some embodiments, the display module 4551 is further configured to: display multiple candidate paths according to the set start point and end point, display the selected candidate path as the target path, and display the real-time status of the target path.

[0173] In some embodiments, the display module 4551 is further configured to: display a historical status entry for the target path on the map page; and, in response to a trigger operation on the historical status entry, display a query condition setting area for the target path on the map page.

[0174] This application provides a computer-readable storage medium storing executable instructions. When these executable instructions are executed by a processor, they cause the processor to execute the map-based path state processing method provided in this application. For example, ... Figure 4 The map-based path state processing method is shown.

[0175] In some embodiments, the computer-readable storage medium may be a memory such as FRAM, ROM, PROM, EPROM, EEPROM, flash memory, magnetic surface memory, optical disk, or CD-ROM; or it may be a variety of devices including one or any combination of the above-mentioned memories.

[0176] In some embodiments, executable instructions may take the form of a program, software, software module, script, or code, written in any form of programming language (including compiled or interpreted languages, or declarative or procedural languages), and may be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment.

[0177] As an example, executable instructions may, but do not necessarily, correspond to files in a file system. They may be stored as part of a file that holds other programs or data, for example, in one or more scripts in a Hyper Text Markup Language (HTML) document, in a single file dedicated to the program in question, or in multiple collaborating files (e.g., a file that stores one or more modules, subroutines, or code sections).

[0178] As an example, executable instructions can be deployed to execute on a single computing device, or on multiple computing devices located in one location, or on multiple computing devices distributed across multiple locations and interconnected via a communication network.

[0179] In summary, after receiving the query condition setting operation in the query condition setting area of ​​the map page, this application embodiment displays the query conditions and the arrival time corresponding to at least one departure time in the departure date range. In this way, it can provide users with departure time and arrival time for reference, and realize intelligent travel route planning services.

[0180] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, and improvements made within the spirit and scope of this application are included within the scope of protection of this application.

Claims

1. A map-based path state processing method, characterized in that, include: Display the target path on the map page; The map page displays a query criteria setting area for the target path; In response to a query condition setting operation received in the query condition setting area, display the query conditions set by the query condition setting operation for the target path; The query conditions include at least a departure date range and a departure time; The map page displays the arrival time corresponding to at least one departure time within the departure date range; wherein the arrival time is the time taken to travel along the target path; When the start date and end date of the departure date range are different departure dates, perform the following operations: For each departure date in the range of departure dates, display the first arrival time corresponding to the departure time set in the query condition setting area; For each departure date in the multiple departure dates within the departure date range, the target departure time and the corresponding second arrival time are displayed; wherein, the target departure time is obtained by filtering a time period centered on the departure time set in the query condition setting area; and the second arrival time is the shortest actual arrival time or the predicted arrival time. When the start date and end date of the departure date range are the same departure date, perform the following operations: For each departure date within the given departure date range, a third arrival time is displayed that corresponds one-to-one with multiple departure times included in the departure date range; the third arrival time is the actual arrival time or the predicted arrival time from the departure time. For the departure dates within the given departure date range, display the target departure time among multiple departure times included in the departure date range, and the corresponding fourth arrival time; In response to the movement of the sliding button on the progress bar corresponding to the departure date range on the map page, the road conditions corresponding to the departure date or departure time are displayed for the departure date or departure time corresponding to the sliding button.

2. The method according to claim 1, characterized in that, The query condition setting area includes a date selection area; the step of responding to a query condition setting operation received in the query condition setting area by displaying the query conditions set by the query condition setting operation for the target path includes: In response to the query condition setting operation received in the date selection area for setting at least one endpoint date, the departure date range corresponding to the set at least one endpoint date is displayed.

3. The method according to claim 2, characterized in that, The query condition setting area also includes a time selection area; the step of displaying the query conditions set for the target path in response to a query condition setting operation received in the query condition setting area includes: In response to the query condition setting operation received in the time selection area for setting the departure time, at least one selected time is displayed as the departure time.

4. The method according to claim 1, characterized in that, The step of displaying the arrival time corresponding to at least one departure time within the departure date range on the map page includes: When the departure date is a historical date, the first arrival time is the actual arrival time from the departure time; when the departure date is a current date or a future date, the first arrival time is the predicted arrival time from the departure time. When the departure date is a historical date, the target departure time is the actual departure time with the shortest travel time, and the second arrival time is the actual arrival time with the shortest travel time; when the departure date is a current date or a future date, the target departure time is the predicted departure time with the shortest travel time, and the second arrival time is the predicted arrival time with the shortest travel time.

5. The method according to claim 1, characterized in that, The step of displaying the arrival time corresponding to at least one departure time within the departure date range on the map page includes: When the departure time is of historical time type, the third arrival time is the actual arrival time from the departure time; when the departure time is of current time or future time type, the third arrival time is the predicted arrival time from the departure time. The target departure time is the actual departure time or the predicted departure time with the shortest travel time, and the corresponding fourth arrival time is the actual predicted arrival time or the predicted arrival time with the shortest travel time.

6. The method according to claim 4 or 5, characterized in that, The predicted departure time and the predicted arrival time are obtained by sending a prediction request to the server, which instructs the server to perform the following processing: Based on the historical and real-time traffic data of the target route, a machine learning model is invoked for prediction processing to obtain the predicted departure time and the predicted arrival time output by the machine learning model. The historical traffic data and the real-time traffic data both include the following types of data: road conditions and population mobility data.

7. The method according to claim 1, characterized in that, Displaying the target path on the map page includes: Based on the set start and end points, multiple candidate paths are displayed, and the selected candidate path is displayed as the target path; Displays the real-time status of the target path.

8. The method according to claim 1, characterized in that, The area for setting query conditions for the target path displayed on the map page includes: Display the historical status entry for the target path on the map page; In response to a triggered operation for the historical status entry, a query condition setting area for the target path is displayed on the map page.

9. A map-based path status processing device, characterized in that, include: The display module is used to display the target path on the map page; It is also used to display a query condition setting area for the target path on the map page; It is also configured to, in response to a query condition setting operation received in the query condition setting area, display the query conditions set by the query condition setting operation for the target path; wherein the query conditions include at least a departure date range and a departure time; and to, in the map page, display the arrival time corresponding to at least one departure time in the departure date range; wherein the arrival time is the time taken to travel along the target path; The display module is further configured to perform the following operations when the start date and end date of the departure date range are different departure dates: For each departure date in the range of departure dates, display the first arrival time corresponding to the departure time set in the query condition setting area; For each departure date in the multiple departure dates within the departure date range, the target departure time and the corresponding second arrival time are displayed; wherein, the target departure time is obtained by filtering a time period centered on the departure time set in the query condition setting area; the second arrival time is the shortest actual arrival time or the predicted arrival time. The display module is further configured to perform the following operations when the start date and end date of the departure date range are the same departure date: For each departure date within the given departure date range, a third arrival time is displayed that corresponds one-to-one with multiple departure times included in the departure date range; the third arrival time is the actual arrival time or the predicted arrival time from the departure time. For the departure dates within the given departure date range, display the target departure time among multiple departure times included in the departure date range, and the corresponding fourth arrival time; The display module is also configured to respond to the movement operation of the sliding button of the progress bar corresponding to the departure date range on the map page, and display the road conditions corresponding to the departure date or departure time for the departure date or departure time corresponding to the sliding button.

10. The apparatus according to claim 9, characterized in that, The query criteria setting area includes a date selection area; The display module is also configured to, in response to the query condition setting operation received in the date selection area for setting at least one endpoint date, display the departure date range corresponding to the set at least one endpoint date.

11. The apparatus according to claim 10, characterized in that, The query condition setting area also includes a time selection area; The display module is also configured to, in response to the query condition setting operation for setting a departure time received in the time selection area, display at least one selected time as the departure time.

12. The apparatus according to claim 9, characterized in that, The display module is further configured to, when the departure date is a historical date, have the first arrival time be the actual arrival time from the departure time; and when the departure date is a current date or a future date, have the first arrival time be the predicted arrival time from the departure time. When the departure date is a historical date, the target departure time is the actual departure time with the shortest travel time, and the second arrival time is the actual arrival time with the shortest travel time; when the departure date is a current date or a future date, the target departure time is the predicted departure time with the shortest travel time, and the second arrival time is the predicted arrival time with the shortest travel time.

13. The apparatus according to claim 9, characterized in that, The display module is further configured to, when the departure time is of historical time type, the third arrival time is the actual arrival time from the departure time; when the departure time is of current time or future time type, the third arrival time is the predicted arrival time from the departure time. The target departure time is the actual departure time or the predicted departure time with the shortest travel time, and the corresponding fourth arrival time is the actual predicted arrival time or the predicted arrival time with the shortest travel time.

14. The apparatus according to claim 12 or 13, The predicted departure time and the predicted arrival time are obtained by sending a prediction request to the server. The device further includes: The prediction module is used to call a machine learning model to perform prediction processing based on the historical traffic data and real-time traffic data of the target route, so as to obtain the predicted departure time and the predicted arrival time output by the machine learning model. The historical traffic data and the real-time traffic data both include the following types of data: road conditions and population mobility data.

15. The apparatus according to claim 9, characterized in that, The display module is also used to display multiple candidate paths according to the set start and end points, and to display the selected candidate path as the target path; Displays the real-time status of the target path.

16. The apparatus according to claim 9, characterized in that, The display module is also used to display the historical status entry of the target path on the map page; In response to a triggered operation for the historical status entry, a query condition setting area for the target path is displayed on the map page.

17. An electronic device, characterized in that, The electronic device includes: Memory, used to store executable instructions; A processor, when executing executable instructions stored in the memory, implements the map-based path state processing method as described in any one of claims 1 to 8.

18. A computer-readable storage medium, characterized in that, The system stores executable instructions, which, when executed, are used to implement the map-based path state processing method as described in any one of claims 1 to 8.

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