Reachable area and destination intelligent calculation method and device, equipment and storage medium

Abstract

The invention discloses a reachable area and destination intelligent calculation method and device, equipment and a storage medium. The method comprises the following steps: acquiring real-time traffic data and a route network input by a user; according to the real-time traffic data and the route network, constructing a reachable area which takes a starting point position as a center and takes maximum acceptable travel time as a limit; determining a target interest point of the user in the reachable area, and visually displaying the target interest point; the method can be used for supporting efficient processing of various transportation modes, is suitable for various applications such as travel exploration, life service recommendation and holiday and festival travel planning, can integrate multi-source data, is excellent in visualization effect, high in expandability and expansibility, can be suitable for house property site selection and urban commuting analysis, and improves the speed and efficiency of intelligent calculation of reachable areas and destinations.

Description

Technical Field

[0001] The present invention relates to the technical field of map navigation and travel route planning, and in particular to a method, device, equipment and storage medium for intelligent calculation of reachable areas and destinations. Background Art

[0002] Currently, map navigation systems generally use a "point-to-point" route planning model. Users must explicitly enter their starting and ending points. The system then provides a recommended route and estimated arrival time based on the selected travel mode (e.g., driving, public transportation, etc.). These systems typically rely on sophisticated route calculation algorithms, such as the Dijkstra algorithm or the A* algorithm, to optimize routes by combining map topology with traffic data. However, existing technologies have the following limitations: 1. Lack of support for reverse exploration: Existing navigation systems (such as Amap and Baidu Maps) focus on route planning to known destinations and cannot meet users' needs for "exploring the reachable range" within time constraints. For example, if a user wants to know "what tourist attractions or cities are within a two-hour driving distance," existing technologies cannot directly provide a solution.

[0003] 2. Lack of time and travel mode integration capabilities: Existing systems struggle to combine user-acceptable time ranges with multiple travel modes to generate dynamic reachable areas. For example, Chinese patent CN109612447A proposes a path optimization method based on real-time traffic conditions, but it is limited to one-way planning and does not involve the integration and reverse deduction of multiple modes of transportation.

[0004] 3. Limitations of recommendation functions: Existing navigation products generally only provide route navigation and lack intelligent filtering and recommendations for points of interest (POIs) or administrative divisions within accessible areas. Users must search and verify the accessibility of their destinations, which affects the user experience.

[0005] The above defects are particularly obvious in actual scenarios, such as holiday travel planning, commuting range analysis, or life service recommendations. User needs have shifted from "where to go" to "where can I go", and existing technologies cannot effectively support this. Summary of the Invention

[0006] The main purpose of the present invention is to provide a method, device, equipment and storage medium for intelligent calculation of reachable areas and destinations, aiming to solve the technical problems in the existing technology that it does not support reverse exploration needs, lacks the ability to integrate time and travel modes, and has limitations in recommendation functions.

[0007] In a first aspect, the present invention provides a method for intelligently calculating a reachable area and a destination, the method comprising the following steps: Get real-time traffic data and route networks input by users; Constructing a reachable area centered on the starting location and limited by the maximum acceptable travel time based on the real-time traffic data and the route network; Determine the user's target point of interest within the reachable area, and visualize the target point of interest.

[0008] Optionally, obtaining the real-time traffic data and route network input by the user includes: Receive user input of the starting location, travel mode, and maximum acceptable travel time; According to the travel mode, the corresponding traffic data source is retrieved to obtain real-time traffic data and route network.

[0009] Optionally, the step of retrieving a corresponding traffic data source according to the travel mode to obtain real-time traffic data and route network includes: Performing a joint path simulation based on a preset path network model using the starting point location received from the user, the travel mode, and the maximum acceptable travel time to obtain a path simulation result; A corresponding traffic data source is retrieved according to the travel mode, and real-time traffic data and a route network are obtained according to the traffic data source and the path simulation result, wherein the travel mode is a combination of one or more traffic modes.

[0010] Optionally, constructing a reachable area centered on the starting point and limited by a maximum acceptable travel time based on the real-time traffic data and the route network includes: constructing a path calculation model based on the real-time traffic data and the route network; The path calculation model is combined with a preset map topology structure to construct a reachable area with the starting point as the center and the maximum acceptable travel time as the limit.

[0011] Optionally, the constructing a reachable area centered on the starting point and limited by the maximum acceptable travel time by combining the path calculation model with a preset map topology structure includes: The path calculation model is combined with a preset map topology structure to construct all areas within an isochronous reachable time range with the starting position as the center and the maximum acceptable travel time as the limit, and all the areas are regarded as reachable areas.

[0012] Optionally, the path calculation model is combined with a preset map topology structure to construct all areas within an isochronous reachable time range centered on the starting point and limited by the maximum acceptable travel time, and all areas are used as reachable areas, including: The path calculation model is combined with a preset map topology structure to construct isochronous boundary points in all directions with the starting point as the center; Updating the path according to real-time traffic conditions, and dynamically adjusting the time boundary according to the updated path and the isochronous boundary points; All areas within a reachable time range limited by the maximum acceptable travel time are determined according to the dynamically adjusted time boundary, and all the areas are taken as reachable areas.

[0013] Optionally, determining the target point of interest of the user within the reachable area and visually displaying the target point of interest includes: Retrieving, within the reachable area, geographical areas and points of interest that meet the preset conditions set by the user; Classify and filter the points of interest within the geographical area according to geographical dimensions and functional dimensions to obtain a target area and target points of interest; The target area and the target interest are visually displayed.

[0014] Optionally, classifying and screening the points of interest in the geographical area according to the geographical dimension and the functional dimension to obtain the target area and target points of interest includes: Performing spatial intersection of the reachable area and a preset geographic information database according to geographic dimensions, identifying and extracting geographic administrative units within the reachable area, and using the geographic administrative units as target areas; The points of interest within the geographical area are classified and screened according to the geographical dimension and the functional dimension to obtain functional points of interest, and each functional point of interest is used as a target point of interest.

[0015] Optionally, the classifying and screening the points of interest in the geographical area according to the geographical dimension and the functional dimension to obtain functional points of interest, and using the functional points of interest as target points of interest, includes: The points of interest in the geographical area are classified into multiple levels according to the geographical dimension and the functional dimension to obtain functional points of interest corresponding to different administrative divisions and different service types, and each functional point of interest is used as a target point of interest.

[0016] Optionally, the visual display of the target area and the target interest includes: The target area and the target point of interest are marked on the map interface of the user's terminal according to a preset display rule, and the target area and the target point of interest are visually displayed according to a preset display rule.

[0017] In a second aspect, to achieve the above-mentioned objectives, the present invention further provides a device for intelligently calculating reachable areas and destinations, the device comprising: Data acquisition module, used to obtain real-time traffic data and route network input by users; an area construction module, configured to construct a reachable area centered on a starting point and limited by a maximum acceptable travel time based on the real-time traffic data and the route network; A display module is used to determine the user's target interest point within the reachable area and visually display the target interest point.

[0018] In the third aspect, in order to achieve the above-mentioned purpose, the present invention also proposes a reachable area and destination intelligent computing device, which includes: a memory, a processor, and a reachable area and destination intelligent computing program stored on the memory and runnable on the processor, and the reachable area and destination intelligent computing program is configured to implement the steps of the reachable area and destination intelligent computing method described above.

[0019] In a fourth aspect, in order to achieve the above-mentioned purpose, the present invention also proposes a storage medium, on which a reachable area and destination intelligent calculation program is stored. When the reachable area and destination intelligent calculation program is executed by a processor, the steps of the reachable area and destination intelligent calculation method as described above are implemented.

[0020] The method for intelligent calculation of reachable areas and destinations proposed in the present invention obtains real-time traffic data and route networks input by users; constructs a reachable area centered on a starting point and limited by a maximum acceptable travel time based on the real-time traffic data and the route network; determines the user's target points of interest within the reachable area and visually displays the target points of interest; can be used to support efficient processing of multiple modes of transportation, and is suitable for various applications such as travel exploration, life service recommendations, and holiday itinerary planning. It can integrate multi-source data, has excellent visualization effects, strong scalability, and strong extensibility, and is applicable to real estate site selection and urban commuting analysis, thereby improving the speed and efficiency of intelligent calculation of reachable areas and destinations. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 A schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention; Figure 2 This is a flowchart of a first embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention; Figure 3 This is a flow chart of a second embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention; Figure 4A flowchart of a third embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention; Figure 5 A flowchart of a fourth embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention; Figure 6 Schematic diagram of the destination classification structure in the method for intelligently calculating reachable areas and destinations of the present invention; Figure 7 A schematic diagram of a reachable area generation process in the reachable area and destination intelligent calculation method of the present invention; Figure 8 A schematic diagram of a user interaction page in the method for intelligently calculating reachable areas and destinations according to the present invention; Figure 9 This is a functional module diagram of the first embodiment of the reachable area and destination intelligent calculation device of the present invention.

[0022] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0023] It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0024] The solution of the embodiment of the present invention is mainly: by obtaining real-time traffic data and route network input by the user; constructing a reachable area with the starting position as the center and the maximum acceptable travel time as the limit based on the real-time traffic data and the route network; determining the user's target interest points within the reachable area, and visually displaying the target interest points; it can be used to support efficient processing of multiple transportation modes, and is suitable for various applications such as travel exploration, life service recommendations, and holiday itinerary planning. It can integrate multi-source data, has excellent visualization effects, strong scalability, and strong extensibility. It can be applied to real estate site selection and urban commuting analysis, improves the speed and efficiency of intelligent calculation of reachable areas and destinations, and solves the technical problems in the existing technology that it does not support reverse exploration needs, lacks the ability to integrate time and travel modes, and has limitations in recommendation functions.

[0025] Reference Figure 1 , Figure 1 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiment of the present invention.

[0026] like Figure 1As shown, the device may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement communication between these components. The user interface 1003 may include a display and an input unit such as a keyboard. Optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM memory or a non-volatile memory, such as a disk storage. The memory 1005 may also be a storage device independent of the processor 1001.

[0027] Those skilled in the art will understand that Figure 1 The device structure shown in the figure does not constitute a limitation of the device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0028] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating device, a network communication module, a user interface module, and a reachable area and destination intelligent calculation program.

[0029] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001 and performs the following operations: Get real-time traffic data and route networks input by users; Constructing a reachable area centered on the starting location and limited by the maximum acceptable travel time based on the real-time traffic data and the route network; Determine the user's target point of interest within the reachable area, and visualize the target point of interest.

[0030] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: Receive user input of the starting location, travel mode, and maximum acceptable travel time; According to the travel mode, the corresponding traffic data source is retrieved to obtain real-time traffic data and route network.

[0031] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: Performing a joint path simulation based on a preset path network model using the starting point location received from the user, the travel mode, and the maximum acceptable travel time to obtain a path simulation result; A corresponding traffic data source is retrieved according to the travel mode, and real-time traffic data and a route network are obtained according to the traffic data source and the path simulation result, wherein the travel mode is a combination of one or more traffic modes.

[0032] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: constructing a path calculation model based on the real-time traffic data and the route network; The path calculation model is combined with a preset map topology structure to construct a reachable area with the starting point as the center and the maximum acceptable travel time as the limit.

[0033] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: The path calculation model is combined with a preset map topology structure to construct all areas within an isochronous reachable time range with the starting position as the center and the maximum acceptable travel time as the limit, and all the areas are regarded as reachable areas.

[0034] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: The path calculation model is combined with a preset map topology structure to construct isochronous boundary points in all directions with the starting point as the center; Updating the path according to real-time traffic conditions, and dynamically adjusting the time boundary according to the updated path and the isochronous boundary points; All areas within a reachable time range limited by the maximum acceptable travel time are determined according to the dynamically adjusted time boundary, and all the areas are taken as reachable areas.

[0035] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: Retrieving, within the reachable area, geographical areas and points of interest that meet the preset conditions set by the user; Classify and filter the points of interest within the geographical area according to geographical dimensions and functional dimensions to obtain a target area and target points of interest; The target area and the target interest are visually displayed.

[0036] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: Performing spatial intersection of the reachable area and a preset geographic information database according to geographic dimensions, identifying and extracting geographic administrative units within the reachable area, and using the geographic administrative units as target areas; The points of interest within the geographical area are classified and screened according to the geographical dimension and the functional dimension to obtain functional points of interest, and each functional point of interest is used as a target point of interest.

[0037] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: The points of interest in the geographical area are classified into multiple levels according to the geographical dimension and the functional dimension to obtain functional points of interest corresponding to different administrative divisions and different service types, and each functional point of interest is used as a target point of interest.

[0038] The device of the present invention calls the reachable area and destination intelligent calculation program stored in the memory 1005 through the processor 1001, and further performs the following operations: The target area and the target point of interest are marked on the map interface of the user's terminal according to a preset display rule, and the target area and the target point of interest are visually displayed according to a preset display rule.

[0039] This embodiment uses the above solution to obtain real-time traffic data and route network input by the user; constructs a reachable area centered on the starting position and limited by the maximum acceptable travel time based on the real-time traffic data and the route network; determines the user's target point of interest within the reachable area and visualizes the target point of interest; can be used to support efficient processing of multiple modes of transportation, and is suitable for various applications such as travel exploration, life service recommendations, and holiday itinerary planning. It can integrate multi-source data, has excellent visualization effects, strong scalability, and strong extensibility, and is suitable for real estate site selection and urban commuting analysis, thereby improving the speed and efficiency of intelligent calculation of reachable areas and destinations.

[0040] Based on the above hardware structure, an embodiment of the method for intelligent calculation of reachable areas and destinations of the present invention is proposed.

[0041] Reference Figure 2 , Figure 2 2 is a flow chart of the first embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention.

[0042] In a first embodiment, the method for intelligently calculating reachable areas and destinations includes the following steps: Step S10: Acquire real-time traffic data and route network input by the user.

[0043] It should be noted that the real-time traffic data is real-time traffic data generated corresponding to various parameters input by the user, and the route network is a network constructed by various routes generated corresponding to various parameters input by the user.

[0044] Step S20: constructing a reachable area centered on the starting point and limited by the maximum acceptable travel time based on the real-time traffic data and the route network.

[0045] It should be understood that, based on the real-time traffic data and the route network, an area centered on the starting point and limited by the maximum acceptable travel time can be constructed as a reachable area.

[0046] Step S30: determining the user's target point of interest within the reachable area, and visually displaying the target point of interest.

[0047] It is understandable that the user's target point of interest may be determined within the reachable area, and then the target point of interest may be visually displayed according to pre-set display rules.

[0048] This embodiment uses the above solution to obtain real-time traffic data and route network input by the user; constructs a reachable area centered on the starting position and limited by the maximum acceptable travel time based on the real-time traffic data and the route network; determines the user's target point of interest within the reachable area and visualizes the target point of interest; can be used to support efficient processing of multiple modes of transportation, and is suitable for various applications such as travel exploration, life service recommendations, and holiday itinerary planning. It can integrate multi-source data, has excellent visualization effects, strong scalability, and strong extensibility, and is suitable for real estate site selection and urban commuting analysis, thereby improving the speed and efficiency of intelligent calculation of reachable areas and destinations.

[0049] Further, Figure 3 This is a flow chart of the second embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention. Figure 3 As shown, a second embodiment of the method for intelligently calculating reachable areas and destinations of the present invention is proposed based on the first embodiment. In this embodiment, step S10 specifically includes the following steps: Step S11: receiving the starting location, travel mode and maximum acceptable travel time input by the user.

[0050] It should be noted that the starting location, travel mode and maximum acceptable travel time are generally collected from multi-dimensional inputs, that is, the system receives the starting location, travel mode (for example: self-driving, high-speed rail, walking, etc.) and maximum acceptable travel time (for example: 2 hours) input by the user, and the input data is converted into calculation parameters through structured processing.

[0051] In a specific implementation, the travel mode includes one or more combinations of driving, bus, subway, train, high-speed rail, airplane, ferry, cycling and walking.

[0052] Step S12: retrieve the corresponding traffic data source according to the travel mode to obtain real-time traffic data and route network.

[0053] It is understandable that, according to the travel mode, the corresponding traffic data source can be retrieved to obtain real-time traffic data and route network.

[0054] Furthermore, the step S12 specifically includes the following steps: Performing a joint path simulation based on a preset path network model using the starting point location received from the user, the travel mode, and the maximum acceptable travel time to obtain a path simulation result; A corresponding traffic data source is retrieved according to the travel mode, and real-time traffic data and a route network are obtained according to the traffic data source and the path simulation result, wherein the travel mode is a combination of one or more traffic modes.

[0055] It should be understood that the travel mode includes a combination of two or more transportation modes, and a joint path simulation and area construction are performed through the corresponding path network model, that is, a joint path simulation is performed according to the preset path network model using the starting position received from the user input, the travel mode and the maximum acceptable travel time to obtain a path simulation result, and the corresponding traffic data source is retrieved according to the travel mode, and then real-time traffic data and route network are obtained based on the traffic data source and the path simulation result.

[0056] Through the above scheme, this embodiment receives the starting location, travel mode and maximum acceptable travel time input by the user; retrieves the corresponding traffic data source according to the travel mode, obtains real-time traffic data and route network, which can be used to support efficient processing of multiple traffic modes and improve the speed and efficiency of intelligent calculation of accessible areas and destinations.

[0057] Furthermore, Figure 4 This is a flow chart of the third embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention. Figure 4As shown, a third embodiment of the method for intelligently calculating reachable areas and destinations of the present invention is proposed based on the first embodiment. In this embodiment, step S20 specifically includes the following steps: Step S21: constructing a path calculation model based on the real-time traffic data and the route network.

[0058] It should be noted that a path calculation model can be constructed based on the real-time traffic data and the route network.

[0059] Step S22: constructing a reachable area centered on the starting point and limited by the maximum acceptable travel time by combining the path calculation model with a preset map topology structure.

[0060] It is understandable that the path calculation model can be combined with a preset map topology structure to construct a reachable area centered on the starting point and limited by the maximum acceptable travel time.

[0061] In the specific implementation, path calculation is based on Dijkstra, A* or improved time reverse path algorithm, and the path cost is dynamically adjusted in combination with factors such as real-time traffic conditions, road speed limits, traffic light delays, etc.; the reachable area is constructed using the multi-directional path extension method to form "isochrones" or closed polygons to represent all areas within the reachable time range.

[0062] Furthermore, the step S22 specifically includes the following steps: The path calculation model is combined with a preset map topology structure to construct all areas within an isochronous reachable time range with the starting position as the center and the maximum acceptable travel time as the limit, and all the areas are regarded as reachable areas.

[0063] In the specific implementation, based on the travel mode selected by the user, the corresponding traffic data source (for example: Amap API, railway timetable) is called to obtain real-time traffic information (including road conditions, speed limits, congestion conditions, etc.) and route networks; based on this, a path analysis model is constructed, combining the map topology structure with dynamic traffic data to provide a basis for subsequent calculations.

[0064] Furthermore, the step of constructing all areas within the reachable time range of equal time lines with the starting position as the center and the maximum acceptable travel time as the limit by combining the path calculation model with a preset map topology structure, and taking all the areas as reachable areas, specifically includes the following steps: The path calculation model is combined with a preset map topology structure to construct isochronous boundary points in all directions with the starting point as the center; Updating the path according to real-time traffic conditions, and dynamically adjusting the time boundary according to the updated path and the isochronous boundary points; All areas within a reachable time range limited by the maximum acceptable travel time are determined according to the dynamically adjusted time boundary, and all the areas are taken as reachable areas.

[0065] In the specific implementation, based on the dynamic time-constrained path algorithm, combined with real-time traffic data and scheduling information, the isochronous boundaries of the reachable area are generated, the isochronous boundary points from the starting point to each direction are calculated, and the time boundaries are dynamically adjusted based on the real-time road conditions. The path calculation and reachable area generation adopt a dynamic multi-level weight scheduling algorithm to optimize path selection, support user-defined time ranges, and generate different reachable areas based on the range. Virtual path rays can be emitted in multiple directions with the starting point as the center, and the time boundary points in each direction are calculated in combination with real-time traffic data; the ray simulation process takes into account factors such as road traffic efficiency, speed limit, and traffic light delay, and finally connects each boundary point to form an isochronous polygon or "isochrone line", which represents the reachable area within the specified time range; generally, dynamic adjustments can be made, the path calculation results are updated according to real-time road conditions, and the boundaries of the reachable area are dynamically adjusted to ensure that the results accurately reflect the current traffic conditions.

[0066] This embodiment uses the above-mentioned scheme to construct a path calculation model using the real-time traffic data and the route network; and uses the path calculation model in combination with a pre-set map topology structure to construct a reachable area centered on the starting location and limited by the maximum acceptable travel time. This can be used to support efficient processing of multiple modes of transportation, thereby improving the speed and efficiency of intelligent calculation of reachable areas and destinations.

[0067] Further, Figure 5 This is a flow chart of the fourth embodiment of the method for intelligently calculating reachable areas and destinations according to the present invention. Figure 5 As shown, a fourth embodiment of the method for intelligently calculating reachable areas and destinations of the present invention is proposed based on the first embodiment. In this embodiment, step S30 specifically includes the following steps: Step S31: Retrieve geographical areas and points of interest that meet the preset conditions set by the user within the reachable area.

[0068] It should be noted that, within the reachable area, geographical areas and points of interest that meet the preset conditions set by the user can be retrieved.

[0069] Step S32: Classify and filter the points of interest within the geographical area according to geographical dimensions and functional dimensions to obtain a target area and target points of interest.

[0070] It is understandable that the points of interest within the geographical area are classified and screened according to the geographical dimension and the functional dimension, so as to obtain the target area and target points of interest.

[0071] In the specific implementation, within the generated reachable area, eligible geographical areas (such as provinces, cities, districts) and points of interest (POIs, such as attractions, hotels, shopping malls, etc.) are retrieved; destinations are classified by geographical dimensions (such as administrative divisions) and functional dimensions (such as service types), and user-defined filtering conditions (such as distance priority and category priority) are supported.

[0072] Furthermore, the step S32 specifically includes the following steps: Performing spatial intersection of the reachable area and a preset geographic information database according to geographic dimensions, identifying and extracting geographic administrative units within the reachable area, and using the geographic administrative units as target areas; The points of interest within the geographical area are classified and screened according to the geographical dimension and the functional dimension to obtain functional points of interest, and each functional point of interest is used as a target point of interest.

[0073] It should be noted that, by performing spatial intersection between the reachable area and the geographic information database, the geographic administrative units within the reachable area are identified and extracted, and then the geographic administrative units can be used as target areas; after classifying and screening the points of interest within the geographic area according to the geographic dimension and the functional dimension, points of interest corresponding to different functionalities, i.e., various functional points of interest, can be obtained, and each functional point of interest can be used as a target point of interest.

[0074] Furthermore, the step of classifying and screening the points of interest in the geographical area according to the geographical dimension and the functional dimension to obtain functional points of interest, and using each functional point of interest as a target point of interest, specifically includes the following steps: The points of interest in the geographical area are classified into multiple levels according to the geographical dimension and the functional dimension to obtain functional points of interest corresponding to different administrative divisions and different service types, and each functional point of interest is used as a target point of interest.

[0075] It should be understood that the screening of points of interest is carried out by multi-level classification according to geographical dimensions (administrative divisions) and functional dimensions (service types), which can support topic recommendations, that is, the points of interest in the geographical area are classified into multi-level categories according to the geographical dimensions and functional dimensions, so as to obtain functional points of interest corresponding to different administrative divisions and different service types, and use each functional point of interest as a target point of interest.

[0076] In the specific implementation, see Figure 6 , Figure 6This is a schematic diagram of the destination classification structure in the method for intelligently calculating reachable areas and destinations according to the present invention. Figure 6 As shown, reachable destinations can be classified according to geographical divisions and functional divisions of points of interest (POIs). Geographic divisions are divided into domestic and foreign. Domestic corresponds to provinces / cities / districts / streets, and foreign corresponds to states / regions. Functional divisions of POIs correspond to scenic spots, shopping malls, hospitals, leisure and entertainment venues, etc. This embodiment does not impose any restrictions on this.

[0077] Correspondingly, the reachable area generation process can be found in Figure 7 , Figure 7 This is a schematic diagram of the process of generating a reachable area in the intelligent calculation method of the reachable area and destination of the present invention, as shown in FIG. Figure 7 As shown, the user inputs the starting point + travel mode + travel time, loads the traffic network / timetable / real-time traffic conditions, builds a traffic map model (multimodal network), and generates a visual polygon area.

[0078] Step S33: Visually display the target area and the target interest.

[0079] It should be understood that after obtaining the target area and the target interest point, a matched visual display can be performed according to the display rules.

[0080] Furthermore, the step S33 specifically includes the following steps: The target area and the target point of interest are marked on the map interface of the user's terminal according to a preset display rule, and the target area and the target point of interest are visually displayed according to a preset display rule.

[0081] It should be noted that the target area and the target point of interest can be marked on the map interface of the user's terminal according to the preset display rules, and the target area and the target point of interest can be visually displayed according to the preset display rules.

[0082] Understandably, see Figure 8 , Figure 8 This is a schematic diagram of the user interaction page in the method for intelligently calculating reachable areas and destinations of the present invention, as shown in FIG. Figure 8As shown, after the travel plan is determined, the travel plan recommendation results can be generated and then displayed on the visual interface. In addition to visual output, list output can also be performed. The visual output is to highlight the reachable area on the map interface and mark the POI location in the area; the list output is to display the reachable destinations in the form of a list, support sorting by distance, time, category, etc., and provide detailed information (for example: location, evaluation, route planning) for users to choose; the destinations include corresponding types: one type is geographical administrative division type (such as province, city, district, county, etc.); the other type is functional point of interest type (such as scenic spots, hotels, shopping malls, hospitals, etc.).

[0083] In the specific implementation, in the self-driving travel scenario: If the user selects "Depart from the starting point, travel by car, and allow a maximum travel time of 2 hours," the system first receives these parameters through the input module and then calls the data interface module to obtain real-time traffic data (for example, traffic information provided by the AutoNavi Map application programming interface (API)). The calculation module simulates multi-directional paths based on map topology and a dynamic multi-level weighted scheduling algorithm, generating an isochronous polygonal reachable area centered at the starting point. Administrative divisions (for example, Langfang and Baoding) and points of interest (POIs) (for example, Fragrant Hills Park and the Badaling Great Wall) are identified within the area. The display module highlights the reachable area on the map, annotates the POI locations, and displays the destinations in a list format. Users can click to view specific locations, reviews, and route details.

[0084] In the high-speed rail + walking combination scenario: The user selects "departing from Shanghai Hongqiao Station, travel by high-speed rail + walking, maximum travel time 3 hours"; the system obtains high-speed rail timetable and walking path data, calculates cities reachable by high-speed rail (for example: Hangzhou, Suzhou), and generates walkable areas within each city; finally, it recommends POIs such as Hangzhou West Lake Scenic Area and Suzhou Humble Administrator's Garden, and displays them on maps and lists, so that users can further plan their specific itinerary.

[0085] In emergency rescue scenarios: Starting from the center of the disaster area (e.g., the epicenter of a certain county in Sichuan), users can enter a combination of travel modes (e.g., helicopter + off-road vehicle) within a maximum travel time of two hours. The system will recommend suitable locations for supply drop-offs or rescue stations (e.g., a township middle school) and provide detailed routes from the command center to those locations. Users can also combine their location information with travel modes (e.g., walking + driving) to reach suitable rescue locations.

[0086] This embodiment proposes a reverse path search mechanism, which differs from traditional "origin-to-destination" route planning. Its core concept is to reversely calculate all spatial ranges and destinations reachable within a given time range, given a known departure point, travel mode, and travel time range, to generate a reachable area. Based on a time-costed transportation map (including road networks and public transportation networks), this module constructs a time-weighted directed graph and performs time-budgeted reverse traversal on all adjacent nodes, thereby identifying a set of destinations reachable within T minutes using the selected travel mode. This reverse path search module efficiently handles multiple transportation modes, including driving, walking, public transportation, subways, and high-speed rail. It also dynamically adjusts path accessibility and reachable boundaries by integrating real-time traffic information (such as traffic congestion index, frequency, and delays returned by the map API). The generated reachable area is visualized on a map as isochrones or heat maps, serving as the spatial boundaries for subsequent destination screening and recommendation.

[0087] After obtaining the reachable area, this embodiment further constructs a multi-level, multi-dimensional POI screening and recommendation module. This module performs a spatial intersection operation on a pre-connected massive geographic location database (e.g., POI data from map service providers, open platform information, etc.) with the reachable area to extract all destination information within the reachable area. Destination information is organized and filtered according to a two-tier classification system: the first tier is administrative division-based destinations (e.g., provinces, cities, counties, and districts), which are used for coarse-grained aggregation and navigation; the second tier is functional destinations, including scenic spots, hotels, shopping malls, supermarkets, stations, hospitals, and schools, supporting type screening, tag matching, and theme recommendations. In addition, the system supports multi-condition combination filtering, including travel mode matching, travel time adaptability, user historical preferences, venue popularity, evaluation score, operating hours, etc. This mechanism ensures that users only receive POIs that are "reliably reachable at a specific time and travel mode" and allows sorting by recommendation, distance, or theme.

[0088] This embodiment uses the above scheme to retrieve geographical areas and points of interest that meet the preset conditions set by the user within the reachable area; classify and filter the points of interest within the geographical area according to geographical dimensions and functional dimensions to obtain target areas and target points of interest; and visualize the target area and the target interest. It can be used to support efficient processing of multiple modes of transportation and is suitable for various applications such as travel exploration, life service recommendations, and holiday itinerary planning. It can integrate multi-source data, has excellent visualization effects, strong scalability, and is suitable for real estate site selection and urban commuting analysis, thereby improving the speed and efficiency of intelligent calculation of reachable areas and destinations.

[0089] Accordingly, the present invention further provides a device for intelligently calculating reachable areas and destinations.

[0090] Reference Figure 9 , Figure 9 This is a functional module diagram of the first embodiment of the reachable area and destination intelligent calculation device of the present invention.

[0091] In a first embodiment of the reachable area and destination intelligent calculation device of the present invention, the reachable area and destination intelligent calculation device includes: The data acquisition module 10 is used to acquire real-time traffic data and route network input by the user.

[0092] The area construction module 20 is used to construct a reachable area centered on the starting point and limited by the maximum acceptable travel time based on the real-time traffic data and the route network.

[0093] The display module 30 is configured to determine the user's target point of interest within the reachable area and visually display the target point of interest.

[0094] The data acquisition module 10 is further configured to receive user input of a starting point location, travel mode, and maximum acceptable travel time; retrieve corresponding traffic data sources according to the travel mode, and obtain real-time traffic data and route networks.

[0095] The data acquisition module 10 is further configured to perform a joint path simulation based on a preset path network model using the starting location received from the user, the travel mode, and the maximum acceptable travel time to obtain a path simulation result; retrieve a corresponding traffic data source based on the travel mode, and obtain real-time traffic data and a route network based on the traffic data source and the path simulation result, wherein the travel mode is a combination of one or more traffic modes.

[0096] The area construction module 20 is further used to construct a path calculation model based on the real-time traffic data and the route network; and to construct a reachable area centered on the starting position and limited by the maximum acceptable travel time through the path calculation model combined with a pre-set map topology structure.

[0097] The area construction module 20 is further used to construct all areas within the reachable time range of the equal time line with the starting position as the center and the maximum acceptable travel time as the limit through the path calculation model combined with the preset map topology structure, and take all the areas as reachable areas.

[0098] The area construction module 20 is further configured to construct isochronous boundary points in all directions centered on the starting position through the path calculation model in combination with a pre-set map topology structure; update the path according to real-time traffic conditions, and dynamically adjust the time boundary according to the updated path and the isochronous boundary points; determine all areas within a reachable time range limited by the maximum acceptable travel time based on the dynamically adjusted time boundary, and use all areas as reachable areas.

[0099] The display module 30 is further used to retrieve geographical areas and points of interest that meet the preset conditions set by the user within the reachable area; classify and filter the points of interest within the geographical area according to geographical dimensions and functional dimensions to obtain target areas and target points of interest; and visually display the target area and the target interest.

[0100] The display module 30 is further used to spatially intersect the accessible area with a preset geographic information database according to geographic dimensions, identify and extract geographic administrative units within the accessible area, and use the geographic administrative units as target areas; classify and screen the points of interest within the geographic area according to the geographic dimensions and functional dimensions, obtain various functional points of interest, and use each functional point of interest as a target point of interest.

[0101] The display module 30 is further used to perform multi-level classification of the points of interest in the geographical area according to the geographical dimension and the functional dimension, obtain functional points of interest corresponding to different administrative divisions and different service types, and use each functional point of interest as a target point of interest.

[0102] The display module 30 is further configured to mark the target area and the target interest point on the map interface of the user's terminal according to preset display rules, and visually display the target area and the target interest point according to preset display rules.

[0103] Among them, the steps implemented by each functional module of the reachable area and destination intelligent calculation device can refer to the various embodiments of the reachable area and destination intelligent calculation method of the present invention, and will not be repeated here.

[0104] In addition, an embodiment of the present invention further provides a storage medium, on which a reachable area and destination intelligent calculation program is stored. When the reachable area and destination intelligent calculation program is executed by a processor, the following operations are implemented: Get real-time traffic data and route networks input by users; Constructing a reachable area centered on the starting location and limited by the maximum acceptable travel time based on the real-time traffic data and the route network; Determine the user's target point of interest within the reachable area, and visualize the target point of interest.

[0105] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: Receive user input of the starting location, travel mode, and maximum acceptable travel time; According to the travel mode, the corresponding traffic data source is retrieved to obtain real-time traffic data and route network.

[0106] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: Performing a joint path simulation based on a preset path network model using the starting point location received from the user, the travel mode, and the maximum acceptable travel time to obtain a path simulation result; A corresponding traffic data source is retrieved according to the travel mode, and real-time traffic data and a route network are obtained according to the traffic data source and the path simulation result, wherein the travel mode is a combination of one or more traffic modes.

[0107] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: constructing a path calculation model based on the real-time traffic data and the route network; The path calculation model is combined with a preset map topology structure to construct a reachable area with the starting point as the center and the maximum acceptable travel time as the limit.

[0108] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: The path calculation model is combined with a preset map topology structure to construct all areas within an isochronous reachable time range with the starting position as the center and the maximum acceptable travel time as the limit, and all the areas are regarded as reachable areas.

[0109] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: The path calculation model is combined with a preset map topology structure to construct isochronous boundary points in all directions with the starting point as the center; Updating the path according to real-time traffic conditions, and dynamically adjusting the time boundary according to the updated path and the isochronous boundary points; All areas within a reachable time range limited by the maximum acceptable travel time are determined according to the dynamically adjusted time boundary, and all the areas are taken as reachable areas.

[0110] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: Retrieving, within the reachable area, geographical areas and points of interest that meet the preset conditions set by the user; Classify and filter the points of interest within the geographical area according to geographical dimensions and functional dimensions to obtain a target area and target points of interest; The target area and the target interest are visually displayed.

[0111] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: Performing spatial intersection of the reachable area and a preset geographic information database according to geographic dimensions, identifying and extracting geographic administrative units within the reachable area, and using the geographic administrative units as target areas; The points of interest within the geographical area are classified and screened according to the geographical dimension and the functional dimension to obtain functional points of interest, and each functional point of interest is used as a target point of interest.

[0112] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: The points of interest in the geographical area are classified into multiple levels according to the geographical dimension and the functional dimension to obtain functional points of interest corresponding to different administrative divisions and different service types, and each functional point of interest is used as a target point of interest.

[0113] Furthermore, when the processor executes the reachable area and destination intelligent calculation program, the following operations are also implemented: The target area and the target point of interest are marked on the map interface of the user's terminal according to a preset display rule, and the target area and the target point of interest are visually displayed according to a preset display rule.

[0114] Those skilled in the art will understand that all or part of the steps in the above-mentioned implementation methods can be implemented by instructing related hardware through a program. The program is stored in a storage medium and includes a number of instructions for enabling a device (which may be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application; and the aforementioned storage medium is a computer-readable storage medium, including: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, and other media that can store program codes.

[0115] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0116] The serial numbers of the above embodiments of the present invention are for description only and do not represent the advantages or disadvantages of the embodiments.

[0117] The above are only preferred embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention description and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A method for intelligent calculation of reachable areas and destinations, characterized in that: The intelligent calculation method of the reachable area and destination: Get real-time traffic data and route networks input by users; Constructing a reachable area centered on the starting location and limited by the maximum acceptable travel time based on the real-time traffic data and the route network; Determine the user's target point of interest within the reachable area, and visualize the target point of interest.

2. The method for intelligently calculating reachable areas and destinations according to claim 1, wherein: The step of obtaining the real-time traffic data and route network input by the user includes: Receive user input of the starting location, travel mode, and maximum acceptable travel time; According to the travel mode, the corresponding traffic data source is retrieved to obtain real-time traffic data and route network.

3. The method for intelligently calculating reachable areas and destinations according to claim 2, wherein: The step of retrieving a corresponding traffic data source according to the travel mode to obtain real-time traffic data and route network includes: Performing a joint path simulation based on a preset path network model using the starting point location received from the user, the travel mode, and the maximum acceptable travel time to obtain a path simulation result; A corresponding traffic data source is retrieved according to the travel mode, and real-time traffic data and a route network are obtained according to the traffic data source and the path simulation result, wherein the travel mode is a combination of one or more traffic modes.

4. The method for intelligently calculating reachable areas and destinations according to claim 1, wherein: The constructing, based on the real-time traffic data and the route network, a reachable area centered on the starting location and limited by the maximum acceptable travel time includes: constructing a path calculation model based on the real-time traffic data and the route network; The path calculation model is combined with a preset map topology structure to construct a reachable area with the starting point as the center and the maximum acceptable travel time as the limit.

5. The method for intelligently calculating reachable areas and destinations according to claim 4, wherein: The step of constructing a reachable area centered on the starting point and limited by the maximum acceptable travel time by combining the path calculation model with a preset map topology structure includes: The path calculation model is combined with a preset map topology structure to construct all areas within an isochronous reachable time range with the starting position as the center and the maximum acceptable travel time as the limit, and all the areas are regarded as reachable areas.

6. The method for intelligently calculating reachable areas and destinations according to claim 5, wherein: The path calculation model is combined with a preset map topology structure to construct all areas within the reachable time range of the equal time line with the starting position as the center and the maximum acceptable travel time as the limit, and all areas are used as reachable areas, including: The path calculation model is combined with a preset map topology structure to construct isochronous boundary points in all directions with the starting point as the center; Updating the path according to real-time traffic conditions, and dynamically adjusting the time boundary according to the updated path and the isochronous boundary points; All areas within a reachable time range limited by the maximum acceptable travel time are determined according to the dynamically adjusted time boundary, and all the areas are taken as reachable areas.

7. The method for intelligently calculating reachable areas and destinations according to claim 1, wherein: Determining the user's target point of interest within the reachable area and visually displaying the target point of interest includes: Retrieving, within the reachable area, geographical areas and points of interest that meet the preset conditions set by the user; Classify and filter the points of interest within the geographical area according to geographical dimensions and functional dimensions to obtain a target area and target points of interest; The target area and the target interest are visually displayed.

8. The method for intelligently calculating reachable areas and destinations according to claim 7, wherein: The classifying and screening the points of interest in the geographical area according to the geographical dimension and the functional dimension to obtain the target area and target points of interest includes: Performing spatial intersection of the reachable area and a preset geographic information database according to geographic dimensions, identifying and extracting geographic administrative units within the reachable area, and using the geographic administrative units as target areas; The points of interest within the geographical area are classified and screened according to the geographical dimension and the functional dimension to obtain functional points of interest, and each functional point of interest is used as a target point of interest.

9. The method for intelligently calculating reachable areas and destinations according to claim 8, wherein: The classifying and screening the points of interest in the geographical area according to the geographical dimension and the functional dimension to obtain functional points of interest, and using the functional points of interest as target points of interest, includes: The points of interest in the geographical area are classified into multiple levels according to the geographical dimension and the functional dimension to obtain functional points of interest corresponding to different administrative divisions and different service types, and each functional point of interest is used as a target point of interest.

10. The method for intelligently calculating reachable areas and destinations according to claim 7, wherein: The visual display of the target area and the target interest includes: The target area and the target point of interest are marked on the map interface of the user's terminal according to a preset display rule, and the target area and the target point of interest are visually displayed according to a preset display rule.

11. A device for intelligently calculating reachable areas and destinations, characterized in that: The reachable area and destination intelligent calculation device includes: Data acquisition module, used to obtain real-time traffic data and route network input by users; an area construction module, configured to construct a reachable area centered on a starting point and limited by a maximum acceptable travel time based on the real-time traffic data and the route network; A display module is used to determine the user's target interest point within the reachable area and visually display the target interest point.

12. An intelligent computing device for reachable areas and destinations, characterized in that: The reachable area and destination intelligent calculation device includes: a memory, a processor, and a reachable area and destination intelligent calculation program stored in the memory and executable on the processor, wherein the reachable area and destination intelligent calculation program is configured to implement the steps of the reachable area and destination intelligent calculation method as described in any one of claims 1 to 10.

13. A storage medium, characterized in that: The storage medium stores a reachable area and destination intelligent calculation program, which, when executed by a processor, implements the steps of the reachable area and destination intelligent calculation method according to any one of claims 1 to 10.

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