Path planning method and device adaptive to physiological needs of children, medium and product

Abstract

The invention discloses a path planning method and device adaptive to physiological needs of children, a medium and a product. The method comprises the following steps: acquiring movement track data of the children in a target area; constructing a walking road network of the child according to the movement track data and a preset target location; identifying a child activity hot spot area based on the activity track data, and performing two-stage division on each path in the walking road network in combination with a preset child stride to generate a plurality of child-friendly road sections; calling a preset walking evaluation index system to score each child-friendly road section, and rejecting walking paths including road sections lower than a standard score to obtain a target path set; and adopting a weighted summation algorithm to predict the comprehensive score of each target path according to the road section score, and selecting the path with the highest score as the optimal child walking path. A safe, interesting and comfortable walking environment can be created for children, and the walking experience and safety of the children in the target area are improved.

Description

Technical Field

[0001] This invention relates to the field of path planning technology, and in particular to a path planning method, device, medium and product adapted to the physiological needs of children. Background Technology

[0002] With urban development, people's demands for the quality of community environments are increasing, especially the construction of child-friendly environments, which has received widespread attention. Currently, while there are some path selection methods based on the needs of different groups in community pedestrian path planning, most do not fully consider the behavioral characteristics, psychological needs, and developmental needs of children as a special group. Children prefer environments that are fun, safe, and social during walks. Traditional path planning methods struggle to meet these needs, resulting in less attractive pedestrian paths within the community and an inability to effectively guarantee children's experience and safety during walks. Summary of the Invention

[0003] This invention provides a path planning method, device, medium, and product adapted to children's physiological needs. By constructing a walking path evaluation index system that meets children's needs, and combining multi-source data and intelligent algorithms, walking paths are scientifically and rationally planned to create a safe, fun, and comfortable walking environment for children, thereby improving children's walking experience and safety within the area.

[0004] To achieve the above objectives, embodiments of the present invention provide a path planning method adapted to the physiological needs of children, including: Acquire activity trajectory data of children within the target area; construct a pedestrian route network for children based on the activity trajectory data and preset target locations; Based on activity trajectory data, hotspots for children's activities are identified. Combined with preset children's stride length, each path in the pedestrian road network is divided into two levels to generate several child-friendly road sections. The preset pedestrian evaluation index system is used to score each child-friendly section, and pedestrian paths containing sections with scores below the standard are removed to obtain the target path set; A weighted summation algorithm is used to predict the comprehensive score of each target path based on the road segment score, and the path with the highest score is selected as the optimal walking path for children.

[0005] As an improvement to the above solution, the method of identifying children's activity hotspots based on activity trajectory data, and dividing the paths in the pedestrian road network into two levels based on preset children's stride length, generates several child-friendly road segments, including: Each walking path in the pedestrian road network is divided according to the children's activity hotspots, resulting in several basic road segments for each walking path. Each basic path is divided according to the preset child stride length, resulting in several child-friendly sections for each walking path.

[0006] As an improvement to the above scheme, the pedestrian road network is divided into several basic road segments based on children's activity hotspots, resulting in several basic road segments for each pedestrian path, including: Based on the activity trajectory data, determine the children's activity hotspot areas of the pedestrian road network; Based on the children's activity hotspots, each walking path in the pedestrian road network is divided to obtain several basic road segments for each walking path.

[0007] As an improvement to the above scheme, the step of calling a preset pedestrian evaluation index system to score each child-friendly road section includes: Obtain the score of each evaluation indicator in the preset pedestrian evaluation index system for each child-friendly road section; normalize the score of each evaluation indicator. The child-friendly road segment score is obtained by weighting the processed scores and the corresponding evaluation indicators.

[0008] As an improvement to the above solution, the step of constructing a pedestrian path network for children based on the activity trajectory data and preset target locations includes: Based on the activity trajectory data and the preset target locations, the child's target start and end points are determined; Construct a pedestrian path network for children based on the path between the target starting point and the target ending point.

[0009] As an improvement to the above scheme, the method for constructing the preset walking evaluation index system includes: Based on the cognitive development stage characteristics, emotional safety needs, and group social behavior patterns of children aged 3-12, the core needs of children when walking were determined through questionnaires and behavioral observation. These core needs include safety, physical comfort, and exploration and interaction. For each core requirement, a corresponding quantifiable evaluation index is designed, and a pre-set walking evaluation index system is constructed through expert scoring.

[0010] To achieve the above objectives, embodiments of the present invention provide a path planning device adapted to the physiological needs of children, comprising: A road network construction module is used to acquire children's activity trajectory data within a target area; and to construct a pedestrian road network for children based on the activity trajectory data and preset target locations. The child-friendly road segmentation module is used to identify children's activity hotspots based on activity trajectory data, and to divide each path in the pedestrian road network into two levels by combining preset children's stride length, generating several child-friendly road segments. The target route determination module is used to call the preset walking evaluation index system to score each child-friendly route, eliminate walking routes containing routes with scores below the standard, and obtain the target route set. The optimal path determination module is used to predict the comprehensive score of each target path based on the road segment score using a weighted summation algorithm, and select the path with the highest score as the optimal walking path for children.

[0011] To achieve the above objectives, embodiments of the present invention provide a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the above-mentioned path planning method adapted to the physiological needs of children.

[0012] To achieve the above objectives, embodiments of the present invention also provide a computer-readable storage medium, the computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the above-mentioned path planning method adapted to the physiological needs of children.

[0013] To achieve the above objectives, embodiments of the present invention also provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the path planning method adapted to children's physiological needs described above.

[0014] Compared with existing technologies, the present invention discloses a path planning method, device, medium, and product adapted to children's physiological needs. This method acquires children's activity trajectory data within a target area; constructs a children's walking path network based on the activity trajectory data and preset target locations; identifies children's activity hotspots based on the activity trajectory data; divides each path in the walking path network into two levels based on preset children's stride length, generating several child-friendly road segments; scores each child-friendly road segment using a preset walking evaluation index system; eliminates walking paths containing segments with scores below the standard, obtaining a set of target paths; and uses a weighted summation algorithm to predict the comprehensive score of each target path based on the road segment scores, selecting the path with the highest score as the optimal children's walking path. This method can divide and evaluate each walking path based on the activity trajectory data and children's activity hotspots, obtaining the optimal walking path for children, enhancing the attractiveness of the target area to children and their families, creating a safe, fun, and comfortable walking environment for children, promoting children's physical and mental health development, and improving children's walking experience and safety within the target area. Attached Figure Description

[0015] Figure 1 This is a flowchart illustrating a path planning method adapted to children's physiological needs provided in an embodiment of the present invention. Figure 2 This is a schematic diagram of the structure of a path planning device adapted to the physiological needs of children provided in an embodiment of the present invention; Figure 3 This is a structural block diagram of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] It should be noted that the terms "comprising" and "specific" in this invention, and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0018] Please see Figure 1 , Figure 1 This is a flowchart illustrating a path planning method adapted to children's physiological needs provided in an embodiment of the present invention. The path planning method includes: S1, acquire activity trajectory data of children within the target area; construct a pedestrian route network for children based on the activity trajectory data and preset target locations; S2, based on activity trajectory data, identifies hotspots for children's activities, and combines preset children's stride length to divide each path in the pedestrian road network into two levels, generating several child-friendly road sections; S3, call the preset walking evaluation index system to score each child-friendly road segment, remove walking paths containing road segments with scores below the standard, and obtain the target path set; S4 uses a weighted summation algorithm to predict the comprehensive score of each target path based on the road segment score, and selects the path with the highest score as the optimal walking path for children.

[0019] For example, the path planning method adapted to children's physiological needs described in this embodiment of the invention is implemented by a path planning server, which is capable of interacting with the target user and with a geographic information system. The path planning server acquires children's activity trajectory data within the target area (e.g., GIS geographic information, children's daily activity trajectory data, dynamic popularity of child-friendly facilities, real-time status of rest spaces, and residential area distribution characteristics, etc.); constructs an intelligent association network of residential areas and child-friendly facilities based on the activity trajectory data in a spatiotemporal dimension, and acquires geographic environmental information related to children's walking; constructs a children's walking path network using graph theory algorithms based on the geographic environmental information and preset target locations; divides each walking path in the walking path network according to children's activity hotspots and preset children's stride length, obtaining several child-friendly segments for each walking path; evaluates each child-friendly segment according to a preset walking evaluation index system, obtaining a score for each child-friendly segment; eliminates walking paths corresponding to child-friendly segments with scores lower than a preset standard score, obtaining the target paths of the walking path network; predicts the comprehensive score of each target path based on the score of each child-friendly segment, and determines the optimal path among the target paths based on the predicted comprehensive score, in order to plan children's walking paths. This invention integrates multi-source data, including not only traditional geographic information but also dynamic data such as children's activity trajectories, to comprehensively and in real-time reflect the status of children's walking environment. It can divide and evaluate each walking path based on the activity trajectory data and children's activity hotspots, obtain the optimal walking path for children, enhance the attractiveness of the target area to children and their families, create a safe, fun, and comfortable walking environment for children, promote children's physical and mental health development, and improve children's walking experience and safety in the target area.

[0020] Specifically, step S2 includes: S21, Divide each walking path of the pedestrian road network according to the children's activity hotspot areas to obtain several basic road segments for each walking path; S22, divide each basic road segment according to the preset child stride to obtain several child-friendly road segments for each walking path.

[0021] For example, based on children's activity monitoring data, hotspot areas for children's activities are identified within the target area. Each walking path in the pedestrian network is then divided according to these hotspots to obtain several basic road segments. Starting from the children's activity concentration point of each basic road segment, the path is divided to both sides in multiples of the average child's stride length (e.g., using 50 cm as the basic unit) to obtain several child-friendly road segments. Road segments whose length is less than an integer multiple of the average child's stride length are treated as separate child-friendly road segments. More specifically, step S21 includes: S211, Based on the activity trajectory data, determine the children's activity hotspot areas of the pedestrian road network; S212, Divide each walking path of the pedestrian road network according to the children's activity hotspot area to obtain several basic road segments for each walking path.

[0022] For example, using children's activity hotspots as dividing points, each walking path in the pedestrian network is divided into basic road segments with independent functional attributes, which facilitates targeted analysis of children's needs in different areas (e.g., hotspot areas need to focus on social space, while non-hotspot areas need to focus on safety). Based on the preset children's stride length (e.g., average children's stride length), starting from the children's activity concentration point of each basic road segment, the road is divided to both sides to obtain several child-friendly road segments for each walking path.

[0023] It is worth noting that children's activity hotspots refer to areas where children frequently stop, gather, or are active while walking in the target area, such as playground entrances, school gates, near bookstores, and rest areas under the shade of trees. Children's activity hotspots can be determined through location data from smart wearable devices (such as wristbands and watches), camera monitoring data in the target area, and on-site observation records. Children's average stride refers to the average stride length of children aged 6-12 when walking, usually 40-60 centimeters (e.g., using 50 centimeters as a benchmark). The road segment is divided based on children's physiological characteristics to ensure that the length of the road segment matches the children's walking rhythm and avoids fatigue or interruption of experience due to excessively long or short segments. Children's activity concentration points refer to the specific locations within the basic road segment where children stay the longest and are most active, such as next to benches, in front of shops, and at intersection corners. These can be determined through high-density location data clustering analysis or camera video recognition.

[0024] For example, suppose a walking path is "Residential Area → Main Road → Park", with a total length of 800 meters. Based on the activity trajectory data, determine the children's activity hotspot area 1 and children's activity hotspot area 2 of the walking road network. Children's activity hotspot area 1: Near the bookstore in the middle of the main road (children's dwell rate 40%, average dwell time 15 minutes). Children's activity hotspot area 2: The playground entrance at the intersection of the main road and the park (dwell rate 60%, average dwell time 30 minutes). The resulting segmentation of the walking path is as follows: Basic segment A: Residential Area → Bookstore (300 meters, non-hotspot area, connecting the residential area and activity point). Basic segment B: Bookstore → Playground entrance (400 meters, including hotspot area 1, high-frequency children's dwell time). Basic segment C: Playground entrance → Park (100 meters, hotspot area 2, concentrated activity area before reaching the destination). Start from the children's activity concentration point within each basic segment (e.g., the bookstore entrance in basic segment B). Extend the route in both directions as an integer multiple of the average child's stride: divide the route in 50-centimeter increments in front of the starting point (e.g., from bookstore to playground) until the end of the basic section; divide the route in 50-centimeter increments behind the starting point (e.g., from residential area to bookstore) until the beginning of the basic section. If the remaining length at the end is less than 50 centimeters, it is divided into a separate child-friendly section (e.g., if 30 centimeters remain, it is treated as an independent section).

[0025] Taking basic road segment B as an example, basic road segment B is from the bookstore to the playground entrance (400 meters), with the children's activity center at the bookstore entrance (location O). Dividing towards the playground: Starting from point O, divide into 800 segments, each 50 centimeters long (400 meters ÷ 0.5 meters = 800 segments), ending at the playground entrance. Dividing towards the residential area: Basic road segment B starts at the bookstore and does not need to be divided further (if the starting point of the basic road segment is not the activity center, then it needs to be divided in both directions, forward and backward from the center). Finally, basic road segment B is divided into 800 child-friendly segments of 50 centimeters each, with each segment corresponding to a micro-scale assessment unit.

[0026] Specifically, in step S3, the step of calling a preset pedestrian evaluation index system to score each child-friendly road segment includes: S31, obtain the score of each evaluation indicator in the preset walking evaluation index system corresponding to each child-friendly road section; normalize the score of each evaluation indicator. S32, a weighted average is calculated based on the processed scores and the weights of the corresponding evaluation indicators to obtain the score for each child-friendly road segment.

[0027] For example, real-time location information of children during walking can be obtained through positioning data from children's smart wristbands; data from children's activity monitoring cameras in the target area can be used to analyze children's activities and dwell time on different road sections; online feedback data from children in the target area can be collected to understand children's evaluations and suggestions on walking routes in the target area; and on-site surveys of children can be organized to obtain users' intuitive feelings and opinions on the walking environment. Combining these data, walking data corresponding to each walking route and evaluation data corresponding to the walking evaluation index system can be obtained. For any child-friendly road section, the fuzzy comprehensive evaluation method is used to convert the performance of the road section on evaluation indicators such as interesting landscape, social space, safety protection, and cultural elements into scores. Then, the scores corresponding to each evaluation indicator are normalized to ensure that the scores are on the same order of magnitude. Next, the analytic hierarchy process (AHP) is used to determine the weight of each evaluation indicator, and the score of the child-friendly road section is calculated using a weighted average method based on the processed scores and the weights of the corresponding evaluation indicators.

[0028] Specifically, from all child-friendly road sections, road sections with scores below a preset standard score (which can be set as needed based on expert experience) are selected and marked as low-quality road sections. Walking paths containing low-quality road sections are then removed from all walking paths to obtain the target paths. The relevant data for each target path is input into a deep learning model (such as a convolutional neural network or a recurrent neural network). The model learns from a large amount of historical data to predict the comprehensive score of each target path, determines the optimal path based on the predicted score, and recommends the optimal path to the user.

[0029] Specifically, in step S1, constructing a pedestrian route network for children based on the activity trajectory data and preset target locations includes: S11, Based on the activity trajectory data and the preset target location, determine the child's target starting point and ending point; S12, construct a pedestrian path network for children based on the path between the target starting point and the target ending point.

[0030] For example, GIS geographic information data of the target area is acquired, including geographic elements such as roads, buildings, and green spaces. Children's smart wearable devices (such as children's smartwatches) are used to collect big data on children's daily activity trajectories, recording information such as activity time, location, and duration of stay. Dynamic popularity data of child-friendly facilities is obtained through internet platforms and relevant commercial data providers to understand the usage frequency and popularity of various children's facilities (such as playgrounds and libraries). Sensors and cameras are installed in the target area to monitor the usage status and environmental conditions of rest spaces in real time. Simultaneously, combined with existing residential area distribution data, data mining and analysis techniques are used to construct an intelligent association network of residential areas and child-friendly facilities based on spatiotemporal dimensions, obtaining the aforementioned activity trajectory data. Users set the target location for children (such as school, extracurricular classes, etc.) through a mobile application. Simultaneously, children's smart wearable devices collect high-frequency location and time patterns of children's daily activities. Using the residential area as the default starting point, and combining the target location set by parents with the child's activity patterns, the target starting and ending points for walking are comprehensively determined. Graph theory algorithms are used to abstract the roads in the target area into nodes and edges, constructing a pedestrian road network based on the actual road connections and traffic rules. At the same time, artificial intelligence technology is used to optimize the road network, taking into account factors such as road slope, width, and pedestrian traffic, to ensure that the constructed network meets the actual needs of children walking.

[0031] Specifically, the method for constructing the preset walking evaluation index system includes: Based on the cognitive development stage characteristics, emotional safety needs, and group social behavior patterns of children aged 3-12, the core needs of children when walking were determined through questionnaires and behavioral observation. These core needs include safety, physical comfort, and exploration and interaction. For each core requirement, a corresponding quantifiable evaluation index is designed, and a pre-set walking evaluation index system is constructed through expert scoring.

[0032] For example, a research team composed of child psychologists, child educators, and urban planning experts was organized to conduct in-depth research on children's behavior, psychological needs, and preferences during walks in the target area through questionnaires, field observations, and group interviews. For instance, questionnaires were conducted with children of different age groups to inquire about their preferred elements of the walking environment; children's activities were observed within the target area, recording the areas where they spent the most time and the types of activities they participated in; and group interviews were conducted with children to understand their expectations and suggestions regarding walking routes in the target area. Based on these research findings, children's cognitive development characteristics, emotional needs, and social behavior patterns were identified to determine their needs for exploration and novelty, social interaction, safety and fun, and cultural experience while walking in the target area. Indicators for interesting landscapes, social spaces, safety protection, and cultural elements were designed to address these needs. Expert scoring and the analytic hierarchy process (AHP) were used to determine the weights of each indicator, establishing a walking evaluation index system tailored to children's needs.

[0033] This invention establishes a unique walking evaluation index system by deeply analyzing children's behavioral characteristics and psychological needs, enabling the planned walking routes to accurately match children's needs. For example, it can set up rich and interesting landscapes and sufficient social spaces to enhance children's enjoyment and participation during the walking process.

[0034] This invention discloses a path planning method adapted to children's physiological needs. The method involves acquiring children's activity trajectory data within a target area; constructing a children's walking path network based on the activity trajectory data and preset target locations; identifying children's activity hotspots based on the activity trajectory data; dividing each path in the walking path network into two levels based on preset children's stride lengths to generate several child-friendly road segments; scoring each child-friendly road segment using a preset walking evaluation index system; eliminating walking paths containing segments with scores below the standard, resulting in a set of target paths; and using a weighted summation algorithm to predict the comprehensive score of each target path based on the road segment scores, selecting the path with the highest score as the optimal children's walking path. This method can divide and evaluate each walking path based on the activity trajectory data and children's activity hotspots, obtaining the optimal walking path for children, enhancing the attractiveness of the target area to children and their families, creating a safe, fun, and comfortable walking environment for children, promoting children's physical and mental health development, and improving children's walking experience and safety within the target area.

[0035] See Figure 2 , Figure 2 This is a schematic diagram of the structure of a path planning device 10 adapted to the physiological needs of children provided in an embodiment of the present invention. The path planning device 10 adapted to the physiological needs of children includes: The road network construction module 11 is used to acquire children's activity trajectory data within the target area; and to construct a pedestrian road network for children based on the activity trajectory data and preset target locations. The child-friendly road segment division module 12 is used to identify children's activity hotspots based on activity trajectory data, and to divide each path in the pedestrian road network into two levels in combination with the preset children's stride length, generating several child-friendly road segments. The target path determination module 13 is used to call the preset walking evaluation index system to score each child-friendly road segment, remove walking paths containing road segments with scores below the standard, and obtain the target path set. The optimal path determination module 14 is used to predict the comprehensive score of each target path based on the road segment score using a weighted summation algorithm, and select the path with the highest score as the optimal walking path for children.

[0036] The path planning device 10 adapted to the physiological needs of children provided in this embodiment of the invention can realize all the processes of the path planning method adapted to the physiological needs of children in the above embodiment. The functions and technical effects of each module in the device are the same as the functions and technical effects of the path planning method adapted to the physiological needs of children in the above embodiment, and will not be repeated here.

[0037] See Figure 3 , Figure 3 This is a schematic diagram of the structure of a terminal device 20 provided in an embodiment of the present invention. The terminal device 20 of this embodiment includes: a processor 21, a memory 22, and a computer program stored in the memory 22 and executable on the processor 21. When the processor 21 executes the computer program, it implements the steps in the above-described embodiment of the path planning method adapted to children's physiological needs. Alternatively, when the processor 21 executes the computer program, it implements the functions of each module in the above-described embodiment of the path planning device adapted to children's physiological needs.

[0038] For example, the computer program may be divided into one or more modules, which are stored in the memory 22 and executed by the processor 21 to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device 20.

[0039] The terminal device 20 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The terminal device 20 may include, but is not limited to, a processor 21 and a memory 22. Those skilled in the art will understand that the schematic diagram is merely an example of the terminal device 20 and does not constitute a limitation on the terminal device 20. It may include more or fewer components than shown, or combine certain components, or different components. For example, the terminal device 20 may also include input / output devices, network access devices, buses, etc.

[0040] The processor 21 may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor. The processor 21 is the control center of the terminal device 20, connecting all parts of the terminal device 20 via various interfaces and lines.

[0041] The memory 22 can be used to store the computer programs and / or modules. The processor 21 implements various functions of the terminal device 20 by running or executing the computer programs and / or modules stored in the memory 22 and calling the data stored in the memory 22. The memory 22 may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as sound playback function, image playback function, etc.), etc.; the data storage area may store data created according to the use of the mobile phone (such as audio data, phonebook, etc.). In addition, the memory 22 may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0042] If the modules integrated in the terminal device 20 are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by the processor 21, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electrical carrier signals and telecommunication signals.

[0043] It should be noted that the device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can be specifically implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0044] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein the computer program, when running, controls the device where the computer-readable storage medium is located to execute a path planning method adapted to the physiological needs of children as described in the above embodiments.

[0045] Furthermore, embodiments of the present invention also provide a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the path planning method adapted to the physiological needs of children described in the above embodiments.

[0046] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A path planning method for adapting to physiological needs of children, characterized in that, The method comprises the following steps: acquiring activity trajectory data of children in a target area; and constructing a walking road network of children according to the activity trajectory data and a preset target location; identifying a child activity hotspot area based on the activity trajectory data, and performing two-level division on each path in the walking road network in combination with a preset child step to generate a plurality of child-friendly road segments; calling a preset walking evaluation index system to score each child-friendly road segment, eliminating a walking path containing a road segment with a score lower than a standard score, and obtaining a target path set; using a weighted summation algorithm to predict a comprehensive score of each target path according to the score of the road segment, and selecting a path with the highest score as an optimal child walking path.

2. The path planning method for adapting to children's physiological needs according to claim 1, wherein, The method of identifying a child activity hotspot area based on activity trajectory data, and performing two-level division on each path in the walking road network in combination with a preset child step to generate a plurality of child-friendly road segments comprises the following steps: dividing each walking path of the walking road network according to the child activity hotspot area to obtain a plurality of basic road segments of each walking path; dividing each basic road segment according to a preset child step to obtain a plurality of child-friendly road segments of each walking path.

3. The path planning method for adapting to children's physiological needs according to claim 2, wherein, The method of dividing each walking path of the walking road network according to the child activity hotspot area to obtain a plurality of basic road segments of each walking path comprises the following steps: determining a child activity hotspot area of the walking road network according to the activity trajectory data; dividing each walking path of the walking road network according to the child activity hotspot area to obtain a plurality of basic road segments of each walking path. 4.The path planning method for adapting to children's physiological needs according to claim 1, wherein, The method of calling a preset walking evaluation index system to score each child-friendly road segment comprises the following steps: acquiring a score of each evaluation index in the preset walking evaluation index system corresponding to each child-friendly road segment; and performing normalization processing on the score of each evaluation index; performing weighted averaging on the processed score and the weight of the corresponding evaluation index to obtain a score of each child-friendly road segment.

5. The path planning method for adapting to children's physiological needs according to claim 1, wherein, The method of constructing a walking road network of children according to the activity trajectory data and a preset target location comprises the following steps: determining a target starting point and a target ending point of children according to the activity trajectory data and the preset target location; constructing a walking road network of children according to a path between the target starting point and the target ending point. 6.The path planning method for adapting to children's physiological needs according to claim 1, wherein, The method of constructing a preset walking evaluation index system comprises the following steps: combining the characteristics of the cognitive development stage, the emotional safety demand and the group social behavior mode of children aged 3-12 years old, determining core demands of children when walking through questionnaire investigation and behavior observation, and the core demands include safety guarantee, physiological comfort and exploration interaction; designing a corresponding quantifiable evaluation index for each core demand, and constructing a preset walking evaluation index system through expert scoring method.

7. A path planning device suitable for adapting to physiological needs of children, characterized in that, The method comprises the following steps: a road network construction module is configured to acquire activity trajectory data of children in a target area; a walking road network of children is constructed according to the activity trajectory data and a preset target location; a friendly road segment division module is configured to identify a child activity hotspot area based on the activity trajectory data, and perform two-level division on each path in the walking road network in combination with a preset child step to generate a plurality of child-friendly road segments. The target path determination module is configured to call a preset walking evaluation index system to score each child-friendly road segment, eliminate a walking path including a road segment with a score lower than a standard score, and obtain a target path set; The optimal path determination module is configured to use a weighted summation algorithm to predict a comprehensive score of each target path according to the road segment score, and select a path with the highest score as an optimal child walking path.

8. A terminal device, characterized by comprising: The computer readable storage medium comprises a stored computer program, wherein the computer program, when executed by the processor, implements the path planning method adapted to physiological needs of children according to any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium comprises a stored computer program, wherein the computer program, when executed by the processor, implements the path planning method adapted to physiological needs of children according to any one of claims 1-6.

10. A computer program product, characterised in that, The computer program product is stored in a storage medium, and the program product is executed by at least one processor to implement the steps of the path planning method adapted to physiological needs of children according to any one of claims 1-6.

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