Path planning method and device based on adaptive heuristic

Abstract

The invention discloses a path planning method and device based on an adaptive heuristic mode, and relates to the technical field of path planning. The method comprises the following steps: receiving a first request sent by a target user; determining a first position and first information according to the first request; inputting the first position and the first information into a preset path database for query to obtain a plurality of path plans; calculating each path plan to obtain a plurality of adaptive heuristic scores; obtaining a first heuristic score from the plurality of adaptive heuristic scores, and determining a first path plan according to the first heuristic score; acquiring second information sent by a target user; and when the second information is consistent with the preset first information, confirming that the first path plan is displayed to the target user, so that the target user moves according to the first path plan. By implementing the technical scheme provided by the invention, the problem that the preference difference of different runners to routes cannot be considered in traditional route planning is effectively solved, so that the route planning experience of the user is improved.

Description

Technical Field

[0001] The present application relates to the technical field of path planning, and in particular to a path planning method and device based on adaptive heuristics. Background Art

[0002] As an indispensable key link in the smart city architecture, the in-depth implementation of the construction and operation strategy of smart parks is of great significance to promoting the development trajectory of urban informatization and intelligence, and at the same time lays a solid foundation for the innovation of urban management models and the significant improvement of service quality. In the actual application scenarios of smart parks, especially in meeting the user's sports and exercise needs, running is a popular activity, and the efficiency and personalization of its route planning have become the key links in optimizing user experience.

[0003] However, given that smart parks usually have a relatively large geographical space, users often need to plan a reasonable running route in advance when preparing for running exercises to ensure the continuity and safety of the exercise process. However, the current route planning mechanism mainly relies on the user's pre-set starting and end points to generate a fixed running path. Although this route planning method based on initial settings can provide users with basic navigation services, it fails to fully consider the differences in route preferences among different runners, such as scenery diversity, difficulty adaptability, safety considerations, etc., resulting in a poor path planning experience for users.

[0004] Therefore, there is an urgent need for a path planning method and device based on adaptive heuristics that can solve the above technical problems. Summary of the invention

[0005] The present application provides a path planning method and device based on adaptive heuristics, which effectively solves the problem that traditional path planning cannot take into account the differences in route preferences of different runners, thereby improving the user's path planning experience.

[0006] In the first aspect, the present application provides a path planning method based on adaptive heuristics, which is applied to a server, and the method includes: receiving a first request sent by a target user; determining a first position and a first information according to the first request, the first information including movement distance information, movement duration information and calorie consumption information, and the first position is the position of the target user in the smart park; inputting the first position and the first information into a preset path database for query to obtain multiple path plans; calculating each path plan to obtain multiple adaptive heuristic scores; obtaining a first heuristic score from multiple adaptive heuristic scores, and determining a first path plan according to the first heuristic score; obtaining second information sent by the target user, and determining whether the second information is consistent with the preset first information, the preset first information being the information corresponding to the first path plan; when the second information is consistent with the preset first information, confirming that the first path plan is displayed to the target user, so that the target user can move according to the first path plan.

[0007] By adopting the above technical solution, a first request sent by a target user is received, and a first position and a first information are determined according to the first request. The first information can reflect the personalized needs of the target user. By inputting the first position and the first information into a preset path database for query, multiple path plans are generated. These path plans take into account the first information of the target user. Then, each path plan is calculated to obtain multiple adaptive heuristic scores. After determining the first path plan corresponding to the first heuristic score from multiple adaptive heuristic evaluations, the second information sent by the target user is obtained, and the second information is compared with the preset first information to ensure that the selected path can meet the user's needs. When the second information is consistent with the preset first information, it is confirmed that the first path plan will be displayed to the target user. Based on the feedback of the target user, the path planning can be continuously optimized to better meet the personalized needs of the target user, which effectively solves the problem that the current route planning method with initialization settings cannot consider the differences in route preferences of different runners, thereby improving the user's path planning experience.

[0008] Optionally, a first heuristic score is obtained from multiple adaptive heuristic scores, and a first path plan is determined according to the first heuristic score; specifically, the method includes: sorting multiple adaptive heuristic scores according to preset rules to obtain a target sorting result, wherein the preset rule is a priority queue rule; obtaining the first heuristic score from the target sorting result, and determining a first path plan corresponding to the first heuristic score, wherein the first heuristic evaluation is the heuristic score corresponding to the first position in the target sorting result.

[0009] By adopting the above technical solution, multiple adaptive heuristic scores are sorted according to preset rules to obtain the target sorting result, which can automatically and quickly identify the optimal or most user-friendly path planning. The priority queue rules can be adjusted and optimized according to different user needs. The first path planning is determined by sorting and selecting the first heuristic score, which can reduce unnecessary calculation and comparison processes, thereby improving the overall performance.

[0010] Optionally, before determining whether the second information is consistent with the preset first information, the method also includes: obtaining multiple first target scores corresponding to the first path planning, the multiple first target scores including terrain complexity assessment, camera coverage score, obstacle density score, pedestrian flow score, vegetation coverage score and air quality score; weighted summing up the multiple first target scores to obtain a first safety score; obtaining multiple second target scores corresponding to the first path planning, the multiple second target scores including path length score, expected running time score, energy consumption score, terrain score and congestion score; weighted summing up the multiple second target scores to obtain a first efficiency score; and outputting the first safety score and the first efficiency score as the preset first information.

[0011] By adopting the above technical solution, a first target score of multiple dimensions can be introduced, and the safety score of the first path planning can be evaluated through the first target score. Then, a second target score of multiple dimensions can be introduced, and the efficiency score of the first path planning can be evaluated through the second target score. The quality of the first path planning can be evaluated based on the safety score and the efficiency score. This comprehensive evaluation method helps the target user to have a more comprehensive understanding of the advantages and disadvantages of the selected path, so as to make more informed decisions.

[0012] Optionally, determining whether the second information is consistent with the preset first information specifically includes: obtaining a second safety score and a second efficiency score from the second information; determining whether the first safety score is greater than or equal to the second safety score, and whether the first efficiency score is greater than or equal to the second efficiency score; when the first safety score is greater than or equal to the second safety score, and the first efficiency score is greater than or equal to the second efficiency score, confirming that the first path planning is recommended to the target user.

[0013] By adopting the above technical solution, comparing the first safety score with the second safety score, and also comparing the first efficiency score with the second efficiency score, it is possible to ensure that the path planning recommended to the target user is at least not lower than the target user's own expectations in terms of safety and efficiency. By introducing a scoring comparison mechanism, the advantages and disadvantages of different path plans can be evaluated more accurately. When the first path planning meets the user's needs in terms of safety and efficiency, it can be recommended to the target user, which helps to reduce the situation where inappropriate path planning is recommended to the user, thereby improving the accuracy of the overall path planning.

[0014] Optionally, after determining the first position and the first information according to the first request, and the first information includes exercise distance information, exercise duration information and calorie consumption information, the method also includes: obtaining a second position sent by the target user, the second position being any position in the smart park except the first position; inputting the first position and the second position into a preset path database for query to obtain a second path plan; determining whether the second information is consistent with the preset second information, the preset second information being the information corresponding to the second path plan; when the second information is consistent with the preset second information, confirming that the second path plan will be displayed to the target user.

[0015] By adopting the above technical solution, the target user is allowed to specify the second position as the end point of the path planning, thereby increasing the flexibility of the target user when using the path planning function. The target user can adjust the end point of the path at any time according to his or her needs, so as to find the movement path that best suits him or her. The second path planning can be obtained by quickly querying the preset path database to reduce the calculation time, and then it is determined whether the second information is consistent with the preset second information to choose whether to display the second path planning, which can improve the efficiency of path planning.

[0016] Optionally, when the second information is consistent with the preset first information, it is confirmed that the first path planning is displayed to the target user so that the target user can move according to the first path planning. The method also includes: obtaining a target image at a preset time interval, the target image is an image corresponding to a third position, and the third position is any position to be moved in the first path planning; processing the target image to obtain a target analysis result; confirming that the third position is marked as an abnormal position according to the target analysis result, and determining an alternative position based on the abnormal position; replacing the third position with an alternative position, regenerating the third path planning, and displaying the third path planning to the target user so that the target user can move based on the third path planning.

[0017] By adopting the above technical solution, the target image is acquired at preset intervals, each position in the first path planning is monitored in real time, possible abnormal situations are sent in time, the target image is processed to obtain the target analysis result, the abnormal position is determined according to the target analysis result, the alternative position is called based on the abnormal position, and the third position is replaced by the alternative position to regenerate the third path planning. This flexible adjustment mechanism can dynamically adjust the path planning according to the real-time situation, ensure that the user can move along the optimal path, and display the updated third path planning to the target user in time, which helps to improve user satisfaction.

[0018] Optionally, before acquiring the target image at a preset time interval, the method also includes: receiving a second request corresponding to the target user; determining third information and a fourth position based on the second request, the fourth position being a position of the target user corresponding to a target time point, the target time point being a time point corresponding to the target user sending the second request, and the third information being road information; inputting the fourth position and the third information into a preset path database for query to obtain a fourth path plan; and displaying the fourth path plan to the target user.

[0019] By adopting the above technical solution, the second request sent by the target user is received in real time, the fourth position and the third information are determined according to the second request, and the fourth position and the third information are input into the preset path database for query to obtain the fourth path plan. It is possible to generate a personalized path plan for the user in real time. This path planning takes into account the user's actual needs and current location, saves the user from the process of querying the path by himself, and improves the user's usage efficiency.

[0020] In a second aspect of the present application, a path planning device based on adaptive heuristic is provided, the device is a server, and the server includes an acquisition unit, a processing unit and a display unit; the acquisition unit receives a first request sent by a target user; acquires a first heuristic score from multiple adaptive heuristic scores, and determines a first path planning according to the first heuristic score; acquires second information sent by the target user, and the processing unit determines a first position and a first information according to the first request, the first information includes movement distance information, movement duration information and calorie consumption information, and the first position is the position of the target user in the smart park; the first position and the first information are input into a preset path database for query to obtain multiple path planning; each path planning is calculated to obtain multiple adaptive heuristic scores; it is determined whether the second information is consistent with the preset first information, and the preset first information is the information corresponding to the first path planning; the display unit, when the second information is consistent with the preset first information, confirms that the first path planning is displayed to the target user, so that the target user can move according to the first path planning.

[0021] Optionally, the processing unit is used to sort multiple adaptive heuristic scores according to preset rules to obtain a target sorting result, and the preset rules are priority queue rules; the acquisition unit is used to obtain a first heuristic score from the target sorting result, and determine a first path planning corresponding to the first heuristic score, and the first heuristic evaluation is the heuristic score corresponding to the first position in the target sorting result.

[0022] Optionally, the acquisition unit is used to obtain multiple first target scores corresponding to the first path planning, the multiple first target scores include terrain complexity assessment, camera coverage score, obstacle density score, pedestrian flow score, vegetation coverage score and air quality score; the processing unit is used to perform weighted summation on the multiple first target scores to obtain a first safety score; the acquisition unit is used to obtain multiple second target scores corresponding to the first path planning, the multiple second target scores include path length score, expected running time score, energy consumption score, terrain score and congestion level score; the processing unit is used to perform weighted summation on the multiple second target scores to obtain a first efficiency score; and output the first safety score and the first efficiency score as preset first information.

[0023] Optionally, the acquisition unit is used to obtain a second safety score and a second efficiency score from the second information; the processing unit is used to determine whether the first safety score is greater than or equal to the second safety score, and whether the first efficiency score is greater than or equal to the second efficiency score; when the first safety score is greater than or equal to the second safety score, and the first efficiency score is greater than or equal to the second efficiency score, it is confirmed that the first path planning is recommended to the target user.

[0024] Optionally, the acquisition unit is used to obtain a second location sent by the target user, where the second location is any location in the smart park except the first location; the processing unit is used to input the first location and the second location into a preset path database for query to obtain a second path plan; it is determined whether the second information is consistent with the preset second information, where the preset second information is the information corresponding to the second path plan; the display unit is used to confirm that the second path plan will be displayed to the target user when the second information is consistent with the preset second information.

[0025] Optionally, the acquisition unit is used to acquire a target image at a preset time interval, where the target image is an image corresponding to a third position, and the third position is any position to be moved in the first path planning; the processing unit is used to process the target image to obtain a target analysis result; based on the target analysis result, the third position is marked as an abnormal position, and an alternative position is determined based on the abnormal position; the display unit is used to replace the third position with an alternative position, regenerate a third path planning, and display the third path planning to the target user so that the target user can move based on the third path planning.

[0026] Optionally, the acquisition unit is used to receive a second request corresponding to the target user; the processing unit is used to determine third information and a fourth position based on the second request, the fourth position being the position of the target user corresponding to the target time point, the target time point being the time point corresponding to the target user sending the second request, and the third information being road information; the fourth position and the third information are input into a preset path database for query to obtain a fourth path plan; the display unit is used to display the fourth path plan to the target user.

[0027] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.

[0028] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.

[0029] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. Receive a first request sent by a target user, determine a first position and first information according to the first request, the first information can reflect the personalized needs of the target user, and generate multiple path plans by inputting the first position and the first information into a preset path database for query. These path plans take into account the first information of the target user, and then calculate each path plan to obtain multiple adaptive heuristic scores. After determining the first path plan corresponding to the first heuristic score from multiple adaptive heuristic evaluations, obtain the second information sent by the target user, compare the second information with the preset first information, and ensure that the selected path can meet the user's needs. When the second information is consistent with the preset first information, confirm that the first path plan is displayed to the target user. Based on the feedback of the target user, the path planning can be continuously optimized to better meet the personalized needs of the target user, which effectively solves the problem that the current initialization route planning method cannot consider the differences in route preferences of different runners, thereby improving the user's path planning experience.

[0030] 2. Allow the target user to specify the second location as the end point of the path planning, increase the flexibility of the target user when using the path planning function, and the target user can adjust the end point of the path at any time according to their needs, so as to find the most suitable movement path for themselves. The second path planning can be obtained by quickly querying the preset path database to reduce the calculation time, and then determine whether the first information is consistent with the preset second information to choose whether to display the second path planning, which can improve the efficiency of path planning.

[0031] 3. Acquire the target image at preset intervals, monitor each position in the first path planning in real time, send possible abnormal situations in time, process the target image to obtain the target analysis result, determine the abnormal position according to the target analysis result, call the alternative position based on the abnormal position, replace the third position with the alternative position to regenerate the third path planning. This flexible adjustment mechanism can dynamically adjust the path planning according to the real-time situation, ensure that the user can move along the optimal path, and display the updated third path planning to the target user in time, which helps to improve user satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a flowchart of a path planning method based on adaptive heuristics provided in an embodiment of the present application; Figure 2 It is a structural schematic diagram of a path planning device based on adaptive heuristics provided in an embodiment of the present application; Figure 3 It is a structural schematic diagram of an electronic device disclosed in an embodiment of the present application.

[0033] Explanation of the reference numerals: 201, acquisition unit; 202, processing unit; 203, display unit; 300, electronic device; 301, processor; 302, communication bus; 303, user interface; 304, network interface; 305, memory. DETAILED DESCRIPTION

[0034] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0035] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0036] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0037] As an indispensable key link in the smart city architecture, the in-depth implementation of the construction and operation strategy of smart parks is of great significance to promoting the development trajectory of urban informatization and intelligence, and at the same time lays a solid foundation for the innovation of urban management models and the significant improvement of service quality. In the actual application scenarios of smart parks, especially in meeting the user's sports and exercise needs, running is a popular activity, and the efficiency and personalization of its route planning have become the key links in optimizing user experience.

[0038] However, given that smart parks usually have a relatively large geographical space, users often need to plan a reasonable running route in advance when preparing for running exercises to ensure the continuity and safety of the exercise process. However, the current route planning mechanism mainly relies on the user's pre-set starting and end points to generate a fixed running path. Although this route planning method based on initial settings can provide users with basic navigation services, it fails to fully consider the differences in route preferences among different runners, such as scenery diversity, difficulty adaptability, safety considerations, etc., resulting in a poor path planning experience for users.

[0039] Therefore, how to solve the current problem of how to initialize the route planning method and fail to take into account the personalized needs of different runners, resulting in poor user route planning experience. The embodiment of the present application provides a path planning method based on adaptive heuristics, which is applied to the server. The server of the present application can be a platform that provides path planning services for smart parks. Figure 1 is a flow chart of a path planning method based on adaptive heuristics provided in an embodiment of the present application, with reference to Figure 1 The method includes the following steps S101-S107.

[0040] S101: Receive a first request sent by a target user.

[0041] In the above S101, the target user refers to a person who enters the smart park to exercise. The target user sends a first request to the server through an electronic device. The first request includes the target user's need to exercise in the smart park, and the demand includes the type of exercise, duration, and distance. The server is a management platform corresponding to the smart park, and the server receives the first request sent by the target user. This application takes running as an example of the exercise type.

[0042] S102: Determine a first location and first information according to the first request, where the first information includes exercise distance information, exercise duration information, and calorie consumption information. The first location is the location of the target user in the smart park.

[0043] In the above S102, after receiving the first request, the server can use GPS positioning technology or WiFi / Bluetooth positioning technology to determine the user's location. At this time, the user's location is defined as the first location, which can be understood as the starting location of the target user after entering the smart park. The first request is then parsed to obtain the first information, which includes exercise distance information, exercise duration information, and calorie consumption information. The exercise distance information refers to the total distance information expected to be run by the user, the exercise duration refers to the total duration information expected to be run by the user, and the calorie consumption information refers to the information on the calorie consumption expected to be consumed by the user.

[0044] S103: Input the first position and the first information into a preset path database for query to obtain multiple path plans.

[0045] In the above S103, before the first position and the first information are input into the preset path database for query and multiple path plans are obtained, it is necessary to build a preset path database, which is a database that stores all possible paths and their attributes in the smart park, including path length, required time, and calories consumed. After the preset path database is built, a qualified path is determined according to the first position and the first information (such as movement distance, duration, and calories consumed) input by the target user, and multiple destinations can be determined based on the first information, and then the path between the first position and each destination is constructed, and the multiple path plans are output.

[0046] S104: Calculate each path plan to obtain multiple adaptive heuristic scores.

[0047] In the above S104, after obtaining multiple path plans, an adaptive heuristic function can be used to calculate each path plan. The adaptive heuristic function aims to find the path that best suits the user's needs. The adaptive heuristic score obtained takes into account factors such as the terrain complexity, camera coverage, obstacle density, and path usage frequency, weather changes, and avoiding crowds. Adaptive heuristic score = a*basic heuristic score + (1-a)*experience adjustment factor; where a is a weight between 0 and 1, which is used to balance the basic heuristic score and the experience adjustment factor. The basic heuristic score is a static evaluation, while the experience adjustment factor is a dynamic adjustment based on historical data and real-time feedback. The specific calculation method is: basic heuristic score = W1*terrain complexity score + W2*camera coverage score + W3*obstacle density score, where W1, W2, and W3 are the weights of each factor. Terrain complexity score = 1-actual terrain complexity / maximum possible terrain complexity; camera coverage score = 1-camera coverage area / total park area; obstacle density score = 1-number of obstacles / unit area; experience adjustment factor = f (path usage frequency, weather changes, avoiding crowds), where f is a function that adjusts the score based on input historical data and real-time information. The actual terrain complexity, camera coverage area, and obstacle data mentioned above refer to the actual data corresponding to each path planning. If the target path planning is adaptively heuristically calculated at this time, the actual terrain complexity, camera coverage area, and obstacle data corresponding to the target path planning are obtained, not the data of a certain area. Based on the above calculation method, each path planning is calculated in turn to obtain multiple adaptive heuristic scores, and one adaptive heuristic score corresponds to one path planning.

[0048] S105: Obtain a first heuristic score from the multiple adaptive heuristic scores, and determine a first path plan according to the first heuristic score.

[0049] In the above S105, after obtaining multiple adaptive heuristic scores, a first heuristic score is obtained from the multiple adaptive heuristic scores, and a first path plan is determined according to the first heuristic score; specifically, the method includes: sorting the multiple adaptive heuristic scores according to a preset rule to obtain a target sorting result, wherein the preset rule is a priority queue rule; obtaining the first heuristic score from the target sorting result, and determining the first path plan corresponding to the first heuristic score, wherein the first heuristic evaluation is the heuristic score corresponding to the first position in the target sorting result. Specifically, the multiple adaptive heuristic scores can be sorted according to the preset rule, wherein the preset rule refers to the priority queue rule. The priority queue is a special type of queue, which is different from the traditional first-in-first-out (FIFO) queue. In a priority queue, each element is assigned a priority, and the operation of the queue is performed based on these priorities. According to the definition of priority, the priority queue can be divided into a maximum priority queue and a minimum priority queue. In a maximum priority queue, the element with the highest priority is processed first; and in a minimum priority queue, the element with the lowest priority is processed first. In this application, the preset rule is to use the minimum priority queue for sorting. First, the adaptive heuristic scores of all path plans are collected into a list, and then multiple adaptive heuristic scores are sorted according to the preset rules. This list is sorted, that is, the one with the smallest adaptive heuristic score is placed first, and then sorted in order from small to large. After the sorting is completed, the resulting list is the target sorting result, in which the path plan with the lowest score is at the top of the list. Since the target sorting result is already a list sorted by heuristic score, the first heuristic score can be obtained directly from the first place in the list. After obtaining the first heuristic score, it is necessary to find the path plan corresponding to this score. This usually means that a mapping relationship from score to path plan needs to be maintained, and the first path plan is determined based on the mapping relationship.

[0050] S106: Acquire second information sent by the target user, and determine whether the second information is consistent with preset first information, where the preset first information is information corresponding to the first path planning.

[0051] In the above S106, when the second information sent by the target user is obtained, the second information refers to the target user's preference information for path planning, and the preference information refers to the user's consideration of path safety and efficiency. Before comparing whether the second information is consistent with the preset first information, the preset first information corresponding to the first path planning needs to be obtained, and the preset first information is the safety and efficiency actually corresponding to the first path planning.

[0052] In addition, obtaining the preset first information corresponding to the first path planning specifically includes: obtaining multiple first target scores corresponding to the first path planning, the multiple first target scores include terrain complexity evaluation, camera coverage score, obstacle density score, traffic flow score, vegetation coverage score and air quality score; weighted summing the multiple first target scores to obtain a first safety score; obtaining multiple second target scores corresponding to the first path planning, the multiple second target scores include path length score, expected running time score, energy consumption score, terrain score and congestion score; weighted summing the multiple second target scores to obtain a first efficiency score; outputting the first safety score and the first efficiency score as the preset first information. Specifically, the evaluation can be performed according to the terrain characteristics (such as slope, undulation, road surface material, etc.) of the first path planning. The higher the complexity, the lower the score. The coverage of the camera on the first path planning can be evaluated. The more comprehensive the coverage, the higher the score. The number and density of obstacles on the first path planning can be evaluated. The lower the density, the higher the score. At this time, the obstacles refer to physical obstacles, smart device obstacles, obstacles caused by human factors, etc. The flow of people on the first path planning can be evaluated. When the flow of people is moderate or low, the score is high, and when it is too high, the score is low. The vegetation coverage around the first path planning can be evaluated. The more vegetation coverage, the higher the score. The current time can also be determined based on the received first request, and then the weather information of the corresponding area of ​​the smart park is obtained according to the current time. The air quality around the first path planning is evaluated according to the weather information. The better the quality, the higher the score. Geographic Information System (GIS) technology can be used to obtain data such as terrain, vegetation, and air quality. Camera coverage and obstacle density can be obtained through the park's management system or sensor network. The flow of people can be estimated through surveillance cameras, Wi-Fi hotspot tracking, or mobile phone APP data. A weight is then assigned to each first target score, and the size of the weight reflects the importance of the score to safety. Each score is then multiplied by its corresponding weight to obtain a weighted score. Finally, all weighted scores are added together to obtain a first safety score. The weight allocation can be determined based on user feedback or data analysis. The score is then scored based on the actual length of the first path planning. When the length is moderate or short, the score is higher. Based on the length of the first path planning and the speed set by the user, the expected running time is estimated and a score is given. The energy consumption required to complete the path is evaluated. The lower the energy consumption, the higher the score. Unlike the terrain complexity evaluation, the terrain score here may focus more on the aesthetics of the terrain or the degree of suitability for running. The congestion level on the first path planning is evaluated. The lower the congestion level, the higher the score. Similar to the calculation of the first safety score, weights are assigned to each second target score and weighted summed. However, the weight allocation here should be based on efficiency considerations, that is, which factors are more important for improving running efficiency or user experience. The method of weight allocation and weighted summation is the same as the calculation of the first safety score.The calculated first safety score and first efficiency score are used as two key indicators for evaluating the first path planning. The first safety score and the first efficiency score are output as the preset first information. A correspondence relationship between the preset first information and the first path planning can be established, and when the first path planning is subsequently obtained, the preset first information can be retrieved based on the correspondence relationship.

[0053] Further, judging whether the second information is consistent with the preset first information specifically includes: obtaining the second safety score and the second efficiency score from the second information; judging whether the first safety score is greater than or equal to the second safety score, and whether the first efficiency score is greater than or equal to the second efficiency score; when the first safety score is greater than or equal to the second safety score, and the first efficiency score is greater than or equal to the second efficiency score, then confirming that the first path planning is recommended to the target user. Specifically, the second safety score and the second efficiency score are extracted from the second information, and the second safety score and the second efficiency score are the target user's preference settings for the path, which are reflected by numerical values. Comparing whether the preset first information is consistent with the second information, that is, comparing the first safety score and the second safety score, and the first efficiency score and the second efficiency score. Since two conditions need to be met at the same time (that is, the first safety score is greater than or equal to the second safety score, and the first efficiency score is greater than or equal to the second efficiency score). Once it is confirmed that the first safety score is greater than or equal to the second safety score, and the first efficiency score is greater than or equal to the second efficiency score, it is confirmed that the first path planning is superior to (or at least not inferior to) the second path planning in terms of both safety and efficiency. Then, recommendation information can be sent to the target user. At this time, the first path planning is recommended to the user for the target user to choose.

[0054] Furthermore, if the first safety score is less than the second safety score, and the first efficiency score is less than the second efficiency score, or the first safety score is equal to the second safety score, and the first efficiency score is less than the second efficiency score, then it is confirmed that the first path planning does not meet the target user's preference, and it is necessary to obtain other path planning from the target sorting result, and obtain the preset information corresponding to the other path planning in turn, and compare the preset information with the second information, and then determine whether to recommend the path to the target user based on the comparison result.

[0055] S107: When the second information is consistent with the preset first information, it is confirmed that the first path planning is displayed to the target user, so that the target user can move according to the first path planning.

[0056] In the above S107, when the second information is consistent with the preset first information, it is confirmed that the first route planning matches the needs of the target user, so the first route planning is displayed to the target user through the electronic device, and the first route planning includes information such as a map, navigation instructions, and estimated time. Real-time navigation functions such as GPS tracking and voice prompts can also be provided to help users move along the planned route.

[0057] In addition, after the target user moves according to the first path planning, the path is dynamically adjusted by collecting environmental data in real time, so that the user can quickly adjust the path to avoid these risk areas during the movement. Specifically, it includes: obtaining a target image at a preset time interval, the target image is an image corresponding to the third position, and the third position is any position to be moved in the first path planning; processing the target image to obtain a target analysis result; confirming that the third position is marked as an abnormal position according to the target analysis result, and determining an alternative position according to the abnormal position; replacing the third position with an alternative position, regenerating the third path planning, and displaying the third path planning to the target user so that the target user can move based on the third path planning. Specifically, first set a time interval, which can be fixed (such as every 5 minutes) or dynamically adjusted based on certain conditions. When the preset time arrives, the image corresponding to the third position (the position to be moved to in the current path planning) is obtained by a camera or other image acquisition device installed in the smart park. The acquired image data is transmitted to the processing server or edge computing device through the network for further processing. The acquired target image is preprocessed (such as denoising, contrast enhancement, etc.), and then a specific image processing algorithm (such as target detection, image classification, etc.) is applied to identify key information in the image. Based on the results of image processing, a target analysis result is generated. This result may include information such as whether there are obstacles, crowd density, road conditions, etc. Image processing libraries (such as OpenCV, PIL) can be used for image preprocessing. Then, based on specific indicators in the target analysis results (such as the existence of obstacles, high crowd density), it is determined whether the third position is an abnormal position. If the third position is confirmed to be an abnormal position, it is necessary to select a suitable position from the preset set of candidate positions as the new mobile target. The selection of the candidate position can be based on a variety of factors, such as the degree of deviation from the original path, the safety of the path, the efficiency, etc. Graph theory algorithms (such as Dijkstra algorithm, A* algorithm) or heuristic search algorithms can be used to find suitable candidate positions in the path planning graph. After the candidate position is determined, the third position in the original path planning is replaced with the candidate position, and the path planning algorithm is used to recalculate the optimal path from the starting point to the end point. At this time, the optimal path planning is the third path planning. The regenerated route planning is presented to the target user in an appropriate manner (such as map display, voice navigation, etc.).

[0058] Furthermore, the current path can be adjusted according to the information fed back by the target user, and the target user can be allowed to set new preference information, thereby dynamically adjusting the path, specifically including: receiving the second request corresponding to the target user; determining the third information and the fourth position according to the second request, the fourth position is the position corresponding to the target user at the target time point, the target time point is the time point corresponding to the target user sending the second request, and the third information is the road information; inputting the fourth position and the third information into the preset path database for query to obtain the fourth path planning; and displaying the fourth path planning to the target user. Specifically, the target user sends the second request to the server through a mobile device, a web page or an application. This request may include the user's identity information (such as user ID, session token, etc.) and the request type (such as a path planning request). The second request is then parsed to obtain the third information and the fourth position, at which point the third information is the road information, and the road information may include the slope of the road, stairs, congestion, construction information, and accident information. When receiving the second request sent by the target user, the target time point is determined, and then the location of the target user at the target time point in the smart park, i.e., the fourth position, is obtained based on the positioning information (such as GPS coordinates) of the user device. The determined fourth position and the third information (road information) are input as query parameters into the preset path database. The path database may contain the calculation results of multiple path planning algorithms, as well as a dynamic adjustment mechanism based on real-time traffic information. The third information and the fourth position are input into the preset path database for query to generate a fourth path plan, and the queried fourth path plan is converted into a format suitable for user viewing (such as a line on a map, a step-by-step description in a list format, etc.). The path plan is displayed to the user through the user's mobile device, web page, or application user interface. This may involve multiple display methods such as map rendering, text display, and voice navigation.

[0059] In a possible implementation, in addition to determining the first path planning by the first position and the first information, the corresponding path planning can also be generated based on the terminal position selected by the target user, specifically including: obtaining the second position sent by the target user, the second position being any position in the smart park except the first position; inputting the first position and the second position into the preset path database for query to obtain the second path planning; judging whether the second information is consistent with the preset second information, the preset second information is the information corresponding to the second path planning; when the second information is consistent with the preset second information, it is confirmed that the second path planning is displayed to the target user. Specifically, the target user can select the corresponding second position on the smart park map displayed on the mobile device, and the second position can be understood as the terminal that the target user needs to reach. Then the first position and the second position are input into the preset path database for query to obtain the second path planning, and the second path planning represents the set of all paths that meet the requirements of starting from the first position and reaching the second position. The preset path database is a database that stores various path planning information in the smart park. These path planning may be pre-calculated and stored based on different standards (such as the shortest path, the safest path, the most beautiful path, etc.). The first position (i.e., the user's starting position) and the second position (i.e., the user's target position) are input as query parameters into the path database, and the database retrieves and returns the corresponding path plan according to these parameters. If the second path plan set includes multiple paths, the multiple paths can be calculated in the above manner to reach the adaptive heuristic score corresponding to each path, and the adaptive heuristic scores can be sorted to reach the sorting result, and then the second heuristic score is obtained from the sorting result. The corresponding path plan is determined according to the second heuristic score, and the preset second information corresponding to the path plan is obtained, and then the second information is compared with the preset second information. If the second path plan set includes only one path, the preset second information corresponding to the second path plan can be directly obtained, and then the simplified second information is compared with the preset second information. The second information here is the preference information sent by the target user in the previous step, that is, the user's safety score and efficiency score for the path plan. The preset second information is the relevant information of the newly queried second path plan. Once it is confirmed that the second information is consistent with the preset second information, the second path plan is presented to the user in an appropriate manner. The display method may include displaying a path map on the screen of the mobile device and providing voice navigation prompts.

[0060] The above method can plan the optimal path in the smart park in real time and efficiently based on the preference information and location information sent by the user to meet the personalized needs of users in complex and changing environments. In the path planning, it can also accept environmental changes and user feedback, and dynamically adjust the path according to this information. It can quickly adjust the path to avoid risk areas, ensuring that the path planning recommended to users meets the personalized needs of users.

[0061] The present application also provides a path planning device based on adaptive heuristics, Figure 2 is a schematic diagram of a path planning device based on adaptive heuristics provided in an embodiment of the present application, with reference to Figure 2 The device is a server, and the server includes an acquisition unit 201, a processing unit 202 and a display unit 203.

[0062] The acquisition unit 201 receives a first request sent by a target user; acquires a first heuristic score from a plurality of adaptive heuristic scores, and determines a first path plan according to the first heuristic score; and acquires second information sent by the target user.

[0063] The processing unit 202 determines a first position and first information according to a first request, wherein the first information includes movement distance information, movement duration information, and calorie consumption information, and the first position is the position of the target user in the smart park; the first position and the first information are input into a preset path database for query to obtain multiple path plans; each path plan is calculated to obtain multiple adaptive heuristic scores; and it is determined whether the second information is consistent with the preset first information, wherein the preset first information is the information corresponding to the first path plan.

[0064] The display unit 203 confirms to display the first path planning to the target user when the second information is consistent with the preset first information, so that the target user can move according to the first path planning. In a possible implementation, the processing unit 202 is used to sort multiple adaptive heuristic scores according to a preset rule to obtain a target sorting result, and the preset rule is a priority queue rule; the acquisition unit 201 is used to obtain a first heuristic score from the target sorting result, and determine a first path plan corresponding to the first heuristic score, and the first heuristic evaluation is the heuristic score corresponding to the first place in the target sorting result.

[0065] In a possible implementation, the acquisition unit 201 is used to acquire multiple first target scores corresponding to the first path planning, the multiple first target scores include terrain complexity assessment, camera coverage score, obstacle density score, pedestrian flow score, vegetation coverage score and air quality score; the processing unit 202 is used to perform weighted summation on the multiple first target scores to obtain a first safety score; the acquisition unit 201 is used to acquire multiple second target scores corresponding to the first path planning, the multiple second target scores include path length score, expected running time score, energy consumption score, terrain score and congestion score; the processing unit 202 is used to perform weighted summation on the multiple second target scores to obtain a first efficiency score; and output the first safety score and the first efficiency score as preset first information.

[0066] In one possible implementation, the acquisition unit 201 is used to acquire a second safety score and a second efficiency score from the second information; the processing unit 202 is used to determine whether the first safety score is greater than or equal to the second safety score, and whether the first efficiency score is greater than or equal to the second efficiency score; when the first safety score is greater than or equal to the second safety score, and the first efficiency score is greater than or equal to the second efficiency score, it is confirmed that the first path planning is recommended to the target user.

[0067] In a possible implementation, the acquisition unit 201 is used to acquire a second location sent by a target user, where the second location is any location in the smart park except the first location; the processing unit 202 is used to input the first location and the second location into a preset path database for query to obtain a second path plan; it is determined whether the second information is consistent with the preset second information, where the preset second information is the information corresponding to the second path plan; the display unit 203 is used to confirm that the second path plan will be displayed to the target user when the second information is consistent with the preset second information.

[0068] In a possible implementation, the acquisition unit 201 is used to acquire a target image at a preset time interval, where the target image is an image corresponding to a third position, and the third position is any position to be moved in the first path planning; the processing unit 202 is used to process the target image to obtain a target analysis result; based on the target analysis result, the third position is marked as an abnormal position, and an alternative position is determined based on the abnormal position; the display unit 203 is used to replace the third position with an alternative position, regenerate a third path planning, and display the third path planning to the target user so that the target user can move based on the third path planning.

[0069] In a possible implementation, the acquisition unit 201 is used to receive a second request corresponding to a target user; the processing unit 202 is used to determine third information and a fourth position based on the second request, the fourth position being the position of the target user corresponding to a target time point, the target time point being the time point corresponding to the target user sending the second request, and the third information being road information; the fourth position and the third information are input into a preset path database for query to obtain a fourth path plan; the display unit 203 is used to display the fourth path plan to the target user.

[0070] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0071] The present application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 305 , and at least one communication bus 302 .

[0072] The communication bus 302 is used to realize the connection and communication between these components.

[0073] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0074] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0075] Among them, the processor 301 may include one or more processing cores. The processor 301 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 305, and calling data stored in the memory 305. Optionally, the processor 301 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 301 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application requests; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 301, and it can be implemented separately through a chip.

[0076] Among them, the memory 305 may include a random access memory (RAM) or a read-only memory (Read-Only Memory). Optionally, the memory 305 includes a non-transitory computer-readable storage medium. The memory 305 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 305 may include a program storage area and a data storage area, wherein the program storage area. Instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc. can be stored; the data storage area can store data involved in the above-mentioned various method embodiments, etc. The memory 305 can also be optionally at least one storage device located away from the aforementioned processor 301.

[0077] like Figure 3 As shown, the memory 305 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application for adaptive heuristic path planning.

[0078] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application for adaptive heuristic path planning stored in the memory 305. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0079] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all described as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the order of the actions described, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0080] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0081] In the several embodiments provided in the present application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0082] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0083] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0084] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0085] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, it will be easy for those skilled in the art to think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field that are not recorded in the present disclosure.

Claims

1. A path planning method based on adaptive heuristics, characterized in that: Applied in a server, the method comprises: receiving a first request sent by a target user; Determine a first location and first information according to the first request, where the first information includes exercise distance information, exercise duration information, and calorie consumption information, and the first location is the location of the target user in the smart park; Inputting the first position and the first information into a preset path database for query to obtain multiple path plans; Calculating each of the path plans to obtain a plurality of adaptive heuristic scores; Obtaining a first heuristic score from the plurality of adaptive heuristic scores, and determining a first path plan according to the first heuristic score; Acquire second information sent by the target user, and determine whether the second information is consistent with preset first information, where the preset first information is information corresponding to the first path planning; When the second information is consistent with the preset first information, it is confirmed that the first path planning is displayed to the target user so that the target user can move according to the first path planning.

2. The method according to claim 1, characterized in that The step of obtaining a first heuristic score from the plurality of adaptive heuristic scores and determining a first path plan according to the first heuristic score specifically includes: Sorting the plurality of adaptive heuristic scores according to a preset rule to obtain a target sorting result, wherein the preset rule is a priority queue rule; The first heuristic score is obtained from the target ranking result, and the first path plan corresponding to the first heuristic score is determined, wherein the first heuristic evaluation is the heuristic score corresponding to the first position in the target ranking result.

3. The method according to claim 1, characterized in that: Before determining whether the second information is consistent with the preset first information, the method further includes: Obtaining multiple first target scores corresponding to the first path planning, the multiple first target scores including terrain complexity assessment, camera coverage score, obstacle density score, pedestrian flow score, vegetation coverage score, and air quality score; Performing a weighted summation on the plurality of first target scores to obtain a first safety score; Acquire multiple second target scores corresponding to the first path planning, the multiple second target scores including a path length score, an estimated running time score, an energy consumption score, a terrain score, and a congestion level score; Taking a weighted sum of the plurality of second target scores to obtain a first efficiency score; The first safety score and the first efficiency score are output as the preset first information.

4. The method according to claim 3, characterized in that The determining whether the second information is consistent with the preset first information specifically includes: Obtaining a second safety score and a second efficiency score from the second information; Determining whether the first safety score is greater than or equal to the second safety score, and whether the first efficiency score is greater than or equal to the second efficiency score; When the first safety score is greater than or equal to the second safety score, and the first efficiency score is greater than or equal to the second efficiency score, it is confirmed that the first path planning is recommended to the target user.

5. The method according to claim 1, characterized in that After determining the first position and the first information according to the first request, wherein the first information includes movement distance information, movement duration information, and calorie consumption information, the method further includes: Acquire a second location sent by the target user, where the second location is any location in the smart park except the first location; Inputting the first position and the second position into the preset path database for query to obtain a second path plan; Determine whether the second information is consistent with preset second information, where the preset second information is information corresponding to the second path planning; When the second information is consistent with the preset second information, it is confirmed that the second path planning is displayed to the target user.

6. The method according to claim 1, characterized in that After confirming that the first path planning is to be displayed to the target user when the second information is consistent with the preset first information so that the target user can move according to the first path planning, the method further includes: At preset intervals, a target image is acquired, where the target image is an image corresponding to a third position, and the third position is any position to be moved in the first path planning; Processing the target image to obtain a target analysis result; Confirming that the third position is marked as an abnormal position according to the target analysis result, and determining an alternative position according to the abnormal position; The third position is replaced by the alternative position, a third path plan is regenerated, and the third path plan is displayed to the target user so that the target user moves based on the third path plan.

7. The method according to claim 6, characterized in that Before acquiring the target image at the preset time interval, the method further includes: receiving a second request corresponding to the target user; determining third information and a fourth position according to the second request, the fourth position being a position of the target user at a target time point, the target time point being a time point corresponding to when the target user sends the second request, and the third information being road information; Inputting the fourth position and the third information into the preset path database for query to obtain a fourth path plan; The fourth path planning is displayed to the target user.

8. A path planning device based on adaptive heuristics, characterized in that: The device is a server, and the server comprises an acquisition unit (201), a processing unit (202) and a display unit (203); The acquisition unit (201) receives a first request sent by a target user; acquires a first heuristic score from a plurality of adaptive heuristic scores, and determines a first path plan according to the first heuristic score; acquires second information sent by the target user, The processing unit (202) determines a first position and first information according to the first request, the first information including movement distance information, movement duration information and calorie consumption information, the first position being the position of the target user in the smart park; inputs the first position and the first information into a preset path database for query to obtain a plurality of path plans; calculates each of the path plans to obtain a plurality of adaptive heuristic scores; and determines whether the second information is consistent with the preset first information, the preset first information being information corresponding to the first path plan; The display unit (203) confirms that the first path planning is to be displayed to the target user when the second information is consistent with the preset first information, so that the target user can move according to the first path planning.

9. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (305), a user interface (303) and a network interface (304), wherein the memory (305) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (305) so that the electronic device (300) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is executed.

Images