Guide navigation method based on fusion of guide route and road network

Abstract

The invention relates to the technical field of path guidance, in particular to a tour guide navigation method based on fusion of a tour guide route and a road network, and the method comprises the following steps: connecting a plurality of user terminals in the same tour group, collecting tour coordinates, constructing a road network, and analyzing the influence of road network nodes and road network edges to optimize a tour guide network; a starting point is configured according to the real-time position and progress of a user, a guide optimization model is established, multidirectional guide tracking iteration is carried out, a multidirectional balance guide route set is obtained, and route navigation guidance is carried out, so that the technical problems that a scenic spot guide mode is mainly based on a fixed route, the dynamic response capability to tourist demands is lacked, and the utilization rate of scenic spot resources is low are solved; the guiding route is dynamically planned through influence analysis of the road network nodes and the road network edges, the utilization rate of scenic spot resources is improved, tourist flow distribution optimization is achieved, and meanwhile the guiding efficiency is optimized and the touring experience is improved through multidirectional guiding tracking iteration under the time balance constraint.

Description

Technical Field

[0001] The present invention relates to the technical field related to path guidance, and in particular to a navigation method based on the fusion of a navigation route and a road network. Background Art

[0002] With the rapid development of tourism and the continuous improvement of tourists' demands, conventional scenic spot guided tours can no longer meet the diverse needs of modern tourists. Conventional guided tour services rely on manual explanations or electronic equipment with fixed routes, and the actual needs of tourists are difficult to be fully met. In addition, in some large scenic spots, nature reserves or cultural relics, due to the wide distribution of scenic spots, the large number of tourists and their high mobility, some scenic spots are crowded with tourists, while other scenic spot resources are idle, and the utilization rate of scenic spot resources is low, which affects the tourists' tour experience and the efficiency of scenic spot operations.

[0003] In summary, the existing technology has technical problems that the scenic spot guidance method mainly uses fixed routes, lacks the ability to dynamically respond to tourists' needs, and has low utilization rate of scenic spot resources. Summary of the invention

[0004] This application provides a guide navigation method based on the integration of guide routes and road networks, aiming to solve the technical problems in the existing technology that the scenic spot guidance method is mainly based on fixed routes, lacks the ability to dynamically respond to tourists' needs, and has low utilization rate of scenic spot resources.

[0005] In view of the above problems, the technical solution to implement this application is:

[0006] The present application provides a tour navigation method based on the fusion of tour routes and road networks, wherein the method comprises: connecting multiple user terminals in the same tour group, collecting multiple basic tour coordinates, wherein the multiple basic tour coordinates have tour item tags; uploading the internal tour network of the multiple basic tour coordinates based on the multiple basic tour coordinates, and formulating multiple basic tour routes, wherein each basic tour route is connected to the multiple basic tour coordinates; analyzing the road network nodes and the influence of the road network nodes on the distribution of tourist flow according to the internal tour network of the multiple basic tour coordinates, obtaining a type of influence assessment combination, and performing a tourist behavior pattern correlation analysis according to the type of influence assessment combination, and establishing a first tour optimization network using the first behavior pattern correlation analysis result; and The internal navigation road network of the tour coordinates is analyzed, and the influence of the road network edge and the road network edge on the efficiency of the tour route is analyzed to obtain two types of impact assessment combinations, and the tourist behavior pattern association analysis is performed according to the two types of impact assessment combinations, and the second behavior pattern association analysis result is used to establish a second navigation optimization network; the navigation starting point is configured according to the real-time location information and tour progress of multiple user terminals in the same tour group, and a navigation optimization model is established according to the first navigation optimization network and the second navigation optimization network; based on the navigation optimization model, in combination with the navigation starting point and the navigation demand corresponding to any one of the multiple user terminals in the same tour group, a multi-directional navigation tracking iteration under the time balance constraint is performed to obtain a multi-directional balanced navigation route set, and route navigation guidance is performed.

[0007] In summary, one or more technical solutions provided in this application solve the technical problems that the scenic area guidance method is mainly based on fixed routes, lacks the ability to dynamically respond to tourists' needs, and has low utilization rate of scenic spot resources. Through the impact analysis of road network nodes and road network edges, the guidance routes are dynamically planned to improve the utilization rate of scenic spot resources, and the optimization of tourist flow distribution is achieved. At the same time, through multi-guide tracking iterations under time balance constraints, the guidance efficiency is optimized and the technical effect of improving the tour experience is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] Figure 1 A flowchart of a navigation method based on the fusion of navigation routes and road networks is provided for this application;

[0009] Figure 2 A schematic flow chart of one-way navigation locking in a navigation method based on the fusion of navigation routes and road networks is provided for this application. DETAILED DESCRIPTION

[0010] Example

[0011] The present application is described in detail below with reference to the accompanying drawings. Figure 1As shown, the present application provides a navigation method based on the fusion of navigation route and road network, wherein the method comprises:

[0012] S1: connecting multiple user terminals in the same tour group, collecting multiple basic tour coordinates, wherein the multiple basic tour coordinates have tour item tags.

[0013] Specifically, the user end refers to the smart device used by tourists, such as a smartphone or a dedicated guide device, which can receive and send data; the basic tour coordinates refer to the specific location information of each important scenic spot in the scenic area. These coordinate points are marked for easy identification and navigation; the tour item mark refers to the identifier associated with the basic tour coordinates, such as the name, number or other descriptive information of the scenic spot, which is used for quick identification and positioning. Furthermore, each tourist’s mobile phone is installed with a guide application. When tourists in a tour group enter the scenic area, the application automatically connects to the mobile phones of other tourists via Bluetooth or Wi-Fi, and starts collecting the location coordinates of each scenic spot, such as attraction A, attraction B, etc. These coordinate points are accompanied by tour item marks, including skiing, movie watching, etc.

[0014] Connecting multiple users in the same tour group can be achieved through wireless network technologies such as Wi-Fi or Bluetooth to ensure that all users can communicate and exchange data in real time. Subsequently, the basic tour coordinates provided by each user are collected. These coordinate points include tour item marks, so that each coordinate point can be uniquely identified, providing the necessary location data for subsequent route planning and optimization.

[0015] S2: Based on the multiple basic tour coordinates, an internal guide road network of the multiple basic tour coordinates is uploaded to plan multiple basic guide routes, each of which connects the multiple basic tour coordinates.

[0016] Specifically, the internal guide road network refers to the path network used for guidance within the scenic area, including roads and trails connecting various scenic spots; the basic guide routes are routes connecting multiple basic tour coordinates designed based on the internal guide road network. These routes provide tourists with basic navigation from one point to another. Furthermore, according to the collected coordinate points of scenic spots A, scenic spot B, etc., the corresponding internal guide road network data is uploaded. After analyzing these data, multiple basic guide routes can be formulated, such as the "scenic spot entrance-scenic spot A-scenic spot B-scenic spot exit" route. Each route ensures that tourists can navigate smoothly from the previous scenic spot to the next one. These basic routes will serve as the basis for subsequent dynamic optimization and personalized adjustment.

[0017] After collecting the basic tour coordinates, upload the internal guide road network data corresponding to these coordinates. This data includes information such as road connectivity, direction, and length. Based on this data, plan multiple basic guide routes. Each route connects multiple basic tour coordinates to provide tourists with a basic navigation path from the starting point to the end point, and provide tourists with preliminary guide route options. These routes will serve as the basis for subsequent optimization.

[0018] S3: Analyze the road network nodes and the impact of the road network nodes on the distribution of tourist flow according to the internal guide road network of the multiple basic tour coordinates, obtain a type of impact assessment combination, and perform a tourist behavior pattern correlation analysis based on the type of impact assessment combination, and use the first behavior pattern correlation analysis result to establish a first guide optimization network.

[0019] Specifically, road network nodes refer to key points in the internal guide road network of the scenic area, such as intersections, scenic spot entrances, etc.; one type of impact assessment combination is based on the assessment results of the impact of road network nodes on the distribution of tourist flow. Furthermore, through analysis, it is found that the entrance of scenic spot A is a key node, where tourist congestion often occurs. This node is used as an impact assessment point, and the behavior patterns of tourists at this node are analyzed. For example, most tourists tend to tour clockwise. Based on this information, the guided route can be optimized to guide tourists to be more evenly distributed in various attractions and reduce congestion.

[0020] Analyze the road network nodes in the internal guided road network and their impact on the distribution of tourist flow. By collecting and analyzing the behavioral data of tourists at each node, identify those nodes that have a significant impact on the distribution of tourist flow. For example, some nodes may cause tourist congestion or diversion. After obtaining a class of impact assessment combinations, further tourist behavior pattern association analysis is carried out to understand the behavioral habits and preferences of tourists at these nodes. These analysis results will be used to establish the first guided tour optimization network, aiming to optimize guided routes, reduce congestion, and improve tourists' tour experience.

[0021] The first tour guide optimization network is an optimization network established based on the results of the correlation analysis of a type of impact assessment combination and tourist behavior patterns. Furthermore, the first tour guide optimization network is established using the results of the correlation analysis of a type of impact assessment combination and tourist behavior patterns. The first tour guide optimization network comprehensively considers the impact of road network nodes on tourist flow distribution and tourists' behavioral habits, and aims to optimize the tour route, improve the tour efficiency, and improve the tourist experience. The first tour guide optimization network will adjust the route in the actual tour guide service, such as increasing or decreasing the recommendation level of certain attractions, or adjusting the opening status of attractions within a specific time period. For example, according to the congestion at the entrance of attraction A and tourists' preference for clockwise tours, the first tour guide optimization network is established. In the first tour guide optimization network, combined with the above analysis, a counterclockwise tour route is used to disperse tourist flow and reduce congestion at the entrance of attraction A. At the same time, during peak hours, tourists are recommended to visit other attractions with less traffic first to balance the distribution of tourists in the entire scenic area.

[0022] S4: Analyze the influence of the road network edge and the road network edge on the efficiency of the guided route according to the internal guided road network of the multiple basic tour coordinates, obtain two types of impact assessment combinations, and perform a tourist behavior pattern correlation analysis based on the two types of impact assessment combinations, and use the second behavior pattern correlation analysis results to establish a second guided tour optimization network.

[0023] Specifically, the road network edge refers to the path or section connecting various nodes (such as scenic spots or intersections) in the internal guide road network of the scenic area; the second type of impact assessment combination is based on the assessment results of the impact of the road network edge on the efficiency of the guide route. Furthermore, through analysis, it is found that the path connecting scenic spots A and B has slow tourist travel during a specific time period. This section is taken as an impact assessment point, and the behavior patterns of tourists on this section are analyzed. For example, most tourists tend to stop at a certain viewing point on the path; based on this information, the guide route is optimized, such as providing more rest areas near viewing points to reduce congestion on the guide route and improve the guide efficiency.

[0024] Analyze the road network edges in the internal guided road network and their impact on the efficiency of the guided route. By collecting and analyzing the movement data of tourists on each road section, identify those sections that have a significant impact on the efficiency of the guided route. For example, some sections may cause delays or congestion in tourists' travel. After obtaining the second type of impact assessment combination, further correlation analysis of tourist behavior patterns is carried out to understand the behavioral habits and preferences of tourists on these sections. These analysis results will be used to establish a second guided tour optimization network, aiming to optimize the guided route, improve the guide efficiency, and improve the tourist experience.

[0025] The second tour guide optimization network is an optimization network established based on the results of the correlation analysis of the two types of impact assessment combinations and tourist behavior patterns. Furthermore, the second tour guide optimization network is established using the results of the correlation analysis of the two types of impact assessment combinations and tourist behavior patterns. The second tour guide optimization network comprehensively considers the impact of road network edges on the efficiency of tour guide routes and tourists' behavioral habits, aiming to optimize tour guide routes, improve tour guide efficiency, and improve tourist experience. The second tour guide optimization network will adjust routes in actual tour guide services, such as increasing or decreasing the recommendation level of certain routes, or adjusting the open status of routes within a specific time period. For example, a second tour guide optimization network is established based on the congestion of the path connecting scenic spots A and scenic spots B and tourists' stay preferences. Combined with the above analysis, in the second tour guide optimization network, more alternative routes are recommended to disperse tourist flow and reduce congestion on main paths. At the same time, tourists are recommended to use fast lanes during peak hours to improve the efficiency of tour routes.

[0026] S5: configuring a tour navigation starting point according to the real-time location information and tour progress of multiple users in the same tour group, and establishing a tour optimization model according to the first tour optimization network and the second tour optimization network.

[0027] Specifically, real-time location information refers to data about the user's current location provided in real time by the user end; tour progress refers to the progress of the user during the tour, including the attractions visited and the estimated tour time; the starting point of the tour navigation refers to the starting point of the tour service determined according to the user's real-time location and tour progress. The tour optimization model is used to optimize the tour route according to the first tour optimization network and the second tour optimization network. Furthermore, the real-time location information and tour progress are collected. If it is found that most tourists have visited attraction A and are heading to attraction B, attraction B is set as the new starting point of the tour navigation for subsequent tour route planning and optimization. For example, during peak hours, it is recommended that tourists first visit other attractions with less traffic, and then visit popular attractions when there are fewer people, so as to balance the distribution of tourists in the entire scenic area and improve the tour efficiency.

[0028] By collecting the real-time location information and tour progress of multiple users in the same tour group to configure the starting point of the guided navigation, it means that the starting point of the guided tour service can be dynamically adjusted according to the actual location and tour situation of the tourists, ensuring that the guided tour service can be dynamically adjusted according to the actual location and tour situation of the tourists, and providing more personalized and flexible guided tour services; in this way, more personalized and flexible guided tour services are provided to ensure that the guided tour route can meet the actual needs and preferences of the tourists, thereby improving the responsiveness and adaptability of the guided tour service to adapt to the tour rhythm of different tourists; a comprehensive guided tour optimization model is established based on the first guided tour optimization network (focusing on the optimization of tourist flow distribution) and the second guided tour optimization network (focusing on the optimization of guided tour route efficiency). The guided tour optimization model will be used for subsequent guided tour route planning and optimization to ensure that the guided tour service is both efficient and meets the actual needs of tourists, providing users with more efficient and personalized guided tour services.

[0029] S6: Based on the navigation optimization model, in combination with the navigation starting point and navigation requirements corresponding to any one of the multiple user terminals in the same tour group, multi-directional navigation tracking iterations are performed under time balance constraints to obtain a multi-directional balanced navigation route set and perform route navigation guidance.

[0030] Specifically, multi-directional guided tour tracking iteration refers to the process of performing multiple iterative calculations to optimize the guided route based on the starting point and needs of the user under the constraint of time balance; the multi-directional balanced guided route set is a set of optimal guided routes obtained through iterative calculations, which comprehensively considers factors such as time, efficiency, and tourist flow; route navigation guidance provides users with real-time navigation instructions based on the optimized guided route.

[0031] Based on the guide optimization model, combined with the guide navigation starting point and needs of any user in the same tour group, multi-guide tracking iterations are performed under the time balance constraint, involving real-time analysis of user location, tour progress and guide needs, and combined with the preset time window, the guide route is optimized through iterative calculation to obtain a set of multi-directional balanced guide route sets. These route sets comprehensively consider factors such as time, efficiency and tourist flow to provide the best guide service; real-time navigation guidance is carried out according to these optimized routes to ensure that tourists can smoothly tour along the established route and improve the tour efficiency and experience.

[0032] In combination with the above example, according to the tour guide optimization model and each tourist's real-time location (such as starting from attraction B) and sightseeing needs (such as hoping to visit all the main attractions within two hours), multi-directional tour tracking iterations are performed; each tourist's sightseeing time window is considered, such as the planned stay time in the Forbidden City, and the tour guide navigation needs, such as attractions of special interest; through iterative calculation, a set of balanced tour routes is obtained, and the multi-directional balanced tour route set takes into account both the personal interests of tourists and the tourist flow and route efficiency; navigation guidance is carried out according to these routes to achieve orderly diversion of tourists to avoid congestion, thereby improving the tourists' sightseeing experience on the basis of improving the efficiency of the tour guide service.

[0033] Furthermore, based on the navigation optimization model, combined with the navigation starting point and navigation requirements corresponding to any one of the multiple user terminals in the same tour group, multiple navigation tracking iterations are performed under time balance constraints. The method of the present application includes:

[0034] S61: Collecting historical tour records of any one of multiple user terminals in the same tour group; S62: Identifying tour points of interest through the historical tour records; S63: Adding a matching score to each alternative route in the iterative process of guided tracking based on the tour points of interest.

[0035] Specifically, historical tour records refer to the data records generated by users during their past tours, including the attractions visited, length of stay, and tour routes; tour points of interest refer to the attractions or areas in which users show special interest or preference during their tours; matching scores refer to the process by which the system scores alternative routes based on the user's points of interest and tour needs to determine which routes are more in line with the user's interests and needs.

[0036] Collect the historical tour records of any user in the same tour group, including the attractions visited by the user in the past, the length of stay at each attraction, and their tour routes; identify the user's tour points of interest by analyzing these historical data, that is, the attractions where the user spends more time or visits frequently; after identifying the tour points of interest, add a matching score to each alternative route during the guided tracking iteration process based on these points of interest, evaluate the degree of matching between each route and the user's points of interest, and give a score accordingly; the matching score is used to determine the route that best meets the user's personalized needs, in this way, provide a more personalized and optimized guided service.

[0037] If the historical tour records show that the user has visited natural landscape attractions many times in previous tours and spent a long time in each tour, by analyzing the user's historical tour records, it is identified that natural landscape attractions are the user's tour interests. When planning a guided route for the user starting from attraction A, the user's interest in natural landscape attractions will be taken into consideration, and the routes including natural landscape attractions will be given a higher matching score. Furthermore, if the user's planned time is limited, routes that can cover the user's most interesting attractions can be recommended based on the user's tour interests and time constraints. In this way, not only the efficiency of the guided service can be improved, but also the user's tour experience can be enhanced.

[0038] Furthermore, according to the tourist points of interest, a matching score is added to each alternative route during the iterative process of the guided tracking. The method of the present application includes:

[0039] S631: Based on the historical tour records, a tour information database is constructed, and the tour information database is used to store historical tour tracks and historical stay times; S632: Through the tour information database, potential points of interest are mined in combination with social network information; S633: The tour points of interest and potential points of interest are graded and a matching evaluation strategy is formulated.

[0040] Specifically, the tour information database refers to the storage medium used to store the user's historical tour data, including tour tracks and the length of stay at various attractions. The historical tour track is a record of the path that the user has taken during past tours. The historical stay time is a record of the length of time the user stayed at each attraction.

[0041] The user's historical tour data, including the order of visiting attractions and the length of stay at each attraction, are stored in a tour information database in order to analyze the user's tour habits. For example, it is found that the user's stay at natural landscape attractions is always longer than that at other attractions, indicating that the user has a special interest in natural landscape attractions. A tour information database is constructed based on the collected historical tour records. This database not only stores the user's historical tour trajectory and the length of stay at each attraction, but also serves as the basis for analyzing and mining the user's tour behavior. Through this database, we can gain an in-depth understanding of the user's tour habits and preferences, providing data support for subsequent guided tour services.

[0042] Social network information refers to posts, comments, photos and other information about travel experiences shared by users on social networks; potential points of interest are new attractions or areas that users may be interested in, which are mined by analyzing historical travel records and social network information; after establishing a travel information database, potential points of interest are mined through this database combined with social network information. Social network information can provide users with emotional feedback and recommendations on attractions, which is helpful for discovering new attractions that users may be interested in; through social network information, users' shares and comments on social networks are mined, and it is found that users have shown great interest in calligraphy and painting exhibitions. As potential points of interest, when planning guided routes, routes containing natural landscape attractions will be given priority, and these routes will be given higher matching scores. At the same time, routes containing calligraphy and painting exhibitions will also be considered, especially when users' travel time permits. In this way, new attractions that users may like can be predicted and recommended, thereby enriching users' travel experience.

[0043] Grading refers to classifying points of interest into different grades according to the user's interest in each point of interest; the matching evaluation strategy is an evaluation system used to evaluate the degree of match between alternative routes and user points of interest and to score them accordingly; after identifying tourist points of interest and potential points of interest, these points are graded and a matching evaluation strategy is formulated; grading can help the system sort scenic spots according to the user's interest, while the matching evaluation strategy is used to evaluate the degree of match between alternative routes and user points of interest; through this evaluation, each alternative route can be scored, so that the route that best meets the user's interests and needs can be selected.

[0044] Further, according to the internal guide road network of the plurality of basic tour coordinates, the road network nodes and the influence of the road network nodes on the distribution of tourist flow are analyzed to obtain a type of impact assessment combination. The application method includes:

[0045] S31: Collect tourist flow data of each scenic spot through Internet of Things devices; S32: Based on the tourist flow data of each scenic spot, identify the peak and low periods of tourist flow and the trend of tourist flow, and draw up a tourist flow distribution map; S33: According to the internal guide road network of the multiple basic tour coordinates, combined with the degree of influence of the tourist flow distribution map, determine the impact assessment information, the impact assessment information includes the node congestion degree and the waiting time of tourists; S34: According to the internal guide road network of the multiple basic tour coordinates, combined with the impact assessment information, traverse the road network nodes to obtain a type of impact assessment combination.

[0046] Specifically, IoT devices refer to smart devices deployed in scenic spots for collecting data, such as sensors, cameras, etc.; tourist flow data refers to data on the number and distribution of tourists collected at various scenic spots; tourist flow distribution maps are used to display the distribution of tourist flow at different times and in different scenic spots; the aforementioned type of impact assessment combination is a combination formed by the evaluation results of optimizing road network nodes based on impact assessment information, wherein impact assessment information refers to information obtained by evaluating the degree of impact of tourist flow distribution on guided routes and road network nodes, such as node congestion levels and tourist waiting time.

[0047] By deploying IoT devices in the scenic area, we collect tourist flow data of each scenic spot, including the number of tourists, the time of entering and exiting the scenic spot, etc. By analyzing these data, we can identify the peak and trough periods of tourist flow, as well as the flow trends of tourists, and provide real-time data support for subsequent tourist flow management and guided route optimization. After collecting the tourist flow data of each scenic spot, we identify the peak periods, trough periods and tourist flow trends based on these data, and draw up a tourist flow distribution map. The tourist flow distribution map can intuitively show the distribution of tourists in the scenic area, better understand tourist behavior, and conduct flow management and guided route optimization accordingly.

[0048] After drawing up a tourist flow distribution map, the impact assessment information is determined based on the tourist flow distribution map and the internal guided road network, including the congestion level of each road network node and the waiting time of tourists. The congestion level of each road network node and the waiting time of tourists provide support for evaluating the efficiency of the guided route and the tourists' sightseeing experience, and then identify those guided routes and road network nodes that need to be optimized so as to propose improvement measures. After determining the impact assessment information, each node of the internal guided road network is traversed in combination with this information to obtain a type of impact assessment combination. A type of impact assessment combination contains optimization suggestions for each road network node, such as measures to reduce congestion and optimize the waiting time of tourists. Its role is to provide specific improvement plans for guided route optimization to improve guided efficiency and tourist satisfaction.

[0049] Furthermore, the present application method also includes:

[0050] Utilize GIS technology and remote sensing data to evaluate the ecological environment of the nature reserve and identify sensitive areas; based on the sensitive areas, screen the alternative routes of the first time window in combination with the preset safety distance, and incorporate the alternative screened routes of the first time window into the guide optimization model.

[0051] Specifically, GIS technology refers to geographic information system technology, which is used to capture, store, analyze and manage geospatial data; remote sensing data is data obtained through remote sensing technologies such as satellites or aerial photography, and is used to monitor and evaluate the environment; ecological environmental assessment refers to the analysis and evaluation of the natural environment conditions of nature reserves to understand ecological health and changes; sensitive areas refer to areas where the ecological environment is fragile or has special protection value.

[0052] GIS technology and remote sensing data are used to evaluate the ecological environment of nature reserves. By analyzing these data, sensitive areas in the ecological environment can be identified. These areas may need special protection due to ecological fragility, rich biodiversity or special scientific research value. The purpose of the above steps is to ensure that the guided tour service will not have a negative impact on the ecological environment of the nature reserve, and also provide a basis for ecological protection for subsequent route planning. For example, when planning a guided tour route in a nature reserve near scenic spot A, GIS technology and remote sensing data analysis show that a certain area is an important habitat for migratory birds. This area is marked as a sensitive area and taken into consideration in subsequent guided tour route planning.

[0053] The preset safety distance refers to the distance within a certain range set to protect sensitive areas that cannot be entered or approached, such as no entry within 100 meters around the habitat of migratory birds; the first time window refers to the time range for route planning and optimization determined according to tourist flow and environmental conditions within a specific time period; the alternative screening route is the alternative route that meets the ecological protection requirements screened out according to the preset safety distance within the first time window; after identifying sensitive areas, the alternative routes within the first time window are screened based on these areas and the preset safety distance, which means that the system will exclude routes that are too close to sensitive areas to reduce the impact on the ecological environment. The screened alternative routes will be included in the guide optimization model, which will comprehensively consider factors such as ecological protection, tourist flow and guide efficiency to optimize the final guide route.

[0054] Furthermore, the alternative screening routes of the first time window are incorporated into the navigation optimization model, and the method of the present application further includes:

[0055] Based on the alternative screening routes of the first time window, the first negative impact on the sensitive area is evaluated in combination with the preset safety distance; according to the preset safety distance and the first negative impact, the remaining screening routes are adjusted to avoid the sensitive area as a limiting condition, and the alternative adjustment routes of the first time window are determined; a second time window is set, and in the overlapping part between the second time window and the first time window, the alternative adjustment routes of the first time window are incorporated into the navigation optimization model.

[0056] Specifically, the first negative impact refers to the adverse impact that the alternative screening route may have on sensitive areas within the first time window, such as interference with wild animals, destruction of vegetation, etc.; the alternative adjustment route refers to the new route that is adjusted from the original alternative route after taking into account sensitive areas and the first negative impact; the second time window refers to another time range for route planning and optimization determined within different time periods based on environmental conditions and changes in tourist flow.

[0057] Based on the alternative screening routes and preset safety distances in the first time window, evaluate the first negative impact that these routes may have on sensitive areas. The purpose of the evaluation is to quantify and identify the potential risks of the routes to the environment so that measures can be taken to reduce these impacts in subsequent route planning. Its role is to ensure that the guided route planning not only takes into account the tourists' tour experience, but also takes into account the needs of ecological protection. Further combined with the above examples, evaluate the possible impact of alternative routes around the area with a preset safety distance as the radius on the breeding of migratory birds, such as noise interference, and determine the first negative impact of these routes accordingly.

[0058] After evaluating the first negative impact, the remaining routes will be adjusted according to the preset safety distance and these impacts. The purpose of the adjustment is to avoid sensitive areas and reduce interference with the ecological environment. The alternative adjustment routes for the first time window will be determined. These routes not only meet the sightseeing needs but also meet the requirements of ecological protection. After determining the alternative adjustment routes for the first time window, these routes will be included in the guide optimization model. Subsequently, the second time window will be set, and the overlapping part between the second time window and the first time window will be found. These alternative adjustment routes will be included in the model. The purpose is to provide flexible guide services in different time periods, while ensuring that route planning can adapt to changes in the environment and tourist flow.

[0059] For example, if the system finds that some alternative routes are too close to the breeding grounds of migratory birds and may cause noise interference, these routes will be adjusted to move away from the breeding grounds, or the use of these routes will be restricted during specific time periods to reduce the impact on migratory birds. For example, morning and evening are the times when migratory birds are most active. Morning and evening are set as sensitive periods, and routes are adjusted during these periods to avoid sensitive areas. At the same time, a second time window is set during the noon period, and the routes adjusted in the morning are incorporated into the model so as to provide guided tour services during the noon period while protecting sensitive areas. In this way, adaptable and eco-friendly guided tour services can be provided during different time periods.

[0060] Furthermore, if Figure 2As shown, based on the navigation optimization model, combined with the navigation starting point and navigation requirements corresponding to any one of the multiple user terminals in the same tour group, multiple navigation tracking iterations are performed under time balance constraints. The method of the present application also includes:

[0061] S64: Establish a sliding time window mechanism, integrate the environmental change data and resource change data corresponding to the multiple basic tour coordinates, and update the open status bit marked by the tour item; S65: If the updated open status bit is 1, activate the one-way tour; S66: Traverse the open status bits associated with multiple basic tour coordinates, and activate the one-way tour multiple times.

[0062] Specifically, the sliding time window mechanism is a dynamic time management technology that is used to adjust the time range according to real-time data to adapt to changes in the environment and resources; environmental change data refers to the change data of environmental factors in the scenic area, such as weather, temperature, humidity, etc.; resource change data refers to the change data of resources in the scenic area, such as tourist flow, scenic spot maintenance status, etc.; the open status bit refers to the open status mark of the scenic spot or tour project, which is used to indicate whether the scenic spot is open to tourists; one-way tour activation refers to activating the one-way tour mode under specific conditions to optimize tourist flow management and resource protection.

[0063] A sliding time window mechanism is established to integrate and process the environmental change data and resource change data corresponding to multiple basic tour coordinates. The sliding time window mechanism allows the time window to be dynamically adjusted to adapt to the real-time changes in the environment and resources. In this way, the open status bit of the tour item mark can be updated in real time to ensure the accuracy and timeliness of the guide information; if the updated open status bit is 1, it means that the scenic spot is open, and a one-way guide will be activated, which means that the one-way guide mode will be activated according to the current tourist flow, environmental conditions and resource conditions to optimize the tourist flow management and protect the scenic area resources; the open status bits associated with multiple basic tour coordinates will be traversed, and the one-way guide will be activated multiple times, ensuring that the guide strategy can be dynamically adjusted according to real-time data in different tour coordinates and different time windows to adapt to the changing environment and tourist needs, ensuring that the tourist flow of each scenic spot in the entire scenic area is effectively managed, while protecting the resources of each scenic spot. In this way, effective guide services are provided while ensuring the safety of tourists and protecting the resources of the scenic area.

[0064] Furthermore, a sliding time window mechanism is established, and the method of the present application also includes:

[0065] S641: Based on the sliding time window mechanism, an overlapping constraint strategy is introduced, and the overlapping constraint strategy is used to adjust the overlap between the second time window and the first time window; S642: According to the overlapping constraint strategy, a smooth transition mechanism is configured, and the smooth transition mechanism is used to handle data interruption during time window switching; S643: According to the smooth transition mechanism, feedback is provided to adjust the window switching logic of the sliding time window mechanism.

[0066] Specifically, the overlapping constraint strategy is a time management strategy used to adjust the degree of overlap between different time windows to ensure data continuity; the overlap degree refers to the proportion of the overlapping parts of two time windows on the time axis; the smooth transition mechanism is a mechanism for handling data interruptions when switching time windows, ensuring the smooth operation of the system during the time window switching process.

[0067] On the basis of establishing the sliding time window mechanism, an overlapping constraint strategy is introduced to adjust the overlap between the second time window and the first time window. The purpose is to have enough data to support decision-making during the switching process of the two time windows, thereby improving the stability and reliability of the guide service. By setting the overlap reasonably, it can be ensured that there is enough data to support decision-making when the time window is switched, thereby improving the stability and reliability of the guide service. According to the overlapping constraint strategy, a smooth transition mechanism is configured to handle the data interruption that may occur during the time window switching process. By gradually adjusting the data weights in the overlapping time period, it is ensured that there will be no sudden changes or interruptions in the data when the time window is switched. The role of the smooth transition mechanism is to improve the fluency and user experience of the guide service, realize the smooth transition of data, avoid service interruption or wrong decision caused by data interruption, and ensure the continuity and stability of the guide service. According to the implementation effect of the smooth transition mechanism, feedback adjustment is carried out to optimize the window switching logic of the sliding time window mechanism. This feedback adjustment is based on the feedback of actual operation data and user experience to optimize the sliding time window mechanism. Through continuous adjustment and optimization, it can better adapt to environmental changes and user needs, continuously ensure the quality of the guide service, and improve the adaptability and efficiency of the guide service.

[0068] In summary, the beneficial effects of the embodiments of the present application are:

[0069] Connect multiple user terminals in the same tour group, collect multiple basic tour coordinates, upload the internal tour guide network, and plan multiple basic tour routes; analyze the influence of the network nodes and the network nodes on the distribution of tourist flow according to the internal tour guide network, obtain a first type of impact assessment combination, conduct a correlation analysis of tourist behavior patterns, and establish a first tour optimization network; analyze the influence of the network edges and the network edges on the efficiency of the tour routes according to the internal tour guide network, obtain a second type of impact assessment combination, conduct a correlation analysis of tourist behavior patterns, and establish a second tour optimization network; configure the tour navigation starting point through real-time location information and tour progress, and establish a tour optimization model according to the first tour optimization network and the second tour optimization network, combine the tour navigation starting point and the tour navigation demand corresponding to any one of the multiple user terminals in the same tour group to perform multi-directional tour tracking iterations under time balance constraints, obtain a multi-directional balanced tour route set, and provide route navigation guidance. Through the influence analysis of road network nodes and road network edges, the guided route is dynamically planned to improve the utilization rate of scenic spot resources and optimize the distribution of tourist flow. At the same time, through multi-guided tracking iteration under the constraint of time balance, the technical effect of optimizing the guided tour efficiency and improving the sightseeing experience is achieved.

[0070] In summary, any step can be stored as a computer instruction or program in an unlimited computer memory, and can be called and recognized by an unlimited computer processor, and no unnecessary restrictions are made here.

[0071] Furthermore, the above-mentioned technical scheme only reflects the preferred technical scheme of the technical scheme of the embodiment of the present application. Some changes that may be made to some parts thereof by technicians in this technical field all reflect the novel principles of the embodiment of the present application. Obviously, technicians in this field can make various changes and modifications to the present application without departing from the scope of the present application.

Claims

1. A navigation method based on the fusion of navigation route and road network, characterized in that: The method comprises: Connecting multiple user terminals in the same tour group to collect multiple basic tour coordinates, wherein the multiple basic tour coordinates have tour item tags; Based on the multiple basic tour coordinates, an internal tour guide network of the multiple basic tour coordinates is uploaded to formulate multiple basic tour routes, each of which is connected to the multiple basic tour coordinates; Analyze the road network nodes and the influence of the road network nodes on the distribution of tourist flow according to the internal guide road network of the multiple basic tour coordinates, obtain a type of impact assessment combination, perform a tourist behavior pattern association analysis according to the type of impact assessment combination, and establish a first guide optimization network using the first behavior pattern association analysis result; Analyze the influence of the road network edge and the road network edge on the efficiency of the guided route according to the internal guided road network of the multiple basic tour coordinates, obtain two types of impact assessment combinations, perform tourist behavior pattern correlation analysis according to the two types of impact assessment combinations, and establish a second guided tour optimization network using the second behavior pattern correlation analysis result; The tour guide starting point is configured according to the real-time location information and tour progress of multiple user terminals in the same tour group, and a tour guide optimization model is established according to the first tour guide optimization network and the second tour guide optimization network; Based on the navigation optimization model, combined with the navigation starting point and navigation requirements corresponding to any one of the multiple user terminals in the same tour group, multi-directional navigation tracking iterations are performed under time balance constraints to obtain a multi-directional balanced navigation route set and perform route navigation guidance.

2. The navigation method based on the fusion of navigation route and road network as claimed in claim 1, characterized in that: Based on the navigation optimization model, combined with the navigation starting point and navigation requirements corresponding to any one of the multiple user terminals in the same tour group, multiple navigation tracking iterations are performed under time balance constraints, and the method includes: Collect historical tour records of any user terminal among multiple user terminals in the same tour group; Identifying points of interest through the historical tour records; According to the tour points of interest, a matching score is added to each alternative route during the iterative process of the guided tracking.

3. The navigation method based on the fusion of navigation route and road network as claimed in claim 2, characterized in that: According to the tour points of interest, a matching score is added to each alternative route in a guide tracking iteration process, and the method includes: Based on the historical tour records, a tour information database is constructed, wherein the tour information database is used to store historical tour tracks and historical stay times; Mining potential points of interest by combining the tour information database with social network information; The tourist points of interest and potential points of interest are graded and a matching evaluation strategy is formulated.

4. The navigation method based on the fusion of navigation route and road network as claimed in claim 3, characterized in that: According to the internal guide road network of the multiple basic tour coordinates, the road network nodes and the influence of the road network nodes on the distribution of tourist flow are analyzed to obtain a type of impact assessment combination, and the method includes: Collect tourist flow data at each scenic spot through IoT devices; Based on the tourist flow data of each scenic spot, identify the peak and low periods of tourist flow and tourist flow trends, and draw up a tourist flow distribution map; Determine impact assessment information based on the internal guide road network of the multiple basic tour coordinates and the impact degree of the tourist flow distribution map, wherein the impact assessment information includes node congestion degree and tourist waiting time; According to the internal guide road network of the multiple basic tour coordinates, the road network nodes are traversed in combination with the impact assessment information to obtain a type of impact assessment combination.

5. The navigation method based on the fusion of navigation route and road network as claimed in claim 4, characterized in that: The method further comprises: Use GIS technology and remote sensing data to assess the ecological environment of nature reserves and identify sensitive areas; Based on the sensitive area and in combination with a preset safety distance, the alternative routes of the first time window are screened, and the alternative screened routes of the first time window are incorporated into the navigation optimization model.

6. The navigation method based on the fusion of navigation route and road network as claimed in claim 5, characterized in that: Incorporating the alternative screening routes of the first time window into the navigation optimization model, the method further includes: An alternative screening route based on the first time window and a first negative impact on the sensitive area are evaluated in combination with the preset safety distance; According to the preset safety distance and the first negative impact, the remaining routes are adjusted to avoid the sensitive area as a limiting condition, and an alternative adjustment route for the first time window is determined; A second time window is set, and in the overlapping portion between the second time window and the first time window, the alternative adjustment route of the first time window is incorporated into the navigation optimization model.

7. The navigation method based on the fusion of navigation route and road network as claimed in claim 6, characterized in that: Based on the navigation optimization model, combining the navigation starting point and navigation requirements corresponding to any one of the multiple user terminals in the same tour group, performing multiple navigation tracking iterations under time balance constraints, the method further includes: Establishing a sliding time window mechanism, integrating the environmental change data and resource change data corresponding to the multiple basic tour coordinates, and updating the open status bit of the tour item mark; If the updated open status bit is 1, the one-way navigation is activated; Traverse the open status bits associated with multiple basic tour coordinates and activate the one-way tour multiple times.

8. The navigation method based on the fusion of navigation route and road network as claimed in claim 7, characterized in that: A sliding time window mechanism is established, the method further comprising: Based on the sliding time window mechanism, an overlap constraint strategy is introduced, where the overlap constraint strategy is used to adjust the overlap between the second time window and the first time window; According to the overlap constraint strategy, a smooth transition mechanism is configured, wherein the smooth transition mechanism is used to handle data interruption during the time window switching process; According to the smooth transition mechanism, feedback is provided to adjust the window switching logic of the sliding time window mechanism.

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