A kind of walking vehicle for rent in scenic area

Abstract

The present invention relates to the field of scenic spot mobility scooter management technology, in particular to a scenic spot rental mobility scooter, including a mobility scooter and a positioning component, a camera component, a touch screen, a communication module, a wearable device and a control host arranged on the mobility scooter, and also includes a cloud system, the cloud system contains a scenic spot model construction, a scenic spot real-time situation synchronization, a rental management, a tour guide and a fee settlement module. The scenic spot model construction module uses satellite and drone images to build a model and mark the scenic spot range; the scenic spot real-time situation synchronization module collects the flow of people and estimates and grades; the rental management module performs identity authentication, mode selection and itinerary records; the tour guide module plans the itinerary and voice broadcasts; the fee settlement module calculates the fee according to the itinerary record and the rental mode. The present invention enhances the tourist experience, optimizes the scenic spot management, improves the operational efficiency, and is suitable for the rental management of mobility scooters in various scenic spots.

Description

Technical Field

[0001] The invention relates to the technical field of scenic spot mobility scooter management, in particular to a scenic spot rental mobility scooter. Background Art

[0002] With the vigorous development of tourism, the number of tourists in scenic spots is increasing, and the convenience of tourists' travel and experience in scenic spots have become important concerns for scenic spot management. The traditional way of visiting scenic spots mainly relies on walking. For scenic spots with large areas, tourists often need to spend a lot of physical energy and time on the road, which not only easily leads to fatigue of tourists, but also reduces the time tourists spend on visiting attractions and participating in activities, affecting the overall experience of tourists.

[0003] Although there are some scenic spot transportation tools on the market, such as sightseeing buses and cable cars, these transportation tools usually have fixed routes and stops and cannot meet the personalized sightseeing needs of tourists. For example, tourists may want to stay at a certain scenic spot for a longer time for an in-depth tour, or freely choose the order of sightseeing according to their own interests, but traditional transportation tools cannot provide such flexibility.

[0004] In addition, scenic spots also face many challenges in management. In terms of crowd flow monitoring, there is a lack of real-time and accurate means, making it difficult to adjust management strategies in a timely manner according to actual conditions, which can easily lead to overcrowding in some scenic spots and the inability to ensure the safety of tourists. At the same time, it is also impossible to effectively guide the diversion of tourists and optimize resource allocation. In terms of vehicle management, the use of rental vehicles is not accurately recorded, making it difficult to achieve efficient scheduling and maintenance, affecting operating costs and service quality.

[0005] Therefore, a scenic spot rental vehicle is proposed in response to the above problems. Summary of the invention

[0006] The purpose of the present invention is to provide a scenic area rental vehicle to solve the problems raised in the above background technology.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A scenic spot rental vehicle, comprising:

[0009] A mobility scooter and a positioning component, a camera component, a touch screen, a communication module, a wearable device and a control host arranged on the mobility scooter, wherein the positioning component, the camera component, the touch screen, and the communication module are all connected to the control host, and the wearable device is wirelessly connected to the communication module;

[0010] Cloud system: The cloud system includes scenic area model building module, scenic spot real-time situation synchronization module, rental management module, tour guide module and fee settlement module;

[0011] The scenic area model building module uses remote sensing satellites and drones equipped with lidar cameras to collect remote sensing satellite images and lidar images of the scenic area, builds a scenic area model based on the remote sensing satellite images and lidar images, and constructs a virtual range for the area where the scenic spots in the scenic area model are located, and marks the virtual range of each scenic spot to obtain a scenic spot distribution model;

[0012] The scenic spot real-time situation synchronization module collects the flow information of each scenic spot in real time, builds the flow estimation curve of the scenic spot on the day based on the flow information and ticket purchase information of the scenic spot, classifies the flow level according to the capacity of the scenic spot, generates flow estimation data, and synchronizes the flow estimation data of each scenic spot to the virtual range corresponding to the scenic spot distribution model;

[0013] The rental management module includes an identity authentication unit, a rental mode selection unit and a trip recording unit. The identity authentication unit receives the tourist's ticket purchase information and basic information and creates a tourist account; the rental mode selection unit designs a rental mode according to the tourist's ticket purchase information and basic information. After the tourist enters the tourist account, he / she checks the rental mode to confirm and completes the car rental action; after the tourist completes the car rental action, the trip recording unit locates the real-time position of the car with time as the axis, records the tourist's car usage time, mileage and itinerary route, and generates itinerary record information;

[0014] The tour guide module receives the scenic spot distribution model, and synchronizes the real-time location of the scooter and the tourists' ticket purchase information to the scenic spot distribution model, and plans the travel itinerary model based on the real-time location of the scooter, the tourists' ticket purchase and the estimated flow of people choosing the scenic spot; the tour guide module reads the real-time location of the scooter on the scenic spot distribution model in real time, and when the scooter enters the virtual range corresponding to the scenic spot, the scenic spot tour guide voice broadcast is triggered, and the wearable device broadcasts it;

[0015] The fee settlement module receives the itinerary record information and rental mode of the tourist, calculates the vehicle fee according to the itinerary record information, generates a payment code and sends it to the touch screen of the scooter for the tourist to change the vehicle. After the tourist completes the payment, the scooter rental business is completed.

[0016] As a preferred solution, when creating a tourist account, the identity authentication unit establishes data communication with the scenic spot ticket purchase website and ticket office, obtains the tourist ticket purchase data and the tourist's personal information, builds a tourist information storage package based on the tourist ticket purchase data and the tourist's personal information, analyzes the valid time period of the tourist ticket in the tourist ticket purchase data, establishes the scenic spot opening time axis, and synchronizes the tourist information storage package to the valid time period corresponding to the scenic spot opening time axis; the tourist uses the camera component to scan and identify the ticket voucher, and matches the scanned information with the tourist ticket purchase data and the tourist's personal information stored on the scenic spot opening time axis. After the pairing is successful, if the time period when the camera component scans and identifies the ticket voucher is within the valid time period, a tourist account is built; the tourist uses the camera component to scan facial information, and the tourist account records the tourist's facial information for facial information binding.

[0017] As a preferred solution, the leasing mode includes leasing mode 1 and leasing mode 2. Leasing mode 1 determines the scenic spot information for which tourists have purchased tickets based on the ticket purchase data of tourists; receives the scenic spot distribution model, synchronizes the virtual range of the scenic spot corresponding to the scenic spot information to the scenic spot distribution model, and circles the passage area between the scenic spots on the scenic spot distribution model, summarizes the passage area and the virtual range of the scenic spot, and generates the leasing mode 1 activity area. The charging mode of leasing mode 1 = activity area car fee + non-activity area car fee, activity area car fee = basic fee + duration fee 1×car usage time + unit mileage fee 1×mileage, non-activity area car fee = duration fee 2×car usage time + unit mileage fee 2×mileage; the activity area of ​​leasing mode 2 is the entire area, and the charging mode of leasing mode 2 = basic fee 2 + duration fee 3×car usage time + unit mileage fee 3×mileage.

[0018] As a preferred solution, when recording the tourist's vehicle usage time, mileage and travel route, the itinerary recording unit shall be based on the location and duration of the vehicle when the tourist account is logged in.

[0019] As a preferred solution, constructing a crowd flow estimation curve for a scenic spot on the day according to the crowd flow information and ticket purchase information of the scenic spot includes the following steps:

[0020] Step S1: Deploy crowd flow monitoring equipment at the entrance and exit of the scenic spot to monitor the flow of people at fixed time intervals. Collect the number of people entering and leaving the attraction and Calculate each time point Real-time number of people in attractions , Initially ,in, , ;

[0021] Get the ticket information of different time periods of the day from the scenic spot ticket system. The number of tickets purchased for the interval and the estimated time frame for each ticket ;

[0022] Step S2: analysis and quantification of influencing factors;

[0023] Define date type functions ,like For working days, ;like For the weekend, ;like For holidays, ;

[0024] Get the weather conditions in the real-time weather data of the scenic spot, quantify the weather conditions, and , when it rains , cloudy days , then the comprehensive value of weather factors ,in, In order to adjust the weight of weather conditions in the comprehensive impact, historical data regression analysis is used to determine: A quantitative value representing weather conditions;

[0025] Defining seasonal functions , seasons are divided according to months, spring , Summer time , in autumn , in winter ;

[0026] Step S3, constructing a crowd flow estimation model;

[0027] Assume that the estimated flow rate is , the weight coefficients determined based on historical data are date type weight , Weather factor weight , Seasonal factor weight , Real-time number of people weight , Ticket quantity weight , then the formula for estimating the flow of people is ,in, As a constant term, the weight coefficient is solved by multivariate linear regression analysis using historical data ;

[0028] Step S4: real-time crowd flow estimation and curve construction;

[0029] During the day's operation, the date type obtained in real time , Weather Factors , Seasonal factors , Real-time number of people and the number of tickets purchased Substitute into the flow estimation formula and calculate at each time point Estimated traffic volume ;

[0030] By time is the horizontal axis, the estimated value of the flow of people As the vertical axis, draw the estimated flow curve of the scenic spot on that day.

[0031] As a preferred solution, when generating the crowd flow estimation data, the crowd flow estimation curve of the scenic spot on that day is received, and the crowd flow estimation curve of the scenic spot on that day is calculated based on the number of people that the scenic spot can accommodate. , set different traffic thresholds , , , where k is the number of levels, and the estimated flow of people is Compare with these thresholds to classify the flow level. When When When When the crowd level is very crowded, each crowd level corresponds to a queue time, and the estimated crowd flow value is , the crowd level and the time t corresponding to the crowd level to generate the crowd flow estimation data.

[0032] As a preferred solution, when planning a travel itinerary model based on the real-time location of the mobility scooter, the estimated data of tourist traffic when tourists purchase tickets and select attractions, the real-time location of the mobility scooter and the ticket purchase information are associated with the attraction distribution model, the current location and unvisited attractions are marked, and the driving time from the real-time location of the mobility scooter to each unvisited attraction and the driving time between each unvisited attraction are analyzed; the estimated data of tourist traffic at the ticketed attractions are analyzed to determine the waiting time and tour time for each unvisited attraction; a travel itinerary timeline is constructed, starting from the current location of the mobility scooter, and according to the strategy of giving priority to attractions that are close and have short waiting times, the unvisited attractions are selected in turn and arranged on the travel itinerary timeline to generate a travel itinerary model.

[0033] It can be seen from the technical solution provided by the present invention that the scenic spot rental mobility scooter provided by the present invention has the following beneficial effects: the scenic spot real-time situation synchronization module collects crowd flow information in real time, constructs a crowd flow estimation curve and performs grade classification, and the generated crowd flow estimation data is synchronized to the scenic spot distribution model. The tour guide module plans the travel itinerary model according to the real-time position of the mobility scooter, the tourist ticket purchase information, the scenic spot crowd flow estimation data and the scenic spot distribution model, which allows tourists to give priority to scenic spots with short distances and short queues, avoid blindly queuing and waiting, effectively save travel time, and allow tourists to visit more favorite attractions within a limited time; the itinerary recording unit accurately records the tourist's vehicle usage time, mileage and itinerary route. Whether it is a single mobility scooter used or a tourist changes a mobility scooter, it can be accurately counted to provide detailed data for scenic spot vehicle management. Scenic spot managers can reasonably arrange vehicle maintenance, scheduling and deployment based on these data to ensure efficient use of mobility scooter resources, reduce operating costs, and ensure that tourist needs are met. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a schematic diagram of the cloud system architecture in the present invention;

[0035] Figure 2 It is a schematic diagram of the framework of the scenic spot rental vehicle in the present invention.

[0036] In the figure: 1. mobility scooter; 11. front of the vehicle; 12. seat; 2. power supply assembly; 3. main chassis; 31. positioning assembly; 32. touch screen; 33. camera assembly. DETAILED DESCRIPTION

[0037] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0038] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0039] like Figure 1-2 As shown, an embodiment of the present invention provides a scenic spot rental vehicle, including a vehicle 1 and a positioning component 31, a camera component 33, a touch screen 32, a communication module, a wearable device and a control host arranged on the vehicle 1, wherein the positioning component 31, the camera component 33, the touch screen 32 and the communication module are all connected to the control host, and the wearable device is wirelessly connected to the communication module;

[0040] in:

[0041] The camera component 33 is a high-definition camera, which is used to collect the QR code of the scenic spot ticket, the facial information of the tourists, etc.

[0042] The touch screen 32 allows tourists to build tourist accounts, select rental modes, browse attractions, etc.;

[0043] Wearable devices include Bluetooth headsets, etc.

[0044] It also includes a cloud system; the cloud system includes a scenic area model building module, a scenic spot real-time situation synchronization module, a rental management module, a tour guide module and a fee settlement module.

[0045] In this embodiment, the scenic area model construction module uses remote sensing satellites and drones equipped with laser radar cameras to collect remote sensing satellite images and laser radar images of the scenic area, constructs a scenic area model based on the remote sensing satellite images and laser radar images, constructs a virtual range for the area where the scenic spots in the scenic area model are located, and marks the virtual range of each scenic spot to obtain a scenic spot distribution model;

[0046] The specific steps of constructing the scenic spot distribution model in the scenic spot model construction module are as follows:

[0047] Image acquisition preparation:

[0048] For remote sensing satellites, we accurately set parameters such as orbital height and resolution to ensure that we can obtain an overall macroscopic image of the scenic area, so that it covers the entire area and the image clarity meets the requirements of model construction. At the same time, we carefully plan the routes of drones equipped with lidar cameras, fully consider the complexity of the terrain and the distribution of scenic spots in the scenic area, and combine factors such as the drone's endurance, flight altitude and speed to ensure that it can fully scan all areas in the scenic area, so that the lidar camera can collect detailed information on the scenic spots from different angles.

[0049] Comprehensively calibrate and debug related equipment used for image acquisition (such as various sensors on remote sensing satellites and drones) to ensure their stable working status and accurate data acquisition;

[0050] Image acquisition process:

[0051] The remote sensing satellite is started on time according to the set plan, and the scenic spot is continuously photographed at predetermined time intervals (such as every certain period), and remote sensing satellite images of multiple time periods are obtained to analyze the state changes of the scenic spot at different times;

[0052] The drone is dispatched to perform flight missions strictly according to the planned route. During the flight, the lidar camera keeps working uninterruptedly, emitting laser beams and receiving reflected signals to obtain three-dimensional spatial information of the scenic area and form a lidar image. At the same time, with the help of the GPS positioning system, inertial measurement unit and other equipment carried by the drone, key information such as the position and posture when the image is taken is accurately recorded, providing strong data support for subsequent precise stitching and registration of images.

[0053] Data preprocessing:

[0054] Use professional denoising algorithms (such as median filtering for remote sensing satellite images, and statistical filtering for lidar images based on their point cloud data characteristics) to denoise the collected images, effectively eliminate noise points caused by atmospheric interference, sensor noise and other factors, and significantly improve image quality;

[0055] Based on the feature points in the image (such as natural feature points, artificially set obvious landmarks, etc.) or ground control points (marker points with precise coordinates set in advance in the scenic area), advanced image matching algorithms are used for image registration to accurately calculate the transformation parameters between images, ensuring that images acquired from different sources and at different times are accurately aligned in space and have a unified coordinate system;

[0056] For the point cloud data of the LiDAR image, based on the set conditions such as height threshold and slope threshold, the filtering and classification algorithms are used to accurately distinguish different types of points such as ground points, building points, and vegetation points, laying a solid foundation for the subsequent construction of an accurate scenic area model;

[0057] Scenic area model construction:

[0058] Based on the processed LiDAR image point cloud data, the ground point data is processed using an interpolation algorithm to construct a scenic area terrain model that accurately presents the undulating features of the scenic area, including the trends of mountains, valley shapes, lake distribution and other terrain details;

[0059] Based on the classified building point cloud data, through fine operations such as contour extraction, wall and roof reconstruction, the building model in the scenic area is constructed to accurately restore various building structures, such as the layout of the halls of temple buildings, the structural form of pavilions, the style of pavilions, etc.

[0060] Use texture mapping technology to accurately map the texture information of remote sensing satellite images to the corresponding positions of terrain models and building models, enhancing the realism of the models and making their visual effects more realistic;

[0061] Construction and marking of the virtual scope of scenic spots:

[0062] According to the planning layout of the scenic spot and the actual geographical distribution, in the constructed scenic spot model, the boundary range of each scenic spot is determined by manually drawing the polygonal boundary accurately or automatically extracting the boundary range with the help of the landmark buildings and natural landscape features of the scenic spot to ensure that the boundary accurately defines the scenic spot area;

[0063] A unique identifier (such as attraction name, number, etc.) is given to the virtual scope of each attraction, and a complete attribute information database is built in the scenic area model to record in detail key information such as attraction name, introduction, opening hours, tour routes, etc., to facilitate subsequent efficient query and management, and finally successfully build a scenic spot distribution model.

[0064] In this embodiment, the scenic spot real-time situation synchronization module collects the flow information of each scenic spot in real time, constructs the flow estimation curve of the scenic spot on the day according to the flow information of the scenic spot and the ticket purchase information, classifies the flow of people according to the number of people accommodated by the scenic spot, generates the flow estimation data, synchronizes the flow estimation data of each scenic spot to the virtual range corresponding to the scenic spot distribution model, and constructs the flow estimation curve of the scenic spot on the day according to the flow information of the scenic spot and the ticket purchase information, including the following steps:

[0065] Step S1: Deploy crowd flow monitoring equipment at the entrance and exit of the scenic spot to monitor the flow of people at fixed time intervals. Collect the number of people entering and leaving the attraction and Calculate each time point Real-time number of people in attractions , Initially ,in, , ;

[0066] Get the ticket information of different time periods of the day from the scenic spot ticket system. The number of tickets purchased for the interval and the estimated time frame for each ticket ;

[0067] Step S2: analysis and quantification of influencing factors;

[0068] Define date type functions ,like For working days, ;like For the weekend, ;like For holidays, ;

[0069] Get the weather conditions in the real-time weather data of the scenic spot, quantify the weather conditions, and , when it rains , cloudy days , then the comprehensive value of weather factors ,in, In order to adjust the weight of weather conditions in the comprehensive impact, historical data regression analysis is used to determine: A quantitative value representing weather conditions;

[0070] Defining seasonal functions , seasons are divided according to months, spring , Summer time , in autumn , in winter ;

[0071] Step S3, constructing a crowd flow estimation model;

[0072] Assume that the estimated flow rate is , the weight coefficients determined based on historical data are date type weight , Weather factor weight , Seasonal factor weight , Real-time number of people weight , Ticket quantity weight , then the formula for estimating the flow of people is ,in, As a constant term, the weight coefficient is solved by multivariate linear regression analysis using historical data ;

[0073] Step S4: real-time crowd flow estimation and curve construction;

[0074] During the day's operation, the date type obtained in real time , Weather Factors , Seasonal factors , Real-time number of people and the number of tickets purchased Substitute into the flow estimation formula and calculate at each time point Estimated traffic volume ;

[0075] By time is the horizontal axis, the estimated value of the flow of people As the vertical axis, draw the estimated flow curve of the scenic spot on that day;

[0076] Furthermore, when the crowd flow estimation data is generated, the crowd flow estimation curve of the scenic spot on that day is received, and the crowd flow estimation curve of the scenic spot on that day is calculated according to the number of people that can accommodate the scenic spot. , set different traffic thresholds , , , where k is the number of levels, and the estimated flow of people is Compare with these thresholds to classify the flow level. When When When When the crowd level is very crowded, each crowd level corresponds to a queue time, and the estimated crowd flow value is , the crowd level and the time t corresponding to the crowd level to generate the crowd flow estimation data.

[0077] In this embodiment, the rental management module includes an identity authentication unit, a rental mode selection unit and a trip recording unit. The identity authentication unit receives the tourist's ticket purchase information and basic information and creates a tourist account;

[0078] Among them, when creating a tourist account, the identity authentication unit establishes data communication with the scenic spot ticket purchase website and the ticket office, obtains the tourist ticket purchase data and the tourist's personal information, builds a tourist information storage package based on the tourist ticket purchase data and the tourist's personal information, analyzes the valid time period of the tourist ticket in the tourist ticket purchase data, establishes the scenic spot opening time axis, and synchronizes the tourist information storage package to the valid time period corresponding to the scenic spot opening time axis; the tourist uses the camera component 33 to scan and identify the ticket voucher, and matches the scanned information with the tourist ticket purchase data and the tourist's personal information stored on the scenic spot opening time axis. After the pairing is successful, if the time period when the camera component 33 scans and identifies the ticket voucher is within the valid time period, a tourist account is built; the tourist uses the camera component 33 to scan facial information, and the tourist account records the facial information of the tourist for facial information binding;

[0079] The rental mode selection unit designs the rental mode according to the tourist's ticket purchase information and basic information. After the tourist enters the tourist account, he / she checks the rental mode to confirm and completes the car rental action;

[0080] Among them, the leasing mode includes leasing mode 1 and leasing mode 2. Leasing mode 1 determines the scenic spot information for which tourists have purchased tickets based on the ticket purchase data of tourists; receives the scenic spot distribution model, synchronizes the virtual range of the scenic spot corresponding to the scenic spot information to the scenic spot distribution model, and circles the passage area between the scenic spots on the scenic spot distribution model, summarizes the passage area and the virtual range of the scenic spot, and generates the leasing mode 1 activity area. The charging mode of leasing mode 1 = vehicle use fee in the activity area + vehicle use fee in the non-activity area, vehicle use fee in the activity area = basic fee + duration fee 1× vehicle use time + unit mileage fee 1× mileage, vehicle use fee in the non-activity area = duration fee 2× vehicle use time + unit mileage fee 2× mileage; the activity area of ​​leasing mode 2 is the entire area, and the charging mode of leasing mode 2 = basic fee 2 + duration fee 3× vehicle use time + unit mileage fee 3× mileage;

[0081] After the tourist completes the rental of the mobility scooter, the trip recording unit locates the real-time position of the mobility scooter based on time, records the tourist's vehicle usage time, mileage and itinerary route, and generates trip record information. When recording the tourist's vehicle usage time, mileage and itinerary route, the trip recording unit shall be based on the location and duration of the mobility scooter 1 when the tourist account is in the logged-in state;

[0082] Generating travel record information specifically includes the following steps:

[0083] Step 1: Initialize the record and associate it with the vehicle

[0084] After the tourist completes the first mobility scooter rental and logs in to the account, the trip recording unit starts and records the current time as the start time of the first trip. , get the initial position of scooter 1 in this era and associate the mobility scooter 1 with the tourist account;

[0085] Step 2: Real-time location positioning, data collection and trip records (during the use of a single mobility scooter)

[0086] Continuously communicate with the current scooter positioning component to obtain real-time location information at fixed time intervals (such as every 10 seconds) ( Indicates the number of times the location information is obtained during the use of the first mobility scooter);

[0087] After each location is obtained, calculate the difference with the previous location The distance difference , add up the distance difference to calculate the mileage ; Record time at the same time , calculate the duration of car use ;

[0088] Draw the itinerary based on the location information and mark it on the map;

[0089] Step 3: Replace the scooter

[0090] When a tourist changes a mobility scooter, the check-out time of the current mobility scooter 1 is recorded , get the current logout location ; Calculate the total time the first mobility scooter is used , complete the route drawing of the first mobility scooter;

[0091] Record the login time of the second mobility scooter , get its initial position , associate it with the tourist account, and restart the trip recording process, as described in step 2, to calculate the mileage during the use of the second mobility scooter , length of time using the vehicle and other information;

[0092] Step 4: Integrate the travel information of multiple mobility scooters (if more mobility scooters are replaced, the same applies)

[0093] If tourists change mobility scooters several times during their tour, repeat step 3 and record the usage time, mileage and itinerary of each mobility scooter;

[0094] Integrate the travel information of each mobility scooter in the order of use to form a complete travel record; total mileage , total vehicle usage time , where n is the number of vehicles replaced, and the complete itinerary is the sequential connection of the itineraries of each vehicle;

[0095] Step 5: Generate and store final trip record information

[0096] When the tourist finishes using the last mobility scooter and returns it, the check-out time of the last mobility scooter is recorded. , get the logout location , complete the travel record calculation and route drawing of the last scooter;

[0097] The integrated total mileage, total vehicle usage time, complete travel route and detailed usage information of each mobility vehicle (starting time, starting location, check-in time, check-out location, mileage and travel route of a single mobility vehicle, etc.) are used to generate the final travel record information, which is stored in the system for subsequent cost settlement, travel analysis and other operations.

[0098] In this embodiment, the tour guide module receives the scenic spot distribution model, and synchronizes the real-time location of the scooter and the ticket purchase information of the tourists to the scenic spot distribution model, and plans the travel itinerary model according to the real-time location of the scooter, the estimated data of the number of tourists buying tickets and selecting scenic spots;

[0099] Among them, when planning the travel itinerary model according to the real-time position of the mobility scooter, the estimated data of the flow of tourists buying tickets and selecting attractions, the real-time position of the mobility scooter and the ticket purchase information are associated with the attraction distribution model, the current position and the unvisited attractions are marked, and the driving time from the real-time position of the mobility scooter to each unvisited attraction and the driving time between each unvisited attraction are analyzed; the estimated data of the flow of tourists at the ticketed attractions are analyzed to determine the waiting time and the tour time of each unvisited attraction; the travel itinerary time axis is constructed, starting from the current position of the mobility scooter, according to the strategy of giving priority to attractions with short distances and short queues, the unvisited attractions are selected in turn and arranged on the travel itinerary time axis to generate the travel itinerary model;

[0100] The tour guide module checks the real-time position of the mobility scooter on the scenic spot distribution model in real time. When the mobility scooter enters the virtual range corresponding to the scenic spot, the scenic spot tour guide voice broadcast is triggered and broadcast by the wearable device. The tour guide module voice broadcast triggering and execution steps are as follows:

[0101] Real-time location monitoring and judgment:

[0102] The tour guide module continuously maintains communication connection with the positioning component of the mobility scooter, and obtains the real-time location information of the mobility scooter in the scenic area (in the form of latitude and longitude coordinates or location coding customized by the scenic area) at very short time intervals (such as every 1 second);

[0103] Compare and judge the acquired real-time position with the virtual range of each scenic spot in the scenic spot distribution model; the virtual range of the scenic spot is defined in the scenic spot distribution model with a pre-set geometric shape (such as a polygonal area) and boundary coordinates;

[0104] Trigger condition detection:

[0105] When the real-time position coordinates of the mobility scooter fall within the virtual range boundary of a certain scenic spot, it is determined that the mobility scooter has entered the corresponding area of ​​the scenic spot, and the conditions for triggering the scenic spot tour guide voice broadcast are met;

[0106] Voice broadcast command sending:

[0107] After the tour guide module detects the trigger condition, it immediately selects the corresponding tour guide voice broadcast content from the system's pre-stored voice library based on the identification information of the current scenic spot (such as the name and number of the scenic spot, etc.); the voice broadcast content includes rich information such as the introduction of the scenic spot, historical and cultural background, and tour precautions, and can be stored in multiple languages ​​according to different language requirements (such as Chinese, English, Japanese, etc.);

[0108] The tour guide module sends the selected voice broadcast command to the wearable device associated with the tourist account (such as a smart bracelet, Bluetooth headset, or other device with voice playback function);

[0109] Wearable device voice broadcast execution:

[0110] After receiving the voice broadcast command, the wearable device automatically starts the voice playback function and plays the tour guide's voice content to tourists through the built-in speakers or headphones; during the playback process, tourists can operate the voice broadcast through the control buttons on the wearable device (such as pause, continue, adjust the volume, etc.) to meet personalized listening needs; at the same time, the tour guide module can automatically pause or stop the voice broadcast according to the tourist's location movement when the tourist leaves the virtual range of the current attraction to avoid unnecessary information interference.

[0111] The fee settlement module receives the itinerary record information and rental mode of the tourist, calculates the vehicle usage fee based on the itinerary record information, generates a payment code, and sends it to the touch screen 32 of the scooter for the tourist to change vehicles. After the tourist completes the payment, the scooter rental business is completed. The fee settlement module operation steps are as follows:

[0112] Data reception and analysis:

[0113] The fee settlement module monitors the travel record information from the travel record unit and the rental mode information from the rental management module in real time;

[0114] After receiving this information, the itinerary record information is immediately parsed to extract key data, including but not limited to the start time, end time, mileage of each itinerary, and the length of stay in different areas (such as the active area and inactive area in rental mode 1); at the same time, the rental mode selected by the tourist (rental mode 1 or rental mode 2) is accurately identified;

[0115] Cost calculation logic (rental model 1):

[0116] If tourists adopt rental mode 1:

[0117] First, determine the scope of the activity area based on the scenic spot distribution model, and then filter out the driving data in the activity area from the itinerary records; calculate the vehicle usage fee in the activity area, and the calculation formula is: vehicle usage fee in the activity area = basic fee + duration fee 1 × vehicle usage time in the activity area + unit mileage fee 1 × mileage in the activity area; the basic fee, duration fee 1 and unit mileage fee 1 here are all fixed parameters pre-set by the scenic spot based on cost accounting and market research;

[0118] Next, the non-activity area car fee is calculated; the driving data of the non-activity area is also obtained from the trip record, and the calculation formula is: non-activity area car fee = duration fee 2 × non-activity area car duration + unit mileage fee 2 × non-activity area driving mileage; duration fee 2 and unit mileage fee 2 are also preset parameters;

[0119] Finally, add the car usage fees in the activity area and the car usage fees in the non-activity area to get the total car usage fee under the rental model;

[0120] Cost calculation logic (rental model 2):

[0121] For leasing model 2, since its activity area is the entire field:

[0122] Get the car usage time and mileage during the entire rental period directly from the trip record;

[0123] Calculate the total vehicle usage fee according to the charging formula of leasing mode 2: total vehicle usage fee = basic fee 2 + duration fee 3 × total vehicle usage time + unit mileage fee 3 × total mileage; among which, basic fee 2, duration fee 3 and unit mileage fee 3 are parameters specially set for leasing mode 2;

[0124] Payment code generation and push:

[0125] Based on the calculated total vehicle usage fee, the fee settlement module generates a payment code through the payment interface integrated with the scenic spot payment system; the payment code can be a QR code, barcode or other coding format that meets the payment standards, and contains necessary information such as fee amount, order number, scenic spot logo and payment validity period;

[0126] Push the generated payment code to the touch screen 32 of the scooter currently used by the tourist for display, while ensuring that the payment code is displayed clearly and completely, and remains stable during the payment process without being disturbed by other operations or information;

[0127] Payment result verification and business closed loop:

[0128] After seeing the payment code on the touch screen 32 of the mobility scooter, the tourist uses the payment application (such as WeChat Pay, Alipay, etc.) on the mobile phone to scan the payment code to make the payment; the payment system feeds back the payment result to the fee settlement module in real time;

[0129] After receiving the notification of successful payment, the fee settlement module performs a series of subsequent operations: updates the order status in the system to "paid", records detailed payment information such as payment time and payment channel, so as to facilitate subsequent financial reconciliation and statistical analysis; at the same time, sends instructions to the rental management module to notify it to complete the mobility vehicle rental business process related to the tourist account, including lifting vehicle usage rights restrictions, recording vehicle return information, etc., to ensure that the entire rental business process is completed completely and accurately; if the payment fails, the fee settlement module will prompt the tourist the reason for the payment failure on the touch screen 32, and guide the tourist to re-initiate payment or choose other appropriate payment methods. At the same time, the unpaid orders are handled accordingly according to the regulations of the scenic spot, such as setting a certain payment waiting time or handling them according to the breach of contract rules.

[0130] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A scenic spot rental vehicle, characterized by: include: A mobility scooter (1) and a positioning component (31), a camera component (33), a touch screen (32), a communication module, a wearable device and a control host arranged on the mobility scooter (1), wherein the positioning component (31), the camera component (33), the touch screen (32) and the communication module are all connected to the control host, and the wearable device is wirelessly connected to the communication module; Cloud system; the cloud system includes a scenic area model building module, a scenic spot real-time situation synchronization module, a rental management module, a tour guide module and a fee settlement module; The scenic area model construction module uses remote sensing satellites and drones equipped with laser radar cameras to collect remote sensing satellite images and laser radar images of the scenic area, constructs a scenic area model based on the remote sensing satellite images and laser radar images, constructs a virtual range for the area where the scenic spots in the scenic area model are located, and marks the virtual range of each scenic spot to obtain a scenic spot distribution model; The scenic spot real-time situation synchronization module collects the flow information of each scenic spot in real time, constructs the flow estimation curve of the scenic spot on the day according to the flow information of the scenic spot and the ticket purchase information, classifies the flow of people according to the number of people accommodated by the scenic spot, generates the flow estimation data, and synchronizes the flow estimation data of each scenic spot to the virtual range corresponding to the scenic spot distribution model; The rental management module includes an identity authentication unit, a rental mode selection unit and a trip recording unit. The identity authentication unit receives the tourist's ticket purchase information and basic information and creates a tourist account; the rental mode selection unit designs a rental mode according to the tourist's ticket purchase information and basic information. After the tourist logs in to the tourist account, the rental mode is determined to complete the rental action; after the tourist completes the rental action of the mobility scooter, the trip recording unit locates the real-time position of the mobility scooter with time as the axis, records the tourist's vehicle usage time, mileage and itinerary route, and generates itinerary record information; The tour guide module receives the scenic spot distribution model, and synchronizes the real-time position of the scooter and the ticket purchase information of tourists to the scenic spot distribution model, and plans the travel itinerary model according to the real-time position of the scooter, the estimated data of the number of tourists buying tickets and selecting scenic spots; the tour guide module calls the real-time position of the scooter on the scenic spot distribution model in real time, and when the scooter enters the virtual range corresponding to the scenic spot, the scenic spot tour guide voice broadcast is triggered, and the wearable device broadcasts it; The fee settlement module receives the itinerary record information and rental mode of the tourist, calculates the vehicle usage fee according to the itinerary record information, generates a payment code, and sends the payment code to the touch screen (32) of the scooter on which the tourist performs the vehicle change operation. After the tourist completes the payment, the scooter rental business is completed; Constructing a crowd estimation curve for a scenic spot on the day based on the crowd information and ticket purchase information of the scenic spot includes the following steps: Step S1: Deploy crowd flow monitoring equipment at the entrance and exit of the scenic spot to monitor the flow of people at fixed time intervals. Collect the number of people entering and leaving the attraction and Calculate each time point Real-time number of people in attractions , Initially ,in, , ; Get the ticket information of different time periods of the day from the scenic spot ticket system. The number of tickets purchased for the interval and the estimated time frame for each ticket ; Step S2: analysis and quantification of influencing factors; Defining date types ,like ;like ;like ; Get the weather conditions in the real-time weather data of the scenic spot, quantify the weather conditions, and , when it rains , cloudy days , then weather factors ,in, In order to adjust the weight of weather conditions in the comprehensive impact, historical data regression analysis is used to determine: A quantitative value representing weather conditions; Defining seasonal functions , seasons are divided according to months, spring , Summer time , in autumn , in winter ; Step S3, constructing a crowd flow estimation model; Assume that the estimated flow rate is , the weight coefficients determined based on historical data are date type weight , Weather factor weight , Seasonal factor weight , Real-time number of people weight , Ticket quantity weight , then the formula for estimating the flow of people is ,in, As a constant term, the weight coefficient is solved by multivariate linear regression analysis using historical data ; Step S4: real-time crowd flow estimation and curve construction; During the day's operation, the date type obtained in real time , Weather Factors , Seasonal factors , Real-time number of people and the number of tickets purchased Substitute into the flow estimation formula and calculate at each time point Estimated traffic volume ; By time point is the horizontal axis, the estimated value of the flow of people As the vertical axis, draw the estimated flow curve of the scenic spot on that day.

2. A scenic area rental vehicle according to claim 1, characterized in that: When creating a tourist account, the identity authentication unit establishes data communication with the scenic spot ticket purchase website and the ticket office, obtains the tourist ticket purchase data and the tourist's personal information, builds a tourist information storage package based on the tourist ticket purchase data and the tourist's personal information, analyzes the valid time period of the tourist ticket in the tourist ticket purchase data, establishes the scenic spot opening time axis, and synchronizes the tourist information storage package to the valid time period corresponding to the scenic spot opening time axis; the tourist uses the camera component (33) to scan and identify the ticket voucher, and matches the scanned information with the tourist ticket purchase data and the tourist's personal information stored on the scenic spot opening time axis. After the pairing is successful, if the time period for scanning and identifying the ticket voucher by the camera component (33) is within the valid time period, then the tourist account is built; The tourist uses the camera component (33) to scan the facial information, and the tourist account is bound to the recorded facial information of the tourist.

3. A scenic area rental vehicle according to claim 2, characterized in that: The rental mode includes rental mode 1 and rental mode 2. Rental mode 1 determines the scenic spot information for which the tourist has purchased tickets based on the tourist ticket purchase data; Receive the scenic spot distribution model, synchronize the virtual range of the scenic spot corresponding to the scenic spot information to the scenic spot distribution model, circle the passage area between the scenic spots on the scenic spot distribution model, summarize the passage area and the virtual range of the scenic spot, and generate the rental mode one activity area. The charging mode of the rental mode one = the vehicle use fee in the activity area + the vehicle use fee in the non-activity area. The vehicle use fee in the activity area = the basic fee + the duration fee 1× the vehicle use duration + the unit mileage fee 1× the mileage. The vehicle use fee in the non-activity area = the duration fee 2× the vehicle use duration + the unit mileage fee 2× the mileage. The activity area of ​​leasing mode 2 is the entire field, and the charging model of leasing mode 2 = basic fee 2 + time fee 3 × vehicle usage time + unit mileage fee 3 × mileage.

4. A scenic area rental vehicle according to claim 3, characterized in that: When recording the duration of use of the vehicle, mileage and itinerary of the tourist, the itinerary recording unit is based on the location and duration of the vehicle (1) when the tourist account is in the logged-in state.

5. The scenic area rental vehicle according to claim 1, characterized in that: When the crowd flow estimation data is generated, the crowd flow estimation curve of the scenic spot on that day is received, and the crowd flow estimation curve of the scenic spot is calculated based on the number of people that can accommodate the scenic spot. , set different traffic thresholds , , , where k is the number of levels, and the estimated value of the flow of people is Compare with the above thresholds to divide the flow level. When When , the flow level is moderate; When When the crowd level is very crowded, each crowd level corresponds to a queue time, and the estimated crowd flow value is , the crowd level and the time point t corresponding to the crowd level are combined to generate the crowd flow estimation data.

6. A scenic area rental vehicle according to claim 1, characterized in that: When planning a travel itinerary model based on the real-time location of the mobility scooter, the estimated data of tourist traffic when tourists purchase tickets and select attractions, the real-time location of the mobility scooter and the ticket purchase information are associated with the attraction distribution model, the current location and unvisited attractions are marked, and the driving time from the real-time location of the mobility scooter to each unvisited attraction and the driving time between each unvisited attraction are analyzed; Analyze the estimated data of visitor flow at ticketed attractions to determine the waiting time and tour time for each unvisited attraction; construct a travel itinerary timeline, starting from the current location of the mobility scooter, give priority to attractions that are close and have short waiting times, and then synchronize the unvisited attractions to the travel itinerary timeline in turn to generate a travel itinerary model.

Images