Vehicle leading type navigation control method and system

Abstract

The invention provides a vehicle leading type navigation control method and system, relates to the technical field of navigation, and can improve the technical problem of poor vehicle navigation effect in a parking lot in related technologies. The method comprises the following steps: acquiring parking space information, wherein the parking space information comprises the number of unoccupied parking spaces and the positions of the unoccupied parking spaces; generating matching information of the unoccupied parking space and the vehicle; generating a navigation route map according to the matching information and sending the navigation route map to a navigation system of the vehicle; projecting the navigation route map to a designated area of a front windshield of a vehicle; when the vehicle passes through the beacon point, position information is sent to the vehicle, and the vehicle position in the navigation route map is updated according to the position information.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of parking lot navigation technology, and more particularly to a vehicle-guided navigation control method and system. Background Art

[0002] In a parking lot environment, the positioning signal of a vehicle is easily interfered by a variety of factors. For example, the building structure of the parking lot (such as concrete walls and ceilings) will block and reflect satellite positioning signals (such as GPS signals), resulting in signal attenuation and multipath effect. The multipath effect refers to the signal reaching the receiver through different paths (direct path and reflected path), causing the receiver to receive multiple copies of the signal with different delays and attenuations, which will seriously affect the accuracy of positioning. In a multi-story parking lot, satellite signals are reflected back and forth between floors, and the vehicle's positioning device may receive confusing signals, making it impossible to accurately determine the vehicle's location.

[0003] Some commonly used vehicle positioning technologies have their own accuracy limitations. Taking traditional positioning based on radio frequency identification (RFID) as an example, its positioning accuracy is usually between several meters and more than ten meters, which is far from enough for large parking lots. Due to poor positioning accuracy, the parking map display in the vehicle navigation system is not accurate enough. For example, the displayed position of the vehicle on the navigation map may deviate from the actual position. When the owner checks the map to find a parking space, he will find that the vehicle icon seems to "float" in the middle of the parking space or the passage, rather than being accurately located at the actual location of the vehicle, making it difficult for the owner to intuitively judge the relative position relationship between himself and the surrounding parking spaces, passage exits, etc.

[0004] Inaccurate positioning can cause navigation instructions to become unclear. For example, the navigation system may instruct the driver to turn left to find an open parking space, but due to positioning errors, the vehicle has actually passed the intersection where it should have turned. In a multi-storey car park, the navigation system may not be able to accurately distinguish which floor the vehicle is on, resulting in the driver being directed to the wrong floor to find a parking space. Summary of the invention

[0005] The embodiments of the present application provide a vehicle-guided navigation control method and system for improving the technical problem of poor vehicle navigation effect in parking lots in related technologies.

[0006] To achieve the above objectives, the embodiments of the present application adopt the following technical solutions:

[0007] An embodiment of the present application provides a vehicle-guided navigation control method, the method comprising: acquiring parking space information, the parking space information including the number of vacant parking spaces and the locations of the vacant parking spaces; generating matching information between the vacant parking spaces and the vehicles; generating a navigation route map based on the matching information and sending it to the navigation system of the vehicle; projecting the navigation route map onto a designated area of ​​the vehicle's windshield; sending location information to the vehicle when the vehicle passes a beacon point, and updating the vehicle position in the navigation route map based on the location information.

[0008] In a possible implementation of the first aspect, the method includes: obtaining beacon point information of the vehicle's route according to the navigation route map; obtaining vehicle speed information; determining the number of vehicles connected to the beacon point within a preset time period based on the speed information, the location information and the beacon point information; when the number of vehicles connected to the beacon point within the preset time period is two or more, sending a prompt message to the vehicles connected to the beacon point.

[0009] In a possible implementation manner of the first aspect, the prompt information includes indicator light warning information and alarm sound warning information.

[0010] In a possible implementation manner of the first aspect, the method further includes: projecting the indicator light warning information onto a designated area of ​​a windshield of the vehicle.

[0011] In a possible implementation of the first aspect, the method also includes: obtaining key factors for the growth of parking spaces in the target parking lot; constructing a prediction model based on the key factors, wherein the prediction model is used to predict the number of parking spaces; obtaining an intermediate value of the key factor based on historical parking space data, current actual parking space data and the prediction model; and predicting the number of parking spaces based on the prediction model corresponding to the intermediate value of the key factor.

[0012] In a possible implementation of the first aspect, the key factors include a first key factor and a second key factor, the first key factor is used to characterize the impact of the operating characteristics of the parking lot on the growth of parking spaces in the parking lot, and the second key factor is used to characterize the impact of environmental factors on the growth of parking spaces in the parking lot.

[0013] In a possible implementation manner of the first aspect, the prediction model is expressed as:

[0014]

[0015] Among them, I(t) is the number of parking spaces at time t, T represents the total number of parking space demanders, p is the first key factor, and q is the second key factor.

[0016] In a possible implementation of the first aspect, an intermediate value of the key factor is obtained according to the historical parking space data, the current actual parking space data and the prediction model, including: constructing an intermediate model according to the historical parking space data; obtaining first predicted parking space data according to the intermediate model; obtaining second predicted parking space data according to the current actual parking space data and the first predicted parking space data; and obtaining the intermediate value of the key factor according to the data of key time points in the second predicted parking space data and the prediction model.

[0017] In a possible implementation of the first aspect, obtaining the second predicted parking space data based on the current actual parking space data and the first predicted parking space data includes: obtaining the average deviation between first data in the first predicted parking space data and the current actual parking space data, the first data being the data in the first predicted parking space data corresponding to the current actual parking space data; and correcting the first predicted parking space data according to the average deviation to obtain the second predicted parking space data.

[0018] In a second aspect, the present application also provides a vehicle-guided navigation control system, the system comprising: a detection module, the detection module being used to obtain parking space information, the parking space information including the number of vacant parking spaces and the locations of the vacant parking spaces; an analysis module, the analysis module being communicatively connected to the detection module, the analysis module being used to generate matching information between vacant parking spaces and vehicles; and a guidance module, the guidance module being communicatively connected to the analysis module, the guidance module being used to guide the vehicle into a vacant parking space matching its model according to the matching information; wherein the guidance module is communicatively connected to the vehicle, the guidance module generates a navigation route map according to the matching information and projects the navigation route map onto a designated area of ​​the vehicle's windshield, and sends location information to the vehicle when the vehicle passes a beacon point, and updates the vehicle position in the navigation route map according to the location information. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flow chart of a control method provided for some embodiments of the present application;

[0020] Figure 2 A flow chart of a control method provided for other embodiments of the present application;

[0021] Figure 3 for Figure 2 Schematic diagram of the process of S30;

[0022] Figure 4 for Figure 3 Schematic diagram of the process flow of S33. DETAILED DESCRIPTION

[0023] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0024] In the following, the terms "first", "second", etc. are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first", "second", etc. may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0025] In addition, in the present application, directional terms such as "up", "down", "left" and "right" may be defined including but not limited to the orientation relative to the schematic placement of the components in the drawings. It should be understood that these directional terms may be relative concepts, which are used for relative description and clarification, and may change accordingly according to the change in the orientation of the components in the drawings.

[0026] In this application, unless otherwise specified or limited, the term "connection" should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be a direct connection or an indirect connection through an intermediate medium. In addition, the term "coupling" can be a way of achieving electrical connection for signal transmission.

[0027] As used herein, “about,” “substantially,” or “approximately” includes the stated value and reference values ​​that are within an acceptable range of deviation from the particular value, where the acceptable range of deviation is as determined by one of ordinary skill in the art taking into account the measurements in question and the errors associated with the measurement of the particular quantity (i.e., the limitations of the measurement system).

[0028] In the embodiments of the present application, the words "exemplarily" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplarily" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplarily" or "for example" is intended to present related concepts in a specific way.

[0029] The embodiments of the present application provide a vehicle-guided navigation control method and system for improving the technical problem of poor vehicle navigation effect in parking lots in related technologies.

[0030] like Figure 1 As shown, an embodiment of the present application provides a vehicle-guided navigation control method, which is applied to a control system to achieve parking space management in a parking lot. The method includes:

[0031] S100: Acquire parking space information, where the parking space information includes the number and locations of vacant parking spaces.

[0032] For example, a variety of sensors may be provided at the parking space to detect the state and size of the parking space. For example, an image sensor, such as a camera, may be provided at each parking space to monitor in real time whether the parking space is occupied by a vehicle. The control system may obtain whether the parking space is occupied and the size of the parking space based on the image captured by the image sensor, and analyze the size of the vehicle that is suitable for parking in the parking space.

[0033] S200: Generate matching information between vacant parking spaces and vehicles.

[0034] For example, an image sensor may be provided at the entrance of the parking lot to send the image of each vehicle entering the parking lot to the control system. The control system analyzes the size of the vehicle based on the onboard image analysis algorithm and matches the vehicle with a parking space of corresponding size in the parking lot.

[0035] It is understandable that the control system may be built with a variety of image analysis algorithms to analyze the size of parking spaces and vehicles based on images. This is a conventional technical means used by those skilled in the art, and this application will not be elaborated here.

[0036] S300: Generate a navigation route map according to the matching information and send it to the navigation system of the vehicle.

[0037] For example, after determining the parking space information matching the vehicle, a navigation route map for the vehicle to the corresponding parking space is generated based on the parking space location information preset in the control system and the map information of the parking lot. The control system is connected to the vehicle in communication and sends the generated navigation route map to the navigation system in the vehicle.

[0038] It can be understood that the navigation system in the vehicle can be a navigation system installed in the vehicle itself, or it can be a device with navigation function located in the vehicle, such as a user's mobile phone.

[0039] It should be noted that the navigation route map can be a specific driving route generated by the control system to navigate to the parking space, or the control system can send the parking space location information to the vehicle navigation system, and the vehicle navigation system generates a corresponding route map based on the location information. This application does not limit this, and those skilled in the art can select appropriate technical means to set it according to needs.

[0040] S400: Projecting the navigation route map onto a designated area of ​​the windshield of the vehicle.

[0041] Exemplarily, the windshield in the vehicle is equipped with a head-up display function component. When the navigation system of the vehicle receives a navigation route map, the navigation route map can be projected to the area of ​​the windshield with the head-up display function.

[0042] S500. Sending location information to the vehicle when the vehicle passes a beacon point, and updating the vehicle position in the navigation route map according to the location information.

[0043] For example, beacon points (such as Bluetooth beacon modules) are set at intervals in the parking lot, and each time a vehicle passes a beacon point, it can communicate with the beacon point. The control system determines the location information of the vehicle based on the signal of the beacon point, and sends the location information to the vehicle to update the vehicle position in the navigation route map. For example, a beacon point can be set at each bend in the parking lot.

[0044] In this way, the technical problem that the navigation of vehicles in parking lots is not intuitive and accurate due to poor positioning accuracy in related technologies can be improved. And the technical problem that multiple vehicles in parking lots are prone to accidents when they meet at corners can be solved.

[0045] S600: Acquire the beacon point information along the vehicle's route according to the navigation route map.

[0046] Exemplarily, when generating a navigation route map between a vehicle and a parking space, the control system may determine a specific route of the vehicle, thereby acquiring beacon points on the route according to the determined route.

[0047] S700: Obtaining speed information of the vehicle. Exemplarily, after the control system communicates with the vehicle, the vehicle sends speed information to the control system.

[0048] S800: Determine the number of vehicles connected to the beacon point within a preset time period based on the speed information, the location information, and the beacon point information along the route.

[0049] For example, after the control system obtains the vehicle position information and the waypoint information on the driving route, it can determine the next beacon point that the vehicle will pass. The control system can determine the time when the vehicle arrives at the next beacon point based on the distance between the current beacon point and the next beacon point and the vehicle speed.

[0050] S900: When the number of vehicles connected to the beacon point within a preset time period is two or more, a prompt message is sent to the vehicles connected to the beacon point.

[0051] When the control system determines that two or more vehicles will pass by a beacon point within a preset time, such as 30 seconds, the control system sends a prompt message to the vehicles that will pass by the beacon point within the preset time. Exemplarily, the prompt message includes indicator light warning information and alarm sound warning information.

[0052] Exemplarily, after receiving the indicator light warning information, the vehicle projects the relevant indicator light warning information onto a designated area of ​​the vehicle's windshield.

[0053] Parking space demand forecasting is a key link in parking lot operations. It aims to estimate the usage trend of parking spaces based on historical parking data and various environmental factors, and provide data support for the optimal allocation of parking resources. In related technologies, parking space prediction methods are mainly based on empirical judgment, statistical model prediction, and machine learning monitoring. Although the existing parking space prediction technology provides a reference for parking quantity to a certain extent, it still has many defects. For example, many current prediction models are often based on simple trend extensions based on historical parking data. When faced with special circumstances such as sudden traffic control or the opening of new commercial facilities in the surrounding area, the prediction results will deviate significantly from the actual parking space demand situation. In addition, many prediction models rely heavily on massive and complete historical parking data. Once the data collection is missing or inaccurate, or there is less historical data in emerging development areas, the reliability and accuracy of the model will be greatly reduced.

[0054] At the same time, the use of parking spaces is affected by a variety of complex environmental factors, including weather conditions (such as heavy rain and heavy snow will reduce the number of vehicles traveling and thus affect parking demand), the intensity of surrounding commercial activities (shopping mall promotions will significantly increase parking demand), the operation of the public transportation system (the increase in bus and subway services may cause some people to give up driving and thus reduce parking demand), and seasonal changes in residents' travel habits. Existing prediction models often find it difficult to accurately simulate the dynamic impact of these factors on parking space demand.

[0055] Moreover, with the rapid development of cities, the continuous evolution of traffic patterns and the continuous changes in people's lifestyles, the demand dynamics of parking spaces may change rapidly. The update and iteration speed of existing models is slow, and it is difficult to achieve real-time or near real-time accurate predictions. It is impossible to make adequate resource allocation and management strategy adjustments in advance, which in turn affects the smooth operation of urban traffic and the efficient use of parking lots.

[0056] Therefore, the parking lot control method in the prior art has a poor management effect on parking spaces. Figure 2-Figure 4 As shown, the control method of the present application may also include:

[0057] S10. Obtain key factors for the increase in parking spaces in the target parking lot.

[0058] The growth of parking space utilization rate of a parking lot is significantly affected by its operational characteristics, which determine the parking lot's ability to attract users, increase utilization rate and expand market share. The operational characteristics of a parking lot, such as parking space turnover rate, length of business hours, adaptability to changes in market demand and charging model, are all key factors affecting the growth of its parking space utilization rate.

[0059] For example, a parking lot with a high parking space turnover rate can quickly improve the recycling efficiency of its parking spaces, thereby accelerating the growth process of parking space utilization. Parking lots with long business hours can meet parking needs at more times and can quickly expand their service coverage when there is market demand.

[0060] In addition, the peak and trough usage patterns of parking lots will also affect the growth rate and scope of their parking space utilization rate. Some parking lots have more concentrated parking demands during specific time periods (such as office areas during the day on weekdays and shopping malls during the weekends), resulting in peak growth in parking space utilization rates. The adaptability of parking lots to the market environment, including the ability to tolerate the needs of different consumer groups and changes in the economic situation, will also affect the potential for growth in parking space utilization rates. For example, parking lots that can survive in economic downturns or fierce competition in the surrounding areas by flexibly adjusting charging strategies may have more stable customer sources and market share. In addition, the marketing strategies and management models of parking lots, such as cooperative behaviors such as launching parking discount packages with surrounding businesses, will also affect the growth methods and success rates of their parking space utilization rates.

[0061] Therefore, the operational characteristics of a parking lot are the basis for determining the growth pattern and speed of its parking space utilization rate. In the embodiment of the present application, the ability of the operational characteristics of a parking lot to drive users to select the parking lot is used as the first key factor. The larger the value of the first key factor, the faster the growth rate of parking spaces driven by the operational characteristics of the target parking lot.

[0062] Environmental factors such as surrounding traffic conditions, regional development trends, business atmosphere, public facilities, surrounding population density, competitor distribution and urban planning adjustments all affect the parking lot's customer acquisition, user retention and parking space utilization rate growth dynamics in different ways.

[0063] For example, surrounding traffic conditions play a decisive role in the attractiveness of a parking lot and the convenience of parking for users. Areas with smooth traffic and clear parking guidance signs tend to help parking lots attract more users, while traffic congestion or difficult-to-find parking entrances may limit the growth of parking space utilization.

[0064] Regional development trends may bring new parking demands, bringing new customer growth opportunities to parking lots at an appropriate stage of development. The business atmosphere not only provides a stable customer base for parking lots (such as shopping malls and office buildings), but may also indicate the direction of future changes in parking demand. Public facilities (such as bus stops, subway stations and other transfer points) and surrounding population density directly affect the scale and distribution of potential parking demand, thereby affecting the market coverage of parking lots. Areas with densely distributed competitors may enhance their own advantages through differentiated competition strategies, and urban planning adjustments (such as new commercial centers, residential areas, etc.) may change the parking demand pattern, forcing parking lots to adjust their operating strategies, which in turn affects the growth rate and pattern of parking space utilization in parking lots.

[0065] Therefore, the key parameters of the present application also include a second key factor, which is used to characterize the impact of environmental factors on the growth of parking spaces in the parking lot. The larger the value of the second key factor, the stronger the role of environmental factors in promoting the growth of parking spaces in the parking lot. In this way, the prediction model composed of the ability of the parking lot's operating characteristics to drive users to choose the parking lot as the first key factor and the impact of environmental factors on the growth of parking spaces in the parking lot as the second key factor can combine multiple influencing factors to better predict the data of the parking lot.

[0066] S20: construct a prediction model based on the key factors, the prediction model is used to predict the number of parking lots. Exemplarily, the prediction model is expressed as:

[0067]

[0068] Among them, I(t) is the number of parking spaces at time t, T represents the total number of parking space demanders, p is the first key factor, and q is the second key factor.

[0069] The prediction model can simultaneously consider the attractiveness of the parking lot itself (the first key factor) and factors such as the external environment and word-of-mouth communication (the second key factor). In this way, the model can fully integrate the various factors that affect the use of parking spaces and avoid the prediction bias caused by focusing on a single factor. At the same time, the model accurately depicts the dynamic change trend of parking spaces over time, how parking spaces can further grow on the basis of those already occupied, and the contribution of parking potential that has not yet been fully utilized to the overall increase in parking spaces. It constructs the use change process of parking spaces in a parking lot as a dynamic system that is jointly affected by its own operating characteristics and external environmental factors.

[0070] Specifically, the first key factor in the prediction model accurately reflects the parking lot's ability to attract new customers and the potential for expanding parking space resources. For parking lots, innovative marketing methods, high-quality service experience, and convenient parking facilities can quickly attract new parking customers, open up new market shares, and promote the sustained growth of parking spaces. The second key factor reflects the impact of various environmental factors on the growth of parking spaces. For example, environmental factors such as the economic development vitality of the surrounding areas, changes in population density, the degree of perfection of transportation infrastructure, the activeness of the business atmosphere, and the distribution of competitors may promote or inhibit the growth of parking space usage. Using this prediction model, parking lot managers can clearly grasp the changes in the use of parking spaces in a specific time period and in a specific area, thereby providing support for decision-making, including but not limited to the reasonable formulation of charging strategies, accurate planning of parking space resource allocation, effective marketing and promotion activities, and flexible response to changes in the external environment, so as to achieve efficient operation and sustainable development of parking lots and meet the needs of the parking market to the greatest extent.

[0071] S30, obtaining the intermediate value of the key factor according to the historical parking space data, the current actual parking space data and the prediction model. Exemplarily, S30 includes:

[0072] S31. Construct an intermediate model according to the historical parking space data.

[0073] Exemplarily, the intermediate model may be composed of multiple prediction models. For example, the intermediate prediction model may be composed of a BP neural network model, a fuzzy neural network model, and an adaptive probabilistic neural network model. The weight of each model may be determined by the accuracy of its prediction result. The higher the accuracy, the greater the weight when constituting the intermediate prediction model.

[0074] S32. Obtain first predicted parking space data according to the intermediate model.

[0075] The trained intermediate model is used to predict the number of parking spaces to obtain the first predicted parking space data, such as predicting the data from January 2023 to December 2023.

[0076] S33, obtaining second predicted parking space data according to the current actual parking space data and the first predicted parking space data. The S33 includes:

[0077] S331. Obtain an average deviation between first data in the first predicted parking space data and the current actual parking space data, where the first data is data in the first predicted parking space data corresponding to the current actual parking space data.

[0078] Exemplarily, the current actual parking space data includes data from January 2023 to June 2023. The data to be predicted is data from July 2023 to December 2023.

[0079] The data corresponding to the current actual parking space data in the first predicted parking space data is taken out, that is, the data from January 2023 to June 2023 in the first predicted parking space data, and analyzed with the actual parking space data from January 2023 to December 2023 to obtain the average deviation between the two.

[0080] For example, the monthly deviation between the first predicted parking space data and the current actual parking space data from January 2023 to June 2023 is calculated, all deviation values ​​are summed up and divided by the number of months to obtain the average deviation for that period of time.

[0081] S332. Correct the first predicted parking space data according to the average deviation to obtain the second parking space predicted data.

[0082] Exemplarily, the predicted data of each month in the first parking space prediction data are added with the average deviation to correct the first predicted parking space data to obtain the second predicted parking space data. It can be understood that the second parking space prediction data includes data from January 2023 to December 2023, that is, it includes parking space data that has occurred and parking space data that has not occurred / to be predicted.

[0083] S34. Obtaining an intermediate value of the key factor according to the data of the key time point in the second predicted parking space data and the prediction model.

[0084] For example, a parking lot started operation in March 2022, and the average daily parking volume in the first month (March 2022) was 50. In the following months, with the promotion of surrounding publicity and word-of-mouth spread by users, the number of parking spaces gradually increased: from March 2022 to April 2022, the number of parking spaces increased by 30, and the average daily parking volume reached 80. From April 2022 to May 2022, the increase in the number of parking spaces further increased, with an increase of 40, and the average daily parking volume reached 120. From May 2022 to June 2022, affected by the increase in surrounding commercial activities, the number of parking spaces increased by 50, and the average daily parking volume reached 170. From June 2022 to July 2022, the number of parking spaces increased by 45, and the average daily parking volume reached 215. From July 2022 to August 2022, there was an increase of 40, and the average daily parking volume reached 255. From August 2022 to September 2022, due to the emergence of new competitors in the surrounding area, the increase in the number of parking spaces slowed down, with an increase of 30 vehicles, and the average daily parking volume reached 285 vehicles. From September 2022 to October 2022, an increase of 25 vehicles was added, and the average daily parking volume reached 310 vehicles. From October 2022 to November 2022, an increase of 20 vehicles was added, and the average daily parking volume reached 330 vehicles. After November 2022, due to factors such as the gradual saturation of the market and changes in surrounding traffic conditions, the increase in the number of parking spaces continued at a low level, with the monthly increase remaining at around 10-15 vehicles, and the average daily parking volume fluctuating between 340-350 vehicles. The growth of parking spaces in the parking lot has gradually slowed down, and it is necessary to further optimize the operation strategy to attract more vehicles to park.

[0085] It can be seen that January 2022 is the first opening time. April 2022 is the turning point between the initial growth and stable period of parking spaces. At this time, the growth trend of parking numbers is good and relatively stable. August 2022 is the turning point between the stable period and the recession period, and the growth of parking numbers begins to slow down. November 2022 is the turning point between the recession period and the residual period (smooth period). Since then, the growth of parking numbers has been extremely slow and almost stagnant. Therefore, in the entire process of parking space growth in parking lots, there are several key time points: the first opening time point, the turning point from the initial growth to the stable period of parking spaces, the turning point from the stable period to the recession period, and the turning point from the recession period to the residual period.

[0086] The number of parking spaces corresponding to each key time point in the second predicted parking space data is obtained, substituted into the prediction model, and the prediction model is solved to obtain the intermediate value of the corresponding key factor.

[0087] S40, predicting the number of parking spaces according to the prediction model corresponding to the intermediate value of the key factor. Exemplarily, the intermediate value of the key factor obtained is substituted into the prediction model, that is, the determined first key factor and the second key factor are substituted into the prediction model, and the data to be predicted is predicted according to the prediction model, that is, the number of parking spaces from July 2023 to December 2023 is predicted using the model.

[0088] The control system can formulate a navigation management strategy based on the predicted number of parking spaces. For example, when it is predicted that the number of vehicles that may be parked in the parking lot on a certain month / day is greater than a threshold, such as greater than 3 / 4 of the total capacity of the parking lot, the control system will give priority to selecting the parking spaces on the bottom floor of the parking lot when navigating the vehicle during this period. If the parking lot has a negative first floor and a negative second floor, the parking spaces on the negative second floor will be given priority. Furthermore, the control system can give priority to selecting the parking spaces farthest from the exit to facilitate the parking of subsequent vehicles.

[0089] An embodiment of the present application also provides a vehicle-guided navigation control system, the system comprising: a detection module, the detection module being used to obtain parking space information, the parking space information including the number of vacant parking spaces and the locations of the vacant parking spaces; an analysis module, the analysis module being communicatively connected to the detection module, the analysis module being used to generate matching information between vacant parking spaces and vehicles; and a guidance module, the guidance module being communicatively connected to the analysis module, the guidance module being used to guide the vehicle into a vacant parking space matching its model according to the matching information; wherein the guidance module is communicatively connected to the vehicle, the guidance module generates a navigation route map according to the matching information and projects the navigation route map onto a designated area of ​​the vehicle's windshield, and sends location information to the vehicle when the vehicle passes a beacon point, and updates the vehicle position in the navigation route map according to the location information.

[0090] Through the description of the above implementation methods, the technicians in the relevant field can clearly understand that the prediction method in the above embodiment can be implemented by means of software plus the necessary general hardware platform, and of course it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the relevant technology can be embodied in the form of a software product, and the computer software product is stored in a storage medium (such as ROM / RAM, disk, CD), including a number of instructions to enable a terminal device (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods of various embodiments of the present invention.

[0091] Through the description of the above implementation methods, technical personnel in the relevant field can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0092] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0093] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, that is, they may be located in one place or distributed in multiple different places. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.

[0094] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated units may be implemented in the form of hardware.

[0095] The above contents are only specific implementation methods of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions within the technical scope disclosed in the present application shall be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.

Claims

1. A vehicle-guided navigation control method, characterized in that: The method comprises: Acquire parking space information, where the parking space information includes the number of vacant parking spaces and the locations of the vacant parking spaces; Generate matching information between vacant parking spaces and vehicles; generating a navigation route map according to the matching information and sending the navigation route map to the navigation system of the vehicle; Projecting the navigation route map onto a designated area of ​​the windshield of the vehicle; When the vehicle passes a beacon point, position information is sent to the vehicle, and the vehicle position in the navigation route map is updated according to the position information.

2. The vehicle-guided navigation control method according to claim 1, characterized in that: The method comprises: Acquiring the beacon point information along the vehicle's route according to the navigation route map; Get the speed information of the vehicle; Determine the number of vehicles connected to the beacon point within a preset time period based on the speed information, the location information and the beacon point information along the route; When the number of vehicles connected to the beacon point within a preset time period is two or more, prompt information is sent to the vehicles connected to the beacon point.

3. The vehicle-guided navigation control method according to claim 2, characterized in that: The prompt information includes indicator light warning information and alarm sound warning information.

4. The vehicle-guided navigation control method according to claim 3, characterized in that: The method further includes: projecting the indicator warning information onto a designated area of ​​a windshield of the vehicle.

5. The vehicle-guided navigation control method according to claim 1, characterized in that: The method further comprises: Obtain the key factors for the growth of parking spaces in the target parking lot; Building a prediction model based on the key factors, the prediction model is used to predict the number of parking lots; Obtaining an intermediate value of the key factor according to historical parking space data, current actual parking space data and the prediction model; The parking quantity is predicted according to the prediction model corresponding to the intermediate value of the key factor.

6. The vehicle-guided navigation control method according to claim 5, characterized in that: The key factors include a first key factor and a second key factor. The first key factor is used to characterize the impact of the operation characteristics of the parking lot on the growth of parking spaces in the parking lot. The second key factor is used to characterize the impact of environmental factors on the growth of parking spaces in the parking lot.

7. The vehicle-guided navigation control method according to claim 6, characterized in that: The expression of the prediction model is: Among them, I(t) is the number of parking spaces at time t, T represents the total number of parking space demanders, p is the first key factor, and q is the second key factor.

8. The vehicle-guided navigation control method according to claim 7, characterized in that: According to the historical parking space data, the current actual parking space data and the prediction model, the intermediate value of the key factor is obtained, including: Building an intermediate model based on the historical parking space data; Acquire first predicted parking space data according to the intermediate model; Obtaining second predicted parking space data according to current actual parking space data and the first predicted parking space data; According to the data of the key time point in the second predicted parking space data and the prediction model, an intermediate value of the key factor is obtained.

9. The vehicle-guided navigation control method according to claim 8, characterized in that: The obtaining the second predicted parking space data according to the current actual parking space data and the first predicted parking space data comprises: Obtaining an average deviation between first data in the first predicted parking space data and the current actual parking space data, the first data being data in the first predicted parking space data corresponding to the current actual parking space data; The first predicted parking space data is corrected according to the average deviation to obtain the second predicted parking space data.

10. A vehicle-guided navigation control system, characterized in that: The system comprises: A detection module, the detection module is used to obtain parking space information, the parking space information includes the number of vacant parking spaces and the locations of the vacant parking spaces; An analysis module, the analysis module is in communication with the detection module, and the analysis module is used to generate matching information between vacant parking spaces and vehicles; and a guiding module, the guiding module being in communication with the analyzing module and configured to guide the vehicle into an empty parking space matching its model according to the matching information; Among them, the guidance module is communicatively connected to the vehicle, and the guidance module generates a navigation route map according to the matching information and projects the navigation route map to a designated area of ​​the vehicle's windshield, and sends location information to the vehicle when the vehicle passes a beacon point, and updates the vehicle position in the navigation route map according to the location information.

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