Parking lot vehicle searching method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a parking lot vehicle searching method and device, electronic equipment and a storage medium. The method comprises the steps that a vehicle searching environment model of a parking lot where a vehicle is located is acquired based on regional position information of the vehicle and user attribute characteristics; correspondingly determining a user position in the model and a vehicle position in the model based on the current position of the user and the parking position of the vehicle; and generating a user vehicle searching route based on the vehicle searching environment model, the user position in the model and the vehicle position in the model, so that the user follows the vehicle searching route to search the vehicle. According to the embodiment of the invention, the method can provide a vehicle searching path which meets the personalized demands of different users for the different users.

Description

Technical Field

[0001] This invention relates to the field of parking management technology, and in particular to a parking lot vehicle locating method, device, electronic device, and storage medium. Background Technology

[0002] With the acceleration of urbanization and the continuous expansion of parking facilities, many cities have built large parking lots at airports, shopping malls, and hospitals. Due to the generally complex structure and large number of parking spaces in these large parking lots, drivers are prone to getting lost after parking due to similar environments or failure to record their location, often spending considerable time searching for their vehicles, especially in scenarios with over a thousand parking spaces. Existing parking lot car-finding solutions typically provide the same route based on the user's location and the parking spot. However, since different users have different access needs—for example, users carrying large luggage require a path without stairs—existing car-finding solutions cannot meet the personalized needs of different users. Summary of the Invention

[0003] This invention provides a parking lot vehicle locating method, device, electronic device, and storage medium, which can provide different users with vehicle locating paths that meet their personalized needs.

[0004] In a first aspect, embodiments of the present invention provide a parking lot vehicle locating method, including:

[0005] A vehicle-finding environment model for the parking lot where the vehicle is located is obtained based on the vehicle's regional location information and user attribute characteristics.

[0006] The user's current location and the vehicle's parking location are used to determine the user's location and the vehicle's location in the model. The user's location in the model is the user's position within the vehicle-finding environment model, and the vehicle's location in the model is the vehicle's position within the vehicle-finding environment model.

[0007] Based on the vehicle search environment model, the user's location in the model, and the vehicle's location in the model, a vehicle search route is generated for the user to follow in order to find the vehicle.

[0008] Secondly, embodiments of the present invention provide a parking lot vehicle locator, comprising:

[0009] The vehicle search environment model acquisition module is used to acquire the vehicle search environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute characteristics.

[0010] The model location determination module is used to determine the user's location and the vehicle's location in the model based on the user's current location and the vehicle's parking location. The user's location in the model is the user's position within the vehicle-finding environment model, and the vehicle's location in the model is the vehicle's position within the vehicle-finding environment model.

[0011] The vehicle search route generation module is used to generate a user vehicle search route based on the vehicle search environment model, the user's location in the model, and the vehicle's location in the model, so that the user can follow the vehicle search route to find the vehicle.

[0012] Thirdly, embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the parking lot vehicle locating method as described in any of the embodiments of the present invention.

[0013] Fourthly, embodiments of the present invention also provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the parking lot vehicle locating method as described in any of the embodiments of the present invention.

[0014] This invention provides a parking lot vehicle locating method, device, electronic device, and storage medium. By obtaining a vehicle locating environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute characteristics, a vehicle locating environment model matching the user attribute characteristics can be obtained. Then, based on the user's current location and the vehicle's parking location, the user's position and the vehicle's position in the model are determined. Based on the vehicle locating environment model, the user's position in the model, and the vehicle's position in the model, a vehicle locating route is generated. This can provide different users with vehicle locating routes that meet their personalized needs, thereby facilitating users to find their vehicles smoothly and improving the user's vehicle locating experience. Attached Figure Description

[0015] To more clearly illustrate the technical solution of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a schematic flowchart of a parking lot vehicle locating method provided in an embodiment of the present invention;

[0017] Figure 2 This is another schematic flowchart of the parking lot vehicle locating method provided in this embodiment of the invention;

[0018] Figure 3This is another schematic flowchart of the parking lot vehicle locating method provided in this embodiment of the invention;

[0019] Figure 4 This is another schematic flowchart of the parking lot vehicle locating method provided in this embodiment of the invention;

[0020] Figure 5 This is a schematic diagram of a parking lot car finding device provided in an embodiment of the present invention;

[0021] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0022] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0023] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0024] Figure 1 This is a flowchart illustrating a parking lot vehicle locating method provided in an embodiment of the present invention. This embodiment is applicable to scenarios involving vehicle locating in large parking lots. The method can be executed by a parking lot vehicle locating device provided in this embodiment, which can be implemented using software and / or hardware. In a specific embodiment, the device can be integrated into an electronic device, such as a mobile user terminal. The following embodiments will illustrate this using the integration of the device into a mobile user terminal as an example. (Reference) Figure 1 The method may specifically include the following steps:

[0025] Step 101: Obtain a vehicle-finding environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute characteristics. This step can obtain a vehicle-finding environment model that matches the user's attribute characteristics, and facilitate the generation of a vehicle-finding route that accurately matches the user's needs based on the vehicle-finding environment model.

[0026] Specifically, the aforementioned regional location information of the vehicle can be understood as the location information of the geographical area where the vehicle is located.

[0027] Specifically, the vehicle's location information can be determined through onboard satellite positioning sensors, and the location information input by the user can also be obtained through the user interface.

[0028] Specifically, the parking lot information where the vehicle is located can be determined based on the vehicle's regional location information, and an environment model of the parking lot where the vehicle is located can be established based on the parking lot information and user attribute characteristics, or a pre-established environment model parking lot model can be obtained based on the user attribute characteristics, thereby obtaining the above-mentioned vehicle search environment model.

[0029] Specifically, multiple parking lots suspected to be where vehicles are located can be identified and displayed to the user based on the vehicle's regional location information. Then, the parking lot where the vehicle is located can be selected and entered by the user from the multiple suspected parking lots. Alternatively, the parking lot where the vehicle is located can be determined directly based on the vehicle's regional location information.

[0030] Specifically, the target path characteristics can be determined based on the user's attribute characteristics, and the above-mentioned car-finding environment model can be established based on the target path characteristics and the parking lot information where the vehicle is located.

[0031] Specifically, the aforementioned target path characteristics may include the characteristics of the passage space included in the path, wherein the passage space characteristics include: whether it includes barrier-free access, pedestrian walkways, stairs, elevators, ramps, narrow passages, obstacles, automatic sensor doors and / or equipment noise areas.

[0032] Specifically, the aforementioned user attribute features can be input by the user through the interactive interface or pre-stored by the system.

[0033] Specifically, the aforementioned user attribute characteristics may include the user's or their companions' age, gender, health status, and / or the status of their belongings.

[0034] Understandably, a user's age, gender, and health status determine their needs regarding the safety and physical exertion of the vehicle search route. For example, the elderly, young children, people with mobility impairments, or pregnant women require routes that require less physical exertion and are safer. When carrying large luggage, strollers, or shopping carts, users need routes that are wide enough and free of stairs. Therefore, determining the characteristics of the target route based on the user's or their companions' age, gender, health status, and / or the status of their belongings, and then building a vehicle search environment model based on these characteristics, can help to accurately and efficiently create a vehicle search environment model that matches the user's needs.

[0035] Step 102: Based on the user's current location and the vehicle's parking location, determine the user's location and the vehicle's location in the model. The user's location in the model is the user's position within the vehicle-finding environment model, and the vehicle's location in the model is the vehicle's position within the vehicle-finding environment model. This step facilitates the accurate generation of a vehicle-finding route that matches the user's needs based on the user's location, the vehicle's location, and the vehicle-finding environment model.

[0036] Specifically, the user's current location and the vehicle's parking location can be obtained automatically or determined based on location information manually entered by the user through the user interface.

[0037] Specifically, satellite positioning sensors can automatically obtain the user's current location and the vehicle's parking location.

[0038] Optionally, before step 102, the parking lot vehicle locating method provided in this embodiment of the invention further includes: acquiring environmental perception data of the parking location through the vehicle's on-board sensing device, and determining the parking location based on the environmental perception data.

[0039] Specifically, the aforementioned vehicle-mounted sensing devices may include camera equipment, ultrasonic equipment, lidar equipment, satellite positioning equipment, and / or inertial navigation equipment.

[0040] Optionally, the process of acquiring environmental perception data of the parking location through the vehicle's onboard sensing devices and determining the parking location based on the environmental perception data includes:

[0041] The vehicle uses an in-vehicle camera to capture the parking space number and the parking area sign of the corresponding parking space, and determines the vehicle's parking location based on the parking space number and the parking area sign.

[0042] Step 103: Generate a vehicle-finding route based on the vehicle-finding environment model, the user's location within the model, and the vehicle's location within the model, so that the user can follow the route to find their vehicle. This step, building upon steps 101 and 102, obtains the vehicle-finding environment model of the parking lot where the vehicle is located by using the vehicle's regional location information and user attribute characteristics. This results in a vehicle-finding environment model that matches the user's attribute characteristics. Then, based on the user's current location and the vehicle's parking location, the user's location within the model and the vehicle's location are determined. Finally, a vehicle-finding route is generated based on the vehicle-finding environment model, the user's location within the model, and the vehicle's location within the model. This allows for personalized vehicle-finding routes to be provided to different users, facilitating vehicle retrieval and improving the user's vehicle-finding experience.

[0043] Optionally, the process of generating user car-finding routes based on the car-finding environment model, the user location in the model, and the vehicle location in the model includes: generating multiple user car-finding routes based on the car-finding environment model, the user location in the model, and the vehicle location in the model, and sorting the multiple user car-finding routes according to the recommendation index.

[0044] Optionally, the process of generating a user's car-finding route based on the car-finding environment model, the user's location in the model, and the vehicle's location in the model includes: generating a user's car-finding route based on the car-finding environment model, the user's location in the model, and the vehicle's location in the model.

[0045] Specifically, user car-finding routes can be generated using the A* algorithm or Dijkstra algorithm based on the car-finding environment model, the user's location in the model, and the vehicle's location in the model.

[0046] Optionally, before generating the user's car-finding route based on the car-finding environment model, the user's location in the model, and the vehicle's location in the model, the target path features are determined based on user attribute features.

[0047] Optionally, the process of generating a user's car-finding route based on the car-finding environment model, the user's location in the model, and the vehicle's location in the model includes: generating a user's car-finding route based on target path features, the car-finding environment model, the user's location in the model, and the vehicle's location in the model.

[0048] The parking lot vehicle locating method provided by the embodiments of the present invention is further described below, such as... Figure 2 As shown, that is Figure 1 Step 101 may include the following steps:

[0049] Step 101A1: Obtain a distribution map of the parking lots where the vehicles are located based on the regional location information.

[0050] Optionally, the process of obtaining the distribution map of the parking lot where the vehicle is located based on the regional location information includes: determining the parking lot where the vehicle is located based on the regional location information, and querying the official website of the parking lot, the parking lot's supporting application, or the relevant platform of the local government to obtain the distribution map of the parking lot where the vehicle is located.

[0051] Specifically, a distribution map of all parking lots in the service area can be obtained in advance and stored in a distribution map database.

[0052] Optionally, the process of obtaining the distribution map of the parking lot where the vehicle is located based on the regional location information includes: after determining the parking lot where the vehicle is located, the distribution map of the parking lot can be obtained by directly querying the distribution map database.

[0053] Step 101A2: Determine all pedestrian access spaces in the parking lot where the vehicle is located based on the distribution map.

[0054] Specifically, the aforementioned pedestrian access space can be understood as the sum of all physical spaces within the parking lot where vehicles are located, providing safe, free, and barrier-free access for pedestrians (including walkers, people with mobility impairments using wheelchairs or other assistive devices, and pedestrians carrying luggage or items). This includes both dedicated pedestrian areas and spaces shared with other modes of transportation but where pedestrians' right-of-way must be guaranteed. Its core purpose is to meet the complete access needs of pedestrians from start to finish.

[0055] Specifically, all the aforementioned pedestrian passage spaces may include: parking areas, passageways, stairs, elevators, ramps, obstacles, safety gates, and automatic sensor gates, etc.

[0056] Optionally, before determining all pedestrian access spaces in the parking lot where the vehicle is located based on the distribution map, images of access-related signs in the parking lot where the vehicle is located can be obtained.

[0057] Specifically, the aforementioned traffic-related signage images can be understood as signage images in the parking lot where the vehicle is located that use elements such as graphics, text, symbols, and colors to convey information such as guidance, warnings, restrictions, and notifications to users.

[0058] Specifically, the aforementioned access-related signage images may include, for example, signs indicating "Caution Steps," "No Pets Allowed," "Noise Zone," and "Automatic Door."

[0059] Optionally, the process of determining all pedestrian access spaces in the parking lot where the vehicle is located based on the distribution map includes:

[0060] Based on traffic-related sign images and distribution maps, a pre-trained traffic space recognition model is used to determine all pedestrian traffic spaces in the parking lot where the vehicle is located.

[0061] Step 101A3: Determine the user-accessible space in the total pedestrian access space based on user attribute features.

[0062] Optionally, before determining the user-accessible space in all pedestrian access spaces based on user attribute characteristics, the spatial characteristics of each pedestrian access space are determined.

[0063] Specifically, the spatial characteristics of the aforementioned pedestrian passageways can be understood as the inherent features exhibited by the pedestrian passageways in terms of their physical form, functional layout, and environmental attributes. These characteristics directly affect pedestrian passage efficiency, safety, and experience. Specifically, they can include features such as the width, height, elevation difference, and / or accessibility of the pedestrian passageway.

[0064] Specifically, the spatial characteristics of the aforementioned pedestrian passage space may also include whether the corresponding pedestrian passage space is a high-frequency opening area of ​​automatic sensor doors and an area with equipment noise, and whether the corresponding pedestrian passage space is equipped with pet-friendly facilities, such as pet defecation points and drinking points.

[0065] Optionally, the process of determining the spatial characteristics of each pedestrian passage space can also be determined using the passage space identification model described above.

[0066] Specifically, the aforementioned passage space recognition model can be a model based on a convolutional neural network.

[0067] Specifically, the training process of the aforementioned pedestrian space recognition model includes: acquiring sample parking lot distribution maps and sample pedestrian-related signs, and using the sample parking lot distribution maps and sample pedestrian-related signs as training inputs to the pedestrian space recognition model to be trained, so that the pedestrian space recognition model can predict the spatial characteristics of all pedestrian passage spaces and each pedestrian passage space in the corresponding parking lot; and using the annotation information of the spatial characteristics of all pedestrian passage spaces and each pedestrian passage space in the corresponding parking lot to guide the training output of the pedestrian space recognition model to be trained, thereby training the pedestrian space recognition model to be trained.

[0068] Specifically, after inputting the sample parking lot distribution map and sample access-related signs into the access space recognition model to be trained, a series of convolution and pooling operations are performed to obtain the prediction results, namely the predicted values ​​of all pedestrian access spaces and the spatial features of each pedestrian access space in the sample distribution map; the prediction results are compared with the real labels, i.e., the annotation information, to calculate the loss value; the gradient of the model parameters is calculated through the backpropagation algorithm, and the model parameters are updated according to the gradient to make the model's prediction results closer to the real labels; the above steps are repeated to continuously update the model parameters until the model converges or reaches the preset number of training rounds.

[0069] Optionally, the process of determining the user-accessible space in the entire pedestrian access space based on user attribute characteristics includes:

[0070] The target path features are determined based on user attribute features; and the user's passable space is determined from all pedestrian spaces based on the target path features and the spatial features of each pedestrian passable space.

[0071] In a specific instance, if the user attribute features include age greater than 60, the target path feature is determined to include: excluding stairs.

[0072] In a specific instance, if the user attribute features include carrying a pet, then the target path features are defined as excluding high-frequency opening zones and noise zones of automatic sensor doors.

[0073] Step 101A4: Establish a vehicle search environment model based on the user's accessible space.

[0074] Specifically, the above-mentioned vehicle-finding environment model can be established based on the user's accessible space and corresponding spatial characteristics.

[0075] In a specific instance, one of the following vehicle search environment models can be used:

[0076] Model A (Base Model): Contains all accessible paths.

[0077] Model B (walking-only model): This model can be further refined to exclude areas where only vehicles are allowed.

[0078] Model C (Carrying Items Model): Exclude narrow passages, stairs, and other areas, and prioritize marking wide passages, ramps, and elevators.

[0079] Model D (Trolley Model): Exclude stairs, prioritize marking elevators or ramps, and mark flat ground.

[0080] Model E (Special Population Model): Prioritize marking accessible pathways, elevators, and ramps, and avoid complex areas.

[0081] Model F (with pet model): Prioritize avoiding areas that may be uncomfortable for pets (such as areas with high frequency of automatic sensor door opening, noisy areas), and prioritize marking pet-friendly facilities (such as toilet areas, watering points).

[0082] The embodiments of the present invention can conveniently, efficiently and accurately obtain a vehicle search environment model that meets the user's needs, enabling the user to conveniently, efficiently and accurately find the vehicle in the corresponding parking lot, thereby improving the user experience.

[0083] The parking lot vehicle locating method provided by the embodiments of the present invention is further described below. For example... Figure 3 As shown, that is Figure 1Step 101 may include the following steps:

[0084] Step 101B1: Based on the vehicle's regional location information, determine multiple candidate environment models and determine the model features of each candidate environment model. The multiple candidate environment models are pre-established environment models.

[0085] Specifically, the aforementioned candidate environment models can be pre-built and stored on the server.

[0086] Specifically, the vehicle's regional location information can be sent to the server, so that the server can return the identifiers of multiple candidate environment models and the model features of each candidate environment model based on the vehicle's regional location information.

[0087] Specifically, the model features of each of the above candidate environment models may include the features of the pedestrian passage space included in the corresponding candidate environment model, as well as the user attribute features of the target population for the corresponding candidate environment model.

[0088] Optionally, the process of determining multiple candidate environment models based on the vehicle's regional location information and determining the model features of each candidate environment model includes: determining multiple candidate environment models corresponding to multiple parking lots located in the corresponding area based on the location information, or determining multiple candidate environment models corresponding to one parking lot located in the corresponding area based on the location information.

[0089] Optionally, the multiple candidate environment models corresponding to the above parking lot include: multiple candidate environment models matched with users of different user attribute characteristics.

[0090] Specifically, the aforementioned candidate environment models may include: a basic model, a walking-only model, a model with carried items, a stroller model, a special population model, and a model with pets.

[0091] Step 101B2: Determine the target environment model features based on user attribute features.

[0092] In a specific example, the process of determining the target environment model features based on user attribute features includes: if the user attribute features include age greater than 60, the target environment model features are determined to include: excluding stairs.

[0093] In a specific example, the process of determining the target environment model characteristics based on user attribute characteristics includes: if the user attribute characteristics include being older than 60 years old, the target environment model characteristics are determined to be applicable to older users.

[0094] In a specific instance, if the user attribute features include carrying a pet, then the target environment model features are defined as excluding high-frequency opening areas and noise areas of automatic sensor doors.

[0095] Step 101B3: Obtain the vehicle search environment model from multiple candidate environment models based on the characteristics of the target environment model and the model characteristics of each candidate environment model.

[0096] Specifically, the identifier of the vehicle-finding environment model can be determined from the identifiers of multiple candidate environment models, and the data of the vehicle-finding environment model can be obtained from the server based on the identifier of the vehicle-finding environment model to obtain the aforementioned vehicle-finding environment model.

[0097] This invention, by pre-establishing multiple candidate environment models and selecting the matching environment model in real time based on user attribute characteristics, can reduce real-time computing pressure and improve response speed while ensuring accuracy.

[0098] The parking lot vehicle locating method provided by the embodiments of the present invention is further described below, such as... Figure 4 As shown, it may include the following steps:

[0099] Step 401: Obtain user identification information through wearable devices and determine user identity based on the identification information.

[0100] Specifically, the wearable devices mentioned above can store user identification information in advance or collect user identification information on-site.

[0101] Specifically, the aforementioned identity verification information may be the user's account information.

[0102] Specifically, the process of collecting users' basic identity information on-site may include: connecting to a wearable device that stores users' basic identity information, such as a smart bracelet, to obtain the users' basic identity information.

[0103] Specifically, the aforementioned user identification information can also be the user's biometric information, such as fingerprint information and facial images.

[0104] Step 402: Determine user attribute characteristics based on user identity.

[0105] Specifically, user attribute features of different authorized user identities can be stored in the user database in advance. Then step 402 includes querying the user database based on the user identity to obtain the aforementioned user attribute features.

[0106] Step 403: Obtain the vehicle search environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute features.

[0107] Step 404: Determine the user's location and the vehicle's location in the model based on the user's current location and the vehicle's parking location.

[0108] Step 405: Generate a vehicle search route based on the vehicle search environment model, the user's location in the model, and the vehicle's location in the model, so that the user can follow the vehicle search route to find the vehicle.

[0109] It is understandable that some groups, such as the elderly and disabled, find it difficult to input user attribute characteristics. Therefore, obtaining user identification information through wearable devices and then determining user attribute characteristics based on the corresponding identification information can help improve the user experience.

[0110] Figure 5 This is a structural diagram of a parking lot vehicle locating device provided in an embodiment of the present invention. This device is suitable for executing the parking lot vehicle locating method provided in an embodiment of the present invention. Figure 5 As shown, the device may specifically include:

[0111] The vehicle location environment model acquisition module 501 is used to acquire a vehicle location environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute characteristics. This module can obtain a vehicle location environment model that matches the user attribute characteristics and facilitates the generation of a vehicle location route based on the vehicle location environment model that meets the user's needs.

[0112] The model location determination module 502 is used to determine the user's location and the vehicle's location in the model based on the user's current location and the vehicle's parking location. The user's location in the model is the user's position within the vehicle-finding environment model, and the vehicle's location in the model is the vehicle's position within the vehicle-finding environment model. This module enables the accurate generation of a vehicle-finding route that matches the user's needs based on the user's location, the vehicle's location, and the vehicle-finding environment model.

[0113] The vehicle search route generation module 503 is used to generate a vehicle search route for the user based on the vehicle search environment model, the user's location in the model, and the vehicle's location in the model, so that the user can follow the route to find the vehicle. This module can combine with modules 501 and 502 to obtain the vehicle search environment model of the parking lot where the vehicle is located by using the vehicle's regional location information and user attribute characteristics. It can obtain a vehicle search environment model that matches the user's attribute characteristics. Then, based on the user's current location and the vehicle's parking location, it determines the user's location and the vehicle's location in the model, and generates a vehicle search route based on the vehicle search environment model, the user's location in the model, and the vehicle's location in the model. This can provide vehicle search routes that meet the personalized needs of different users, thereby making it easier for users to find their vehicles and improving the user's vehicle search experience.

[0114] Optionally, the above-mentioned vehicle search environment model acquisition module 501 can be specifically used to: acquire a distribution map of the parking lot where the vehicle is located based on regional location information; determine all pedestrian access spaces in the parking lot where the vehicle is located based on the distribution map; determine the user-accessible space in all pedestrian access spaces based on user attribute characteristics; and establish a vehicle search environment model based on the user-accessible space.

[0115] Optionally, the above-mentioned vehicle search environment model acquisition module 501 can be specifically used to acquire the traffic-related sign images of the parking lot where the vehicle is located; and determine all pedestrian traffic spaces in the parking lot where the vehicle is located based on the traffic-related sign images and distribution maps through a pre-trained traffic space recognition model.

[0116] Optionally, the vehicle search environment model acquisition module 501 can be specifically used to: determine the spatial characteristics of each pedestrian passage space; determine the target path characteristics based on user attribute characteristics; and determine the user's passable space from all pedestrian passage spaces based on the target path characteristics and the spatial characteristics of each pedestrian passage space.

[0117] Optionally, the vehicle search environment model acquisition module 501 can be specifically used to: determine multiple candidate environment models based on the vehicle's regional location information and determine the model features of each candidate environment model; determine the target environment model features based on user attribute features; and acquire the vehicle search environment model from multiple candidate environment models based on the target environment model features and the model features of each candidate environment model.

[0118] Optionally, the parking lot vehicle locator provided in this embodiment of the invention further includes a user attribute feature acquisition module, which is used to acquire user identification information through a wearable device and determine the user's identity based on the identification information, and to determine user attribute features based on the user's identity.

[0119] Optionally, the parking lot vehicle locator provided in this embodiment of the invention further includes a parking location determination module, which is used to obtain environmental perception data of the parking location through the vehicle's on-board sensing device before determining the user's location and the vehicle's location in the model based on the user's current location and the vehicle's parking location, and to determine the parking location based on the environmental perception data.

[0120] Optionally, the parking lot vehicle locator provided in this embodiment of the invention further includes a traffic rule determination module, used to determine target path features based on user attribute features.

[0121] Optionally, the above-mentioned vehicle search route generation module 503 can be specifically used to generate a user's vehicle search route based on the target path features, the vehicle search environment model, the user's location in the model, and the vehicle's location in the model.

[0122] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional modules is merely an example. In practical applications, the above 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. The specific working process of the functional modules described above can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0123] This invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the parking lot car-finding method provided in any of the above embodiments.

[0124] This invention also provides a computer-readable medium having a computer program stored thereon, which, when executed by a processor, implements the parking lot vehicle locating method provided in any of the above embodiments.

[0125] This invention also provides a computer program product, including a computer program that, when executed by a processor, implements the parking lot vehicle locating method as described in any of the embodiments of this invention.

[0126] The following is for reference. Figure 6 It shows a schematic diagram of the structure of a computer system 600 suitable for implementing an electronic device according to embodiments of the present invention. Figure 6 The electronic device shown is merely an example and should not be construed as limiting the functionality and scope of the embodiments of the present invention.

[0127] like Figure 6 As shown, the computer system 600 includes a central processing unit (CPU) 601, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 602 or programs loaded from storage section 608 into random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the system 600. The CPU 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0128] The following components are connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 610 as needed so that computer programs read from it can be installed into storage section 608 as needed.

[0129] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 609, and / or installed from removable medium 611. When the computer program is executed by central processing unit (CPU) 601, it performs the functions defined above in the system of this invention.

[0130] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0131] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0132] The modules and / or units described in the embodiments of the present invention can be implemented in software or hardware. The described modules and / or units can also be housed in a processor; for example, a processor can be described as including a vehicle-finding environment model acquisition module, a model location determination module, and a vehicle-finding route generation module. The names of these modules do not necessarily constitute a limitation on the module itself.

[0133] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs that, when executed by the device, cause the device to: obtain a vehicle-finding environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute characteristics; determine the user's position and the vehicle's position in the model based on the correspondence between the user's current position and the vehicle's parking position; and generate a user vehicle-finding route based on the vehicle-finding environment model, the user's position in the model, and the vehicle's position in the model, so that the user can follow the vehicle-finding route to find the vehicle.

[0134] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A parking lot vehicle location method, characterized in that, include: A vehicle-finding environment model for the parking lot where the vehicle is located is obtained based on the vehicle's regional location information and user attribute characteristics. The user's current location and the vehicle's parking location are used to determine the user's location and the vehicle's location in the model. The user's location in the model is the location of the user in the vehicle search environment model, and the vehicle's location in the model is the location of the vehicle in the vehicle search environment model. as well as Based on the vehicle search environment model, the user's location in the model, and the vehicle's location in the model, a vehicle search route is generated for the user to follow in order to find the vehicle.

2. The parking lot vehicle locating method according to claim 1, characterized in that, The model for obtaining the vehicle search environment in the parking lot based on the vehicle's regional location information and user attribute features includes: A distribution map of the parking lots where the vehicles are located is obtained based on the regional location information; Based on the distribution map, determine all pedestrian access spaces in the parking lot where the vehicle is located; Based on the user attribute characteristics, determine the user-accessible space in the total pedestrian access space; and The vehicle search environment model is established based on the user's accessible space.

3. The parking lot vehicle locating method according to claim 2, characterized in that, Before determining all pedestrian access spaces in the parking lot where the vehicle is located based on the distribution map, the method includes: Obtain images of access-related signs in the parking lot where the vehicle is located; The step of determining all pedestrian access spaces in the parking lot where the vehicle is located based on the distribution map includes: Based on the traffic-related sign images and the distribution map, a pre-trained traffic space recognition model is used to determine all pedestrian traffic spaces in the parking lot where the vehicle is located.

4. The parking lot vehicle locating method according to claim 2, characterized in that, Before determining the user-accessible space among all pedestrian access spaces based on the user attribute features, the method further includes: Determine the spatial characteristics of each pedestrian passage space; The step of determining the user-accessible space in the total pedestrian access space based on the user attribute features includes: Determine the target path features based on the aforementioned user attribute features; Based on the target path features and the spatial features of each pedestrian passage space, the user-accessible space is determined from all pedestrian passage spaces.

5. The parking lot vehicle locating method according to claim 1, characterized in that, The model for obtaining the vehicle search environment in the parking lot based on the vehicle's regional location information and user attribute features includes: Based on the vehicle's regional location information, multiple candidate environment models are determined and the model features of each candidate environment model are determined. The multiple candidate environment models are pre-established environment models. Determine the target environment model features based on the aforementioned user attribute features; and The vehicle-finding environment model is obtained from multiple candidate environment models based on the characteristics of the target environment model and the model characteristics of each candidate environment model.

6. The parking lot vehicle locating method according to claim 1, characterized in that, Before obtaining the vehicle-finding environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute features, the method further includes: Acquire user identification information through wearable devices and determine user identity based on the identification information; and The user attribute characteristics are determined based on the user's identity.

7. The parking lot vehicle locating method according to claim 1, characterized in that, Before generating the user's car-finding route based on the car-finding environment model, the user's location in the model, and the vehicle's location in the model, the method includes: Determine the target path features based on the aforementioned user attribute features; The process of generating a user's car-finding route based on the car-finding environment model, the user's location in the model, and the vehicle's location in the model includes: The user's vehicle search route is generated based on the target path features, the vehicle search environment model, the user's location in the model, and the vehicle's location in the model.

8. A parking lot car finding device, characterized in that, include: The vehicle search environment model acquisition module is used to acquire the vehicle search environment model of the parking lot where the vehicle is located based on the vehicle's regional location information and user attribute characteristics. The model location determination module is used to determine the user's location and the vehicle's location in the model based on the user's current location and the vehicle's parking location. The user's location in the model is the user's location in the vehicle search environment model, and the vehicle's location in the model is the vehicle's location in the vehicle search environment model. as well as The vehicle search route generation module is used to generate a user vehicle search route based on the vehicle search environment model, the user's location in the model, and the vehicle's location in the model, so that the user can follow the vehicle search route to find the vehicle.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the parking lot vehicle locating method as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the parking lot vehicle locating method as described in any one of claims 1 to 7.

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