Vehicle position information generation method and device, equipment and medium

Abstract

The invention discloses a vehicle position information generation method and device, equipment and a medium. The method comprises the following steps: acquiring an environment detection instruction corresponding to a to-be-detected vehicle; according to the environment detection instruction, a to-be-detected area corresponding to the to-be-detected vehicle is detected, environment image information is determined, and the environment image information comprises at least one collection type and real-time environment information corresponding to each collection type; identifying at least one environment feature according to the environment image information; and determining vehicle position information corresponding to the to-be-detected vehicle according to each environment feature. According to the embodiment of the invention, the accuracy of vehicle position information generation can be improved.

Description

Technical Field

[0001] This invention relates to the field of data testing technology, and in particular to a method, apparatus, device, and medium for generating vehicle location information. Background Technology

[0002] With the rapid development of technology, the types of vehicles are gradually increasing, and the parking environments for vehicles are becoming more diverse. In order to ensure the safety of vehicle parking, it is necessary to inspect the environment around the vehicle.

[0003] Currently, the safety status of the vehicle's surrounding environment is assessed by acquiring video streams around the vehicle.

[0004] However, relying solely on video streams to view the vehicle's surroundings consumes a large amount of network traffic and data, and has a high memory footprint. Summary of the Invention

[0005] This invention provides a method, apparatus, device, and medium for generating vehicle location information, in order to improve the accuracy of vehicle location information generation.

[0006] In a first aspect, embodiments of the present invention provide a method for generating vehicle location information, the method comprising:

[0007] Obtain the environmental testing instructions corresponding to the vehicle to be tested;

[0008] According to the environmental detection instructions, the detection area corresponding to the vehicle to be detected is detected to determine the environmental image information. The environmental image information includes: at least one acquisition type and the real-time environmental information corresponding to each acquisition type.

[0009] Based on the environmental image information, at least one environmental feature is identified;

[0010] Based on the characteristics of each environment, determine the vehicle location information corresponding to the vehicle to be detected.

[0011] Secondly, embodiments of the present invention also provide a vehicle location information generation device, the device comprising:

[0012] The instruction acquisition module is used to acquire the environmental detection instructions corresponding to the vehicle to be tested.

[0013] The area detection module is used to detect the area to be detected corresponding to the vehicle to be detected according to the environmental detection command, and to determine the environmental image information. The environmental image information includes: at least one acquisition type and the real-time environmental information corresponding to each acquisition type.

[0014] The feature acquisition module is used to identify at least one environmental feature based on environmental image information;

[0015] The information determination module is used to determine the vehicle location information corresponding to the vehicle to be detected based on various environmental characteristics.

[0016] Thirdly, embodiments of the present invention also provide a vehicle location information generation device, the vehicle location information generation device comprising:

[0017] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the vehicle location information generation method of any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, which stores computer instructions for causing a processor to execute and implement the vehicle location information generation method of any embodiment of the present invention.

[0019] The technical solution of this invention involves obtaining an environmental detection command corresponding to the vehicle to be detected; detecting the area to be detected corresponding to the vehicle to be detected according to the environmental detection command to determine environmental image information, which includes at least one acquisition type and real-time environmental information corresponding to each acquisition type; identifying at least one environmental feature based on the environmental image information; and determining the vehicle location information corresponding to the vehicle to be detected based on each environmental feature. By determining the vehicle location information through multi-dimensional data, the accuracy of vehicle location information generation is improved.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a vehicle location information generation method according to Embodiment 1 of the present invention;

[0023] Figure 2 This is a flowchart of a vehicle location information generation method according to Embodiment 2 of the present invention;

[0024] Figure 3This is a structural diagram of a vehicle location information generation device according to an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of a vehicle location information generation device provided in an embodiment of the present invention. Detailed Implementation

[0026] 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.

[0027] 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 a 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.

[0028] The acquisition, storage, and application of environmental monitoring instructions and other related technologies in the technical solutions of this invention comply with relevant laws and regulations and do not violate public order and good morals.

[0029] Example 1

[0030] Figure 1 This is a flowchart illustrating a vehicle location information generation method according to Embodiment 1 of the present invention. This embodiment of the invention is applicable to situations involving vehicle location information generation. The method can be executed by a vehicle location information generation device, which can be implemented in hardware and / or software.

[0031] See Figure 1 The method for generating vehicle location information shown includes:

[0032] S101. Obtain the environmental detection command corresponding to the vehicle to be tested.

[0033] The vehicle to be tested can be a vehicle whose environmental information is being tested while it is parked. The environmental testing command can be a command to perform environmental information testing on the vehicle to be tested.

[0034] Specifically, a vehicle location information acquisition system can be established. The system comprises three parts: a user terminal, a cloud server, and a vehicle terminal. The vehicle terminal includes a main control unit, visible light cameras, infrared thermal imaging cameras, an in-vehicle communication module, and a power management module. The main control unit, as the core processing component of the vehicle terminal, is integrated into the intelligent driving domain controller. It is responsible for receiving environmental detection commands from the in-vehicle communication module, scheduling the corresponding cameras based on these commands, and encoding, compressing, and packaging the collected raw audio and video data. It operates in a low-power sleep state for most of the time after the vehicle is turned off, but can be woken up by specific network commands (such as the network management message NM), effectively reducing power consumption during vehicle parking. This design ensures rapid system response when needed while avoiding the impact of prolonged high-power operation on the vehicle battery. The visible light camera group includes at least two wide-angle or surround-view cameras (front-view and rear-view), and can also add left and right side-view or surround-view cameras to provide comprehensive field of view coverage. It is responsible for acquiring visible light video streams or high-resolution still images of the vehicle's surrounding environment. Infrared thermal imaging camera: Deployed at least at the front of the vehicle, it collects thermal radiation signals from the surrounding environment to generate thermal imaging video streams or images. It can effectively detect heat-generating objects such as living organisms even in complete darkness, fog, or haze. The visible light camera group provides comprehensive visual coverage, meeting monitoring needs in everyday environments. The infrared thermal imaging camera compensates for the limitations of the visible light camera in adverse weather and low-light conditions, effectively detecting heat-generating objects. Together, they ensure the system provides clear and reliable monitoring images in various environments. Vehicle communication module (T-Box): The T-Box's built-in 4G / 5G cellular network module ensures high-speed and stable communication between the vehicle and the cloud. It can not only transmit monitoring data in real time but also receive commands from the cloud, enabling remote control and management of the vehicle. Power management module: This module is designed to ensure that critical components such as the T-Box, main control unit (in sleep mode), and cameras continue to receive low-voltage power even when the vehicle is turned off, thus guaranteeing the system's all-weather monitoring capability. Cloud Server: As a reliable data relay, it receives instructions from the user terminal (user app) and accurately forwards them to the vehicle terminal of the vehicle under test. It also receives data uploaded from the vehicle terminal and distributes it to the corresponding users. This decouples the direct connection between the user and the vehicle, improving system reliability and scalability. User Terminal: Provides the user interface, typically a dedicated app on a smartphone. Users initiate requests to view images or videos through it, and it receives and displays media information returned by the vehicle terminal. It acquires interaction information generated between the user and the user terminal. Based on this interaction information, it generates environmental detection commands for the vehicle under test.

[0035] S102. According to the environmental detection instruction, the detection area corresponding to the vehicle to be detected is detected to determine the environmental image information. The environmental image information includes: at least one acquisition type and the real-time environmental information corresponding to each acquisition type.

[0036] The area to be detected can be the area where environmental information of the vehicle to be detected is collected. The environmental image information can be image information of the surrounding environment of the vehicle to be detected. The acquisition type can be the type of acquisition method for the environmental information of the vehicle to be detected. The implemented environmental information can be the environmental information of the vehicle to be detected collected according to the acquisition type.

[0037] Specifically, after receiving an environmental detection command, the vehicle's main control unit schedules the corresponding camera group to detect the area to be detected corresponding to the vehicle, determining the environmental image information. This environmental image information includes at least one acquisition type and the corresponding real-time environmental information. The environmental detection command can correspond to at least one acquisition type, which can be either image acquisition or video acquisition. The real-time environmental information corresponding to the image acquisition type is at least one image of the area to be detected on the vehicle. The real-time environmental information corresponding to the video acquisition type is at least one video segment of the area to be detected on the vehicle. When the acquisition type is image acquisition, the main control unit can quickly compress multiple acquired images (e.g., using JPEG or WebP format) and package them into a data packet, which is then transmitted back to the user terminal (user APP) via T-Box and the cloud. The user terminal can display the environmental image information around the vehicle in a mosaic or matrix format.

[0038] S103. Based on the environmental image information, identify at least one environmental feature.

[0039] Among them, environmental features can be representative descriptive information from environmental image information that can be used to identify and analyze the location and environment of the vehicle to be detected.

[0040] Specifically, the vehicle's main control unit can identify environmental features from environmental image information using image processing and computer vision technologies. For example, edge detection algorithms can identify the outlines of objects in environmental images, thereby determining the position and shape of objects such as parking lines, pillars, or other vehicles; image classification algorithms can identify features such as the brand or color of surrounding vehicles. Deep learning models, such as convolutional neural networks, can also be used to identify environmental image information, accurately extracting various environmental features, such as abnormal personnel around the vehicle, character recognition of parking space numbers, feature recognition of different vehicle models, or the relative distance between objects around the vehicle and the vehicle being detected.

[0041] S104. Based on the environmental characteristics, determine the vehicle location information corresponding to the vehicle to be detected.

[0042] Among them, vehicle location information can be a collection of environmental information about the area where the vehicle to be detected is located.

[0043] Specifically, the vehicle's main control unit quickly locates the vehicle to be detected by matching environmental features with their positions on the map, based on map information. For example, the main control unit acquires at least one environmental feature, such as the parking space number corresponding to the vehicle, features of surrounding vehicles, and the positions of pillars around the vehicle. It then matches these environmental features with the map information to determine the vehicle's exact location. This specific location and the environmental features are then used to define the vehicle's location information. Therefore, the vehicle location information acquisition system can operate in dual modes, using either image or video detection to detect the environmental information surrounding the vehicle within the acquisition time, saving detection costs and improving detection accuracy.

[0044] The technical solution of this invention involves obtaining an environmental detection command corresponding to the vehicle to be detected; detecting the area to be detected corresponding to the vehicle to be detected according to the environmental detection command to determine environmental image information, which includes at least one acquisition type and real-time environmental information corresponding to each acquisition type; identifying at least one environmental feature based on the environmental image information; and determining the vehicle location information corresponding to the vehicle to be detected based on each environmental feature. By determining the vehicle location information through multi-dimensional data, the accuracy of vehicle location information generation is improved.

[0045] Example 2

[0046] Figure 2 This is a flowchart illustrating a vehicle location information generation method according to Embodiment 2 of the present invention. Based on the above embodiments, this embodiment optimizes and improves the vehicle location information generation operation.

[0047] Furthermore, the process of "detecting the area to be detected corresponding to the vehicle to be detected according to the environmental detection command, and determining the environmental image information, which includes at least one acquisition type and the real-time environmental information corresponding to each acquisition type" is refined to "determining at least one acquisition type and the acquisition duration corresponding to each acquisition type according to the environmental detection command; for each acquisition type, acquiring images of the area to be detected according to the acquisition device corresponding to the acquisition type within the acquisition duration, and obtaining the real-time environmental information corresponding to the acquisition type" to improve the operation of vehicle location information generation.

[0048] It should be noted that for parts not described in detail in the embodiments of the present invention, please refer to the descriptions in other embodiments.

[0049] See Figure 2 The method for generating vehicle location information shown includes:

[0050] S201. Obtain the environmental detection command corresponding to the vehicle to be tested.

[0051] S202. Based on the environmental monitoring instructions, determine at least one collection type and the collection duration corresponding to each collection type.

[0052] The collection duration can be the length of time for collecting environmental information of the vehicle to be tested, according to the collection type.

[0053] Specifically, the environment detection command includes collection rules for the user's current time requirements. These rules may differ for different time periods. After the user interacts with the page provided on the user terminal, the collection rules for the user's current time requirements are determined based on the interaction information. Based on the collection rules information contained in the environment detection command, at least one collection type and its corresponding collection duration are determined. The environment detection command may include at least one collection type. There is a one-to-one correspondence between collection types and collection durations. A mapping relationship between collection types and collection durations can be preset, and the collection type is searched within this mapping relationship to determine its corresponding collection duration. Search methods include, but are not limited to, sequential search algorithms, binary search algorithms, hash search algorithms, or tree table search algorithms; this embodiment of the invention does not impose any limitations on these methods.

[0054] S203. For each acquisition type, the acquisition device corresponding to the acquisition type acquires images of the area to be detected within the acquisition time to obtain the real-time environmental information corresponding to the acquisition type.

[0055] Among them, the data acquisition equipment can be a device that collects environmental information of the area to be detected.

[0056] Specifically, there must be at least one acquisition type. The acquisition type can be either image acquisition or video acquisition. Different acquisition types may correspond to different acquisition device models, quantities, or functions. The acquisition duration for video acquisition is longer than that for image acquisition. For each acquisition type, at least one acquisition device with a preset mapping relationship to the acquisition type is acquired. Based on the acquisition duration of each acquisition device corresponding to the acquisition type, images of the area to be detected are acquired, resulting in real-time environmental information corresponding to the acquisition type.

[0057] S204. Based on the environmental image information, identify at least one environmental feature.

[0058] S205. Based on the environmental characteristics, determine the vehicle location information corresponding to the vehicle to be detected.

[0059] This invention, through environmental detection instructions, determines at least one acquisition type and the acquisition duration corresponding to each acquisition type; for each acquisition type, the acquisition device corresponding to the acquisition type acquires images of the area to be detected within the acquisition duration to obtain real-time environmental information corresponding to the acquisition type. Different acquisition methods are used to acquire image information for different acquisition types, refining the steps of image information acquisition and improving the accuracy of image information acquisition.

[0060] Optionally, based on the environmental detection instructions, at least one collection type and the collection duration corresponding to each collection type are determined, including: performing word segmentation processing based on the environmental detection instructions to determine word segmentation information, which includes: at least one instruction word segmentation; for each instruction word segmentation, matching the instruction word segmentation with each sample type in the preset instruction library to determine the collection type; and querying the collection duration corresponding to the collection type based on the collection type.

[0061] The word segmentation information can be a set of words obtained after processing the environmental detection command. Command word segmentation can be words obtained after processing the environmental detection command. The preset command library can be a database that stores the pre-set mapping relationship between command word segmentation and the corresponding collection type.

[0062] Specifically, environmental detection commands (such as "take an infrared photo of the front of the car, then record a 10-second side video") are broken down into their smallest semantic units (words or phrases) to extract key information. The resulting "command segments" typically include actions (such as "take" and "record"), the object of collection (such as "infrared photo" and "side video"), parameters (such as "10 seconds"), and location (such as "front of the car" and "side"). Meaningless words (such as "of" and "again") are filtered out, retaining only the core segments. The broken command segments are compared with the mapping information in the preset command library to identify the user's desired collection type (such as image or video). Based on the determined collection type, the collection duration is obtained from the preset "collection type - collection duration" (if no collection duration corresponding to the collection type is found, the preset default value is used as the collection duration corresponding to the collection type).

[0063] By performing word segmentation processing based on environmental detection instructions, word segmentation information is determined, including: at least one instruction word segmentation; for each instruction word segmentation, the instruction word segmentation is matched with each sample type in the preset instruction library to determine the collection type; the collection duration corresponding to the collection type is obtained by querying based on the collection type. The collection type can be determined through multi-dimensional data, which improves the accuracy of collection type determination.

[0064] Optionally, before acquiring the image of the area to be detected by the acquisition device corresponding to the acquisition type within the acquisition time to obtain the real-time environmental information corresponding to the acquisition type, the method further includes: obtaining the current light intensity and light intensity threshold corresponding to the vehicle to be detected; comparing the current light intensity with the light intensity threshold to determine the threshold comparison result; if the threshold comparison result is determined to be that the current light intensity is less than or equal to the light intensity threshold, then the infrared device is determined as the acquisition device; if the threshold comparison result is determined to be that the current light intensity is greater than the light intensity threshold, then the visible light device is determined as the acquisition device.

[0065] Specifically, the current light intensity corresponding to the vehicle under test can be obtained through a light sensor, and a pre-set light intensity threshold can be determined. The current light intensity is compared with the light intensity threshold to obtain a threshold comparison result. If the threshold comparison result shows that the current light intensity is less than or equal to the light intensity threshold, it indicates that the ambient light is low. In this case, an infrared device corresponding to the acquisition type is selected as the acquisition device, because infrared devices can better capture image information in low-light or no-light environments. If the threshold comparison result shows that the current light intensity is greater than the light intensity threshold, it indicates that the ambient light is sufficient. In this case, a visible light device corresponding to the acquisition type is selected as the acquisition device, as visible light devices can provide clear images under normal lighting conditions.

[0066] By acquiring the current light intensity and light intensity threshold corresponding to the vehicle to be detected, comparing the current light intensity with the light intensity threshold, and determining the threshold comparison result, if the threshold comparison result is that the current light intensity is less than or equal to the light intensity threshold, then the infrared device is determined as the acquisition device; if the threshold comparison result is that the current light intensity is greater than the light intensity threshold, then the visible light device is determined as the acquisition device. Different acquisition devices are used for different lighting conditions, thereby improving the accuracy of environmental information acquisition.

[0067] Optionally, based on various environmental characteristics, determine the vehicle location information corresponding to the vehicle to be detected, including: for each environmental characteristic, determine the characteristic object and the relative distance between the characteristic object and the vehicle to be detected; obtain map information corresponding to the area to be detected; determine the object position coordinates corresponding to the characteristic object based on the map information; and determine the vehicle location information corresponding to the vehicle to be detected based on the object position coordinates and relative distance.

[0068] Specifically, for each environmental feature, "feature objects" with positioning value (such as fixed landmarks, parking space numbers, or surrounding stationary vehicles) are selected from the identified environmental features, and the distance and directional relationship between these objects and the vehicle to be detected is calculated. Fixed objects that can be marked on the map (such as parking lot pillars, wall markings, parking space number signs, or fire hydrants) or identifiable temporary fixed objects (such as vehicles parked nearby) can be prioritized. Relative distance can be achieved through vehicle-side sensors (such as camera depth-of-field algorithms, ultrasonic radar, or lidar). For example, if a camera captures a pillar marked "C-05" 10 meters ahead, the relative distance is calculated to be 10 meters, and the direction is directly ahead, based on the pillar's size, pixel ratio, and camera focal length. High-precision map data of the vehicle parking area (such as parking lot maps or community ground parking space maps) is retrieved; the map must include pre-marked locations of the feature objects or objects associated with them. Based on map information, determine the coordinates of the corresponding feature objects. Based on these coordinates and relative distances, determine the vehicle's position. This involves assigning the vehicle's position, at least one feature object, and the relative distances between each feature object. This process establishes the vehicle's position information.

[0069] By targeting various environmental features, the system determines the feature objects and their relative distances to the vehicles under test; acquires map information corresponding to the area to be tested; determines the object position coordinates corresponding to the feature objects based on the map information; and determines the vehicle position information corresponding to the vehicles under test based on the object position coordinates and relative distances. By using multi-dimensional data to determine vehicle position information, the comprehensiveness of vehicle position information is improved.

[0070] Optionally, after identifying at least one environmental feature based on the environmental image information, the method further includes: performing anomaly detection on each environmental feature and determining the anomaly detection result; if the anomaly detection result is that no anomaly was detected, then determining the vehicle location information corresponding to the vehicle to be detected based on each environmental feature; if the anomaly detection result is that an anomaly was detected, then determining the alarm operation based on the detection result and issuing an alarm according to the alarm operation.

[0071] Specifically, by using preset rules or algorithms, the system can analyze whether the identified environmental features are inconsistent with normal conditions (such as abnormal objects, abnormal object states, or sudden environmental changes) to determine if there are any security risks. Anomaly types include: Object anomalies: such as the sudden appearance of strangers, suspicious items (such as an unextinguished fire), or collision marks (such as dents on a vehicle); State anomalies: such as sudden movement of surrounding vehicles (abnormal departure), abnormal opening of barriers / access control systems, or sudden changes in light (such as a sudden bright light appearing next to a vehicle at night); Feature loss: such as the sudden disappearance of previously existing fixed landmarks (such as parking space signs) (possibly due to obstruction or vehicle movement). Detection logic: The system uses a preset normal environmental feature library (such as the normal environment when a vehicle is parked: static objects, no strangers, and no obvious traces). It compares the real-time identified environmental features with the data in the library. If no anomalies are detected, the vehicle's surrounding environment is considered safe, and the vehicle's location can be further estimated using environmental features (such as combining parking space numbers and pillar coordinates to determine the specific parking point). If an anomaly is detected, an alarm is triggered to alert the user or relevant parties. Alarm operation types: Mild alarm: If there are people moving slowly next to the vehicle (not suspicious behavior), push an alert to the user's APP saying "People are active nearby"; Moderate alarm: If a minor collision is detected (vibration of the vehicle body or displacement of surrounding objects is detected by the camera), push an alarm message with real-time pictures / videos and location coordinates; Severe alarm: If a stranger is found to be prying open the car door or there is an open flame nearby, immediately trigger an audible and visual alarm (vehicle horn or flashing lights), simultaneously make a phone call to the user / send an emergency text message, and link with the parking lot security system (push the abnormal location to the security guard).

[0072] Anomaly detection is performed on various environmental features to determine the anomaly detection result. If the anomaly detection result is no anomaly detected, the vehicle location information corresponding to the vehicle to be detected is determined based on the environmental features. If the anomaly detection result is an anomaly detected, an alarm operation is determined based on the detection result, and an alarm is issued according to the alarm operation. Different operations are performed for different anomaly detection results, which refines the anomaly detection steps and improves the accuracy of anomaly detection.

[0073] Optionally, obtaining the environmental detection command corresponding to the vehicle to be detected includes: obtaining user input information, including: collection type, collection duration and collection angle range; obtaining motion detection information, including: at least one moving target and the moving speed corresponding to each moving target; and generating the environmental detection command corresponding to the vehicle to be detected based on the user input information and the motion detection information.

[0074] Specifically, the user-input type, duration, and angle range of the data collection can be obtained through a human-computer interaction interface on the user end, such as a touchscreen or voice input. For example, a user might select "video" as the data collection type, "60 seconds" as the duration, and "120 degrees in front" as the angle range via a touchscreen. The vehicle's motion detection function is used to acquire motion detection information, including at least one moving target and its corresponding speed. For example, the camera detects a car and a pedestrian ahead, measuring the car's speed at 30 km / h and the pedestrian's speed at 5 km / h. If user input is present, an environmental detection command is generated based on it. If no user input is present but motion detection information is available, an environmental detection command is generated based on the speed and number of moving objects in the motion detection information. Specifically, the larger the number of moving targets, the longer the data collection duration; the greater the speed, the higher the data collection type (video). If neither user input nor motion detection information is available, no environmental detection command is generated at that time.

[0075] By acquiring user input information, including the acquisition type, acquisition duration, and acquisition angle range; acquiring motion detection information, including at least one moving target and the corresponding moving speed of each moving target; and generating environmental detection commands for the vehicle to be detected based on the user input information and motion detection information, the environmental detection commands can be obtained through human interaction or triggered by changes in the surrounding environment, thus improving the comprehensiveness of command generation.

[0076] Example 3

[0077] Figure 3 This is a schematic diagram of a vehicle location information generation device according to Embodiment 3 of the present invention. This embodiment of the present invention is applicable to situations involving vehicle location information generation. The device can execute a vehicle location information generation method and can be implemented in hardware and / or software.

[0078] See Figure 3 The vehicle location information generation device shown includes: an instruction acquisition module 301, an area detection module 302, a feature acquisition module 303, and an information determination module 304, wherein...

[0079] The instruction acquisition module 301 is used to acquire the environmental detection instruction corresponding to the vehicle to be detected.

[0080] The area detection module 302 is used to detect the area to be detected corresponding to the vehicle to be detected according to the environmental detection command, and to determine the environmental image information. The environmental image information includes: at least one acquisition type and the real-time environmental information corresponding to each acquisition type.

[0081] The feature acquisition module 303 is used to identify at least one environmental feature based on environmental image information;

[0082] The information determination module 304 is used to determine the vehicle location information corresponding to the vehicle to be detected based on various environmental characteristics.

[0083] The technical solution of this invention involves obtaining an environmental detection command corresponding to the vehicle to be detected; detecting the area to be detected corresponding to the vehicle to be detected according to the environmental detection command to determine environmental image information, which includes at least one acquisition type and real-time environmental information corresponding to each acquisition type; identifying at least one environmental feature based on the environmental image information; and determining the vehicle location information corresponding to the vehicle to be detected based on each environmental feature. By determining the vehicle location information through multi-dimensional data, the accuracy of vehicle location information generation is improved.

[0084] Optionally, the area detection module 302 includes:

[0085] The information collection determination unit is used to determine at least one collection type and the collection duration corresponding to each collection type according to the environmental monitoring instructions.

[0086] The image acquisition unit is used to acquire images of the area to be detected within the acquisition time according to the acquisition device corresponding to each acquisition type, so as to obtain the real-time environmental information corresponding to the acquisition type.

[0087] Optionally, the information collection and determination unit is specifically used for:

[0088] The environmental detection instructions are used for word segmentation to determine the word segmentation information, which includes at least one instruction word segmentation.

[0089] For each instruction, the segmented words are matched with the sample types in the preset instruction library to determine the collection type;

[0090] The collection duration corresponding to the collection type can be obtained by querying the collection type.

[0091] Optionally, the area detection module 302 is also specifically used for:

[0092] Before acquiring images of the area to be detected by the acquisition device corresponding to the acquisition type within the acquisition time, and obtaining the real-time environmental information corresponding to the acquisition type, the current light intensity and light intensity threshold of the vehicle to be detected are obtained.

[0093] Compare the current light intensity with the light intensity threshold to determine the threshold comparison result;

[0094] If the threshold comparison result is that the current light intensity is less than or equal to the light intensity threshold, then the infrared device is identified as the acquisition device.

[0095] If the threshold comparison result shows that the current light intensity is greater than the light intensity threshold, then the visible light device is identified as the acquisition device.

[0096] Optionally, the information determination module 304 is specifically used for:

[0097] For each environmental characteristic, determine the characteristic object and the relative distance between the characteristic object and the vehicle to be detected based on the environmental characteristics;

[0098] Obtain map information corresponding to the area to be detected;

[0099] Based on the map information, determine the coordinates of the object location corresponding to the feature object;

[0100] Based on the object's position coordinates and relative distance, determine the vehicle position information corresponding to the vehicle to be detected.

[0101] Optionally, the vehicle location information generating device is also specifically used for:

[0102] After identifying at least one environmental feature based on environmental image information, anomaly detection is performed on each environmental feature to determine the anomaly detection result.

[0103] If the anomaly detection result is no anomaly detected, then the vehicle location information corresponding to the vehicle to be detected is determined based on each environmental characteristic.

[0104] If the anomaly detection result indicates that an anomaly has been detected, then the alarm action is determined based on the detection result, and the alarm is issued in accordance with the alarm action.

[0105] Optionally, the instruction acquisition module 301 is specifically used for:

[0106] Acquire user input information, including: collection type, collection duration, and collection angle range;

[0107] Acquire motion detection information, which includes: at least one moving target and the corresponding moving speed of each moving target;

[0108] Based on user input and mobile detection information, generate environmental detection instructions corresponding to the vehicle to be detected.

[0109] The vehicle location information generation device provided in this embodiment of the invention can execute the vehicle location information generation method provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of executing the vehicle location information generation method.

[0110] Example 4

[0111] Figure 4A schematic diagram of the structure of a vehicle location information generation device 400 that can be used to implement embodiments of the present invention is shown.

[0112] like Figure 4 As shown, the vehicle location information generation device 400 includes at least one processor 401 and a memory, such as a read-only memory (ROM) 402 and a random access memory (RAM) 403, communicatively connected to the at least one processor 401. The memory stores computer programs executable by the at least one processor. The processor 401 can perform various appropriate actions and processes based on the computer program stored in the ROM 402 or loaded into the RAM 403 from the storage unit 408. The RAM 403 can also store various programs and data required for the operation of the vehicle location information generation device 400. The processor 401, ROM 402, and RAM 403 are interconnected via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0113] Multiple components in the vehicle location information generation device 400 are connected to the I / O interface 405, including: an input unit 406, such as a keyboard, mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, optical disk, etc.; and a communication unit 409, such as a network card, modem, wireless communication transceiver, etc. The communication unit 409 allows the vehicle location information generation device 400 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0114] Processor 401 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 401 performs the various methods and processes described above, such as vehicle location information generation methods.

[0115] In some embodiments, the vehicle location information generation method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the vehicle location information generation device 400 via ROM 402 and / or communication unit 409. When the computer program is loaded into RAM 403 and executed by processor 401, one or more steps of the vehicle location information generation method described above may be performed. Alternatively, in other embodiments, processor 401 may be configured to perform the vehicle location information generation method by any other suitable means (e.g., by means of firmware).

[0116] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0117] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0118] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0119] To provide user interaction, the systems and techniques described herein can be implemented on a vehicle location information generation device, which includes: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the vehicle location information generation device. Other types of devices can also be used to provide user interaction; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0120] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0121] A computing system can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system. It addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability.

[0122] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0123] 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 be made according to 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 vehicle position information generation method characterized by comprising: The method comprises: acquiring an environment detection instruction corresponding to a vehicle to be detected; detecting a detection area corresponding to the vehicle to be detected according to the environment detection instruction, determining environment image information, wherein the environment image information comprises at least one collection type and real-time environment information corresponding to each collection type; identifying at least one environment feature according to the environment image information; determining vehicle position information corresponding to the vehicle to be detected according to each environment feature.

2. The method of claim 1, wherein, The detection of the detection area corresponding to the vehicle to be detected according to the environment detection instruction, the determination of the environment image information, and the environment image information comprising at least one collection type and real-time environment information corresponding to each collection type, comprises: determining at least one collection type and the collection duration corresponding to each collection type according to the environment detection instruction; for each collection type, collecting images of the detection area within the collection duration by a collection device corresponding to the collection type, to obtain real-time environment information corresponding to the collection type.

3. The method of claim 2, wherein, The determination of at least one collection type and the collection duration corresponding to each collection type according to the environment detection instruction comprises: performing word segmentation processing according to the environment detection instruction to determine word segmentation information, wherein the word segmentation information comprises at least one instruction word segment; for each instruction word segment, matching the instruction word segment with each sample type in a preset instruction library to determine a collection type; querying the collection duration corresponding to the collection type according to the collection type.

4. The method of claim 2, wherein, Before the image collection of the detection area within the collection duration by the collection device corresponding to the collection type to obtain the real-time environment information corresponding to the collection type, the method further comprises: acquiring a current light intensity corresponding to the vehicle to be detected and a light intensity threshold value; comparing the current light intensity with the light intensity threshold value to determine a threshold comparison result; when it is determined that the threshold comparison result is that the current light intensity is less than or equal to the light intensity threshold value, determining an infrared device as the collection device; when it is determined that the threshold comparison result is that the current light intensity is greater than the light intensity threshold value, determining a visible light device as the collection device.

5. The method of claim 1, wherein, The determination of the vehicle position information corresponding to the vehicle to be detected according to each environment feature comprises: for each environment feature, determining a feature object and a relative distance between the feature object and the vehicle to be detected according to the environment feature; acquiring map information corresponding to the detection area; determining object position coordinates corresponding to the feature object according to the map information; determining the vehicle position information corresponding to the vehicle to be detected according to the object position coordinates and the relative distance.

6. The method of claim 1, wherein, After the identification of at least one environment feature according to the environment image information, the method further comprises: performing anomaly detection on each environment feature to determine an anomaly detection result; if the anomaly detection result is that no anomaly is detected, determining the vehicle position information corresponding to the vehicle to be detected according to each environment feature; If the abnormality detection result is that an abnormality is detected, an alarm operation is determined according to the detection result, and an alarm is performed according to the alarm operation.

7. The method of claim 1, wherein, The environment detection instruction corresponding to the vehicle to be detected is obtained, and the environment detection instruction includes: The user input information includes a collection type, a collection time length, and a collection angle range. The movement detection information includes at least one movement target and a movement speed corresponding to each movement target. The environment detection instruction corresponding to the vehicle to be detected is obtained according to the user input information and the movement detection information.

8. A vehicle position information generating apparatus characterized by comprising: The device includes: An instruction obtaining module configured to obtain an environment detection instruction corresponding to a vehicle to be detected; An area detection module configured to detect a to-be-detected area corresponding to the vehicle to be detected according to the environment detection instruction, and determine environment image information, the environment image information including at least one collection type and real-time environment information corresponding to each collection type; A feature obtaining module configured to identify at least one environment feature according to the environment image information; An information determining module configured to determine vehicle position information corresponding to the vehicle to be detected according to each environment feature.

9. A vehicle position information generating apparatus characterized by comprising: The vehicle position information generation device includes: At least one processor; and a memory connected to the at least one processor in communication; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the vehicle position information generation method in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to enable the processor to execute the vehicle position information generation method in any one of claims 1-7 when executed.

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