Application method of parking map data

Abstract

The invention discloses a parking map data application method, which relates to the technical field of G6PD detection, and comprises the following steps: S1, data information acquisition; s2, data processing; s3, verifying the coordinates; s4, updating the data; and S5, a vehicle central control system. According to the parking map data application method, multi-azimuth parking map basic data acquisition is realized through vehicle inspection environment acquisition and manual measurement information acquisition, data processing is utilized to conveniently calculate accurate geographic coordinates of parking spaces, and meanwhile, the specific position of a target parking vehicle is acquired on the basis of a real-time positioning system, so that the accuracy of parking is improved. The method comprises the following steps: acquiring real-time vehicle positions, planning a parking path, acquiring parking data of a target parking lot through acquired data information, taking the acquired real-time vehicle positions, the real-time parking path and the real-time parking spaces as a parking map, and through coordinate verification, comparing parking coordinates again and ensuring accurate geographic coordinates of the parking spaces.

Description

Technical Field

[0001] The present invention relates to the technical field of parking maps, and in particular to an application method of parking map data. Background Art

[0002] For automatic parking products, high-precision self-positioning of the vehicle is a crucial function, and a reliable parking map is a prerequisite for providing positioning. In order to navigate the vehicle from the road into the parking lot and accurately park in the planned area of ​​the parking lot, the parked vehicle needs an accurate parking map.

[0003] However, there is a deviation between the existing parking map data and the actual parking map, and the data is not accurate enough, which makes it difficult to park in the actual planned area when using the parking map to control the vehicle intelligent parking, affecting the parking order.

[0004] Therefore, in view of this, the existing structure and defects are studied and improved, and an application method of parking map data is proposed. Summary of the invention

[0005] In view of the deficiencies of the prior art, the present invention provides a method for applying parking map data, which solves the problems raised in the above-mentioned background technology.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for applying parking map data, the method for applying parking map data comprising the following operating steps:

[0007] S1. Data information collection:

[0008] Information is collected through installed sensors, environmental inspections by vehicles, and manual measurements;

[0009] S2. Data processing:

[0010] Use GPS to correct data, extract features from the acquired data information, and then use the sensor fusion algorithm to combine GPS and sensor data to calculate the precise geographic coordinates of the parking space. Based on the real-time positioning system, obtain the specific location of the target parking vehicle, plan the parking path, and obtain the parking data of the target parking lot through the collected data information. Use the acquired real-time vehicle location, real-time parking path, and real-time parking space as a parking map;

[0011] S3. Coordinate verification:

[0012] Verify the accuracy of the calculated coordinates through field tests and compare the calculated data;

[0013] S4. Data update:

[0014] By using IoT technology, the real-time update and transmission of parking space coordinates can be achieved. At the same time, periodic inspections are carried out to regularly re-inspect the parking areas and update coordinate information that may have changed.

[0015] S5. Vehicle central control system:

[0016] The parking map is archived in the vehicle's central control module and is updated in real time based on data from the Internet of Things. The matching degree between the parking map and the real-time updated map is determined, and the parking map of the vehicle at the current real-time location is obtained, thereby obtaining the parking path of the parking location. When the target parking vehicle parks, the real-time updated parking space coordinate information is transmitted to the vehicle's central control module to match the real-time updated map with the parking map, select the vehicle's parking path with a suitable path, plan the vehicle's starting point, select the target parking space, and control the vehicle to park intelligently.

[0017] Furthermore, in step S1, sensor information collection is specifically performed by installing sensors such as GPS, cameras, and lidar on vehicles or fixed infrastructure (street lights or buildings).

[0018] Furthermore, in step S1, vehicle inspection environment collection specifically involves regular inspection of the target area using a sensor-equipped vehicle to collect environmental data around the parking area, and manual measurement information collection specifically involves manual measurement using high-precision GPS equipment for specific areas.

[0019] Furthermore, in step S2, the GPS data correction data is performed by using differential GPS technology or other sensor data to provide GPS positioning accuracy.

[0020] Furthermore, in step S2, the feature extraction of the data information is specifically to extract features related to the parking space, such as edges, signs, etc., from the camera and LiDAR data.

[0021] Furthermore, in step S3, the calculated data is compared by comparing and correcting the calculated coordinates with the existing high-precision map data.

[0022] Furthermore, the LiDAR is used to accurately measure distances and construct three-dimensional environmental maps.

[0023] Furthermore, in step S4, an embedded computing platform is used for real-time sensor data, and the algorithm software used in steps S3 and S4 are sensor fusion algorithm, image processing algorithm and coordinate calculation algorithm.

[0024] Furthermore, in step S4, the re-inspection specifically includes inspecting the target area using a sensor vehicle to collect environmental data around the parking area, and the manual measurement information collection specifically includes manually measuring a specific area using a high-precision GPS device.

[0025] The present invention provides a method for applying parking map data, which has the following beneficial effects:

[0026] 1. The application method of the parking map data collects the basic data of the parking map from multiple directions through the information collection of the installed sensors, the vehicle inspection environment, and the manual measurement information collection, and uses the data processing to process the data, so as to calculate the precise geographic coordinates of the parking space, and at the same time obtain the specific position of the target parking vehicle based on the real-time positioning system, plan the parking path, obtain the parking data of the target parking lot through the collected data information, and use the obtained real-time vehicle position, real-time parking path and real-time parking space as the parking map, and verify the coordinates to compare the parking coordinates again to ensure the precise geographic coordinates of the parking space, and in addition, through the data updating technology, it is convenient to obtain the coordinate changes of the parking area in real time, which is conducive to the real-time transmission of the updated parking coordinate information to the vehicle control module, so as to match the real-time updated map with the parking map, select the vehicle parking path of the appropriate path, plan the vehicle starting point, select the target parking space, control the vehicle to park intelligently, and avoid errors between the parking vehicle and the actual vehicle parking division area during intelligent parking, which affects the subsequent parking of other vehicles. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 A schematic diagram of the overall steps of a parking map data application method of the present invention;

[0028] Figure 2 The present invention is a schematic diagram of a specific operation flow of a method for applying parking map data. DETAILED DESCRIPTION

[0029] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0030] like Figure 1-Figure 2 As shown, the present invention provides a technical solution: a method for applying parking map data, the method for applying parking map data includes the following steps:

[0031] The method for applying parking map data includes the following steps:

[0032] S1. Data information collection:

[0033] Information is collected through installed sensors, collected through vehicle inspection environment, and collected through manual measurement. In step S1, sensor information collection specifically includes installing GPS, cameras, lidar and other sensors on vehicles or fixed infrastructure (street lights or buildings). In step S1, vehicle inspection environment collection specifically includes using the equipped sensor vehicle to conduct regular inspections of the target area and collect environmental data around the parking area. Manual measurement information collection specifically includes the need to manually use high-precision GPS equipment to measure specific areas. Information is collected through installed sensors, collected through vehicle inspection environment, and collected through manual measurement to realize the collection of basic data of parking maps from all directions.

[0034] S2. Data processing:

[0035] GPS is used to perform data correction, and features are extracted from the acquired data information. Then, a sensor fusion algorithm is used to combine GPS and sensor data to calculate the precise geographic coordinates of the parking space. The specific location of the target parking vehicle is obtained based on the real-time positioning system, and a parking path is planned. The parking data of the target parking lot is obtained through the collected data information, and the acquired real-time vehicle location, real-time parking path, and real-time parking space are used as a parking map. In step S2, GPS performs data correction data to provide the accuracy of GPS positioning through differential GPS technology or other sensor data. In step S2, data information performs feature extraction, specifically extracting features related to the parking space from the camera and LiDAR data, such as sidelines, signs, etc. LiDAR is used to accurately measure distances and build three-dimensional environmental maps;

[0036] S3. Coordinate verification:

[0037] The accuracy of the calculated coordinates is verified by field testing, and the calculated data is compared. In step S3, the calculated data is compared and corrected by comparing the calculated coordinates with the existing high-precision map data.

[0038] S4. Data update:

[0039] The Internet of Things technology is used to realize real-time updating and transmission of parking space coordinates, and periodic inspections are carried out at the same time. The parking area is re-inspected regularly to update the coordinate information that may change. In step S4, an embedded computing platform is used for real-time sensor data. The algorithm software used in steps S3 and S4 is a sensor fusion algorithm, an image processing algorithm and a coordinate calculation algorithm. In step S4, the re-inspection is specifically to inspect the target area using a sensor vehicle equipped to collect environmental data around the parking area. Manual measurement information collection is specifically for specific areas. It is necessary to manually use high-precision GPS equipment for measurement, so as to obtain more accurate information around the actual parking area, avoid the phenomenon that there is a large deviation between the actual parking map and the real-time map, and make up for the lack of data information.

[0040] S5. Vehicle central control system:

[0041] The parking map is archived in the vehicle central control module and is updated in real time based on the data of the Internet of Things. The matching degree between the parking map and the real-time updated map is determined, and the parking map of the vehicle at the current real-time position is obtained, thereby obtaining the parking path of the parking position. When the target parking vehicle is parked, the parking space coordinate information updated in real time is transmitted to the vehicle central control module to match the real-time updated map with the parking map, select the vehicle parking path with a suitable path, plan the vehicle starting point, select the target parking space, and control the vehicle to park intelligently. In addition, through data updating technology, it is convenient to obtain the coordinate changes of the parking area in real time, which is conducive to the real-time transmission of the updated parking coordinate information to the vehicle control module, to match the real-time updated map with the parking map, select the vehicle parking path with a suitable path, plan the vehicle starting point, select the target parking space, and control the vehicle to park intelligently, so as to avoid errors in the parking vehicle and the actual vehicle parking area division during intelligent parking, which affects the subsequent parking of other vehicles.

[0042] In summary, the application method of the parking map data is to collect parking data when it is used, and collect information through installed sensors. The sensor information collection is specifically to install GPS, cameras, lidar and other sensors on vehicles or fixed infrastructure (street lights or buildings). Vehicle inspection environment collection is specifically to use the equipped sensor vehicles to conduct regular inspections of the target area and collect environmental data around the parking area. Manual measurement information collection is specifically for specific areas. It is necessary to use high-precision GPS equipment for manual measurement. Through the installed sensor information collection, vehicle inspection environment collection, and manual measurement information collection, the basic data of the parking map is collected from all directions. After data collection, GPS is used for data correction, and feature extraction is performed on the acquired data information. Then, the sensor fusion algorithm is used to combine GPS and sensor data to calculate the precise geographic coordinates of the parking space, and the specific location of the target parking vehicle is obtained based on the real-time positioning system to plan parking. Path, obtain the parking data of the target parking lot through the collected data information, and use the acquired real-time vehicle position, real-time parking path and real-time parking space as the parking map. GPS performs data correction data to provide GPS positioning accuracy through differential GPS technology or other sensor data. Data information performs feature extraction, specifically extracting features related to parking spaces from camera and LiDAR data, such as edges, signs, etc. LiDAR is used to accurately measure distances and build three-dimensional environmental maps. The above is used to obtain parking maps and real-time parking maps. Then, the Internet of Things technology is used to realize real-time update and transmission of parking space coordinates. In addition, periodic inspections are carried out to re-inspect the parking area regularly to update the coordinate information that may change. An embedded computing platform is used for real-time sensor data. At the same time, sensor fusion algorithms, image processing algorithms and coordinate calculation algorithms are used to analyze and process the acquired data. The processed data is a real-time parking map and a parking map.

[0043] The parking map is archived in the vehicle central control module and updated in real time based on the data of the Internet of Things. The matching degree between the parking map and the real-time updated map is determined, and the parking map of the vehicle at the current real-time position is obtained, so as to obtain the parking path of the parking position. When the target parking vehicle is parked, the real-time updated parking space coordinate information is transmitted to the vehicle central control module to match the real-time updated map with the parking map, select the vehicle parking path with a suitable path, plan the vehicle starting point, select the target parking space, and control the vehicle to park intelligently. Secondly, the re-inspection is specifically to inspect the target area with the equipped sensor vehicle, collect the surrounding environment data of the parking area, and manually measure the information collection. For specific areas, it is necessary to manually use high-precision GPS equipment for measurement, so as to obtain more accurate information about the actual parking area and avoid large deviations between the actual parking map and the real-time map, which can make up for the lack of data information. In addition, through data update technology, it is convenient to obtain the coordinate changes of the parking area in real time, which is conducive to the real-time transmission of updated parking coordinate information to the vehicle control module, so as to match the real-time updated map with the parking map, select the vehicle parking path with a suitable path, plan the vehicle starting point, select the target parking space, and control the vehicle to park intelligently, so as to avoid errors in the parking area division between the parked vehicle and the actual vehicle during intelligent parking, which will affect the subsequent parking of other vehicles.

[0044] The embodiments of the present invention are given for the purpose of illustration and description, and are not intended to be exhaustive or to limit the invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

Claims

1. A method for applying parking map data, characterized in that: The parking map data application method comprises the following steps: S1. Data information collection: Information is collected through installed sensors, environmental inspections by vehicles, and manual measurements; S2. Data processing: Use GPS to correct data, extract features from the acquired data information, and then use the sensor fusion algorithm to combine GPS and sensor data to calculate the precise geographic coordinates of the parking space. Based on the real-time positioning system, obtain the specific location of the target parking vehicle, plan the parking path, and obtain the parking data of the target parking lot through the collected data information. Use the acquired real-time vehicle location, real-time parking path, and real-time parking space as a parking map; S3. Coordinate verification: Verify the accuracy of the calculated coordinates through field tests and compare the calculated data; S4. Data update: Use IoT technology to achieve real-time update and transmission of parking space coordinates, and conduct periodic inspections, regularly re-inspect parking areas, and update coordinate information that may have changed; S5. Vehicle central control system: The parking map is archived in the vehicle's central control module and is updated in real time based on data from the Internet of Things. The matching degree between the parking map and the real-time updated map is determined, and the parking map of the vehicle at the current real-time location is obtained, thereby obtaining the parking path of the parking location. When the target parking vehicle parks, the real-time updated parking space coordinate information is transmitted to the vehicle's central control module to match the real-time updated map with the parking map, select the vehicle's parking path with a suitable path, plan the vehicle's starting point, select the target parking space, and control the vehicle to park intelligently.

2. The parking map data application method according to claim 1, characterized in that: In step S1, sensor information collection specifically includes installing sensors such as GPS, cameras, and lidar on vehicles or fixed infrastructure (street lights or buildings).

3. The parking map data application method according to claim 1, characterized in that: In step S1, vehicle inspection environment collection specifically involves using a sensor-equipped vehicle to conduct regular inspections of the target area to collect environmental data around the parking area, and manual measurement information collection specifically involves manually using a high-precision GPS device to measure a specific area.

4. The parking map data application method according to claim 1, characterized in that: In step S2, the GPS data correction data is provided by differential GPS technology or other sensor data to improve the accuracy of GPS positioning.

5. The parking map data application method according to claim 1, characterized in that: In step S2, the feature extraction of the data information specifically involves extracting features related to the parking space, such as edges, signs, etc., from the camera and LiDAR data.

6. The parking map data application method according to claim 1, characterized in that: In step S3, the calculated data is compared specifically by comparing and correcting the calculated coordinates with the existing high-precision map data.

7. The parking map data application method according to claim 5, characterized in that: The LiDAR is used to accurately measure distances and build three-dimensional environmental maps.

8. The parking map data application method according to claim 1, characterized in that: In the step S4, an embedded computing platform is used for real-time sensor data, and the algorithm software used in the steps S3 and S4 are sensor fusion algorithm, image processing algorithm and coordinate calculation algorithm.

9. The parking map data application method according to claim 1, characterized in that: In step S4, the re-inspection specifically includes inspecting the target area using a sensor vehicle to collect environmental data around the parking area, and the manual measurement information collection specifically includes manually measuring a specific area using a high-precision GPS device.

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