Vehicle-mounted green vision rate acquisition control method and system based on planned route

Abstract

The invention relates to a vehicle-mounted green vision rate acquisition control method and system based on a planned route, and is applied to image acquisition equipment installed on an acquisition vehicle, and the acquisition control method comprises the steps: obtaining a starting point coordinate of a to-be-acquired road section of a target green vision rate acquisition region; initializing exposure parameters and equipment control parameters of the image acquisition equipment; calculating a first distance between the current position coordinate of the collected vehicle and the starting point coordinate of the to-be-collected road section; judging whether the first distance is greater than a first preset distance threshold; if yes, dynamically adjusting the calculation frequency of the first distance; if not, sending an exposure starting control instruction to the image acquisition equipment; calculating a second distance between the current position coordinate and the end point coordinate of the current collection road section; judging whether the second distance is greater than a second preset distance threshold; and if not, sending an exposure closing instruction to the image acquisition equipment, and marking the current acquisition road section as an acquired road section. According to the invention, efficient and accurate green vision rate data acquisition can be realized.

Description

Technical Field

[0001] The present application relates to the technical field of automated data collection, and in particular to a vehicle-mounted green view rate collection and control method and system based on a planned route. Background Art

[0002] With the acceleration of urbanization, the maintenance and evaluation of urban ecological environment has gradually become a key topic of social concern. As an important indicator to measure the quality of urban ecological environment, green view rate refers to the proportion of green plant coverage within the visual area, which directly reflects the greening degree and ecological health level of the urban area. In many fields such as urban planning and garden design, accurate collection of green view rate data is crucial for evaluating environmental quality and optimizing landscape layout.

[0003] In recent years, the green view rate collection method based on vehicle-mounted equipment has gradually emerged. By combining the image acquisition equipment with the collection vehicle and using computer-assisted control, data collection can be completed while the vehicle is driving. However, some current vehicle-mounted collection systems cannot achieve complete automatic control, especially in the identification of the starting and ending points of the road section. Operators are still required to operate the software to control the camera exposure. However, when the vehicle speed is fast or there are many sections to collect, it is easy to cause missed shots or repeated shots, thus affecting the accuracy of the green view rate data. Summary of the invention

[0004] In order to achieve efficient and accurate green view rate data collection, the present application provides a vehicle-mounted green view rate collection control method and system based on a planned route.

[0005] In a first aspect, the present application provides a vehicle-mounted green view rate acquisition control method based on a planned route, which adopts the following technical solution: A vehicle-mounted green view rate acquisition control method based on a planned route is applied to an image acquisition device installed on a acquisition vehicle, and the acquisition control method includes: Obtain the starting point coordinates of the road section to be collected in the target green view rate collection area; Initializing exposure parameters and device control parameters of the image acquisition device; Receiving the current position coordinates and current speed data of the collected vehicle; Calculating the distance between the current position coordinates and the starting point coordinates of the road section to be collected to obtain a first distance; Determine whether the first distance is greater than a first preset distance threshold; if so, dynamically adjust the calculation frequency of the corresponding first distance according to the first distance and the current speed data of the collected vehicle; If not, sending an exposure start control instruction to the image acquisition device, and determining the section to be acquired as the current acquisition section; Receiving in real time the road section image data collected by the image collection device on the current collection road section; Calculate the distance between the current position coordinates and the end point coordinates of the current collection section to obtain a second distance; Determine whether the second distance is greater than a second preset distance threshold; if not, send an exposure closing instruction to the image acquisition device, and mark the current acquisition section as a acquired section.

[0006] By adopting the above technical solution, based on the precise calculation of the real-time status of the collected vehicle (including position and speed), as well as the dynamic adjustment of the collection frequency and automatic exposure control, efficient and accurate green view rate data collection is achieved. It can not only flexibly adapt to complex environments and reduce human intervention, but also ensure the accurate matching of the collected images with the target road sections, while effectively optimizing computing resources and collection time, and has wide practicality and reliability.

[0007] Optionally, before the step of obtaining the starting point coordinates of the road section to be collected in the target green view rate collection area, the method further includes: Receiving coordinate data of a plurality of key nodes of the target green viewing rate acquisition area; Based on the preset route division rules, the roads between multiple key nodes are divided into multiple sections, and the corresponding planned route information is generated; Based on the planned route information, a plurality of the road sections are determined as road sections to be collected and a collection task list is generated.

[0008] By adopting the above technical solution, the key node data of the target area is received, the roads between the nodes are divided based on preset rules and the planning route information is generated. This technical solution divides the complex collection area into multiple independent sections, and manages each section in a structured manner to clarify the starting and ending information of the collection task. Then, by marking the sections to be collected and dynamically extracting the starting point coordinates, the system can achieve refined planning and automated execution of large-scale collection tasks.

[0009] Optionally, the planned route information includes the number, starting point coordinates and end point coordinates of each road section.

[0010] Optionally, the exposure parameters include exposure time, ISO value and aperture size, and the device control parameters include the first preset distance threshold and the second preset distance threshold.

[0011] Optionally, the step of initializing the exposure parameters of the image acquisition device includes: Acquire the current speed data and current ambient light data of the collected vehicle in real time; Based on a preset mapping relationship, corresponding exposure parameters are determined according to the current vehicle speed data and the current ambient light data.

[0012] By adopting the above technical solution, the vehicle speed data and ambient light data are acquired in real time, and the exposure parameters of the camera (including exposure time, ISO value and aperture) are determined in combination with the preset mapping relationship. This technical solution realizes the intelligent adaptive adjustment of the image acquisition device to the dynamic acquisition environment, and can effectively solve the problem of image blur or too dark caused by speed changes and diverse lighting conditions in traditional green view rate acquisition. At the same time, it reduces the complexity of manual parameter setting, improves acquisition efficiency, ensures the consistency of image acquisition quality in different environments, and provides reliable data support for green view rate evaluation.

[0013] Optionally, after the step of marking the current collection section as a collected section, the method further includes: Update the status information of the collected road section in the collection task list, and remove the collected road section from the collection task list; According to the updated collection task list, the next road section data to be collected is loaded in sequence and the road section image data collection step is executed cyclically until all the road sections to be collected are marked as collected sections, and the road section image data of all the road sections are obtained; The road section image data of all road sections are classified and stored according to the road section numbers to obtain a collection data report of the target green view rate collection area.

[0014] By adopting the above technical solutions, dynamic scheduling and efficient execution of collection tasks are achieved. From the removal of collected sections to the sequential loading of sections to be collected, and then to the cyclic execution of collection tasks, the system ensures the accuracy and consistency of tasks at each stage. Finally, through the dynamic update of the collection task list and the determination of the termination conditions, the image collection of all sections can be completed without human intervention, and a structured data report can be generated.

[0015] In the second aspect, the present application provides a vehicle-mounted green view rate acquisition and control system based on a planned route, which adopts the following technical solutions: A vehicle-mounted green view rate acquisition and control system based on a planned route is applied to an image acquisition device installed on a acquisition vehicle, and the acquisition and control system includes: An acquisition module is used to acquire the starting point coordinates of the road section to be collected in the target green view rate collection area; A parameter initialization module, used to initialize the exposure parameters and device control parameters of the image acquisition device; A receiving module, used for receiving the current position coordinates and current speed data of the collected vehicle; A first distance calculation module, used to calculate the distance between the current position coordinates and the starting point coordinates of the road section to be collected, to obtain a first distance; A first judgment module, used to judge whether the first distance is greater than a first preset distance threshold; if so, output a first judgment result; if not, output a second judgment result; a calculation frequency adjustment module, configured to dynamically adjust the calculation frequency of the corresponding first distance according to the first distance and the current speed data of the collected vehicle in response to the first judgment result; A control module, configured to send an exposure start control instruction to the image acquisition device in response to the second judgment result, and determine the section to be acquired as a current acquisition section; A receiving module, used for receiving in real time the road section image data collected by the image acquisition device on the current acquisition road section; A second distance calculation module, used to calculate the distance between the current position coordinates and the end point coordinates of the current collection section to obtain a second distance; A second judgment module, used to judge whether the second distance is greater than a second preset distance threshold; if not, output a third judgment result; The control module is further used to send an exposure closing instruction to the image acquisition device in response to the third judgment result, and mark the current acquisition section as a acquired section.

[0016] Optionally, the acquisition control system further includes: A coordinate data receiving module, used to receive coordinate data of multiple key nodes in the target green viewing rate acquisition area; A route planning module is used to divide the roads between multiple key nodes into multiple sections based on preset route division rules and generate corresponding planned route information; The collection task list generation module is used to determine the plurality of road sections as road sections to be collected and generate a collection task list based on the planned route information.

[0017] In a third aspect, the present application provides a computer device, which adopts the following technical solution: A computer device comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method as described in the first aspect.

[0018] In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the methods in the first aspect.

[0019] To summarize, the present application includes at least one of the following beneficial technical effects: the present application realizes the automatic exposure triggering and stopping of the vehicle-mounted image acquisition equipment during the vehicle driving process, completely getting rid of the need for manual intervention, significantly reducing the operation time and labor cost of green view rate acquisition, and greatly improving work efficiency. It is particularly suitable for application scenarios that require batch collection of road section data over a large range and multiple routes. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 This is a first flow chart of a vehicle-mounted green view rate acquisition control method based on a planned route in one of the embodiments of the present application.

[0021] Figure 2 This is a second flow chart of a vehicle-mounted green view rate acquisition control method based on a planned route in one of the embodiments of the present application.

[0022] Figure 3 It is a third flow chart of a vehicle-mounted green view rate acquisition control method based on a planned route in one of the embodiments of the present application.

[0023] Figure 4 It is a fourth flow chart of a vehicle-mounted green view rate acquisition control method based on a planned route according to one of the embodiments of the present application. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-4 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0025] The embodiment of the present application discloses a vehicle-mounted green view rate collection and control method based on a planned route.

[0026] Reference Figure 1 , a vehicle-mounted green view rate acquisition control method based on a planned route is applied to an image acquisition device installed on a acquisition vehicle, and the acquisition control method includes: Step S101, obtaining the starting point coordinates of the road section to be collected in the target green viewing rate collection area; Specifically, the target green view rate collection area is usually pre-set through a planned route file, which contains the starting and ending coordinates of multiple road sections. The system loads the planned route file and extracts the starting coordinates of the next section to be collected from the list to be collected to clarify the target section of the current collection task and provide an accurate starting point reference for subsequent automatic control.

[0027] Step S102, initializing exposure parameters and device control parameters of the image acquisition device; Among them, exposure parameters (such as ISO value, aperture size, and shutter speed) are the key to the image acquisition device taking clear images, and can be initially set according to the current vehicle speed data and ambient light data; the device control parameters include the starting trigger distance (the first preset distance threshold) and the end stop distance (the second preset distance threshold), which are used to define the start and stop conditions and logic of automatic control.

[0028] It is understandable that the initialization parameters can ensure that the device has appropriate shooting capabilities and control logic when the acquisition work starts, thereby improving acquisition efficiency and image quality.

[0029] It should be noted that the image acquisition device must have high resolution, dynamic parameter adjustment capabilities, and good environmental adaptability, and be able to achieve accurate shooting in environments where the vehicle is traveling at high speed or the light changes rapidly, thereby providing high-quality image data support for the green view rate acquisition in the planned route. In some embodiments, the image processing device can be a camera device with high-resolution shooting capabilities, or a high-definition industrial camera designed specifically for vehicles. Step S103, receiving and collecting the current position coordinates and current speed data of the vehicle; Among them, the real-time coordinates and speed of the current vehicle can be obtained through the GNSS module and the on-board speed sensor, and periodically transmitted to the control system for subsequent distance calculation and logical judgment.

[0030] Step S104, calculating the distance between the current position coordinates and the starting point coordinates of the road section to be collected to obtain a first distance; Among them, based on the path planning algorithm, the shortest path from the current position coordinates to the starting point of the road section to be collected can be found from the current position of the vehicle. The length of this path is the first distance.

[0031] Step S105, determining whether the first distance is greater than a first preset distance threshold; if so, jumping to step S106; if not, jumping to step S107; Step S106, dynamically adjusting the calculation frequency of the corresponding first distance according to the first distance and the current speed data of the collected vehicle; Among them, the first preset distance threshold is a reference value for triggering collection, which is used to prevent the vehicle from starting collection too early or too late outside the target section; the dynamic adjustment of the calculation frequency is determined by the mapping relationship between the first distance and the current vehicle speed data. When the first distance is greater than the first preset distance threshold, it means that the collection vehicle is far away from the starting point of the section. At this time, the distance calculation frequency can be flexibly adjusted in combination with the first distance and the current speed of the vehicle. For example, the smaller the first distance and the faster the current speed, the higher the calculation frequency is set.

[0032] For example, when the vehicle speed is lower than 30 km / h, the distance calculation frequency can be configured to be 5 seconds / time because the vehicle is in a low-speed driving state; when the vehicle speed is in the range of 30-60 km / h, the distance calculation frequency is 3 seconds / time; when the vehicle speed exceeds 60 km / h, in order to more accurately and timely monitor the position changes of the vehicle during high-speed driving, the frequency is increased to 2 seconds / time; in addition, when the first distance is close to the first preset distance threshold, it means that the vehicle is relatively close to the coordinates of the starting point of the road section, and the distance calculation frequency can be automatically adjusted to 1 second / time.

[0033] It can be understood that the above technical solution can flexibly balance the amount of calculation according to the actual speed of the vehicle while ensuring the accurate grasp of the vehicle's relative position to the planned route. It can more accurately monitor the changes in the vehicle's position during high-speed driving, and save computing resources at low speeds, reduce unnecessary computing power, and avoid excessive occupation of system resources. At the same time, it will not have a significant impact on the overall route tracking accuracy, so that the entire operation process achieves a good balance between efficiency and accuracy.

[0034] Step S107, sending an exposure start control instruction to the image acquisition device, and determining the road section to be acquired as the current acquisition road section; Among them, when the first distance is less than or equal to the first preset distance threshold, it means that the distance between the collection vehicle and the starting point of the road section is relatively close. The system starts the exposure of the image acquisition device through the exposure start control instruction, and the number or identification of the road section to be collected is written into the current collection task list, which is convenient for associating the image data and ensuring the matching of the image data and the road section.

[0035] Step S108, receiving in real time the road section image data collected by the image collection device for the current collection road section; Among them, the road section image data is transmitted to the storage module in real time through a high-bandwidth interface, and the GNSS coordinates and timestamp information are attached to achieve efficient image collection and data integrity assurance, providing a basis for subsequent green view rate data analysis.

[0036] Step S109, calculating the distance between the current position coordinates and the end point coordinates of the current acquisition section to obtain a second distance; Among them, based on the path planning algorithm, the shortest path from the current position coordinates to the end point of the current collection section can be found from the current position of the vehicle on the road section, and the length of the path is the second distance.

[0037] Step S110, determining whether the second distance is greater than a second preset distance threshold; if not, jumping to step S111; if yes, not performing any operation; Step S111, sending an exposure closing instruction to the image acquisition device, and marking the current acquisition section as an acquired section.

[0038] The second preset distance threshold defines the stop condition of the acquisition. By stopping the exposure of the image acquisition device, the current acquisition task is accurately ended to avoid repeated acquisition and improve the acquisition efficiency. At the same time, the current acquisition section is marked as a acquired section and removed from the task list.

[0039] In the above implementation, based on the precise calculation of the real-time status of the collected vehicle (including position and speed), as well as the dynamic adjustment of the collection frequency and automatic exposure control, efficient and accurate green view rate data collection is achieved. It can not only flexibly adapt to complex environments and reduce human intervention, but also ensure the precise matching of the collected image with the target road section, while effectively optimizing computing resources and collection time, and has wide practicality and reliability.

[0040] Reference Figure 2 As a further implementation of the acquisition control method, before the step of obtaining the starting point coordinates of the road section to be acquired in the target green view rate acquisition area, the method further includes: Step S201, receiving coordinate data of multiple key nodes in the target green viewing rate acquisition area; Among them, key nodes are geographic coordinate points in the target green view rate collection area, which are used to calibrate regional boundaries or important locations, such as intersections, road turning points or regional boundary points. The coordinates of these points can be manually set, imported from map data or generated by planning software.

[0041] Step S202, based on a preset route division rule, divide the roads between the multiple key nodes into multiple sections, and generate corresponding planned route information; The planned route information includes the number, starting point coordinates and end point coordinates of each road section. For each divided road section, the coordinate acquisition function of the map software is used to automatically call the corresponding interface programmatically to obtain the precise coordinates of the starting point and end point of the road section in the map coordinate system (in the form of longitude and latitude coordinates), and these coordinate values ​​are recorded in the "road section starting point coordinates" and "road section end point coordinates" fields of the corresponding road section file respectively. The entire process does not require manual measurement and input, which greatly improves efficiency and accuracy.

[0042] Specifically, the system defines the roads between adjacent key nodes as independent sections according to the order of the key nodes. The division rules can be based on the map topology. For example, the road from node 1 to node 2 is defined as an independent section and marked with numbers. The numbers are generated in sequence according to a certain sequence rule (incremental digital method) to ensure that each section can be accurately distinguished.

[0043] In addition, the route division rules can also be optimized based on the length of the road segment or terrain features (such as whether the road segment crosses a river). For example, if the road between two nodes is too long, a virtual node can be inserted in the middle to further subdivide the road segment.

[0044] It should be noted that the multiple road sections in the planned route information may be multiple discontinuous road sections, that is, there may be a certain interval between adjacent road sections.

[0045] Step S203: Based on the planned route information, multiple road sections are determined as road sections to be collected and a collection task list is generated.

[0046] Among them, the sections to be collected are the sections in the planned route that need to collect green view rate data. By default, the system sets all planned sections to the state to be collected and generates a collection task list. The collection task list can also be filtered or adjusted according to user needs.

[0047] It is understandable that the system allows users to filter the sections in the planned route, for example, based on the length of the section, the collection priority of the target area, or excluding sections with repeated collection; the priority can be set based on specific task requirements, for example, sections of urban main roads can be preferentially marked as "high priority to be collected".

[0048] In the above implementation, the key node data of the target area is received, the roads between the nodes are divided based on the preset rules and the planning route information is generated. This technical solution divides the complex collection area into multiple independent sections, and manages each section in a structured manner to clarify the starting and ending information of the collection task. Then, by marking the sections to be collected and dynamically extracting the starting point coordinates, the system can achieve refined planning and automated execution of large-scale collection tasks.

[0049] Reference Figure 3 As an implementation of step S102, the step of initializing the exposure parameters of the image acquisition device includes: Step S301, acquiring the current vehicle speed data and current ambient light data of the collected vehicle in real time; The vehicle speed data is usually collected through the vehicle speed sensor or GNSS module. The vehicle speed sensor can directly measure the real-time speed of the vehicle, while the GNSS module calculates the speed based on the continuous position information. The real-time speed is crucial for the subsequent exposure parameter adjustment, especially when driving at high speed (such as >30km / h), the vehicle moves fast, the scene changes frequently, and the exposure time needs to respond quickly.

[0050] In addition, ambient light data is usually measured in real time by a light sensor installed on the collection vehicle, and the light intensity is expressed in "illuminance" units (such as Lux). Real-time measurement of light intensity is used to determine the brightness of the current collection environment, for example: strong light (such as >1000 Lux): outdoor sunny day; weak light (such as <200 Lux): shadow area or night environment.

[0051] It can be understood that by collecting vehicle speed and ambient light data in real time, the necessary basic information is provided for dynamically adjusting exposure parameters, ensuring that the collection equipment can quickly adapt to different driving speeds and environmental changes.

[0052] Step S302: Based on a preset mapping relationship, corresponding exposure parameters are determined according to the current vehicle speed data and the current ambient light data.

[0053] The mapping relationship is generated based on preset rules or empirical data, and is used to map vehicle speed data and light data to corresponding exposure parameter combinations. Exposure parameters include exposure time (used to control the light-sensitive time of the image sensor), ISO value (indicates the camera's sensitivity, the higher the value, the greater the sensitivity to light, but the noise will also increase) and aperture (indicates the aperture size of the camera lens, controlling the amount of light entering).

[0054] Exemplarily, the system searches for the corresponding parameter combination from the preset mapping table through the real-time input of vehicle speed data and lighting data. For example: when the vehicle speed is relatively slow (between 0-30km / h), according to the actual light conditions, while ensuring the image quality, the exposure time is extended and adjusted between 1 / 200-1 / 100 seconds, and the appropriate ISO value and aperture are matched; when the vehicle speed is relatively fast (above 30km / h), in order to prevent the photo from being blurred due to the movement of the vehicle, the exposure time needs to be further optimized and adjusted between 1 / 800-1 / 500 seconds, and the ISO value and aperture size are adjusted accordingly according to the light changes. For example, for sections with good lighting conditions, the ISO value is set at a lower level (100-400) to ensure that the photo quality is delicate and less noise; for sections with poor lighting conditions, the ISO value is increased to 800-1200 to enhance the camera's sensitivity to light and make up for the problem of insufficient light.

[0055] It should be noted that the higher the vehicle speed, the shorter the exposure time to avoid image blur caused by vehicle movement; the lower the ambient light intensity, the higher the ISO value and the larger the aperture value to compensate for insufficient brightness.

[0056] It is understandable that during vehicle driving, the exposure time, ISO value and aperture are comprehensively adjusted for different road sections to ensure that the image acquisition equipment can quickly adapt to the environment under different driving and lighting conditions, achieve a balance between image quality and efficiency, and provide strong support for subsequent data statistics and analysis.

[0057] In the above implementation, the vehicle speed data and ambient light data are acquired in real time, and the exposure parameters of the camera (including exposure time, ISO value and aperture) are determined in combination with a preset mapping relationship. This technical solution realizes the intelligent adaptive adjustment of the image acquisition device to the dynamic acquisition environment, and can effectively solve the problem of image blur or too dark image caused by speed changes and diverse lighting conditions in traditional green view rate acquisition. At the same time, it reduces the complexity of manual parameter setting, improves acquisition efficiency, ensures the quality consistency of image acquisition in different environments, and provides reliable data support for green view rate evaluation.

[0058] Reference Figure 4 As a further implementation of the acquisition control method, after the step of marking the current acquisition section as the acquired section, the method further includes: Step S401, updating the status information of the collected road sections in the collection task list, and removing the collected road sections from the collection task list; The system stores all the sections to be collected in a list format, and each section is recorded as structured data, including the section number, starting point coordinates, end point coordinates, and priority information (which can be pre-sorted according to the location or importance of each section). In addition, after each collection is completed, the system will re-update the task list and remove the collected sections.

[0059] Exemplarily, when a collection section is marked as "collected", the system removes it from the collection task list, traverses the task list, and checks the status field of each section; for sections with a status of "completed", the corresponding record is deleted from the task list.

[0060] Step S402, according to the updated collection task list, sequentially load the next road section data to be collected and cyclically execute the road section image data collection step until all the road sections to be collected are marked as collected sections, and the road section image data of all the road sections are obtained; After the system completes the acquisition of the current road section, it can load the next road section in the task list as the current acquisition road section, and repeat the above-mentioned road section image data acquisition steps (steps S101 to S111). The loaded road section data includes the road section number, starting point coordinates, end point coordinates and priority information. The system will load the road section according to the priority; for example: the main road section is collected first, and the secondary road section is collected later. When all road sections in the acquisition task list are marked as "already collected", the system can determine that the acquisition task has been completed.

[0061] It is understandable that the scheduling logic can be combined with a priority-based sorting algorithm to achieve sequential loading according to the importance of the task. By sequentially loading the road section data to be collected, the system can quickly switch to the next task after completing the current task, ensuring that the collection task is executed continuously and efficiently. At the same time, combined with priority scheduling, it can adapt to the needs of different collection scenarios.

[0062] Step S403: Classify and store the road section image data of all road sections according to the road section numbers to obtain a collection data report of the target green view rate collection area.

[0063] After all road sections are collected, the system integrates all collected road section image data, including classification and storage by section number, adding GNSS coordinates, timestamp and other metadata, and generating data index files for subsequent retrieval and analysis.

[0064] In the above implementation, dynamic scheduling and efficient execution of acquisition tasks are achieved. From the removal of acquired road sections to the sequential loading of road sections to be acquired, and then to the cyclic execution of acquisition tasks, the system ensures the accuracy and consistency of tasks at each stage. Finally, through the dynamic update of the acquisition task list and the determination of the termination conditions, the image acquisition of all road sections can be completed without human intervention, and a structured data report can be generated.

[0065] The core technology of this application lies in the rational use of the planned route and the unique automatic control method. The pre-planned route provides a clear goal and direction for the acquisition control operation, making the acquisition process more precise and able to accurately capture the image data of key sections. In addition, a unique automatic control method is formed by combining distance parameters, real-time positioning, dynamic camera parameter adjustment, and automatic elimination of the collected sections. The technical process effectively avoids repeated shooting and missed shooting.

[0066] Compared with the prior art, this application demonstrates significant advantages in terms of efficiency, accuracy and reliability. Through automated control, the system can complete efficient collection according to the preset route without manual operation by operators, especially when covering multiple areas or long-distance routes, it can perform tasks in an orderly manner. Accurate route planning combined with dynamic distance parameters and real-time positioning ensures the accuracy of collection, and will not miss key locations or have redundant collection. The carefully designed control logic further reduces the risk of errors caused by human operation, ensures the consistency and integrity of the collected data, and enhances the stability and reliability of the system in different scenarios.

[0067] The embodiment of the present application also discloses a vehicle-mounted green view rate acquisition and control system based on a planned route.

[0068] A vehicle-mounted green view rate acquisition and control system based on a planned route is applied to an image acquisition device installed on a acquisition vehicle. The acquisition and control system includes: An acquisition module is used to acquire the starting point coordinates of the road section to be collected in the target green view rate collection area; A parameter initialization module is used to initialize the exposure parameters and device control parameters of the image acquisition device; A receiving module is used to receive and collect the current position coordinates and current speed data of the vehicle; A first distance calculation module, used to calculate the distance between the current position coordinates and the starting point coordinates of the road section to be collected, to obtain a first distance; A first judgment module, used to judge whether the first distance is greater than a first preset distance threshold; if so, output a first judgment result; if not, output a second judgment result; A calculation frequency adjustment module, for dynamically adjusting the calculation frequency of the corresponding first distance according to the first distance and the current speed data of the collected vehicle in response to the first judgment result; A control module, configured to send an exposure start control instruction to the image acquisition device in response to the second judgment result, and determine the section to be acquired as the current acquisition section; A receiving module, used for receiving in real time the road section image data collected by the image acquisition device for the current acquisition road section; A second distance calculation module is used to calculate the distance between the current position coordinates and the end point coordinates of the current collection section to obtain a second distance; A second judgment module, used to judge whether the second distance is greater than a second preset distance threshold; if not, output a third judgment result; The control module is further used to send an exposure closing instruction to the image acquisition device in response to the third judgment result, and mark the current acquisition section as a acquired section.

[0069] As a further implementation of the acquisition control system, it also includes: A coordinate data receiving module, used to receive coordinate data of multiple key nodes in the target green viewing rate collection area; A route planning module is used to divide the roads between multiple key nodes into multiple sections based on preset route division rules and generate corresponding planned route information; The collection task list generation module is used to determine multiple road sections as sections to be collected and generate a collection task list based on the planned route information.

[0070] The vehicle-mounted green visibility rate acquisition and control system based on a planned route in an embodiment of the present application can implement any of the above-mentioned acquisition and control methods, and the specific working process of each module in the acquisition and control system can refer to the corresponding process in the above-mentioned method embodiment.

[0071] In the several embodiments provided in this application, it should be understood that the provided methods and systems can be implemented in other ways. For example, the system embodiments described above are only illustrative; for example, the division of a certain module is only a logical function division, and there may be other division methods in actual implementation, such as multiple modules can be combined or integrated into another system, or some features can be ignored or not executed.

[0072] The embodiment of the present application also discloses a computer device.

[0073] A computer device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, a vehicle-mounted green view rate acquisition control method based on a planned route as described above is implemented.

[0074] The embodiment of the present application also discloses a computer-readable storage medium.

[0075] A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any one of the above-mentioned vehicle-mounted green view rate acquisition control methods based on a planned route.

[0076] Among them, computer-readable storage media can be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus or device; the program code contained on the computer-readable medium can be transmitted using any appropriate medium, including but not limited to wireless, wire, optical cable, RF, etc., or any suitable combination of the above.

[0077] It should be noted that in the above embodiments, the description of each embodiment has different emphases, and for parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0078] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A vehicle-mounted green view rate acquisition control method based on a planned route, applied to an image acquisition device installed on a acquisition vehicle, characterized in that: The acquisition control method comprises: Obtain the starting point coordinates of the road section to be collected in the target green view rate collection area; Initializing exposure parameters and device control parameters of the image acquisition device; Receiving the current position coordinates and current speed data of the collected vehicle; Calculating the distance between the current position coordinates and the starting point coordinates of the road section to be collected to obtain a first distance; Determine whether the first distance is greater than a first preset distance threshold; if so, dynamically adjust the calculation frequency of the corresponding first distance according to the first distance and the current speed data of the collected vehicle; If not, sending an exposure start control instruction to the image acquisition device, and determining the section to be acquired as the current acquisition section; Receiving in real time the road section image data collected by the image collection device on the current collection road section; Calculate the distance between the current position coordinates and the end point coordinates of the current collection section to obtain a second distance; Determine whether the second distance is greater than a second preset distance threshold; if not, send an exposure closing instruction to the image acquisition device, and mark the current acquisition section as a acquired section.

2. The vehicle-mounted green view rate acquisition and control method based on a planned route according to claim 1 is characterized in that: Before the step of obtaining the starting point coordinates of the road section to be collected in the target green view rate collection area, the following steps are also included: Receiving coordinate data of a plurality of key nodes of the target green viewing rate acquisition area; Based on the preset route division rules, the roads between multiple key nodes are divided into multiple sections, and the corresponding planned route information is generated; Based on the planned route information, a plurality of the road sections are determined as road sections to be collected and a collection task list is generated.

3. The vehicle-mounted green view rate acquisition and control method based on a planned route according to claim 2 is characterized in that: The planned route information includes the number, starting point coordinates and end point coordinates of each road section.

4. The vehicle-mounted green view rate acquisition and control method based on a planned route according to claim 1 is characterized in that: The exposure parameters include exposure time, ISO value and aperture size, and the device control parameters include the first preset distance threshold and the second preset distance threshold.

5. The vehicle-mounted green view rate acquisition and control method based on planned route according to claim 4 is characterized in that: The step of initializing the exposure parameters of the image acquisition device comprises: Acquire the current speed data and current ambient light data of the collected vehicle in real time; Based on a preset mapping relationship, corresponding exposure parameters are determined according to the current vehicle speed data and the current ambient light data.

6. The vehicle-mounted green view rate acquisition and control method based on a planned route according to claim 2 is characterized in that: After the step of marking the current collected road section as a collected road section, the step further includes: Update the status information of the collected road section in the collection task list, and remove the collected road section from the collection task list; According to the updated collection task list, the next road section data to be collected is loaded in sequence and the road section image data collection step is executed cyclically until all the road sections to be collected are marked as collected sections, and the road section image data of all the road sections are obtained; The road section image data of all road sections are classified and stored according to the road section numbers to obtain a collection data report of the target green view rate collection area.

7. A vehicle-mounted green view rate acquisition control system based on a planned route, applied to an image acquisition device installed on a acquisition vehicle, characterized in that: The acquisition control system comprises: An acquisition module is used to acquire the starting point coordinates of the road section to be collected in the target green view rate collection area; A parameter initialization module, used to initialize the exposure parameters and device control parameters of the image acquisition device; A receiving module, used for receiving the current position coordinates and current speed data of the collected vehicle; A first distance calculation module, used to calculate the distance between the current position coordinates and the starting point coordinates of the road section to be collected, to obtain a first distance; A first judgment module, used to judge whether the first distance is greater than a first preset distance threshold; if so, output a first judgment result; if not, output a second judgment result; a calculation frequency adjustment module, configured to dynamically adjust the calculation frequency of the corresponding first distance according to the first distance and the current speed data of the collected vehicle in response to the first judgment result; A control module, configured to send an exposure start control instruction to the image acquisition device in response to the second judgment result, and determine the section to be acquired as a current acquisition section; A receiving module, used for receiving in real time the road section image data collected by the image acquisition device on the current acquisition road section; A second distance calculation module, used to calculate the distance between the current position coordinates and the end point coordinates of the current collection section to obtain a second distance; A second judgment module, used to judge whether the second distance is greater than a second preset distance threshold; if not, output a third judgment result; The control module is further used to send an exposure closing instruction to the image acquisition device in response to the third judgment result, and mark the current acquisition section as a acquired section.

8. The vehicle-mounted green view rate acquisition and control system based on planned route according to claim 7, characterized in that: The acquisition control system also includes: A coordinate data receiving module, used to receive coordinate data of multiple key nodes in the target green viewing rate acquisition area; A route planning module is used to divide the roads between multiple key nodes into multiple sections based on preset route division rules and generate corresponding planned route information; The collection task list generation module is used to determine the plurality of road sections as road sections to be collected and generate a collection task list based on the planned route information.

9. A computer device, characterized in that: The method comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 6 is implemented.

10. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method according to any one of claims 1 to 6.

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