Vehicle-mounted camera self-cleaning and image enhancement system under severe working conditions and control method

Abstract

The invention discloses a vehicle-mounted camera self-cleaning and image enhancement system under severe working conditions and a control method, and relates to the technical field of unmanned vehicles, and the vehicle-mounted camera self-cleaning and image enhancement system comprises an unmanned vehicle working condition analysis module and a camera self-cleaning device. According to the method, the visual picture quality of the unmanned vehicle-mounted camera module can be actively analyzed, and when it is detected that the image quality is reduced due to rain, snow, mud, dust and the like, a cleaning program is automatically started. It is ensured that the vehicle-mounted camera can still provide clear visual information under various severe weathers or road conditions, and therefore the safety and reliability of an automatic driving or auxiliary driving system are guaranteed. The telescopic camera side cover protects a camera lens area during cleaning, cleaning liquid or pollutants are prevented from being sputtered to a lens body, meanwhile, an action space is provided for circulating the cleaning liquid and ultrasonic waves, and the cleaning pertinence is improved. Through an image enhancement algorithm of the GPU chip, the problems of image blurring, color distortion and the like caused by weather, illumination or slight pollution can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned vehicles, and in particular to a self-cleaning and image enhancement system and a control method for a vehicle-mounted camera under harsh working conditions. Background Art

[0002] With the rapid development of intelligent driving technology, the performance of vehicle cameras, as core components of vehicle perception systems, is directly related to driving safety. However, in-vehicle cameras face severe challenges in practical applications: environmental factors such as bad weather, dust, mud, ice and snow can seriously affect the camera's imaging quality; Harsh operating conditions have multiple impacts on automotive cameras, including lens obstruction caused by physical contamination and image quality degradation due to changing environmental conditions. These factors collectively pose significant challenges to the practical application of automotive cameras.

[0003] In terms of physical contamination, rain, snow, dust, mud, and other particles can adhere to the camera surface, blurring or completely obscuring the image. These pollutants can come from blowing sand generated by the vehicle itself or from splashes from other vehicles. Studies have shown that even tiny particles can significantly degrade image quality and blur the image if they adhere to the camera surface. For example, raindrops on rainy days can create irregular transparent areas on the lens, distorting light and causing image distortion. Snowflakes on snowy days can accumulate on the lens, partially obscuring the field of view. Dust and mud can form an opaque coating that can completely blind the camera in severe cases.

[0004] Therefore, the development of a self-cleaning and image enhancement system for vehicle-mounted cameras that can maintain effective perception capabilities under harsh working conditions has become a key issue that needs to be urgently addressed in the field of intelligent driving. Summary of the Invention

[0005] In order to solve the above technical problems, the present invention provides a self-cleaning and image enhancement system and control method for vehicle-mounted cameras under harsh working conditions. The following technical solutions are adopted: A self-cleaning and image enhancement system for a vehicle camera under adverse operating conditions includes an unmanned vehicle operating condition analysis module and a camera self-cleaning device. The unmanned vehicle operating condition analysis module is communicatively connected to the unmanned vehicle camera module and determines whether adverse operating conditions have occurred based on visual image quality analysis of the unmanned vehicle camera module. The camera self-cleaning device includes a telescopic camera side cover, an ultrasonic-based circulating cleaning fluid cleaning component, and a chip-based cleaning controller. The telescopic camera side cover is mounted in a slot provided around the camera. A circulating cleaning fluid pipe of the circulating cleaning fluid cleaning component is connected to a circulating cleaning fluid path within the telescopic camera side cover. The cleaning controller is communicatively connected to the unmanned vehicle operating condition analysis module. When the unmanned vehicle operating condition analysis module analyzes that the visual image quality is greater than or equal to a set scoring threshold, the cleaning controller controls the telescopic camera side cover to be retracted and the circulating cleaning fluid cleaning component to be inoperative. When the unmanned vehicle operating condition analysis module analyzes that the visual image quality is less than the set scoring threshold, the cleaning controller performs a cleaning action. The cleaning action involves controlling the telescopic camera side cover to be extended and controlling the circulating cleaning fluid cleaning component to start circulating cleaning fluid and ultrasonic cleaning, which continues for a set time and then retracts. The cleaning action is repeated three times according to the set time.

[0006] By employing this technical solution, the system proactively analyzes the visual image quality of autonomous vehicle camera modules and automatically initiates a cleaning process when it detects image quality degradation (below a scoring threshold) caused by rain, snow, mud, dust, and other factors. This ensures that the onboard cameras can still provide clear visual information in various adverse weather and road conditions, thereby safeguarding the safety and reliability of autonomous or assisted driving systems.

[0007] The retractable camera side cover is designed to protect the camera lens area during cleaning, preventing cleaning fluid or contaminants from splashing onto the lens itself. It also provides space for circulating cleaning fluid and ultrasonic waves, improving the targeted cleaning effect.

[0008] The combined cleaning method of ultrasonic waves and circulating cleaning fluid offers superior cleaning capabilities compared to traditional pure water rinsing or simple wiping. Ultrasonic waves create a micro-cavitation effect, effectively stripping away stubborn stains, oil films, and ice layers adhering to the lens surface, while the circulating cleaning fluid removes the removed dirt, preventing secondary contamination.

[0009] The three-time repeated cleaning design avoids a single cleaning time that is too long and affects the visual image acquisition. Of course, the machine can also be stopped for processing within 10 seconds to 20 seconds of the cleaning action, ensuring that even if the stains are more serious, better cleaning effects can be achieved through multiple actions, thereby improving the reliability of cleaning.

[0010] Timely and effective cleaning can reduce the long-term erosion and wear of camera lenses and internal components by dirt, especially in harsh environments with highly corrosive substances such as sand, gravel, and chemicals (such as snow melting agents). This can significantly extend the service life of the camera module and reduce maintenance costs.

[0011] The system activates the cleaning mechanism only when needed (i.e., when image quality falls below a threshold), remaining retracted and in standby mode. This avoids unnecessary energy consumption and enables on-demand cleaning, resulting in an intelligent energy-saving design. The retracted side covers also help reduce wind resistance.

[0012] Optionally, it also includes an image enhancement module, which includes a buffer and a GPU chip. The buffer is communicated with the unmanned vehicle camera module and the vehicle control system respectively, and the GPU chip is communicated with the unmanned vehicle working condition analysis module and the buffer respectively. If the unmanned vehicle working condition analysis module determines that the visual picture quality is less than the set scoring threshold, the image enhancement module intervenes, and the GPU chip enhances the visual picture collected by the unmanned vehicle camera module based on the image enhancement algorithm and stores it in the buffer. The vehicle control system uses the enhanced visual picture stored in the buffer.

[0013] By implementing this technical solution, even when the camera's self-cleaning mechanism activates, even when image quality degrades due to contamination, it may still be incomplete or require time to recover. The image enhancement module can process images before, during, or after cleaning, or even supplement the cleaning process. By using the GPU chip to execute advanced image enhancement algorithms (such as dehazing, contrast enhancement, edge sharpening, and low-light enhancement), it can effectively improve image blur and color distortion caused by weather (fog, rain, snow), lighting (strong or weak), or even minor contamination.

[0014] This enables the on-board control system to obtain relatively clearer and more information-rich images even when the physical cleaning of the camera has not reached optimal conditions, thereby improving the perception accuracy and decision-making reliability of the autonomous driving system in harsh environments.

[0015] Not only does it restore image quality through physical means (self-cleaning), it also uses digital processing (image enhancement) to compensate for the deficiency or delay of physical cleaning.

[0016] This "soft and hard" combination significantly improves the vision system's ability to cope with harsh working conditions. Even if there are still small, difficult-to-remove stains or water droplets on the physical lens, image enhancement can restore image details to a certain extent, providing usable visual information and reducing the risk of system performance degradation due to failure of a single link.

[0017] Optionally, the unmanned vehicle operating condition analysis module includes a memory, a visual analysis chip and a data analysis chip. The memory is communicatively connected to the unmanned vehicle camera module, the visual analysis chip is communicatively connected to the memory, and the data analysis chip is communicatively connected to the visual analysis chip.

[0018] Optionally, the telescopic camera side cover includes an electric push rod, a side cover base plate and a side plate. The electric push rod is installed inside the unmanned vehicle shell. A side cover through hole is opened in the unmanned vehicle shell surrounding the unmanned vehicle camera module. One side of the side cover base plate is installed on the piston rod of the electric push rod, and one end of the side plate is installed on the other side of the side cover base plate. When the piston rod of the electric push rod is extended, the side plate surrounds the unmanned vehicle camera module. When the piston rod of the electric push rod is retracted, the side plate retracts and the end is flush with the unmanned vehicle shell.

[0019] Optionally, the circulating cleaning liquid cleaning assembly includes a circulating cleaning liquid tank, a micro pump, a connecting hose, an ultrasonic generator and multiple nozzles. The circulating cleaning liquid tank is installed inside the unmanned vehicle shell, and a circulating cleaning liquid channel is provided inside the side cover bottom plate and the side plate. The micro pump connects the circulating cleaning liquid channel and the circulating cleaning liquid tank through a connecting hose. Multiple nozzles are respectively installed at multiple spray holes on the inner side of the side plate, and the ultrasonic generator is installed in the circulating cleaning liquid channel.

[0020] By adopting the above technical solution, electric actuators can achieve precise control of the extension and retraction of the side cover base and side panels, including position and speed. This allows the side cover base and side panels to stably and accurately surround the unmanned vehicle camera module. The design of the side panels surrounding the camera enables surround-type jet ultrasonic cleaning with the cooperation of multiple nozzles. The ultrasonic waves generated by the ultrasonic generator create a cavitation effect in the cleaning fluid, which can effectively remove stubborn stains (such as oil film, salt crystals, and partially dried mud) adhering to the lens surface. This physical cleaning method is more thorough and efficient than simple water rinsing.

[0021] The electric actuators and most of the side cover structure (bottom plate, side panels) are designed to be internal to the unmanned vehicle's shell and only extend when cleaning is required. This design makes the vehicle's appearance more simple and beautiful, does not add additional external structure during normal driving, and reduces the risk of damage from foreign objects.

[0022] A circulating system, comprised of a cleaning fluid tank and a micropump, continuously provides a constant supply of fluid at a defined pressure and high cleaning power. Compared to a one-time spray, this system ensures multiple, continuous flushing of the lens within a set timeframe, ensuring effective cleaning. The cleaning fluid can be replaced regularly to maintain its cleaning performance.

[0023] The circulating cleaning fluid channel is directly integrated into the side cover bottom plate and side panel, cleverly utilizing the structural space of the side cover itself, making the entire cleaning assembly more compact, reducing additional pipes and connectors, and reducing the risk of leakage and installation complexity.

[0024] Multiple nozzles are distributed on the inner side of the side panels, which can flush the camera lens from different angles to ensure that the entire lens surface is covered and avoid cleaning blind spots.

[0025] Optionally, the cleaning controller includes an instruction cache and a control chip, the instruction cache is communicatively connected to the unmanned vehicle working condition analysis module, and the control chip is communicatively connected to the instruction cache, and respectively controls the execution actions of the electric push rod, micro pump and ultrasonic generator.

[0026] A method for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under harsh working conditions is provided. The method uses a system for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under harsh working conditions, and includes the following steps: Step 1: The unmanned vehicle camera module continuously collects raw images, and the raw image data is stored in the memory of the working condition analysis module; Step 2: The visual analysis chip performs multi-dimensional analysis, evaluates the visual image quality, and outputs a visual image quality score; Step 3: Set a scoring threshold. When the visual image quality score output by the data analysis chip is less than the scoring threshold, the instruction buffer stores the cleaning action instruction. Step 4, the control chip executes the cleaning action instruction, controls the piston rod of the electric push rod to extend, controls the micro pump to start, and controls the ultrasonic generator to start; the cleaning action instruction lasts for the set time; every set time, the cleaning action instruction is executed three times in a cycle.

[0027] Optionally, when the visual image quality score output by the data analysis chip is less than the score threshold, the GPU chip obtains the original image from the cache and performs bad pixel repair, adaptive dehazing, HDR synthesis, and dynamic sharpening in sequence to obtain an enhanced visual image.

[0028] Optionally, in step 2, evaluating the visual image quality includes the following specific steps: Step 21, calculating the Laplacian variance value of the image, calculating the clarity index according to the Laplacian variance value of the image, and setting the weight of the clarity index; Step 22: segment the HSV color space, calculate the percentage of stain pixels to obtain a stain coverage index, and set the weight of the stain coverage index; Step 23, performing optical interference detection to identify halo characteristics to obtain an optical interference index, and setting a weight for the optical interference index; In step 24, each indicator is multiplied by the corresponding weight and the sum is added to obtain a visual image quality score.

[0029] Optionally, in step 4, the time is set to 10 seconds to 20 seconds.

[0030] In summary, the present invention includes at least one of the following beneficial technical effects: The present invention can provide a self-cleaning and image enhancement system and control method for vehicle-mounted cameras under harsh working conditions. The system can actively analyze the visual image quality of the unmanned vehicle-mounted camera module, and automatically start the cleaning program when it detects image quality degradation caused by rain, snow, mud, dust, etc.

[0031] This ensures that the on-board camera can still provide clear visual information in various severe weather or road conditions, thereby ensuring the safety and reliability of the autonomous driving or assisted driving system.

[0032] The retractable camera side cover protects the camera lens area during cleaning, preventing cleaning fluid or contaminants from splashing onto the lens itself. It also provides space for circulating cleaning fluid and ultrasonic waves, improving the targeted cleaning effect.

[0033] The combined cleaning method of ultrasonic waves and circulating cleaning fluid offers superior cleaning capabilities compared to traditional pure water rinsing or simple wiping. Ultrasonic waves create a micro-cavitation effect, effectively stripping away stubborn stains, oil films, and ice layers adhering to the lens surface, while the circulating cleaning fluid removes the removed dirt, preventing secondary contamination.

[0034] Through timely and effective cleaning, the long-term erosion and wear of dirt on the camera lens and internal components can be reduced, which can significantly extend the service life of the camera module and reduce maintenance costs.

[0035] The system activates the cleaning mechanism only when needed, remaining retracted and in standby mode. This avoids unnecessary energy consumption and enables on-demand cleaning, resulting in an intelligent energy-saving design. The retracted telescopic side covers also help reduce wind resistance.

[0036] The image enhancement algorithm of the GPU chip can effectively improve problems such as image blur and color distortion caused by weather, lighting or slight pollution.

[0037] Even if there are still a small amount of stains or water droplets on the physical lens that are difficult to completely remove, image enhancement can restore image details to a certain extent, provide usable visual information, and reduce the risk of system performance degradation due to failure of a single link. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a schematic diagram of the electrical component connection principle of the vehicle-mounted camera self-cleaning and image enhancement system under harsh working conditions of the present invention; Figure 2 2. It is a structural schematic diagram of the camera self-cleaning device of the vehicle-mounted camera self-cleaning and image enhancement system under harsh working conditions of the present invention in an initial state; Figure 3 The present invention is a structural schematic diagram of a camera self-cleaning device in a cleaning state of a vehicle-mounted camera self-cleaning and image enhancement system under harsh working conditions.

[0039] Explanation of the accompanying symbols: 1. Unmanned vehicle working condition analysis module; 11. Memory; 12. Visual analysis chip; 13. Data analysis chip; 2. Unmanned vehicle camera module; 311. Electric push rod; 312. Side cover bottom plate; 313. Side panel; 321. Circulating cleaning liquid tank; 322. Micro pump; 323. Connecting hose; 324. Ultrasonic generator; 325. Nozzle; 33. Cleaning controller; 34. Instruction cache; 35. Control chip; 4. Image enhancement module; 41. Cache; 42. GPU chip; 100. Vehicle control system. DETAILED DESCRIPTION

[0040] The present invention will be further described in detail below with reference to the accompanying drawings.

[0041] The embodiments of the present invention disclose a self-cleaning and image enhancement system and a control method for a vehicle-mounted camera under harsh working conditions.

[0042] Reference Figure 1-Figure 3 , Example 1, a self-cleaning and image enhancement system for a vehicle-mounted camera under harsh working conditions, including an unmanned vehicle working condition analysis module 1 and a camera self-cleaning device. The unmanned vehicle working condition analysis module 1 is in communication with the unmanned vehicle-mounted camera module 2, and determines whether a harsh working condition occurs based on the visual image quality analysis of the unmanned vehicle-mounted camera module 2. The camera self-cleaning device includes a telescopic camera side cover, an ultrasonic-based circulating cleaning liquid cleaning component, and a chip-based cleaning controller 33. The telescopic camera side cover is installed in a slot set around the camera, and the circulating cleaning liquid pipe of the circulating cleaning liquid cleaning component is connected to the circulating cleaning liquid circuit in the telescopic camera side cover. The cleaning controller 33 is connected to the unmanned vehicle working condition analysis module 1. When the unmanned vehicle working condition analysis module 1 analyzes that the visual image quality is greater than or equal to the set scoring threshold, the cleaning controller 33 controls the telescopic camera side cover to be in a retracted state, and the circulating cleaning liquid cleaning component does not work. When the unmanned vehicle working condition analysis module 1 analyzes that the visual image quality is less than the set scoring threshold, the cleaning controller 33 performs a cleaning action. The cleaning action is to control the telescopic camera side cover to be in an extended state, control the circulating cleaning liquid cleaning component to start circulating cleaning liquid and ultrasonic cleaning, and retract after a set time. Repeat the cleaning action three times according to the set time.

[0043] The system proactively analyzes the visual image quality of the autonomous vehicle's camera module. When it detects image quality degradation (below a scoring threshold) caused by rain, snow, mud, or dust, it automatically initiates a cleaning process. This ensures that the vehicle's camera can still provide clear visual information in adverse weather and road conditions, thereby safeguarding the safety and reliability of autonomous or assisted driving systems.

[0044] The retractable camera side cover is designed to protect the camera lens area during cleaning, preventing cleaning fluid or contaminants from splashing onto the lens itself. It also provides space for circulating cleaning fluid and ultrasonic waves, improving the targeted cleaning effect.

[0045] The combined cleaning method of ultrasonic waves and circulating cleaning fluid offers superior cleaning capabilities compared to traditional pure water rinsing or simple wiping. Ultrasonic waves create a micro-cavitation effect, effectively stripping away stubborn stains, oil films, and ice layers adhering to the lens surface, while the circulating cleaning fluid removes the removed dirt, preventing secondary contamination.

[0046] The three-time repeated cleaning design avoids a single cleaning time that is too long and affects the visual image acquisition. Of course, the machine can also be stopped for processing within 10 seconds to 20 seconds of the cleaning action, ensuring that even if the stains are more serious, better cleaning effects can be achieved through multiple actions, thereby improving the reliability of cleaning.

[0047] Timely and effective cleaning can reduce the long-term erosion and wear of camera lenses and internal components by dirt, especially in harsh environments with highly corrosive substances such as sand, gravel, and chemicals (such as snow melting agents). This can significantly extend the service life of the camera module and reduce maintenance costs.

[0048] The system activates the cleaning mechanism only when needed (i.e., when image quality falls below a threshold), remaining retracted and in standby mode. This avoids unnecessary energy consumption and enables on-demand cleaning, resulting in an intelligent energy-saving design. The retracted side covers also help reduce wind resistance.

[0049] Example 2 also includes an image enhancement module 4, which includes a buffer 41 and a GPU chip 42. The buffer 41 is respectively communicated with the unmanned vehicle camera module 2 and the vehicle control system 100, and the GPU chip 42 is respectively communicated with the unmanned vehicle working condition analysis module 1 and the buffer 41. If the unmanned vehicle working condition analysis module 1 determines that the visual image quality is less than the set scoring threshold, the image enhancement module 4 intervenes, and the GPU chip 42 enhances the visual image collected by the unmanned vehicle camera module 2 based on the image enhancement algorithm and stores it in the buffer 41. The vehicle control system 100 uses the enhanced visual image stored in the buffer 41.

[0050] When camera image quality degrades due to contamination, even if the self-cleaning mechanism is activated, cleaning may not be complete or may require time to recover. The image enhancement module can process images before, during, or after cleaning, or even supplement the cleaning effect. The GPU chip 42 executes advanced image enhancement algorithms (such as dehazing, contrast enhancement, edge sharpening, and low-light enhancement) to effectively improve image blur and color distortion caused by weather (fog, rain, snow), lighting (strong light, weak light), or even minor contamination.

[0051] This enables the on-board control system to obtain relatively clearer and more information-rich images even when the physical cleaning of the camera has not reached optimal conditions, thereby improving the perception accuracy and decision-making reliability of the autonomous driving system in harsh environments.

[0052] Not only does it restore image quality through physical means (self-cleaning), it also uses digital processing (image enhancement) to compensate for the deficiency or delay of physical cleaning.

[0053] This "soft and hard" combination significantly improves the vision system's ability to cope with harsh working conditions. Even if there are still small, difficult-to-remove stains or water droplets on the physical lens, image enhancement can restore image details to a certain extent, providing usable visual information and reducing the risk of system performance degradation due to failure of a single link.

[0054] In embodiment 3, the unmanned vehicle operating condition analysis module 1 includes a memory 11, a visual analysis chip 12 and a data analysis chip 13. The memory 11 is communicatively connected to the unmanned vehicle camera module 2, the visual analysis chip 12 is communicatively connected to the memory 11, and the data analysis chip 13 is communicatively connected to the visual analysis chip 12.

[0055] Example 4, the telescopic camera side cover includes an electric push rod 311, a side cover bottom plate 312 and a side plate 313. The electric push rod 311 is installed inside the unmanned vehicle shell, and a side cover through hole is opened in the unmanned vehicle shell surrounding the unmanned vehicle camera module 2. One side of the side cover bottom plate 312 is installed on the piston rod of the electric push rod 311, and one end of the side plate 313 is installed on the other side of the side cover bottom plate 312. When the piston rod of the electric push rod 311 is extended, the side plate 313 surrounds the unmanned vehicle camera module 2. When the piston rod of the electric push rod 311 is retracted, the side plate 313 retracts and the end is flush with the unmanned vehicle shell.

[0056] Example 5, the circulating cleaning liquid cleaning component includes a circulating cleaning liquid tank 321, a micro pump 322, a connecting hose 323, an ultrasonic generator 324 and multiple nozzles 325. The circulating cleaning liquid tank 321 is installed inside the unmanned vehicle shell, and a connected circulating cleaning liquid channel is set inside the side cover bottom plate 312 and the side plate 313. The micro pump 322 connects the circulating cleaning liquid channel and the circulating cleaning liquid tank 321 through the connecting hose 323. Multiple nozzles 325 are respectively installed at multiple spray holes on the inner side of the side plate 313, and the ultrasonic generator 324 is installed in the circulating cleaning liquid channel.

[0057] The electric push rod 311 enables precise control of the extension and retraction of the side cover base plate 312 and side plates 313, including their position and speed. This allows the side cover base plate 312 and side plates 313 to stably and accurately surround the unmanned vehicle camera module 2. The design of the side plates 313 surrounding the camera enables a surround-type jet-type ultrasonic cleaning method with the cooperation of multiple nozzles 325. The ultrasonic waves generated by the ultrasonic generator 324 create a cavitation effect in the cleaning fluid, effectively removing stubborn stains (such as oil film, salt crystals, and partially dried mud) adhering to the lens surface. This physical cleaning method is more thorough and efficient than simple water rinsing.

[0058] The electric actuator 311 and most of the side cover structure (bottom plate and side panels) are designed to be internal to the unmanned vehicle's shell and only extend when cleaning is required. This design makes the vehicle's appearance more simple and beautiful, does not add additional external structure during normal driving, and reduces the risk of damage from foreign objects.

[0059] The circulating cleaning fluid tank 321 and micropump 322 form a circulation system that continuously supplies a liquid with a certain pressure and cleaning power. Compared to a one-time spray, the circulation system ensures multiple, continuous flushing of the lens within a set time, ensuring effective cleaning. The cleaning fluid can be replaced regularly to maintain its cleaning performance.

[0060] The circulating cleaning liquid channel is directly integrated into the side cover bottom plate 312 and the side plate 313, which cleverly utilizes the structural space of the side cover itself, making the entire cleaning assembly more compact, reducing additional pipes and connectors, and reducing the risk of leakage and installation complexity.

[0061] Multiple nozzles 325 are distributed on the inner side of the side panel, which can flush the camera lens from different angles to ensure that the entire lens surface is covered and avoid cleaning dead corners.

[0062] In Example 6, the cleaning controller 33 includes an instruction cache 34 and a control chip 35. The instruction cache 34 is communicated with the unmanned vehicle working condition analysis module 1, and the control chip 35 is communicated with the instruction cache 34, and respectively controls the execution actions of the electric push rod 311, the micro pump 322 and the ultrasonic generator 324.

[0063] Example 7, a method for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under harsh working conditions, uses a system for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under harsh working conditions, comprising the following steps: Step 1: The unmanned vehicle camera module 2 continuously collects raw images, and the raw image data is stored in the memory 11 of the working condition analysis module 1; Step 2: The visual analysis chip 12 performs multi-dimensional analysis to evaluate the visual image quality and outputs a visual image quality score; Step 3: Set a scoring threshold. When the visual image quality score output by the data analysis chip 13 is less than the scoring threshold, the instruction buffer 34 stores the cleaning action instruction. Step 4, the control chip 35 executes the cleaning action instruction, controls the piston rod of the electric push rod 311 to extend, controls the micro pump 322 to start, and controls the ultrasonic generator 324 to start; the cleaning action instruction lasts for the set time; and the cleaning action instruction is executed three times in a cycle every set time.

[0064] In Example 8, when the visual image quality score output by the data analysis chip 13 is less than the score threshold, the GPU chip 42 obtains the original image from the cache 41, and sequentially performs bad pixel repair, adaptive dehazing, HDR synthesis, and dynamic sharpening to obtain an enhanced visual image.

[0065] In Example 9, in step 2, evaluating the visual image quality includes the following specific steps: Step 21, calculating the Laplacian variance value of the image, calculating the clarity index according to the Laplacian variance value of the image, and setting the weight of the clarity index; Step 22: segment the HSV color space, calculate the percentage of stain pixels to obtain a stain coverage index, and set the weight of the stain coverage index; Step 23, performing optical interference detection to identify halo characteristics to obtain an optical interference index, and setting a weight for the optical interference index; In step 24, each indicator is multiplied by the corresponding weight and the sum is added to obtain a visual image quality score.

[0066] In Example 10, in step 4, the time is set to 10 seconds to 20 seconds.

[0067] The following describes the implementation principle of the present invention through specific examples: A driverless taxi is driving on a muddy road after rain. Its forward-facing onboard camera module 2 (for example, lane recognition and obstacle detection) begins collecting a real-time video stream. The combination of rain and splashing water on the road has deposited a thin layer of mud and water on the lens. While this doesn't completely obstruct the view, the image quality has significantly degraded.

[0068] The camera module 2 continuously transmits the collected original image data to the unmanned vehicle working condition analysis module 1 and stores it in its memory 11.

[0069] The visual analysis chip 12 analyzes the most recent image in memory 11. It quickly calculates the image's clarity (using metrics like the Laplacian variance to determine the degree of edge blur), detects large clusters of blue or green pixels (indicated by water or mud stains in the HSV color space), and identifies slight halo effects (optical interference) at the edges of the image. These analysis results are quantified into a score.

[0070] The data analysis chip 13 receives the scores for each indicator output by the visual analysis chip 12 and performs a weighted summation based on preset weights (for example, clarity has a higher weight, stain coverage has a lower weight, and optical interference has a lowest weight), thereby obtaining a comprehensive visual image quality score. This score (for example, a score of 45) is lower than a preset score threshold (for example, a threshold of 60).

[0071] The data analysis chip 13 sends the signal below the threshold to the cleaning controller 33. The instruction buffer 34 in the cleaning controller 33 receives the instruction and stores the instruction sequence of "perform three cleaning actions".

[0072] Self-cleaning execution process: First cleaning: The control chip 35 reads instructions from the instruction buffer 34 and first controls the electric push rod 311 to move. Its piston rod extends, driving the side cover bottom plate 312 and side plate 313 to move outward from the slot inside the unmanned vehicle shell until the side plate 313 completely surrounds the camera module 2 and its end is flush with the vehicle shell. At this point, the nozzle 325 installed on the inside of the side plate is also located around the lens.

[0073] The control chip 35 then instructs the micro pump 322 to start, draw cleaning liquid (which may be an aqueous solution containing a small amount of surfactant) from the circulating cleaning liquid tank 321, and transport the cleaning liquid to each nozzle 325 through the connecting hose 323 and the circulating cleaning liquid channel inside the side cover.

[0074] At the same time, the control chip 35 instructs the ultrasonic generator 324 to start, generating ultrasonic waves in the circulating cleaning liquid channel, and the cleaning liquid carrying the ultrasonic energy is evenly sprayed from the nozzle 325 to the lens surface.

[0075] This combined action of "extending, spraying, and ultrasonic waves" lasts for a set time, such as 15 seconds. The ultrasonic cavitation effect helps to remove some of the muddy and water mixture, while the circulating cleaning fluid flushes it away, flowing back into the cleaning fluid tank 321 (or circulating after filtration) through the drainage holes (or return channels) in the side cover bottom plate 312.

[0076] After 15 seconds, the control chip 35 instructs the electric push rod 311 to retract, the side cover is retracted, and the cleaned lens is exposed. The micro pump and ultrasonic generator also stop working.

[0077] Second cleaning: The system waits for a short time (e.g. a few seconds) and then repeats the above complete cleaning action of extending, spraying, ultrasonic, and retracting, which lasts for another 15 seconds. This cleaning further removes the remaining stains.

[0078] Third cleaning: Similarly, the system waits for a few seconds again and then performs a third complete 15-second cleaning action to ensure that the lens reaches the best cleaning state.

[0079] After cleaning and image enhancement (optional): After three cleanings are complete, the side covers retract, and camera module 2 resumes image acquisition. Working condition analysis module 1 reassesses the image quality. Assuming the score has now improved to 75, exceeding the threshold of 60 points, the system determines that the cleaning was successful.

[0080] During this time, if the image enhancement module 4 is configured to intervene during or immediately after cleaning, the GPU chip 42 will begin operating when the data analysis chip 13 first signals a signal below a threshold. It retrieves the original blurred image from buffer 41, acquired before or during cleaning, and rapidly executes a series of image enhancement algorithms: first, it repairs any remaining bad pixels in the image, then performs adaptive dehazing to restore distant image clarity, then utilizes HDR (High Dynamic Range) synthesis to balance details in bright and dark areas, and finally performs dynamic sharpening to enhance edges and textures. The processed, enhanced image is then stored back in buffer 41.

[0081] The vehicle control system 100 preferentially reads and uses these enhanced images from the buffer 41 for subsequent perception, decision-making and control. Even if there is still a small amount of water stains on the lens that are difficult to completely remove, the enhanced images provide clearer and more useful information.

[0082] As the vehicle continues driving, if the weather improves or the road dries, the operating condition analysis module 1 continuously monitors image quality. If the score stabilizes above the threshold again, the system retracts the side covers and places the cleaning components in standby mode until the next cleaning is detected. Throughout this process, the system achieves on-demand, efficient, and intelligent self-cleaning and image optimization.

[0083] The above are all preferred embodiments of the present invention, and are not intended to limit the scope of protection of the present invention. Therefore, any equivalent changes made based on the structure, shape, and principle of the present invention should be included in the scope of protection of the present invention.

Claims

1. The vehicle-mounted camera self-cleaning and image enhancement system for harsh working conditions is characterized by: The invention comprises an unmanned vehicle working condition analysis module (1) and a camera self-cleaning device, wherein the unmanned vehicle working condition analysis module (1) is connected to the unmanned vehicle camera module (2) for communication, and judges whether a bad working condition occurs based on the visual image quality analysis of the unmanned vehicle camera module (2). The camera self-cleaning device comprises a telescopic camera side cover, an ultrasonic-based circulating cleaning liquid cleaning component, and a chip-based cleaning controller (33), wherein the telescopic camera side cover is installed at a slot provided around the camera, a circulating cleaning liquid pipe of the circulating cleaning liquid cleaning component is connected to a circulating cleaning liquid path in the telescopic camera side cover, and the cleaning controller ( 33) is connected to the unmanned vehicle working condition analysis module (1) for communication. When the unmanned vehicle working condition analysis module (1) analyzes that the visual image quality is greater than or equal to the set scoring threshold, the cleaning controller (33) controls the telescopic camera side cover to be in a retracted state, and the circulating cleaning liquid cleaning component does not work. When the unmanned vehicle working condition analysis module (1) analyzes that the visual image quality is less than the set scoring threshold, the cleaning controller (33) performs a cleaning action. The cleaning action is to control the telescopic camera side cover to be in an extended state, control the circulating cleaning liquid cleaning component to start circulating cleaning liquid and ultrasonic cleaning, and retract after a set time. The cleaning action is repeated three times according to the set time.

2. The vehicle-mounted camera self-cleaning and image enhancement system for harsh working conditions according to claim 1, characterized in that: The system further includes an image enhancement module (4), the image enhancement module (4) including a buffer (41) and a GPU chip (42), the buffer (41) being respectively connected to the unmanned vehicle camera module (2) and the vehicle control system (100), and the GPU chip (42) being respectively connected to the unmanned vehicle working condition analysis module (1) and the buffer (41), and if the unmanned vehicle working condition analysis module (1) determines that the visual image quality is less than a set scoring threshold, the image enhancement module (4) intervenes, and the GPU chip (42) enhances the visual image collected by the unmanned vehicle camera module (2) based on the image enhancement algorithm and stores the enhanced visual image in the buffer (41), and the vehicle control system (100) uses the enhanced visual image stored in the buffer (41).

3. The vehicle-mounted camera self-cleaning and image enhancement system for harsh working conditions according to claim 2, characterized in that: The unmanned vehicle operating condition analysis module (1) comprises a memory (11), a visual analysis chip (12) and a data analysis chip (13), wherein the memory (11) is communicatively connected to the unmanned vehicle-mounted camera module (2), the visual analysis chip (12) is communicatively connected to the memory (11), and the data analysis chip (13) is communicatively connected to the visual analysis chip (12).

4. The vehicle-mounted camera self-cleaning and image enhancement system for harsh working conditions according to claim 3, characterized in that: The telescopic camera side cover comprises an electric push rod (311), a side cover bottom plate (312) and a side plate (313), wherein the electric push rod (311) is mounted inside the unmanned vehicle shell, and a side cover through hole is provided in the unmanned vehicle shell surrounding the unmanned vehicle camera module (2), one side of the side cover bottom plate (312) is mounted on the piston rod of the electric push rod (311), and one end of the side plate (313) is mounted on the other side of the side cover bottom plate (312), when the piston rod of the electric push rod (311) is extended, the side plate (313) surrounds the unmanned vehicle camera module (2), and when the piston rod of the electric push rod (311) is retracted, the side plate (313) is retracted, and the end thereof is flush with the unmanned vehicle shell.

5. The vehicle-mounted camera self-cleaning and image enhancement system for harsh working conditions according to claim 4, characterized in that: The circulating cleaning liquid cleaning assembly comprises a circulating cleaning liquid tank (321), a micro pump (322), a connecting hose (323), an ultrasonic generator (324) and a plurality of nozzles (325). The circulating cleaning liquid tank (321) is installed inside the unmanned vehicle housing. A communicating circulating cleaning liquid channel is provided inside the side cover bottom plate (312) and the side plate (313). The micro pump (322) connects the circulating cleaning liquid channel and the circulating cleaning liquid tank (321) via the connecting hose (323). The plurality of nozzles (325) are respectively installed at a plurality of spray holes inside the side plate (313). The ultrasonic generator (324) is installed in the circulating cleaning liquid channel.

6. The vehicle-mounted camera self-cleaning and image enhancement system for harsh working conditions according to claim 5, characterized in that: The cleaning controller (33) includes an instruction buffer (34) and a control chip (35), wherein the instruction buffer (34) is in communication with the unmanned vehicle operating condition analysis module (1), and the control chip (35) is in communication with the instruction buffer (34) and controls the execution actions of the electric push rod (311), the micro pump (322), and the ultrasonic generator (324) respectively.

7. A method for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under harsh working conditions, characterized by: The self-cleaning and image enhancement system for a vehicle-mounted camera under harsh working conditions according to claim 6 is used to control the self-cleaning and image enhancement of the vehicle-mounted camera under harsh working conditions, comprising the following steps: Step 1: The unmanned vehicle-mounted camera module (2) continuously collects raw images, and the raw image data is stored in the memory (11) of the working condition analysis module (1); Step 2: The visual analysis chip (12) performs multi-dimensional analysis to evaluate the visual image quality and outputs a visual image quality score; Step 3, setting a scoring threshold, when the visual image quality score output by the data analysis chip (13) is less than the scoring threshold, the instruction buffer (34) stores a cleaning action instruction; Step 4, the control chip (35) executes the cleaning action instruction, controls the piston rod of the electric push rod (311) to extend, controls the micro pump (322) to start, and controls the ultrasonic generator (324) to start; the cleaning action instruction continues for a set time; and the cleaning action instruction is executed cyclically (3) times every set time.

8. The method for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under severe working conditions according to claim 7, characterized in that: When the visual image quality score output by the data analysis chip (13) is less than the score threshold, the GPU chip (42) obtains the original image from the buffer (41) and sequentially performs bad pixel repair, adaptive defogging, HDR synthesis, and dynamic sharpening to obtain an enhanced visual image.

9. The method for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under severe working conditions according to claim 7, characterized in that: In step 2, the visual image quality assessment includes the following specific steps: Step 21, calculating the Laplacian variance value of the image, calculating the clarity index according to the Laplacian variance value of the image, and setting the weight of the clarity index; Step 22: segment the HSV color space, calculate the percentage of stain pixels to obtain a stain coverage index, and set the weight of the stain coverage index; Step 23, performing optical interference detection to identify halo characteristics to obtain an optical interference index, and setting a weight for the optical interference index; In step 24, each indicator is multiplied by the corresponding weight and the sum is added to obtain a visual image quality score.

10. The method for controlling the self-cleaning and image enhancement of a vehicle-mounted camera under severe working conditions according to claim 7, characterized in that: In step 4, set the time to 10 seconds to 20 seconds.

Images