Automobile anti-collision control method and device

Abstract

The invention relates to an automobile anti-collision control method which comprises the following steps: firstly, controlling a camera module to obtain current image information, obtaining surrounding environment information through the current image information, judging whether the surrounding environment information meets a laser radar operation condition or not, and if the surrounding environment information meets the laser radar operation condition, judging whether the laser radar operates. If the surrounding environment information meets the running condition of the laser radar, the laser radar is preferentially used for anti-collision detection, if the surrounding environment information does not meet the running condition of the laser radar, the camera module is used for anti-collision detection, and meanwhile, the laser radar at the corresponding position can be accurately turned on or turned off by sensing the movement of the vehicle; therefore, the camera module and the laser radar can be accurately and quickly matched for use.

Description

Technical Field

[0001] The present application relates to the field of anti-collision technology, and in particular to a method and device for controlling an automobile anti-collision. Background Art

[0002] Anti-collision vehicles are mainly used in highway construction, tunnel construction, and road construction. They minimize the safety risks of construction vehicles, maintenance personnel, and accident handling traffic police in the maintenance and construction of urban roads and highways. The anti-collision buffer energy absorption module of the anti-collision buffer vehicle is mainly composed of an on-board anti-collision buffer pad and a guide sign frame, acting as a buffer guard behind the construction vehicle. In the event of a rear-end collision, a buffer area can be built between the vehicle and the construction area in front, and the energy of the impact can be absorbed by the deformation of the machine structure, minimizing the probability of collision of the protected personnel and equipment.

[0003] With the advancement of technology, in order to improve the driving safety of vehicles, most vehicles have added automatic collision avoidance systems to improve the driving safety of vehicles. The principle of active collision avoidance is to use high-tech means such as on-board sensors, high-precision maps and computer algorithms to enable vehicles to have functions such as sensing the environment, making judgments and decisions, and executing control, thereby achieving the purpose of vehicle collision avoidance.

[0004] With the popularization of vehicle collision avoidance technology, laser radar or camera systems used for vehicle collision avoidance purposes are becoming more and more popular. However, the use of laser radar will damage the electronic components in the camera module in the surrounding environment, causing the camera module in the surrounding environment to be unable to be used normally. Summary of the invention

[0005] Based on this, it is necessary to provide a vehicle anti-collision control method to address the problem that the use of traditional laser radar will damage the electronic components in the camera module in the surrounding environment, causing the camera module in the surrounding environment to fail to work normally.

[0006] The present application provides a vehicle anti-collision control method, comprising: Control the camera module to obtain current image information; Analyze the current image information and obtain the current surrounding environment information; Determine whether the current surrounding environment information meets the conditions for the operation of the laser radar; If the current surrounding environment information meets the conditions for the operation of the laser radar, the laser radar is enabled; Analyze the laser radar to obtain the laser radar data; Based on the current vehicle operation data, determine whether the lidar data meets the braking conditions; If the laser radar data reaches the braking condition, the vehicle is controlled to brake; If the current surrounding environment information does not meet the conditions for lidar operation, the camera module is enabled; Parse the camera module to obtain the data of the camera module; Based on the current vehicle operation data, determine whether the data of the camera module reaches the braking condition; If the data of the camera module reaches the braking condition, control the vehicle to brake.

[0007] Furthermore, the parsing of the current image information to obtain the current surrounding environment information includes: Preprocess the current image information to obtain the preprocessed current image information; Extract features from the preprocessed current image information to obtain multiple features; Determine whether the multiple obtained features contain a camera; If the multiple obtained features contain a camera, extract the features containing the camera to obtain the extracted features.

[0008] By preprocessing the images contained in the current image information, and then extracting features from the preprocessed images, preprocessing the images can increase the success rate and accuracy of subsequent feature extraction.

[0009] Furthermore, after the step of if the multiple obtained features contain a camera, extract the features containing the camera to obtain the extracted features, it further includes: Select one of the extracted features; Parse the extracted feature to obtain the shooting range information of the camera in the extracted feature; Obtain the scanning range information of the lidar; Determine whether there is an intersection between the shooting range information of the camera and the scanning range information of the lidar; If there is an intersection between the shooting range information of the camera and the scanning range information of the lidar, the current surrounding environment information does not meet the conditions for lidar operation; If there is no intersection between the shooting range information of the camera and the scanning range information of the lidar, return to the step of selecting one of the extracted features; If there is no intersection between the shooting range information of the camera in each of the extracted features and the scanning range information of the lidar, the current surrounding environment information meets the conditions for lidar operation.

[0010] By comparing the shooting range information of multiple cameras in the acquired surrounding environment information with the scanning range information of the lidar one by one, when there is an intersection between the shooting range information of one of the multiple cameras and the scanning range information of the lidar, the current surrounding environment information does not meet the conditions for the lidar to operate. Only when none of the shooting range information of the multiple cameras has an intersection with the scanning range information of the lidar, the current surrounding environment information meets the conditions for the lidar to operate.

[0011] Further, parsing the extracted features to obtain the shooting range information of the camera in the extracted features includes: Establish a three-dimensional coordinate system with the camera module as the origin; Parse the extracted features to obtain the coordinate information of the camera in the three-dimensional coordinates and the tilt angle of the camera in the extracted features; Parse the camera to obtain the shooting range of the camera, and the shooting range of the camera includes the horizontal shooting angle range and the vertical shooting angle range of the camera; Integrate the obtained horizontal shooting angle range and vertical shooting angle range of the camera into the three-dimensional coordinate system to obtain the three-dimensional coordinate system updated for the first time.

[0012] By first establishing a three-dimensional coordinate system with the camera module as the origin, and then integrating the shooting range of the camera in the extracted features into the three-dimensional coordinate system, three-dimensional data based on the position and shooting range of the camera in the current state can be obtained.

[0013] Further, the obtaining of the scanning range information of the lidar includes: Obtain the scanning range of the lidar, and the scanning range of the lidar includes the horizontal scanning angle range and the vertical scanning angle range of the lidar; Integrate the horizontal scanning angle range and the vertical scanning angle range of the lidar into the three-dimensional coordinate system updated for the first time to obtain the three-dimensional coordinate system updated for the second time.

[0014] The installation position of the lidar on the vehicle and the installation position of the camera module are known. By integrating the scanning range of the lidar into the three-dimensional coordinate system again, the scanning range of the lidar and the shooting range of the camera can be compared in the same dimension.

[0015] Further, the judgment of whether there is an intersection between the shooting range information of the camera and the scanning range information of the lidar includes: Parse the three-dimensional coordinate system updated for the second time to obtain the coordinate information of the camera and the shooting range of the camera in the three-dimensional coordinate system updated for the second time; the coordinate information of the lidar and the scanning range of the lidar; If the coordinate information of the camera is within the scanning range of the lidar, and at the same time the coordinate information of the lidar is within the shooting range of the camera, then there is an intersection between the shooting range information of the camera and the scanning range information of the lidar; If the coordinate information of the camera is within the scanning range of the lidar, but the coordinate information of the lidar is not within the shooting range of the camera, then there is no intersection between the shooting range information of the camera and the scanning range information of the lidar; If the coordinate information of the camera is not within the scanning range of the lidar, but the coordinate information of the lidar is within the shooting range of the camera, then there is no intersection between the shooting range information of the camera and the scanning range information of the lidar.

[0016] By comparing the coordinate information of the camera with the coordinate information of the lidar, as well as the shooting range of the camera and the scanning range of the lidar, it is determined whether there is an intersection between the shooting range information of the camera and the scanning range information of the lidar.

[0017] At the same time, it is also possible to control the lidar at other positions to be turned on or off in advance by obtaining the specific coverage data of the camera and the lidar and the changes in the coverage data.

[0018] Further, the determining whether the lidar data reaches the braking condition based on the current vehicle operation data includes: Obtain the current vehicle operation data; Analyze the current vehicle operation data to obtain the driving speed of the current vehicle, the minimum braking distance of the driving speed of the current vehicle, and the driving direction; Analyze the lidar data to obtain the distance to the nearest obstacle in the lidar data and the position direction of the nearest obstacle relative to the current vehicle; Determine whether the current vehicle reaches the braking condition; If the driving direction is the same as the position direction of the nearest obstacle relative to the current vehicle, and at the same time the distance to the nearest obstacle is close to the minimum braking distance of the driving speed of the current vehicle, then the current vehicle reaches the braking condition.

[0019] Through the real-time change of the current vehicle operation data, it is used to analyze in real time whether the lidar data meets the braking condition of the current vehicle. At the same time, it is also possible to predict the lidar data at the next moment based on the current vehicle operation data, and then analyze the lidar data at the next moment or control the operation of the lidar at the next moment.

[0020] Further, the determining whether the camera module data reaches the braking condition based on the current vehicle operation data includes: Obtain the current vehicle operation data; Analyze the current vehicle operation data to obtain the driving speed of the current vehicle, the minimum braking distance of the driving speed of the current vehicle, and the driving direction; Analyze the data of the camera module to obtain the distance to the nearest obstacle and the position and direction of the nearest obstacle relative to the current vehicle in the data of the camera module; Determine whether the current vehicle reaches the braking condition; If the driving direction is consistent with the position and direction of the nearest obstacle relative to the current vehicle, and at the same time the distance to the nearest obstacle is close to the minimum braking distance of the driving speed of the current vehicle, then the current vehicle reaches the braking condition.

[0021] By analyzing the data of the camera module, the distance between the camera module and surrounding objects is further obtained. Based on the current vehicle operation data, it is determined whether the distance between the camera module and surrounding objects meets the braking condition of the current vehicle; at the same time, the vehicle operation state at the next moment can also be predicted based on the current vehicle operation state. The prediction can be assisted by obtaining the steering wheel data, brake data, and throttle data. When the vehicle operation state at the next moment is obtained, the distance between the camera module and surrounding objects at the corresponding next moment can be obtained, which is convenient for judging whether the braking condition will be reached in the future.

[0022] This application also provides an anti-collision device, including: Vehicle body; Detection devices, which are set in multiple numbers. The multiple detection devices are all fixedly connected to the vehicle body. The multiple detection devices are arranged around the vehicle body. The detection devices are used to detect the surrounding environment information, and the detection devices are also used to detect obstacle information; Processing device, fixedly connected to the vehicle body. The multiple detection devices are all communicatively connected to the processing device. The processing device is used to execute the vehicle anti-collision control method as described above.

[0023] The surrounding environment information and obstacle information around the vehicle body are obtained in real time through multiple detection devices, and the obtained surrounding environment information and obstacle information are analyzed and processed by the processing device to obtain a method for specifically controlling the detection devices and a judgment result on whether to brake the current vehicle.

[0024] Further, the detection device includes: Camera module, fixedly connected to the vehicle body. The camera module is used to obtain image information; Lidar, arranged close to the camera module. The lidar is fixedly connected to the camera module. The lidar is used to obtain obstacle information.

[0025] The image information obtained by the camera module is not only used for judging the vehicle braking conditions, but also for judging the conditions for enabling the lidar. The obstacle information obtained by the lidar is only used for judging the vehicle braking conditions.

[0026] This application relates to an automobile anti-collision control method. First, it controls the camera module to obtain the current image information, and obtains the surrounding environmental information through the current image information, and judges whether the surrounding environmental information meets the conditions for the lidar to operate. If the surrounding environmental information meets the conditions for the lidar to operate, the lidar is preferentially used for anti-collision detection. If the surrounding environmental information does not meet the conditions for the lidar to operate, the camera module is used for anti-collision detection. At the same time, it is also possible to accurately turn on or off the corresponding lidar by sensing the vehicle's own movement, so as to achieve precise and rapid coordinated use between the camera module and the lidar. Brief Description of the Drawings

[0027] Figure 1 It is a schematic flowchart of the automobile anti-collision control method provided by an embodiment of this application.

[0028] Figure 2 It is a schematic structural diagram of the anti-collision device provided by an embodiment of this application.

[0029] Figure 3 It is a schematic diagram of the positional relationship between the camera module and the lidar in the anti-collision device provided by an embodiment of this application.

[0030] Reference Signs: 11, vehicle body; 12, detection device; 121, camera module; 122, lidar; 13, processing device. Detailed Description of the Embodiment

[0031] In order to make the purpose, technical solutions and advantages of this application clearer, the following further details this application in conjunction with the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not used to limit this application.

[0032] As Figure 1 shown, in an embodiment of this application, the automobile anti-collision control method includes the following S001 to S011: S001, control the camera module to obtain the current image information.

[0033] Specifically, controlling the camera module to obtain the current image information means taking a picture at the installation angle of the current camera module, and the camera module in this step can also be a real-time video capture. The current image information is further obtained by parsing the real-time video obtained.

[0034] S002. Analyze the current image information to obtain the current surrounding environment information.

[0035] Specifically, the current surrounding environment information refers to the information in the image obtained by the camera module. For example, the information in the image includes pedestrians, guardrails, trees, walls, anti-collision vehicles, buses, transport engineering vehicles, and cameras.

[0036] S003. Determine whether the current surrounding environment information meets the conditions for the lidar to operate.

[0037] Specifically, the conditions for the lidar to operate are established based on the criterion of not damaging the cameras within the working range of the lidar.

[0038] S004. If the current surrounding environment information meets the conditions for the lidar to operate, enable the lidar.

[0039] S005. Analyze the lidar to obtain the lidar data.

[0040] Specifically, the lidar data is the real-time data obtained by the lidar at the current moment for detecting surrounding obstacles.

[0041] S006. Based on the current vehicle operation data, determine whether the lidar data reaches the braking condition.

[0042] Specifically, the current vehicle operation data is the driving data of the current vehicle, which can be obtained through the vehicle's own sensors.

[0043] S007. If the lidar data reaches the braking condition, control the vehicle to brake.

[0044] Specifically, the braking condition is established based on the current vehicle operation data with the aim of not causing collisions.

[0045] S008. If the current surrounding environment information does not meet the conditions for the lidar to operate, enable the camera module.

[0046] S009. Analyze the camera module to obtain the camera module data.

[0047] S010. Based on the current vehicle operation data, determine whether the camera module data reaches the braking condition.

[0048] S011. If the camera module data reaches the braking condition, control the vehicle to brake.

[0049] In this embodiment, the camera module is first controlled to obtain the current image information, and the surrounding environment information is obtained through the current image information, and it is determined whether the surrounding environment information meets the operating conditions of the lidar. If the surrounding environment information meets the operating conditions of the lidar, the lidar is preferentially used for collision avoidance detection. If the surrounding environment information does not meet the operating conditions of the lidar, the camera module is used for collision avoidance detection. At the same time, the lidar at the corresponding position can be accurately turned on or off by sensing the movement of the vehicle itself, so as to achieve the precise and rapid coordinated use between the camera module and the lidar.

[0050] In an embodiment of the present application, the parsing of the current image information to obtain the current surrounding environment information includes the following S002a to S002d: S002a, preprocess the current image information to obtain the preprocessed current image information; Specifically, the current image information includes the current image. Preprocessing the current image information includes performing noise reduction processing on the current image to obtain the current image after noise reduction processing, and then performing feature enhancement processing on the current image after noise reduction processing to obtain the preprocessed current image.

[0051] S002b, extract features from the preprocessed current image information to obtain multiple features; S002c, determine whether the multiple obtained features include a camera; S002d, if the multiple obtained features include a camera, extract the features including the camera to obtain the extracted features.

[0052] In this embodiment, by preprocessing the images included in the current image information, and then extracting features from the preprocessed images, preprocessing the images can increase the success rate and accuracy of subsequent feature extraction.

[0053] In an embodiment of the present application, if the multiple obtained features include a camera, extract the features including the camera to obtain the extracted features, and then the following S002e to S002k are also included: S002e, select one of the extracted features.

[0054] S002f, parse the extracted feature to obtain the shooting range information of the camera in the extracted feature.

[0055] Specifically, for the shooting range information of the camera in the extracted features, the brand information of the camera can be obtained from the extracted features first, and then the corresponding shooting range information can be retrieved; if the brand information of the camera cannot be obtained, the application scenario of the camera is analyzed, and the conventional usage specifications of the scenario are used as the shooting range information of the camera.

[0056] S002g, obtain the scanning range information of the lidar.

[0057] S002h, determine whether there is an intersection between the shooting range information of the camera and the scanning range information of the lidar.

[0058] S002i, if there is an intersection between the shooting range information of the camera and the scanning range information of the lidar, the current surrounding environment information does not meet the conditions for the lidar to operate.

[0059] S002j, if there is no intersection between the shooting range information of the camera and the scanning range information of the lidar, return the selected one of the extracted features.

[0060] S002k, if there is no intersection between the shooting range information of the camera in each of the extracted features and the scanning range information of the lidar, the current surrounding environment information meets the conditions for the lidar to operate.

[0061] In this embodiment, by comparing the shooting range information of multiple cameras in the obtained surrounding environment information with the scanning range information of the lidar one by one, when there is an intersection between one of the shooting range information of multiple cameras and the scanning range information of the lidar, the current surrounding environment information does not meet the conditions for the lidar to operate. Only when there is no intersection between any of the shooting range information of multiple cameras and the scanning range information of the lidar, the current surrounding environment information meets the conditions for the lidar to operate.

[0062] In an embodiment of the present application, the parsing of the extracted features to obtain the shooting range information of the camera in the extracted features includes the following S003f to S006f: S003f, establish a three-dimensional coordinate system with the camera module as the origin.

[0063] S004f, parse the extracted features to obtain the coordinate information of the camera in the three-dimensional coordinates and the tilt angle of the camera.

[0064] S005f, parse the camera to obtain the shooting range of the camera, and the shooting range of the camera includes the horizontal shooting angle range and the vertical shooting angle range of the camera.

[0065] S006f, incorporate the horizontal shooting angle range and vertical shooting angle range of the camera into the three-dimensional coordinate system to obtain the three-dimensional coordinate system after the first update.

[0066] Specifically, the extracted features are compared with the preprocessed image. The coordinate information of the camera in the three-dimensional coordinates and the tilt angle of the camera can both be obtained through the transformation from two dimensions to three dimensions.

[0067] In this embodiment, first establish a three-dimensional coordinate system with the camera module as the origin, and then integrate the shooting range of the camera in the extracted features into the three-dimensional coordinate system, so as to obtain the three-dimensional data based on the camera position and shooting range in the current state.

[0068] In an embodiment of the present application, the obtaining of the scanning range information of the lidar includes the following S003g to S004g: S003g, obtain the scanning range of the lidar, and the scanning range of the lidar includes the horizontal scanning angle range and vertical scanning angle range of the lidar.

[0069] S004g, incorporate the horizontal scanning angle range and vertical scanning angle range of the lidar into the three-dimensional coordinate system after the first update to obtain the three-dimensional coordinate system after the second update.

[0070] Specifically, the scanning range of the lidar can be obtained by analyzing the configuration parameters of the lidar.

[0071] In this embodiment, the installation positions of the lidar on the vehicle and the camera module are known. By integrating the scanning range of the lidar into the three-dimensional coordinate system again, the scanning range of the lidar and the shooting range of the camera can be compared in the same dimension.

[0072] In an embodiment of the present application, the judging whether there is an intersection between the shooting range information of the camera and the scanning range information of the lidar includes the following S003h to S006h: S003h, analyze the three-dimensional coordinate system after the second update to obtain the coordinate information of the camera and the shooting range of the camera in the three-dimensional coordinate system after the second update; the coordinate information of the lidar and the scanning range of the lidar.

[0073] S004h, if the coordinate information of the camera is within the scanning range of the lidar, and at the same time the coordinate information of the lidar is within the shooting range of the camera, then there is an intersection between the shooting range information of the camera and the scanning range information of the lidar.

[0074] S005h, if the coordinate information of the camera is within the scanning range of the lidar, but the coordinate information of the lidar is not within the shooting range of the camera, then there is no intersection between the shooting range information of the camera and the scanning range information of the lidar.

[0075] S006h, if the coordinate information of the camera is not within the scanning range of the lidar, but the coordinate information of the lidar is within the shooting range of the camera, then there is no intersection between the shooting range information of the camera and the scanning range information of the lidar.

[0076] Specifically, the scanning range of the lidar includes the coordinate information of the lidar, the scanning range information of the lidar, and the scanning distance information of the lidar, where the scanning distance information of the lidar is the distance at which the lidar will no longer cause harm to the camera after exceeding a certain distance.

[0077] In this embodiment, by comparing the coordinate information of the camera with the coordinate information of the lidar, and the shooting range of the camera with the scanning range of the lidar, it is determined whether there is an intersection between the shooting range information of the camera and the scanning range information of the lidar.

[0078] At the same time, it is also possible to control the lidar at other positions to be turned on or off in advance by obtaining the specific coverage data of the camera and the lidar and the change of the coverage data.

[0079] In an embodiment of the present application, determining whether the lidar data meets the braking condition based on the current vehicle operation data includes the following S006a to S006e: S006a, obtain the current vehicle operation data.

[0080] S006b, analyze the current vehicle operation data to obtain the driving speed of the current vehicle, the minimum braking distance of the driving speed of the current vehicle, and the driving direction.

[0081] S006c, analyze the lidar data to obtain the distance to the nearest obstacle in the lidar data and the position direction of the nearest obstacle relative to the current vehicle.

[0082] S006d, determine whether the current vehicle meets the braking condition.

[0083] S006e, if the driving direction is consistent with the position direction of the nearest obstacle relative to the current vehicle, and at the same time the distance to the nearest obstacle is close to the minimum braking distance of the driving speed of the current vehicle, then the front vehicle meets the braking condition.

[0084] Specifically, the current vehicle operation data changes in real time, thereby making the lidar data also change in real time.

[0085] In this embodiment, by the real-time change of the current vehicle operation data, it is possible to analyze in real time whether the data of the lidar meets the braking conditions of the current vehicle. At the same time, it is also possible to predict the data of the lidar at the next moment based on the current vehicle operation data. For example, the prediction of the range that the lidar will scan at the next moment, and then analyze the data of the lidar at the next moment or control the operation of the lidar at the next moment, so as to achieve the advanced control of the lidar.

[0086] In an embodiment of the present application, based on the current vehicle operation data, determining whether the data of the camera module reaches the braking conditions includes the following S010a to S010e: S010a, obtain the current vehicle operation data.

[0087] S010b, analyze the current vehicle operation data to obtain the driving speed of the current vehicle, the minimum braking distance of the driving speed of the current vehicle, and the driving direction.

[0088] S010c, analyze the data of the camera module to obtain the distance to the nearest obstacle in the data of the camera module and the position direction of the nearest obstacle relative to the current vehicle.

[0089] S010d, determine whether the current vehicle reaches the braking conditions.

[0090] S010e, if the driving direction is the same as the position direction of the nearest obstacle relative to the current vehicle, and at the same time the distance to the nearest obstacle is close to the minimum braking distance of the driving speed of the current vehicle, then the current vehicle reaches the braking conditions.

[0091] Specifically, the nearest obstacle in the data of the camera module can identify the type of the obstacle by feature extraction of the data of the camera module. When the obstacle is a stationary object such as a wall, a crash vehicle, and a tree, the minimum braking distance of the current vehicle is obtained in real time and compared with the distance between the vehicle and the nearest obstacle. An alarm is issued when the distance between the vehicle and the nearest obstacle is close to the minimum braking distance of the current vehicle.

[0092] When the vehicle loses control for some unknown reason and the speed of the vehicle cannot be decelerated and controlled by artificial means, etc., it is also possible to obtain a feasible safety impact plan by obtaining the data of the camera module in real time. For example, when the vehicle is out of control, by analyzing the features of the data of the camera module, it is obtained that the features of the driving direction of the vehicle are a crash vehicle, a tree, and a wall. By analyzing the energy absorption capabilities of each feature and arranging them in a ranking, the crash vehicle with the highest energy absorption level is used as the highest-level target for the out-of-control vehicle to collide and decelerate.

[0093] In this embodiment, by parsing the data of the camera module, the distance between the camera module and the surrounding objects is obtained, and based on the current vehicle operation data, it is determined whether the distance between the camera module and the surrounding objects meets the braking conditions of the current vehicle; at the same time, the vehicle operation state at the next moment can also be predicted based on the current vehicle operation state, and the prediction can be assisted by obtaining the steering wheel data, brake data, and throttle data. When the vehicle operation state at the next moment is obtained, the corresponding distance between the camera module and the surrounding objects at the next moment can be obtained, which is convenient for judging whether the braking conditions will be reached in the future.

[0094] As Figure 2 shown, in an embodiment of the present application, an anti-collision device is provided, including a vehicle body 11, a plurality of detection devices 12, and a processing device 13.

[0095] A plurality of the detection devices 12 are provided. The plurality of detection devices 12 are fixedly connected to the vehicle body 11. The plurality of detection devices 12 are arranged around the vehicle body 11. The detection device 12 is used to detect the surrounding environment information. The detection device 12 is also used to detect obstacle information.

[0096] The processing device 13 is fixedly connected to the vehicle body 11. The plurality of detection devices 12 are communicatively connected to the processing device 13. The processing device 13 is used to execute the vehicle anti-collision control method as described above.

[0097] Specifically, the processing device 13 is used to process the surrounding environment information and obstacle information obtained from the detection device 12, and through the analysis and judgment of the surrounding environment information and obstacle information, and then issue a control instruction to the detection device 12.

[0098] In this embodiment, the surrounding environment information and obstacle information around the vehicle body 11 are obtained in real time through a plurality of detection devices 12, and the obtained surrounding environment information and obstacle information are analyzed and processed by the processing device 13 to obtain a method for specifically controlling the detection device 12 and a judgment result on whether to brake the current vehicle.

[0099] As Figure 3 shown, in an embodiment of the present application, the detection device 12 includes a camera module 121 and a lidar 122.

[0100] The camera module 121 is fixedly connected to the vehicle body 11. The camera module 121 is used to obtain image information.

[0101] The lidar 122 is arranged close to the camera module 121. The lidar 122 is fixedly connected to the camera module 121. The lidar 122 is used to obtain obstacle information.

[0102] Specifically, the positions of the camera module 121 and the lidar 122 in the same detection device 12 can be approximated to the same position, so as to reduce the calculation of data, improve the time during data processing, and enhance the processing speed.

[0103] In this embodiment, the image information acquired by the camera module 121 is not only used for judging the vehicle braking condition, but also the image information acquired by the camera module 121 is used for judging the condition for enabling the lidar 122, and the obstacle information acquired by the lidar 122 is used for judging the vehicle braking condition.

[0104] The technical features of the above-described embodiments can be combined arbitrarily, and there is no limitation on the execution order of the method steps. For the sake of concise description, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0105] The above-described embodiments only represent several implementation manners of the present application. The description is relatively specific and detailed, but it should not be construed as a limitation on the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A vehicle anti-collision control method, characterized in that: The automobile anti-collision control method comprises: Control the camera module to obtain current image information; Analyze the current image information and obtain the current surrounding environment information; Determine whether the current surrounding environment information meets the conditions for the operation of the laser radar; If the current surrounding environment information meets the conditions for the operation of the laser radar, the laser radar is enabled; Analyze the laser radar to obtain the laser radar data; Based on the current vehicle operation data, determine whether the lidar data meets the braking conditions; If the laser radar data reaches the braking condition, the vehicle is controlled to brake; If the current surrounding environment information does not meet the conditions for the operation of the laser radar, the camera module is enabled; Analyze the camera module to obtain the camera module data; Based on the current vehicle operation data, determine whether the camera module data meets the braking conditions; If the camera module data meets the braking conditions, the vehicle is controlled to brake.

2. The vehicle anti-collision control method according to claim 1, characterized in that: The step of analyzing the current image information to obtain the current surrounding environment information includes: Preprocessing the current image information to obtain preprocessed current image information; Perform feature extraction on the preprocessed current image information to obtain multiple features; Determine whether the obtained multiple features include a camera; If the obtained multiple features include a camera, the features including the camera are extracted to obtain extracted features.

3. The vehicle anti-collision control method according to claim 2, characterized in that: If the obtained multiple features include a camera, the features including the camera are extracted to obtain the extracted features, and then the following steps are further included: Select an extracted feature; Analyze the extracted features to obtain the shooting range information of the camera in the extracted features; Get the scanning range information of the laser radar; Determine whether the camera's shooting range information and the laser radar's scanning range information intersect; If the camera's shooting range information and the laser radar's scanning range information overlap, the current surrounding environment information does not meet the laser radar's operating conditions; If the shooting range information of the camera and the scanning range information of the laser radar do not intersect, then the selected extracted feature is returned; If the shooting range information of the camera and the scanning range information of the lidar in each extracted feature have no intersection, the current surrounding environment information meets the conditions for the operation of the lidar.

4. The vehicle anti-collision control method according to claim 3, characterized in that: The step of analyzing the extracted features to obtain the shooting range information of the camera in the extracted features includes: Establish a three-dimensional coordinate system with the camera module as the origin; Analyze the extracted features to obtain the coordinate information of the camera in the three-dimensional coordinates and the tilt angle of the camera in the extracted features; Analyze the camera to obtain the shooting range of the camera, wherein the shooting range of the camera includes the horizontal shooting angle range and the vertical shooting angle range of the camera; The horizontal shooting angle range and the vertical shooting angle range of the camera are integrated into the three-dimensional coordinate system to obtain the three-dimensional coordinate system after the first update.

5. The vehicle anti-collision control method according to claim 4, characterized in that: The obtaining of the scanning range information of the laser radar includes: Acquire a scanning range of the laser radar, where the scanning range of the laser radar includes a horizontal scanning angle range and a vertical scanning angle range of the laser radar; The horizontal scanning angle range and the vertical scanning angle range of the laser radar are integrated into the three-dimensional coordinate system after the first update to obtain the three-dimensional coordinate system after the second update.

6. The vehicle anti-collision control method according to claim 5, characterized in that: The determining whether the shooting range information of the camera and the scanning range information of the laser radar have an intersection includes: Parse the three-dimensional coordinate system after the second update to obtain the coordinate information of the camera and the shooting range of the camera in the three-dimensional coordinate system after the second update; the coordinate information of the laser radar and the scanning range of the laser radar; If the coordinate information of the camera is within the scanning range of the laser radar, and the coordinate information of the laser radar is within the shooting range of the camera, then the shooting range information of the camera and the scanning range information of the laser radar have an intersection; If the coordinate information of the camera is within the scanning range of the laser radar, but the coordinate information of the laser radar is not within the shooting range of the camera, then the shooting range information of the camera and the scanning range information of the laser radar have no intersection; If the coordinate information of the camera is not within the scanning range of the laser radar, but the coordinate information of the laser radar is within the shooting range of the camera, then the shooting range information of the camera and the scanning range information of the laser radar have no intersection.

7. The vehicle anti-collision control method according to claim 6, characterized in that: The determining, based on the current vehicle operation data, whether the laser radar data meets the braking condition includes: Get current vehicle operation data; Analyze the current vehicle operation data to obtain the current vehicle speed, the minimum braking distance of the current vehicle speed, and the driving direction; Analyze the laser radar data to obtain the distance of the nearest obstacle in the laser radar data and the position direction of the nearest obstacle relative to the current vehicle; Determine whether the current vehicle meets the braking condition; If the driving direction is consistent with the position direction of the nearest obstacle relative to the current vehicle, and the distance of the nearest obstacle is close to the minimum braking distance of the current vehicle's driving speed, the current vehicle meets the braking condition.

8. The vehicle anti-collision control method according to claim 7, characterized in that: The determining, based on the current vehicle operation data, whether the camera module data reaches the braking condition includes: Get current vehicle operation data; Analyze the current vehicle operation data to obtain the current vehicle speed, the minimum braking distance of the current vehicle speed, and the driving direction; Parse the camera module data to obtain the distance of the nearest obstacle and the position direction of the nearest obstacle relative to the current vehicle in the camera module data; Determine whether the current vehicle meets the braking condition; If the driving direction is consistent with the position direction of the nearest obstacle relative to the current vehicle, and the distance of the nearest obstacle is close to the minimum braking distance of the current vehicle's driving speed, the current vehicle meets the braking condition.

9. An anti-collision device, characterized in that: include: Vehicle body; A detection device is provided, wherein the detection devices are fixedly connected to the vehicle body, the detection devices are arranged around the vehicle body, and the detection devices are used to detect surrounding environment information and obstacle information; A processing device is fixedly connected to the vehicle body, and a plurality of the detection devices are communicatively connected to the processing device, and the processing device is used to execute the vehicle anti-collision control method as described in claims 1 to 8 above.

10. The anti-collision device according to claim 9, characterized in that: The detection device comprises: A camera module, fixedly connected to the vehicle body, and used to obtain image information; A laser radar is arranged near the camera module, the laser radar is fixedly connected to the camera module, and the laser radar is used to obtain obstacle information.

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