CN114347905A - Vehicle-mounted driving-assistant panoramic image system - Google Patents
Vehicle-mounted driving-assistant panoramic image system Download PDFInfo
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Abstract
The invention discloses a vehicle-mounted driving-assistant panoramic image system, which comprises: the information acquisition module is used for acquiring information around the vehicle through the panoramic camera equipment and the radar ranging equipment; the obstacle identification module is used for matching the information acquired by the information acquisition module with an obstacle model, determining an obstacle identification and associating the obstacle identification with a corresponding obstacle; the panoramic image forming module is used for integrating information collected by the panoramic camera equipment and the radar ranging equipment to form a panoramic image, and marking all obstacles and obstacle identifiers on the panoramic image; and identifies the distance between the obstacle and the preset position of the vehicle. The barrier mark is displayed in the panoramic image, the distance between the barrier and the vehicle is marked, and under the condition that the panoramic image is deformed or distorted, the barrier can be conveniently and accurately judged by a driver through the distance between the barrier and the vehicle and the barrier mark, so that safe driving is realized.
Description
Technical Field
The invention relates to the technical field of vehicle-mounted systems, in particular to a vehicle-mounted driving-assistant panoramic image system.
Background
With the rapid development of economy and the continuous progress of society, automobiles gradually replace other vehicles and become the most important travel tool in modern society. However, since the observation range of the driver is limited during the driving of the vehicle, there are many "blind spots", and tragedies such as scratches, even rolling, etc. may occur inadvertently.
At present, in order to enable a driver to monitor the surrounding situation of a vehicle in real time, many manufacturers respectively install a wide-angle camera at the front, back, left and right of the vehicle for collecting images, finally display a synthesized overhead bird's-eye view image in real time in a video display device in the vehicle through the steps of camera inside and outside parameter calibration, perspective transformation and the like, so as to provide the information around the vehicle for the driver, improve the driving safety, and because the perspective transformation is the transformation between two planes, the method realizes the transformation from an original distortion correction image to the overhead bird's-eye view image by utilizing the perspective transformation, so that the information above the horizon line in the scene cannot be reserved in the overhead bird's-eye view image. In addition, when the overhead view has a large visual field, non-ground objects (such as nearby pedestrians and trees) may be projected onto the ground, which may cause a significant stretching phenomenon of the image in the overhead view, which is not conducive to the driver to intuitively and quickly understand the surrounding scene, and thus, the potential safety hazard still exists.
Disclosure of Invention
The invention provides a vehicle-mounted driving-assistant panoramic image system, which is used for solving the problems in the prior art.
Compared with the prior art, the invention has the following advantages:
the invention provides a vehicle-mounted driving-assistant panoramic image system, which comprises:
the information acquisition module is used for acquiring information around the vehicle through the panoramic camera equipment and the radar ranging equipment;
the obstacle identification module is used for matching the information acquired by the information acquisition module with an obstacle model, determining an obstacle identification and associating the obstacle identification with a corresponding obstacle;
the panoramic image forming module is used for integrating information collected by the panoramic camera equipment and the radar ranging equipment to form a panoramic image, and marking all obstacles and obstacle identifiers on the panoramic image; and identifies the distance between the obstacle and the preset position of the vehicle.
Preferably, the method further comprises the following steps:
a panoramic image display module for displaying the panoramic image formed by the panoramic image forming module on the panoramic image display module;
and the human-computer interaction module is used for determining display nodes of the panoramic image on the panoramic image display module in a human-computer interaction mode.
Preferably, the panoramic image display module comprises a sub-display unit and an area display switching unit, the sub-display unit divides the panoramic image into a plurality of sub-display areas according to areas, one or more sub-display areas can be displayed on the panoramic image display module, and the displayed panoramic image or the sub-display areas are freely switched through the area display switching unit; the free switching mode comprises the step of carrying out autonomous intelligent switching on the corresponding display nodes through autonomously learning the habits of the users.
Preferably, the panoramic camera equipment comprises a plurality of 180-degree wide-angle cameras which are respectively arranged on the outer edges of two rearview mirrors of the vehicle and two sides of a front license plate and a rear license plate; a 180-degree wide-angle camera arranged on one of the two sides of the front license plate and the rear license plate shoots a video or an image above the vehicle;
radar range finding equipment measures the position relation between all obstacles and the vehicle preset position in the preset range around the vehicle through short wave radar technology, the position relation includes: distances and angles between an obstacle and a plurality of preset positions of the vehicle; or the distance and angle between different positions of an obstacle relative to a particular preset position of the vehicle.
Preferably, the obstacle model comprises a big data acquisition unit, an obstacle feature extraction unit and a deep neural network classification identification unit;
the big data acquisition unit acquires images of different obstacles at different angles through a big database, the obstacle feature extraction unit performs obstacle feature analysis on the acquired images and extracts obstacle features, the deep neural network classification unit classifies the extracted obstacle features in a deep learning mode, obstacle identifiers are formed according to classification results, and the classified obstacle identifiers, the obstacle images and the obstacle features are in one-to-one correspondence to form an obstacle model based on obstacle feature matching.
Preferably, the deep neural network classification unit has a plurality of classification bases, including dividing the deep neural network classification unit into a dynamic barrier and a static barrier according to the dynamic and static states of the barrier, and forming a dynamic barrier identifier and a static barrier identifier;
the obstacle is divided into a cylindrical obstacle, a circular obstacle, a conical obstacle, a square or rectangular obstacle according to the shape of the obstacle; and forming barrier marks in corresponding shapes;
dividing the obstacle into an oversized obstacle, a large obstacle and a small obstacle according to the volume of the obstacle; and forming obstacle identifications of corresponding volume classifications;
dividing the obstacle into point obstacles, line obstacles, surface obstacles and body obstacles according to the obstacle forming rule; and forming barrier marks with corresponding rules;
the same barrier can be classified into different barrier categories according to different classification bases to form different barrier identifications.
Preferably, the obstacle identification module associates the obstacle identification with a corresponding obstacle, and accordingly, after the panoramic image is formed in the panoramic image forming module, the obstacle identification needs to be marked on the obstacle of the panoramic image, and when a certain obstacle on the panoramic image is blurred and unclear, the obstacle identification can determine the characteristics of the obstacle, so that the obstacle can be conveniently viewed by a driver.
Preferably, the panoramic image forming module identifies a distance between the obstacle and a preset position of the vehicle, when the vehicle and the obstacle both move relatively, the distance between the obstacle and the preset position of the vehicle is a relative distance, and when the vehicle and the obstacle move, the preset position of the obstacle and the preset position of the vehicle will change, and correspondingly, the distance between the obstacle and a certain preset position of the vehicle will be converted into the distance between the obstacle and another preset position of the vehicle.
Preferably, in the panoramic image forming module, the obstacle in the panoramic image is analyzed through the obstacle in the image collected by the panoramic camera device to form a first anchor point, the obstacle around the vehicle is determined through the radar ranging device, and a second anchor point of the obstacle is formed in the radar ranging image; establishing locking association between a first anchor point of an obstacle in the panoramic image and a second anchor point in the radar ranging image, displaying a distance value between the obstacle and a preset position of the vehicle on the panoramic image, and changing the displayed distance value along with the change of the distance between the obstacle and the preset position of the vehicle;
the preset vehicle positions can be set through a vehicle-mounted control system, the vehicle-mounted control system automatically sets the preset vehicle positions through the driving years of a driver, and when the driving years of the driver are smaller, the number of the preset vehicle positions is larger.
Preferably, the obstacle identification comprises a danger level identification of the obstacle, the danger level of the obstacle judges the danger level of the obstacle according to the danger level of the obstacle recorded in the cloud server, probability statistics is carried out on feedback data to determine a temporary danger level of the obstacle, the temporary danger level is defined as the danger level of the obstacle when the temporary danger level does not change after a preset time, and a corresponding danger level identification is set;
and in the panoramic image forming module, when the distance between the obstacle and the preset position of the vehicle is smaller than a preset value, or the number of the danger levels of the obstacle in the panoramic image, which is higher than the set level, exceeds the set number, the panoramic image forming module is determined as an emergency, and the driver is reminded through the emergency mark in the panoramic image.
The invention provides a vehicle-mounted driving-assistant panoramic image system, which comprises: the information acquisition module is used for acquiring information around the vehicle through the panoramic camera equipment and the radar ranging equipment;
the obstacle identification module is used for matching the information acquired by the information acquisition module with an obstacle model, determining an obstacle identification and associating the obstacle identification with a corresponding obstacle;
the panoramic image forming module is used for integrating information collected by the panoramic camera equipment and the radar ranging equipment to form a panoramic image, and marking all obstacles and obstacle identifiers on the panoramic image; and identifies the distance between the obstacle and the preset position of the vehicle.
Therefore, by adopting the scheme provided by the invention, not only the image information of the panoramic camera equipment is collected, but also the obstacle information around the vehicle collected by the radar ranging equipment is collected, the obstacle is identified according to the difference of the obstacles, the obstacle identification is displayed in the panoramic image, if the obstacle displayed in the panoramic image is not clear or has deformation, the type of the obstacle can be determined through the obstacle identification under the condition that a driver cannot accurately judge the obstacle, the obstacle is basically identified, the distance between the obstacle and the vehicle is directly marked on the panoramic image, and also under the condition that the panoramic image has deformation or distortion, the obstacle can be conveniently and accurately judged by the driver through the distance between the obstacle and the vehicle and the obstacle identification, so that safe driving is realized.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
fig. 1 is a schematic structural diagram of a vehicle-mounted driving assistant panoramic image system according to an embodiment of the present invention;
FIG. 2 is a schematic illustration of a panoramic image according to an embodiment of the present invention;
fig. 3 is a schematic diagram of a panoramic image with obstacle identifications and distances according to an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
An embodiment of the present invention provides a vehicle-mounted driving assistance panoramic image system, as shown in fig. 1, the system includes:
the information acquisition module is used for acquiring information around the vehicle through the panoramic camera equipment and the radar ranging equipment;
the obstacle identification module is used for matching the information acquired by the information acquisition module with an obstacle model, determining an obstacle identification and associating the obstacle identification with a corresponding obstacle;
the panoramic image forming module is used for integrating information collected by the panoramic camera equipment and the radar ranging equipment to form a panoramic image, and marking all obstacles and obstacle identifiers on the panoramic image; and identifies the distance between the obstacle and the preset position of the vehicle.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that an information acquisition module is arranged and used for acquiring information around a vehicle through panoramic camera equipment and radar ranging equipment;
the obstacle identification module is used for matching the information acquired by the information acquisition module with an obstacle model, determining an obstacle identification and associating the obstacle identification with a corresponding obstacle;
the panoramic image forming module is used for integrating information collected by the panoramic camera equipment and the radar ranging equipment to form a panoramic image, and marking all obstacles and obstacle identifiers on the panoramic image; and identifies the distance between the obstacle and the preset position of the vehicle.
The beneficial effects of the above technical scheme are: the scheme information acquisition module provided by the embodiment is used for acquiring information around the vehicle through the panoramic camera equipment and the radar ranging equipment;
the obstacle identification module is used for matching the information acquired by the information acquisition module with an obstacle model, determining an obstacle identification and associating the obstacle identification with a corresponding obstacle;
the panoramic image forming module is used for integrating information collected by the panoramic camera equipment and the radar ranging equipment to form a panoramic image, and marking all obstacles and obstacle identifiers on the panoramic image; and identifies the distance between the obstacle and the preset position of the vehicle.
Therefore, the scheme provided by the embodiment is adopted to collect not only the image information of the panoramic camera device, but also the obstacle information around the vehicle collected by the radar ranging device, identify the obstacle according to the difference of the obstacles, display the obstacle identification in the panoramic image, determine the type of the obstacle through the obstacle identification under the condition that the driver cannot accurately judge the obstacle when the obstacle displayed in the panoramic image is fuzzy or deformed, basically identify the obstacle, directly mark the distance between the obstacle and the vehicle on the panoramic image, and facilitate the driver to accurately judge the obstacle through the distance between the obstacle and the vehicle and the obstacle identification under the condition that the panoramic image is deformed or distorted so as to realize safe driving.
In another embodiment, a panoramic image presentation module for displaying the panoramic image formed by the panoramic image forming module on the panoramic image presentation module;
and the human-computer interaction module is used for determining display nodes of the panoramic image on the panoramic image display module in a human-computer interaction mode.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the panoramic image display module is used for displaying the panoramic image formed by the panoramic image forming module on the panoramic image display module;
and the human-computer interaction module is used for determining display nodes of the panoramic image on the panoramic image display module in a human-computer interaction mode.
The beneficial effects of the above technical scheme are: the panoramic image display module of the scheme provided by the embodiment is used for displaying the panoramic image formed by the panoramic image forming module on the panoramic image display module;
and the human-computer interaction module is used for determining display nodes of the panoramic image on the panoramic image display module in a human-computer interaction mode.
In another embodiment, as shown in fig. 2, the panoramic image display module includes a sub-display unit and a sub-display switching unit, the sub-display unit divides the panoramic image into a plurality of sub-display areas according to areas, one or more sub-display areas can be displayed on the panoramic image display module, and the displayed panoramic image or the sub-display areas are freely switched by the sub-display switching unit; the free switching mode comprises the step of carrying out autonomous intelligent switching on the corresponding display nodes through autonomously learning the habits of the users.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the panoramic image display module comprises a sub-area display unit and an area display switching unit, the sub-area display unit divides the panoramic image into a plurality of sub-display areas according to areas, one or more sub-display areas can be displayed on the panoramic image display module, and the displayed panoramic image or the sub-display areas are freely switched through the area display switching unit; the free switching mode comprises the step of carrying out autonomous intelligent switching on the corresponding display nodes through autonomously learning the habits of the users.
The beneficial effects of the above technical scheme are: the panoramic image display module comprises a sub-display unit and an area display switching unit, wherein the sub-display unit divides the panoramic image into a plurality of sub-display areas according to areas, one or more sub-display areas can be displayed on the panoramic image display module, and the displayed panoramic image or the sub-display areas are freely switched through the area display switching unit; the free switching mode comprises the step of carrying out autonomous intelligent switching on the corresponding display nodes through autonomously learning the habits of the users.
In another embodiment, the panoramic camera device comprises a plurality of 180-degree wide-angle cameras which are respectively arranged on the outer edges of two rearview mirrors of the vehicle and on two sides of a front license plate and a rear license plate; a 180-degree wide-angle camera arranged on one of the two sides of the front license plate and the rear license plate shoots a video or an image above the vehicle;
radar range finding equipment measures the position relation between all obstacles and the vehicle preset position in the preset range around the vehicle through short wave radar technology, the position relation includes: distances and angles between an obstacle and a plurality of preset positions of the vehicle; or the distance and angle between different positions of an obstacle relative to a particular preset position of the vehicle.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the panoramic camera equipment comprises a plurality of 180-degree wide-angle cameras which are respectively arranged on the outer edges of two rearview mirrors of a vehicle and on two sides of a front license plate and a rear license plate of the vehicle; a 180-degree wide-angle camera arranged on one of the two sides of the front license plate and the rear license plate shoots a video or an image above the vehicle;
radar range finding equipment measures the position relation between all obstacles and the vehicle preset position in the preset range around the vehicle through short wave radar technology, the position relation includes: distances and angles between an obstacle and a plurality of preset positions of the vehicle; or the distance and angle between different positions of an obstacle relative to a particular preset position of the vehicle.
The beneficial effects of the above technical scheme are: the panoramic shooting equipment adopting the scheme provided by the embodiment comprises a plurality of 180-degree wide-angle cameras which are respectively arranged at the outer edges of two rearview mirrors of a vehicle and at the two sides of a front license plate and a rear license plate of the vehicle; a 180-degree wide-angle camera arranged on one of the two sides of the front license plate and the rear license plate shoots a video or an image above the vehicle;
radar range finding equipment measures the position relation between all obstacles and the vehicle preset position in the preset range around the vehicle through short wave radar technology, the position relation includes: distances and angles between an obstacle and a plurality of preset positions of the vehicle; or the distance and angle between different positions of an obstacle relative to a particular preset position of the vehicle.
In another embodiment, the obstacle model comprises a big data acquisition unit, an obstacle feature extraction unit and a deep neural network classification identification unit;
the big data acquisition unit acquires images of different obstacles at different angles through a big database, the obstacle feature extraction unit performs obstacle feature analysis on the acquired images and extracts obstacle features, the deep neural network classification unit classifies the extracted obstacle features in a deep learning mode, obstacle identifiers are formed according to classification results, and the classified obstacle identifiers, the obstacle images and the obstacle features are in one-to-one correspondence to form an obstacle model based on obstacle feature matching.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the obstacle model comprises a big data acquisition unit, an obstacle feature extraction unit and a deep neural network classification identification unit;
the big data acquisition unit acquires images of different obstacles at different angles through a big database, the obstacle feature extraction unit performs obstacle feature analysis on the acquired images and extracts obstacle features, the deep neural network classification unit classifies the extracted obstacle features in a deep learning mode, obstacle identifiers are formed according to classification results, and the classified obstacle identifiers, the obstacle images and the obstacle features are in one-to-one correspondence to form an obstacle model based on obstacle feature matching.
The beneficial effects of the above technical scheme are: the obstacle model adopting the scheme provided by the embodiment comprises a big data acquisition unit, an obstacle feature extraction unit and a deep neural network classification identification unit;
the big data acquisition unit acquires images of different obstacles at different angles through a big database, the obstacle feature extraction unit performs obstacle feature analysis on the acquired images and extracts obstacle features, the deep neural network classification unit classifies the extracted obstacle features in a deep learning mode, obstacle identifiers are formed according to classification results, and the classified obstacle identifiers, the obstacle images and the obstacle features are in one-to-one correspondence to form an obstacle model based on obstacle feature matching.
In another embodiment, the deep neural network classification unit has a plurality of classification bases, including dividing the deep neural network classification unit into dynamic barriers and static barriers according to the dynamic and static states of the barriers, and forming dynamic barrier identifiers and static barrier identifiers;
the obstacle is divided into a cylindrical obstacle, a circular obstacle, a conical obstacle, a square or rectangular obstacle according to the shape of the obstacle; and forming barrier marks in corresponding shapes;
dividing the obstacle into an oversized obstacle, a large obstacle and a small obstacle according to the volume of the obstacle; and forming obstacle identifications of corresponding volume classifications;
dividing the obstacle into point obstacles, line obstacles, surface obstacles and body obstacles according to the obstacle forming rule; and forming barrier marks with corresponding rules;
the same barrier can be classified into different barrier categories according to different classification bases to form different barrier identifications.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the deep neural network classification unit has a plurality of classification bases, including dividing the deep neural network classification unit into dynamic barriers and static barriers according to the dynamic and static states of the barriers to form dynamic barrier identifications and static barrier identifications;
the obstacle is divided into a cylindrical obstacle, a circular obstacle, a conical obstacle, a square or rectangular obstacle according to the shape of the obstacle; and forming barrier marks in corresponding shapes;
dividing the obstacle into an oversized obstacle, a large obstacle and a small obstacle according to the volume of the obstacle; and forming obstacle identifications of corresponding volume classifications;
dividing the obstacle into point obstacles, line obstacles, surface obstacles and body obstacles according to the obstacle forming rule; and forming barrier marks with corresponding rules;
the same barrier can be classified into different barrier categories according to different classification bases to form different barrier identifications.
The beneficial effects of the above technical scheme are: the deep neural network classification unit is divided into a plurality of classification bases by adopting the scheme provided by the embodiment, and comprises a dynamic barrier and a static barrier according to the dynamic and static states of the barrier, so as to form a dynamic barrier identifier and a static barrier identifier;
the obstacle is divided into a cylindrical obstacle, a circular obstacle, a conical obstacle, a square or rectangular obstacle according to the shape of the obstacle; and forming barrier marks in corresponding shapes;
dividing the obstacle into an oversized obstacle, a large obstacle and a small obstacle according to the volume of the obstacle; and forming obstacle identifications of corresponding volume classifications;
dividing the obstacle into point obstacles, line obstacles, surface obstacles and body obstacles according to the obstacle forming rule; and forming barrier marks with corresponding rules;
the same barrier can be classified into different barrier categories according to different classification bases to form different barrier identifications.
In another embodiment, the obstacle identification module associates the obstacle identification with the corresponding obstacle, and accordingly, after the panoramic image is formed in the panoramic image forming module, the obstacle identification needs to be marked on the obstacle of the panoramic image, and when a certain obstacle on the panoramic image is blurred and unclear, the obstacle identification can determine the characteristics of the obstacle, so that the obstacle can be conveniently viewed by the driver.
The working principle of the technical scheme is as follows: the obstacle identification module associates an obstacle identification with a corresponding obstacle, and correspondingly, after a panoramic image is formed in the panoramic image forming module, the obstacle identification needs to be marked on the obstacle of the panoramic image, and when a certain obstacle on the panoramic image is blurred and unclear, the obstacle identification can be used for determining the characteristics of the obstacle, so that the obstacle identification is convenient for a driver to view.
The beneficial effects of the above technical scheme are: by adopting the scheme provided by the embodiment, the obstacle identification module associates the obstacle identification with the corresponding obstacle, correspondingly, after the panoramic image is formed in the panoramic image forming module, the obstacle identification needs to be marked on the obstacle of the panoramic image, and when a certain obstacle on the panoramic image is blurred and unclear, the obstacle identification can be used for determining the characteristics of the obstacle, so that the obstacle identification is convenient for a driver to view.
In another embodiment, the panoramic image forming module identifies a distance between an obstacle and a preset position of the vehicle, when the vehicle and the obstacle both move relatively, the distance between the obstacle and the preset position of the vehicle is a relative distance, and when the vehicle and the obstacle move, the obstacle and the preset position of the vehicle will change in position, and accordingly, the distance between the obstacle and a certain preset position of the vehicle will be converted into the distance between the obstacle and another preset position of the vehicle.
The working principle of the technical scheme is as follows: the scheme that this embodiment adopted is distance between the position is predetermine to sign barrier and vehicle in the panorama image formation module, and when vehicle and barrier all take place relative motion, the distance between barrier and the vehicle preset position is relative distance, and when vehicle and barrier in the motion process, barrier and vehicle preset position will take place position change, and correspondingly, the distance between certain preset position of barrier and vehicle will be converted into the distance between another preset position of barrier and vehicle.
The beneficial effects of the above technical scheme are: adopt the scheme that this embodiment provided the distance between the position is predetermine to sign barrier and vehicle in the panorama image formation module, when vehicle and barrier all take place relative motion, the distance between barrier and the vehicle preset position is relative distance, and when vehicle and barrier in the motion process, barrier and vehicle preset position will take place position change, and correspondingly, the distance between certain preset position of barrier and vehicle will be converted into the distance between another preset position of barrier and vehicle.
In another embodiment, the panoramic image forming module forms a first anchor point for the obstacle in the panoramic image through obstacle analysis in the image collected by the panoramic camera device, determines the obstacle around the vehicle through the radar ranging device, and forms a second anchor point for the obstacle in the radar ranging image; establishing locking association between a first anchor point of an obstacle in the panoramic image and a second anchor point in the radar ranging image, displaying a distance value between the obstacle and a preset position of the vehicle on the panoramic image, and changing the displayed distance value along with the change of the distance between the obstacle and the preset position of the vehicle;
the preset vehicle positions can be set through a vehicle-mounted control system, the vehicle-mounted control system automatically sets the preset vehicle positions through the driving years of a driver, and when the driving years of the driver are smaller, the number of the preset vehicle positions is larger.
The working principle of the technical scheme is as follows: in the panoramic image forming module, a first anchor point is formed on an obstacle in a panoramic image through obstacle analysis in an image acquired by a panoramic camera device, obstacles around a vehicle are determined through a radar ranging device, and a second anchor point of the obstacle is formed in the radar ranging image; and establishing locking association between a first anchor point of an obstacle in the panoramic image and a second anchor point in the radar ranging image, displaying a distance value between the obstacle and the preset position of the vehicle on the panoramic image, and changing the displayed distance value along with the change of the distance between the obstacle and the preset position of the vehicle.
In addition, before the anchor point is set, the obstacle in the panoramic image needs to be segmented, and the specific processing method is as follows:
determining cluster centers and membership functions by the following formulas:
g is a clustering center, T (ij) is a membership function, t is a weight parameter for adjusting the influence of pixels in a neighborhood on a segmentation result, c is the number of clustering groups, k is a variable and takes the value from 1 to c; m is a convergence constant, a constant greater than 1, the larger m the faster m the convergence, usually between 1.5 and 2.5, xiIs the gray level of the ith pixel point, yjGray level of cluster center of jth category, PiIs a pixel point xiSet of pixels in eight neighborhoods, PTAs a set PiNumber of middle pixels, xsThe gray value of the s-th pixel point of the image in the neighborhood; s is the variable value of the image pixel point in the neighborhood, and s belongs to Pi；
And finally, determining which category the pixel point belongs to according to the convergence characteristics of the membership function, and further determining the contour line of the obstacle.
The beneficial effects of the above technical scheme are: in the panoramic image forming module adopting the scheme provided by the embodiment, a first anchor point is formed by the obstacle in the panoramic image through obstacle analysis in the image acquired by the panoramic camera equipment, the obstacle around the vehicle is determined by the radar ranging equipment, and a second anchor point of the obstacle is formed in the radar ranging image; and establishing locking association between a first anchor point of an obstacle in the panoramic image and a second anchor point in the radar ranging image, displaying a distance value between the obstacle and the preset position of the vehicle on the panoramic image, and changing the displayed distance value along with the change of the distance between the obstacle and the preset position of the vehicle.
In another embodiment, as shown in fig. 3, the obstacle identifiers on the panoramic image include danger level identifiers of obstacles, the danger level identifiers of the obstacles are judged according to the danger level identifiers of the obstacles recorded in the cloud server, the fed-back data is subjected to probability statistics to determine a temporary danger level of the obstacles, and when the temporary danger level does not change in level after a preset time, the temporary danger level is defined as the danger level of the obstacle, and a corresponding danger level identifier is set;
and in the panoramic image forming module, when the distance between the obstacle and the preset position of the vehicle is smaller than a preset value, or the number of the danger levels of the obstacle in the panoramic image, which is higher than the set level, exceeds the set number, the panoramic image forming module is determined as an emergency, and the driver is reminded through the emergency mark in the panoramic image.
The working principle of the technical scheme is as follows: the scheme adopted by the embodiment is that the obstacle identification comprises a danger level identification of the obstacle, the danger level of the obstacle is judged according to the danger level of the obstacle recorded in the cloud server, probability statistics is carried out on feedback data to determine the temporary danger level of the obstacle, when the temporary danger level does not change in level after a preset time, the temporary danger level is defined as the danger level of the obstacle, and a corresponding danger level identification is set;
and in the panoramic image forming module, when the distance between the obstacle and the preset position of the vehicle is smaller than a preset value, or the number of the danger levels of the obstacle in the panoramic image, which is higher than the set level, exceeds the set number, the panoramic image forming module is determined as an emergency, and the driver is reminded through the emergency mark in the panoramic image.
The beneficial effects of the above technical scheme are: according to the scheme provided by the embodiment, the obstacle identification comprises a danger level identification of the obstacle, the danger level of the obstacle is judged according to the danger level of the obstacle recorded in the cloud server, probability statistics is carried out on feedback data to determine the temporary danger level of the obstacle, when the temporary danger level does not change in level after a preset time, the temporary danger level is defined as the danger level of the obstacle, and a corresponding danger level identification is set;
and in the panoramic image forming module, when the distance between the obstacle and the preset position of the vehicle is smaller than a preset value, or the number of the danger levels of the obstacle in the panoramic image, which is higher than the set level, exceeds the set number, the panoramic image forming module is determined as an emergency, and the driver is reminded through the emergency mark in the panoramic image.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. An on-vehicle driving assistance panoramic image system, characterized by comprising:
the information acquisition module is used for acquiring information around the vehicle through the panoramic camera equipment and the radar ranging equipment;
the obstacle identification module is used for matching the information acquired by the information acquisition module with an obstacle model, determining an obstacle identification and associating the obstacle identification with a corresponding obstacle;
the panoramic image forming module is used for integrating information collected by the panoramic camera equipment and the radar ranging equipment to form a panoramic image, and marking all obstacles and obstacle identifiers on the panoramic image; and identifies the distance between the obstacle and the preset position of the vehicle.
2. The vehicle-mounted driving assistance panoramic image system according to claim 1, characterized by further comprising:
a panoramic image display module for displaying the panoramic image formed by the panoramic image forming module on the panoramic image display module;
and the human-computer interaction module is used for determining display nodes of the panoramic image on the panoramic image display module in a human-computer interaction mode.
3. The vehicle-mounted driving assistance panoramic image system according to claim 2, wherein the panoramic image display module comprises a sub-display unit and a sub-display switching unit, the sub-display unit divides the panoramic image into a plurality of sub-display areas according to areas, one or more sub-display areas can be displayed on the panoramic image display module, and the displayed panoramic image or the sub-display areas are freely switched by the sub-display switching unit; the free switching mode comprises the step of carrying out autonomous intelligent switching on the corresponding display nodes through autonomously learning the habits of the users.
4. The vehicle-mounted driving-assistant panoramic image system according to claim 2, wherein the panoramic camera device comprises a plurality of 180-degree wide-angle cameras which are respectively arranged on the outer edges of two rearview mirrors of the vehicle and on two sides of a front license plate and a rear license plate; a 180-degree wide-angle camera arranged on one of the two sides of the front license plate and the rear license plate shoots a video or an image above the vehicle;
radar range finding equipment measures the position relation between all obstacles and the vehicle preset position in the preset range around the vehicle through short wave radar technology, the position relation includes: distances and angles between an obstacle and a plurality of preset positions of the vehicle; or the distance and angle between different positions of an obstacle relative to a particular preset position of the vehicle.
5. The vehicle-mounted driving assistance panoramic image system according to claim 1, wherein the obstacle model comprises a big data acquisition unit, an obstacle feature extraction unit and a deep neural network classification identification unit;
the big data acquisition unit acquires images of different obstacles at different angles through a big database, the obstacle feature extraction unit performs obstacle feature analysis on the acquired images and extracts obstacle features, the deep neural network classification unit classifies the extracted obstacle features in a deep learning mode, obstacle identifiers are formed according to classification results, and the classified obstacle identifiers, the obstacle images and the obstacle features are in one-to-one correspondence to form an obstacle model based on obstacle feature matching.
6. The vehicle-mounted driving assistance panoramic image system according to claim 5, wherein the deep neural network classification unit is classified into a plurality of groups according to dynamic and static states of obstacles, and forms a dynamic obstacle identifier and a static obstacle identifier;
the obstacle is divided into a cylindrical obstacle, a circular obstacle, a conical obstacle, a square or rectangular obstacle according to the shape of the obstacle; and forming barrier marks in corresponding shapes;
dividing the obstacle into an oversized obstacle, a large obstacle and a small obstacle according to the volume of the obstacle; and forming obstacle identifications of corresponding volume classifications;
dividing the obstacle into point obstacles, line obstacles, surface obstacles and body obstacles according to the obstacle forming rule; and forming barrier marks with corresponding rules;
the same barrier can be classified into different barrier categories according to different classification bases to form different barrier identifications.
7. The vehicle-mounted driving assistance panoramic image system according to claim 1, wherein the obstacle identification module associates obstacle identifications with corresponding obstacles, and accordingly, after the panoramic image is formed in the panoramic image forming module, the obstacle identifications need to be marked on the obstacles in the panoramic image, and when a certain obstacle on the panoramic image is blurred and not clear, the characteristics of the obstacle can be determined through the obstacle identifications, so that the driver can conveniently view the obstacle identifications.
8. The vehicle-mounted driving assistant panoramic image system according to claim 1, wherein the panoramic image forming module identifies a distance between an obstacle and a preset position of the vehicle, the distance between the obstacle and the preset position of the vehicle is a relative distance when the vehicle and the obstacle move relatively, and the distance between the obstacle and the preset position of the vehicle changes when the vehicle and the obstacle move, and accordingly the distance between the obstacle and a certain preset position of the vehicle is converted into a distance between the obstacle and another preset position of the vehicle.
9. The vehicle-mounted driving assistance panoramic image system according to claim 1, wherein in the panoramic image forming module, a first anchor point is formed by an obstacle in the panoramic image through obstacle analysis in an image collected by the panoramic camera device, an obstacle around the vehicle is determined through the radar ranging device, and a second anchor point is formed by the obstacle in the radar ranging image; establishing locking association between a first anchor point of an obstacle in the panoramic image and a second anchor point in the radar ranging image, displaying a distance value between the obstacle and a preset position of the vehicle on the panoramic image, and changing the displayed distance value along with the change of the distance between the obstacle and the preset position of the vehicle;
the preset vehicle positions can be set through a vehicle-mounted control system, the vehicle-mounted control system automatically sets the preset vehicle positions through the driving years of a driver, and when the driving years of the driver are smaller, the number of the preset vehicle positions is larger.
10. The vehicle-mounted driving assistance panoramic image system according to claim 9, wherein the obstacle identifiers include obstacle danger level identifiers, the obstacle danger levels are judged according to the obstacle danger levels recorded in the cloud server, the fed-back data is subjected to probability statistics to determine temporary danger levels of the obstacles, the temporary danger levels are defined as the danger levels of the obstacles when no level change occurs in the temporary danger levels after a preset time, and corresponding danger level identifiers are set;
and in the panoramic image forming module, when the distance between the obstacle and the preset position of the vehicle is smaller than a preset value, or the number of the danger levels of the obstacle in the panoramic image, which is higher than the set level, exceeds the set number, the panoramic image forming module is determined as an emergency, and the driver is reminded through the emergency mark in the panoramic image.
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| CN116661501A (en) * | 2023-07-24 | 2023-08-29 | 北京航空航天大学 | Unmanned aerial vehicle cluster high dynamic environment obstacle avoidance and moving platform landing combined planning method |
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