CN106240454B - System for providing vehicle collision early warning and vehicle-mounted equipment - Google Patents
System for providing vehicle collision early warning and vehicle-mounted equipment Download PDFInfo
- Publication number
- CN106240454B CN106240454B CN201610653753.1A CN201610653753A CN106240454B CN 106240454 B CN106240454 B CN 106240454B CN 201610653753 A CN201610653753 A CN 201610653753A CN 106240454 B CN106240454 B CN 106240454B
- Authority
- CN
- China
- Prior art keywords
- vehicle
- early warning
- dimensional
- point clouds
- warning area
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000012545 processing Methods 0.000 claims abstract description 43
- 238000000034 method Methods 0.000 claims abstract description 29
- 238000004422 calculation algorithm Methods 0.000 claims description 7
- 230000006870 function Effects 0.000 description 7
- 238000010586 diagram Methods 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 238000004590 computer program Methods 0.000 description 2
- 238000005259 measurement Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 238000011160 research Methods 0.000 description 2
- 238000013461 design Methods 0.000 description 1
- 230000007613 environmental effect Effects 0.000 description 1
- 238000013178 mathematical model Methods 0.000 description 1
- 238000000691 measurement method Methods 0.000 description 1
- 230000002265 prevention Effects 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60Q—ARRANGEMENT OF SIGNALLING OR LIGHTING DEVICES, THE MOUNTING OR SUPPORTING THEREOF OR CIRCUITS THEREFOR, FOR VEHICLES IN GENERAL
- B60Q9/00—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling
- B60Q9/008—Arrangement or adaptation of signal devices not provided for in one of main groups B60Q1/00 - B60Q7/00, e.g. haptic signalling for anti-collision purposes
Landscapes
- Engineering & Computer Science (AREA)
- Human Computer Interaction (AREA)
- Mechanical Engineering (AREA)
- Traffic Control Systems (AREA)
Abstract
The invention provides a system for providing vehicle collision early warning and vehicle-mounted equipment. The system comprises: the point cloud acquirer is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle; at least one processing device for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer; generating a plurality of three-dimensional vehicle early warning areas on a ground plane according to a preset vehicle size; dividing a first geometric body containing a plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area; determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and the warning device is used for sending out vehicle collision warning in a preset mode. The embodiment of the invention can quickly and accurately identify and position the vehicles in the road scene and send out vehicle collision early warning.
Description
Technical Field
The invention relates to the technical field of intelligent vehicle environment perception, in particular to a system for providing vehicle collision early warning and vehicle-mounted equipment.
Background
Among the car safety problems, the car collision problem should be paid sufficient attention. The current automobile anti-collision technology focuses on the research of collision prevention of rear-end collision of vehicles on a straight line, and the core of the technology is the calculation of the safe distance of the vehicles.
In the related technology, a method for measuring the distance of the vehicle mainly utilizes a GPS (global positioning system), and specifically utilizes GPS information to acquire information such as longitude and latitude, speed, course and the like of the vehicle so as to calculate the braking distance. However, the current GPS method has two problems, one is the positioning accuracy, and the error is generally in the order of 10 meters, which is not enough for the vehicle collision avoidance accuracy; another problem is the completeness of information acquisition, for example, only the speed of the vehicle with low accuracy can be acquired by GPS, which is not only problematic in terms of accuracy, but also information of other vehicles can be obtained only by estimation. Thus, there is a need to solve this problem.
Disclosure of Invention
In view of the above, the present invention has been made to provide a system for providing a vehicle collision warning and an in-vehicle apparatus that overcome or at least partially solve the above problems.
According to an aspect of the present invention, there is provided a system for providing a vehicle collision warning, including:
the point cloud acquirer is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle;
at least one processing device for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer;
generating a plurality of three-dimensional vehicle early warning areas on the ground plane according to a preset vehicle size;
dividing a first geometric body containing the plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and
determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area;
and the warning device is used for sending out the vehicle collision warning in a preset mode when the at least one processing device determines that the vehicle collision warning is sent out aiming at the three-dimensional vehicle warning area.
Optionally, the at least one processing device is further configured to:
randomly generating a plurality of three-dimensional areas on the ground plane according to a preset vehicle size, wherein the three-dimensional areas are determined by appointed parameters;
and selecting a three-dimensional area which is less than a specified distance away from the motor vehicle from the plurality of three-dimensional areas as a three-dimensional vehicle early warning area.
Optionally, the specified parameters include at least one of:
three-dimensional coordinates of the center of the vehicle, the size of the vehicle, and the orientation angle of the vehicle on the ground plane.
Optionally, the point cloud obtainer comprises at least one of:
laser radar, binocular camera.
Optionally, when the point cloud acquirer is a laser radar, the laser radar is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle.
Optionally, when the point cloud acquirer is a binocular camera, the binocular camera is configured to capture a plurality of images in a road scene during driving of the motor vehicle, and acquire a plurality of point clouds from the plurality of images.
Optionally, the at least one processing device is further configured to:
and determining point clouds belonging to the ground plane in the road scene in the plurality of point clouds through a random sample consensus (RANSAC) algorithm.
Optionally, the at least one processing device is further configured to:
and discretizing the cuboid containing the point clouds according to a fixed interval, and dividing the discretized cuboid into a set of cubes with a specified number.
Optionally, the at least one processing device is further configured to:
calculating the number of point clouds and/or the average height of the point clouds in each three-dimensional vehicle early warning area by using a three-dimensional integral graph according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area;
and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area according to the number of point clouds and/or the average height of the point clouds in each three-dimensional vehicle early warning area.
Optionally, the at least one processing device is further configured to:
summing and weighting the number of point clouds and the average height of the point clouds in each three-dimensional vehicle early warning area according to the specified weight to obtain a comprehensive score value of each three-dimensional vehicle early warning area;
and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to the comprehensive score value of each three-dimensional vehicle early warning area.
According to another aspect of the invention, an on-board device is also provided, which comprises the system for providing the vehicle collision warning.
The embodiment of the invention provides a novel vehicle collision early warning system which comprises a point cloud acquirer, at least one processing device and an alarm device, wherein the point cloud acquirer is used for acquiring a plurality of point clouds in a road scene in the driving process of a motor vehicle; at least one processing device for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer; generating a plurality of three-dimensional vehicle early warning areas on a ground plane according to a preset vehicle size; dividing a first geometric body containing a plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area; determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and the warning device is used for sending out the vehicle collision warning in a preset mode when the at least one processing device determines that the vehicle collision warning is sent out aiming at the three-dimensional vehicle warning area. Therefore, the embodiment of the invention utilizes the prior knowledge that the vehicle is positioned near the ground level and the template with the known vehicle size to generate a plurality of three-dimensional vehicle early warning areas on the ground level, and further determines whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning areas or not based on the point cloud contained in each three-dimensional vehicle early warning area, thereby rapidly and accurately identifying and positioning the vehicle in the road scene and sending out vehicle collision early warning.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments thereof, taken in conjunction with the accompanying drawings.
Drawings
Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
FIG. 1 illustrates a schematic block diagram of a system for providing early warning of vehicle collisions in accordance with an embodiment of the present invention;
FIG. 2 is a schematic configuration diagram of an in-vehicle apparatus according to an embodiment of the present invention; and
fig. 3 shows a functional classification diagram of a motor vehicle according to an exemplary embodiment of the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
In order to solve the technical problem, the embodiment of the invention provides a system for providing vehicle collision early warning. Fig. 1 shows a schematic structural diagram of a system 100 for providing vehicle collision warning according to an embodiment of the present invention. As shown in fig. 1, the system may include at least a point cloud obtainer 110, at least one processing device 120, and an alarm device 130.
The functions of the components or devices of the system 100 for providing a vehicle collision warning and the connection relationship between the components will now be described:
the point cloud acquirer 110 is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle;
at least one processing device 120, coupled to the point cloud obtainer 110, for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer 110;
generating a plurality of three-dimensional vehicle early warning areas on a ground plane according to a preset vehicle size;
dividing a first geometric body containing a plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area;
determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and
and the warning device 130 is coupled with the at least one processing device 120 and is used for sending out the vehicle collision warning in a preset mode when the at least one processing device 120 determines that the vehicle collision warning is sent out aiming at the three-dimensional vehicle warning area.
The embodiment of the invention provides a novel vehicle collision early warning system which comprises a point cloud acquirer, at least one processing device and an alarm device, wherein the point cloud acquirer is used for acquiring a plurality of point clouds in a road scene in the driving process of a motor vehicle; at least one processing device for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer; generating a plurality of three-dimensional vehicle early warning areas on a ground plane according to a preset vehicle size; dividing a first geometric body containing a plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area; determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and the warning device is used for sending out the vehicle collision warning in a preset mode when the at least one processing device determines that the vehicle collision warning is sent out aiming at the three-dimensional vehicle warning area. Therefore, the embodiment of the invention utilizes the prior knowledge that the vehicle is positioned near the ground level and the template with the known vehicle size to generate a plurality of three-dimensional vehicle early warning areas on the ground level, and further determines whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning areas or not based on the point cloud contained in each three-dimensional vehicle early warning area, thereby rapidly and accurately identifying and positioning the vehicle in the road scene and sending out vehicle collision early warning.
In an alternative embodiment of the present invention, the point cloud obtainer 110 mentioned above may be installed in a motor vehicle to obtain a plurality of point clouds in a road scene during driving of the motor vehicle. The point cloud acquirer 110 may be a laser radar, a binocular camera, or a combination of a laser radar and a binocular camera.
The laser radar is one of important sensors for acquiring external information of the intelligent vehicle, has the advantages of high reliability and real-time performance, high accuracy and the like, and is widely applied to the environmental perception research of the intelligent vehicle. The radar has a plurality of laser sensors, each of which measures discrete data points, which may be expressed as Pi (x, y, z, s), x, y, z respectively representing a three-dimensional physical distance in meters, s representing a reflection intensity, as a dimensionless value. The point cloud data is a large-scale set of discrete measurement point data { P1, P2, P3.., PN }, which provides sufficient information for the basic shape features and structural details of the reduction-type measurement object. When the point cloud acquirer 110 is a laser radar, the laser radar may acquire a plurality of point clouds in a road scene during the driving process of the motor vehicle, and may acquire a three-dimensional coordinate (XYZ) and a laser reflection Intensity (Intensity) of the point clouds.
The binocular camera is characterized in that two cameras are placed on the same plane to shoot a target object to obtain a plurality of groups of corresponding object image pairs, and the cameras and the object accord with the triangulation principle, and meanwhile, the three-dimensional information of the object is calculated by adopting the parallax of corresponding points, so that the three-dimensional point cloud data of the object is obtained. When the point cloud acquirer 110 is a binocular camera, a plurality of images in a road scene can be captured during the driving process of the motor vehicle, a plurality of point clouds can be acquired from the plurality of images, and the three-dimensional coordinates (XYZ) and the color information (RGB) of the point clouds can be acquired.
When the point cloud acquirer 110 is a combination of a laser radar and a binocular camera, three-dimensional coordinates (XYZ), laser reflection Intensity (Intensity), and color information (RGB) of the point cloud may be obtained.
In an optional embodiment of the present invention, when determining the ground plane in the road scene, the at least one processing device 120 may determine, through a RANdom Sample Consensus (RANdom Sample Consensus) algorithm, a point cloud belonging to the ground plane in the road scene from among the plurality of point clouds, and further determine the ground plane in the road scene.
RANSAC can iteratively estimate the parameters of the mathematical model from a set of observed data sets containing "outliers". It is an uncertain algorithm with a certain probability to get a reasonable result. The basic assumptions of RANSAC are:
(1) the data consists of "local points", for example: the distribution of the data can be interpreted with some model parameters;
(2) "outliers" are data that cannot fit into the model;
(3) the data beyond this is noise.
The reasons for the occurrence of the out-of-office points are: extreme values of noise, wrong measurement methods, wrong assumptions on the data. RANSAC also makes the following assumptions: given a set of (usually small) local points, there is a process that can estimate the parameters of a model that can be interpreted or adapted to the local points.
The input to the RANSAC algorithm is a set of observations, a parameterized model that can be interpreted or adapted to the observations, some trusted parameters. RANSAC achieves this goal by iteratively selecting a set of random subsets in the data. The selected subset is assumed to be an in-office point and verified by the following method:
1) a model is adapted to the assumed local interior point, that is, all unknown parameters can be calculated from the assumed local interior point;
2) testing all other data with the model obtained in 1), and if a certain point is suitable for the estimated model, considering it to be an in-office point;
3) if enough points are classified as the assumed intra-office points, the estimated model is reasonable enough;
4) then, all the assumed intra-office points are used to re-estimate the model, since it is estimated only by the initial assumed intra-office points;
5) finally, the model is evaluated by estimating the error rate of the local interior point and the model.
This process is repeated a fixed number of times, each time the resulting model is either discarded because there are too few local points or selected for use because it is better than the existing models.
In the embodiment of the invention, a large amount of point clouds in the input point cloud data belong to a ground plane, and the ground plane can be estimated robustly by using the RANSAC algorithm. Ground plane pi ═ (a, b, c, d)TThe reference coordinate system is an observation coordinate system which takes the sensor as the center through the parameterized representation of the four-dimensional vector.
In an optional embodiment of the present invention, when the at least one processing device 120 generates the plurality of three-dimensional vehicle warning regions on the ground plane according to the preset vehicle size, the plurality of three-dimensional regions may be randomly generated on the ground plane according to the preset vehicle size, where the three-dimensional regions are determined by the designated parameters; and then selecting a three-dimensional area with a distance less than a specified distance from the motor vehicle from the plurality of three-dimensional areas as a three-dimensional vehicle early warning area. The specified parameter here may be a three-dimensional coordinate of the center of the vehicle, a size of the vehicle, an orientation angle of the vehicle on the ground plane, and the like, and the present invention is not limited thereto.
Specifically, according to a preset vehicle size, when a plurality of three-dimensional regions are randomly generated on a ground plane, under a natural lane scene, assuming that vehicles are all located near a road surface (i.e., the ground plane) (without considering the extreme conditions of suspended vehicles and the like), a size template (length, width and height) of the vehicle is input according to a known vehicle type, slight disturbance is made near the road surface, and meanwhile, possible orientation angles of the vehicle template are traversed, so that M possible three-dimensional regions can be obtained, and the three-dimensional regions can be determined by 7 parameters (x, y, z, l, w, h, theta), wherein (x, y, z) represents three-dimensional coordinates of the center of the vehicle; (l, w, h) are length, width and height templates of the vehicle; θ represents the orientation angle of the vehicle on the horizontal plane.
In addition, in another optional embodiment of the invention, the three-dimensional vehicle early warning area can be selected from a plurality of three-dimensional areas by combining the information of the size, the speed, the direction and the like of the motor vehicle.
In an alternative embodiment of the present invention, the at least one processing device 120 may discretize the rectangular solid including the plurality of point clouds at fixed intervals into a set of a specified number of cubes when dividing the first geometry including the plurality of point clouds into a set of a specified number of second geometries. Specifically, a cuboid containing all input three-dimensional point clouds is discretized at fixed intervals and divided into a plurality of small cube sets, and then for the M three-dimensional vehicle early warning areas obtained above, each three-dimensional vehicle early warning area corresponds to a plurality of small cube sets in the area. Here, the specified number may be set according to actual requirements, for example, a larger specified number is set if it is necessary to divide a smaller cube.
After one or more second geometric objects included in each three-dimensional vehicle early warning area are obtained, because each second geometric object includes at least one point cloud in a road scene, the at least one processing device 120 may determine the characteristics of each three-dimensional vehicle early warning area according to the one or more second geometric objects included in each three-dimensional vehicle early warning area, and may further identify and locate vehicles in the three-dimensional vehicle early warning area according to the characteristics of each three-dimensional vehicle early warning area, and determine whether to issue a vehicle collision early warning for the three-dimensional vehicle early warning area. The characteristic of the three-dimensional vehicle early warning area may be the number of point clouds, the average height of the point clouds, the ratio of the number of the point clouds to the upper and lower sides, and the like, which are contained in the three-dimensional vehicle early warning area, and the invention is not limited thereto. In the optional embodiment of the invention, the characteristics of each three-dimensional vehicle early warning area can be calculated by using the three-dimensional integral map, the calculation complexity is O (1), the calculation amount is saved, and the characteristics of a large number of three-dimensional vehicle early warning areas can be quickly calculated.
Further, the at least one processing device 120 may identify and locate vehicles in the three-dimensional vehicle early warning area according to the number of point clouds included in the three-dimensional vehicle early warning area, and determine whether to issue a vehicle collision early warning for the three-dimensional vehicle early warning area; or identifying and positioning the vehicles in the three-dimensional vehicle early warning area according to the average height of the point cloud contained in the three-dimensional vehicle early warning area, and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area; or identifying and positioning the vehicles in the three-dimensional vehicle early warning area by combining the number of point clouds and the average height of the point clouds in the three-dimensional vehicle early warning area, and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area. Here, the number of point clouds and the average height of the point clouds included in each three-dimensional vehicle early warning region may be summed and weighted according to a specified weight to obtain a comprehensive score value of each three-dimensional vehicle early warning region, and then whether to issue a vehicle collision early warning for the three-dimensional vehicle early warning region is determined according to the comprehensive score value of each three-dimensional vehicle early warning region, for example, when the comprehensive score value is greater than a specified threshold, it is determined to issue a vehicle collision early warning for the three-dimensional vehicle early warning region. The specified threshold value can be set according to actual requirements, and the invention is not limited to this.
When the at least one processing device 120 determines that a vehicle collision warning is issued for the three-dimensional vehicle warning region, the warning device 130 issues the vehicle collision warning in a preset manner. The preset mode may be voice, or a combination of voice and image, etc., and the present invention is not limited thereto.
The system for providing vehicle collision early warning provided by the embodiment of the invention is a real-time system, and can be applied to the driving process of a motor vehicle, wherein the point cloud acquirer 110 acquires a plurality of point clouds in a road scene in real time; the at least one processing device 120 can perform real-time processing to determine whether to issue a vehicle collision warning for each of the three-dimensional vehicle warning areas. When the at least one processing device 120 determines that a vehicle collision warning is issued for the three-dimensional vehicle warning region, the warning device 130 issues the vehicle collision warning in a form of voice, image, or the like.
Based on the same inventive concept, as shown in fig. 2, an embodiment of the present invention further provides an on-board device 200, including the system 100 for providing a vehicle collision warning as described in any one of the above.
Fig. 3 shows some functional categories included in a motor vehicle, such as an intelligent control function, a basic control function, an expansion function, a common function, and the like, where the in-vehicle device 200 provided in the embodiment of the present invention may be classified into the expansion function. It is to be understood that such is by way of illustration and not of limitation.
According to any one or a combination of the above preferred embodiments, the following advantages can be achieved by the embodiments of the present invention:
the embodiment of the invention provides a novel vehicle collision early warning system and vehicle-mounted equipment, wherein the system comprises a point cloud acquirer, at least one processing device and an alarm device, wherein the point cloud acquirer is used for acquiring a plurality of point clouds in a road scene in the driving process of a motor vehicle; at least one processing device for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer; generating a plurality of three-dimensional vehicle early warning areas on a ground plane according to a preset vehicle size; dividing a first geometric body containing a plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area; determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and the warning device is used for sending out the vehicle collision warning in a preset mode when the at least one processing device determines that the vehicle collision warning is sent out aiming at the three-dimensional vehicle warning area. Therefore, the embodiment of the invention utilizes the prior knowledge that the vehicle is positioned near the ground level and the template with the known vehicle size to generate a plurality of three-dimensional vehicle early warning areas on the ground level, and further determines whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning areas or not based on the point cloud contained in each three-dimensional vehicle early warning area, thereby rapidly and accurately identifying and positioning the vehicle in the road scene and sending out vehicle collision early warning.
In the description provided herein, numerous specific details are set forth. It is understood, however, that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures and techniques have not been shown in detail in order not to obscure an understanding of this description.
Similarly, it should be appreciated that in the foregoing description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the various inventive aspects. However, the disclosed method should not be interpreted as reflecting an intention that: that the invention as claimed requires more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive aspects lie in less than all features of a single foregoing disclosed embodiment. Thus, the claims following the detailed description are hereby expressly incorporated into this detailed description, with each claim standing on its own as a separate embodiment of this invention.
Those skilled in the art will appreciate that the modules in the device in an embodiment may be adaptively changed and disposed in one or more devices different from the embodiment. The modules or units or components of the embodiments may be combined into one module or unit or component, and furthermore they may be divided into a plurality of sub-modules or sub-units or sub-components. All of the features disclosed in this specification (including any accompanying claims, abstract and drawings), and all of the processes or elements of any method or apparatus so disclosed, may be combined in any combination, except combinations where at least some of such features and/or processes or elements are mutually exclusive. Each feature disclosed in this specification (including any accompanying claims, abstract and drawings) may be replaced by alternative features serving the same, equivalent or similar purpose, unless expressly stated otherwise.
Furthermore, those skilled in the art will appreciate that while some embodiments described herein include some features included in other embodiments, rather than other features, combinations of features of different embodiments are meant to be within the scope of the invention and form different embodiments. For example, in the claims, any of the claimed embodiments may be used in any combination.
The various component embodiments of the invention may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof. It will be appreciated by those skilled in the art that a microprocessor or Digital Signal Processor (DSP) may be used in practice to implement some or all of the functions of some or all of the components of the system for providing vehicle collision warning and the on-board device according to embodiments of the present invention. The present invention may also be embodied as apparatus or device programs (e.g., computer programs and computer program products) for performing a portion or all of the methods described herein. Such programs implementing the present invention may be stored on computer-readable media or may be in the form of one or more signals. Such a signal may be downloaded from an internet website or provided on a carrier signal or in any other form.
It should be noted that the above-mentioned embodiments illustrate rather than limit the invention, and that those skilled in the art will be able to design alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses shall not be construed as limiting the claim. The word "comprising" does not exclude the presence of elements or steps not listed in a claim. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention may be implemented by means of hardware comprising several distinct elements, and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by one and the same item of hardware. The usage of the words first, second and third, etcetera do not indicate any ordering. These words may be interpreted as names.
Thus, it should be appreciated by those skilled in the art that while a number of exemplary embodiments of the invention have been illustrated and described in detail herein, many other variations or modifications consistent with the principles of the invention may be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Accordingly, the scope of the invention should be understood and interpreted to cover all such other variations or modifications.
In one aspect of the embodiments of the present invention, a1, a system for providing vehicle collision warning, includes:
the point cloud acquirer is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle;
at least one processing device for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer;
generating a plurality of three-dimensional vehicle early warning areas on the ground plane according to a preset vehicle size;
dividing a first geometric body containing the plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area;
determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and
and the warning device is used for sending out the vehicle collision warning in a preset mode when the at least one processing device determines that the vehicle collision warning is sent out aiming at the three-dimensional vehicle warning area.
A2, the system of A1, wherein the at least one processing device is further configured to:
randomly generating a plurality of three-dimensional areas on the ground plane according to a preset vehicle size, wherein the three-dimensional areas are determined by appointed parameters;
and selecting a three-dimensional area which is less than a specified distance away from the motor vehicle from the plurality of three-dimensional areas as a three-dimensional vehicle early warning area.
A3, the system of A2, wherein the specified parameters include at least one of:
three-dimensional coordinates of the center of the vehicle, the size of the vehicle, and the orientation angle of the vehicle on the ground plane.
A4, the system according to any one of A1-A3, wherein the point cloud obtainer comprises at least one of:
laser radar, binocular camera.
A5, the system according to A4, wherein when the point cloud acquirer is a laser radar, the laser radar is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle.
A6, the system according to A4, wherein when the point cloud acquirer is a binocular camera, the binocular camera is used for capturing a plurality of images in a road scene during the driving process of the motor vehicle and acquiring a plurality of point clouds from the images.
A7, the system of any one of A1-A6, wherein the at least one processing device is further configured to:
and determining point clouds belonging to the ground plane in the road scene in the plurality of point clouds through a random sample consensus (RANSAC) algorithm.
A8, the system of any one of A1-A7, wherein the at least one processing device is further configured to:
and discretizing the cuboid containing the point clouds according to a fixed interval, and dividing the discretized cuboid into a set of cubes with a specified number.
A9, the system of any one of A1-A8, wherein the at least one processing device is further configured to:
calculating the number of point clouds and/or the average height of the point clouds in each three-dimensional vehicle early warning area by using a three-dimensional integral graph according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area;
and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area according to the number of point clouds and/or the average height of the point clouds in each three-dimensional vehicle early warning area.
A10, the system of A9, wherein the at least one processing device is further configured to:
summing and weighting the number of point clouds and the average height of the point clouds in each three-dimensional vehicle early warning area according to the specified weight to obtain a comprehensive score value of each three-dimensional vehicle early warning area;
and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to the comprehensive score value of each three-dimensional vehicle early warning area.
In another aspect of the embodiment of the invention, B11 and vehicle-mounted equipment are further provided, wherein the vehicle-mounted equipment comprises the system for providing the vehicle collision early warning, which is described in any one of A1-A10.
Claims (7)
1. A system for providing vehicle collision warning, comprising:
the point cloud acquirer is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle;
at least one processing device for determining a ground plane in the road scene based on the plurality of point clouds output by the point cloud obtainer;
according to a preset vehicle size, a plurality of three-dimensional vehicle early warning areas are generated on the ground plane, and the method specifically comprises the following steps: randomly generating a plurality of three-dimensional areas on the ground plane according to a preset vehicle size, wherein the three-dimensional areas are determined by appointed parameters; selecting a three-dimensional area which is less than a specified distance away from the motor vehicle from the plurality of three-dimensional areas as a three-dimensional vehicle early warning area;
dividing a first geometric body containing the plurality of point clouds into a set of a specified number of second geometric bodies, and determining one or more second geometric bodies contained in each three-dimensional vehicle early warning area;
determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area; and
the warning device is used for sending out vehicle collision warning in a preset mode when the at least one processing device determines that the vehicle collision warning is sent out aiming at the three-dimensional vehicle warning area;
when the point cloud acquirer is a laser radar, the laser radar is used for acquiring a plurality of point clouds in a road scene in the driving process of the motor vehicle;
when the point cloud acquirer is a binocular camera, the binocular camera is used for shooting a plurality of images in a road scene in the driving process of the motor vehicle, and calculating stereo information from the images through parallax so as to acquire a plurality of point clouds.
2. The system of claim 1, wherein the specified parameters include at least one of:
three-dimensional coordinates of the center of the vehicle, the size of the vehicle, and the orientation angle of the vehicle on the ground plane.
3. The system of claim 1 or 2, wherein the at least one processing device is further configured to:
and determining point clouds belonging to the ground plane in the road scene in the plurality of point clouds through a random sample consensus (RANSAC) algorithm.
4. The system of claim 1 or 2, wherein the at least one processing device is further configured to:
and discretizing the cuboid containing the point clouds according to a fixed interval, and dividing the discretized cuboid into a set of cubes with a specified number.
5. The system of claim 1 or 2, wherein the at least one processing device is further configured to:
calculating the number of point clouds and/or the average height of the point clouds in each three-dimensional vehicle early warning area by using a three-dimensional integral graph according to one or more second geometric bodies contained in each three-dimensional vehicle early warning area;
and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area according to the number of point clouds and/or the average height of the point clouds in each three-dimensional vehicle early warning area.
6. The system of claim 5, wherein the at least one processing device is further to:
summing and weighting the number of point clouds and the average height of the point clouds in each three-dimensional vehicle early warning area according to the specified weight to obtain a comprehensive score value of each three-dimensional vehicle early warning area;
and determining whether to send out vehicle collision early warning aiming at the three-dimensional vehicle early warning area or not according to the comprehensive score value of each three-dimensional vehicle early warning area.
7. An on-board device comprising the system for providing early warning of a vehicle collision of any one of claims 1-6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610653753.1A CN106240454B (en) | 2016-08-10 | 2016-08-10 | System for providing vehicle collision early warning and vehicle-mounted equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201610653753.1A CN106240454B (en) | 2016-08-10 | 2016-08-10 | System for providing vehicle collision early warning and vehicle-mounted equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN106240454A CN106240454A (en) | 2016-12-21 |
| CN106240454B true CN106240454B (en) | 2020-02-04 |
Family
ID=58078210
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201610653753.1A Active CN106240454B (en) | 2016-08-10 | 2016-08-10 | System for providing vehicle collision early warning and vehicle-mounted equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN106240454B (en) |
Families Citing this family (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107662541A (en) * | 2017-08-23 | 2018-02-06 | 六六房车有限公司 | A kind of height of car obstacle caution system |
| CN110516564A (en) * | 2019-08-06 | 2019-11-29 | 深兰科技（上海）有限公司 | Pavement detection method and apparatus |
| CN111002904B (en) * | 2019-12-20 | 2022-04-22 | 铁将军汽车电子股份有限公司 | Front collision early warning system and configuration method and device thereof |
| CN112712733B (en) * | 2020-12-23 | 2022-01-11 | 交通运输部公路科学研究所 | Vehicle-road cooperation-based collision early warning method and system and road side unit |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7529609B2 (en) * | 2004-10-05 | 2009-05-05 | Vision Works Ip Corporation | Absolute acceleration sensor for use within moving vehicles |
| CN102779280A (en) * | 2012-06-19 | 2012-11-14 | 武汉大学 | Traffic information extraction method based on laser sensor |
| CN104149729A (en) * | 2013-05-13 | 2014-11-19 | 上海汽车集团股份有限公司 | Method and system for recognizing barrier around driving vehicle |
| US9296393B2 (en) * | 2013-10-08 | 2016-03-29 | Hyundai Motor Company | Apparatus and method for recognizing vehicle |
| US9327726B2 (en) * | 2004-10-05 | 2016-05-03 | Vision Works Ip Corporation | Absolute acceleration sensor for use within moving vehicles |
-
2016
- 2016-08-10 CN CN201610653753.1A patent/CN106240454B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7529609B2 (en) * | 2004-10-05 | 2009-05-05 | Vision Works Ip Corporation | Absolute acceleration sensor for use within moving vehicles |
| US9327726B2 (en) * | 2004-10-05 | 2016-05-03 | Vision Works Ip Corporation | Absolute acceleration sensor for use within moving vehicles |
| CN102779280A (en) * | 2012-06-19 | 2012-11-14 | 武汉大学 | Traffic information extraction method based on laser sensor |
| CN104149729A (en) * | 2013-05-13 | 2014-11-19 | 上海汽车集团股份有限公司 | Method and system for recognizing barrier around driving vehicle |
| US9296393B2 (en) * | 2013-10-08 | 2016-03-29 | Hyundai Motor Company | Apparatus and method for recognizing vehicle |
Also Published As
| Publication number | Publication date |
|---|---|
| CN106240454A (en) | 2016-12-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11632536B2 (en) | Method and apparatus for generating three-dimensional (3D) road model | |
| US10534091B2 (en) | Method and apparatus for generating road surface, method and apparatus for processing point cloud data, computer program, and computer readable recording medium | |
| JP2022538927A (en) | 3D target detection and intelligent driving | |
| US10909411B2 (en) | Information processing apparatus, information processing method, and computer program product | |
| CN108564615B (en) | Method, device and system for simulating laser radar detection and storage medium | |
| CN106240454B (en) | System for providing vehicle collision early warning and vehicle-mounted equipment | |
| JP2020507137A (en) | System and method for identifying and positioning objects around a vehicle | |
| US10885353B2 (en) | Information processing apparatus, moving object, information processing method, and computer program product | |
| CN106080397B (en) | Self-adaption cruise system and mobile unit | |
| CN109946703B (en) | Sensor attitude adjusting method and device | |
| CN112154454A (en) | Target object detection method, system, device and storage medium | |
| JP6520740B2 (en) | Object detection method, object detection device, and program | |
| WO2006090736A1 (en) | Object recognizing device | |
| CN110674705A (en) | Small-sized obstacle detection method and device based on multi-line laser radar | |
| CN111352074B (en) | Method and system for locating a sound source relative to a vehicle | |
| CN112744217B (en) | Collision detection method, travel path recommendation device, and storage medium | |
| JP6038422B1 (en) | Vehicle determination device, vehicle determination method, and vehicle determination program | |
| WO2022231879A1 (en) | Data driven resolution function derivation | |
| JP5375249B2 (en) | Moving path planning device, moving body control device, and moving body | |
| CN117795378A (en) | System and method for particle filter tracking | |
| CN113428178B (en) | Control method, device and medium for automatically driving vehicle and vehicle | |
| WO2007046336A1 (en) | Object recognizing device | |
| CN115523929B (en) | SLAM-based vehicle-mounted integrated navigation method, device, equipment and medium | |
| JP6813436B2 (en) | Information processing equipment, mobiles, information processing methods, and programs | |
| CN115359332A (en) | Data fusion method and device based on vehicle-road cooperation, electronic equipment and system |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20240113 Address after: 100088 room 112, block D, 28 new street, new street, Xicheng District, Beijing (Desheng Park) Patentee after: BEIJING QIHOO TECHNOLOGY Co.,Ltd. Address before: 100088 room 112, block D, 28 new street, new street, Xicheng District, Beijing (Desheng Park) Patentee before: BEIJING QIHOO TECHNOLOGY Co.,Ltd. Patentee before: Qizhi software (Beijing) Co.,Ltd. |
|
| TR01 | Transfer of patent right |