CN106209546A - Based on binocular camera and area array cameras automatic with car system - Google Patents
Based on binocular camera and area array cameras automatic with car system Download PDFInfo
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- CN106209546A CN106209546A CN201610573014.1A CN201610573014A CN106209546A CN 106209546 A CN106209546 A CN 106209546A CN 201610573014 A CN201610573014 A CN 201610573014A CN 106209546 A CN106209546 A CN 106209546A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L12/40006—Architecture of a communication node
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
- B60R1/00—Optical viewing arrangements; Real-time viewing arrangements for drivers or passengers using optical image capturing systems, e.g. cameras or video systems specially adapted for use in or on vehicles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W50/08—Interaction between the driver and the control system
- B60W50/14—Means for informing the driver, warning the driver or prompting a driver intervention
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T1/00—General purpose image data processing
- G06T1/0007—Image acquisition
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L12/00—Data switching networks
- H04L12/28—Data switching networks characterised by path configuration, e.g. LAN [Local Area Networks] or WAN [Wide Area Networks]
- H04L12/40—Bus networks
- H04L2012/40208—Bus networks characterized by the use of a particular bus standard
- H04L2012/40215—Controller Area Network CAN
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- Transportation (AREA)
- Traffic Control Systems (AREA)
- Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
Abstract
This application discloses a kind of based on binocular camera and area array cameras automatic with car system, including: area array cameras, gather front vehicles and the image information on road surface, and image information is delivered to FPGA module；Binocular camera, gathers the fore-and-aft distance between front truck and this car；FPGA module, carries out pretreatment to the view data of area array cameras and binocular camera collection, and this pretreatment includes distortion correction and image filtering；Embedded controller, identifies the characteristics of image of front truck, and calculates vehicle traveling control parameter, and it is mutual to realize the information between vehicle-mounted control computer；Vehicle-mounted control computer, in order to start tracking system so that makes vehicle follow front truck with certain following distance and travels on given track.Use the system of the present invention, can actively controlling with garage drives into row vehicle, help driver to control vehicle traveling direction and travel speed, it is possible to decrease driver is tired, reduce contingency occurrence probability, and increase traffic system efficiency.
Description
Technical field
The present invention, based on road environment identification and detection technique field, particularly relates to a kind of based on binocular camera dough-making powder battle array phase
The auxiliary of machine is with car system and method.
Background technology
In recent years, Domestic Automotive Industry develops rapidly, automobile pollution also cumulative year after year, but vehicle accident and road block up
The frequency of plug is consequently increased.Due to the increase of automobile, the average speed of vehicle is caused to decline so that driver needs for a long time
Focus on following front vehicles, easily cause driving fatigue, cause vehicle accident.
Summary of the invention
It is an object of the invention to provide a kind of based on binocular camera and area array cameras automatic with car system, existing to overcome
There is the deficiency in technology.
For achieving the above object, the present invention provides following technical scheme:
The embodiment of the present application discloses a kind of based on binocular camera and area array cameras automatic with car system, including:
Area array cameras, gathers front vehicles and the image information on road surface, and image information is delivered to FPGA module；
Binocular camera, gathers the fore-and-aft distance between front truck and this car；
FPGA module, carries out pretreatment to the view data of area array cameras and binocular camera collection, and this pretreatment includes abnormal
Become and correct and image filtering, then the signal after process is delivered to embedded controller；
Embedded controller, for realizing the post processing to view data, identifies the characteristics of image of front truck, and calculates car
Travel control parameter, and realize and vehicle-mounted control computer between information mutual；
Vehicle-mounted control computer, in order to start tracking system so that make vehicle with certain following distance follow front truck to
Determine to travel on track.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with in car system, described vehicle-mounted control electricity
It is connected by CAN between brain with embedded controller.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with, in car system, also including speaker, will
The operating result of pro-active intervention feeds back to driver.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with in car system, described embedded Control
The image information that device utilizes area array cameras to collect determines this car and the position relationship of both sides traffic lane line, is ensureing that vehicle travels
On the premise of former track, embedded controller is according to Ben Che and front truck and the relative fore-and-aft distance of road, lateral separation and works as
Front speed, calculates suitable speed control parameter numerical value, then by CAN, control parameter passes to vehicle-mounted control electricity
Brain, vehicle-mounted control computer is according to the corner of these speed control parameter numerical control electric power-aid steering electric machines and the spray of electromotor
Oil, the parameter of air inflow, make vehicle follow front truck with certain following distance and travel on given track.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with in car system, the traveling of described vehicle,
Drive parameter includes the speed of vehicle, steering wheel angle information, brake pedal and the angle information of gas pedal.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with, in car system, meeting automatically with car
During the condition terminated, vehicle-mounted control computer carries out pro-active intervention to the traveling of vehicle, terminate automatically with car, automatically terminates with car
Condition is selected from:
(1), driver intervenes the traveling of automobile；
(2), front vehicles lane change, turn, turn around.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with in car system, the image of described front truck
Feature includes license board information.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with in car system, described vehicle-mounted control electricity
Brain includes touch screen controller, selects characteristics of image to be followed the tracks of by touch screen controller, and starts tracking system.
Preferably, above-mentioned based on binocular camera and area array cameras automatic with in car system, described distortion correction
Method includes:
If Pw(Xw, Yw, Zw) it is a bit in world coordinate system, PC(XC, YC, ZC) it is that this point is in binocular camera or face battle array phase
Coordinate under machine coordinate, Pd(u, v) is the image coordinate of this point under ideal model, uses below equation to carry out image flame detection:
In formula, M is the projection matrix of 3 × 4, by experimental calibration, obtains the projection matrix of M, and then utilizes Metzler matrix
Camera image is corrected.
Compared with prior art, it is an advantage of the current invention that: the present invention utilizes area array cameras and binocular camera to check this
Car and front vehicles and the distance of road, and interacted with vehicle-mounted computer by CAN, the traveling of vehicle is carried out actively
Controlling, help driver to control vehicle traveling direction and travel speed, it is possible to decrease driver is tired, minimizing accident occurs general
Rate, and increase traffic system efficiency.
Accompanying drawing explanation
In order to be illustrated more clearly that the embodiment of the present application or technical scheme of the prior art, below will be to embodiment or existing
In having technology to describe, the required accompanying drawing used is briefly described, it should be apparent that, the accompanying drawing in describing below is only this
Some embodiments described in application, for those of ordinary skill in the art, on the premise of not paying creative work,
Other accompanying drawing can also be obtained according to these accompanying drawings.
Fig. 1 show in the specific embodiment of the invention based on binocular camera and area array cameras automatic with the principle of car system
Block diagram；
Fig. 2 show a kind of typical vehicle feature recognition schematic diagram；
Fig. 3 show in the specific embodiment of the invention calculation flow chart beating rudder amount；
Fig. 4 show the algorithm flow chart of image binaryzation in the specific embodiment of the invention；
Fig. 5 show the road image in the specific embodiment of the invention after Morphological scale-space；
Fig. 6 show in the specific embodiment of the invention a kind of typical BP neural network structure figure；
Fig. 7 show the layout schematic diagram of binocular camera in the specific embodiment of the invention；
Fig. 8 show the range measurement principle of binocular camera in the specific embodiment of the invention；
Fig. 9 show speed and acceleration calculation flow chart in the specific embodiment of the invention；
Figure 10 show the feedback mechanism functional-block diagram of speed and acceleration in the specific embodiment of the invention；
Figure 11 show system in the specific embodiment of the invention and judges to terminate automatically with the condition flow chart of car；
Figure 12 show in the specific embodiment of the invention graph of relation of maximum steering wheel angle and speed.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out detailed retouching
State, it is clear that described embodiment is only a part of embodiment of the present invention rather than whole embodiments.Based on the present invention
In embodiment, the every other enforcement that those of ordinary skill in the art are obtained on the premise of not making creative work
Example, broadly falls into the scope of protection of the invention.
See Fig. 1 based on binocular camera and area array cameras automatic with the structural representation of car system, including speaker 1,
Area array cameras 2, FPGA module 3, embedded controller 4, CAN 5, vehicle-mounted control computer 6, binocular camera 7, FPGA module 8,
Touch screen 9.
Further illustrate based on binocular camera and area array cameras automatic with the control of car system in conjunction with specific embodiment
Method:
1, the operation trigger condition of system
Time in vehicle traveling and track, driver can start auxiliary with car system by touch screen 9.After system start-up,
Area array cameras 2 obtains vehicle front road information, and picture signal is delivered to FPGA module 3 carries out distortion correction and image filter
Ripple, is then delivered to embedded controller 4 the picture signal after rectification.Embedded controller 4 processes the picture number after correction
According to, identify the characteristics of image of front truck, such as car plate etc., then output image information and optional characteristics of image on touch screen 9.
Now, user can select characteristics of image to be followed the tracks of by touch screen 9, and system starts to be tracked this characteristics of image.
A kind of typical vehicle feature recognition schematic diagram is as shown in Figure 2.Characteristics of image includes license board information.
2, vehicle front wheel angle control method
The present embodiment utilize area array cameras 2 come collection vehicle and road mark line, road separator and and front truck between
Laterally opposed position data.
After area array cameras 2 collects image, automatically pass data to FPGA module 3 and carry out pretreatment, these pretreatment
Including image distortion rectification, image filtering.
Utilizing embedded A/D modular converter, the signal that area array cameras 2 collects can be converted to numeral letter by FPGA module 3
Number.
The algorithm that pattern distortion is corrected is relevant with the area array cameras camera lens of employing and internal structure thereof.For preferable pin hole
Video camera, if Pw(Xw, Yw, Zw) it is a bit in world coordinate system, PC(XC, YC, ZC) it is this seat under camera coordinates
Mark, Pd(u, is v) image coordinate of this point under preferable pin-hole model, then below equation can be used to carry out image flame detection:
In formula, M is the projection matrix of 3 × 4.By experimental calibration, the projection matrix of M can be obtained, and then utilize M
Camera image is corrected by matrix.
The image arrived due to collected by camera may contain some signal noise, and these signal noises can be in FPGA module 3
In utilize space filtering or frequency domain filtering to eliminate.
After FPGA module 3 has processed image, view data is flowed to embedded controller 4, start to calculate and beat rudder amount, its
Flow process is as shown in Figure 3.
As long as the identification of roadmarking, road separator and vehicle location is based on image pattern recognition.First, to figure
As carrying out image enhaucament, such as image sharpening and contrast stretching, then carry out image binaryzation.
Image Segmentation Technology by carrying out abstract to characteristics of image, thus can extract image outline interested.?
When carrying out image segmentation, need the characteristics of image selecting that there is higher positioning accuracy.As a example by the identification of roadmarking, extracting
During the image outline of roadmarking, can split according to the rectilinearity feature at its edge.By extracting the edge of image, and sentence
Whether disconnected its meets rectilinearity, can pick out the lane line of vehicle both sides.The substantially flow process of its algorithm is as shown in Figure 4.Fig. 5 is
Road image after Morphological scale-space.Afterwards, by identifying the characteristics of image of road, and with the road road sign in java standard library
After line mates, system can pick out the image coordinate location of roadmarking in the picture.
In like manner, by similar method, system can pick out the selected feature of isolation strip and front vehicles in the picture
Position.What the now system it should be noted that obtained is the image coordinate location of these features, and system still needs these
Coordinate carries out Coordinate Conversion, can obtain the true relative position information between vehicle and object of reference.Meanwhile, roadmarking is utilized
Positional information, system utilizes method of least square can simulate road axis and lane line, thus obtain vehicle with
Relative position between road axis with mark border, track.
Embedded controller 4 can obtain current speed at vehicle-mounted control computer 6.Now, system can comprehensive root
According to speed and vehicle position information, calculate and beat rudder amount G, i.e.
G=g (d1, d2, v) (2)
In formula, d1For the distance between vehicle and road axis, d2For the distance between vehicle and front truck, v is working as of vehicle
Front speed.
By neural network learning, three input quantities d can be approached1, d2, v and the function curve exported between G, and profit
With this network of BP Algorithm for Training.A kind of typical BP neural network structure is as shown in Figure 6.Wherein, the output of output layer neuron
For:
Wherein, x 'jFor the output of each hidden neuron, wjkFor the weight of hidden layer to output layer, θkFor hidden layer to output layer
Threshold value.
3, car speed and acceleration control method
The present embodiment uses binocular camera 7 to obtain the range information of this car and front truck.A kind of typical binocular camera cloth
Put form as shown in Figure 7.
The range measurement principle of binocular camera is as shown in Figure 8.Impact point A is double through be made up of the left and right camera that two optical axises are parallel
During mesh range-measurement system, image in the A1 point in left CCD image planes and the A2 point in right CCD image planes, the position in the image planes of left and right respectively
It is respectively xleftAnd xright.Known two focal length of camera are f, can derive tested distance l according to Similar Principle of Triangle:
In formula, x is binocular parallax, x=xlaft-xrtght。
The speed of system and acceleration calculation flow process are as shown in Figure 9.Calculating after being changed by coordinate system, system can obtain
To Ben Che and the actual spacing D of front truck.System knot and this car current vehicle speed v, acceleration a and the actual spacing D with front truck, calculate
Go out required target vehicle speed vtWith aimed acceleration at.Equation below can be used to calculate:
vt=k11·D2+k12·D+p11·v2+p12·v+q11·a2+q12·a+m (5)
at=k21·D2+k22·D+p21·v2+p22·v+q21·a2+q22·a+n (6)
In formula, kij、pij、qij, m, n be fitting formula coefficient.These coefficients equally utilize BP neural network algorithm to ask
Go out.
The feedback mechanism of speed and acceleration is as shown in Figure 10.System is by coming current acceleration, speed and spacing
Judge that each control parameter is the most suitable.
4, the Rule of judgment automatically terminated with car
System judges to terminate the automatic condition with car as shown in figure 11.System needs main according to driving behavior and front truck
Behavior is used as basis for estimation.
Wherein, the operation of steering wheel, gas pedal and brake is identified by driving behavior Main Basis driver.This
Time, system can collect steering wheel angle θf, angular velocityBrake pedal rotational angle thetas, angular velocityWith angular acceleration speedGas pedal rotational angle thetay, plate angular velocityWith angular acceleration speed
In order to set up the relation that contacts between these driving behavior parameter and driver intentions, need to advance with experiment and receive
Collection data are as the learning sample of neutral net.
As a example by steering wheel angle situation.Driver on the operation of steering wheel be affect traffic safety the most directly, most critical
Point volume factor.For steering wheel angle θf, need to add up the maximum steering wheel angle of steering wheel, steering wheel angle standard deviation, side
To dish corner entropy.Wherein, square being inversely proportional to of maximum steering wheel angle and speed, its relation curve is as shown in figure 12.Direction
The variation level of dish standard deviation reflection driver's steering wheel in selected time window and dispersion degree.Steering wheel angle entropy is then used
In evaluating driver's unstability to steering wheel operating, the size that the work of quantization signifying driver psychology meets.Entropy is the biggest,
Showing to operate irregularity the strongest, the mental workload in driver's corresponding moment is the biggest.Steering wheel angular velocityFor weighing driver
The speed stability of twisting steering wheel.Utilize these statistical information above-mentioned, can be at steering wheel angle θfAnd steering wheelWith drive
The person of sailing sets up logical relation between being intended to.
The above is only the detailed description of the invention of the application, it is noted that for the ordinary skill people of the art
For Yuan, on the premise of without departing from the application principle, it is also possible to make some improvements and modifications, these improvements and modifications also should
It is considered as the protection domain of the application.
Claims (9)
1. one kind based on binocular camera and area array cameras automatic with car system, it is characterised in that including:
Area array cameras, gathers front vehicles and the image information on road surface, and image information is delivered to FPGA module；
Binocular camera, gathers the fore-and-aft distance between front truck and this car；
FPGA module, carries out pretreatment to the view data of area array cameras and binocular camera collection, and this pretreatment includes that distortion is rectified
Just and image filtering, then the signal after processing is delivered to embedded controller；
Embedded controller, for realizing the post processing to view data, identifies the characteristics of image of front truck, and calculates vehicle row
Sail control parameter, and it is mutual to realize the information between vehicle-mounted control computer；
Vehicle-mounted control computer, in order to start tracking system so that makes vehicle follow front truck at given car with certain following distance
Travel on road.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: described
It is connected by CAN between vehicle-mounted control computer and embedded controller.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: also wrap
Include speaker, the operating result of pro-active intervention is fed back to driver.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: described
The image information that embedded controller utilizes area array cameras to collect determines this car and the position relationship of both sides traffic lane line, is protecting
Card vehicle travels and on the premise of former track, embedded controller is according to Ben Che and front truck and the relative fore-and-aft distance of road, horizontal stroke
To distance and current vehicle speed, calculate suitable speed control parameter numerical value, then by CAN, control parameter is passed to
Vehicle-mounted control computer, vehicle-mounted control computer according to the corner of these speed control parameter numerical control electric power-aid steering electric machines and
The oil spout of electromotor, the parameter of air inflow, make vehicle follow front truck with certain following distance and travel on given track.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: described
The traveling of vehicle, drive parameter include the angle letter of the speed of vehicle, steering wheel angle information, brake pedal and gas pedal
Breath.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: full
During the condition that foot automatically terminates with car, vehicle-mounted control computer carries out pro-active intervention to the traveling of vehicle, terminates automatically with car, automatically
The condition terminated with car is selected from:
(1), driver intervenes the traveling of automobile；
(2), front vehicles lane change, turn, turn around.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: described
The characteristics of image of front truck includes license board information.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: described
Vehicle-mounted control computer includes touch screen controller, selects characteristics of image to be followed the tracks of by touch screen controller, and starts tracking
System.
It is the most according to claim 1 based on binocular camera and area array cameras automatic with car system, it is characterised in that: described
The method of distortion correction includes:
If Pw(Xw, Yw, Zw) it is a bit in world coordinate system, PC(XC, YC, ZC) it is that this point is sat at binocular camera or area array cameras
Coordinate under Biao, Pd(u, v) is the image coordinate of this point under ideal model, uses below equation to carry out image flame detection:
In formula, M is the projection matrix of 3 × 4, by experimental calibration, obtains the projection matrix of M, and then it is right to utilize Metzler matrix
Camera image is corrected.
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| CN107894767A (en) * | 2016-12-19 | 2018-04-10 | 驭势科技（北京）有限公司 | A kind of automatic driving vehicle transverse movement control object system of selection |
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