CN105868469A - Lane departure forewarning method based on perspective image and forewarning model construction method - Google Patents
Lane departure forewarning method based on perspective image and forewarning model construction method Download PDFInfo
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Abstract
The invention relates to a lane departure forewarning method based on a perspective image and a forewarning model construction method. According to the forewarning method, whether a vehicle departs from a lane or not can be precisely judged on the basis of the included angle formed between lane lines and distance signal information between the vehicle gravity center and the longitudinal middle line of the lane in the perspective image. The forewarning method comprises the steps that firstly, the requirement of a system for the initial included angle formed between the left lane line and the right lane line is met by adjusting the installing angle of a camera; secondly, virtual simulation is conducted on a TLC model in an inverse perspective environment through Prescan/simulink software, and then the included angle formed between the left lane line and the right lane line and the distance that the vehicle gravity center departs from the lane center are simulated at different speeds and different yaw angles when the system sends out forewarning prompt, wherein the included angle and the distance are displayed in the perspective image; lastly, a three-dimensional forewarning model based on the lane line included angle and the distance when the vehicle departs from the lane at the different speeds and the different yaw angles is fitted. The forewarning model reminds a driver of the danger of departing from the lane 0.5 s ahead, that is, in-time forewarning is guaranteed, and meanwhile the phenomenon that frequent forewarning causes driving fatigue is avoided.
Description
Technical field
The present invention relates to intelligent transportation field, particularly relate to a kind of deviation based on fluoroscopy images pre-
Alarm method and Early-warning Model construction method.
Background technology
At present, automobile assistant driving technology is paid high attention to colleges and universities by Ge great automobile vendor, and car
Deviation early warning system in road is driven when driver deviates original track due to fatigue driving as one
The automobile assistant driving technology of the person's of sailing alarm, has attracted the concern of large quantities of automobile vendors,
And it is the substantial amounts of manpower and materials of Innovation Input of this system.
Investigation statistics shows, on highway, the vehicle accident close to half deviates original track with vehicle
Relevant, and most of vehicle deviates original track and is caused by fatigue driving.So developing a
Can in the case of driver is unconscious will run-off-road time give driver's early warning remind system compel
At the eyebrows and eyelashes, and the just right early warning moment is most important, is caused the most pre-by giving warning in advance
Alert, driving fatigue, the generation that delayed early warning then can not well avoid traffic accident will be caused.
About the prediction policy of Lane Departure Warning System, mainly include the Early-warning Model of several classics,
And relatively broad with the application of TLC model, but the application of TLC model is based on inverse fluoroscopy images, i.e.
In image, lane line is parallel, and the fluoroscopy images that video camera is photographed, TLC model cannot obtain
Well application.
Summary of the invention
For the problems referred to above, the present invention obtains TLC by the form of Prescan/simulink analog simulation
A kind of new Early-warning Model that model is mapped in fluoroscopy images, thus conveniently carry out in fluoroscopy images
Accurate early warning.It is inclined that the method for early warning of the present invention can carry out accurate track easily in fluoroscopy images
From early warning, and save the complicated miscellaneous step of image conversion, save program runtime, improve
Early warning efficiency.
Specifically, the present invention provides a kind of lane departure warning method based on fluoroscopy images, and it is special
Levy and be, comprise the following steps that
Step 1, the model parameter of setting TLC lane departure warning model；
Step 2, carrying out emulation experiment modeling, modeling process includes: carry on simulating vehicle for
Carry out the sensor of vehicle driving parameters measurement under inverse perspective mode, and under perspective mode, shoot car
The video camera of forward image, regulation sensor measure field and the visual field of video camera, make the two each other
Overlap, speed and traveling yaw angle, travel route and the width of road of vehicle is set；
Step 3, in simulated scenario, utilize sensor to obtain the driving parameters of vehicle under inverse perspective mode
Carry out early warning judgement being supplied to TLC lane departure warning model, simulate in each friction speed, each
In the case of individual different yaw angle, there is the situation of deviation in vehicle in travelling, and, utilize TLC track
Vehicle deviation is reported to the police by deviation Early-warning Model based on the parameter under inverse perspective mode, and records early warning
Sensor measures parameters under fluoroscopy images that moment shot by camera arrives and inverse perspective mode；
Left and right under early warning moment perspective mode in the case of step 4, acquisition friction speed, different yaw angle
Lane line angle and cross track distance information；
Step 5, according to left and right lane line angle and vehicle's center of gravity and the track under deviation moment perspective mode
The distance of center line and the velocity information of vehicle, set up three-dimensional Early-warning Model；
Step 6, according to set up three-dimensional Early-warning Model, by load video simulation verify its Early-warning Model
Effectiveness；
Step 7, perspective mode image based on actual photographed, extract the lane line in perspective mode image
Angle, and obtain the velocity information of vehicle, utilize described three-dimensional based on lane line angle and velocity information
Early-warning Model carries out vehicle deviation early warning.
In a kind of preferred implementation, described step 2 includes:
Step 201: set up the driving path of vehicle in Prescan software, sets the width in track；
Step 202: carry the lane detection sensor-Lane required for Lane Departure Warning System
Marker sensor and video camera, and regulate video camera and the position of sensor and angle so that camera
The aspect ratio that in the picture photographed, sky is pre-set with system with the ratio of road keeps one
Cause；
Step 203: setting speed and the width of vehicle, speed and width information according to vehicle solve car
Yaw angle this moment.
In a kind of preferred implementation, described step 3 includes:
Step 301: be set under same speed, the yaw angle scope of simulating vehicle；
Step 302: simulating the vehicle early warning moment in the case of same speed, different yaw angle, record is pre-
The fluoroscopy images in alert moment；
Step 303: the fluoroscopy images in the early warning moment remained is processed, and records same speed
The left and right lane line angle in early warning moment and the cross track distance in units of pixel when degree, different yaw angle.
In a kind of preferred implementation, described step 1 includes: set by 0.5s before automotive run-off-road
It is set to pre-warning time parameter T,Wherein, y0Represent vehicle's center of gravity away from wanting run-off-road line
Lateral separation, w is the width of vehicle, and v is the absolute velocity of vehicle, and θ is the yaw angle of vehicle.
In a kind of preferred implementation, described step 203 includes: speed based on vehicle and width
Information Pull simulink plug-in unit solves the yaw angle of vehicle.
In a kind of preferred implementation, described step 4 also includes by Vc6.0/Opencv lane line
Extraction procedure extracts lane line angle and vehicle's center of gravity about the early warning moment based on the picture under perspective mode
Range information away from track center line.
In a kind of preferred implementation, set yaw angle scope is θ ∈ [-10 °, 10 °], and vehicle
Velocity interval be v ∈ [0,35m/s].
In a kind of preferred implementation, it is imitative that described method also includes utilizing Prescan software to be simulated
Very, while calculating the position relationship of vehicle and lane line under the inverse perspective mode of image, output figure
Vehicle under the perspective mode of picture and the position relationship of lane line.
On the other hand, the present invention provides a kind of structure lane departure warning based on fluoroscopy images model
Method, it comprises the following steps that
Step 1, the model parameter of setting TLC lane departure warning model；
Step 2, carrying out emulation experiment modeling, modeling process includes: carry on simulating vehicle for
Carry out the sensor of vehicle driving parameters measurement under inverse perspective mode, and under perspective mode, shoot car
The video camera of forward image, regulation sensor measure field and the visual field of video camera, make the two each other
Overlap, speed and traveling yaw angle, travel route and the width of road of vehicle is set；
Step 3, in simulated scenario, utilize sensor to obtain the driving parameters of vehicle under inverse perspective mode
Carry out early warning judgement being supplied to TLC lane departure warning model, simulate in each friction speed, each
In the case of individual different yaw angle, there is the situation of deviation in vehicle in travelling, and, utilize TLC track
Vehicle deviation is reported to the police by deviation Early-warning Model based on the parameter under inverse perspective mode, and records early warning
Sensor measures parameters under fluoroscopy images that moment shot by camera arrives and inverse perspective mode；
In the case of step 4, acquisition friction speed, different yaw angle, the early warning moment is against the left side under perspective mode
Right lane wire clamp angle and cross track distance information, and by lane line angle under acquired inverse perspective mode and
Cross track distance information is associated with the corresponding information in fluoroscopy images；
Step 5, according to left and right lane line angle and vehicle's center of gravity and the track under deviation moment perspective mode
The distance of center line and the velocity information of vehicle, set up three-dimensional Early-warning Model；
Step 6, according to set up three-dimensional Early-warning Model, by load video simulation verify its Early-warning Model
Effectiveness.
It should be noted that the cross track distance being previously mentioned in the present invention refers in vehicle's center of gravity and track
Distance between heart line.
Beneficial effects of the present invention:
(1) present invention can carry out vehicle deviation early warning based on fluoroscopy images, and without by fluoroscopy images
It is converted into inverse fluoroscopy images；
(2) threedimensional model set up can obtain good early warning effect under fluoroscopy images, and effect is equal to
In classical TLC Early-warning Model；
(3) present invention reduces the amount of calculation of method for early warning, it is to avoid the loaded down with trivial details calculating to image
Or conversion, save the sequential operation time；
Accompanying drawing explanation
Fig. 1 is inverse fluoroscopy images under normal circumstances and fluoroscopy images comparison diagram；
Fig. 2 show the embodiment of the present invention when carrying out early warning, between involved parameters
Relation；
Fig. 3 shows embodiment of the present invention schematic diagram during vehicle yaw angle calculates；
Fig. 4 shows in fluoroscopy images, angle and the relation of range information；
Fig. 5 shows the three-dimensional Early-warning Model that the embodiment of the present invention provides.
Detailed description of the invention
Embodiment 1
Below with reference to accompanying drawing 1-5, the method for early warning provided in one embodiment of the invention is carried out in detail
Describe in detail bright.
Method for early warning in the present invention is implemented under fluoroscopy images, and relevant lane departure warning system
For the classical Early-warning Model of system is both for inverse fluoroscopy images.The new prediction policy of the present invention is
Propose on the basis of TLC Early-warning Model, the TLC Early-warning Model under inverse fluoroscopy images " is translated "
Become under fluoroscopy images based on left and right lane line angle and vehicle's center of gravity and track two kinds of information of center line distance
Method for early warning, concrete grammar will will be described in detail below.
As it is shown in figure 1, the difference against fluoroscopy images with fluoroscopy images is, lane line in inverse perspective view
Being parallel and distance (degree of depth) information can be extracted, and lane line is crossing in fluoroscopy images
And range information is unknowable, and the picture that monocular-camera photographs is all fluoroscopy images, i.e. left and right car
Diatom is certain angle, and vehicle is unknowable with the range information of surrounding objects, therefore, existing
Method for early warning is mainly all based on what inverse fluoroscopy images was carried out, the invention mainly includes and sets up two kinds
One " bridge " under picture state, by this seat " bridge ", the method for early warning in fluoroscopy images
The effect that in inverse fluoroscopy images, TLC prediction policy reaches can be reached.
Present invention is generally directed to deviation system, it is provided that a kind of based on classical TLC method for early warning
A kind of new method for early warning.Below, step the method is described in detail one by one.
Step 1, determine the TLC Early-warning Model of Lane Departure Warning System, take to deviate car at vehicle
Before road, 0.5s gives and driver's early warning, i.e.Wherein T is the time parameter that gives warning in advance,
y0Representing vehicle's center of gravity away from wanting the lateral separation cross track distance of run-off-road line, w is the width of vehicle
Degree, v is the speed of vehicle, and θ is the yaw angle of vehicle.
It is illustrated in figure 2 between the parameters involved by TLC method for early warning under inverse fluoroscopy images
Relation schematic diagram, the method for early warning under inverse fluoroscopy images relates generally to four factors, the width w of vehicle,
The speed v of vehicle, yaw angle θ of vehicle, vehicle's center of gravity are away from lane line distance y0。
For choosing the TLC method for early warning basis as the present invention of classics, main cause is that TLC is pre-
It is commonplace that alarm method uses in Lane Departure Warning System, and can be examined by the corner of steering wheel
Worry is entered, and improves the degree of accuracy of model, and can pre-set time T carry out early warning, reserved
In the response time of driver, pilot model is also contemplated in the middle of method for early warning.
For the TLC method for early warning chosen--In pre-warning time T, used herein
0.5s。
Early-warning Model will give the necessity reminded with driver's early warning not before run-off-road line at vehicle
Accommodating doubtful, driver so can be made to make operation in advance, it is to avoid vehicle deviates original traveling lane, make
Become vehicle accident.But the value that the occurrence of threshold value T does not the most determine, if threshold value is excessive, the most not
Being avoided that the generation of vehicle accident, threshold value is too small, then can frequently send early warning, be easily caused and drive
The person's of sailing driving fatigue, data statistic analysis obtains when threshold value T=0.5s, can well take into account both.
Road surface and the ratio of sky in the picture that step 2, setting video camera photograph, and it is real to carry out emulation
Testing modeling, carry out building of experiment scene by Prescan software, mainly on vehicle, carried experiment needs
The sensor wanted, arranges the speed of vehicle and travels yaw angle, travel route and the width of road,
By Prescan associating simulink plug-in unit, system early warning model algorithm is imported phantom afterwards；Should
Step specifically includes:
Step 201: set up the yaw angle of the driving path of vehicle, i.e. vehicle in Prescan software,
And set the width in track；
The reason of the modeling that selection carries out simulated environment in Prescan software is: in Prescan software
It is provided with the sensor-Lane Marker sensor needed for Lane Departure Warning System, and can be convenient
Build the scene required for system, include road, vehicle parameter, car speed, and the width in track
Degree is set as 3.75m, and the range set of the yaw angle that vehicle travels is θ=[-10 °, 10 °], and every 1
Degree once emulates, and different yaw angles can cause the difference in early warning moment；
Step 202: carry the lane detection sensor-Lane required for Lane Departure Warning System
Marker sensor and video camera, and regulate video camera and the position of sensor and angle so that camera
The aspect ratio that in the picture photographed, sky is pre-set with system with the ratio of road keeps one
Cause；
As it is shown on figure 3, be message processing module and message output module, i.e. Prescan in Prescan software
When processing vehicle with lane line position relationship, process under inverse fluoroscopy images, and can lead to
Cross and the mode of photographic head is installed on vehicle exports fluoroscopy images this moment.The advantage of Prescan software is just
It is (vehicle to be included against the position relationship of (image) process vehicle under perspective mode with lane line
Angle, range information with lane line) while, the car under perspective mode (image) can be exported
With the position relationship of lane line.
Vehicle is installed Lane Marker sensor and Camera photographic head, and two biographies of regulation
The angle of sensor and the length-width ratio of picture photographed, it is ensured that the visual field that two kinds of sensors photograph is identical.
Step 203: setting speed and the width of vehicle, speed and width information according to vehicle exist
Simulink writes prediction policy algorithm and according to Lane Marker sensor transmissions by S function
Information solves vehicle yaw angle this moment by writing S function；
During the associative simulation of Prescan Yu simulink, can be by the signal of sensor collection in Prescan
Speed, vehicle yaw angle as the input signal in prediction policy, such as vehicle.In order to by these
Signal is preferably combined with simulink module and simplifies simulink model, prediction policy module is led to
Cross S function to write, and for the substantial amounts of information of Lane transmission, carry out information processing by S function,
And finally calculate vehicle yaw angle this moment.It is concrete as it is shown on figure 3, pass through Lane Marker
Intersection point between sensor scan line and longitudinal perpendicular bisector and the lane line of vehicle, calculates vehicle this moment
Yaw angle.
Step 3, form by Prescan/simulink associative simulation, simulating vehicle is in same speed
The automotive run-off-road early warning moment in the case of different yaw angles, and record the picture in this early warning moment,
Lane line angle and car about the early warning moment is extracted afterwards by Vc6.0/Opencv lane line extraction procedure
The range information of distance of centre of gravity track center line, and note down；This step specifically includes:
Step 301: be set under same speed, when such as speed is 5m/s, the driftage of simulating vehicle
Angle range is θ ∈ [-10 °, 10 °], can meet the requirement at vehicle yaw angle in the range of this, and vehicle
Velocity interval is v ∈ [0,35m/s], meets the rate request of highway；
Owing to deviation system is mainly applied on a highway, and the speed limit of highway is
120km/h, the speed arranging vehicle in phantom is v ∈ [0,35m/s], it is possible to meet highway
Rate request, under same speed, it is ensured that before automotive run-off-road 0.5s give and driver's early warning
On the premise of prompting, different yaw angles can cause the position of vehicle early warning persistently to change, it is contemplated that
To the angle problem of yaw angle, in the range of yaw angle θ ∈ [-10 °, 10 °], substantially can meet vehicle to partially
The requirement at boat angle, and during regulation vehicle left avertence, yaw angle is negative, during right avertence, vehicle yaw angle is just；
Step 302: simulate same speed by Prescan/simulink, different yaw angle situation is got off
Early warning moment, when automotive run-off-road being detected in early warning program, by Pause function by program
Stopping, and record early warning moment photographic plate, the yaw angle of vehicle is simulated once every once；
The early warning moment of automotive run-off-road is simulated, due to software emulation process only in Prescan software
It is to show automotive run-off-road early warning by visual manner, is difficult to tell system accurately and starts early warning
The first frame picture.Can be by adding Pause function in prediction policy S function, when program judges
When going out automotive run-off-road line, termination program continues to run with, and records the fluoroscopy images in deviation moment,
And under this specific speed, the yaw angle scope of simulating vehicle is θ ∈ [-10 °, 10 °], every 1 degree
Simulation once, records 20 fluoroscopy images deviateing the moment under this speed altogether；
Step 303: by writing the saturating of the intact lane detection program early warning moment to remaining
Visible image processes, and the track, left and right in deviation moment when recording under same speed different yaw angle
Wire clamp angle and the vehicle's center of gravity distance (in units of pixel) between the center line of track.
In the case of same speed difference yaw angle, 20 run-off-road moment that simulation obtains
Fluoroscopy images, by the most compiled lane detection program, detects each run-off-road moment saturating
The left and right lane line angle theta of visible image and vehicle's center of gravity distance y between the longitudinal midline of track0, and right
The two information makes a record, and angle is with range information as shown in Figure 4；
Step 4, by Prescan software change vehicle travel speed, car speed in the range of
V ∈ [0,35m/s], emulates once every 5m/s, again records the left side in friction speed difference yaw angle moment
Right lane wire clamp angle and vehicle's center of gravity range information between the center line of track:
Step 401: the travel speed that vehicle is different is set, be respectively provided with the speed of vehicle be 5m/s,
10m/s, 15m/s, 20m/s, 25m/s, 30m/s, 35m/s, and at each speed Imitating
In the early warning moment in the case of emulation yaw angle θ ∈ [-10 °, 10 °], record early warning moment fluoroscopy images；
In factor influential for the early warning moment, speed and vehicle yaw angle be most important two because of
Element, same yaw angle, when speed is big, the early warning moment shifts to an earlier date, speed hour, and the early warning moment is delayed,
In order to meet the requirement at highway driving, the car speed of simulation is v ∈ [0,35m/s], every 5m/s
Simulate once, the seriality of basic guarantee rate curve, and yaw angle is every 1 degree of simulation once.
Step 402: according to deviateing track wire clamp about the moment under lane detection Program extraction friction speed
Range information between angle and vehicle's center of gravity and track center line.
The fluoroscopy images in the deviation moment for recording, by lane line extraction procedure, carries one by one
Take lane line angle theta and vehicle's center of gravity distance y between the longitudinal midline of track about the deviation moment0, altogether
Count 140 groups of data, record these data messages.
Step 5, distance according to left and right lane line angle and the vehicle's center of gravity in deviation moment with track center line
Information, by MATLAB edit routine, sets up three-dimensional Early-warning Model；In this step.
Step 501: calculating vehicle is the track in run-off-road early warning moment under friction speed difference yaw angle
Range information between wire clamp angle and vehicle and track center line.
140 groups of data messages are added up, and carries out differentiation, it is ensured that the corresponding vehicle that data are correct
Speed, the corresponding 20 groups of deviation moment lane line angles of each speed and range information.
Step 502: write in MATLAB based on speed, left and right lane line angle, vehicle away from car
The three-dimensional Early-warning Model drawing program of road three factors of center line distance, in order to preferably show 3-D graphic
Effect, it is stipulated that car speed is just to left avertence, is negative to right avertence, and lane line angle is negative to left avertence,
Just being to right avertence, vehicle's center of gravity is away from track longitudinal midline distance, and left avertence is just, right avertence is negative.Simulation
Result as it is shown in figure 5, and identical in view of the equidirectional symbol of speed, do not have positive and negative point, institute
With safety zone actual in Fig. 5 it is, after blue region is come with the face symmetry that speed is zero,
More than blueness, red following part, for safety zone, other regions are prewarning area.
For the display that Lane Departure Warning System Early-warning Model based on fluoroscopy images is become apparent from,
Using car speed, lane line angle, vehicle away from track longitudinal direction perpendicular bisector distance as the three of Early-warning Model
Individual coordinate figure, and by the way of writing m file in MATLAB, by directly perceived for three-dimensional Early-warning Model
Show.
Step 6, according to set up three-dimensional Early-warning Model, by load video simulation verify its Early-warning Model
Effectiveness.
Step 7, once establish three-dimensional Early-warning Model, it is possible to pavement image based on actual photographed,
Lane line angle in extraction image, and obtain the velocity information of vehicle, based on lane line angle and speed
Three-dimensional Early-warning Model described in degree Information Pull carries out vehicle deviation early warning.
In the method for the present invention, in simulation process, by passing through sensor on simulating vehicle simultaneously
Obtain the image under inverse perspective mode or the vehicle front image under result, and perspective mode, then
Early warning is carried out based on the measurement result under inverse perspective mode by TLC Early-warning Model, and when recording early warning
Carve the image under perspective mode, be then based on the image under the image zooming-out perspective mode under perspective mode
Parameter (the lane line angle in image and cross track distance), then that the result under fluoroscopy images is saturating with inverse
Result under visible image associates, it is possible to know, in the case of this speed and yaw angle,
Under perspective mode, how to trigger early warning, after various speed and yaw angle are all simulated,
Just can set up the three-dimensional Early-warning Model under fluoroscopy images, and then based on this three-dimensional Early-warning Model, permissible
Directly carry out early warning judgement by fluoroscopy images.Saving calculating resource, response speed is fast, and efficiency is high.
Although the principle of the present invention having been carried out detailed retouching above in conjunction with the preferred embodiments of the present invention
State, it should be appreciated by those skilled in the art that above-described embodiment is only the schematic realization to the present invention
The explanation of mode, not comprises the restriction of scope to the present invention.It is right that details in embodiment is not intended that
The restriction of the scope of the invention, without departing from the spirit and scope of the present invention, any based on this
The equivalent transformation of inventive technique scheme, simple replacement etc. obviously change, and all fall within the present invention and protect
Within the scope of protecting.
Claims (9)
1. a lane departure warning method based on fluoroscopy images, it is characterised in that include that step is such as
Under:
Step 1, the model parameter of setting TLC lane departure warning model；
Step 2, carrying out emulation experiment modeling, modeling process includes: carry on simulating vehicle for
Carry out the sensor of vehicle driving parameters measurement under inverse perspective mode, and under perspective mode, shoot car
The video camera of forward image, regulation sensor measure field and the visual field of video camera, make the two each other
Overlap, speed and traveling yaw angle, travel route and the width of road of vehicle is set；
Step 3, in simulated scenario, utilize sensor to obtain the driving parameters of vehicle under inverse perspective mode
Carry out early warning judgement being supplied to TLC lane departure warning model, simulate in each friction speed, each
In the case of individual different yaw angle, there is the situation of deviation in vehicle in travelling, and, utilize TLC track
Vehicle deviation is reported to the police by deviation Early-warning Model based on the parameter under inverse perspective mode, and records early warning
Sensor measures parameters under fluoroscopy images that moment shot by camera arrives and inverse perspective mode；
Left and right under early warning moment perspective mode in the case of step 4, acquisition friction speed, different yaw angle
Lane line angle and cross track distance information；
Step 5, according to left and right lane line angle and vehicle's center of gravity and the track under deviation moment perspective mode
The distance of center line and the velocity information of vehicle, set up three-dimensional Early-warning Model；
Step 6, according to set up three-dimensional Early-warning Model, by load video simulation verify its Early-warning Model
Effectiveness；
Step 7, perspective mode image based on actual photographed, extract the lane line in perspective mode image
Angle, and obtain the velocity information of vehicle, utilize described three-dimensional based on lane line angle and velocity information
Early-warning Model carries out vehicle deviation early warning.
Lane departure warning method based on fluoroscopy images the most according to claim 1, its feature
Being, described step 2 includes:
Step 201: set up the driving path of vehicle in Prescan software, sets the width in track；
Step 202: carry the lane detection sensor-Lane required for Lane Departure Warning System
Marker sensor and video camera, and regulate video camera and the position of sensor and angle so that camera
The aspect ratio that in the picture photographed, sky is pre-set with system with the ratio of road keeps one
Cause；
Step 203: setting speed and the width of vehicle, speed and width information according to vehicle solve car
Yaw angle this moment.
Lane departure warning method based on fluoroscopy images the most according to claim 1, its feature
Being, described step 3 includes:
Step 301: be set under same speed, the yaw angle scope of simulating vehicle；
Step 302: simulating the vehicle early warning moment in the case of same speed, different yaw angle, record is pre-
The fluoroscopy images in alert moment；
Step 303: the fluoroscopy images in the early warning moment remained is processed, and records same speed
The left and right lane line angle in early warning moment and the cross track distance in units of pixel when degree, different yaw angle.
Lane departure warning method based on fluoroscopy images the most according to claim 1, its feature
Being, described step 1 includes: 0.5s before automotive run-off-road is set as pre-warning time parameter T,Wherein, y0Representing vehicle's center of gravity away from wanting the lateral separation of run-off-road line, w is vehicle
Width, v is the absolute velocity of vehicle, and θ is the yaw angle of vehicle.
Lane departure warning method based on fluoroscopy images the most according to claim 1, its feature
Being, described step 203 includes: speed based on vehicle and width information utilize simulink plug-in unit
Solve the yaw angle of vehicle.
Lane departure warning method based on fluoroscopy images the most according to claim 1, it is special
Levying and be, described step 4 also includes by Vc6.0/Opencv lane line extraction procedure based on perspective mould
Picture under formula extracts lane line angle and the vehicle's center of gravity distance letter away from track center line about the early warning moment
Breath.
Lane departure warning method based on fluoroscopy images the most according to claim 1, its feature
Being, set yaw angle scope is θ ∈ [-10 °, 10 °], and the velocity interval of vehicle is
v∈[0,35m/s]。
Lane departure warning method based on fluoroscopy images the most according to claim 2, its feature
Being, described method also includes utilizing Prescan software to be simulated emulation, at the inverse perspective mould of image
Vehicle while calculating the position relationship of vehicle and lane line under formula, under the perspective mode of output image
Position relationship with lane line.
9. the method building lane departure warning model based on fluoroscopy images, it includes that step is such as
Under:
Step 1, the model parameter of setting TLC lane departure warning model；
Step 2, carrying out emulation experiment modeling, modeling process includes: carry on simulating vehicle for
Carry out the sensor of vehicle driving parameters measurement under inverse perspective mode, and under perspective mode, shoot car
The video camera of forward image, regulation sensor measure field and the visual field of video camera, make the two each other
Overlap, speed and traveling yaw angle, travel route and the width of road of vehicle is set；
Step 3, in simulated scenario, utilize sensor to obtain the driving parameters of vehicle under inverse perspective mode
Carry out early warning judgement being supplied to TLC lane departure warning model, simulate in each friction speed, each
In the case of individual different yaw angle, there is the situation of deviation in vehicle in travelling, and, utilize TLC track
Vehicle deviation is reported to the police by deviation Early-warning Model based on the parameter under inverse perspective mode, and records early warning
Sensor measures parameters under fluoroscopy images that moment shot by camera arrives and inverse perspective mode；
In the case of step 4, acquisition friction speed, different yaw angle, the early warning moment is against the left side under perspective mode
Right lane wire clamp angle and cross track distance information；
Step 5, according to left and right lane line angle and vehicle's center of gravity and the track under deviation moment perspective mode
The distance of center line and the velocity information of vehicle, set up three-dimensional Early-warning Model；
Step 6, according to set up three-dimensional Early-warning Model, by load video simulation verify its Early-warning Model
Effectiveness.
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