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Title: Lane deviation alarm system
Abstract: A lane deviation alarm system is comprised of a forward-observed-point calculating section that calculates a forward observed point by multiplying a vehicle speed of a host vehicle and an anticipated deviation time; a forward-observed-point lateral-displacement calculating section that calculates a lateral displacement at the forward-observed-point, on the basis of a yaw angle and the forward-observed-point; a lane deviation tendency determining section that determines whether the host vehicle is in a lane deviation tendency, on the basis of the forward-observed-point lateral-displacement; and a criteria changing section that changes a criteria for determining a lane deviation tendency of the host vehicle, on the basis of a detecting condition of the lane defining line.
Patent Number: 7,091,838 Issued on 08/15/2006 to Shimakage
| Inventors: |
Shimakage; Masayasu (Yokohama, JP) | | Assignee: |
Nissan Motor Co., Ltd.
(Yokohama,
JP)
|
| Appl. No.:
|
10/790,269 |
| Filed:
|
March 2, 2004 |
Foreign Application Priority Data
| | | | | |
Mar 11, 2003
[JP] | | |
2003-065424 | |
|
| Current U.S. Class: |
340/436 ; 340/435; 340/901; 340/904; 340/937; 340/938; 701/1 |
| Current International Class: |
B60Q 1/00 (20060101) |
| Field of Search: |
340/937,938,435,436,901,904 701/1
|
References Cited [Referenced By]
U.S. Patent Documents
Foreign Patent Documents
| | | | | | |
| 8-5388 | |
Jan., 1996 | |
JP | |
| 2002-193055 | |
Jul., 2002 | |
JP | |
|
Other References
Masato Abe, "Vehicle Dynamics and Control", (third edition) May 31, 1996, pp. 60-70. cited by other. |
Primary Examiner: Hofsass; Jeffery
Assistant Examiner: Labbees; Edny
Attorney, Agent or Firm: Foley & Lardner LLP
Claims
What is claimed is:
1. A lane deviation alarm system, comprising: a lane defining line detecting section that detects a lane defining line of a lane traveled by a host vehicle; and a criteria
changing section that changes a criteria for determining a lane deviation tendency of the host vehicle, on the basis of a detecting condition of the lane defining line.
2. The lane deviation alarm system as claimed in claim 1, further comprising: a yaw angle detecting section that detects a yaw angle of the host vehicle on the basis of the detected lane defining lines; a forward observed point calculating
section that calculates a forward observed point by multiplying a vehicle speed of the host vehicle and an anticipated deviation time; a forward observed point lateral displacement calculating section that calculates a lateral displacement at the
forward observed point, on the basis of the yaw angle and the forward observed point; a lane deviation tendency determining section that determines whether the host vehicle is in a lane deviation tendency, on the basis of the forward observed point
lateral displacement; and a lane deviation tendency informing section that informs a driver that the host vehicle is in the lane deviation tendency, on the basis of the determination result at the lane deviation tendency determining section, wherein the
criteria changing section changes an anticipated deviation time so as to decrease the influence of the yaw angle on the calculation of the forward observed point lateral displacement when the lane defining line detecting section detects only one of both
lane defining lines.
3. The lane deviation alarm system as claimed in claim 1, wherein the criteria changing section changes the criteria of the lane deviation tendency on the basis of the lane defining line, so that a decision of the lane deviation tendency is
suppressed as frequency of detecting no lane defining line increases.
4. The lane deviation alarm system as claimed in claim 1, wherein the criteria changing section increases a change quantity of an anticipated deviation time as frequency of detecting no lane defining line increases.
5. The lane deviation alarm system as claimed in claim 2, wherein the lane deviation tendency determining section determines the lane deviation tendency by comparing the forward observed point lateral displacement and each threshold of each
lane defining line, and further comprising a threshold changing means that changes the threshold when a state that the lane defining line detecting section detects one of both lane defining lines continues for a first predetermined time.
6. The lane deviation alarm system as claimed in claim 5, wherein the threshold changing section increases the change quantity of the threshold as the non detection frequency of the one lane defining line increases.
7. The lane deviation alarm system as claimed in claim 5, further comprising a lane defining line anticipating model which corrects a location of a lane defining line detected with a high detection frequency and a location of the other lane
defining line detected with a low detection frequency, using a detection result of the lane defining line detected with the high detection frequency, wherein the correction result of the lane defining line locations using the lane defining line
anticipation model affects the forward observed point lateral displacement to generate an error, wherein the threshold changing section determines the threshold taking account of the forward observed point lateral displacement including the error due to
the correction result.
8. The lane deviation alarm system as claimed in claim 1, wherein the lane defining line detecting section includes a camera system which takes an image indicative of the lane defining lines of a traveling lane and which changes a setting of an
image picking up condition according to the image picking up environment, and the criteria changing section changes the criteria when the setting of the image picking up condition is changed.
9. The lane deviation alarm system as claimed in claim 5, wherein the lane deviation tendency determining section stops the determination of the lane deviation tendency based on the undetected lane defining line when a state that the lane
defining line detecting section detects one of both lane defining lines continues for a second predetermined time.
10. The lane deviation alarm system as claimed in claim 1, wherein the criteria changing section decreases an anticipated deviation time as the non detection frequency of the lane defining line increases.
11. The lane deviation alarm system as claimed in claim 5, wherein the threshold changing section increases the threshold when a state that the lane defining line detecting section detects one of both lane defining lines continues for the first
predetermined time.
12. A lane deviation alarm system, comprising: a controller arranged to detect a lane defining line of a lane traveled by a host vehicle, to change a decision criteria for determining a lane deviation tendency of the host vehicle, on the basis
of a detecting condition of the lane defining line, and to generate an alarm when the lane deviation tendency is determined by comparing a relationship between the host vehicle and the lane defining line with the criteria.
13. A method of generating an alarm when a lane deviation tendency of a host vehicle is determined, the method comprising: detecting a lane defining line of a lane traveled by a host vehicle; and changing a criteria for determining a lane
deviation tendency of the host vehicle, on the basis of a detecting condition of the lane defining line.
14. A lane deviation alarm system, comprising: lane defining line detecting means for detecting a lane defining line of a lane traveled by a host vehicle; and criteria changing means for changing a criteria for determining a lane deviation
tendency of the host vehicle, on the basis of a detecting condition of the lane defining line.
15. The lane deviation alarm system as claimed in claim 1, further comprising a lane deviation tendency determining section that determines whether the host vehicle is in a lane deviation tendency.
16. The lane deviation alarm system as claimed in claim 1, wherein the criteria is an anticipated deviation time.
17. The lane deviation alarm system as claimed in claim 16, wherein the anticipated deviation time is changed on the basis of a frequency of detecting no lane defining line.
18. The lane deviation alarm system as claimed in claim 1, wherein the criteria is changed on the basis of a frequency of detecting no lane defining line.
Description
BACKGROUND OF THE INVENTION
The present invention relates to a lane deviation alarm system which generates an alarm indicative of a deviation of a vehicle from a traveling lane, on the basis of a picked-up image showing both lane defining lines of the traveling lane on a
road.
Japanese Published Patent Application No. 2002-193055 discloses a lane deviation alarm system which informs a driver that a host vehicle deviates from a traveling lane by generating an alarm. More specifically, this lane deviation alarm system
comprises an image picking-up section for picking up lane defining lines (white lines) of a traveling lane on a road, a yaw angle detecting section for obtaining a yaw angle of the host vehicle relative to the road, a road curvature estimating section
for estimating a forward road curvature on the basis of an image picked up by the image picking-up section, a traveling curvature estimating section for estimating a traveling curvature from a traveling condition of the host vehicle, a lane deviation
determining section for determining a lane deviation of the host vehicle on the basis of the information of a traveling road and the vehicle position, and an informing section for informing a lane deviation possibility to a driver when the host vehicle
deviates from the traveling lane.
SUMMARY OF THE INVENTION
In case that the lane deviation is anticipated using a picked-up image indicative of lane defining lines, when only one of lane defining lines is detected, an estimation error of a vehicle position increases and therefore erroneous alarms tend to
be generated. For example, when only one of lane defining lines is detected, a yaw angle of the host vehicle is erroneously estimated and largely fluctuates due to various factors such as a vehicle pitching. Consequently, an estimation error of the
vehicle position relative to the traveling lane largely increases so as to tend to generate erroneous alarms. Herein, a situation that one of lane defining lines is detected includes a location limit such that lane defining line exists at only one side,
such as at a splitting or merging lane on a highway, and a non-detection state of one lane defining line which is caused by Botts Dots or patchy looking of the lane-defining-line.
On the other hand, if the alarm is arranged to be temporally stopped in case that a non-detection state of one or both lane defining lines continues for a predetermined time, a rate of a system operation time decreases and therefore the validity
of the system degrades. Further, if a sensibility of generating alarm is lowered while setting an alarm generating threshold at a high value, the alarm generation time delays although the frequency of the erroneous alarms decreases.
It is therefore an object of the present invention to provide an improved lane deviation alarm system which is capable of decreasing the frequency of erroneous alarms even when only one of both lane defining lines is detected.
An aspect of the present invention resides a lane deviation alarm system which comprises a lane defining line detecting section that detects a lane defining line of a lane traveled by a host vehicle; and a criteria changing section that changes a
criteria for determining a lane deviation tendency of the host vehicle, on the basis of a detecting condition of the lane defining line.
Another aspect of the present invention resides in a method of generating an alarm when a lane deviation tendency of a host vehicle is determined, which method comprises an operation of detecting a lane defining line of a lane traveled by a host
vehicle; and an operation of changing a criteria for determining a lane deviation tendency of the host vehicle, on the basis of a detecting condition of the lane defining line.
The other objects and features of this invention will become understood from the following description with reference to the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 is a block diagram showing a structure of a lane deviation alarm system according to a first embodiment of the present invention.
FIG. 2A is a top view showing a camera system equipped on a vehicle, and FIG. 2B is a side view showing the camera system equipped on the vehicle.
FIG. 3 is a flowchart showing a processing executed by the camera system.
FIG. 4 is a view for explaining a model lane-defining lines.
FIG. 5 is a view explaining a method of setting an initial value of a line candidate point detection area.
FIG. 6 is a view explaining the method of setting the initial value of the line candidate point detection area in case that actual lane defining lines have been already detected.
FIG. 7 is a view explaining the method of setting line candidate point detection areas on a picked-up image.
FIG. 8 is a view explaining a detecting method of the line candidate point.
FIG. 9 is a view explaining an offset quantity between a previous candidate point and a present candidate point on a lane line model.
FIG. 10 is a flowchart showing a procedure of a traveling condition monitor processing executed by a controller of the lane deviation alarm system according to the first embodiment of the present invention.
FIG. 11 is a flowchart showing a procedure of a line non-detection frequency calculation processing executed by the controller.
FIG. 12 is a flowchart showing a procedure of an anticipated deviation time set processing executed by the controller.
FIG. 13 is a view explaining a forward-observed-point lateral-displacement estimated value y.sub.s.
FIGS. 14A and 14B are views explaining a reason of taking account of a vehicle-body sideslip angle .beta. when a lane-deviation tendency on a curve is determined.
FIG. 15 is a graph showing a relationship between a turn angular speed and a vehicle speed.
FIG. 16 is a graph showing a relationship between a sideslip angle at a center of gravity of the vehicle and the vehicle speed.
FIG. 17 is a flowchart showing a procedure of a lane deviation determination processing executed by the controller.
FIGS. 18A through 18H are timing charts explaining the operations of the lane deviation alarm system of the first embodiment according to the present invention.
FIG. 19 is a flowchart showing a procedure of a traveling condition monitor processing executed by the controller of the lane deviation alarm system according to a second embodiment of the present invention.
FIG. 20 is a flowchart showing a procedure of a deviation determination threshold correcting processing executed by the controller of the lane deviation alarm system according to the second embodiment of the present invention.
FIG. 21 is a flowchart showing a procedure of an anticipated deviation time set processing executed by the controller of the lane deviation alarm system according to the second embodiment of the present invention.
FIGS. 22A through 22H are timing charts explaining the operations of the lane deviation alarm system of the first embodiment according to the present invention.
DETAILED DESCRIPTION OF THE INVENTION
Referring to the drawings, there are discussed embodiments according to the present invention in detail.
Referring to FIGS. 1 to 18, there is shown a first embodiment of a lane deviation alarm system according to the present invention. As shown in FIG. 1, the lane deviation alarm system is installed in a host vehicle 10 and comprises a road
recognition camera system 1, a controller 2, a vehicle speed sensor 4, a steering angle sensor 5 and an alarm device 7.
Camera system 1 is installed in a passenger compartment of host vehicle 10. More specifically, camera system 1 is installed at an upper and laterally center position near a front window as shown in FIGS. 2A and 2B so that a yaw angle between an
optical axis of a lens of camera system 1 and a longitudinal center axis of vehicle 10 is 0 and a pitch angle therebetween is .alpha.. Camera system 1 takes an image of a road view within a range from several meters to several tens meters ahead of
vehicle 10. Further, camera system 1 detects a relative positional relationship between host vehicle 10 and the lane defining lines of a traveling lane. Camera system 1 comprises a CCD (Charge Coupled Device) image sensor as an image taking section.
More specifically, camera system 1 obtains data of the image taken by a CCD of camera system 1. Camera system 1 processes the image in order to detect lane defining lines of a traveling lane. Camera system 1 transforms a shape of the lane
defining lines into a mathematical model by using a plurality of parameters representative of a shape of the road shape and a vehicle behavior of vehicle 10. By updating the parameters so as to correspond the detection result of the lane defining lines
with model lane lines, camera system 1 detects and recognizes the road parameters representative of the road shape and the vehicle behavior. Camera system 1 outputs the obtained road parameter to controller 2. Herein, the road parameters includes a
lateral displacement y.sub.r at a center of gravity of vehicle 10 relative to the lane center line, yaw angle .phi..sub.r of vehicle 10 relative to the lane center line, pitch angle .eta. of vehicle 10, a height h of camera system 1 from a road surface,
a road curvature (an inverse of a radius of curvature) .rho., and a lane width W. The detailed explanation of the processing executed by camera system 1 will be discussed later.
Vehicle speed sensor 4 detects a vehicle speed of vehicle 10 by measuring a revolution speed of an output shaft of a transmission or a revolution speed of a wheel, and outputs a signal indicative of the detected vehicle speed to controller 2.
Steering angle sensor 5 is a sensor for detecting a steering condition manipulated by a driver. More specifically, steering angle sensor 5 amplifies a rotational displacement of a steering shaft (not shown) which is integrally rotated with a steering
wheel, directly or by means of a gear mechanism. Thereafter, steering angle sensor 5 detects the amplified rotational angle as a steering angle detection signal by means of an angle detecting mechanism such as a rotary encoder or potentiometer.
Controller 2 executes the various controls employed in the lane deviation alarm system according to the present invention. More specifically, controller 2 estimates a lane deviation tendency at the moment when a predetermined time elapsed from
the present time moment, on the basis of the vehicle speed detected by vehicle speed sensor 4, the present steering angle detected by steering angle sensor 5, and the road parameters supplied from camera system 1. Herein the predetermined time into
future is a time period necessary for moving vehicle 10 from a present vehicle position on the lane to a predetermined position. Controller 2 monitors a traveling condition of vehicle 10 while estimating the lane deviation tendency of vehicle 10
relative to the lane at a moment when the predetermined time elapsed from the present time.
When controller 2 determines that there is a high possibility that vehicle 10 deviates from the traveling lane, from an estimation result of the lane deviation tendency, controller 2 outputs a drive signal to an alarm device 7 to generate warning
sound or displaying warning information so as to give a warning to the driver.
The detailed explanation as to the monitoring processing of the thus traveling condition will be discussed later.
Alarm device 7 has a function of giving a stimulation to the senses of sight, hearing, touch or the like of a driver, such as a buzzer, audio system, steering actuator or meter display device. By outputting an alarm sound, vibrations to the
steering wheel, or an alarm display, controller 2 informs the driver that there increases the possibility of a lane deviation of vehicle 10 from the traveling lane. Thus, the lane deviation alarm system according to the present invention monitors a
traveling condition of vehicle 10 while estimating the lane deviation tendency of vehicle 10 relative to the lane at a moment when the predetermined time elapsed from the present time. When there is a high possibility that vehicle 10 deviates from the
traveling lane, the lane deviation alarm system warns the driver by applying the stimulations of giving a stimulation to the sense of sight, hearing, touch or the like of the driver, so as to effectively call the driver's attention.
Subsequently, the processing executed by camera system 1 is discussed. A flowchart of FIG. 3 shows a procedure of a lane defining line detect processing executed by camera system 1.
At step S1 camera system 1 initializes the road parameters representative of a road shape and a vehicle behavior. FIG. 4 shows an image taken by camera system 1 and an X-Y image-plane coordinate system. In this coordinate system, model lane
defining lines are represented by the following expressions (1) and (2) using the road parameters. x={a-0.5e}(y-d)+b/(y-d)+c (1) x={a+0.5e}(y-d)+b/(y-d)+c (2) where the expression (1) is an expression adapted to a right hand side as viewed from vehicle
10, the expression (2) is an expression adapted to a left hand side as viewed from vehicle 10, a, b, c, d and e are the road parameters. Assuming that a vertical dimension between camera system 1 and a road surface is constant, road parameter a denotes
a lateral displacement y.sub.cr of vehicle 10 between the lane defining lines, b denotes a road curvature .rho., c denotes yaw angle .phi..sub.r of vehicle 10 (the optical axis of camera system 1) relative to the road, d denotes pitch angle .eta. of
vehicle 10 (the optical axis of camera system 1) relative to the road, and e denotes dimension W between the lane defining lines.
Under the initial condition, the shape of the road and the lane defining lines and the vehicle behavior are set at values corresponding to center values, respectively, since the shapes of the road and the lane defining lines and the vehicle
behavior are not clear in this initial condition. More specifically, road parameter a corresponding to the lateral displacement y.sub.cr of vehicle 10 within the lane defining lines is set at a center between the lane defining lines, road parameter b
corresponding to road curvature .rho. is set at straight (zero), road parameter c corresponding to yaw angle .phi..sub.r relative to the lane defining lines is set at zero, road parameter d corresponding to pitch angle .eta. relative to the lane
defining lines is set at .alpha..degree. indicative of a vehicle stopping condition, and road parameter e corresponding to lane width W between the lane defining lines is set at a lane width of a highway defined by the rule of a road structure.
More specifically, road parameters a, b, c, d and e are defined as follows. In case that a desired point in an actual coordinate system fixed in the vehicle is projected on an image coordinate system (x, y) wherein X-axis is a lateral (right and
left) direction of vehicle 10, Y-axis is a vertical direction of vehicle 10, and Z-axis is a longitudinal (fore-and-aft) direction of vehicle 10, the corresponding image coordinate system (x, y) are expressed by the following expressions (3) x=-(f/Z)X,
y=-(f/Z)Y (3) where f is a lens parameter and is a coefficient corresponding to a focal length of a lens. Assuming that road curvature .rho. is not so large and a road surface is flat, the coordinate of the lane defining lines relative to a vehicle
center line (camera center line) along Z direction (forward direction) is expressed by the following expressions (4), (5) relating to the lateral direction and (6) relating to the vertical direction. Herein, the above assumption is for simplifying a
model, and by increasing the dimension of the model, these expressions are available even under a general condition. X=0.5.rho.Z.sup.2-.phi..sub.rZ-y.sub.cr-0.5W (4) X=0.5.rho.Z.sup.2-.phi..sub.rZ-y.sub.cr+0.5W (5) Y=.eta.Z-h (6) where the expression
(4) is an expression corresponding to the right hand side operation as viewed from vehicle 10, and the expression (5) is an expression corresponding to the left hand side operation as viewed from vehicle 10. By eliminating X, Y and Z from the
expressions (3) through (6), the following expressions (7) and (8) are obtained. x=(y.sub.cr+0.5W)(y+f.eta.)/h+f.phi..sub.r-0.5f.sup.2.rho.h/(y+f.eta.) (7) x=(y.sub.cr-0.5W)(y+f.eta.)/h+f.phi..sub.r-0.5f.sup.2.rho.h/(y+f.eta.- ) (8) where the expression
(7) is an expression corresponding to the right hand side operation as viewed from vehicle 10, and the expression (8) is an expression corresponding to the left hand side operation as viewed from vehicle 10.
By normalizing each road parameter using the expressions (7) and (8) on the assumption the road width W, whose deviation is the smallest in those of the road parameters, is constant, lateral displacement y.sub.cr of vehicle 10, road curvature
.rho., yaw angle .phi..sub.r, and the height h of camera system 1 are expressed by the following expressions (9). y.sub.cr=Wa/e, .rho.=2be(f.sup.2h), .phi..sub.r=c/f, h=We (9)
Road parameters a, b, c, d and e are set in this manner. Accordingly, the road parameters are initialized at step S1, as discussed above.
At step S2 camera system 1 initializes a side of small areas for detecting a candidate point of the lane defining line as shown in FIG. 5. As shown in FIG. 5, in this embodiment ten search areas including five right search areas and five left
search areas are searched, and the size of each search area is set large. Under the initial condition, since it is supposed that there is a large difference between the model lane defining lines obtained by inputting the initial values into the
respective road parameters a to e and the actual lane defining lines on the image plane, it is preferable that relatively large areas are set initially.
When the lane defining lines have been detected already in the previous processing, it is assumed that the difference between the actual lane defining lines and the mode lane defining lines is small. Therefore, as is apparent from the comparison
with FIG. 5, the size of each search area is set small as possible, as shown in FIG. 6. By setting the size of each search area small, a possibility of an erroneous detection of detecting other objects is decreased. Further, it becomes possible to
improve the processing speed of this processing.
At step S3 camera system 1 receives an image which was obtained by the image processing section of camera system 1.
At step S4 camera system 1 sets the search areas of the candidate lane defining lines on the road image produced by the image processing section through the processing at step S1. During this setting, the candidate lane-defining-line search
areas on the road image are set on the basis of the candidate lane-defining-line search arrears obtained at step S2 and one of the road parameters initially set at step S1 and the model lane-defining lines corrected by the road parameters as discussed at
step S9 discussed later.
More specifically, the candidate lane-defining-line search areas are set on the road image so that the model lane-defining-lines are located at centers of the respective search areas as shown in FIG. 7. As shown in FIG. 7, the number of the
lane-defining-line search areas is 10 constituted by 5 search areas for the right lane defining line and 5 search areas for the left lane defining line. It will be understood that the lane-defining-line search areas may be set at positions offset from
the model lane defining lines according to the change of the past model lane defining lines.,
At step S5 camera system 1 detects the candidate point of the lane defining line in each lane-defining-line search area.
In this detecting operation, first a differential image is produced by filtering the input image with a Sobel filter. Then camera system 1 counts suitable pixels which are located on the line segment and whose densities are greater than a value
capable of extracting the detection line, relative to each line segment generated by connecting a point on an upper base line and a point on a lower base line of each search area, as shown in FIG. 8. Further the points on the upper and lower base lines
are varied, and as to a predetermined number of the line segments the counting of the suitable pixels are executed. The line segment, which includes the largest number of the suitable pixels in the whole line segments, is determined as a detection
straight line. The start and end of the detection straight line are determined as the lane-defining-line candidate points. When the number of the suitable pixels of the determined detection straight line is smaller than a predetermined rate to the
number of pixels corresponding to the length of the search area, camera system 1 determines that there is no candidate lane-defining-line point in this search area.
For example, under a condition that the number of pixels corresponding to the length of the search are is 15 and the predetermined rate is 1/2, if the number of the suitable pixels of the detection straight line segment are eight or more, camera
system 1 determines that the start and the end of the selected line segment is treated as the candidate lane-defining-line points. If the number of the suitable pixels of the detection straight line are seven or less, camera system 1 determines that
there is no candidate lane-defining-line point.
The above operation of determining the candidate lane-defining-line points is executed by each candidate lane-defining-line search area. For example, in case that the number of the lane-defining-line search areas is set at 10 constituted by 5
search areas for the right lane defining line and 5 search areas for the left lane defining line, the above operation is executed by each of 10 lane-defining-line search areas.
In determining the candidate lane-defining-line points, the predetermined rate may be set at a constant rate throughout all search areas or may be varied by each search area. Further the predetermined value of the density may be set at a
constant value throughout all search areas or may be varied by each search area.
At step S6 camera system 1 checks whether the number of the candidate lane-defining-line points of the whole candidate lane-defining-line search area is greater than or equal to a predetermined value agreeable to deciding as a lane defining line. When the number of the candidate lane-defining-line points is smaller than the predetermined value, camera system 1 determines that there is no lane defining line in the search areas, and the routine of this flowchart returns to step S2 to again
initialize the size of the search area. When the number of the candidate lane-marker points is greater than or equal to the predetermined value, the routine proceeds to step S7.
At step S7 camera system 1 calculates an offset quantity between the determined candidate lane-defining-line point and a point on the model lane defining line obtained by the previous processing by each candidate lane-defining-line point.
At step S8 camera system 1 calculates fluctuation quantities .DELTA.a, .DELTA.b, .DELTA.c, .DELTA.d and .DELTA.e of the road parameters a through e. The calculation of the fluctuation quantities .DELTA.a through .DELTA.e may be executed on the
basis of a least-square method, for example, disclosed in Japanese Published Patent Application No. 8-5388.
At step S9 camera system 1 corrects road parameters a to e on the basis of fluctuation quantities .DELTA.a to .DELTA.e calculated at step S8. When the model lane defining line expressed by the equation (1) is employed, the correction of the
fluctuation quantities is executed using the following expressions (10). a=a+.DELTA.a, b=b+.DELTA.b, c=c+.DELTA.c, d=d+.DELTA.d, e=e+.DELTA.e (10)
The corrected road parameters a through e are stored in a predetermined memory area of camera system 1 as a road parameters of a new model lane-defining-line. Further, the corrected road parameters a through e are converted into actual physical
quantities using the expressions (9) and stored the obtained physical quantities in the memory area of camera system 1. Subsequent to the execution of step S9, the routine returns to step S3 to repeat the above mentioned routine.
Camera system 1 executes the above-discussed processing and outputs road parameters a through e of the model lane defining lines to controller 2. Controller 2 executes a traveling condition monitor processing for generating alarm according to
the traveling condition of vehicle 10, on the basis of road parameters a through e.
There is briefly explained the calculation for obtaining the above-discussed road parameters a through e, although the detailed explanation is made in Japanese Published Patent Application No. 8-5388.
First it is assumed that a road structure on the road image smoothly varies with respect to a time-axis. FIG. 9 shows a change of a line defining line between a previous moment and a present moment. For example, camera system 1 takes (picks up)
a road surface image at predetermined intervals such as an interval ranging from 50 to 100 msec., and extracts a part of a lane defining line (white line) from the road image. Further controller 2 obtains x and y coordinates of the part of the lane
defining line (white line) and estimates the road parameters in real time. The estimation of the road parameter is executed by a method of comparing a previous line position obtained from a road image of a previous frame and a present line position of a
present frame.
Assuming that fluctuation quantities of the previously obtained road parameters a through e are .DELTA.a through .DELTA.e, a small fluctuation of the j-th point x.sub.ij of the i-th lane-defining-line on the road image (x, y) is expressed by the
following expression (11) based on Taylor's theorem and by neglecting second-order and more-order terms. .DELTA.x.sub.ij=A'.sub.ij.DELTA.a+B'.sub.ij.DELTA.b+C'.sub.ij.DELTA.c+D'.- sub.ij.DELTA.d+E'.sub.ij.DELTA.e (11) where
A'.sub.ij=.differential.x.sub.ij/.differential.a, B'.sub.ij=.differential.x.sub.ij/.differential.b, C'.sub.ij=.differential.x.sub.ij/.differential.c, D'.sub.ij=.differential..sub.ij/.differential.d, E'.sub.ij=.differential.x.sub.ij/.differential.e, and
where a subscript i takes 0 or 1, and a subscript j is an integer for distinguishing the detected lane-defining-line candidate points. When i=0 denotes a right lane defining line and i=1 denotes a left lane defining line, x coordinates of
lane-defining-line candidate points are represented by the expressions (1) and (2), and therefore the expressions (1) and (2) are commonly expressed by the following expressions (11) and (12). x.sub.0j={a-0.5e}(y.sub.0j-d)+b/(y.sub.0j-d)+c (12)
x.sub.1j={a+0.5e}(y.sub.1j-d)+b/(y.sub.1j-d)+c (13) where subscript i may not limited to two values (0 and 1), and may take an integer ranging from 0 to 3 when the system can detect a lane defining line of the adjacent lane, so that the setting can be
changed according to the detected lane defining line.
The estimation of fluctuation quantities .DELTA.a through .DELTA.e is executed using a method of least squares. First at the j-th point of the i-th lane defining line on the road image (x, y), an error between the previous line position obtained
from a road image of a previous frame and a present line position of a present frame is represented by the following expressions (14). When a line candidate point is detected, K.sub.ij=x.sub.newij-x.sub.oldij When a line candidate point is not detected,
K.sub.ij=0 (14) where a subscript new of x means that a value of x.sub.ij is a present value, and a subscript old of x means that a value of x.sub.ij is a previous value of the previous frame before the present frame.
The following expression (15) is defined as an error performance function. J.sub.total=J.sub.model+J.sub.smooth (15) where J.sub.model and J.sub.smooth are represented by the following expressions (16) and (17).
.times..times..DELTA..times..times..times..times..times..times..DELTA..tim- es..times..times..times. ##EQU00001## J.sub.smooth=S.sub..DELTA.a.DELTA.a.sup.2+S.sub..DELTA.b.DELTA.b.sup.2+S.-
sub..DELTA.c.DELTA.c.sup.2+S.sub..DELTA.d.DELTA.d.sup.2+S.sub.66 e.DELTA.e.sup.2 (17)
where an integer n is set as an upper limit of the number of lane-defining-line candidate points for one lane defining line.
The expression (16) is an error performance function defined by a difference between a previously detected result x.sub.ij-1 and a newly detected result x.sub.ij, and P.sub.ij in the expression (16) represents a degree of certainty of the
lane-defining-line candidate point. The expression (17) is an error performance function which represents an assumption that the parameters smoothly vary along the time-axis, and S denotes a weight coefficient.
All elements of the error performance function J.sub.total represented by the expression (15) have the minimum values, respectively, and are represented by monotonously increasing function as the error increases. Therefore, by obtaining extremes
of the function J.sub.total, fluctuation quantities .DELTA.a through .DELTA.e are obtained. That is, the fluctuation quantities .DELTA.a through .DELTA.e are obtained by solving the following equation (18).
.differential..differential..DELTA..times..times..times..differential..dif- ferential..DELTA..times..times..times..differential..differential..DELTA..- times..times..times..differential..differential..DELTA..times..times..time-
s..differential..differential..DELTA..times..times. ##EQU00002##
All of partial differentials of the error performance function in the equation (18) is expressed by the following expressions (19a) through (19e).
.differential..differential..DELTA..times..times..times..differential..dif- ferential..DELTA..times..times..differential..differential..DELTA..times..- times..times..times..times..times..DELTA..times..times..times..times..time-
s..differential..DELTA..times..times..times..differential..DELTA..times..t- imes..times..times..times..times..DELTA..times..times..times..times..times- ..differential..DELTA..times..times..times..differential..DELTA..times..ti-
mes..times..DELTA..times..times..times..DELTA..times..times..times..times.- .times..times..times.'.times..DELTA..times..times..times..times..times..ti- mes..times..times.'.times..DELTA..times..times..times..times..times..DELTA-
..times..times..times..DELTA..times..times..times..differential..different- ial..DELTA..times..times..times..times..times..times..times.'.times..DELTA- ..times..times..times..times..times..times..times..times.'.times..DELTA..t-
imes..times..times..times..times..DELTA..times..times..times..DELTA..times- ..times..times..differential..differential..DELTA..times..times..times..ti- mes..times..times..times.'.times..DELTA..times..times..times..times..times-
..times..times..times.'.times..DELTA..times..times..times..times..times..D- ELTA..times..times..times..DELTA..times..times..times..differential..diffe- rential..DELTA..times..times..times..times..times..times..times.'.times..D-
ELTA..times..times..times..times..times..times..times..times.'.times..DELT- A..times..times..times..times..times..times..DELTA..times..times..times..D- ELTA..times..times..times..differential..differential..DELTA..times..times-
..times..times..times..times..times.'.times..DELTA..times..times..times..t- imes..times..times..times..times.'.times..DELTA..times..times..times..time- s..times..times..DELTA..times..times..times..DELTA..times..times..times. ##EQU00003##
By simultaneously solving the expressions (19a) through (19e) and by expressing the determinant of the equation (18) in the form of a formula, the following expression (20) is obtained. {S.sub.W+S.sub.S}[.DELTA.a .DELTA.b .DELTA.c .DELTA.d
.DELTA.e].sup.T-S.sub.k=0 (20) where S.sub.W, S.sub.K and S.sub.S are column vectors and are respectively expressed by the following expressions (21), (22) and (23).
.times..times..function..times.'.times.'.times.'.times.'.times.'.times..ti- mes.'.times.'.times.'.times.'.times.'.times..times..function..times.'.time- s.'.times.'.times.'.times.'.times..times.'.times.'.times.'.times.'.times.'-
.times..times..function..times.'.times.'.times.'.times.'.times.'.times..ti- mes.'.times..times..function..times.'.times.'.times.'.times.'.times.'.time- s..times.'.DELTA..times..times..DELTA..times..times..DELTA..times..times..-
DELTA..times..times..DELTA..times..times. ##EQU00004##
The fluctuation quantities .DELTA.a through .DELTA.e, which satisfy the expression (20), is obtained using the following expression (24) only when the sum of the expressions (21) and (22) has an inverse matrix.
[.DELTA.a.DELTA.b.DELTA.c.DELTA.d.DELTA.e].sup.T=(S.sub.W+S.sub.S).sup.-1- S.sub.k (24)
Thus, the road parameters a through e are updated by correcting road parameters e through e using fluctuation quantities .DELTA.a through .DELTA.e obtained by the above-discussed manner. Although the embodiment has been explained such that the
road parameters a through e are corrected using the method of least squares, a parameter estimating means adaptable to a non-linear system, such as an extended Kalman filter.
Subsequently, there is explained a traveling condition monitor processing executed by controller 2. FIG. 10 shows a procedure of the traveling monitor processing.
At step S21 controller 2 reads road parameters y.sub.cy, .rho. and .phi..sub.r of the model lane defining line, which have been stored as new road parameters of the model lane defining line. Further controller 2 read a right line non-detection
flag flag_r and a left line non-detection flag flag_l. Right line non-detection flag flag_r is a flag indicative that camera system 1 detects a right lane defining line. When the right lane defining line is detected, right line non-detection flag flag_r
is set at 1 (flag_r=1). When the right lane defining line is not detected, right line non-detection flag flag_r is set at 0 (flag_r=0). Similarly, when the left lane defining line is detected, left line undetected flag flag_l is set at 1 (flag_l=1).
When the left lane defining line is not detected, left line non-detection flag flag_l is set at 0 (flag_l=0).
At step S22 controller 2 reads vehicle traveling condition data. Herein, the vehicle traveling condition data comprises a vehicle speed V detected by vehicle speed sensor 4, a present steering angle .theta. of the steering wheel, which is
detected by steering angle sensor 5.
At step S30 controller 2 executes a calculation processing of the lane-defining-line non-detection frequencies. FIG. 11 shows a procedure of the lane-defining-line non-detection frequency calculation processing.
At step S31 in FIG. 11, controller 2 sets a frequency calculation time T.sub.f (sec.) employed in the lane-defining-line non-detection frequency calculation.
At step S32 controller 2 calculates a right line non-detection frequency Frh. More specifically, controller 2 reads right line non-detection flag flag_r obtained during a period from a present moment to the past frequency calculation time
T.sub.f.
The right line non-detection frequency Frh during the period from a present moment to the past frequency calculation time T.sub.f is calculated using right line non-detection flag flag_r, by means of a moving average processing during the
predetermined time period (the period from a present moment to the past frequency calculation time T.sub.f). Right line non-detection frequency Frh is a frequency of not capable of detecting the right lane defining line during the period from the
present moment to the past frequency calculation time T.sub.f. Herein, when a calculation sampling time is .DELTA.T, right line non-detection frequency Frh(t) is obtained by the following expression (25) representative of the moving average processing.
.function..DELTA..times..times..times..DELTA..times..times..times..times..- times..times..DELTA..times..times. ##EQU00005##
At step S33 controller 2 calculates a left line non-detection frequency Flh. More specifically, controller 2 reads left line non-detection flag flag_l obtained during a period from a present moment to the past frequency calculation time T.sub.f.
The left line non-detection frequency Flh during the period from a present moment to the past frequency calculation time T.sub.f is calculated using left line non-detection flag flag_l, by means of the moving average processing during the
predetermined time period (the period from a present moment to the past frequency calculation time T.sub.f). Left line non-detection frequency Flh is a frequency of not capable of detecting the left lane defining line during the period from the present
moment to the past frequency calculation time T.sub.f. Herein, when a calculation sampling time is .DELTA.T, left line non-detection frequency Flh(t) is obtained by the following expression (26) representative of the moving average processing.
.function..DELTA..times..times..times..DELTA..times..times..times..times..- times..times..DELTA..times..times. ##EQU00006##
The processing from steps S31 through S33 is executed at step S30, and the main routine in FIG. 10 then proceeds to step S40.
At step S40 controller 2 executes a set processing of a anticipated deviation time Tttlc of traveling vehicle 10. Anticipated deviation time Tttlc is a time period from a present moment to an anticipated deviation moment on the basis of a
present vehicle traveling condition (lateral displacement and yaw angle of vehicle 10 relative to a traveling lane). Herein, a lane deviation is defined as a condition that a front wheel of vehicle 10 crosses with a lane defining line of the traveling
lane so that vehicle 10 deviates from a traveling lane.
Anticipated deviation time Tttlc is set as a parameter for defining an alarm timing. By using anticipated deviation time Tttlc as an alarm timing, alarm is generated when the lane deviation is generated after anticipated deviation time Tttlc
elapsed. Therefore, it becomes possible to timely generate the alarm as to the lane deviation.
For example, when it is possible to complete a proper lane-deviation avoidance operation within 1.0 second after a driver is aware of the alarm, anticipated deviation time Tttlc is set at 1.0 second. With this arrangement, it becomes possible
for the driver to properly complete the lane-deviation avoidance by executing the lane-deviation avoidance operation after being aware of the alarm. There is explained a setting of anticipated deviation time Tttlc with reference to FIG. 12.
At step S41 controller 2 determines whether or not right line non-detection frequency Frh(t) obtained at step S32 is greater than left line non-detection frequency Flh(t) obtained at step S33. When the determination at step S41 is affirmative
(Frh(t)>Flh(t)), the program proceeds to step S42. When the determination at step S41 is negative (Frh(t).ltoreq.Flh(t)), the program proceeds to step S43.
At step S42 controller 2 calculates anticipated deviation time Tttlc using the following expressions (27). When Frh(t)<Flo, Tttlc=Tttlc1. When Flo.ltoreq.Frh(t)<Fhi, Tttlc=Tttlc1((Fhi-Frh(t))/(Fhi-Flo)). When Fhi.ltoreq.Frh(t), Tttlc=0
(27) where Tttlc1 is a fixed value which is greater than 0, Flo is a minimum frequency, and Fhi is a maximum frequency. As is apparent from the expressions (27), when right line non-detection frequency Frh(t) is smaller than minimum frequency Flo,
anticipated deviation time Tttlc is set a fixed value Tttlc1. When right line non-detection frequency Frh(t) is greater than or equal to minimum frequency Flo and is smaller than maximum frequency Fhi, anticipated deviation time Tttlc is set according
to right line non-detection frequency Frh(t). When right line non-detection frequency Frh(t) is greater than maximum frequency Flo, anticipated deviation time Tttlc is set at 0.
At step S43 controller 2 calculates anticipated deviation time Tttlc using the following expressions (28). When Flh(t)<Flo, Tttlc=Tttlc1. When Flo.ltoreq.Flh(t)<Fhi, Tttlc=Tttlc1((Fhi-Flh(t))/(Fhi-Flo)). When Fhi.ltoreq.Flh(t), Tttlc=0
(28) where Tttlc1 is a fixed value which is greater than 0, Flo is a minimum frequency, and Fhi is a maximum frequency, as discussed above.
As is apparent from the expressions (28), when left line non-detection frequency Flh(t) is smaller than minimum frequency Flo, anticipated deviation time Tttlc is set a fixed value Tttlc1. When left line non-detection frequency Flh(t) is greater
than or equal to minimum frequency Flo and is smaller than maximum frequency Fhi, anticipated deviation time Tttlc is set according to left line non-detection frequency Flh(t). When right line non-detection frequency Frh(t) is greater than maximum
frequency Flo, anticipated deviation time Tttlc is set at 0.
As discussed above, controller 2 determines the presence or absence of lane-defining-lines, on the basis of the lane-defining-line candidate points defining a boundary of the picked-up image. And the detection result of the presence or absence
of the line defining lines are right line non-detection frequency Frh(t) and left line non-detection frequency Flh(t). At step S40 controller 2 sets anticipated deviation time Tttlc on the basis of right line non-detection frequency Frh(t) and left line
non-detection frequency Flh(t). Therefore, anticipated deviation time Tttlc is set on the basis of the lane-defining-line candidate points in the picked-up image.
The routine in FIG. 10 proceeds to step S23 after anticipated deviation time Tttlc is set on the basis of right and left line non-detection frequencies Frh(t) and Flh(t) through the execution of the anticipated deviation time processing at step
S40. Herein, although anticipated deviation time Tttlc is represented by a first-order function of right line non-detection frequency Frh(t) or left line non-detection frequency Flh(t) using the expressions (27) or (28), the invention is not limited to
this arrangement. Anticipated deviation time Tttlc may not be represented by the first-order function of right line non-detection frequency Frh(t) or left line non-detection frequency Flh(t), and may be arranged to monotonously decrease as right line
non-detection frequency Frh(t) or left line non-detection frequency Flh(t) increases.
At step S23 controller 2 calculates forward-observed-point distance L.sub.s from the following expression (29) using anticipated deviation time Tttlc set at step S40. L.sub.S=V.times.Tttlc (29)
At step S24 controller 2 calculates forward-observed-point lateral displacement estimated value y.sub.s at a position of forward-observed-point distance Ls from the following expression (30).
Y.sub.s=y.sub.cr+L.sub.s.phi..sub.r=y.sub.cr+(V.times.Tttlc).phi..sub.r (30) where forward-observed-point lateral displacement estimated value y.sub.s means a lateral displacement of vehicle 10 from a center of traveling lane at a position of
forward-observed-point distance L.sub.s. Since forward-observed-point distance L.sub.s obtained at step S23 is a product of vehicle speed and anticipated deviation time Tttlc, forward-observed-point lateral-displacement estimated value y.sub.s
represents a lateral distance (anticipated distance) which vehicle 10 travels during a period from a present moment to a moment when anticipated deviation time Tttlc elapsed. For example, when the traveling road is generally straight, the magnitude of
forward-observed-point lateral-displacement estimated value y.sub.s directly represents a lane deviation tendency of vehicle 10. However, when the traveling road is a curve, this concept cannot be adapted directly. Accordingly, when the traveling road
is a curve, controller 2 determines the lane deviation tendency from the following concept. That is, controller 2 determines the lane deviation tendency on a curved road by correcting a vehicle body sideslip angle .beta.(offset between the direction of
the vehicle body and the traveling direction of vehicle 10).
FIGS. 14A and 14B show views for explaining a reason for taking account of vehicle body sideslip angle .beta.. Both of FIGS. 14A and 14B show a situation that vehicle travels a curved road while finely traces a center of a traveling lane.
Vehicle 10 shown in FIG. 14B travels at a vehicle speed higher than that of vehicle 10 shown in FIG. 14A. Although the vehicle speed of vehicle shown in FIG. 14A is different from that of vehicle shown in FIG. 14B, both vehicles are put in a constant
turn condition so as to finely trace a center of the traveling lane. This means that both vehicles are put in an ideal traveling state in the meaning of avoiding a lane-deviation. Therefore, in view of the lane deviation tendency, both traveling
conditions of vehicles shown in FIGS. 14A and 14B should be evaluated to be equivalent. For example, a vehicle having a general under-steer characteristic generates and increases vehicle body sideslip angle at a turn inner side as the vehicle speed
increases.
That is, as shown in FIG. 15, when a vehicle having a neutral steer characteristic turns at a constant steering angle, a turn angular speed linearly increases as the vehicle speed increases. When a vehicle having an under-steer characteristic
(US characteristic in FIG. 15) turns at a constant steering angle, the turn angular speed increases to a predetermined speed as the vehicle speed increases. That is, the turn angular speed does not become greater than the predetermined speed. However,
an absolute value of sideslip angle .beta. at a center of gravity of vehicle 10 increases in proportion to a square of the vehicle speed as shown in FIG. 16. Thus, sideslip angle .beta. at a center of gravity of vehicle 10 varies according to the
vehicle speed regardless of the steer characteristic of vehicle, and the reason thereof is that the vehicle has to obtain a lateral force balanced with a centrifugal force according to the vehicle speed.
Sideslip angle .beta. at a center of gravity of vehicle 10 is an angle between a fore-and-aft direction of vehicle and a traveling direction of a center of gravity of vehicle. More specifically, sideslip angle .beta. corresponds to an angle of
a tangential direction of a turn circle and represents an attitude of vehicle 10 with respect to a turn circle in a steady circular turn. A fact that this sideslip angle takes a negative value and increases its absolute value as vehicle speed increases
represents that the vehicle increases a tendency of executing a circle turn while directing a vehicle head toward an inner side of the turn circle as the vehicle speed increases. A detailed explanation of the above discussed vehicle behaviors is
disclosed in "VEHICLE DYNAMICS AND CONTROL (third edition)", Masato Abe, published on May 31, 1996, pages 60 70.
When there is a difference between the vehicle speeds of the vehicles shown in FIGS. 14A and 14B such that the vehicle speed of the vehicle shown in FIG. 14A is 50 60 km/h and the vehicle speed of the vehicle shown in FIG. 14B is 100 km/h, the
meaning of forward-observed-point lateral-displacement estimated value y.sub.s becomes different therebetween. Therefore, at step S25 controller 2 estimates vehicle body sideslip angle .beta. from a vehicle model identification value, vehicle speed V,
actual steering angle .delta. and road curvature .rho., using the following expression (31).
.beta..delta..function..function..gamma. ##EQU00007## where
.times..times..times..times..times..times..times..times..times..times..tim- es..times..times..times. ##EQU00008## and .gamma.=V.sub.p. Further, I is a vehicle-body yaw inertia moment, m is a vehicle weight, l.sub.f is a distance between a
center of gravity and a front wheel, l.sub.r is a distance between the center of gravity and a rear wheel, C.sub.f is a front-wheel cornering power for 2 wheels, C.sub.r is a rear-wheel cornering power for 2 wheels, V is the vehicle speed, .gamma. is a
yaw rate, .delta. is a front-wheel actual steering angle, .beta. is the sideslip angle and .rho. is the road curvature.
At step S26 controller 2 corrects forward-observed-point lateral-displacement estimated value y.sub.s using vehicle body sideslip angle .beta.. More specifically, controller 2 sets a product of forward-observed-point distance L.sub.s and vehicle
body sideslip angle .delta. (L.sub.s.times..beta.) as a correction value of forward-observed-point lateral-displacement estimated value, and sets forward-observed-point lateral-displacement estimated value (lane deviation evaluation point) y'.sub.s of
the correction value from the following expression (32) using the correction value (L.sub.s.times..beta.). y'.sub.s=y.sub.s+L.sub.s.beta. (32)
The expression (32) expresses that corrected forward-observed-point lateral-displacement estimated value y'.sub.s is varied from pre-correction forward-observed-point lateral-displacement estimated value y.sub.s by a correction quantity
(L.sub.s.times..beta.).
At step S50 controller 2 determines whether or not host vehicle 10 is in a condition of the lane deviation tendency, by comparing the corrected forward-observed-point lateral-displacement estimated value y'.sub.s with predetermined thresholds
Yth_r and Yth_l.
FIG. 17 shows a procedure of a lane deviation determination processing.
At step S51 controller 2 determines whether or not host vehicle 10 is in a lane deviation tendency toward a right adjacent lane, by comparing the corrected forward-observed-point lateral-displacement estimated value y'.sub.s with predetermined
threshold Yth_r. Right deviation determination threshold Yth_r is, for example, set at a predetermined fixed value Yth1. More specifically, controller 2 determines whether corrected forward-observed-point lateral-displacement estimated value y'.sub.s is
smaller than right deviation determination threshold Yth_r. Herein, right deviation determination threshold Yth_r is a value which has been previously obtained as a result of experiments. For example, right deviation determination threshold Yth_r is a
fixed value. When the determination at step S51 is affirmative, that is, when corrected forward-observed-point lateral-displacement estimated value y'.sub.s is smaller than right deviation determination threshold Yth_r (y'.sub.s<Yth_r), controller 2
determines that the vehicle is in the lane deviation tendency toward the right adjacent lane, and the program proceeds to step S52. When the determination at step S51 is negative, that is, when corrected forward-observed-point lateral-displacement
estimated value y'.sub.s is greater than or equal to right deviation determination threshold Yth_r (y'.sub.s.gtoreq.Yth_r), controller 2 determines that the vehicle is not in the lane deviation tendency toward the right adjacent lane, and the program
proceeds to step S53.
At step S52 controller 2 generates a right deviation alarm command, and the program of FIG. 17 is then terminated. At step S53 controller 2 stops the right deviation alarm command, and the program then proceeds to step S54.
At step S54 controller 2 determines whether or not host vehicle 10 is in a lane deviation tendency toward a left adjacent lane, by comparing the corrected forward-observed-point lateral-displacement estimated value y'.sub.s with predetermined
threshold Yth_l. Left deviation determination threshold Yth_l is, for example, set at a predetermined fixed value Yth1. More specifically, controller 2 determines whether corrected forward-observed-point lateral-displacement estimated value y'.sub.s is
smaller than left deviation determination threshold Yth_l. Herein, left deviation determination threshold Yth_l is a value whic
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