JP2019038289A - Vehicle driving support device - Google Patents

Abstract

To provide a vehicle driving support device that can detect inconsistencies of lane information acquired by a camera unit and a navigation system respectively to cancel lane-keeping control at appropriate timing.SOLUTION: The vehicle driving support device calculates an estimated yaw angle deviation from a difference between road curvature RCAM and RMPU acquired by a camera unit and a navigation system respectively, determines an estimated lateral position deviation ±Xdiff of an own vehicle on the basis of the estimated yaw angle deviation, and adds the estimated lateral position deviation ±Xdiff to a lateral position shift width X of the own vehicle from a center in a lane, calculated based on camera lane information, to calculate a lateral position allowable width Xestimation (S8); calculates lateral deviation-determination thresholds XLsl and XRsl for determining lane deviation on the basis of a lane width of a travel lane, the lateral position shift width X and a vehicle width of the own vehicle (S9 and S10); and compares the lateral position allowable width Xestimation with the lateral deviation-determination thresholds XLsl and XRsl (S11 and S12), to determine a possibility of the lane deviation.SELECTED DRAWING: Figure 3

Description

  The present invention relates to a driving support apparatus for a vehicle that cancels lane keeping control when detecting inconsistencies in position information when performing lane keeping control based on position information detected by a plurality of sensing devices.

  In order to reduce the driver's driving load while traveling, various vehicles are equipped with various driving support devices in recent vehicles, and as a representative one, lane keeping (Lane) that causes the vehicle to travel along the driving lane Keep Assist) control is known.

  In such a driving support device, in order to cause the host vehicle to correctly travel along the traveling lane, the road shape is acquired from image data obtained by capturing an image by an on-vehicle camera, map information provided in the navigation device, etc. It is necessary to constantly monitor whether the road shape is consistent by collating the data with the map information. For example, in Patent Document 1 (Japanese Patent Laid-Open No. 2017-61265), first lane information (such as road curvature) is acquired based on image information captured by an on-vehicle camera, and second map information of the navigation device is acquired. If lane information (road curvature etc.) is acquired and the two lane information are compared and it is determined that they are substantially consistent, current lane information is set based on the first lane information, and both lane information There is disclosed a technique of setting the present lane information based on the previously set lane information and the second lane information when the two are not consistent.

JP, 2017-61265, A

  In the technique disclosed in the above-mentioned document, when the first and second lane information do not match, the current lane information is set based on the previous lane information and the second lane information. .

  However, the position information of the own vehicle obtained from the navigation device is set based on the image data from the on-vehicle camera in order to obtain the corresponding map information by specifying the own vehicle position by the gyro sensor in tunnel traveling, for example The first lane information is likely to be more accurate. In addition, if the error of the GPS (GNSS) data is large, the wrong second lane information may be output. Furthermore, the same is true when the map information of the navigation device is old.

  Therefore, if the first lane information and the second lane information do not match, it is difficult to determine which lane information is correct. In this case, the current lane information is set based on the second lane information. In this case, incorrect lane information may be output. In addition, when the first lane information and the second lane information do not match, it is conceivable to cancel the lane keeping control immediately, but the lane keeping control is likely to be canceled frequently in automatic driving, causing inconvenience. There is a disadvantage.

  In view of the above circumstances, the present invention appropriately separates lane information due to the misalignment without canceling driving support control immediately, even if the lane information acquired by a plurality of sensing devices is not consistent. An object of the present invention is to provide a driving assistance apparatus for a vehicle that can obtain high convenience by detecting and continuing driving assistance until reaching a predetermined deviation state.

  In the present invention, vehicle speed detection means for detecting the vehicle speed of the host vehicle, a plurality of sensing devices for acquiring lane information of a traveling lane in which the host vehicle is traveling, and consistency of the lane information acquired by each sensing device And the consistency determination means calculates the lateral displacement width from the center of the lane of the traveling lane of the vehicle based on the lane information acquired by one of the sensing devices. And a road curvature computing means for obtaining a road curvature for each of the sensing devices based on the lane information acquired by each of the sensing devices, and for each of the sensing devices determined by the road curvature computing means In the driving support apparatus for a vehicle, which determines the consistency of the road curvatures based on the difference between the road curvatures of An estimated yaw angle deviation calculating means for calculating an estimated yaw angle deviation from an angle generated by a difference between the road curvatures of the sensing devices determined by the road curvature calculating means; and the estimated yaw angle deviation calculating means The estimated lateral position deviation calculating means for determining the estimated lateral position deviation of the vehicle based on the estimated yaw angle deviation, and the estimated lateral position deviation calculating means for the lateral position deviation width calculated by the lateral position calculating means A lateral position allowable range computing means for calculating an allowable lateral position range by adding an estimated lateral position deviation as an error, a lane width of the traveling lane, the lateral position offset width, and the vehicle's own vehicle obtained by one sensing device Left and right departure determination threshold calculation means for calculating the left departure determination threshold value and the right departure determination threshold value for determining the lane departure of the host vehicle based on the vehicle width and the lateral position allowable width calculation means The allowable lateral position width is compared with the left departure determination threshold and the right departure determination threshold calculated by the left / right departure determination threshold calculation means, and the allowable lateral position width exceeds one absolute value of the respective departure determination thresholds. And a lane departure prediction determination unit that determines that there is a possibility of lane departure.

  According to the present invention, an estimated yaw angle deviation is calculated from an angle generated by a difference between road curvatures acquired by a plurality of sensing devices, and an estimated lateral position deviation of the vehicle is determined based on the estimated yaw angle deviation. An estimated lateral position deviation is added as an error to the lateral position deviation from the lane center of the host vehicle's lane calculated based on the lane information acquired by the sensing device to calculate the lateral position allowance, and one sensing device The left departure determination threshold and the right departure determination threshold are determined to determine the lane departure of the host vehicle based on the lane width of the driving lane, the lateral position offset width, and the vehicle width of the host vehicle. As the determination threshold is compared with the right departure determination threshold and it is determined that there is a possibility of lane departure if the lateral position allowable width exceeds one absolute value of each departure determination threshold, a plurality of sensing is performed. Even if each lane information acquired by vice do not match immediately without canceling the driving support control, it is possible to appropriately detect the deviation of each lane information due to the mismatch. As a result, even when each lane information deviates, driving assistance can be continued until the predetermined deviation state is reached, and high convenience can be obtained.

Overall schematic diagram of the driving support device A flowchart showing an image / map consistency determination routine (part 1) A flowchart showing an image / map consistency determination routine (part 2) An explanatory view showing the vehicle lateral position and the road curvature obtained respectively from the on-vehicle camera and the map information A chart representing the time (decision time) until the estimated lateral position deviation calculated based on the difference in road curvature obtained from the onboard camera and the map information based on the vehicle speed and the road curvature difference

  Hereinafter, an embodiment of the present invention will be described based on the drawings. In FIG. 1, the driving assistance apparatus 1 mounted on the host vehicle M includes a steering control unit 11 as a steering control unit that performs steering control during automatic driving. The steering control unit 11 is mainly configured by a known microcomputer including a CPU, a ROM, and a RAM, and the ROM stores a control program for automatic operation executed by the CPU, fixed data, and the like.

  In addition, as a means for acquiring parameters required for steering control on the input side of the steering control unit 11, the navigation system 14 is used as a vehicle speed detection means for detecting the vehicle speed V of the host vehicle M (vehicle speed). The vehicle speed sensor 15, the camera unit 16, and the automatic driving switch 17 for turning on / off the automatic driving are connected. In the present embodiment, the navigation system 14 and the camera unit 16 correspond to the sensing device of the present invention.

  The camera unit 16 has a stereo camera consisting of a main camera 16a and a sub camera 16b, and an image processing unit (IPU) 16c, and travel environment information ahead of the host vehicle M captured by both cameras 16a and 16b is IPU 16c. The image processing is performed in a predetermined manner and transmitted to the steering control unit 11.

  The navigation system 14 has a receiver that receives position signals from positioning satellites such as Global Navigation Satellite System (GNSS) including GPS (Global Positioning System). Further, a high precision road map database 14 a is connected to the navigation system 14. The high precision road map database 14a is provided in a large capacity storage means such as an HDD, and high precision road map information (dynamic map) is stored. In addition, in the road map information, node information indicating nodes (intersections, connection points, etc.) and link information indicating links (road sections) connecting the nodes are registered. As the node information and the link information, Lanes (lane width, number of lanes), stop lines, pedestrian crossings, road shape (road curvature etc.), longitudinal slope (cant angle), elevation value, sag information, etc. Various information required when performing automatic driving It is memorized.

  The navigation system 14 acquires position information (coordinates such as latitude, longitude, etc.) of the host vehicle M based on the position signal from the positioning satellite received by the receiver, and raises the guidance route to the destination set by the driver. While making it display on the road map information stored in the precision road map database 14a, the current position of the own vehicle M is superimposed on the coordinate of the acquired vehicle position.

  Further, on the output side of the steering control unit 11, an informing unit 18 and an EPS drive unit 19 for driving an electric power steering (EPS) are connected. The notification unit 18 blinks the start and stop of automatic driving and the like to the driver by means of blinking display, character display, voice, etc.

  The steering control unit 11 sets a target travel route on which the host vehicle M travels on the road map, and a steering angle for determining a target steering angle for the host vehicle M to travel along the target travel route. Lane information (map lane information) acquired based on the image from the camera unit 16 of lane information (map lane information) set based on the current position of the host vehicle M specified on the calculation unit 11b and the road map An image / map consistency determination unit 11c as a consistency determination unit determines whether the information is aligned with the camera lane information).

  The target traveled road setting unit 11 a acquires map lane information based on the current position information of the host vehicle M (host vehicle position information) obtained by the navigation system 14. The map lane information is lane width data on the road on which the vehicle is traveling, road curvature R MPU at the center of the lane, or the like read from the road map information stored in the high precision road map database 14a. The target travel path setting unit 11a performs map matching on the road map with the current position of the host vehicle M, and sets the travel path (target travel path) where the host vehicle M should travel in lane maintenance control or the like at the center of the lane.

  The steering angle calculation unit 11b obtains the difference between the lateral positions based on the target traveling path set at the center of the lane and the vehicle position information, obtains a target steering angle such that this difference becomes 0, and determines this target steering angle. The corresponding drive torque is output to the EPS drive unit 19. The EPS drive unit 19 drives the EPS motor with the drive torque determined by the steering control unit 11 to steer the EPS, and performs steering angle control so that the host vehicle M travels along the target traveling path.

  A positioning error is included in the vehicle position information (coordinates such as latitude and longitude) obtained based on the position signal from the positioning satellite, and the positioning accuracy by the navigation system 14 may be further reduced. Therefore, it is necessary to constantly monitor whether the actual vehicle position and the position matched with the map on the road map coincide with each other. Based on the camera lane information acquired from the camera unit 16, the image / map consistency determination unit 11 c described above determines whether the road information acquired by the navigation system 14 is appropriate.

  The camera lane information acquired from the camera unit 16 includes the road curvature RCAM at the center (center of the lane) of the left and right division lines Ll and Lr dividing the left and right sections of the vehicle traveling path, and the lateral position of the host vehicle M based on the center of the lane. There is a shift width (vehicle's lateral position) X or the like. The road curvature RCAM at the center of the lane is, for example, the left and right division lines Ll. Lr is recognized, the curvatures of the left and right division lines Ll and Lr are respectively determined, and the road curvature RCAM of the lane center LCAM is calculated based on the curvatures (see FIG. 4).

  The image / map consistency determination unit 11c compares the road curvature RCAM determined based on the image from the camera unit 16 with the road curvature RMPU of the lane center LMPU on the road map set by the target traveling road setting unit 11a. It is determined whether or not it is consistent. In this case, also in the case of an image from the camera unit 16, the road curvature RCAM of the lane center LCAM may not be accurately determined due to the influence of bad weather, snow road, false detection due to blurring of the left and right section lines Ll, Lr, or the like.

  Therefore, when the road curvatures RCAM and RMPU do not match, the image / map consistency determination unit 11c determines that the reliability is low, and neither data is adopted, but the lane keeping control by automatic driving is canceled. Specifically, the determination of the consistency performed by the image / map consistency determination unit 11c described above is performed according to the image / map consistency determination routine shown in FIGS.

  In this routine, first, the traveling environment information in front of the host vehicle M acquired from the camera unit 16 is read in step S1. Then, in step S2, the left and right demarcation lines Ll and Lr (see FIG. 4) of the vehicle traveling path are detected based on the traveling environment information, and the lane width Xwidth between the left and right demarcation lines Ll and Lr is calculated.

  Next, the process proceeds to step S3, and the curvatures of the left and right division lines Ll and Lr are obtained, and the road curvature RCAM [1 / m] of the lane center LCAM set as the target travel path is obtained based on the both curvatures and the lane width Xwidth See Figure 4). The method of determining the road curvature RCAM is described in detail in JP-A-2017-61265 previously filed by the present applicant, and thus the description thereof is omitted here.

  Thereafter, when the process proceeds to step S4, the vehicle lateral position (lateral positional deviation width) X [m] based on the lane center LCAM is determined based on the traveling environment information acquired from the camera unit 16 (see FIG. 4). The processing in this step corresponds to the lateral position calculation means of the present invention.

In the present embodiment, the left division line L1 side is represented as a positive value (+) and the right division line Lr side is represented as a negative value (−) with reference to the lane center LCAM. Therefore, the distance between the left and right dividing lines Ll, Lr and the vehicle lateral position X is
(Xwidth / 2) -X
The right side is
(-Xwidth / 2) -X
It becomes. By the way, although the lane center LMPU of the current traveling lane can be obtained from the road map information, and the own vehicle lateral position can be obtained based on the own vehicle position information, the nearest position accuracy of the own vehicle M is higher than the road map information. Since the information acquired from the camera unit 16 is higher, the vehicle lateral position X is set based on the information acquired from the camera unit 16 in the present embodiment. Of course, the accuracy of the information acquired by the camera unit 16 may also decrease due to the traveling environment, weather conditions, dirt on the windshield, and the like. Therefore, the vehicle lateral position may be acquired from the navigation system 14.

  Next, in step S5, the vehicle position on the road map is specified based on the vehicle position information from the navigation system 14, and the road curvature RMPU stored in the lane center LMPU closest to the specified vehicle position is stored. Get [1 / m] information. The above-described processes in steps S3 and S5 correspond to the road curvature computing means of the present invention.

  Then, in step S6, the estimated yaw angle deviation Yawdiff [Yawdiff [based on the following equation from the angle generated by the difference (curvature difference) of both road curvatures RCAM, RMPU, ie, the deviation of the direction of the vehicle M by both road curvatures RCAM, RMPU. rad] (see FIG. 4).

Yawdiff ∫ ・ V · Ts · (RCAM-RMPU) dt (1)
Here, V is the own vehicle speed [m / s] detected by the vehicle speed sensor 15, and Ts is a sampling cycle (calculation cycle). The process in step S6 corresponds to the estimated yaw angle deviation computing means of the present invention.

Thereafter, the process proceeds to step S7, and based on the estimated yaw angle deviation Yawdiff, the estimated lateral position deviation ± Xdiff [m], that is, the error of the lateral position of the vehicle M caused by the difference between both road curvatures RCAM and RMPU,
± X diff ∫ V · Ts · sin (Yawdiff) dt (2)
Calculated from The estimated lateral position deviation ± Xdiff indicates the maximum error of the vehicle lateral position X. As a reference, FIG. 5 illustrates a determination time [sec] in which the estimated lateral deviation ± Xdiff [m] is 0.5 [m] based on the host vehicle speed V and the curvature difference (RCAM-RMPU). The process in step S7 corresponds to the estimated lateral position deviation computing means of the present invention.

  Next, the process proceeds to step S8, and the lateral position allowable width Xestimation is calculated by adding the vehicle lateral position X and the estimated lateral position deviation ± Xdiff multiplied by the predetermined weighting gain κ [%] (Xestimation X X + (± Xdiff κ)). The processing in this step corresponds to the lateral position allowable width computing means of the present invention.

  The above-mentioned weighting gain 設定 is a gain for setting which of the road curvatures RCAM and RMPU by the camera unit 16 is higher in reliability, and in the range of 100 to 0% with κ = 50% as a central value. It is set arbitrarily. That is, when the reliability of the road map information is high, == 100 to 50 [%] is set according to the reliability, while when the reliability of the camera unit 16 is high, the reliability is set to Accordingly, 、 is set in the range of 50 to 0 [%]. As a result, if the reliability of the road map information is high, the width of the estimated lateral position deviation ± Xdiff widens, and if the reliability of the camera unit 16 is high, the width of the estimated lateral position deviation ± Xdiff narrows.

  Incidentally, if the road map information and the reliability of the camera unit 16 are comparable, 程度 is set to 50%. The reliability (weighting gain κ) may be set as a fixed value at the time of shipment, but may be varied at the time of traveling depending on the traveling environment and weather conditions. When changing it according to the driving environment and weather conditions, for example, in an environment where the visual recognition by the camera unit 16 is difficult (bad weather, poor visibility), the reliability of road map information is increased. Increase the confidence of unit 16 Furthermore, priority is given to the camera unit 16 in city driving. At this time, the degree of reliability to be set (weighted) may be determined by the sum of individual evaluation values (points) set according to the traveling environment and weather conditions.

Next, the process proceeds to step S9, and a departure determination threshold (left departure determination threshold) XLsl for determining a lane departure on the left side surface of the host vehicle M,
XLsl ← (Xwidth / 2) -X + (-XWcar / 2) (3)
Calculated from Here, XWcar is the width of the host vehicle M.

Thereafter, the process proceeds to step S10, and a departure determination threshold (right departure determination threshold) XRsl for determining a lane departure on the right side surface of the host vehicle M,
XRsl ← (−Xwidth / 2) −X + (XWcar / 2) (4)
Calculated from The processes in steps S9 and S10 correspond to the left / right deviation determination threshold calculation means of the present invention.

  Then, in steps S11 and S12, each deviation determination threshold value XLsl and XRsl is compared with the lateral position allowable width Xestimation to perform deviation prediction determination. When X estimation> XLsl or X estimation <XRsl, it is determined that the left departure determination threshold XLsl or the right departure determination threshold XRsl exceeds the range of the estimated lateral position deviation ± Xdiff of the vehicle lateral position X. In this case, | Xestimation |> | XRsl | is obtained by expressing the right departure determination threshold XRsl and the lateral position allowable width Xestimation as absolute values.

  This means that the road curvature RCAM by the camera unit 16 and the road curvature RMPU from the road map information largely deviate and do not match, and at least one of the road curvatures RCAM and RMPU is wrong. If the lane keeping control is continued, it is determined that there is a possibility that the vehicle M deviates from the left division line Ll or the right division line Lr, and the process proceeds to step S13.

For example, the vehicle lateral position X is 0.3 [m], the estimated lateral position deviation ± X diff ± 0.6, the weighting gain 50 50 [%], the lane width X width 3.5 [m], the vehicle width X W car The horizontal position allowable width Xestimation is given by
Xestimation = 0.3 + (± 0.6 × 0.5) = 0.6,0 (5)
It becomes. Also, the left departure determination threshold XLsl is
XLsl = 3.5 / 2−0.3−2 / 2 = 0.45 (6)
And the right departure determination threshold XRsl is
XRsl = -3.5 / 2-0.3 + 2/2 = -1 .05 (7)
It becomes.

The lateral tolerance Xestimation has a maximum error on the left side,
Xestimation = 0.3 + 0.6 × 0.5 = 0.6 (8)
The maximum error on the right is
Xestimation = 0.3-0.6 × 0.5 = 0 (9)
Therefore, from the equations (6) and (8), the vehicle M on the left side is
0.6> 0.45
Next to the right side, from Eqs. (7) and (9),
0> -1.05
It becomes. As a result, when the deviation of the road curvatures RMPU and RCAM is large and the error is included, it is determined that the host vehicle M may deviate from the left lane line Ll.

  On the other hand, in the case of Xestimation X XLsl and Xestimation 自 XRsl, the vehicle M maintained the lane within the traveling lane even if it deviated from the lane center LCAM detected by the camera unit 16 by the vehicle lateral position X It is determined that the vehicle is traveling in a state, and the routine is exited. The processes in steps S11 and S12 correspond to the lane departure prediction determination means of the present invention.

  When it is determined that there is a possibility that the vehicle M deviates from either of the left and right dividing lines Ll and Lr, and the process proceeds from step S11 or step S12 to step S13, the image / map consistency determination unit 11c A departure warning alert command is output to the notification unit 18, and the display lamp, monitor, speaker, etc. are driven to notify the driver that the host vehicle M may deviate from the lane, and thus the automatic driving is interrupted. Do. The processing in step S13 corresponds to the deviation warning means of the present invention.

  Then, the process proceeds to step S14, and after a time (for example, 5 [sec]) set to cause the driver to take over the driving, the lane keeping control by the automatic driving is canceled and the routine is ended. When the driver tries to restart the lane keeping control by automatic driving, the automatic driving switch 17 is turned on again. Also, the processing in step S14 corresponds to the control cancellation means of the present invention.

  As described above, according to the present embodiment, the estimated lateral position deviation ± Xdiff, which is an error of the vehicle lateral position X, is obtained from the difference between the road curvature RCAM by the camera unit 16 and the road curvature RMPU from the road map information Until the lateral deviation judgment threshold XLsl, XRsl of the host vehicle M deviates from the lateral position allowable range Xestimation which is the range of the maximum error obtained by adding the estimated lateral position deviation ± Xdiff to the vehicle lateral position X, the lane keeping control by automatic driving When it is continued and the left / right deviation judgment threshold value XLsl, XRsl deviates from the lateral position allowable width Xestimation, it is judged that there is a possibility of the lane deviation, and the lane keeping control is canceled. Even when the information and the map lane information from the road map information do not match, it is appropriate to cancel the lane maintenance control due to the deviation of the road information due to the mismatch. It is possible to determine to.

  As a result, even when camera lane information and map lane information deviate, lane maintenance control can be continued until a predetermined deviation state is reached, and high convenience can be obtained.

  The present invention is not limited to the above-described embodiment. For example, the sensing device may add three or more types of navigation devices and other sensing devices capable of recognizing the left and right dividing lines to the camera unit 16. The degree of deviation of each lane information may be detected by a sensing device of

1 ... driving support device,
11: Steering control unit,
11a ... target traveling route setting unit,
11b ... steering angle calculation unit,
11c: Image / map consistency determination unit,
14: Navigation system,
14a ... high precision road map database,
15 Vehicle speed sensor 16 Camera unit
16a ... main camera,
16b ... sub camera,
17 ... Automatic operation switch,
18 ... notification unit,
19 ... EPS drive unit,
LCAM ... middle lane,
Ll ... left lane line,
LMPU ... middle of lane,
Lr ... right parcel line,
M ... own vehicle,
RCAM, RMPU ... Road curvature,
Ts: sampling period,
V ... own vehicle speed,
X ... own vehicle position,
XWcar ... car width,
Xestimation ... horizontal position tolerance width,
XLsl ... left departure judgment threshold,
XRsl ... right departure judgment threshold,
Xwidth ... lane width,
Yawdiff ... estimated yaw angle deviation,
κ ... weighted gain

Claims (3)

Vehicle speed detection means for detecting the speed of the host vehicle;
A plurality of sensing devices for acquiring lane information of a traveling lane in which the host vehicle is traveling;
Integrity determination means for determining the integrity of the lane information acquired by each of the sensing devices;
The consistency determination means
A lateral position calculation unit that calculates a lateral positional deviation width from the center of the lane of the traveling lane of the vehicle based on the lane information acquired by one of the sensing devices;
Road curvature computing means for obtaining a road curvature for each of the sensing devices based on the lane information acquired by each of the sensing devices, and the difference between the road curvatures of each of the sensing devices determined by the road curvature computing means In the driving support device for a vehicle, the consistency of each of the road curvatures is determined based on
The consistency determination means further includes:
Estimated yaw angle deviation calculating means for calculating an estimated yaw angle deviation from an angle generated by a difference between the road curvatures of the sensing devices determined by the road curvature calculating means;
Estimated lateral position deviation calculating means for determining an estimated lateral position deviation of the vehicle based on the estimated yaw angle deviation obtained by the estimated yaw angle deviation calculating means;
Lateral position allowable width computing means for computing an allowable lateral position width by adding the estimated lateral position deviation obtained by the estimated lateral position deviation calculating means as an error to the lateral position deviation width calculated by the lateral position calculating means;
A left departure determination threshold and a right departure determination threshold for determining the lane departure of the own vehicle based on the lane width of the traveling lane, the lateral positional deviation width, and the vehicle width of the own vehicle determined by one sensing device Left and right deviation determination threshold calculation means to calculate;
The lateral position permissible width is calculated by comparing the lateral position permissible width calculated by the lateral position permissible width calculating means with the left departure determination threshold and the right departure determination threshold calculated by the left / right departure determination threshold calculating means And a lane departure prediction determination unit that determines that there is a possibility of a lane departure when one absolute value of the determination threshold is exceeded. Has alarm means to notify the driver of the alarm,
The consistency judging means may further comprise departure warning means for outputting a departure notice warning command to the warning means when the lane departure prediction determining means determines that there is a possibility of lane departure. The driving assistance device for a vehicle according to claim 1.   3. The apparatus according to claim 2, wherein said consistency determination means further comprises control cancellation means for canceling driving support after a predetermined time has elapsed after said departure warning means outputs a departure notice warning instruction to said warning means. Driving assistance device for vehicles.

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