JPH07319541A - Traveling course estimating device for automobile - Google Patents

Abstract

PURPOSE:To accurately estimate a traveling course by comparing estimated traveling coureses and finally selecting any traveling course by majority. CONSTITUTION:Signals from first and second traveling course estimating means 6B and 6C are inputted to a traveling area setting means 28 together with a reliability arithmetic means 27. This reliability arithmetic means 27 is constituted to calculate the reliability of traveling courses (advancing courses) estimated by the traveling course estimating means 6B and 6C. On the other hand, the area setting means 28 finally estimates a traveling area (corresponding to an obstacle judged area) estimated to travel its own automobile later from the advancing courses and traveling courses (left and right white line parts) based on the reliability. When the difference mutually between the reliability values of traveling courses exceeds a threshold value, the traveling courses estimated by the respective traveling course estimating means are compared by a traveling area estimating means and the traveling course is finally selected by majority.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle traveling path estimating device having a plurality of traveling path estimating means.

[0002]

2. Description of the Related Art Conventionally, information obtained by scanning a wide range of a radar device is provided with a traveling road estimating means for estimating a traveling road on which the own vehicle is predicted to travel from the traveling state such as the steering angle of the own vehicle and the vehicle speed. Among them, there is known one that picks up only the one in the region along the traveling road predicted by the traveling road estimating means and judges the possibility that the own vehicle and the obstacle come into contact with each other.

As a traveling road estimating means for estimating such a traveling road, one for estimating the traveling road based on vehicle body state quantities such as a steering angle, a vehicle speed and a corrate (for example, JP-B-51-789).
Japanese Patent Laid-Open No. 2-120910, which estimates a traveling path by image processing using an image processing device.
(See Japanese Patent Publication).

In the case of image processing, usually,
Since the white line parts drawn at the left and right ends of the road are detected and the road edge is recognized, the range of the road that can be estimated is wide and it is more advantageous in estimating the road than by the vehicle state quantity. is there.

[0005]

However, when such an image processing is used, the condition of the white line part on the road may be remarkably bad, or there may be no white line originally. In addition, since the white line parts are on the left and right, there are situations where the estimation results for the left and right white line parts do not necessarily match, due to errors at each estimation stage, actual road shape, vehicle behavior, and the like.

Further, as described above, as a backup in the case where the state of the white line on the road is extremely bad or when there is no white line portion originally, as a backup, the running road estimation means based on image processing is used to estimate another running road with a different estimation method. It is conceivable to use a means (for example, a traveling road estimation means based on the vehicle state quantity) in combination, but even when a traveling road is estimated by using a plurality of traveling road estimation means having different estimation methods, each estimation result is still obtained. There are situations where the two do not match.

The present invention has been made in view of the above points, and in the case of having a plurality of traveling road estimating means, it is possible to accurately estimate a traveling road even if the estimated values by the respective estimating means are different. The present invention is intended to provide a vehicle travel path estimation device.

[0008]

The invention according to claim 1 is
A reliability calculation for calculating the reliability of the traveling road estimated by each traveling road estimating means on the premise of a traveling road estimating device for a vehicle including a plurality of traveling road estimating means for estimating a future traveling road of the own vehicle. Means and the output of the reliability calculation means,
When the difference between the road reliability values exceeds the threshold value,
The traveling paths estimated by the traveling path estimating means are compared with each other, the traveling path is finally selected by majority decision, and the traveling area estimating means for estimating the traveling area is provided.

In the invention according to claim 2, the traveling road estimating means is a first traveling road estimating means for estimating a first traveling road, which is expected to travel the vehicle in the future, as a traveling road based on the vehicle state quantity. , The white line candidate points that are supposed to form the white line portion on the road surface are detected based on the image processing, the white line portion is estimated based on the white line candidate points, and the traveling road where the own vehicle is expected to travel in the future is estimated. A second traveling path estimating means.

In the invention according to claim 3, further,
Distance calculation means for calculating an obstacle judgment distance based on the own vehicle speed, relative speed, road friction coefficient, etc., and, in the area exceeding the obstacle judgment distance upon receipt of the output of the distance calculation means, travel by the traveling area estimation means When estimating the area, an area correction unit is provided that prioritizes the estimation by the first traveling road estimation unit.

In the invention according to claim 4, further,
The distance calculating means for calculating the detectable distance of the white line candidate point by the second traveling path estimating means, and the area which exceeds the detectable distance of the white line candidate point upon receiving the output of the distance calculating means, travels by the traveling area estimating means. Area estimation means for prioritizing the estimation by the first traveling path estimation means when estimating the area.

In the invention according to claim 5, the traveling area estimating means weights the estimated traveling path with a coefficient of a detection rate and a coefficient of a detection time to finally determine the traveling path, and the traveling area is determined. Is estimated.

According to a sixth aspect of the present invention, an environment detecting means for detecting the environment in front of the vehicle is provided, and the traveling area estimating means receives the output of the environment detecting means and selects the traveling path in consideration of the environment. However, the travel area is estimated.

According to the seventh aspect of the invention, an obstacle detecting means for detecting an obstacle in front of the vehicle is provided, and the traveling area estimating means receives the output of the obstacle detecting means and determines the size and movement of the obstacle. Based on this, it is determined which of the estimation by the first traveling road estimating means and the estimation by the second traveling road estimating means is prioritized.

In the invention according to claim 8, further,
And a third traveling road estimating means for estimating the second traveling road as the traveling road based on the vehicle state quantity of the vehicle preceding the own vehicle.

[0016]

According to the first aspect of the present invention, the reliability of the traveling road estimated by each traveling road estimating means is calculated by the reliability calculating means, and the difference between the reliability values of the traveling roads is calculated. When the threshold value is exceeded, the travel area estimation means compares the travel paths estimated by the travel path estimation means, and the travel path is finally selected by a majority vote.

According to the second aspect of the present invention, the traveling road estimating means detects the white line portion on the road surface based on the image processing and estimates the traveling road on which the own vehicle is expected to travel in the future based on the white line portion. The left white line estimating means estimates the traveling path based on the left white line portion, while the right white line estimating means determines the right white line portion. And the road is estimated.

According to the third aspect of the present invention, the area correction means is provided for prioritizing the area based on the travel path estimated by the first travel path estimation means in the area exceeding the obstacle judgment distance.

According to the invention of claim 4, when the white line candidate point exceeds the detectable distance, the area based on the first traveling road estimating means is prioritized.

According to the fifth aspect of the present invention, the estimated traveling path is weighted by the coefficient of the detection rate and the detection time to finally determine the traveling path, and the traveling area is determined based on the traveling path. Is estimated.

According to the sixth aspect of the invention, the traveling path is selected in consideration of the environment in front of the vehicle detected by the environment detecting means.

According to the invention of claim 7, the estimation by the first traveling road estimating means or the estimation by the second traveling road estimating means is selected based on the size and the movement of the obstacle.

According to the eighth aspect of the present invention, the traveling road is estimated in consideration of the estimation by the third traveling road estimating means in addition to the estimation by the first and second traveling road estimating means.

[0024]

Embodiments of the present invention will be described below with reference to the drawings. This example is an example in which the vehicle travel path estimation device according to the present invention is applied to an obstacle detection device.

In FIG. 1 showing the entire automobile, reference numeral 1 is an automobile, and a radar head unit 3 is provided in front of a vehicle body 2. The radar head unit 3 emits a pulsed laser beam as a radar wave from the transmitting unit toward the front of the own vehicle, and at the receiving unit receives a reflected wave reflected by an obstacle such as a preceding vehicle in front of the vehicle. It is configured to receive, and measures the distance to an obstacle on the road. Further, the radar head unit 3 is of a scanning type which is emitted from its transmitting portion and is made to scan a pulse laser beam (beam) which is thin in the vertical direction and spread in a fan shape in the vertical direction in the horizontal direction at a relatively wide angle.

Reference numeral 4 denotes a CCD camera arranged in the upper part of the passenger compartment for photographing a scene (running path) in front of the vehicle within a predetermined range. The scene in front of the vehicle photographed by the camera 4 is: The image is input to the image processing unit 5 and subjected to image processing, and the control unit 6 estimates the traveling route based on the left and right white line portions of the road.

Further, the control unit 6 has a configuration shown in FIG.
As shown in FIG. 7, in addition to the signal from the CCD camera 4, a signal from the laser unit 3 is also detected, a vehicle speed sensor 7 for detecting the vehicle speed of the own vehicle, a steering angle sensor 8 for detecting the steering angle of the steering wheel 8a, and an own vehicle. Signals from a yaw rate sensor 9 that detects the yaw rate generated by the vehicle are also input, and the traveling road condition is displayed on the head-up display 10 based on these signals, and when an obstacle in front of the vehicle is detected, an alarm means 11 is issued. Is activated, the vehicle control device 12 actuates the brake 12a to automatically apply the braking force to each wheel.

Reference numeral 13 indicates the state of the headlamp (that is, ON / O).
It is a headlamp switch that detects FF, High / Low).

Specifically, as shown in FIG. 3, the signal from the radar head unit 3 is transmitted to the control unit 6
Is input to the calculation unit 22 through the signal processing unit 21 of the above, and in the calculation unit 22, the distance and relative speed between each obstacle existing in the scanning range and the own vehicle due to the delay time from the transmission time of the laser reception light. And the direction of the obstacle with respect to the own vehicle is calculated. Then, the signal processing unit 21
The calculating unit 22 constitutes an obstacle detecting means 6A for detecting an obstacle existing in a predetermined area in front of the own vehicle.

The detection signals of the sensors 7 and 8 are input to the first traveling path estimating means 25 and the first traveling path estimating means 23.
Is designed to estimate a predicted traveling route of the vehicle from the future based on the steering angle and the vehicle speed of the vehicle.
Further, the detection signals of the sensors 7, 8 and 9 are input to the second traveling path estimating means 24, and the second traveling path estimating means 24,
From the steering angle of the host vehicle, the vehicle speed, and the yaw rate, it is possible to estimate the predicted traveling path of the host vehicle. The first and second traveling path estimating means 23, 24
, But constitutes the first traveling road estimating means 6B for estimating the traveling road (specifically, its radius of curvature) based on the vehicle state quantity.

The signal from the image processing unit 5 is
It is input to the left white line estimating means 25 and the right white line estimating means 26, which extract the left and right white line portions of the road (running road) on which the vehicle is traveling from the scene in front of the own vehicle and estimate the left and right white line portions, and the left white line estimation means 26 respectively. And the right white line (specifically, their radii of curvature) are estimated. The left white line and right white line estimating means 25, 26 constitute second traveling road estimating means 6C for estimating a traveling road based on image processing.

Then, the signals from the first and second traveling road estimating means 6B and 6C are input to the traveling area setting means 28 together with the reliability calculating means 27. Reliability calculation means 27
Is configured to calculate the reliability of the traveling road (traveling road) estimated by the traveling road estimating means 6B and 6C, as described later. The area setting means 28 determines, based on the reliability of the traveling road, from the traveling road and the traveling road (the left and right white line portions),
The travel area (corresponding to the obstacle judgment area) in which the own vehicle is supposed to proceed is finally estimated.

Further, the obstacle information from the arithmetic unit 22 and the obstacle judging area information from the traveling area setting means 28 are inputted to the obstacle judging means 29, and in the obstacle judging means 29, the radar head unit 3 is used. If the degree of avoidance of the detected obstacle is judged in the traveling area (obstacle judgment area) set by the traveling area setting means 28 and it is judged that the obstacle needs to be avoided, the head-up display 10 is displayed. After the alarm is issued by the alarm device 11, the brake device 12a of the vehicle control device 12 is automatically activated.

Reference numeral 30 denotes an area correcting means for receiving a signal from the headlamp switch 13 and correcting the traveling area estimated by the second traveling path estimating means 6C according to the state of the headlamp. Although not specifically shown, the area correction unit 30 also uses the second traveling road estimation unit 6 based on the obstacle determination distance, the detectable distance of the white line candidate point, and the like.
The travel area estimated by C is corrected.

(1) Basic Control for Obstacle Detection by Obstacle Detection Device Hereinafter, basic control for obstacle detection by the obstacle detection device using the above-mentioned travel path estimation device will be described.

In FIG. 4, when starting, first, in step S1, the first and second traveling path estimating means 6B and 6C are provided.
The road is estimated by the step S2
Then, the front of the vehicle is recognized by the radar head unit 3,
Detect what is presumed to be an obstacle (obstacle information).

Then, in step S3, the area setting means 28 estimates the traveling area to be the obstacle judgment area from the traveling path estimated in step S1.

Then, in step S4, obstacle information is masked based on the obstacle judgment area, and in step S5, obstacle judgment is performed. The obstacle determining means 29 executes the above steps S3 to S5.

Then, in step S6, obstacle avoidance control is performed if necessary, and the process returns. Obstacle avoidance control
For example, although the warning is given by the warning device and the brake 12a of the vehicle control device 12, although not specifically shown, it may be given by an automatic steering device or the like.

(2) Traveling Road Estimation in Step S1 Basic Control for Determining Estimated Value Used for Running Road Estimation As shown in FIG. 5, first, in step 11, backlight determination is made, that is, backlighting is performed based on road surface brightness. Or not. As a result of this determination, in the backlight condition, the brightness of the road surface rises, and the white line portion and other portions cannot be sufficiently discriminated from each other. Therefore, the second traveling road estimating means 6C cannot accurately estimate the traveling road. Therefore, as will be described later, the estimated values R11, R12 by the first traveling road estimating means 6B are adopted without using the estimated values Rl, Rr by the second traveling road estimating means 6C.

If it is not the backlit state, in step 12, the estimated values (radius of curvature) Rl, Rr, R11, R12 for the traveling road are calculated by the traveling road estimating means 6B, 6C, and then the pitch angle of the CCD camera 4 is calculated. Error determination is performed (step S13). If the result of this determination is that there is an error in the pitch angle, it will not be possible for the second traveling road estimating means 6C to accurately estimate the traveling road, as will be described later, so that the estimation by the second traveling road estimating means 6C will be described later. The estimated values R11 and R12 by the first traveling road estimating means 6B are adopted without using the values Rl and Rr.

If there is no pitch angle error and there is no backlight condition, not only the traveling road estimation by the first traveling road estimating means 6B but also the traveling road estimation by the second traveling road estimating means 6C is possible. Once the value is obtained, step S is used to determine how to determine the estimated value.
In 14, the variation of the estimated values Rl, Rr for the traveling road by the second traveling road estimating means 6C, that is, the estimated values Rl, Rr
It is judged whether or not the mutual difference exceeds the threshold value ΔR. If the difference exceeds the threshold value ΔR, the estimated values Rl, R cannot be estimated because the variation is too large to trust.
Based on r and R11, a majority is used to finally select an estimated value to be used for estimating the traveling area (step S15). On the other hand, if the threshold value ΔR is not exceeded, the estimated values Rl and R for the traveling path
Since the reliability of r and R11 is detected (step S16) and the variation is small and the reliability of each estimated value Rl, Rr, and R11 is considered to be high, the reliability is determined based on the reliability without performing the majority control in step S15. Finally, an estimated value used for estimating the traveling area is calculated (step S17).

The control in each step will be specifically described below.

Backlight judgment in step S11 Concrete control is as shown in FIG.
The brightness of each pixel is detected (step S21), then the brightness (average brightness) CNTh of the white line part and the brightness (average brightness) CNTr of the road surface part are detected (step S22), and then the brightness CNTh of the white line part and the road surface part Difference from the brightness CNTr of
It is determined whether it is smaller than the predetermined value KHl (step S23).

If the determination in step S23 is yes,
Since it is considered that there is a backlight condition in which there is little difference in luminance between the white line portion and the road surface portion and the entire road surface is shining, the estimated values Rl and Rr for the traveling road by the second traveling road estimating means 6C are not used ( In the case of NO at step S24), since it is not in the backlight state, the estimated values Rl and Rr for the traveling road by the second traveling road estimating means 6C are used (step S25), and the process returns.

Calculation of Estimated Value for Driving Road in Step S12 (i) Basic Control of Calculation of Estimated Value by First Driving Road Estimating Means 6B In the first traveling road estimating means 23, it is performed according to a subroutine shown in FIG. . That is, after reading each signal from the vehicle speed sensor 5, the steering angle sensor 6 and the yaw rate sensor 7 in step S31, the steering steering angle θH is read in step S32.
And the traveling speed of the vehicle is predicted by the first prediction method based on the vehicle speed v0. Specifically, the estimated values R01 (radius of curvature) and β01 (side slip angle of the vehicle) for the traveling road are calculated by the following formulas.

[0047]

[Equation 1] Then, in step S33, the traveling path of the host vehicle is predicted by the second prediction method based on the yaw rate γ and the vehicle speed V0. Specifically, the estimated values R02 (radius of curvature) and β02 (side slip angle of the vehicle) for the traveling road are calculated by the following formulas.

[0048]

[Equation 2] Then, in step S34, it is determined whether or not the absolute value of the steering angle θH is smaller than the predetermined angle θc. If this determination is YES, the traveling path predicted by the second prediction method is selected in step S35, the estimated value R11 for the traveling path is set to R02, and the estimated value β11 is set to β.
Set 02 and return.

On the other hand, when the determination in step S34 is NO, that is, when the steering steering angle θH is larger than the predetermined angle θc, the absolute value of the estimated value R01 for the traveling path predicted by the first prediction method is further calculated in step S36. The magnitude of the value and the absolute value of the estimated value R02 for the traveling route predicted by the second prediction method are compared. Then, when the estimated value R01 for the traveling road predicted by the first prediction method is smaller, the process proceeds to step S37, and R01 is adopted as the estimated value R11 for the traveling road, and
While the angle β01 is set as the estimated value β11, when the estimated value R02 for the traveling road predicted by the second prediction method is smaller, the process proceeds to step S35, and the estimated value R11 for the traveling road is changed to R02. Is set, and β02 is set to the estimated value β11. That is, estimated value (curvature radius)
The smaller one is selected as the traveling route.

The first traveling route estimating means 23 estimates the traveling route based on the steering angle θH and the vehicle speed V0, and the second traveling route estimating means 24 estimates the traveling route based on the yaw rate γ and the vehicle speed V0. Since either one of the estimations is used according to the traveling state, it is possible to appropriately estimate the traveling path. That is, when the host vehicle turns on a curved road having a cant, the host vehicle makes a turning motion by the cant even if the steering wheel is not steered greatly. The estimated value R02 is the steering angle θH
It becomes smaller than the estimated value R01 for the traveling route predicted based on At this time, since the estimated value R02 for the traveling road predicted based on the yaw rate γ is adopted, the traveling road can be appropriately estimated without being influenced by the cant. Also, when your vehicle makes a sharp turn,
Corresponding to the steering steering angle θH, which is a large value, the estimated value for the traveling road will be estimated to be a small value of R01, and the traveling road should be estimated appropriately in response to a sudden turning operation. You can

When there is a preceding vehicle, the traveling route can be estimated as follows.

As shown in FIG. 8, when starting, it is first determined whether or not there is an obstacle on the traveling road (estimated value R11) estimated by the first traveling road estimating means 6B (step S41). . If there is an obstacle, it is subsequently determined whether or not the obstacle is a moving object and has existed on the traveling path estimated by the first traveling path estimating means 6B for a certain period of time (for example, 3 seconds or more) (step S42). ) On the other hand, if it does not exist, it returns as it is.

If an obstacle is present, the obstacle is the first
On the other hand, it is judged whether or not the vehicle deviates from the traveling road estimated by the traveling road estimating means 6B (step S43).

If the vehicle deviates from the traveling road, it is considered that there is a branch road. Therefore, the lock-on for monitoring the movement of the preceding vehicle is started, and the estimated value R12 (travel The radius of curvature of the road is calculated (step S44), and the process proceeds to step S45, while if there is no deviation, the process directly returns.

In step S45, it is determined whether or not a fixed time has elapsed from the start of lock-on. If the fixed time has elapsed, it is not necessary to monitor the movement of the preceding vehicle.
The lock-on is released (step S46), and if the fixed time has not elapsed, the process proceeds to step S47 to continue monitoring the preceding vehicle.

In step S47, it is determined whether or not the obstacle has returned to the traveling path (curvature radius R11). If the obstacle has returned, it is not necessary to monitor the movement of the preceding vehicle, and therefore the routine returns. If it has not recovered, the process proceeds to step S44.

In the determination in step S45, instead of determining whether a fixed time has elapsed from the start of lock-on,
It may be possible to determine whether 0.2G <V / R12. This is to find out how much lateral G occurs when the vehicle transforms from the traveling path having the radius of curvature R11 to the traveling path having the radius of curvature R12, and determines whether the value exceeds 0.2G. ing.

(Ii) Basic Control for Calculation of Estimated Value by Second Road Estimating Means 6C The flow of the process of road estimation by image processing is usually as shown in FIG.
It is done as shown in. As preconditions, it is considered that a side slip angle does not occur on a straight road, a vehicle body posture angle with respect to a white line portion is small on a straight road, and a running locus is a parallel movement of a lane on a curved road. The coordinates are assumed to have the vehicle on the road surface as the origin, the longitudinal direction of the vehicle as the y-axis, and the lateral direction as the x-axis.

Specifically, first, when starting, image data (luminance CNT (x, y) of each pixel) is taken in (step S51), and a binarization threshold value (THRESH) is set (step S51). S52), the binarization processing of 1 or 0 is performed depending on whether or not the brightness of each pixel exceeds the threshold value (step S53).
That is, if CNT (x, y)> THRESH, BW (x, y) = 1
On the other hand, if CNT (x, y) ≤ THRESH, then BW (x,
y) = 0, and the widths of the left and right scan windows by the CCD camera 4 in the left and right directions are set so as to correspond to the left and right white line portions (step S54), and subsequently,
A scan pitch corresponding to the front-rear direction of the vehicle is set (step S55), and the coordinates WP1x, WP1y and the number NWP- of the white line candidate points, that is, BW (x, y) = 1, are scanned by scanning the scan window according to the scan pitch. L1 (in the left scan window) and NWP-R1 (in the right scan window) are detected (step S56), and the plane coordinates are changed by the inverse perspective transformation (step S57). The coordinates of the white line candidate points after conversion are WP2x and WP2y.

Then, virtual candidate points (coordinates VPx, VPy, number NV) are set as points on the white line after the vehicle has run.
P) is set (step S58), and an approximate curve (y = ax ² + bx + c) by the method of least squares is applied to the left and right white line parts using the white line candidate points and the virtual candidate points, specifically, the quadratic curve of the left white line part. The coefficients aL, bL, cL of the curve and the coefficients aR, bR, cR of the quadratic curve for the right white line portion are calculated (step s59).

Here, in order to detect an obstacle on the road, the white line portion is approximated by a quadratic curve (y = ax ² + bx + c) due to the requirement that it must be detected further forward, and the coefficients aL and aR are white lines. If the radius of curvature of the part (quadratic approximation curve) is Rl (Rr), then a = 1 / 2Rl (1/2
Rr), the coefficients bL and bR represent the vehicle body attitude angle or the side slip angle with respect to the white line portion, and the coefficients cL and cR represent the lateral deviation amount from the vehicle center to the white line portion.

Then, the deviation (H
EN) is calculated (step S60), and the white line candidate points are tested (step S61). That is, if the deviation HEN exceeds the threshold value HENmax, it is excluded from the white line candidate points. Then, the number of white line candidate points after the verification is set to NWP-L2, NWP-
R2.

After that, the scan area is verified (step S62). That is, the number of white line candidate points after the test NWP-
It is determined whether or not L2 and NWP-R2 are smaller than a threshold value NWP-min (lower limit value of white line candidate points). If smaller, a scan window is reset, that is, a parameter related to the scan window is set to an initial value (step S6
3) Return, but if not smaller, update the scan window, that is, set the window to the position of the set width WDTH from the approximate curve (step S64), output the coefficient of the quadratic curve equation (step S65), and return. To do.

Control of Pitch Angle Error Judgment of CCD Camera in Step S13 As shown in FIG. 10, an estimated value for the traveling path based on the left and right white line portions RL and RR estimated by the image processing by the CCD camera 4 ( The radii of curvature Rl and Rr have opposite signs, and their absolute values are their average values (radius of curvature) Rx
In contrast to the absolute value of, when the estimated value (curvature radius) R11 of the traveling path R01 is substantially equal to the average value Rx, it is determined that the error is the pitch angle of the CCD camera. There is a need to do. Rl and Rr indicate an uphill state, and Rl 'and Rr' indicate a downhill state.

As a concrete control, as shown in FIG. 11, when starting, first, the estimated values Rl, Rr, R11 for the traveling road (traveling road) are read (step S70), and traveling based on the left and right white line portions is performed. Estimated value for road (radius of curvature)
The absolute values of Rl and Rr are their average values (radius of curvature) R
Unlike the absolute value of x, it is determined whether the estimated value (curvature radius) R11 for the traveling path is substantially equal to the average value Rx (step S71). Here, “substantially equal” means being equal within a certain threshold range, and does not mean being completely coincident. The same applies hereinafter in this specification.

If YES in the determination in step S71, the current deviation εφ, which is the lateral deviation between the vehicle A and the left and right white line parts, based on the estimated values of the left and right white line parts of the traveling road and the traveling road. It is determined whether the rates of change are substantially equal (step S72). On the other hand, if NO, it is considered that the estimated values for the left and right white line portions of the traveling road are unreliable, so the estimated value R11 for the traveling road is preferentially adopted (step S73), and the process returns.

Then, in the determination of step S72,
If NO, as in the case of NO in the determination in step S71, the estimated value R11 for the traveling path is preferentially adopted (step S73), and the process returns.

If YES in the determination in step S72, it is estimated that there is an error in the pitch angle, so the camera pitch angle is saved and the pitch angle is corrected (step S
74).

After the pitch angle correction in step S74, it is determined whether or not the estimated values Rl and Rr for the left and right white line portions are substantially equal (step S75). If they are substantially equal, the pitch angle correction eliminates the error. Since the judgment is made, the estimated values Rl and Rr for the left and right white line parts are preferentially adopted (step S76), and while returning, if they are not substantially equal, whether the number of repetitions N is the set number Ns in step S78. If the number of repetitions N is not the set number Ns,
Returning to step S74, while the pitch angle correction is repeated, if the number of repetitions N reaches the set number Ns, it is determined that it is not a pitch angle error, so the pitch angle is returned to the original (step S78), and then step S73. Move to.

Control for Determining Estimated Value Based on Reliability As shown in FIG. 12, when starting, first, regarding the radii of curvature Rl, Rr and their estimation based on the left and right white line portions of the road estimated by the image processing. The reliability of S,
Sr is calculated (step S81), and then the reliability Sl
, Sr threshold S01 is set (step S82).

Then, the reliability S of each radius of curvature Rl, Rr
It is determined whether both l and Sr are smaller than the threshold value S0 (step S83). If the values are smaller than the threshold value S0, reliability is poor. Therefore, the radius of curvature R11 based on the traveling path is adopted (step S84).
To return. On the other hand, if it is not smaller, then it is determined whether or not the reliability degrees Sl and Sr of the white line portions Rl and Rr are both higher than the threshold value S0 (step S85). If not, the reliability degrees Sl and Sr are determined. Is used, that is, the radius of curvature of the white line portion larger than the threshold value S0 is adopted (step 86), and the process returns.

If both are greater than the threshold value S0, the radii of curvature are determined by weighting the reliability values Sl and Sr based on the following equation (step S87), and the process returns.

[0073]

[Equation 3] Further, as shown in FIG. 13, the reliability S for the radius of curvature (estimated value) of each white line portion is replaced with the control of step S87 for obtaining the radius of curvature by weighting with the reliability S1, Sr.
It is also possible to compare l and Sr (step S88), use the radius of curvature with the higher reliability (steps S89, S90), and return.

Next, specific examples 1 to 3 as a method of obtaining the reliability will be described.

(I) Concrete Example 1 The reliability is calculated based on the following equation from the number NWP of left and right white line candidate points and the deviation HEN between the white line candidate points and the approximate curve.

[0076]

[Equation 4] (ii) Concrete Example 2 The reliability is determined stepwise based on the rate of change Kh of the radius of curvature (estimated value) obtained by the following formula (see FIG. 14).

[0077]

[Equation 5] Concrete Example 3 Based on the following equation, the reliability is calculated by the detection rate of the radius of curvature (estimated value).

[0078]

[Equation 6] In the control shown in FIG. 13, the reliability is directly compared to determine the estimated value with high reliability. However, the estimated value (curvature radius) with higher reliability is determined. Alternatively, it can be determined as shown in the following specific examples 4 and 5.

Concrete Example 4 In this example, the judgment is made by the cycle of the white line candidate points / scan range.

If the left and right white line parts are not the solid white lines RL and RR but the broken white lines RL 'and RR', the estimated value is accurate unless the scan range W is set properly as shown in FIG. This is because it is not required for. The white line candidate point / scan range value JH is obtained by the following formula. When this period is large, the period is long because of irregular fluctuations, and is considered to be a solid line. When the period is small, the white line is It is considered that the parts are broken lines arranged at regular intervals. Further, in the case of the broken line, since the change is large, it is considered that the amplitude becomes larger than that of the solid line.

[0081]

[Equation 7] As shown in FIG. 16, when the control flow starts, first, the cycles JHLT, JHRT and the amplitudes JHLB, JHRB of the above-mentioned value JH for the left and right white line parts are calculated (step S91), and right. The period JHr T of the above value JH for the white line portion is smaller than the threshold value T1 and the amplitude JHr
It is determined whether B is larger than the threshold value B1 (step S92). Then, whether the judgment is YES or NO, it is judged whether or not the cycle JH1T for the left white line part is smaller than the threshold value T1 and the amplitude JH1B is larger than the threshold value B1 (step S93, S94).

If YES in step S93, it is determined that the left and right white line portions are broken lines with considerably large intervals, and the reliability is considered to be low. Therefore, the estimated value based on the vehicle state quantity is used. The image data is changed to the first approximation, the lane width is estimated, these are used (step S95), and the process returns, while if NO, the cycle JH
Since r T is larger than the threshold value T1 or the amplitude JHr B is smaller than the threshold value B1, the period JHl T is smaller than the threshold value T1 and the amplitude JHl B is larger than the threshold value B1, the white line portion is considered to be a solid line. And the radius of curvature Rl of the left white line
Is used (step S96) and the process returns.

On the other hand, in the determination of step S94, YE
If S, the radius of curvature Rr for the right white line portion is used (step S98), and while returning, if NO,
The radii of curvature Rl and Rr of the left and right white line portions are averaged to determine the radius of curvature used for roadway estimation (step S97), and the process returns.

Concrete Example 6 In this example, judgment is made by comparing current deviations.

As shown in FIG. 17, the specific control flow is such that, when started, the difference between the current deviation B and the current deviation B't seconds ago is calculated for each white line portion (step S101).
), It is determined which of the left and right white line portions is larger (step S102), and the larger the difference, the lower the reliability. Therefore, if the right white line portion is larger, the left white line portion is larger. The radius of curvature Rl for the part is adopted (step S103), and if the left white line part is larger, the radius of curvature Rr for the right white line part is adopted (step S10).
4), return.

In each of the above examples, the reliability of the estimated value for the left and right white line portions is calculated, and the estimated value obtained by estimating the traveling path based on the vehicle state quantity is reliable when the vehicle behavior is in a steady state. Is high and the reliability is low in the transient state, that is, the reliability depends on the rate of change, and therefore the reliability of the estimated value for the traveling path is calculated and used as shown in FIG. You can also do it.

In FIG. 18, when starting, first,
The average value RAVE of R11 in the past N times is calculated (step S10
1) The difference RSUB between the current R11 and the average value RAVE is calculated (step S102).

[0088]

[Equation 8] Then, the reliability PTR is calculated based on the following equation (step S103), and the process returns.

[0089]

[Equation 9] When the basic control for estimating the travel route by majority decision is started, first, as shown in FIG. 19, it is determined whether or not there is an output of the estimated value R12 for the second travel route which is the travel route of the preceding vehicle. (Step S111
).

If the estimated value R12 for the second traveling road is output, it is determined whether or not a winker signal is output to the second traveling road side of the estimated value R12 (curvature radius) (step S112). If the winker signal is output, the second traveling path having the estimated value R12 (radius of curvature) is prioritized (step S113), and the process returns, while if the winker signal is not output, the process proceeds to step S114.

On the other hand, if the estimated value R12 for the second traveling road is not output in step S111, it is determined whether or not the estimated values Rl, Rr, R11 for the traveling road and the traveling road are all substantially equal (step S11). If all of them are substantially equal, the estimated region can be secured widely, so the estimated values Rl and Rr for the traveling road are prioritized (step S116), and the process returns. The relationship between the estimated values in this case is shown in FIG.

If all are not equal, it is determined whether the estimated values Rl and Rr for the left and right white line portions of the traveling road are substantially equal and the estimated value R11 for the traveling road is different from them (step S117). If YES (FIG. 21)
If the answer is NO, the process proceeds to steps S118 and S119, and only one of the estimated values Rl and Rr for the left and right white line portions of the traveling road is the estimated value R11 for the traveling road. Is equal to
If they are equal (see FIG. 22 and FIG. 23), the estimated value Rl (or Rr) of the other one is prioritized (steps S120, S12).
1) If none of them are equal, the estimated value R11 for the traveling path is given priority (step S122), and the process returns.

In step S114, the estimated value Rl for the left white line portion and the estimated value R11 for the traveling road are equal, the estimated value Rr for the right white line portion and the estimated value R12 for the second traveling road are equal, Further, it is determined whether or not the condition that they are not equal is satisfied, and if YES (see FIG. 24), the process proceeds to step S120, while if NO, the estimated value Rr for the right white line portion is further calculated. It is determined whether or not the conditions that the estimated values R11 for the traveling route are equal, the estimated value Rl for the left white line portion and the estimated value R12 for the second traveling route are equal, and they are not equal (step S123). ), If YES (Fig. 2
5), the process proceeds to step S121, while in the case of NO, the majority decision is made (step S124).
), Return.

Further, as shown in FIG. 26, the estimated value for the estimated traveling road is weighted by the coefficient of the detection rate and the detection time, and the majority decision formula is used to finally determine the traveling road. It is also possible to estimate the travel route.

[0095]

[Equation 10] That is, when the vehicle is started, the estimated value Rl for the traveling road,
Rr, R11, R12 are read (step S131), it is determined whether there is a blinker operation by a blinker signal (step S132), and if there is a blinker operation, the estimated value (radius of curvature) of the road in the direction of the blinker is prioritized. On the other hand, the process returns (step S133), and if there is no winker operation, the process proceeds to step S134 to determine whether the image detection rate exceeds 50%.

If the image detection rate exceeds 50%,
Estimated value R by the second traveling road estimating means 6C by image processing
Since it is considered that the reliability of l and Rr is high, the travel route is determined by the majority decision formula (step S135), while 5
If it does not exceed 0%, the radius of curvature R11 is prioritized (step S136), and the traveling area is set (step S13).
7), return.

After determining the traveling road, an estimated value (curvature radius) for the traveling road is calculated (step S138).
), And returns through step S137. Also,
Instead of the majority decision formula, the following formula may be used to directly estimate the travel route.

[0098]

[Equation 11] (6) Correction control The control that changes the estimated range of the left and right white line parts depending on the state of the headlamp switch Considers that the detection state of the white line part differs depending on the lighting state of the headlamps.

As shown in FIG. 27, when starting, the position of the head wrap switch 13 is detected (step S14).
1) It is determined whether or not the headlamp switch is OFF (step S142). If YES, it can be considered that the environment is good in the daytime, so white line data (white line candidates) up to 60 m in front of the vehicle body. Point) is detected to estimate the traveling path, the obstacle judgment area is set by predicting 120 m ahead of the vehicle body, and obstacle judgment is made (step S143). If NO, the headlamp switch is in the high position. Or the Low position is determined (step S144).

In the determination at step S144, it is determined that High
If it is at the h position, the white line data up to 40 m ahead of the vehicle body is detected to estimate the traveling path, the obstacle judgment area is set by predicting up to 60 m ahead of the vehicle body, and the obstacle is judged (Step S145), while Low is determined. If it is at the position, the front of the vehicle is darker than it is at the High position. Therefore, the white line data up to 20 m in front of the vehicle is detected to estimate the traveling path, and the vehicle front 40
The obstacle judgment area is set by predicting up to m, and the obstacle is judged (step S146).

Further, as shown in FIG. 28, when the headlamp is ON, the road surface light due to the light U of the headlight causes not only the original white line candidate points P1 to P4, but also the road surface light portions P5 to P8 to be detected. There is a risk of erroneous detection as a white line candidate point of the white line portions RL and RR. Therefore, in order to avoid this erroneous detection, the headlamp is turned on / off, as shown in FIG. Since it is considered that there is no white line part, the false detection is performed by using the scan windows W11 ′ and W12 ′ that are removed from the original left and right scan windows W11 and W12 for image processing (see FIG. 28). I try to prevent it.

Correction Based on Detection Distance of White Line Candidate Point In this example, up to the distance L11 for originally detecting the white line candidate point and detecting the white line portions RL and RR, such as near the summit of the slope shown in FIG. This is a countermeasure when the white line candidate points cannot be detected.

As shown in FIG. 31, when the vehicle is started, the estimated values Rl and Rr (radius of curvature) for the white line portion of the traveling road estimated by the second traveling road estimating means 6C and the first traveling road estimating means 6B are estimated. Estimated values R11 and R12 (radius of curvature) for the traveled route are read (step S151
), And based on them, the traveling path is estimated by the method described above (step S152). Then, a detectable distance L11 at which a white line candidate point can be actually detected is calculated based on the signal from the traveling road estimation means (step S153),
Then, it is determined whether or not the detectable distance L11 is smaller than a set distance Ls (threshold value) which is predetermined to detect the white line portion (white line candidate point) (step S154).

If the detectable distance L11 is smaller than the set distance Ls, it is considered unlikely that an obstacle exists beyond the detectable distance. The estimated values Rl and Rr for the left and right white lines of the traveling road are prioritized (step S155), and the estimated value R11 for the traveling road is prioritized after the detectable distance L11 (step S156), and obstacle judgment areas are set respectively. (Step S157) and the process returns.

Correction by Laser Data In this example, a laser data unit (environment detecting means) for detecting the environment in front of the own vehicle when the estimated value radius by the traveling road estimating means and the estimated value by the traveling road estimating means are completely different.
Therefore, using the detected structure (for example, a roadside reflector, a vehicle in an adjacent lane, etc.), it is determined which estimated value (curvature radius) is reliable.

As shown in FIG. 32, when starting, first, the estimated values Rl and Rr for the white line portion of the traveling road and the estimated value R11 for the traveling road are read (step S161).
), It is determined whether or not the estimated values Rl, Rr, R11 are all different (step S162).

If all the radii of curvature are different, it is judged whether or not there are N or more regular laser radar data (data relating to the environment in front of the vehicle) (step S).
163) On the other hand, if not, that is, if three or two radii of curvature are equal, a majority rule is used to give priority to the estimation R having the same radius of curvature (step S170). Note that at least N = 3 pieces of laser radar data are necessary for the laser radar data, considering that the traveling road is a curve.

When there are N or more pieces of laser radar data, it is determined whether or not the estimated value (radius of curvature) of the traveling path based on the laser data radar is equal to any of the estimated values Rl, Rr, R11. (Step S165) On the other hand, if there is no laser radar data, it is not possible to determine which of the estimated values (radius of curvature) has high reliability.
Migrate to 163 and shut down the system.

The estimated values (radius of curvature) Rl, Rr, R
If none of 11 is equal to the estimated value (radius of curvature) estimated by the laser radar data, the process similarly proceeds to step S163, but if any of the estimated values Rl, Rr, R11 is equal, It is determined that the reliability of the same estimated value is the highest, and the estimated value (curvature radius) is prioritized (steps S166 to S168), the travel route is estimated, and the obstacle determination area is set based on it (step S169). , Return.

For example, as shown in FIG. 33, the estimated values Rl,
Even if Rr and R11 are all different, the laser data D1 to D4 in front of the vehicle A match the estimated value Rr, and in this case, the estimated value Rr is prioritized.

Correction Based on Obstacle Judgment Distance In this example, it is desirable to judge obstacles over the entire traveling path within the obstacle judgment distance that is immediately before the host vehicle.
If the obstacle determination distance is exceeded, it is not necessary to set the obstacle determination region to be wide, and this is because the region is set based on the traveling route estimated by the traveling route.

As shown in FIG. 34, when the vehicle is started, the traveling road is first estimated based on the above-mentioned method (step S171), and then the obstacle judgment distance L21 is calculated from the own vehicle speed, the relative speed and the road friction coefficient. Yes (step S17
2). The obstacle judgment distance L21 is calculated by the following equation, for example.

[0113]

[Equation 12] Then, even if the estimated values Rl and Rr for the white line portion of the road are prioritized in step S171,
Only within the obstacle judgment distance L21, the estimated values Rl and Rr for the white line portion of the traveling road are prioritized. If the obstacle judgment distance L21 is exceeded, the estimated value R11 for the traveling road is prioritized and the obstacle judgment area is set. Set (step S173) and return.

Therefore, as shown in FIG. 35, the estimated values (radius of curvature) Rl and Rr for the white line portion of the road are prioritized until the obstacle judgment distance L21 where the obstacle judgment request is particularly high. Since the setting is performed and the obstacle determination area is not unnecessarily enlarged, the obstacle determination can be efficiently performed.

When the estimated value (curvature radius) R11 for the traveling road is prioritized in step S171, the estimated value R11 for the traveling road is obtained within the obstacle judgment distance and beyond the obstacle judgment distance. Has priority.

(13) Correction Based on Obstacle Size As shown in FIG. 36, when starting, it is first determined whether or not the estimated values Rl, Rr, R11 for the traveling path are all substantially equal (step S181). ), If equal then step S
At 182, it is determined whether or not the relative speed V1 is equal to the own vehicle speed V0 regarding the movement of the obstacle, and if not, the process immediately returns.

If the relative speed is equal to the own vehicle speed, the obstacle has not moved. Therefore, the routine proceeds to step S183, where it is judged whether or not the width of the obstacle is smaller than a predetermined value. It is determined that the group is a copy, the estimated value R11 is prioritized (step S184), and the traveling path is set (step S18)
5) return.

If the size of the obstacle is less than the predetermined value, the estimated values Rl and Rr are given priority (step S186), the travel area is set (step S185), and the process returns.

(9) Control in the case where only one of the radii of curvature of the left and right white line parts matches the radius of curvature of the vehicle state quantity Specifically, as shown in FIG. The estimated value Rl for the left white line portion of the traveling road estimated by the means is approximately equal to the estimated value R11 for the traveling road estimated by the traveling road estimating means, and the estimated value Rr for the right white line portion is undetectable. It is determined whether or not (step S191).

If YES, the right scan area is shifted to the left (step S192), and it is determined whether or not Rr is detected (step S193). If NO, the process directly returns.

If YES in the determination in step S193, it is determined whether or not the current deviation can be determined (step S194), and if possible, it is determined that it is a so-called lane crossing traveling on a lane (step S194). S195), the lane width is estimated from the estimated values Rl and Rr, and the process returns, while
If NO, the lane width is estimated using the past history of the white line based on the estimated value Rl (step S196), and the process returns.

[0122]

The invention according to claim 1 has the following features.
The reliability of the traveling road estimated by each traveling road estimating means is calculated by the reliability calculating means, and when the difference between the reliability values of the traveling road is equal to or more than a threshold value, the traveling area estimating means performs Since the running paths estimated by the respective running path estimating means are compared and the running path is finally selected by the majority decision, when a plurality of running path estimating means are provided,
Even if the estimation values obtained by the estimation means are different, it is possible to accurately estimate the traveling path.

According to the second aspect of the present invention, the left and right white line portions on the road surface are detected based on the image processing, and based on the left and right white line portions, it is possible to estimate the traveling road on which the vehicle is expected to travel in the future. Therefore, it is possible to estimate a wide traveling path.

According to the third aspect of the present invention, in the area exceeding the obstacle judgment distance, the area based on the traveling road estimated by the first traveling road estimating means is prioritized.
It is possible to estimate a wide traveling road in an area where obstacle judgment is required. .

According to the fourth aspect of the present invention, when the distance over which the white line candidate points can be detected is exceeded, the area based on the first traveling road estimating means is prioritized, so that the traveling road can be estimated without waste.

According to the fifth aspect of the present invention, the road is determined by the majority decision formula weighted by the coefficient of the detection rate and the coefficient of the estimated time. Therefore, the road can be easily estimated.

In the invention according to claim 6, since the traveling path is estimated in consideration of the environment in front of the host vehicle, the accuracy of estimation of the traveling path can be improved.

According to the seventh aspect of the invention, the estimated value by the first traveling road estimating means or the estimated value by the second traveling road estimating means is selected based on the size and movement of the obstacle. It is possible to estimate the traveling path according to the obstacle.

In the invention according to claim 8, the traveling road is estimated in consideration of the estimation by the third traveling road estimating means in addition to the estimation by the first and second traveling road estimating means. It is possible to accurately estimate the traveling path.

[Brief description of drawings]

FIG. 1 is a perspective view of an automobile.

FIG. 2 is a block diagram of a control system.

FIG. 3 is a block diagram of a control unit.

FIG. 4 is a flowchart showing a flow of an obstacle detection process.

FIG. 5 is a flow chart showing basic control of travel route estimation.

FIG. 6 is a flowchart showing the control of backlight determination.

FIG. 7 is a flow chart showing a subroutine of traveling path estimation based on a vehicle state quantity.

FIG. 8 is a flow chart showing a subroutine of traveling path estimation based on a preceding vehicle.

FIG. 9 is a flowchart showing a subroutine of roadway estimation based on image processing.

FIG. 10 is an explanatory diagram of pitch angle correction of a CCD camera.

FIG. 11 is a flowchart showing a subroutine of pitch angle correction of the CCD camera.

FIG. 12 is a flowchart showing a subroutine of reliability calculation.

FIG. 13 is the same flowchart.

FIG. 14 is a diagram showing a relationship between a change rate of an estimated value and reliability.

FIG. 15 is an explanatory diagram of a solid line and a broken line of a white line portion.

FIG. 16 is a flowchart showing a control subroutine for determining one with high reliability.

FIG. 17 is the same flowchart.

FIG. 18 is a flowchart showing a subroutine of reliability calculation.

FIG. 19 is a flow chart of control for determining an estimated value by majority voting.

FIG. 20 is a diagram showing a relationship between estimated values.

FIG. 21 is a diagram showing a relationship between estimated values.

FIG. 22 is a diagram showing a relationship between estimated values.

FIG. 23 is a diagram showing a relationship between estimated values.

FIG. 24 is a diagram showing a relationship between estimated values.

FIG. 25 is a diagram showing a relationship between estimated values.

FIG. 26 is a flowchart showing a modified example.

FIG. 27 is a flowchart showing a headlamp correction subroutine.

FIG. 28 is an explanatory diagram of headlamp correction.

FIG. 29 is an explanatory diagram of the same.

FIG. 30 is an explanatory diagram of a detection distance of a white line candidate point.

FIG. 31 is a flowchart showing a subroutine of correction based on the detection distance of a white line portion candidate point.

FIG. 32 is a flowchart showing a subroutine of correction based on laser data.

FIG. 33 is an explanatory diagram of correction based on laser data.

FIG. 34 is a flowchart showing a subroutine of correction based on an obstacle judgment distance.

FIG. 35 is an explanatory diagram of the same.

FIG. 36 is a flowchart showing a subroutine for correction based on the size of an obstacle or the like.

FIG. 37 is a flowchart showing a lane crossing determination subroutine.

[Explanation of symbols]

 1 Car 6 Control Unit 6A Obstacle Detecting Means 6B First Driving Road Estimating Means 6C Second Driving Road Estimating Means 7 Vehicle Speed Sensor 8 Steering Angle Sensor 9 Yaw Rate Sensor 27 Reliability Calculating Means 28 Traveling Area Setting Means 30 Area Correcting Means

 ─────────────────────────────────────────────────── ─── Continuation of the front page (72) Inventor Tomohiko Adachi No. 3 Shinchi, Fuchu-cho, Aki-gun, Hiroshima Prefecture Mazda Co., Ltd. (72) Inventor Hiroshi Nakaue No. 3 Shinchi, Fuchu-cho, Aki-gun, Hiroshima Mazda Stock In the company

Claims (8)

[Claims] 1. A travel route estimation device for a vehicle, comprising: a plurality of travel route estimation means for estimating a future travel route of a vehicle; calculating reliability of the travel route estimated by each of the travel route estimation means. When the difference between the reliability values of the traveling paths exceeds a threshold value by receiving the output of the reliability calculating means and the reliability calculating means, the traveling paths estimated by the respective traveling path estimating means are compared, A travel route estimating device for an automobile, comprising: a travel region estimating means for finally selecting a travel route by majority decision and estimating a travel region. 2. The traveling road estimating means estimates, as a traveling road, a first traveling road on which the own vehicle is expected to travel in the future based on the vehicle state quantity, and a road surface based on image processing. A second travel route estimating means for detecting a white line candidate point which is supposed to constitute the upper white line portion, estimating the white line portion based on the white line candidate point, and estimating a travel route where the own vehicle is expected to travel in the future; The vehicle travel path estimation device according to claim 1, further comprising: 3. A distance calculation means for calculating an obstacle judgment distance based on a vehicle speed, a relative speed, a friction coefficient of a road surface, and the like, and an area which exceeds an obstacle judgment distance when an output of the distance calculation means is received. 3. The traveling path estimation device for an automobile according to claim 2, further comprising area correction means for prioritizing the estimation by the first traveling path estimation means when estimating the traveling area by the traveling area estimation means. 4. A distance calculating means for calculating a detectable distance of a white line candidate point by the second traveling road estimating means, and an area which receives an output of the distance calculating means and exceeds the detectable distance of the white line candidate point. 3. The vehicle travel path estimation device according to claim 2, further comprising area correction means for prioritizing the estimation by the first travel path estimation means when the travel area estimation means estimates the travel area. 5. The travel area estimating means weights the estimated travel path with a coefficient of a detection rate and a detection time, finally determines the travel path, and estimates the travel area. The vehicle travel path estimation device according to claim 2. 6. An environment detecting means for detecting an environment in front of the own vehicle, wherein the traveling area estimating means receives an output of the environment detecting means, selects a traveling path in consideration of the environment, and estimates a traveling area. The traveling path estimation device for an automobile according to claim 2, which is a vehicle. 7. An obstacle detecting means for detecting an obstacle in front of the vehicle, wherein the traveling area estimating means receives the output of the obstacle detecting means, and based on the size and the movement of the obstacle, the first traveling path. 3. The traveling path estimating device for a vehicle according to claim 2, wherein which of the estimation by the estimating means and the estimation by the second traveling path estimating means is prioritized. 8. The traveling road of the automobile according to claim 2, further comprising a third traveling road estimating means for estimating the second traveling road as a traveling road based on the vehicle state quantity of the vehicle preceding the own vehicle. Estimator.