JPH08136237A - Device for calculating gradient of road and car speed controller - Google Patents

Abstract

PURPOSE: To enable a device mounted on a vehicle for calculating gradient of a road to calculate the gradient of the road where the vehicle is traveling through a simple processing by extracting left and right lane markers indicating the lane on which the vehicle is traveling from an imaged picture showing the stage of the road and detecting the width of the lane on the picture. CONSTITUTION: An image pickup means composed of a CCD camera 201 picks up the scene in front of the vehicle 210 having the image pickup means and a picture processor 203 extracts lane markers and features of vehicles from a picture inputted from the camera 201. The processor 203 also detects the lane width for every scanning line on the picture and the position of the precending vehicle. An arithmetic processing section 204 which operates as a road gradient calculating means and vehicle-to-vehicle distance calculating means calculates the distance to the preceding vehicle and the gradient of the road from the output of the processor 203 and pickup condition. A car speed control section 207 outputs a control parameter in accordance with a preset control program based on the gradient of the road and distance data outputted from the processing section 204 and the speed of the vehicle outputted from a car speed sensor 206.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention is used for consideration of preventive and safe driving of a vehicle, and in particular, when a road gradient in front of the vehicle is detected and another vehicle is present on the lane, The present invention relates to a traveling road gradient calculating device and a vehicle speed control device that detect an inter-vehicle distance between a host vehicle and another vehicle.

[0002]

2. Description of the Related Art As a conventional road gradient calculating device, for example, a device for detecting a road gradient disclosed in JP-A-3-277916, and JP-A-3-2735.
A system or the like for calculating the inter-vehicle distance disclosed in Japanese Patent Publication No. 00 is known.

The details of the above-mentioned Japanese Patent Laid-Open No. 3-273500 will be described in detail. A scene in front of the vehicle is photographed by using one image pickup device, and the characteristics of the vehicle in front are extracted by image processing. The distance to the vehicle in front is calculated by detecting the height of the image captured from the lower edge of the screen. In addition, JP-A-3-2779
No. 16 gazette captures the scenery in front of the vehicle by using two image pickup devices, detects the same feature point from two image pickup screens, and detects that point by the binocular parallax from the image pickup positions on both screens. It calculates the distance and height of.

[0004]

However, in the conventional inter-vehicle distance detection system as described above, the distance to the vehicle in front can be calculated by a relatively simple process, but When there is a gradient, for example, when the vehicle is on an uphill, the vehicle ahead is imaged at a higher position on the screen than when it is on a flat road, so it is calculated as a distance longer than the actual distance, and the accurate inter-vehicle distance is detected. There was a problem that I could not do it.

Further, in the conventional detection of the road gradient, the road gradient can be detected by using the feature points on the road surface. However, in order to perform the detection with high accuracy, one sheet is used. Since the amount of information on the screen is very large, there is a problem that the detection of the same feature point on two screens complicates the processing and prolongs the processing time.

The present invention has been made in view of the above, and an image of a landscape in front of a vehicle is picked up by using one image pickup device, and image processing is performed on the image pickup screen to easily determine a roadway gradient. The purpose is to realize the calculation and to calculate the inter-vehicle distance with high accuracy from the lane width considering the slope of the road.

[0007]

In order to achieve the above-mentioned object, in the traveling road gradient calculating device according to claim 1,
As shown in FIG. 1, an image pickup means CL1 for picking up an image of a road condition ahead of the host vehicle, an image processing part CL2 for extracting a lane marker or a feature of the vehicle from a road condition image picked up by the image pickup part CL1, and the image processing. Lane width detecting means C for detecting the lane width on the screen from the distance between lane markers at a predetermined position of the road condition image processed by the means CL2.
L3, a road gradient calculating means C for calculating the gradient of the traveling road from the lane width detected by the lane width detecting means CL3 and the position and angle of the image pickup means CL1 with respect to the road coordinate system.
And L4.

Further, in the traveling road gradient calculating device according to the second aspect, the image pickup means CL1 for picking up an image of the road condition ahead of the host vehicle, and the lane marker and the vehicle from the road condition image picked up by the image pick-up device CL1. Image processing means CL2 for extracting features, and lane width detection means CL3 for detecting the lane width on the screen from the interval between lane markers at a predetermined position of the road condition image processed by the image processing means CL2.
And a road gradient calculating means CL4 for calculating the gradient of the traveling road from the lane width detected by the lane width detecting means CL3 and the position and angle of the image pickup means CL1 with respect to the road coordinate system.
And a forward vehicle detecting means CL5 for detecting the presence of a forward vehicle from the road condition image, a position on the screen of the forward vehicle detected by the forward vehicle detecting means CL5, and traveling calculated by the road gradient calculating means CL4. Inter-vehicle distance calculating means CL6 for calculating the distance to the vehicle ahead from the road gradient.
It is provided with.

Further, in the vehicle speed control device according to the third aspect, the image pickup means CL1 for picking up an image of the road condition in front of the host vehicle.
And an image processing means C for extracting the features of the lane marker and the vehicle from the road condition image captured by the image capturing means CL1.
L2, a lane width detecting means CL3 for detecting a lane width on the screen from a lane marker interval at a predetermined position of the road condition image processed by the image processing means CL2, and a lane width detected by the lane width detecting means CL3. And a road gradient calculating means CL4 for calculating the gradient of the traveling road from the position and angle of the image pickup means CL1 with respect to the road coordinate system, a forward vehicle detecting means CL5 for detecting the presence of a forward vehicle from the road condition image, and the forward vehicle. An inter-vehicle distance calculation means CL6 for calculating the distance to the front vehicle from the position of the front vehicle on the screen detected by the detection means CL5 and the traveling road gradient calculated by the road gradient calculation means CL4, and the inter-vehicle distance calculation means. CL6 and the road gradient calculating means CL
The vehicle speed control means for controlling the vehicle speed of the host vehicle based on the calculation result obtained from No. 4 is provided.

Further, in the traveling road gradient calculating device according to claim 4, the road gradient calculating means CL4 is arranged on the road condition image of the lane width detected by the lane width detecting means CL3 and the lane width. The traveling road gradient is calculated based on the positional relationship.

Further, in the traveling road gradient calculating device according to the fifth aspect, the inter-vehicle distance calculating means CL6 detects the detected position (y coordinate) on the screen of the vehicle ahead and the lane corresponding to the detected position. The inter-vehicle distance is calculated based on the width.

[0012]

In the traveling road gradient calculating device (Claim 1) according to the present invention, the scenery in front of the vehicle is photographed by one image pickup means CL1, and the lane width detecting means C is taken from the photographed road condition image.
The left and right lane markers indicating the vehicle lane are extracted by L3 to detect the lane width of the vehicle lane on the screen, and the road gradient calculating means CL4 calculates the road gradient from the detected value.

The roadway gradient calculating device according to the present invention (claim 2) photographs the scenery in front of the vehicle by one image pickup means CL1, and the vehicle travels by the lane width detection means CL3 from the photographed road condition screen. The left and right lane markers indicating the lanes are extracted to detect the lane width of the own vehicle traveling lane on the screen, the road gradient calculating means CL4 calculates the traveling road gradient from the detected value, and the forward vehicle detecting means CL5 described above. The front vehicle is detected from the photographed road condition screen, and the inter-vehicle distance detecting means CL6 calculates the inter-vehicle distance from the lane width at the lower end position of the front vehicle.

A vehicle speed control device according to the present invention (claim 3)
Captures the scenery in front of the vehicle with one image capturing means CL1, and detects the lane width detection means CL3 from the captured road condition screen.
By extracting the left and right lane markers indicating the own vehicle traveling lane by detecting the lane width of the own vehicle traveling lane on the screen, the road gradient calculating means CL4 calculates the traveling road gradient from the detected value, and the forward vehicle is detected. The vehicle CL is detected by the means CL5 from the photographed road condition screen, and the vehicle distance detection means CL6 calculates the vehicle distance from the lane width at the lower end position of the vehicle ahead. Further, the vehicle speed control means CL7 includes the inter-vehicle distance calculation means CL6 and the road gradient calculation means CL.
The vehicle speed of the host vehicle is controlled based on the calculation result obtained from 4.

In the traveling road gradient calculating apparatus according to the present invention (claim 4), the road gradient calculating means CL4 calculates the lane width on the screen, and the calculated lane width and the lane width on the screen. The road gradient is calculated based on the positional relationship.

In the traveling road gradient calculating device according to the present invention (claim 5), the inter-vehicle distance calculating means CL6 detects the detected position (y coordinate) on the screen of the vehicle ahead and the lane width corresponding to the detected position. The inter-vehicle distance is calculated based on.

[0017]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS An embodiment of a roadway slope calculating device and a vehicle speed control device according to the present invention will be described below with reference to the accompanying drawings. FIG. 2 is a block diagram showing the system configuration of the roadway slope calculating device and the vehicle speed control device according to the present invention. One CCD camera 201 as an image pickup means for photographing the scenery in front of the vehicle, and the CCD camera 201 Image processing means for extracting lane markers and vehicle features from a given input screen, lane width detecting means for detecting lane width for each scanning line on the screen, and image processing as front vehicle detecting means for detecting the position of the front vehicle. A device 203, an arithmetic processing unit 204 for calculating an inter-vehicle distance and a road gradient with respect to a forward vehicle based on an output of the image processing device 203 and a photographing condition, and an output from the arithmetic processing unit 204 as an inter-vehicle distance calculating unit. Based on the data of the road gradient and the inter-vehicle distance and the vehicle speed of the host vehicle output from the vehicle speed sensor 206, the preset control is performed. A vehicle speed control unit 207 for outputting a control parameter on the basis of the program, the vehicle 210
The throttle actuator 208 and the brake actuator 209, which control the throttle and the brake, perform acceleration / deceleration control of the vehicle.

The image processing device 203 and the arithmetic processing device 204 constitute an environment recognition unit 202, and a vehicle speed sensor 206, a vehicle speed control unit 207, a throttle actuator 208 and a brake actuator 2 are provided.
The vehicle control unit 205 as a vehicle speed control unit is constituted by 09.

The operation of the above configuration will be described. First, the road coordinate system and the screen coordinate system will be described with reference to FIG. FIG. 3A shows a road coordinate system XYZ and a plane coordinate system xy of the image pickup screen. FIG.
In (a), the road coordinate system is projected onto the plane coordinate system as in the following equation. That is, x = −f · X / Z (1) y = −f · Y / Z (2) Here, f represents the focal length of the CCD camera 201 (imaging unit CL1), and h represents the height of the mounting position of the CCD camera 201.

Therefore, if the lane width of the road ahead is W, the lane width w on the screen is w = f · W / Z (3). Furthermore, the relationship between the lane width w on the screen and its y coordinate can be expressed as w = − (W / Y) y (4) from the above equations (2) and (3).

Next, the relationship between the above equation (4) and the condition of the road will be described. 4 to 6 are explanatory views showing the scenery in front of the vehicle on a straight road, FIG. 4 is a flat road, FIG. 5 is an uphill road,
FIG. 6 shows downhill roads, respectively. In addition, FIG.
4 is a graph showing the relationship between the lane width w and the y coordinate in FIGS. 4 to 6 above.

First, in the case of a flat straight road as shown in FIG. 4, since the height of the road surface is constant in the above equation (4),
As shown in (a) flat road of (a), it becomes a linear type. Further, when the traveling road is an uphill slope, the lane marker of the forward landscape is photographed as shown in FIG. 5, so the above equation (4) approaches the upper end of the screen as shown in the uphill slope of (b) in FIG. Therefore, the value becomes larger than that on a flat road, and the coordinates of the vanishing point shift to the upper part of the screen.

Further, when the traveling road is a downhill, the lane marker of the forward scenery is photographed as shown in FIG. 6, so the above equation (4) is displayed at the upper end of the screen as shown in (c) downhill of FIG. The value becomes smaller than that on a flat road as the value approaches, and the coordinates of the vanishing point move to the bottom of the screen. From the above, it is possible to know the outline of the road gradient in front of the host vehicle.

Further, if the focal length f of the CCD camera 201 and the height h of the mounting position of the CCD camera 201 and the actual lane width W of the traveling path shown in FIG. The width w on the screen of the lane width of the front distance Z of the vehicle can be calculated from the equation (3). That is, as shown in FIG. 3B, the focal length f and the measurement point A
If the actual lane width W of the vehicle is known, the actual lane width W from the lane width on the screen at the measurement point A to the lens center of the CCD camera 201 from the equation (3) Z _A (distance Z corresponding to the measurement point A ) Can be calculated, and the actual height Y _A at that position (height Y corresponding to the measurement point A) can be obtained from the y coordinate on the screen at that position by the equation (4 ′). _{w = - (W / Y A} ) y ‥‥‥ (4 ')

Further, as is clear from FIG. 3 (b),
If the height h of CCD camera 201 is known and can be height Y ₀ of the road surface of the position which the own vehicle is currently calculated by (h-Y _A).

FIG. 8 is an explanatory view showing an example of a front view when a front vehicle is photographed. 801 is a front vehicle.
02 is the y coordinate of the lowermost end of the forward vehicle 801. In the figure, when a vehicle 801 in front of the vehicle lane is detected, the y-coordinate 802 of the bottom end of the vehicle features such as the bumper and the shadow projected on the road surface is used as a parameter indicating the position.
Is detected as the position of the vehicle ahead. Based on this value, the distance between the host vehicle 201 and the preceding vehicle 801 can be calculated from the relationship between the y coordinate on the screen calculated in the previous stage and the lane width w.

Although detailed description is omitted, the shadow projected on the bumper or road surface of the vehicle ahead can be easily detected by using, for example, a lateral edge image. That is,
When the vehicle is detected by the image processing device (forward vehicle detection means) 203, the horizontal edge at the bottom of the vehicle width on the screen, which is about the width of the vehicle at the bottom, is detected, and its y coordinate is determined as the position of the vehicle ahead. And Also, if y-w is known, then FIG.
As shown in FIG. 5, since Z _A , Y _A , and Z ₀ are obtained, the actual inter-vehicle distance (the part of the road that is the “road gradient from the current position to the point A” in the figure) can be calculated.

Next, the calculation process will be described in detail. FIG. 9 is a flowchart showing an example of operation processing by the environment recognition unit 202 shown in FIG. When this process is started, first, the focal length f _{0 of the} lens, the actual road lane width W ₀ , the mounting position of the camera (CCD camera 201), and the mounting angle of the camera (CCD camera 201) are input (S901). . Then, the relationship between the distance Z in the traveling direction and the lane width w displayed on the screen, and the y-coordinate 802 at the lowermost end where the lane marker appears on the screen are calculated (S902).
Note that the image processing device 203 of the environment recognition unit 202 is supposed to perform moving image processing, and therefore, “start of processing” here.
Is defined as a time point when the input of the screen to be processed this time is completed in the image processing apparatus 203.

In step 902, the relationship between the distance Z from the host vehicle and the lane width w of the traveling road shown on the screen is calculated using the equation (3). Z = f ₀ · W ₀ / w (5) Next, the bottom y coordinate y _{m of the} lane marker displayed on the screen.
To calculate. Z ₀ , where the lane width w is the number of pixels x _{m in} the x direction of the screen, is Z ₀ = f ₀ · W ₀ / x _m ··· (6) This position is displayed on the screen from the above formula (5). the value y _m y coordinate of the point, and the height of the mounting position of the camera and H _0, is determined as equation _{(2), y m = -f 0 · H} 0 / Z 0 ‥‥‥ (7) .

[0030] In the above, strictly using the height y ₀ of the road surface at the position of the distance Z ₀ is the value of Y but,
Since y _m is what gives the coordinates begin to detect the lane width w on the screen need not be very precise value. Therefore, the above equation (7) can be sufficiently dealt with.

The CCD camera 201 (imaging means CL
When the optical axis of 1) is inclined at an angle θ relative to the ground, as shown in FIG. 10, the value Z ₀ of the apparent Z ₀ 'is represented by the following formula (8). That is, Z ₀ '= H ₀ tan {tan ^-1 (H ₀ / Z ₀ ) + θ} (8). Therefore, instead of Z _{0 in} the equation (7), Z
By using ₀ ', y _m can be obtained when the CCD camera 201 has an elevation angle or a depression angle.

Next, after performing the above calculation processing, the CCD
An image is captured from the camera 201 (S903) and image processing is executed. At this time, first, preprocessing such as edge extraction is executed on the entire screen in order to make it easier to find the lane marker and the preceding vehicle on the screen (S904).

Next, the lane width on the screen for each scanning line is detected (S905). As a method of detecting the lane width in step 905, for example, as shown in FIG. 11, attention is paid to one scanning line of the screen subjected to the edge extraction processing. On a highway or the like, since the lane marker is a white line drawn on the same road surface, the state where the density value changes is very similar in the part where the lane marker is photographed. Therefore,
The lane width is calculated by comparing the installation condition of the CCD camera 201 or the state of the density change near the position of the lane marker, which is calculated from the same processing with the scanning lines in the vicinity, and detecting the position where the lane marker is photographed. . After that, this scanning is sequentially executed from the scanning line at the lower end where the lane marker is photographed.

However, when the lane marker is a broken line as shown in FIG. 4, the lane width cannot be detected because there is no lane marker in the scanning line of the broken line. In such a case, the data becomes larger than the lane width. Therefore, the lane width is obtained by interpolating the data of the uninterrupted portion of the lane markers before and after the lane marker without using the data of the discontinuous portion of the lane marker. Also, FIG.
Although it is not described in the flow chart shown in Fig. 2, if the lane width is detected every other line or every other line, and the process is performed to interpolate between them, the processing time is further shortened. Can be realized.

Next, when the lane width is detected in step 905, the relationship between the y coordinate on the screen and the lane width w at that position as shown in FIG. 7 is calculated (S906). After that, the distance Z in the traveling direction of the position is obtained from the value of the lane width w of each point on the graph showing the relationship using the equation (5), and the following equation (9) is used from the lane width w and the y coordinate. , The height Y _{0 of the} position (see FIG. 3B) is calculated, and the traveling road gradient is calculated (S907). Y ₀ = h + (W ₀ / w) y (9) Further, at this time, the environment recognition unit 202 to the vehicle control unit 20.
The road gradient is output to 5 as data. The vehicle control unit 205 can use this data (travel road gradient) for processing such as lamp light distribution control.

The distance and height in the traveling direction of each point on the graph shown in FIG. 7 are obtained by the above calculation formula, and as shown in FIG. 12, the state of the road gradient, that is, (a) flat road, It is possible to calculate each gradient of (b) an uphill road and (c) a downhill road.

Next, after calculating the traveling road gradient in step 907, it is judged whether or not there is a vehicle ahead in the traveling lane of the own vehicle (S908). A known technique (for example, Japanese Patent Laid-Open No. 3-2
No. 73500), the description is omitted.

At this time, when it is determined that there is no vehicle ahead, the process returns to step 903 and the same processing is repeatedly executed. On the other hand, when it is determined that there is a vehicle ahead, the process proceeds to the next step, and the position of the vehicle on the screen (the y coordinate of the lowermost end) is detected (S909),
The inter-vehicle distance to the preceding vehicle is calculated (S910), the process returns to step 903 and the same process is repeated.
The process of steps 903 to 910 is about 33 m.
It is executed every s.

Further, the calculation processing of the inter-vehicle distance to the preceding vehicle will be described in detail. In the method of detecting the front vehicle, for example, the area of the vehicle traveling lane on the screen is limited by the detection of the lane width in the preceding stage, and therefore the front vehicle is reflected in a portion including many edge components in the area. It is determined to be a region, and the y coordinate of its lower end is obtained. After that, from the obtained y coordinate and the lane width w at this position, the distance and height in the traveling direction in the road coordinate system of the position where the vehicle is reflected can be known. )
It can be calculated from the formula. That is,

[0040]

[Equation 1] Calculate from From the above, the inter-vehicle distance to the preceding vehicle can be calculated by image processing.

By the way, the actual running path is shown in FIG.
In most cases, it is a curved road rather than a straight road, as shown in. In such a case, the position of the vanishing point coordinates does not change, but the lane width w becomes larger as compared to the case of a straight road as the vanishing point becomes closer. This occurs because the lane width at the far side of the curved road is viewed obliquely as shown in FIG.

Therefore, for example, in the case of a screen imaged by the image pickup means CL1 having a standard focal length, the range up to about 100 m in front of the own vehicle is within the range applicable to the present invention. When the present invention is applied to a highway, the minimum radius of curvature of a curved road is about 300 m. The lane width 100 m ahead of the curved road that is curved with a radius of curvature of 300 m and the lane width of the traveling road is 3.5 m is about 3.7 m, which is about 6% wider.

In such a case, the lane width w as shown in FIG.
₁ is imaged at a position clearly shifted to the right or left from the center of the screen. Therefore, when the road is a curved road and an image is taken at a position where the lane width deviates from the center of the screen, the value of the lane width can be corrected. Also, in the case of a curved road with a small curvature, the image is captured at a position that does not deviate much from the center of the screen, but the error in the apparent lane width is also small. Therefore, the present invention can be applied to a curved road.

FIG. 15 shows a vehicle speed control unit 207 in FIG.
3 is a flowchart showing an example of the operation processing of FIG. In the figure, when this process is started, first, the vehicle speed sensor 206
When the vehicle speed data obtained from the above and the road gradient data obtained from the calculation processing unit 204 are fetched (S1501), the inter-vehicle distance data obtained from the calculation processing unit 204 is also fetched (S1502), and a forward vehicle exists from the data. Then, the safe inter-vehicle distance to the vehicle and the deceleration control amount are calculated (S1503), and the calculated safe inter-vehicle distance and the inter-vehicle distance are compared.

The safe inter-vehicle distance and the deceleration control amount can be calculated, for example, using the equation (2).

[0046]

[Equation 2] The deceleration amount is set to, for example, a deceleration amount to the extent that a person in the vehicle feels “a little sudden braking”, and the brake actuator 209 is set so that the deceleration amount is set even on a slope road.
By controlling, the above equation can be established.

That is, it is determined whether or not the inter-vehicle distance is less than or equal to the safe inter-vehicle distance (S1504). At this time, when it is determined that the inter-vehicle distance becomes shorter than the safe inter-vehicle distance, the vehicle speed deceleration control is executed (S1505), and the process returns to step 1501. Also, when it is determined that the inter-vehicle distance is equal to or greater than the safe inter-vehicle distance, the process returns to step 1501 and the same processing is repeated.

By executing the deceleration control in this way, it is possible to realize vehicle control that prevents the occurrence of a rear-end collision accident. Also, regarding the control amount, when the forward vehicle is on the uphill side from the host vehicle based on the road gradient, a deceleration control amount smaller than that on the flat road is generated.
On the other hand, when the vehicle ahead is on a lower slope than the host vehicle, appropriate vehicle control can be realized by controlling so as to generate a deceleration control amount larger than that on a flat road.

FIG. 16 is a flowchart showing the processing operation of the vehicle speed control unit 207 according to another embodiment. This processing example realizes constant speed traveling in autonomous traveling of the vehicle. In the figure, when this process is started, first, constant speed running (holding the throttle opening) is started (S16).
01), the road gradient data is fetched from the arithmetic processing unit 204 (S1602). Further, the own vehicle speed data and the inter-vehicle distance data obtained from the arithmetic processing unit 204 are fetched (S
1603), calculates the safe inter-vehicle distance to the vehicle in front (S)
1604). Then, the inter-vehicle distance is compared with the safe inter-vehicle distance calculated in the previous stage. That is, it is determined whether or not the inter-vehicle distance is less than or equal to the safe inter-vehicle distance (S1605). At this time, when it is determined that the inter-vehicle distance becomes shorter than the safe inter-vehicle distance, the constant speed traveling is canceled (S1611), the deceleration control is started (S1612), and the driver is instructed to cancel the constant speed traveling. Notify (S1613).

On the other hand, when it is determined in step 1605 that the inter-vehicle distance is greater than the safe inter-vehicle distance, tan θ of the future road gradient is calculated from the road gradient data (S1606), and it is determined that tan θ has become larger than a certain value a. At this time (in the case of an uphill slope), (S160
7) Then, the throttle opening is increased (S1608) so that the vehicle speed is controlled so as not to drop even when the vehicle enters an uphill slope.

In step 1607, t
When it is determined that an? Is less than or equal to a certain value a, it is further determined whether tan? Is less than or equal to a certain value-a (S1609). At this time, when it is determined that tan θ is smaller than a certain value −a (in the case of a downhill), the throttle opening is reduced (S1610), and control is performed so that the vehicle speed does not increase even when the vehicle enters the downhill. As described above, safe constant speed traveling can be realized.

[0052]

As described above, the running road gradient calculating device (claim 1) according to the present invention is capable of calculating the scenery in front of the vehicle.
The lane width detection means CL3 extracts left and right lane markers indicating the own vehicle traveling lane from the imaged road condition image to detect the lane width of the own vehicle traveling lane on the screen, Road gradient calculating means C from the detected value
Since the road gradient is calculated by L4, the calculation of the road gradient can be realized by a simple process.

Further, the traveling road gradient calculating device according to the present invention (claim 2) is one image pickup means CL for the scenery in front of the vehicle.
The lane width of the vehicle traveling lane on the screen is detected by extracting the left and right lane markers indicating the vehicle traveling lane by the lane width detection means CL3 from the photographed road condition screen, from the detected value. The road gradient calculating means CL4 calculates the traveling road gradient, the front vehicle detecting means CL5 detects the front vehicle from the photographed road condition screen, and the inter-vehicle distance detecting means CL6 detects the lane width from the lane width at the lower end position of the front vehicle. Therefore, it is possible to realize the calculation of the traveling road gradient by a simple process and to calculate the inter-vehicle distance with high accuracy in consideration of the traveling road gradient from the lane width.

Further, the vehicle speed control device according to the present invention (claim 3) photographs the scenery in front of the vehicle by means of one image pickup means CL1 and the vehicle travels by the lane width detection means CL3 from the photographed road condition screen. The left and right lane markers indicating the lanes are extracted to detect the lane width of the own vehicle traveling lane on the screen, the road gradient calculating means CL4 calculates the traveling road gradient from the detected value, and the forward vehicle detecting means CL5 described above. The front vehicle is detected from the photographed road condition screen, the inter-vehicle distance detection means CL6 calculates the inter-vehicle distance from the lane width at the lower end position of the front vehicle, and the vehicle speed control means CL7
Based on the calculation results obtained from the inter-vehicle distance calculation means CL6 and the road gradient calculation means CL4, the vehicle speed of the host vehicle is controlled, so that the calculation of the traveling road gradient can be realized by a simple process, and the lane width to the traveling road can be calculated. It is possible to calculate the inter-vehicle distance with high accuracy in consideration of the gradient of, and to control the vehicle speed of the own vehicle in consideration of the inter-vehicle distance and the road gradient.

In the traveling road gradient calculating device (claim 4) of the present invention, the road gradient calculating means CL4 calculates the lane width on the screen, and the calculated lane width and the lane width are displayed on the screen. Since the road slope is calculated based on the above positional relationship, more accurate road slope calculation can be realized.

In the traveling road gradient calculating device according to the present invention (claim 5), the inter-vehicle distance calculating means CL6 detects the detected position (y coordinate) on the screen of the preceding vehicle and the lane width corresponding to the detected position. Since the inter-vehicle distance is calculated based on, the more accurate inter-vehicle distance can be detected.

[Brief description of drawings]

FIG. 1 is a block diagram (corresponding to a claim) showing a basic configuration of a traveling road gradient calculating device and a vehicle speed control device according to the present invention.

FIG. 2 is a block diagram showing a system configuration of a traveling road gradient calculating device and a vehicle speed control device according to the present invention.

FIG. 3 is an explanatory diagram showing a road coordinate system and a screen coordinate system according to the present invention.

FIG. 4 is an explanatory view showing a scenery in front of the vehicle on a straight road (flat road) according to the present invention.

FIG. 5 is an explanatory view showing a scenery in front of the vehicle on a straight road (uphill road) according to the present invention.

FIG. 6 is an explanatory view showing a scenery in front of the vehicle on a straight road (downhill road) according to the present invention.

FIG. 7 is a graph showing the relationship between the lane width w and the y coordinate shown in FIGS. 4 to 6;

FIG. 8 is an explanatory diagram showing an example of a forward landscape when a front vehicle according to the present invention is photographed.

FIG. 9 is a flowchart showing an example of operation processing by the environment recognition unit according to the present invention.

FIG. 10 is an explanatory diagram for calculating an apparent Z ₀ when the imaging device according to the present invention has an elevation angle or a depression angle.

FIG. 11 is an explanatory diagram showing an example of a method of detecting a lane width on a traveling lane according to the present invention.

FIG. 12 is an explanatory diagram showing an example of a detected road gradient according to the present invention.

FIG. 13 is an explanatory view showing an example of a front landscape of a flat curved road according to the present invention.

FIG. 14 is an explanatory diagram showing an example of a curved road having a radius of curvature of 300 m according to the present invention.

FIG. 15 is a flowchart showing an example of processing operation of a vehicle speed control section according to the present invention.

FIG. 16 is a flowchart showing another processing operation example of the vehicle speed control section according to the present invention.

[Explanation of symbols]

 CL1 image pickup means CL2 image processing means CL3 lane width detection means CL4 road gradient calculation means CL5 front vehicle detection means CL6 headway distance calculation means CL7 vehicle speed control means 201 CCD camera 202 environment recognition section 203 image processing apparatus 204 arithmetic processing section 205 vehicle control section 206 vehicle speed sensor 207 vehicle speed control unit 210 vehicle

Claims (5)

[Claims] 1. An image pickup means for picking up an image of a road condition ahead of the host vehicle, an image processing part for extracting a lane marker or a feature of the vehicle from a road condition image picked up by the image pick-up part, and the image processing part. Lane width detecting means for detecting the lane width on the screen from the distance between lane markers at a predetermined position of the road situation image, and traveling from the lane width detected by the lane width detecting means and the position and angle of the image pickup means with respect to the road coordinate system. A road slope calculating device, comprising: a road slope calculating means for calculating a road slope. 2. An image pickup means for picking up an image of a road condition in front of the host vehicle, an image processing part for extracting a lane marker or a feature of the vehicle from a road condition image picked up by the image pick-up part, and the image processing part. Lane width detecting means for detecting the lane width on the screen from the distance between lane markers at a predetermined position of the road situation image, and traveling from the lane width detected by the lane width detecting means and the position and angle of the image pickup means with respect to the road coordinate system. Road gradient calculating means for calculating the gradient of the road, forward vehicle detecting means for detecting the presence of a forward vehicle from the road condition image, position of the forward vehicle on the screen detected by the forward vehicle detecting means, and the road gradient Roadway slope calculation, comprising: inter-vehicle distance calculation means for calculating a distance to a vehicle ahead from the roadway slope calculated by the calculation means apparatus. 3. An image pickup means for picking up a road condition ahead of the host vehicle, an image processing means for extracting a lane marker or a feature of the vehicle from a road condition image picked up by the image pick-up device, and the image processing means. Lane width detecting means for detecting the lane width on the screen from the distance between lane markers at a predetermined position of the road situation image, and traveling from the lane width detected by the lane width detecting means and the position and angle of the image pickup means with respect to the road coordinate system. Road gradient calculating means for calculating the gradient of the road, forward vehicle detecting means for detecting the presence of a forward vehicle from the road condition image, position of the forward vehicle on the screen detected by the forward vehicle detecting means, and the road gradient An inter-vehicle distance calculating means for calculating a distance to a vehicle ahead from the traveling road gradient calculated by the calculating means, the inter-vehicle distance calculating means and the road gradient A vehicle speed control device comprising: a vehicle speed control means for controlling a vehicle speed of the own vehicle based on a calculation result obtained from the calculation means. 4. The road gradient calculating means calculates the road gradient based on the lane width detected by the lane width detecting means and the positional relationship of the lane width on the road condition image. The roadway gradient calculating device according to claim 1, 2, or 3. 5. The inter-vehicle distance calculating means calculates the inter-vehicle distance based on the detected position (y coordinate) on the screen of the vehicle ahead and the lane width corresponding to the detected position. Item 2. The roadway slope calculating device according to item 2 or 3.