JP2900737B2 - Inter-vehicle distance detection device - Google Patents

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an inter-vehicle distance detecting apparatus using both a camera and a millimeter wave radar.

[0002]

2. Description of the Related Art In recent years, various devices for reducing the burden on a driver have been mounted on a vehicle, and among them, an alarm is issued or a warning is issued based on a distance between the vehicle and a preceding vehicle. There are devices for performing deceleration control and the like. When using such a device, it is very important to accurately detect the inter-vehicle distance. This is because if the detection of the inter-vehicle distance is not accurate, the control based on this will not be appropriate.

In view of the above, various types of inter-vehicle distance detecting devices have been conventionally proposed, and as a distance measuring means, there is a device using a camera, a laser, an ultrasonic wave, a radar, or the like. For example,
Japanese Unexamined Patent Publication No. 4-155221 discloses a camera equipped with both a camera and a laser, determines a preceding vehicle as a target object from image data obtained by the camera, directs the laser in the direction of the preceding vehicle, and receives reflected light. Thus, an apparatus for measuring the distance between vehicles is shown. According to this apparatus, highly accurate inter-vehicle distance detection can be performed by using the advantages of both a laser having good distance measurement performance but a narrow field of view and a camera having a wide field of view and low stability of distance measurement.

[0004]

However, in this conventional apparatus, when the external environment is deteriorated due to rain, fog, etc., the image obtained by the camera deteriorates, and it becomes impossible to sufficiently detect the preceding vehicle. There is a problem that the control of the direction of the laser beam cannot be performed. Also,
In the case of rain, fog, and the like, the function of distance measurement by a laser is also reduced.

On the other hand, a millimeter wave radar is being studied as a distance measuring means. The millimeter-wave radar is relatively insensitive to rain, fog, and the like, and can accurately detect an inter-vehicle distance regardless of external environmental conditions. However, like the laser, the millimeter-wave radar has a narrow field of view, so there is a high probability that a preceding vehicle cannot be caught at an intersection or a curve, and there is a problem that an appropriate inter-vehicle distance cannot be detected depending on road conditions. .

[0006] The present invention has been made to solve the above problems, and has been made under various conditions.
An object of the present invention is to provide an inter-vehicle distance detection device capable of performing suitable inter-vehicle distance detection.

[0007]

SUMMARY OF THE INVENTION The present invention relates to an inter-vehicle distance detecting apparatus for detecting inter-vehicle distance using detection results of a camera and a millimeter wave radar, which detects environmental conditions such as rain and fog which influence the view of the camera. Environmental state detecting means, a road state recognizing means for recognizing a road state of a road on which a vehicle is running, such as a curve or an intersection, and a camera reliability based on the environmental state and the state of image data obtained by the camera. A camera reliability calculating means for calculating, a millimeter-wave radar reliability calculating means for calculating a millimeter-wave radar reliability for calculating a millimeter-wave radar reliability from the road condition and a detection value of the millimeter-wave radar, and both calculating means. Selection decision means for comparing the reliability calculated in the step (a), and deciding whether to detect the inter-vehicle distance based on the camera or the millimeter wave radar according to the comparison result. It is characterized in.

In the case where the millimeter wave radar is selected by the selection determining means and the reliability of the camera is equal to or more than a predetermined value, the inter-vehicle distance and the millimeter wave obtained from the detection result of the camera are obtained. From the inter-vehicle distance obtained from the radar detection result, a correction value for the inter-vehicle distance obtained from the detection result of the camera is calculated, and the inter-vehicle distance obtained by the camera is corrected by the obtained correction value. It is characterized by detecting an inter-vehicle distance in a direction that cannot be obtained.

[0009]

According to the present invention, the reliability of the camera is compared with the reliability of the millimeter wave radar, and the higher reliability is used to detect the inter-vehicle distance. Therefore, accurate inter-vehicle distance detection can always be performed according to the situation of the vehicle. In particular, effective inter-vehicle distance detection compensates for the disadvantages of both cameras, which are susceptible to rain and fog, but have a wide field of view, and millimeter-wave radars, which have a narrow field of view and are difficult to detect the inter-vehicle distance at curves and intersections It can be performed.

When the inter-vehicle distance is detected by the millimeter wave radar, if the reliability of the camera is equal to or greater than a predetermined value, a correction value for detecting the inter-vehicle distance by the camera is determined based on the detected value of the millimeter wave radar. And calculate. Then, by correcting the inter-vehicle distance obtained by the camera using the correction value, the inter-vehicle distance to a vehicle existing in a direction that cannot be detected by the millimeter wave radar can be accurately obtained.

[0011]

Embodiments of the present invention will be described below with reference to the drawings. FIG. 1 is a block diagram showing the overall configuration of the embodiment. The long-distance camera 10 is a television camera that obtains a relatively distant image (for example, about 100 m ahead) ahead of the vehicle. The long-distance camera 10 includes, for example, a pair of CCD cameras, and obtains two image data for substantially the same target. This long distance camera 10
Is supplied to the image processing ECU 12. The image processing ECU 12 processes the input image to generate image data for each frame, and recognizes a preceding vehicle from the data. For example, a long-distance camera 10
By extracting a change in luminance from the image data, the outline of the vehicle is recognized, and the position and direction of the preceding vehicle are detected.

The image processing ECU 12 detects an inter-vehicle distance from data of a preceding vehicle from an image signal from the long-distance camera 10. That is, an inter-vehicle distance is detected by triangulation or the like using images from two CCD cameras. Further, the image processing ECU 12 determines an optimal aperture and shutter speed from the brightness of the entire image, the movement of each frame of image data, and the like, and controls the aperture and shutter speed of the long-distance camera 10. Then, data on various detection results detected by the image processing ECU 12 in this manner is supplied to the environment recognition ECU 14.

The short-range camera 20 is a pair of CCD cameras for detecting a guide line (white line) existing on both sides near the vehicle, and an image signal obtained by the short-range camera 20 is subjected to image processing. It is supplied to the ECU 12. The image processing ECU 12 is connected to the short distance camera 20.
The white lines on both sides of the vehicle are recognized from the image obtained by the above, and the posture of the vehicle is detected from this. The image processing ECU 2
Reference numeral 2 controls the aperture and shutter speed of the short distance camera 20. The data detected in this way is also supplied to the environment recognition ECU 14.

Further, the direction of the visual field of the long-distance camera 10 and the short-distance camera 20 is determined by the image processing ECU 12 in accordance with the steer mode sent from the environment recognition ECU 14. Then, the steer controllers 26, 2 which operate according to the signal regarding the determined viewing direction are provided.
Reference numeral 8 controls the viewing direction (steer) of the cameras 10 and 20.

Here, there are two steering modes in the environment recognition ECU 14, a mode 1 for normal driving and a mode 2 for turning right and left. That is, during normal running (during road running), the camera steer mode is set to mode 1, and the image processing ECU 12 controls the steer of the cameras 10 and 20 so that both the perspective cameras 10 and 20 have their own lane at the center of the image. Control. When there is no white line, the steer angle of the camera must be determined in consideration of other data. Therefore, the camera steer angle for the direction of the own lane is always finally determined by the environment recognition ECU 14.

When turning right or left within an intersection, the camera steer mode is set to mode 2, and the environment recognizing ECU 14 determines the steer direction of the cameras 10 and 20. That is, when making a right or left turn, the long distance camera 10 is directed toward the oncoming vehicle (forward), and the short distance camera 20 is directed in the traveling direction. This is because it is important to recognize an oncoming vehicle or the like coming from the front when turning right or left.

FIG. 2 shows a flowchart of processing in the image processing ECU 12. Image processing ECU 12
First, the camera steer mode is received from the environment recognition ECU 14 (S101). Next, according to the steer mode and the steer direction determined by the previous process,
The steering of the cameras 10 and 20 is controlled (S102). Then, a traveling lane and a road are detected from the image data obtained by the cameras 10 and 20 (S103), and a preceding vehicle is recognized (S104). In this way, when the predetermined detection is completed, the detection result is sent to the environment recognition ECU.
14 (S105), and returns to S101.

The millimeter wave radar 30 transmits a millimeter wave to the front of the vehicle, receives the millimeter wave reflected from the front, and recognizes the state of the front from the state of transmission and reception signals. The signal from the millimeter wave radar 30 is transmitted to the radar ECU 3
2 is supplied. Then, the radar ECU 32 detects the inter-vehicle distance to the preceding vehicle and the relative speed based on the data obtained by the millimeter wave radar 30. The detection result is supplied to the environment recognition ECU 14.

The environment recognition ECU 14 estimates the direction of the preceding vehicle from the direction of the preceding vehicle obtained from the image from the long-distance camera 10 and the vehicle attitude obtained from the data from the short-distance camera 20. , The directivity direction (steer) of the millimeter wave radar 30 is determined. The signal about the steering is supplied to the millimeter wave radar 30 via the steering controller 34, and the steering of the millimeter wave radar is controlled by the signal from the steering controller 34.

FIG. 3 is a flowchart showing the operation of the radar ECU 32. First, the supplied millimeter wave radar 30
The distance between vehicles and the relative speed are detected from the detection result (S
201). Individually, the relative speed is calculated from the detected change state (derivative) of the following distance. Then, the obtained data is transmitted to the environment recognition ECU 14 (S202).

Further, the GPS antenna 40 receives a predetermined signal from an artificial satellite (usually four satellites),
It is supplied to the receiver 42. The GPS receiver 42 specifies the absolute position (latitude, longitude, altitude) of the vehicle from the obtained reception signal. FIG. 4 is a flowchart showing the operation of the GPS receiver 42. First, the current position, altitude, and the like are detected from the received signal (S301), and the detected data is transmitted to the environment recognition ECU 14 (S302).

The beacon antenna 50 receives a signal from a beacon provided at a predetermined position on the road. A beacon receiver 52 recognizes information on the current position from the received signal and supplies the information to the environment recognition ECU 14. I do. FIG.
Shows a processing flow of the beacon receiver 52. First, it is determined whether a beacon has passed or not (S401). If a beacon has passed, a signal about the current position is received (S402) and supplied to the environment recognition ECU 14 (S403). Here, the information supplied from the beacon includes, in addition to the position information of the beacon, the signal state of the intersection, the position of another vehicle trying to enter this intersection, the road, the lane, and the speed at which the other vehicle approaches. There is information of. The information about the other vehicle is recognized by the other vehicle transmitting information to a receiver attached to the beacon or by providing a detector near the intersection and detecting the information.

Further, the environment recognition ECU 14 is supplied with signals from a vehicle speed sensor, a steering angle sensor, a wiper switch, and the like provided in the vehicle.

The environment recognition ECU 14 includes a map data storage unit 70, a road model storage unit 72, a camera reliability determination unit 74, and a millimeter wave radar reliability determination unit 76.

The camera reliability determination section 74 first determines whether or not the external environment such as rain or fog is suitable for the long distance camera 10 to recognize the preceding vehicle. The degree Rc1 is calculated. For example, the reliability Rc1 is determined according to the intensity of rain. Here, the intensity of rain may be determined based on the driving state of the wiper. That is, when the wiper is driven at a high speed, it is considered that the rain is strong, and it is not suitable for the long distance camera 10 to recognize the preceding vehicle. On the other hand, if the wiper switch is OFF, it can be determined that it is not raining. The fog can be recognized by whether the fog lamp is turned on. The difference between the luminance of the tail lamp inside and outside of the preceding vehicle, that is, the difference between the luminance of the location where the tail lamp is being photographed and the luminance of the surrounding area is represented by the number of gradations of luminance (for example, 25 bits if the luminance is expressed by 8 bits).
6), reliability Rc1 = level difference / 256 reliability can be calculated.

Next, the camera reliability determination section 74 determines the camera reliability Rc2 based on the image data obtained by the camera 10. For example, the reliability is determined as follows from the number of edges when the image processing ECU 12 recognizes the vehicle. That is, when the brightness of the image data obtained by photographing the vehicle is detected, there are various edges (points where the change in brightness is equal to or more than a predetermined value) such as the contour of the vehicle and the window. Therefore, the horizontal edge of the vehicle is detected from the change state of the luminance data in the vertical direction, and the reliability is calculated from the obtained number of edges by the following equation.

Reliability Rc2 = Horizontal Edge Number / Theoretical Maximum Edge Number Here, the theoretical maximum edge number is the theoretical detectable edge number determined from the shape of the vehicle.

In the case of nighttime, the reliability may be calculated from the difference between the brightness of the inside and outside of the tail lamp of the preceding vehicle as in the case of the above-mentioned fog.

Next, the millimeter wave radar reliability calculator 74 calculates
The reliability of the millimeter wave radar is calculated from data such as the complexity of the road, that is, the curve radius R, the speed limit, the road width, the type of road such as a general highway, and whether or not the vehicle is within an intersection. That is, the map data storage unit 70 stores the road shape, the road edge shape,
Data such as road height, intersection position, shape, pedestrian crossing position, stop line position, presence / absence of signal, presence / absence of temporary stop, etc. are stored. Accordingly, the environment recognition ECU 14 determines the position of the host vehicle from both the map data stored in the map data storage unit 70 and the absolute position of the host vehicle based on the signals supplied from the GPS receiver 40 and the beacon receiver 52. You can know the situation. Then, the millimeter wave radar reliability calculation unit 74
Calculates the reliability of the millimeter wave radar 30 from the road environment in which the own vehicle runs. For example, when the radius of the curve is small, the speed limit is small, and the road width is small, or the reliability of the millimeter wave radar is low on a general road or an intersection. Therefore, depending on the situation of each of these factors, the reliability R for the driving environment
Calculate m1.

Further, the reliability Rm2 of the millimeter wave radar is calculated according to the detection value of the millimeter wave radar 30. For this reason, first, a map of the distance and the reception level using the vehicle width as a parameter is created in advance by a static test. In other words, if the vehicle width is constant, the reception intensity starts to decrease when the distance exceeds a predetermined value. In addition, the greater the vehicle width, the greater the distance at which the reception intensity starts to decrease. Therefore,
Using the vehicle width detected in the image, the maximum reception level SR0 is obtained from the map, and this is compared with the actually obtained reception level to calculate the reliability. That is, the reliability Rm2 of the millimeter wave radar is calculated by the following equation.

The reliability Rm2 = the actual reception level / SR0.
0 is connected, and the vehicle control ECU 80 performs alarm generation, acceleration / deceleration control, and the like based on the inter-vehicle distance and the relative speed (detected by a change in the inter-vehicle distance with time) obtained by the environment recognition ECU 14.

Next, the overall operation of the embodiment will be described with reference to FIG. With the operation of the system (for example, turning on the ignition switch of the vehicle), the environment recognition E
The CU 14 is an image processing ECU 12, a millimeter wave radar ECU
32, an initialization process such as an operation check of the GPS receiver 42 and the beacon receiver 52 is performed (S1). Further, the vehicle position immediately before the previous ignition switch is turned off is set to the estimated current position on the map.
Next, according to a signal from the GPS receiver 42, the current position,
An altitude, a direction, and the like are detected (S2). GPS receiver 42
Detects the three-dimensional position and azimuth of the own vehicle about every one second, and transmits data to the environment recognition ECU 14. The environment recognition ECU 14 selects a candidate for a traveling road based on the data from the GPS receiver 42 and the data from the map data storage unit 70. Then, the traveling locus of the vehicle is calculated from data such as the steering angle, the yaw rate, and the lateral acceleration, and the traveling road is specified (S3). Also, by counting the vehicle speed pulse,
Estimate the position in the traveling direction on the road. The traveling locus refers to the history of the position data obtained by the GPS receiver 42.

Next, it is determined whether or not a beacon has passed based on a signal from the beacon receiver 52 (S4). If the beacon has passed, the current position is corrected based on data from the beacon (S5). . This is because the position identification based on the data from the beacon is the most accurate. Thereby, the position of the vehicle on the traveling road is specified, and the position in the traveling direction on the road estimated in S3 is corrected. In addition, at the time of position correction based on the data from the beacon, a correction coefficient for obtaining a traveling distance from a vehicle speed pulse is learned. Accordingly, the accuracy of specifying the position in the traveling direction on the road obtained from the vehicle speed pulse is improved.

Through such processing, the position of the host vehicle on the road (the host vehicle position) is determined.

The environment recognizing ECU 14 determines whether the vehicle is running normally or right or left based on the own vehicle position obtained as described above, and determines the camera steer mode (S6). Then, the determined camera steer mode is transferred to the image processing EC.
Send to U12. The image processing ECU 12 controls the steering of the long-distance camera 10 and the short-distance camera 20 in accordance with the type of the mode transmitted, and detects a road and a preceding vehicle from the obtained images (S7). ). That is, the white line is detected from the image obtained by the short-range camera 20, and the posture of the vehicle is detected. In addition, the long distance camera 10
The preceding vehicle is detected from the image obtained by the above. Then, the obtained data is sent to the environment recognition ECU 14. In addition, the image processing ECU 12 detects the inter-vehicle distance, direction, vehicle width, and the like from the recognized preceding vehicle to the preceding vehicle, in addition to the lateral deviation with respect to the road and the yaw angle. Further, the detection values of the yaw rate sensor and the lateral acceleration sensor are used. Then, the movement amount of the own vehicle is calculated from the obtained yaw rate and lateral acceleration (S8). Then, the moving amount obtained in S8 is added to the own vehicle posture obtained in the previous process to obtain the own vehicle posture, and thereby the own vehicle posture obtained in S7 is corrected (S9). By the processing so far, the lateral deviation, the yaw angle, and the position in the traveling direction of the own vehicle with respect to the traveling path are determined.

Next, the camera reliability Rc is calculated (S
10). The calculation of the reliability is performed based on the above-described conditions such as rain and fog, and detection of edges in an image. Then, it is determined whether the reliability is high (S11),
If the reliability is high, the risk is calculated (S1).
2). This risk is calculated by, for example, risk = 1 / time of collision with each vehicle. Then, based on the obtained degree of danger, the vehicle with the highest degree of danger is selected, and the steer angle for causing the selected vehicle to steer the millimeter wave is determined. When the value of the degree of danger is small and the change in the value is small, it is determined that the state is stable, and the inter-vehicle distance is measured using millimeter waves for vehicles on both adjacent lanes at appropriate intervals. further,
When there is no vehicle, the steer angle is determined so that the own vehicle lane and the lanes on both sides are alternately steered with millimeter waves at appropriate intervals.

On the other hand, if the reliability of the camera is low in S11, the steer angle of the millimeter wave is determined based on the attitude of the vehicle and the shape of the road obtained from the map data (S1).
3). Then, as described above, the steer of the millimeter wave is controlled in accordance with the steer angle determined in S12 and S13 (S14). Then, the millimeter-wave radar ECU 32 detects the inter-vehicle distance to the preceding vehicle, the relative speed, and the reception level of the millimeter wave (S15). Then, the detected data is sent to the environment recognition ECU 14. Environmental awareness E
The CU 14 calculates the reliability of the millimeter wave from the obtained millimeter wave data and the traveling environment of the own vehicle (S16). Then, the reliability by the millimeter wave and the reliability by the camera (S10
And those obtained in S16) are compared (S1
7), the higher reliability is selected (S18). That is, if the reliability of the camera is higher, the inter-vehicle distance obtained by the camera is adopted (S18), and the inter-vehicle distance to the preceding vehicle is used. If the reliability of the millimeter wave is higher, the inter-vehicle distance obtained by the millimeter wave Is adopted (S19).

As described above, according to the present embodiment, both the inter-vehicle distance detection by the camera and the inter-vehicle distance detection by the millimeter wave are always performed, and the inter-vehicle distance is detected using the data having higher reliability. Therefore, accurate inter-vehicle distance detection can always be performed.

Next, additional processing when the reliability of the millimeter wave is high will be described with reference to FIG. That is, when the reliability of the millimeter wave after the processing of S19 is high, it is determined whether or not the reliability of the camera is equal to or more than a predetermined value (S21). If the camera reliability is equal to or greater than a predetermined value, the inter-vehicle distance detected by the millimeter wave is compared with the inter-vehicle distance to the millimeter-wave measurement vehicle detected by the camera. Then, by calculating the difference between them, a correction value of the following distance obtained by the camera is calculated (S
22). Then, the inter-vehicle distance of vehicles other than the millimeter-wave measurement vehicle obtained by the camera is corrected by the above-described correction value (S23). Then, the process returns to S2, including the case of No in S21.

Thus, the inter-vehicle distance obtained by the camera becomes more accurate. Then, the inter-vehicle distance with respect to the vehicle that could not be measured by the millimeter wave can also be obtained as being quite accurate.

[0041]

As described above, the inter-vehicle distance detecting apparatus according to the present invention has two inter-vehicle distance detecting means, that is, a camera and a millimeter wave radar, and uses data having higher reliability. Detect inter-vehicle distance. Therefore, an appropriate detecting means can be selected according to a change in the traveling situation, and accurate inter-vehicle distance detection can be performed.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating an overall configuration of an embodiment.

FIG. 2 is a flowchart illustrating an operation of an image processing ECU 12.

FIG. 3 is a flowchart illustrating an operation of a radar ECU 32;

FIG. 4 is a flowchart showing an operation of the GPS receiver 42.

FIG. 5 is a flowchart showing the operation of the beacon receiver 52.

FIG. 6 is a flowchart illustrating the operation of the embodiment.

FIG. 7 is a flowchart illustrating an additional operation example of the embodiment.

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 10 Long distance camera 14 Environment recognition ECU 20 Short distance camera 30 Millimeter wave radar 40 GPS receiver 50 Beacon receiver 70 Map data storage part 74 Camera reliability judgment part 76 Millimeter wave radar reliability judgment part 80 Alarm / control ECU

Continuation of the front page (56) References JP-A-64-79681 (JP, A) JP-A-3-115985 (JP, A) JP-A-58-92879 (JP, A) JP-A-58-109870 (JP) JP-A-3-165288 (JP, A) JP-A-4-276585 (JP, A) JP-A-64-26913 (JP, A) JP-A-63-67892 (JP, U) JP-A 60-573 (JP, U) Hikaru Hei 3-35490 (JP, U) (58) Fields investigated (Int. Cl. ⁶ , DB name) G01S 13/86 G01C 3/06 G01S 13/93 G08G 1 / 04 G01S 11/12

Claims (2)

(57) [Claims] 1. An inter-vehicle distance detecting apparatus for detecting an inter-vehicle distance by using detection results of a camera and a millimeter wave radar, wherein: an environmental state detecting means for detecting an environmental state such as rain and fog which influences a field of view of the camera; A road condition recognition means for recognizing a road condition of a road on which a vehicle such as an intersection is traveling; and a camera reliability calculation means for calculating a camera reliability from the environmental condition and a state of image data obtained by the camera. A millimeter-wave radar reliability calculating means for calculating the millimeter-wave radar reliability based on the road condition and the millimeter-wave radar detection value, and comparing the reliability calculated by the two calculating means. Selection determining means for determining whether to detect the inter-vehicle distance based on the camera or the millimeter-wave radar according to the comparison result. Distance detection device. 2. The inter-vehicle distance detecting apparatus according to claim 1, wherein the millimeter wave radar is selected by the selection determining means, and the reliability of the camera is equal to or more than a predetermined value. From the inter-vehicle distance obtained from the detection result of the vehicle and the inter-vehicle distance obtained from the detection result of the millimeter wave radar, a correction value for the inter-vehicle distance obtained from the detection result of the camera is calculated, and the correction value obtained by the camera is used. An inter-vehicle distance detection device that corrects the obtained inter-vehicle distance and detects an inter-vehicle distance in a direction that cannot be obtained by a millimeter wave radar.