JP2007278813A - Vehicle-position positioning device - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To solve the problem, wherein the actual position of own vehicle deviates from the position of own vehicle held by a car navigation device, according to the measurement of the position of own vehicle by a combination of autonomous navigation and map matching, using a gyro and a vehicle speed sensor. <P>SOLUTION: This device has a white line extraction means for extracting white lines from a photographed image; a means for determining the distance between own vehicle and the while line by processing the image; a distance change calculation means for calculating the change in the distance to the white line within a fixed time; and a mileage measuring means for measuring a mileage within a fixed time, and calculates a traveling vector of own vehicle by using the change of the distance to the white line and the mileage, and adds the traveling vector to the measured position of own vehicle, to thereby measure the position of own vehicle. Alternatively, the device has a means for acquiring the steering angle of a front wheel of own vehicle; a means for calculating the traveling direction of own vehicle in a fixed time, by using the mean value of the steering angle in the fixed time; and a means for measuring the mileage with a fixed time, and calculates the traveling vector of own vehicle, by using the traveling direction and the mileage. <P>COPYRIGHT: (C)2008,JPO&INPIT

Description

  The present invention relates to a positioning device mounted on a vehicle or the like.

  The locator system in a car navigation system has been mainly based on dead reckoning that uses the results obtained by determining the traveling direction with a gyro and the travel distance with a vehicle speed sensor. In addition, GPS has also been used to correct dead reckoning results. This is disclosed in Japanese Patent Application Laid-Open No. 61-116615.

  In dead reckoning, a reference point is first measured by GPS or the like, a traveling direction and a travel distance are obtained from the point, and used as a movement vector, and the movement vector is added to the reference position to calculate a current position. Further, the movement vector is obtained and added with the current position as the reference position. However, there is an error in the gyroscope and the vehicle speed sensor, and the error accumulates as the movement vector is added. Therefore, the GPS positioning result is adopted at a certain time point together with the GPS positioning result.

Japanese Patent Laid-Open No. 61-116615

  In the dead reckoning disclosed in Japanese Patent Laid-Open No. 61-116615, position errors accumulate due to errors in gyros and vehicle speed pulses. Even if the GPS reset is performed at a certain time, an error of about 10 m may occur in the GPS positioning result, and there is no guarantee that an accurate coordinate is required. With regard to gyros, the accuracy of angle detection is poor when it is installed in the current car navigation system, and it is difficult to distinguish it from straight travel when narrow-angle branching or changing lanes. For this reason, it is difficult to quickly and accurately determine which direction the branch has taken. Further, even if the lane change is frequently repeated, it is not known that the lane has been changed, and it is determined that the vehicle is running straight even if meandering, so that an error in the front-rear position occurs.

  In view of the above, there is a need for a technique for improving positioning accuracy without using a method using a sensor with low accuracy.

  White line extracting means for extracting a white line from the captured image, means for processing the image to determine the distance between the vehicle and the white line, and distance change calculating means for calculating a change in the distance between the white line within a predetermined time And a travel distance measuring means for measuring the travel distance within the predetermined time, calculating a travel vector of the host vehicle using the change in the distance from the white line and the travel distance, and the vehicle position measured last time The vehicle position is measured by adding the travel vector to the vehicle.

  Further, the means for processing the image to obtain the distance between the vehicle and the white line is the first to the first point corresponding to any one point included in the boundary line that bisects the image to the left and right. And a second distance from the first point to the second point corresponding to the first pixel found by scanning in the horizontal direction among the pixels included in the white line extracted by the white line extracting unit And the distance between the first point and the second point is obtained based on the first distance and the second distance, and the distance is defined as the distance between the vehicle and the white line.

  A means for obtaining a steering angle of the front wheel of the host vehicle; a means for calculating a traveling direction of the host vehicle within the fixed time using an average value of the steering angle within the fixed time; Means for measuring the travel distance, calculates the travel vector of the host vehicle using the traveling direction and the travel distance, and adds the travel vector to the previously measured host vehicle position to measure the host vehicle position. .

  According to the present invention, the lateral position in the lane is measured using the distance from the white line in the image, and the position of the vehicle is measured using this, so the positioning accuracy is improved compared to the method using the gyro. To do.

[Example 1]
An embodiment of the present invention will be described with reference to the drawings. FIG. 1 shows the configuration of an apparatus according to the present invention. In the present invention, an image processing device 101, a disk device 104, a GPS 105, and a display device 108 are connected to a car navigation system 103. Further, a vehicle speed sensor 106, a gyro sensor 107, and a rudder angle sensor 109 are connected to the car navigation system 103. A camera 102 is connected to the image processing apparatus 101. The vehicle speed sensor 106, the gyro sensor 107, and the steering angle sensor 109 are connected to the in-vehicle network, and the car navigation system 103 has a function of transmitting / receiving data in the in-vehicle network.

  The disk device 104 is a device for reading out map information all over Japan or a part thereof, and the information is stored in a CD, DVD or HDD. The GPS 105 is a device for measuring the vehicle position. The vehicle speed sensor 106 and the gyro sensor 107 are also devices for measuring the vehicle position, and the vehicle position can be specified using a technique called dead reckoning using these two devices. The camera 102 is installed on the vehicle body and is used for photographing the road surface on which the host vehicle is traveling. The image processing apparatus 101 is used to process video captured by the camera 102.

  The car navigation system 103 has functions of route search and route guidance. For route guidance, it is necessary to accurately grasp the vehicle position. This is described next.

  FIG. 2 is a diagram illustrating a configuration of the vehicle position measurement device according to the present embodiment. The image processing apparatus 101 includes a lane recognition processing unit 202 that extracts a lane from an image captured by the camera 102. Further, the lateral distance between the extracted lane and the own vehicle is obtained using image processing. This is performed by the in-lane position measurement unit 203.

  The output of the vehicle speed sensor 106 is also used to calculate the travel distance, and the travel distance measuring unit 204 performs this. Based on the outputs of the in-lane position measuring unit 203 and the travel distance measuring unit 204, the own vehicle position measuring unit 205 measures the own vehicle position.

The measurement procedure will be illustrated with reference to FIG. FIG. 3 shows a scene where the lane is changed on a two-lane road. This is a scene where the vehicle travels at a point 301 first, then a point 302, and a point 303. At the point 301, the distance between the center line 310 and the own vehicle is d ₁₁ , and the traveling distance until the point 302 is reached is d ₂₁ . At the point 302, the distance between the center line 310 and the own vehicle is d ₁₂ , and the traveling distance until the point 303 is reached is d ₂₂ . In point 303, the distance between the line 311 the vehicle is d _13.

Considering the point 301 as the origin, if the vehicle traveling direction is the y-axis, and the x-axis is orthogonal to the right direction of the vehicle, the coordinates of the point 302 are (d ₁₁ −d ₁₂ , sqrt (d ₂₁ ^ 2- ( d ₁₁ −d ₁₂ ) ^ 2)), and let this be (x ₂ , y ₂ ). Since (x ₂ , y ₂ ) is a relative coordinate with the point 301 as the origin, it is necessary to convert it into longitude and latitude. For this purpose, information on the direction of the currently traveling road is obtained from the map DB 201. This is expressed, for example, by an angle in which the east direction is 0 and the counterclockwise direction is positive. It is only necessary to rotate (x ₂ , y ₂ ) by the angle in the direction of the road and further rotate it by the angle between the direction of the road and the traveling direction of the vehicle and add it to the longitude / latitude of the point 301.

Next, considering the point 302 as the origin, the coordinates of the point 303 are obtained. At this time, the width of the lane is obtained from the map DB 201, and the lateral distance between the vehicle and the center line 310 is obtained. Assuming that the width of the lane is w _r , the amount of movement in the x direction from the point 302 to the point 303 is d ₁₂ + ( _wr −
d ₁₃ ). Subsequent calculations are the same as when moving from the point 301 to the point 302.

The flow of the positioning process will be described with reference to the flow of FIG. First, a reference position is measured (step 401). For this, the GPS 105 is used. When the fixed time has passed, the travel distance from the reference position is measured using the output of the vehicle speed sensor 106 (step 402). The value of “fixed time” may be determined to be 100 ms, for example. Next, a line is extracted from the image photographed by the camera 102, and the distance between the line and the vehicle is calculated. Based on the distance between the vehicle and the line, the lateral movement distance of the vehicle is obtained (step 405). The vehicle position is measured from the lateral movement distance obtained in step 405 and the travel distance obtained in step 402 (step 406). The vehicle position measured here is set as a reference position (step 407), and the process returns to step 402. Steps 402 to 405 are activated at regular intervals, and the vehicle position is measured at regular intervals. By performing such processing, the vehicle position can be measured without using a gyro and without using conventional map matching.

Next, a method for calculating the distance between the vehicle position and the line will be described. First, a state in which the camera 102 is installed in a car is shown in FIG. The vehicle position to be obtained is the center 1001 of the vehicle body. Let the vehicle length be l and the vehicle width be w. Assume that the camera 102 is attached to the back of the car, the optical axis of the camera is parallel to the traveling direction, and the installation position is separated from the center of the car by a distance d _{cam in the} lateral direction.

FIG. 7 shows an example in which lines 901 and 902 are captured in an image captured by the camera 102 attached to the car. An example of a processing flow for calculating the distance between the vehicle position and the line at this time is shown in FIG. First, when an image is taken, distance information from the camera to each pixel is converted into a distance image represented by shading (step 1101). Next, the center pixel P _c of the image toward the right, to scan until it finds a pixel P _r of the line (step 1102). Next, to obtain the distance d _r of the distance d _c and P _r and camera 102 of P _c and the camera 102 from each distance image (step 1103). Next, a distance d _cr between P _c and P _r is obtained. This can be obtained from the relationship d _cr ² = d _c ² + d _r ² (step 1104). A value obtained by adding d _cam to d _cr is set as a distance between the line 902 and the own vehicle (step 1105). However, the distance obtained here is the value at the distance d _c rearward from the vehicle position, because it is not the distance from the side of the car, in the present embodiment, the camera 102 so that the value of d _c is as small as possible It is assumed that the shooting range has been adjusted. As for the longitudinal position, it is necessary to consider the distance d _c. Note that P _c does not have to be the center of the image, but may be on a boundary line that divides the image into left and right halves.

Next, consider a case where the lane is changed from the state of FIG. FIG. 10 shows an example of an image when changing to the right lane. FIG. 10A is immediately before the lane change, and FIG. 10B is immediately after the lane change. Here, in the present embodiment, it is assumed that the camera 102 is attached to the back of the vehicle, and when the lane is changed to the right, it appears that the vehicle has moved to the left in the image. Since the line 902 moves away from the own vehicle, the distance d _cr2 to the line 902 becomes larger than d _cr when the state becomes the state of FIG. Next, _assuming that the state shown in FIG. 10B is obtained when the image is acquired, the distance d _cr3 to the line 901 is calculated. Therefore, the lateral movement distance when _changing from FIG. 10A to FIG. 10B is the lane width −d _cr2 + d _cr3 .

  Here, a line detection method will be described. It is possible to detect a line by detecting a pixel having a large change in brightness in an image and converting the arrangement of the pixel into a straight line by Hough transform or the like.

FIG. 11 shows an example of the relationship between the distance between the vehicle and the line and the time when the lane is changed to the right lane. Distance at time t1 d _cr, until time t8 becomes monotonously distance is increased to d _cr2, the distance becomes the next measurement time t9 decreased suddenly, and has a d _cr3. By observing the change in the distance to the line in this way, it is possible to know the movement of the vehicle in the road width direction within the lane and which line of the lane has been crossed.

First, a line is detected from the image. In the state of FIG. 10A, lines 1201, 901, and 902 are detected. At this time, a line having the shortest distance from the dividing line 903 is detected from the dividing line 903 that divides the image into left and right sides. In the case of FIG. 10A, the line 902 corresponds to this. If the next image obtained is shown in FIG. 10B, the line on the right side from the dividing line 903 and the shortest distance from the dividing line 903 is the line 901. At this time, d _cr2 rapidly decreases. Thus, it can be seen that the state shown in FIGS. 10A to 10B has been reached. In other words, you can see that you crossed the lane.

Incidentally, as shown in FIG. 12, there is a case where an image of a line cannot be found even when scanning from the center of the image to the right. At that time, find P _l from the image center by scanning to the left. Next, a distance d _cl between P _c and P _l is obtained. For this purpose, d _c and d _l are used in accordance with the method described above. The distance from the line 902 can be obtained by the lane width −d _cl + d _cam .

In FIG. 3, the distance to the right line of the vehicle is used, but the left line may be used. FIG. 6 shows a state where the automobile moves from the point 501 to the point 502 via the point 508. At the point 501, the distance d _h1 from the line 601 is calculated using image processing. At this time, the camera image is as shown in FIG. 9, and d _h1 can be obtained from the value of d _cr .

When moving from the point 501 toward the point 508, the camera image transitions from FIG. 10B to FIG. 10A. That is, it is the opposite of moving to the right lane. The distance to the line that is on the left side of the _host vehicle and is closest to the _host vehicle changes from d _cr to d _cr3 , and when the point 508 is reached, the camera image is in the state shown in FIG. It has become. Here, the line 602 corresponds to the line 902. At this time, d _cr2 is obtained, and a distance d _h2 from the line 601 is calculated. Further, the width w of the advance lane is obtained from the map DB 201. The amount of movement in the vertical direction can be obtained from the travel distance d _v1 based on the output of the vehicle speed sensor 106 and the amount of movement in the horizontal direction. The amount of movement in the horizontal direction when moving from the point 501 to 508 is d _h1 + w−d _h2 . Using this and the value of d _v1 , positioning by dead reckoning becomes possible.

Further, when the point 503 is reached at the next positioning time, similarly, the distance d _h31 with the line 601 is calculated, the travel distance d _v2 is obtained, the movement amount in the horizontal and vertical directions is obtained, and the coordinates of the point 502 are obtained. Can be requested.

  This method can also be applied when meandering in the same lane. As shown in step 1105, since the position in the horizontal direction is always grasped while always calculating the distance between the line and the host vehicle, an accurate position can be obtained even if meandering in the same lane.

  These technologies can also be applied at highway branch points.

The above describes the case of traveling on a road without a branch. Next, the case where the vehicle travels in the direction of the road branch will be described with reference to FIG. In the branch, a broken line thicker than a normal line is drawn as a branch line 1604. When the branch line 1604 can be recognized, the lateral movement distance is obtained using the distance between the vehicle and the branch line 1604. At the point 1602, the distance d _h1 is obtained, and when moving to the point 1603, the distance d _h2 is obtained. When a branch line is included in the image, the distance between the vehicle and the branch line is obtained. In this case, it is also determined whether the branch line is on the right side or the left side of the center of the screen. In FIG. 14, when the vehicle moves from the point 1602 to the point 1603, the branch line 1604 moves from the left side to the right side of the own vehicle, so the lateral movement distance of the own vehicle is d _h1 + d _h2 . Further, when the vehicle moves from the point 1603 to the point 1605, the branch line 1604 remains on the right side of the own vehicle, so the lateral movement distance of the own vehicle is d _h2 + d _h3 .

Next, FIG. 15 shows an example of a flow for obtaining the lateral movement distance in step 405. First, an image is acquired (step 1701). Next, the line on the left side of the host vehicle is recognized (step 1702). When a commercially available rear view camera is used, a line existing in the left half of the image may be recognized. Next, a distance d _h1 between the line and the vehicle is obtained (step 1703). This is calculated according to the flow shown in FIG.

Next, it is determined whether or not the recognized line is a branch line (step 1704). If it is a branch line, the next image is acquired (step 1710), and then the branch line included in the image is recognized (step 1711). The distance to the branch line is calculated (step 1712), and when the position of the branch line has changed to the right (step 1713), the lateral movement distance is set to d _h1 + d _h2 (step 1715). If the position of the branch line has not changed, the lateral movement distance is set to d _h1 -d _h2 (step 1714).

If it is determined in step 1704 that the line is not a branch line, the next image is acquired (step 1705), the line on the left side of the vehicle is recognized (step 1706), and the line and the vehicle are The distance d _h2 is calculated (step 1707). In step 1708, the difference between d _h1 and d _h2 is obtained and compared with a threshold value. If it is larger than the threshold value, it is determined that the line has been crossed, and the lateral movement distance is set to d _h1 + w−d _h2 (step 1709). Here, w is the width of the lane. If it is smaller than the threshold value, it is determined that the line is not crossed, and the lateral movement distance is set to d _h1 -d _h2 (step 1714).

  In addition, the processing which calculates | requires the distance of a line and the own vehicle of steps 1707 and 1712 follows the flow shown in FIG.

Next, an example of using the rudder angle sensor 109 instead of using an image will be described. If a white line cannot be detected, the steering angle sensor 109 can be used. The software configuration at this time is shown in FIG. This is a configuration in which a steering angle measurement unit 501 is added to the configuration of FIG. The rudder angle sensor 109 outputs the angle of the front wheel of the vehicle. The rudder angle measurement unit 501 outputs an average value of raw data output from the rudder angle sensor 109 within a predetermined time. For example, the output time interval of the rudder angle sensor 109 is set to 0.01 second, and an average value of 10 output data is output every 0.1 second. As a result, it is possible to correct and output variations in the output of the rudder angle sensor 109.

  About this, a flow is shown in FIG. First, the timer is reset (step 1501), and then the raw output data of the steering angle sensor 109 is acquired (step 1502). Next, it is checked whether or not the timer value has reached a specified value (step 1503). If the specified value has not been reached, the timer is incremented (step 1504), and the process returns to step 1502 to output the next output value of the steering angle sensor 109. Get. When the timer reaches the specified value, the average value of the data acquired within that time is calculated (step 1505) and sent to the vehicle position measuring unit 205 (step 1506). The own vehicle position measuring unit 205 identifies the traveling direction of the own vehicle from the output data of the rudder angle measuring unit 501. Dead reckoning is executed using this traveling direction and travel distance.

  By applying the present invention to a car navigation system, it is possible to contribute to more accurate and detailed route guidance. It can also be applied to safe driving support for drivers.

It is an apparatus block diagram of this invention. It is a software block diagram of this invention. It is a figure which shows the use feature-value at the time of lane change. It is a figure which shows the flow of the own vehicle position measurement. It is a software block diagram of this invention. It is a figure which shows the use feature-value in a branch. It is a figure which shows the parameter when the pitching of a camera generate | occur | produces. It is a flow for obtaining a camera pitch angle. It is a figure which shows the parameter used for the distance calculation of a white line and the own vehicle. It is a figure which shows the example of the installation position of a camera. It is a distance calculation flow between a white line and the own vehicle. It is a figure which shows the parameter used for the distance calculation of a white line and the own vehicle. It is a figure which shows the example of a change of the distance of a white line and the own vehicle. It is a figure which shows the parameter used for the distance calculation of a white line and the own vehicle. It is a flow until a steering angle measurement result by a steering angle sensor is output.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 ... Image processing apparatus, 102 ... Camera, 103 ... Car navigation system, 104 ... Disk apparatus, 105 ... GPS, 106 ... Vehicle speed sensor, 107 ... Gyro sensor, 108 ... Display apparatus, 109 ... Steering angle sensor

Claims (3)

In a car navigation system comprising an imaging device for photographing the periphery of the vehicle, a positioning device for positioning the vehicle position using satellite radio waves, and a storage device for storing road information,
White line extracting means for extracting a white line from the captured image, means for processing the image to determine the distance between the vehicle and the white line, and distance change calculating means for calculating a change in the distance between the white line within a predetermined time And travel distance measuring means for measuring the travel distance within the predetermined time,
A vehicle position characterized by calculating a travel vector of the host vehicle using a change in distance from the white line and the travel distance, and adding the travel vector to the previously measured host vehicle position to measure the host vehicle position. Positioning device. In the vehicle positioning device according to claim 1,
The means for processing the image to determine the distance between the vehicle and the white line is a first distance to a first point corresponding to an arbitrary point included in a boundary line that bisects the image to the left and right. And a second distance from the first point to a second point corresponding to the first pixel found by scanning in the horizontal direction from among the pixels included in the white line extracted by the white line extracting unit. The distance between the first point and the second point is obtained based on the first distance and the second distance, and the distance is the distance between the vehicle and the white line. Vehicle positioning device. In a car navigation system equipped with a positioning device for positioning the vehicle position using satellite radio waves and a storage device for storing road information,
Means for obtaining the rudder angle of the front wheel of the own vehicle, means for calculating the traveling direction of the own vehicle within the certain time using the average value of the rudder angle within the certain time, and the travel distance within the certain time And means for measuring
A vehicle position measuring apparatus that calculates a travel vector of the host vehicle using the traveling direction and the travel distance, and measures the host vehicle position by adding the travel vector to the previously measured host vehicle position.

Images