JP2014157501A - Obstacle detection device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an obstacle detection device capable of grouping the point sequence of a detection distance for each obstacle even when noise is mixed in the point sequence of the detection distance.SOLUTION: When a maximum point 91 of distance difference with the distance difference equal to or more than a specified quantity is present in a point sequence 9 of detection distances, an obstacle detection device sets a continuity range in which a continuity is satisfied between a point sequence 92 of detection distances before the maximum point 91 of distance difference and the maximum point 91 on the basis of fluctuation tendency of the point sequence 92 of detection distances before the maximum point 91 of distance difference. The device sets a continuity range in which a continuity is satisfied between a point sequence 93 of detection distances after the maximum point 91 of distance difference and the maximum point 91 on the basis of fluctuation tendency of the point sequence 93 of detection distances after the maximum point 91 of distance difference. When an end point 931 of the point sequence 93 is included in the continuity range and an end point 921 of the point sequence 92 in included in the continuity range, the device determines that a continuity exists between the point sequences 91, 92 and the maximum point 91 of distance difference is noise. When any of the end points 931, 932 is separated from the continuity range, the device determines that no continuity exists between the point sequence 92, 93, and performs grouping by using the maximum point 91 of distance difference as a boundary.

Description

  The present invention relates to an obstacle detection device that detects an obstacle existing around a host vehicle by using distance detection means such as an ultrasonic sensor that detects a distance from the host vehicle to the obstacle.

  2. Description of the Related Art Conventionally, a parking space detection device that detects a parking space using distance detection means that detects a distance from an own vehicle to an obstacle such as a parked vehicle is known (see, for example, Patent Document 1). For example, in the parking space detection device of Patent Document 1, when the host vehicle is moving on the side of an obstacle (parked vehicle), the distance to the obstacle is sequentially detected by a distance measuring sensor. Then, the shape of the obstacle is estimated by performing curve approximation on the obtained point distance data of the detection distance, and the parking space is detected based on the estimated shape.

JP 2008-21039 A

  By the way, for example, in order to appropriately approximate the point sequence of the detection distance, it is important to correctly demarcate from where to where the single obstacle is, that is, to group the detection distance point sequence for each obstacle. It is. Since the detection distance usually changes greatly at the break of the obstacle, it is conceivable to perform grouping with the changed position as a boundary. Regarding this grouping, in Patent Document 1, it is assumed that the detection of an obstacle is completed when a point sequence having a detection distance equal to or greater than a predetermined reference length is detected and the point sequence no longer exists after a predetermined distance. Yes.

  However, while the detection distance may change greatly at the break of the obstacle, the detection distance may change greatly due to noise such as road surface noise. In other words, if there is a point with a large distance difference (distance difference large point) in the sequence of detection distances, simply grouping them will result in a noise position despite a single obstacle. There is a possibility of grouping by mistake. Thus, when noise is mixed in the point sequence of the detection distance, there is a problem that it is difficult to group the detection distance.

  The present invention has been made in view of the above problems, and an obstacle capable of grouping the detection distance point sequence for each obstacle even when noise is mixed in the detection distance point sequence. It is an object to provide a detection device.

In order to solve the above-described problem, the obstacle detection device of the present invention includes a distance detection unit that sequentially detects the distance to the obstacle when the host vehicle is moving on the side of the obstacle,
First determination means for determining the presence or absence of a large distance difference point that is a detection distance point at which a difference from a detection distance of an adjacent point in the point sequence of detection distances detected by the distance detection means is a predetermined amount or more. When,
Second determining means for determining whether the position of the distance difference large point is a break of an obstacle or whether the distance difference large point is noise when the first determining means determines that the distance difference large point is present. When,
First grouping means for performing grouping of the point sequence of the detection distance with the distance difference large point as a boundary when the second determination means determines that the obstacle is discontinuous;
It is characterized by providing.

  According to the present invention, when there is a distance difference large point in the detection distance point sequence, it is determined whether the position of the distance difference large point is an obstacle break or whether the distance difference large point is noise. Since the determination means of 2 is provided, even if noise is mixed in the point sequence of the detection distance, it is possible to distinguish between the break of the obstacle and the noise. Therefore, when the second determination unit determines that the obstacle is a break, grouping is performed for each obstacle by grouping the break, that is, the distance difference large point as a boundary.

It is the figure which showed schematic structure of the parking assistance apparatus. It is the figure which illustrated the assumption scene of parking space detection. It is the flowchart which showed the basic procedure of parking space detection. It is a figure explaining the calculation method of a reflective point. It is the figure which illustrated the point sequence of the detection distance which does not have continuity. It is a figure of the scene where the pillar 82 was arrange | positioned in the position offset adjacent to the parked vehicle 63. FIG. It is a figure of the scene where the two parked vehicles 63 and 64 were arrange | positioned adjacently. It is a flowchart of a grouping process. It is a detailed flowchart of S23. It is a detailed flowchart of S41 and S42, and is a diagram illustrating a procedure for setting an assumed range according to the first embodiment. It is a figure which shows the point sequence of the detection distance containing a distance difference large point, and is a figure explaining the setting method of the assumption range of the back distance point which concerns on Example 1. FIG. It is a figure explaining the setting method of an increment line and a decrement line, and is the figure which illustrated the point sequence which a detection distance decreases with progress of time. It is a figure explaining the setting method of an increment line and a decrement line, and is the figure which illustrated the point sequence which a detection distance decreases or increases with progress of time. It is a figure which shows the point sequence of the detection distance containing a distance difference large point, and is a figure explaining the setting method of the assumption range of the previous distance point which concerns on Example 1. FIG. It is the figure which illustrated the point sequence of the detection distance which has continuity. It is the figure which set the assumption range of the back distance point with respect to the point sequence of FIG. It is the figure which set the assumption range of the front distance point with respect to the point sequence of FIG. It is a detailed flowchart of S41 and S42, and is a diagram illustrating a procedure for setting an assumed range according to the second embodiment. It is a figure which shows the point sequence of the detection distance containing a distance difference large point, and is a figure explaining the setting method of the assumption range of the front distance point and back distance point which concern on Example 2. FIG. It is a figure explaining the method of noise processing, illustrating the point sequence of detection distance. It is a flowchart of the detail of S27, and is a flowchart of the process which detects the inflection point in the scene where the offset obstruction was arrange | positioned adjacently. It is a figure for demonstrating the process of FIG. 21, and is a figure of the scene where the offset obstruction was arrange | positioned adjacently. FIG. 6 is a diagram illustrating a point sequence 9 that hardly changes in the depth direction within a frame 500; It is a figure of the scene where only the parked vehicle is arrange | positioned. It is a figure of the scene where two parked vehicles are arranged. It is a flowchart of the detail of S27, and is a flowchart of the process which detects the inflection point in the scene where two parked vehicles are arrange | positioned. It is a figure for demonstrating the process of FIG. 26, and is a figure of the scene where two parked vehicles are arrange | positioned.

  Embodiments of an obstacle detection device according to the present invention will be described below with reference to the drawings. FIG. 1 is a diagram showing a schematic configuration of a parking assistance device 1 to which the obstacle detection device of the present invention is applied. The parking assist device 1 is mounted on the host vehicle 5 (see FIG. 2). The parking assist device 1 includes a distance measuring sensor 2, a vehicle speed sensor 12, a steering angle sensor 13, and an ECU 11 connected thereto.

  As shown in FIG. 2, the distance measuring sensor 2 is mounted on the left and right side surfaces (left side surface 51 in FIG. 2) of the host vehicle 5. The distance measuring sensor 2 is a sensor that detects a distance to an obstacle such as a parked vehicle that is present on the side (side of the host vehicle 5). Specifically, the distance measuring sensor 2 exceeds the predetermined distance (for example, every 100 milliseconds) in the front direction of the distance measuring sensor 2 (on the left side of the host vehicle 5 in FIG. 2) based on an instruction from the ECU 11. Transmit exploration waves such as sound waves. The distance measuring sensor 2 receives the reflected wave reflected by the transmitted exploration wave hitting an obstacle. Then, the distance measuring sensor 2 calculates the distance to the obstacle based on the transmission timing of the exploration wave, the reception timing of the reflected wave, and the velocity of the exploration wave (sound velocity when the exploration wave is ultrasonic). Detection information (detection distance) detected by the distance measuring sensor 2 is input to the ECU 11. Note that the ECU 11 may calculate the detection distance.

  The directivity φ (directivity of the exploration wave) of the detection range 21 (see FIG. 2) of the distance measuring sensor 2 is, for example, about 70 ° to 120 °. The maximum detection distance that can be detected by the distance measuring sensor 2 is, for example, about 4 m to 10 m. The distance measuring sensor 2 may be any sensor that transmits an exploration wave and receives a reflected wave of the exploration wave, and uses a radio wave regardless of whether it uses a sound wave or a light wave. May be. As the distance measuring sensor 2, for example, a sensor such as an ultrasonic sensor, a laser radar, or a millimeter wave radar can be used.

  Returning to the description of FIG. 1, the vehicle speed sensor 12 is a sensor that detects the vehicle speed of the host vehicle 5. The steering angle sensor 13 is a sensor that outputs the steering angle from the neutral position as the steering angle, with the steering position when the host vehicle 5 moves straight ahead as the neutral position (0 degree). Detection information (vehicle speed, steering angle) detected by the vehicle speed sensor 12 and the steering angle sensor 13 is input to the ECU 11.

  The ECU 11 is mainly composed of a microcomputer including a CPU, a ROM, a RAM, and the like. The ECU 11 executes a process for assisting parking in a parking space existing around the vehicle 5 (side) based on each detection information input from the distance measuring sensor 2, the vehicle speed sensor 12, and the steering angle sensor 13. . In addition, the ECU 11 includes a memory 111 such as a ROM or a RAM that stores various types of information necessary for processing executed by itself.

  Hereinafter, details of processing executed by the ECU 11 will be described. First, a basic procedure of parking space detection by the ECU 11 will be described. FIG. 3 is a flowchart showing the procedure. FIG. 2 is a diagram illustrating an assumed scene in which the process of FIG. 3 is executed. Specifically, the side of two parked vehicles 61 and 62 arranged with the parking space 7 interposed therebetween is shown. The scene where the own vehicle 5 is moving is shown. An obstacle 81 such as a curb is arranged in the parking space 7.

  The process of FIG. 3 may be started when, for example, a support switch (not shown) provided in the passenger compartment is turned on by the driver of the host vehicle 5 or is always executed in the background when the host vehicle 5 is at a low speed. May be. When the processing of FIG. 3 is started, the ECU 11 causes the distance measuring sensor 2 to sequentially detect the distance (S11). Further, based on the detection information of the vehicle speed sensor 12 and the steering angle sensor 13, the position (sensor position) of the distance measuring sensor 2 when the distance measuring sensor 2 detects the distance is calculated (S12). At this time, the moving distance of the distance measuring sensor 2 from the previous sensor position can be calculated from the vehicle speed and the elapsed time from the previous distance detection. Further, the moving direction of the distance measuring sensor 2 from the previous distance detection can be calculated from the steering angle. The sensor position at the time of the current distance detection can be calculated from the movement distance, the movement direction, and the sensor position at the time of the previous distance detection. The detection distance and sensor position detected in S11 and S12 are stored in the memory 111.

  FIG. 2 illustrates a history of detection distances detected in S11, in other words, a point 9 (ranging point) that is separated from the sensor position detected in S12 by the detection distance in the front direction of the distance measuring sensor 2. Yes. As shown in FIG. 2, the point sequence of the distance measuring points 9 includes a distance measuring point 901 for the first parked vehicle 61, a distance measuring point 903 for the obstacle 81 in the parking space 7, and the second parking. A distance measuring point 902 for the vehicle 62. Since the detection range 21 (see FIG. 2) of the distance measuring sensor 2 has a certain degree of directivity, a little before the host vehicle 5 (strictly, the distance measuring sensor 2) enters the front area of the obstacle. From this point, distance detection for the obstacle is started, and distance detection continues for a while after passing through the front area. Therefore, the width of the point sequence of the distance measuring points 901 in FIG. 2 is wider than the width of the parked vehicle 61.

  Next, in order to reduce the influence of the detection distance error, the detection distance history accumulated in the memory 111 is approximated by a curve using a quadratic function or the like (S13). In the example of FIG. 2, the point sequence of the distance measuring points 9 is approximated by a curve. FIG. 2 shows an approximate curve 301 of a point sequence of the distance measuring points 901.

  Next, based on the detection distance and sensor position history smoothed by the curve approximation of S13, a point on the obstacle to which the exploration wave from the distance measuring sensor 2 hits, that is, the contour point of the obstacle is calculated as a reflection point. (S14). Here, FIG. 4 is a diagram for explaining a method of calculating the reflection point, and shows a scene in which the host vehicle 5 is passing by the parked vehicle 6. FIG. 4 includes a sensor position SenPos (n) and a detection distance L (n) at a certain time point, and a sensor position SenPos (n−1) and a detection distance L (n−1) at the previous time point. A triangle 700 is illustrated. In S14, the position of the vertex 4 of the triangle 700 in FIG. 4 is calculated as the position of the reflection point on the assumption that the exploration wave is reflected at the same point of the obstacle at two adjacent time points. That is, the reflection point is calculated using the principle of triangulation. FIG. 2 illustrates a point sequence of the reflection points 4 for the first parked vehicle 61 calculated in S14. The point sequence of the reflection point 4 is detected on the outline of the parked vehicle 61.

  Next, a corner of an obstacle adjacent to the parking space is detected based on the point sequence calculated in S14 (S15). In the example of FIG. 2, the corner 611 of the first parked vehicle 61 is detected based on the point sequence of the reflection points 4, and the parked vehicle 62 is based on the reflection point (not shown) with respect to the second parked vehicle 62. The corner 621 is detected. Specifically, for example, as shown in FIG. 2, a coordinate system having an X axis corresponding to the left and right direction of the parking space 7 and a Y axis corresponding to the depth direction is set. Then, the X coordinate of the reflection point closest to the parking space 7 in the point sequence of the reflection points 4, that is, the reflection point having the largest X coordinate is set as the X coordinate of the corner 611. Further, the Y coordinate of the reflection point closest to the side passage in the point sequence of the reflection points 4, that is, the reflection point having the smallest Y coordinate is set as the Y coordinate of the corner 611. The corner 621 of the second parked vehicle 62 is similarly calculated.

  Next, the space between the corners 611 and 621 detected in S15 is set as the parking space 7 (S16). Thereafter, the process of FIG. 3 is terminated. Thereafter, the ECU 11 determines whether or not the parking space 7 can be parked based on the detected width of the parking space 7 and the vehicle width of the host vehicle 5. When the ECU 11 determines that parking is possible, the ECU 11 calculates a route for the host vehicle 5 to move to the parking space 7 based on the positional relationship between the parking space 7 and the host vehicle 5. Then, ECU11 controls a steering motor and an engine, moves the own vehicle 5 to the parking space 7 according to the path | route, and completes parking.

  As described above, in order to detect a parking space, it is necessary to approximate the history of the detection distance with a curve in S13 of FIG. At this time, when different obstacles are arranged as in the scene of FIG. 2, it is necessary to perform curve approximation by distinguishing (grouping) the history of the detection distance for each obstacle. In the example of FIG. 2, it is necessary to group the point sequence of the distance measuring points 901, the point sequence of the distance measuring points 902, and the point sequence of the distance measuring points 903, and approximate the curve for each grouped point sequence. . This is because if the detection distance points of different obstacles coexist, the accuracy of the approximate curve decreases, and as a result, the detection accuracy of reflection points and corners decreases.

  Usually, the detection distance greatly fluctuates at the break of the obstacle. In other words, the difference of the detection distance becomes large at the break of the obstacle. Therefore, a method of performing grouping of detection distances at a position where the difference in detection distance becomes large can be considered. However, the distance measuring sensor 2 may detect the distance on the road surface, for example. In this case, a point of noise is included in the detection distance point sequence, and the detection distance greatly varies depending on the position of the noise point. Here, FIG. 5 illustrates a point sequence 9 (detection distance time-series data) including a detection distance point 91 (distance difference large point) having a large distance difference. When the distance difference large point 91 is included in the detection distance point sequence 9, it is necessary to determine whether the distance difference large point 91 is a noise or an obstacle break. Otherwise, the point sequence 92 of the detection distance before the distance difference large point 91 and the point sequence 93 after the single difference may be grouped, or the obstacles may be different obstacles. This is because the point sequences 92 and 93 are grouped into one group.

  On the other hand, depending on the scene, the distance difference may not be large despite the break of the obstacle. FIG. 6 illustrates a scene where the distance difference is small regardless of the break of the obstacle. Specifically, FIG. 6 shows a scene in which the pillar 82 is disposed adjacent to the parked vehicle 63 and offset in the depth direction from the front surface of the parked vehicle 63 (surface on which distance detection is performed). In the scene of FIG. 6, the detection distance point sequence 94 with respect to the parked vehicle 63 and the detection distance point sequence 95 with respect to the column 82 are detected to be continuous despite the break between the parked vehicle 63 and the column 82. Is done. That is, the difference between the end point 941 of the point sequence 94 and the end point 951 of the point sequence 95 is small. Even in such a case, it is necessary to distinguish and group the point sequences 94 and 95.

  Further, depending on the scene, the distance difference may not increase even if the obstacle is not arranged at the offset position. FIG. 7 is a diagram illustrating the scene, and in detail, shows a scene where two parked vehicles 63 and 64 are arranged adjacent to each other without being offset. In the scene of FIG. 7, the detection distance point sequence 971 for the left parked vehicle 63 and the detection distance point sequence 972 for the right parked vehicle 64 continue in spite of the break of the parked vehicles 63 and 64. Is detected. That is, the difference between the end point 973 of the point sequence 971 and the end point 974 of the point sequence 972 is small. Even in such a case, it is necessary to group the point sequences 971 and 972 separately.

  Therefore, the ECU 11 executes a process (grouping process) for grouping the detection distances for each obstacle, which can be applied to the cases of FIG. 5, FIG. 6, and FIG. Details of the grouping process will be described below. FIG. 8 shows a flowchart of the grouping process. The process in FIG. 8 starts when, for example, a support switch (not shown) provided in the passenger compartment is turned on by the driver of the host vehicle 5 and is executed in parallel with the process in FIG. During the process of FIG. 8, the ECU 11 causes the distance measurement sensor 2 to perform distance detection every time the distance detection time t is updated in S31 described later, in other words, every time a predetermined distance detection interval dt elapses. .

  When the processing of FIG. 8 is started, first, the detected distance detected by the distance measuring sensor 2 and the sensor position calculated in S12 of FIG. 3 are associated with each other and stored in the memory 111 (see FIG. 1) (S21). Next, the presence / absence of a large distance difference point, which is a detection distance point having a large distance difference, is determined from the detection distance point sequence (history) stored in the memory 111 (S22). Specifically, in the point sequence of the detection distance, the point of the detection distance where the difference from the detection distance of the adjacent point is a predetermined amount or more is set as the distance difference large point, and the presence / absence of the distance difference large point is determined. . In the example of FIG. 5, it is determined that there is a large distance difference point, assuming that the difference between the two points 91 between the adjacent detection distance points 921 and 931 is greater than or equal to a predetermined amount. On the other hand, in the examples of FIGS. 6 and 7, it is determined that there is no large distance difference point.

  When there is a distance difference large point (difference: large), the process proceeds to S23, and it is determined whether the distance difference large point is noise or an obstacle break. A point sequence of detection distances detected from a single obstacle has continuity between the points. On the other hand, in the point sequence of the detection distance detected from a plurality of obstacles, the fluctuation tendency (continuity) of the point sequence of the detection distance detected from one obstacle and the detection detected from other obstacles There is a difference in the variation tendency (continuity) of the point sequence of distance. Therefore, in S23, based on whether there is continuity between the point sequence of the detection distance before the distance difference large point and the point sequence of the subsequent detection distance, whether the distance difference large point is noise or not Determine if it is a break in the object. FIG. 9 is a detailed flowchart of S23. The case where the process of FIG. 9 is applied to the point sequence of the detection distance of FIG. 5 will be described as an example.

  9, first, if continuity is established with the point sequence 92 of the detection distance point (previous distance point) before the distance difference large point 91, the distance difference large point 91 is established. An assumed range in which a later detection distance point 93 (rear distance point) is assumed is set based on the continuity (variation tendency) of the point sequence 92 (S41). In other words, a range in which continuity is established between the area of the rear distance points 93 and the point sequence 92 of the previous distance points is set as an assumed range (S41). Further, in S41, an assumed range is set based on a point sequence of a certain interval (three intervals in FIG. 5) immediately before the distance difference large point 91 in the point sequence 92 of the previous distance point. In the present embodiment, two examples will be described as the setting method of the assumed range of S41 and the assumed range of S42 described later. FIG. 10 is a detailed flowchart of S41, and shows a procedure for setting an assumed range according to the first embodiment.

  When the processing shifts to FIG. 10, first, a line (incremental line) indicating an increasing tendency of the detection distance in the section of the point sequence 92 of the previous distance point is set in the area of the rear distance point 93 (S51). FIG. 11 is a diagram for explaining each process of FIG. 10 and shows a point sequence having the same detection distance as FIG. In the example of FIG. 11, the detection distance of the three points constituting the point sequence 92 tends to increase with time. In S51, for example, the difference B (increase) between the minimum detection distance point 922 and the maximum detection distance point 921 in the point sequence 92 is calculated. Then, in the sections other than the point sequence 92, it is assumed that the detection distance increases linearly at a rate of an increase B per section length A of the point sequence 92 with the passage of time. 411 is set as the incremental line. In other words, a line 411 passing through a point 921 having a slope B / A is set as an incremental line.

  In the example of FIG. 11, the detection distance of the point sequence 92 increases with the passage of time, but as shown in FIG. 12, the detection distance of the point sequence 92 may decrease with the passage of time. In this case, for example, in the section after the point sequence 92, the horizontal line 413 passing through the end point 9a is set as the increment line of S51 on the assumption that the distance is equal to or less than the detection distance at the end point 9a of the point sequence 92. In other words, since the increment is zero in the point sequence 92 of FIG. 12, the line 413 passing through the point 9a having a zero slope is set as the increment line.

  Further, as shown in FIG. 13, the detection distance may decrease or increase with the passage of time. In the example of FIG. 13, with the passage of time, the detection distance decreases (point 9b> point 9c), and then the detection distance increases (point 9c <point 9d). In the entire section A, the detection distance decreases (point 9b> point 9d). In this case, for example, in the section after the point sequence 92, it is assumed that the detection distance increases linearly at the ratio of the increase C in the detection distance between the points 9c and 9d per section length A. A line 414 having a slope C / A passing through 9d is set as an incremental line. In the example of FIGS. 11, 12, and 13, the section of the point sequence 92 is a three-point section. However, in the case of a section A ′ having more points, the section A ′ The difference B ′ between the minimum value of the detected distance and the detected distance value of the end point of the section A ′ (point 921 in the example of FIG. 11) is calculated as an increment. A line passing through the end point of the slope B ′ / A ′ may be set as an incremental line.

  Returning to the description of FIG. 10, next, a line (decrement line) indicating a decreasing tendency of the detected distance in the section of the point sequence 92 of the previous distance point is set in the area of the rear distance point 93 (S52). In the example of FIG. 11, the detection distance of the point sequence 92 increases with the passage of time, and the amount of decrease is zero. In this case, for example, in the section after the point sequence 92, the horizontal line 412 passing through the end point 921 is set as a decrement line, assuming that the distance is equal to or greater than the detection distance at the end point 921 of the point sequence 92 (S52). .

  In the example of FIG. 12, since the detection distance decreases with the passage of time, for example, a line 415 connecting the two end points of the point sequence 92 is set as a decrement line. In the example of FIG. 13, since the entire section A is decreased by the difference D between the detection distance at the point 9b and the detection distance at the point 9d, in S52, for example, an inclination (−D / A) passing through the point 9d. ) Line 416 is set as a decrement line. In the case of the section A ′ having three or more points, for example, the difference D ′ between the maximum value of the detection distance in the section A ′ and the detection distance value of the end point of the section A ′ is reduced. Calculate as minutes. Then, a line passing through the end point of the inclination −D ′ / A ′ may be set as a decrement line.

  It is assumed that the increment line set in S51 and the decrement line set in S52 are limit lines where continuity is established with the point sequence 92 of the previous distance point. And the range 410 (refer FIG. 11) between these increment lines and decrement lines is set as an assumption range of the back distance point 93 (S53). This assumed range 410 is a first continuity range in which continuity is established with the point sequence 92. An increment line 411 in FIG. 11 is a line that gives an upper limit value of a detection distance at which continuity is established with the point sequence 92 of the previous distance point. The decrement line 412 is a line that gives a lower limit value of the detection distance that establishes continuity with the point sequence 92 of the previous distance point. Further, in S53, the assumed range may be set by giving a predetermined margin to the range 410. Specifically, a range that is expanded from the range 410 by a predetermined amount d1 (see FIG. 11) up and down is assumed. May be set as Thereby, it is possible to prevent the point sequence 92 from being determined to be discontinuous even when there is no obstacle break. After S53, the process of the flowchart of FIG. 10 is terminated, and the process returns to the process of FIG.

  Returning to the processing in FIG. 9, next, assuming that continuity is established with the point sequence 93 of the rear distance point, an assumed range in which the front distance point 92 is assumed is represented by It sets based on continuity (fluctuation tendency) (S42). In other words, a range in which continuity is established between the area of the previous distance points 92 and the point sequence 93 of the rear distance points is set as an assumed range (S42). Further, in S42, an assumed range is set based on the point sequence of the fixed interval (three-point interval in FIG. 5) immediately after the distance difference large point 91 in the point sequence 93 of the rear distance points.

  In S42, the assumed range is set in the same manner as in S41, that is, according to the processing of the flowchart of FIG. FIG. 14 is a diagram for explaining each process of FIG. 10 with respect to the process of S42, and shows a point sequence having the same detection distance as FIG. 10, the line (incremental line) indicating the increasing tendency of the detection distance in the section of the point sequence 93 of the rear distance point is set in the area of the front distance point 92 (S51). Specifically, an incremental line is set in the same manner as the incremental line in the process of S41. In other words, in the example of FIG. 14, the detection distance of the point sequence 93 tends to increase with the passage of time. Therefore, in S51, for example, the difference between the minimum value and the maximum value of the detection distance in the point sequence 93 F (increase) is calculated. Then, in the sections other than the point sequence 93, it is assumed that the detection distance changes linearly at the rate of the increment F per section length E of the point sequence 93, and the end point 931 of the point sequence 93 adjacent to the distance difference large point 91 is assumed. A line (straight line) 421 having an inclination F / E passing through is set as an incremental line. When the variation tendency of the point sequence 93 is the same as the variation tendency of FIGS. 12 and 13, an incremental line may be set as will be described with reference to FIGS. 12 and 13.

  The increment line 421 in FIG. 14 is a line that gives a lower limit value of the detection distance that establishes continuity with the point sequence 93 for the interval before the point sequence 93, that is, the interval of the previous distance point 92. It becomes.

  Next, a line (decrement line) indicating a decreasing tendency of the detection distance in the section of the point sequence 93 of the rear distance point is set in the area of the front distance point 92 (S52). In the example of FIG. 14, the detection distance of the point sequence 93 increases with the passage of time, and the amount of decrease is zero. In this case, for example, in the section before the point sequence 93, the horizontal line 422 passing through the end point 931 is set as a decrement line on the assumption that the distance is equal to or less than the detection distance at the end point 931 of the point sequence 93 (S52). ). The decrement line 422 is a line that gives an upper limit value of the detection distance that establishes continuity with the point sequence 93 for the section of the previous distance point 92.

  Next, a range 420 between the increment line 421 and the decrement line 422 is set as an assumed range of the previous distance point (second continuity range in which continuity is established with the point sequence 93). Similarly to S41, the assumed range may be set by giving a predetermined margin to the range 420. Specifically, a range that is expanded from the range 420 by a predetermined amount is set as the assumed range. Also good.

  Note that either the process of S41 or the process of S42 may be executed first. Returning to the processing of FIG. 9, next, the rear distance point 931 (end point of the rear distance point point sequence 93) adjacent to the distance difference large point 91 is included in the assumed range 410 (see FIG. 11) set in S41. It is determined whether or not (S43). If it is not included (S43: No), it is determined that the back distance point does not have continuity with the point sequence of the previous distance point, that is, is discontinuous (S46). Then, the process of FIG. 9 is complete | finished. In the example of FIG. 11, the rear distance point 931 is determined to be included in the assumed range 410. In addition, it is not determined whether or not the points other than the end point 931 in the point sequence 93 are included in the assumed range 410. This is because the accuracy of the increment line 411 and the decrement line 412 set in S41 decreases as the distance from the point sequence 92 of the previous distance point decreases, so that continuous or discontinuous misjudgment is prevented.

  When the rear distance point 931 is included in the assumed range 410 (S43: Yes), the front distance point 921 (the end point of the point sequence 92 of the previous distance point) adjacent to the distance difference large point 91 is the assumed range 420 ( It is determined whether it is included (see FIG. 14) (S44). In the example of FIG. 14, it is determined that the previous distance point 921 is not included in the assumed range 420. In this case (S44: No), it is determined that the front distance point 921 does not have continuity with the point sequence 93 of the rear distance point, that is, is discontinuous (S46). Then, the process of FIG. 9 is complete | finished.

  On the other hand, when the previous distance point is included in the assumed range (S44: Yes), it is determined that the previous distance point has continuity with the point sequence of the rear distance point (S45). Thereafter, the processing of the flowchart of FIG. 9 ends. As described above, in FIG. 9, when the rear distance point is included in the assumed range and the previous distance point is included in the assumed range, the point distance between the point range of the previous distance point and the point range of the rear distance point. Therefore, it is determined to have continuity, and otherwise, it is determined to be discontinuous. Eventually, in the example of FIG. 5, it is determined that there is no continuity (discontinuity) between the point sequence 92 and the point sequence 93.

  Here, FIG. 15 shows a point sequence having a detection distance different from that of FIG. 5, although the fluctuation tendency is similar to that of FIG. 5. In FIG. 15, the increasing tendency of the point sequence 93 of the rear distance points is slightly different from that in FIG. 5, and the other tendency is the same as that in FIG. 5. An example in which the process of FIG. 9 is applied to the point sequence of FIG. 15 will be described. FIG. 16 shows an example in which the process of S41 of FIG. 9 (the process of FIG. 10) is applied to the point sequence of FIG. As shown in FIG. 16, in S41, a range 430 between the increment line 431 set in S51 of FIG. 10 and the decrement line 432 set in S52 is set as an assumed range of the rear distance point 931.

  FIG. 17 shows an example in which the process of S42 of FIG. 9 (the process of FIG. 10) is applied to the point sequence of FIG. As shown in FIG. 17, in S42, a range 440 between the increment line 441 set in S51 of FIG. 10 and the decrement line 442 set in S52 is set as an assumed range of the previous distance point 921.

  The rear distance point 931 is included in the assumed range 430 (see FIG. 16), and the front distance point 921 is also included in the assumed range 440 (see FIG. 17). Therefore, in the example of FIG. 15, it is determined that there is continuity between the point sequences 92 and 93. As described above, the processing shown in FIGS. 9 and 10 can be used to determine continuous or discontinuous after determining the fine fluctuation tendency of the point sequence of the detection distance.

  Next, a second embodiment of the assumed range setting method in S41 and S42 of FIG. 9 will be described. FIG. 18 is a flowchart showing details of S41 and S42, and shows a procedure for setting an assumed range according to the second embodiment. FIG. 19 is a diagram for explaining the processing of FIG. 18 and shows a point sequence of detection distances having a variation tendency similar to that of FIGS. 5 and 15 described above. The point sequence of FIG. 19 includes two distance difference large points 91, a point sequence 92 of the previous distance point before the distance difference large point 91, and a point sequence 93 of the rear distance point after the distance difference large point 91. have. The point sequence 92 is a point sequence in a certain section (three points in FIG. 19) immediately before the distance difference large point 91. The point sequence 93 is a point sequence in a certain interval (three intervals in FIG. 19) immediately after the distance difference large point 91.

  When the process proceeds to the process of FIG. 18 in S41, first, a single line 451 that gives an estimated value of a detection distance that establishes continuity with the point sequence 92 of the previous distance point for the area of the rear distance point 93. (Estimated line of the rear distance point 93) is set based on the fluctuation tendency of the point sequence 92 (S61). Specifically, for example, in the sections other than the section of the point sequence 92, it is assumed that the detection distance varies linearly with the same tendency as the section of the point sequence 92. Then, for example, a straight line 451 connecting both end points 921 and 922 of the point sequence 92 is set as an estimated line of the rear distance point 93. Alternatively, linear approximation may be performed using all the points in the point sequence 92, and the obtained approximate straight line may be set as an estimated line.

  Next, a range within a predetermined distance from the estimated line 451 is set as an assumed range of the rear distance point 93 (S62). Specifically, a range 450 that is a predetermined amount d2 or less from the point 452 on the estimated line 451 at the position (time) of the end point 931 of the back distance point sequence 93 is assumed as the assumed range of the back distance point 931. Set (S62). Then, the process of FIG. 18 is complete | finished.

  Further, when the process proceeds to the process of FIG. 18 in S42, first, a single distance that provides an estimated value of the detection distance that establishes continuity with the point sequence 93 of the rear distance point for the area of the front distance point 92 is provided. A line 461 (estimated line of the previous distance point 92) is set based on the fluctuation tendency of the point sequence 93 (S61). Specifically, as described above, a straight line connecting both end points 931 and 932 of the point sequence 93 and an approximate straight line obtained by linear approximation of the point sequence 93 are set as the estimation line 461.

  Next, a range 460 that is below a predetermined amount d2 from the point 462 on the estimated line 461 at the position (time) of the end point 921 of the point sequence 92 of the previous distance point is set as an assumed range of the previous distance point 921. (S62). Then, the process of FIG. 18 is complete | finished.

  Thereafter, in the processes of S43 to S46 of FIG. 9 described above, it is determined whether or not there is continuity between the point sequence 92 of the previous distance point and the point sequence 93 of the rear distance point. In the example of FIG. 19, since the rear distance point 931 is included in the assumed range 450 and the front distance point 921 is included in the assumed range 460, it is determined to be continuous (S45).

  Returning to the processing of FIG. 8, it is next determined whether or not the determination in S23 is a determination that there is continuity (S24). When there is continuity (when it is determined to be continuous in S45 of FIG. 9) (S24: Yes), there is no break of the obstacle at the position of the distance difference large point, and the distance difference large point is noise. Then, the noise is processed (S25). The point sequence described above with reference to FIG. 15 is a point sequence that has no break between the obstacles and is subject to noise processing in S25.

  Here, FIG. 20 is a diagram for explaining the noise processing method in S25, and shows the same point sequence as the point sequence of FIG. The details of S25 will be described with reference to FIG. 20. In S25, first, the section of the distance difference large point 91 is set to a point 921 of the detection distance immediately before the distance difference large point 91 (of the point sequence 92 of the previous distance point). (End point) and the next detection distance point 931 (the end point of the back distance point point sequence 93) are used for linear interpolation. Specifically, a straight line 100 connecting the points 921 and 931 is set as a linear interpolation line. Next, the distance difference large point 91 is corrected so as to be on the line 100 of the linear interpolation. At this time, for example, the distance difference large point 91 is corrected by holding the time when the distance difference large point 91 is detected, that is, by lowering the distance difference large point 91 directly below or directly above in the example of FIG. Do. FIG. 20 shows the point 911 after correction. This makes it possible to remove noise from the detection distance point sequence without reducing the number of detection distance points.

  In S25, instead of correcting the distance difference large point 91, the distance difference large point 91 may be invalidated (removed). According to this, since it is not necessary to perform linear interpolation or correction as shown in FIG. 20, noise can be easily removed.

  After processing the noise in S25, next, for example, whether the support switch (not shown) is turned off or whether the setting of the parking space is completed in the processing of FIG. It is determined whether or not the end condition is satisfied (S30). If the end condition is not satisfied (S30: No), the distance detection time is updated to the next time (t = t + dt) (S31). And it returns to S21 and performs the process below S21 in the time after an update. When the end condition is satisfied, that is, when the support switch is turned off or the setting of the parking space is completed (S30: Yes), the process of FIG. 8 is ended.

  On the other hand, in S24, when there is no continuity (when it is determined that the discontinuity is determined in S46 of FIG. 9) (S24: No), the distance difference is assumed to be an obstacle break at the position of the distance difference large point. Grouping of detection distances is performed with a large point as a boundary (S26). Specifically, the history (point sequence) of the detection distance before the distance difference large point is set as one obstacle group, and the history (point sequence) of the detection distance after the distance difference large point is set to other obstacles. Group. The point sequence of FIG. 5 described above is a point sequence that is the target of grouping in S26 because there is a break in the obstacle. In the example of FIG. 5, the point sequence 92 of the front distance points forms one group, and the point sequence 93 of the back distance points forms one group. The distance difference large point 91 is a point (noise) that does not belong to either group.

  Thereafter, it is determined whether or not the process termination condition of FIG. 8 is satisfied (S30). If not satisfied (S30: No), the time is updated (S31) and the above-described process is repeated. If the end condition is satisfied (S30: Yes), the process of FIG. 8 is ended. Then, in S13 of FIG. 13 after the processing of FIG. 8 is finished, curve approximation is performed for each history of detection distances grouped by the processing of FIG.

  On the other hand, in S22, when there is no distance difference large point in the detection distance point sequence (difference: small), the process proceeds to S27. In this case, it is considered that the scene is a scene where distance detection of a single obstacle continues (a scene without a break between obstacles), the scene shown in FIG. 6, or the scene shown in FIG. In S27, the presence / absence of an obstacle break is determined while distinguishing these scenes. Specifically, as shown in FIGS. 6 and 7, when two obstacles are arranged adjacent to each other, the variation tendency of the point sequence of the detection distance changes at the position of the break of the obstacle. In the scene of FIG. 6, if distance detection is performed in the order of the parked vehicle 63 and the pillar 82, the distance detection with respect to the parked vehicle 63 continues for a while after the host vehicle exceeds the front of the parked vehicle 63. In the detection distance point sequence 940 in the meantime, the value of the detection distance increases with the passage of time, in other words, as the host vehicle advances toward the column 82 side. That is, the point sequence 940 varies in an oblique direction from the corner 631 of the parked vehicle 63 toward the front surface 821 of the column 82.

  Then, when the distance detection with respect to the parked vehicle 63 ends, the distance detection with respect to the pillar 82 starts immediately. When the distance detection with respect to the column 82 is started, a point of the detection distance is detected along the front surface 821 of the column 82 at first. Thereafter, when the host vehicle passes the front of the column 82, distance detection continues for a while, and the value of the detected distance during that time gradually increases as the host vehicle moves away from the column 82.

  As described above, at the boundary between the parked vehicle 63 and the pillar 82 (discontinuity between obstacles), the variation tendency of the point sequence 940 (trend moving in an oblique direction) and the variation tendency of the point sequence 95 with respect to the column 82 (on the front surface 821). A tendency to change along the direction). The detection distance point 951 at the position where the difference occurs is an inflection point of the detection distance point sequence.

  Even in the scene of FIG. 7, an inflection point 973 occurs in the point sequence of the detection distance, but the variation tendency (point row shape) of the point sequence near the inflection point 973 is different from the scene of FIG. That is, in the scene of FIG. 7, if distance detection is performed in the order of the left parked vehicle 63 and the right parked vehicle 64, the parked vehicle 63 will remain for a while after the host vehicle has passed the front of the parked vehicle 63. The distance detection for continues. The value of the detection distance during that time gradually increases as the host vehicle leaves the parked vehicle 63. Thereafter, when the distance detection for the left parked vehicle 63 ends, the distance detection for the right parked vehicle 64 starts immediately. When the distance detection for the right parked vehicle 64 is started, the value of the detected distance gradually decreases as the host vehicle approaches the parked vehicle 64 until the host vehicle comes to the front of the parked vehicle 64. Thereafter, when the host vehicle comes to the front of the parked vehicle 64, a point of the detection distance is detected along the front of the parked vehicle 64.

  In this way, at the boundary between the left parked vehicle 63 and the right parked vehicle 64 (a break between obstacles), a point sequence of detection distances with respect to the parked vehicle 63 and a point sequence of detection distances with respect to the parked vehicle 64 are V-shaped. Is formed. The point 973 of the V-shaped apex becomes an inflection point.

  In this way, in the scenes of FIGS. 6 and 7, an inflection point is generated in the point sequence of the detection distance at the position of the obstacle break. Further, as described above, the scene of FIG. 6 and the scene of FIG. 7 are different in the pattern of inflection points, in other words, the shape of the point sequence around the inflection points. Therefore, in S27, processing for detecting the inflection point corresponding to the scene of FIG. 6 (processing of FIG. 21) and processing for detecting the inflection point corresponding to the scene of FIG. 7 (processing of FIG. 26) are performed in parallel. And run. First, an inflection point detection method in the scene of FIG. 6 will be described.

  FIG. 21 is a detailed flowchart of S27, and is a flowchart of processing for detecting an inflection point in a scene where an offset obstacle is arranged adjacently (scene in FIG. 6). FIG. 22 is a diagram for explaining the processing of FIG. 21, and is a diagram of the same scene as FIG. When the processing shifts to the processing in FIG. 21, first, a frame 500 (search section) for searching for an inflection point is set for the point sequence of the detection distance (S81). An inflection point is searched from within the frame 500. As shown in FIG. 22, assuming that the X axis is set in a direction corresponding to the direction in which the point sequence changes, and the Y axis is set at right angles to the X axis, the frame 500 has a predetermined width W1 ( For example, it is a frame having about 1 to 2 m. The width in the depth direction (Y-axis direction) of the frame 500 is set to a sufficiently long finite length or infinite length so that all the detection distance points included in the left-right width W1 fall within the frame 500. In addition, in which section of the detection distance point sequence the frame 500 is set, the setting position of the frame 500 is determined so that, for example, the latest detection distance point is located at the end of the frame 500.

  The X axis and the Y axis are set at the start of the process in FIG. 8, for example. Specifically, for example, the own vehicle position at the start of the process is the origin, the X axis is the traveling direction of the own vehicle, and the direction perpendicular to the X axis. Is set to a coordinate system having a Y axis.

  Next, a difference ΔL1 between the maximum value and the minimum value of the detection distance within the frame 500 is calculated (S82). In the example of FIG. 22, assuming that the rightmost point 962 in the frame 500 is the maximum value of the detection distance and the minimum value of the detection distance of the leftmost point 961, the difference ΔL1 between the detection distances 961 and 962 is calculated. Is done.

  Next, it is determined whether or not the difference ΔL1 is greater than or equal to a predetermined threshold value TH1 (S83). If it is less than the threshold value TH1 (S83: No), it is determined that there is no portion offset in the depth direction (Y-axis direction) in the point sequence in the frame 500, and the processing in FIG. By the determination in S83, the point sequence 9 illustrated in FIG. 23, that is, the point sequence 9 that hardly fluctuates in the depth direction within the frame 500 (the difference ΔL1 is small) is erroneously determined as having an inflection point. Can be prevented.

  When the difference ΔL1 is greater than or equal to the threshold value TH1 (S83: Yes), a detection distance range in which the difference from the maximum detection distance is a predetermined amount or less is set in the frame 500 (S84). Specifically, as shown in FIG. 22, a position 501a of a certain amount (for example, about 10 cm) from the maximum detection distance point (maximum distance point) 962 in the Y-axis direction, and a distance maximal point 962 from the Y-axis direction. A range 501 between a certain amount (for example, about 10 cm) of the position 501b is set in the opposite direction (front side) (S84). Hereinafter, the range 501 is referred to as an in-frame range. At this time, the width of the in-frame range 501, that is, the certain amount is set not to be too large. If it is too large, the detection distance point that fluctuates in the depth direction is also included in the in-frame range 501, and the presence or absence of the point sequence tendency of the offset obstacle (column 82) cannot be accurately determined.

  Next, the width W2 of the point sequence 963 included in the in-frame range 501 is calculated (S85). Specifically, the sensor positions when both end points 951 and 962 of the point sequence 963 are detected are read from the memory 111, and the difference between the two read sensor positions is calculated as the width W2 of the point sequence 963.

  Next, it is determined whether the point sequence width W2 is greater than or equal to a predetermined threshold value TH2 (S86). If it is less than the threshold TH2 (S86: No), it is determined that the scene is not an offset obstacle, and the process of FIG. By the determination in S86, the scene illustrated in FIG. 24, that is, the scene where only the parked vehicle 63 is arranged can be excluded. That is, in the example of FIG. 24, since the width W2 of the point sequence 963 included in the in-frame range 501 is small, the processes after S86 are not executed.

  If the point sequence width W2 is greater than or equal to the threshold value TH2 (S86: Yes), it is next determined whether or not any end point of the point sequence in the frame 500 is included in the in-frame range 501 (S87). . In the example of FIG. 22, the right end point 962 in the frame 500 is included in the in-frame range 501. The end point 962 is also the maximum distance point with the maximum detection distance in the frame 500. If the end point is not included in the in-frame range 501 (S87: No), the process of FIG. By the determination in S87, the scene illustrated in FIG. 25, that is, the scene where the two parked vehicles 63 and 64 are arranged without offset can be excluded. In the example of FIG. 25, both end points 964 in the frame 500 are outside the in-frame range 501 even if the width W2 of the point sequence included in the in-frame range 501 is not less than the threshold value TH2. The processes after S87 are not executed. Note that the inflection point in the scene of FIG. 25 is detected by the process of FIG.

  If any of the end points is included in the in-frame range 501 (S87: Yes), it is determined that there is an inflection point related to the offset obstacle in the frame 500 (S88). For example, the end point 951 of the point sequence 963 included in the in-frame range 501 (the end point on the maximum distance point 961 side) is set as the inflection point (S88). Then, the process of FIG. 21 is complete | finished.

  Note that the process of S21 is repeatedly executed on the condition that there is no large distance difference every time the time is updated in S31 of FIG. The frame 500 is set, for example, based on the latest detection distance point. Therefore, the frame 500 slides in the X-axis direction over time.

  Next, an inflection point detection method in the scene of FIG. 7 will be described. FIG. 26 is a detailed flowchart of S27, and is a flowchart of processing for detecting an inflection point in the scene of FIG. 7, that is, an inflection point in a scene where the two parked vehicles 63 and 64 are arranged without being offset. It is. FIG. 27 is a diagram for explaining the processing of FIG. 26, and is a diagram of the same scene as FIG. 26, first, a frame 600 having a predetermined width W3 (for example, about 1 m to 2 m) in the left-right direction, similar to the frame set in the previous S81, with respect to the point sequence of the detection distance (search). (Section) is set (S91). The frame 600 is set so that, for example, the point of the latest detection distance is located at the end in the frame 600.

  Next, the value Lmax of the point PosMax (maximum distance point) of the detection distance in the frame 600 and the value Ledge1 of one end point Edge1 (hereinafter referred to as the first end point) of the point sequence in the frame 600. The difference (Lmax−Ledge1) is calculated (S92). In the example of FIG. 27, the difference between the detection distance of the point 973 and the detection distance of the point 975 is calculated.

  Next, a difference (Lmax−Ledge2) between the value Lmax of the maximum distance point PosMax and the value Edge2 of the other end point Edge2 (hereinafter referred to as the second end point) of the point sequence in the frame 600 is calculated (S93). . In the example of FIG. 27, the difference between the detection distance of the point 973 and the detection distance of the point 976 is calculated.

  Next, the point sequence width W4 between the maximum distance point PosMax and the first end point Edge1 is calculated (S94). Specifically, the sensor position when the maximum distance point PosMax is detected and the sensor position when the first end point Edge1 is detected are read from the memory 111, and the difference between the two sensor positions is set as a point sequence width W4. calculate.

  Next, a point sequence width W5 between the maximum distance point PosMax and the second end point Edge2 is calculated (S95). Specifically, the sensor position when the maximum distance point PosMax is detected and the sensor position when the second end point Edge2 is detected are read from the memory 111, and the difference between the two sensor positions is set as a point sequence width W5. calculate.

  Next, it is determined whether or not all of the following conditions S96 to S101 are satisfied. That is, it is determined whether or not the difference (Lmax−Ledge1) calculated in S92 is equal to or greater than a predetermined threshold TH3 (S96). Further, it is determined whether or not the difference (Lmax−Ledge2) calculated in S93 is equal to or greater than a predetermined threshold TH3 (S97). Further, it is determined whether or not the first end point Edge1 is different from the maximum distance point PosMax (S98). Further, it is determined whether or not the second end point Edge2 is different from the maximum distance point PosMax (S99). Further, it is determined whether or not the point sequence width W4 calculated in S94 is equal to or greater than a predetermined threshold value TH4 (S100). Further, it is determined whether the point sequence width W5 calculated in S95 is equal to or larger than a predetermined threshold TH4 (S101).

  When all the conditions of S96 to S101 are satisfied, it is assumed that the shape of the point sequence in the frame 600 is V-shaped, and that two obstacles are arranged adjacent to each other with no offset in the frame 600. It is determined that there is an inflection point related to the scene (S102). Then, the maximum distance point PosMax is set as an inflection point (S102). In the example of FIG. 27, the point 973 is detected as an inflection point. Thereafter, the processing in FIG. 26 is terminated.

  On the other hand, if even one of the conditions of S96 to S101 is not satisfied, the process in FIG. 26 is terminated assuming that the two obstacles are not adjacent to each other without an offset. Note that the processing of S26 is repeatedly executed on condition that there is no large distance difference point every time the time is updated in S31 of FIG. The setting of the frame 600 is set based on, for example, the latest detection distance point. Therefore, the frame 600 slides in the X-axis direction over time.

  Returning to the processing of FIG. 8, it is next determined whether or not there is an inflection point in the detection distance point sequence based on the determination result of S27 (S28). When there is an inflection point, that is, when it is determined that there is an inflection point in S88 of FIG. 21 or S102 of FIG. 26 (S28: Yes), the detection distance of the inflection point detected in S88 or S102 is the boundary. Grouping is performed (S29). In the example of FIG. 6, grouping is performed with the point sequence 94 of the detection distance with respect to the parked vehicle 63, and grouping is performed with the point sequence 95 of the detection distance with respect to the column 82. Further, in the example of FIG. 7, grouping is performed using the detection distance point sequence 971 for the left parked vehicle 63, and grouping is performed using the detection distance point sequence 972 for the right parked vehicle 64. Thereafter, the process proceeds to S30, and the above process is repeated until the end condition of the process of FIG. 8 is satisfied (S30: No). Then, in S13 of FIG. 13 after the processing of FIG. 8 is finished, curve approximation is performed for each history of detection distances grouped by the processing of FIG.

  In S28, when there is no inflection point (S28: No), it is determined that there is still no break of the obstacle, grouping is not performed, the process proceeds to S30, and the process termination condition in FIG. S30: No), the above process is repeated.

  As described above, according to the present embodiment, when a distance difference large point having a large distance difference exists in the point sequence of the detection distance, it is determined whether the distance difference large point is noise or an obstacle break. it can. Therefore, even if noise is mixed in the point sequence of the detection distance, the detection distance can be accurately grouped. Further, when the distance difference is small, it is determined whether or not there is an inflection point in the detection distance point sequence. Therefore, even if there is an adjacent obstacle, it is possible to accurately detect the break of the obstacle. Moreover, since the presence or absence of the inflection point is determined without differentiating the history of the detection distance, the determination can be performed accurately. Since the detection distance has some error, the history of the detection distance varies finely regardless of whether or not there is an inflection point. Therefore, even if the differential value of the history of the detection distance is seen, the presence or absence of an inflection point cannot be detected accurately.

  The obstacle detection device according to the present invention is not limited to the above-described embodiment, and various modifications are possible without departing from the scope of the claims. For example, in the above-described embodiment, the scene where the parked vehicle and the pillar are arranged is described as an example of the detection scene of the inflection point of the offset obstacle, but the obstacle other than the parked vehicle and the pillar is arranged. The present invention can also be applied to scenes. For example, the present invention can also be applied to a scene in which a curb is disposed adjacent to a parked vehicle, as in the scene of FIG.

DESCRIPTION OF SYMBOLS 1 Parking assistance apparatus 2 Ranging sensor 5 Own vehicle 11 ECU
63, 64 Parked vehicle 82 Pillar 91 Distance difference large point

Claims (15)

Distance detecting means (2) for sequentially detecting the distance to the obstacle when the host vehicle (5) is moving along the side of the obstacle (63, 64, 82);
A first determination is made as to whether or not there is a large distance difference point (91) that is a point of a detection distance where a difference from a detection distance of an adjacent point in the point sequence of detection distances detected by the distance detection means is a predetermined amount or more. Determining means (S22),
Second determining means for determining whether the position of the distance difference large point is a break of an obstacle or whether the distance difference large point is noise when the first determining means determines that the distance difference large point is present. (S23, S24),
First grouping means (S26) for performing grouping of the point sequence of the detection distance with the large distance difference point as a boundary when the second determination means determines that it is an obstacle break;
An obstacle detection device (1) comprising:   The obstacle detection device according to claim 1, further comprising a noise processing unit (S25) for processing the noise when the second determination unit determines that the noise is detected. An inflection point detection means (S27) for detecting an inflection point of the point sequence of the detection distance when the first determination means determines that there is no large distance difference point;
Second grouping means (S29) for performing grouping of the point sequence of the detection distance at the inflection point detected by the inflection point detection means;
The obstacle detection device according to claim 1, further comprising:   The second determination means includes a point sequence (92) of a previous distance point that is a point of the detection distance before the distance difference large point and a point of the detection distance after the distance difference large point. 4. The method according to claim 1, wherein it is determined whether the obstacle is a break or noise based on the presence or absence of continuity with the point sequence (93) of the distance points. 5. Obstacle detection device. The second determination means includes
A first continuity range (410, 430, 450), which is a range in which continuity is established with the point sequence of the previous distance point, is set based on a variation tendency of the point sequence of the previous distance point. 1 range setting means (S41);
A second continuity range (420, 440, 460), which is a range in which continuity is established with the point sequence of the rear distance points, is set based on the variation tendency of the point sequence of the rear distance points. Two range setting means (S42);
While the rear distance point is included in the first continuity range and the front distance point is included in the second continuity range, the rear distance point is determined not to be an obstacle break, while the rear A break determination means (S43) that determines a break of an obstacle when at least one of a distance point deviates from the first continuity range and a previous distance point deviates from the second continuity range is established. To the obstacle detection device according to claim 4. The first range setting means (S51 to S53) includes a lower limit value (412, 432) of the detection distance in which continuity is established between the area of the rear distance point and the point sequence of the previous distance point; An upper limit value (411, 431) is set on the basis of the fluctuation tendency of the point sequence of the previous distance point, and a first range (410, 430) sandwiched between the lower limit value and the upper limit value is set as the first continuity range. Set as
The second range setting means (S51 to S53) includes a lower limit value (421, 441) of the detection distance that establishes continuity with the point sequence of the rear distance point with respect to the region of the front distance point, and An upper limit value (422, 442) is set based on the variation tendency of the point sequence of the rear distance point, and a second range (420, 440) sandwiched between the lower limit value and the upper limit value is set as the second continuity range. The obstacle detection device according to claim 5, wherein the obstacle detection device is set as follows. The first range setting means sets a range obtained by expanding the first range by a predetermined amount as the first continuity range,
The obstacle detection device according to claim 6, wherein the second range setting unit sets a range obtained by expanding the second range by a predetermined amount as the second continuity range. The first range setting means (S61, S62) calculates the estimated value (451) of the detection distance that establishes continuity with the point range of the previous distance point with respect to the region of the rear distance point. Set based on the variation tendency of the point sequence of the distance points, set a range (450) in which the difference from the estimated value is equal to or less than a predetermined amount as the first continuity range,
The second range setting means (S61, S62) provides the estimated value (461) of the detection distance that establishes continuity with the point range of the rear distance point with respect to the area of the front distance point. 6. The range according to claim 5, wherein the second continuity range is set based on a variation tendency of a point sequence of distance points, and a range (460) in which a difference from the estimated value is equal to or less than a predetermined amount is set. The obstacle detection device described. The first range setting means assumes that in the section after the point sequence of the previous distance point, the detection distance varies linearly by an amount corresponding to the amount of variation in the predetermined section of the point sequence of the previous distance point. Set the first continuity range;
The second range setting means assumes that the detection distance fluctuates linearly by an amount corresponding to a fluctuation amount in a predetermined section of the point sequence of the rear distance point in a section before the point sequence of the rear distance point. The obstacle detection device according to any one of claims 5 to 8, wherein the second continuity range is set.   The noise processing means linearly interpolates the section of the distance difference large point using the detection distance points (921, 931) before and after the distance difference large point, and comes to the position (911) where the linear interpolation is performed. The obstacle detection apparatus according to claim 2, wherein the large point of distance difference is corrected as described above.   The obstacle detection device according to claim 2, wherein the noise processing unit invalidates the distance difference large point. The lateral direction of the host vehicle is the depth direction,
The inflection point detection means is disposed at a position adjacent to the first obstacle and offset from the first obstacle in the depth direction. It comprises first detection means (S81 to S88) for detecting the first inflection point (951) of the point sequence (94, 95) of the detection distance with respect to the second obstacle (82) made. The obstacle detection device according to claim 3.   The first detection means applies a frame (500) having a predetermined width in a first direction corresponding to the traveling direction of the host vehicle to the point sequence of the detection distance while sliding in the first direction. The width of the detection distance point sequence (963) in which the difference between the maximum value and the minimum value of the detection distance is equal to or greater than a predetermined amount, and the difference from the maximum value within the frame is equal to or less than the predetermined amount. If any end point (962) that is equal to or greater than a predetermined value and is located at the end of the point sequence of the detection distance in the frame is included in the point sequence constituting the width, The obstacle detection device according to claim 12, wherein the first inflection point is detected from the inside of the frame as the first inflection point exists. The lateral direction of the host vehicle is the depth direction,
The inflection point detection means includes a first obstacle (63) disposed on a side of the host vehicle and a first obstacle adjacent to the first obstacle and not offset in the depth direction from the first obstacle. A second detection means (S91 to S102) for detecting a second inflection point (973) of the point sequence (971, 972) of the detection distance with respect to three obstacles (64) is provided. The obstacle detection device according to any one of 3, 12, and 13. The second detection means is fitted to the point sequence of the detection distance while sliding a frame (600) having a predetermined width in a first direction corresponding to the traveling direction of the host vehicle in the first direction,
The value of the maximum distance point (973) that is the point of the maximum detection distance in the frame and the value of the first end point (975) that is one end point of the point sequence of the detection distance in the frame The difference is greater than or equal to a predetermined threshold, and the difference from the value of the second endpoint (976), which is the other endpoint, is greater than or equal to a predetermined threshold, and
The width of the point sequence of the detection distance between the maximum distance point and the first end point is equal to or greater than a predetermined threshold, and
The width of the point sequence of the detection distance between the maximum distance point and the second end point is equal to or greater than a predetermined threshold, and
The distance maximum point and the first end point are different, and
The obstacle detection device according to claim 14, wherein when the maximum distance point is different from the second end point, the maximum distance point is set as the second inflection point.

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