JP2012014298A - Vehicle route estimation device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To improve an estimation accuracy of a route of an own vehicle without using a yaw rate sensor, in other words, using only object detecting means for detecting objects in front of the vehicle.SOLUTION: A vehicle route estimation device includes: object detecting means mounted on a vehicle for detecting objects in front of the vehicle; stationary object determination means determining whether a detected object is a stationary object or not; means for selecting two position data based on the speed of the vehicle from time-series position data of the stationary object projected on a two-dimensional coordinates with the position of the vehicle defined as an origin; means for calculating the locus of the stationary object from a circle which has the center on an X axis and passes through the selected two position data in the two-dimensional coordinates; and means for calculating a turning radius of the vehicle based on the locus of the stationary object.

Description

  The present invention relates to a vehicle traveling path estimation device, and more particularly to detecting a stationary object in front of a vehicle and estimating a traveling path of the vehicle from its position information.

  Patent Document 1 discloses a traveling path estimation device for a vehicle. In this traveling path estimation device, the traveling path of the host vehicle is estimated from data representing the traveling state of the host vehicle with respect to the detected obstacle without using a yaw rate sensor.

JP-A-8-132997

  In the traveling path estimation apparatus described in Patent Document 1, it is necessary to use output values of various sensors such as a rudder angle sensor in place of the yaw rate sensor in order to obtain data representing the traveling state of the host vehicle with respect to the detected obstacle. There is. In addition, the estimation accuracy of the traveling path of the host vehicle may be lowered due to the superimposition of the error of the output value of each sensor.

  Therefore, the present invention reduces or eliminates the problems of the prior art, that is, without using a yaw rate sensor, in other words, using only object detection means for detecting an object in front of the vehicle, The purpose is to improve the estimation accuracy.

  The present invention provides a traveling path estimation device for a vehicle. The traveling path estimation device includes: an object detection unit that detects an object in front of the vehicle; a stationary object determination unit that determines whether the detected object is a stationary object; Means for selecting two position data based on the speed of the vehicle from time-series position data of a stationary object projected on the two positions data having a center on the X axis and selected on two-dimensional coordinates Means for calculating the trajectory of the stationary object from a circle passing through the vehicle, and means for calculating the turning radius of the vehicle from the trajectory of the stationary object.

  According to the present invention, in order to focus on time-series position data for one stationary object, only the object detection means is used regardless of road conditions or the like in an environment where one or more stationary objects exist. Thus, it is possible to accurately estimate the traveling path of the host vehicle. In addition, since estimation can be performed using only two points of data, a single stationary object can be estimated multiple times with different combinations of data, so even if unusual data appears, it is excluded from other estimation results. It becomes possible. Furthermore, since the distance between the two data can be set according to the vehicle speed, the traveling path of the host vehicle can be estimated within the target error range between the two points.

  According to one aspect of the present invention, the means for calculating a deviation amount in the X-axis direction between the calculated vehicle trajectory and each of the time-series position data of the stationary object, and the deviation amount and the predetermined threshold value Means for determining the accuracy of the turning radius of the vehicle from the comparison.

  According to one aspect of the present invention, it is possible to maintain and promote highly accurate estimation by comparing the estimated trajectory and actual data, and if the error is large, stop estimating the traveling path of the host vehicle. It becomes.

  According to an aspect of the present invention, there is provided means for calculating a yaw rate of a vehicle from a turning radius obtained for each stationary object when a plurality of stationary objects are present, and estimating a traveling path of the vehicle from an average value of the calculated yaw rates. Further prepare.

  According to one aspect of the present invention, when a plurality of stationary objects can be detected, by averaging the calculated yaw rates (turning radii), if an abnormal value is estimated, The influence can be reduced.

It is a block diagram which shows the structure of the advancing route estimation apparatus of the vehicle according to one Example of this invention. It is a figure for demonstrating the attachment position of an object detection means etc. according to one Example of this invention. It is a figure which shows the processing flow in a control unit according to one Example of this invention. It is a conceptual diagram of the positional information on the detected object candidate according to one Example of this invention. It is a figure which shows the log | history (position change) of the detected stationary object according to one Example of this invention. It is a figure for demonstrating the selection method of two position data according to one Example of this invention. It is a figure which shows the relationship between the distance (DELTA) Y between two position data, and the vehicle speed V according to one Example of this invention. It is a figure showing the error (shift | offset | difference) in the horizontal (X) direction of the locus | trajectory (turning radius) of a vehicle and an actual position coordinate according to one Example of this invention. It is a block diagram which shows the flow which leads to the average value calculation of a yaw rate according to one Example of this invention.

  Embodiments of the present invention will be described with reference to the drawings. FIG. 1 is a block diagram showing a configuration of a traveling path estimation device for a vehicle according to an embodiment of the present invention. The traveling path estimation device is based on a radar 10, a control unit 12 for estimating a traveling path of a vehicle based on object information (position, distance, etc.) acquired by the radar 10, and a control signal from the control unit 12. And a speaker 14 that generates a warning by sound or voice, and a display device 16 that performs a display for causing the driver to recognize an object around the vehicle from the object information acquired by the radar 10.

  The radar 10 corresponds to, for example, a scanning laser radar, and receives the reflected light from the object of the beam scanned in each direction, thereby detecting the position (region) of the object (candidate) in each direction as a detection point and Detect distance. The radar 10 may be another type of radar (for example, a millimeter wave radar). Further, instead of the radar 10, a camera such as an infrared camera may be used. Furthermore, in a vehicle provided with a navigation device, the corresponding function provided in the navigation device may be used as the speaker 14 and the display device 16.

  The control unit 12 of FIG. 1 has the functions indicated by blocks 121 to 128 as its configuration (function). That is, the control unit 12 receives a detection signal from the radar 10 and detects an object in front of the vehicle, an object detection unit 121, a stationary object determination unit 122 that determines whether the detected object is a stationary object, Means 123 for selecting two position data based on the speed of the vehicle from time-series position data of a stationary object projected on the two-dimensional coordinates with the vehicle position as the origin, and the X axis on the two-dimensional coordinates It functions as means 124 for calculating the trajectory of the stationary object from the circle passing through the two selected position data having the center above, and means 125 for calculating the turning radius of the vehicle from the trajectory of the stationary object.

  The control unit 12 further includes means 126 for calculating a deviation amount in the X-axis direction between the calculated vehicle trajectory and each of the time-series position data of the stationary object, and the deviation amount and a predetermined threshold value. From the comparison, the means 127 for determining the accuracy of the turning radius of the vehicle, and when there are a plurality of stationary objects, the yaw rate of the vehicle is calculated from the turning radius obtained for each stationary object, and the average value of the calculated yaw rate is calculated. It also functions as means 128 for estimating the traveling path.

  The control unit 12 is further required to receive detection signals from a vehicle speed sensor, a brake sensor, a yaw rate (a change speed of the rotation angle in the turning direction) that detects the speed (vehicle speed) of the host vehicle, and the like. It has a function to perform processing. The processing includes generating a control signal for performing braking control of the vehicle based on the estimation result of the traveling path of the vehicle, various sensor values, and the like.

  The function of each block is realized by a computer (CPU) included in the control unit 12. The configuration of the control unit 12 may be incorporated in the navigation device.

  The control unit 12 includes, for example, an A / D conversion circuit that converts an input analog signal into a digital signal, an image memory that stores a digitized image signal, and a central processing unit (CPU) that performs various arithmetic processes. , RAM used by the CPU to store data for computation, ROM for storing programs executed by the CPU and data used (including tables and maps), driving signals for the speaker 14 and display signals for the display device 16 are output. Output circuit.

  FIG. 2 is a diagram for explaining a mounting position of the radar 10 or the like shown in FIG. 1 according to one embodiment of the present invention. For example, as shown in FIG. 2, the radar 10 is disposed on the front bumper portion of the vehicle 20 at the center in the vehicle width direction. Reference numeral 16 a in FIG. 2 shows an example in which a head-up display (hereinafter referred to as “HUD”) is used as the display device 16. As shown in the figure, the HUD 16a is provided such that the display screen is displayed at a position that does not obstruct the front view of the driver of the front windshield of the vehicle 20.

  FIG. 3 is a process flow executed by the control unit 12 according to one embodiment of the present invention. This processing flow is executed at predetermined time intervals by the CPU of the control unit 12 calling a processing program stored in the memory.

  In step S10, the position of the object in front of the vehicle is specified by receiving a signal from the radar 10. An arbitrary method can be used for the identification, for example, as follows.

  A scanning laser radar is used as the radar 10, and the position of an object, for example, an obstacle candidate is specified from the width of the detection point group. Specifically, the scanning laser radar measures the distance to the object in each direction as a detection point by receiving reflected light from the object of the beam scanned in each direction. A set of detection points is obtained by plotting the positions of these detection points on a two-dimensional coordinate system (see FIG. 2) having the laser radar position as the origin, the Y-axis as the front direction of the radar, and the X-axis as the horizontal direction. From these set of detection points, detection point groups are grouped as detection point groups whose mutual distance between detection points is equal to or smaller than a predetermined value, and among the grouped detection point groups, those having a spread width equal to or smaller than a predetermined value are grouped as predetermined objects. The position is identified as a candidate (for example, an obstacle candidate). The position information of the detected object candidates is sequentially stored in the memory as time series information.

  FIG. 4 is a conceptual diagram of position information of detected object candidates. In FIG. 4, a total of eight objects 23 of 1 to 8 are detected in a region 22 that can be detected by the radar in the traveling direction 21 of the vehicle 20 represented by XY coordinates. The eight objects 23 can include both stationary objects and other objects.

  In step S11, it is determined whether or not the detected object is a stationary object. The determination is made, for example, based on whether or not the relative speed between the host vehicle and the detected object, that is, the difference between the host vehicle speed and the amount of movement of the detected object per unit time is equal to or less than a predetermined value. Or you may determine by calculating | requiring the movement vector of a detection object, and the magnitude | size being below a predetermined value. If this determination is Yes, the process proceeds to the next step S12, and if No, the process ends.

In step S12, it is determined whether the distance (position) of the stationary object is correctly obtained as time series data. FIG. 5 is a diagram showing a history (position change) of a detected stationary object. In FIG. 5, a plurality of position data (X _max , Y _max ) to (X _min , Y _min ) are recorded as the history of the stationary object along the arc A on the XY coordinates where the position of the vehicle 20 is the origin (0, 0). )It is shown. Details of FIG. 5 will be described later. The determination in step S12 is performed based on, for example, whether or not the relationship of the following expression (1) is established using the Y coordinate value of the position data. By determining the expression (1), it is possible to detect whether the position (distance) of the stationary object is closer (shorter) to the vehicle as the vehicle travels.

Y _max >...> Y _min (1)

If this determination is Yes, the process proceeds to the next step S13, and if No, the process ends.

  In step S13, it is determined whether there are two or more time-series position data of each detected stationary object. If this determination is Yes, the process proceeds to the next step S14, and if it is No, the process returns to step S10 to repeat data acquisition.

  In step S14, it is determined whether the amount of change (deg / s) in the yaw rate detected by the yaw rate sensor is within a predetermined value. This is because the estimation process is stopped when the vehicle has an unstable trajectory such as a curve entrance or a winding road and the yaw rate change amount is large. If this determination is Yes, the process proceeds to the next step S15, and if No, the process ends.

  In step S15, two position data are selected from time-series position data of each stationary object on two-dimensional (XY) coordinates. FIG. 6 is a diagram for explaining a method of selecting two position data. FIG. 6 illustrates two methods (a) and (b). These two methods can be used properly according to the situation such as the running state of the vehicle, or both can be used simultaneously. In (a) and (b), time-series position data P1 to P8 of one stationary object along the arc A on the XY coordinates are shown. The meanings of arcs A and B and their calculation will be described later.

  In (a), two data P1 and P6 are first selected (No1). Next, P2 next to P1 (front) and P7 next to P6 (front) are selected (No2). Similarly, P3 next to P2 next (front) and P8 next to P7 (front) are selected (No2). Thus, in (a), the position of the data pair is sequentially shifted in the direction approaching the vehicle 20. At that time, the distance between the two positions constituting the data pair is selected to be substantially constant. In this case, a plurality of data pairs can be obtained for one stationary object, and the trajectory of the stationary object and the course of the vehicle, which will be described later, are used to estimate the accuracy of the estimation. In addition, since different data is used every time, even if the data fluctuates greatly, the influence can be eliminated. However, it is difficult to acquire data over a long distance.

  On the other hand, in (b), one side of the data pair is fixed at the first position P1, and the other party of the pair is sequentially shifted in the direction approaching the vehicle 20 with P6 (No1), P7 (No2), and P8 (No3). In this case, since a plurality of data pairs can be obtained over a long distance for one stationary object, it is possible to improve the estimation accuracy of the vehicle course as compared with the case of (a). However, if the error of the first data (P1 in FIG. 6) is large, the influence is exerted in all estimations, so it is important that the error of the first data is small.

  In step S16, it is determined whether or not the distance between the two selected position data is greater than or equal to a predetermined value. FIG. 7 is a diagram showing the relationship between the distance ΔY between the two position data and the vehicle speed V. 7 is stored in advance in the memory of the control unit 12 as a map (table). The distance between the two position data needs to be determined so that the finally estimated turning radius or yaw rate has a predetermined accuracy. In the present invention, the distance between the two position data is determined so that the maximum error in the lateral (X) direction is not more than a predetermined value in consideration of the deviation accuracy of the radar in the lateral (X) direction. Since this maximum error varies depending not only on the distance but also on the vehicle speed, in FIG. 7, a range in which the maximum error is equal to or less than a predetermined value is set using two parameters of the distance ΔY and the vehicle speed V.

  That is, the maximum error can be set to 0.5 (deg / s) or less by selecting the distance ΔY in the range above the straight line C in FIG. The value of 0.5 (deg / s) is an example of the accuracy of the radar, and can be arbitrarily set from the performance of the radar. From FIG. 7, for example, when the vehicle speed V is about 40 km / s, the distance ΔY needs to be about 25 m or more, and when the vehicle speed V is about 80 km / s, the distance ΔY needs to be about 45 m or more. Therefore, the predetermined value in step S16 is determined according to the vehicle speed V. When it is assumed that the maximum error is 0.5 (deg / s) or more, for example, the vehicle speed V is 25 m at 40 km / s. If this determination is Yes, the process proceeds to the next step S17, and if No, the process returns to the first step S10 to repeat the process.

In step S17, the locus of the stationary object and the locus of the vehicle (turning radius) are calculated. This calculation method will be described with reference to FIG. In FIG. 5, it is assumed that the two selected position data are positions (points) specified by coordinates (X _max , Y _max ) and (X _min , Y _min ). Assuming a circle that first passes through these two points and has a center on the X axis, it is possible to draw a circle whose part is represented as an arc A. This arc A represents the trajectory of a stationary object. If the center of the circle is (R, 0) and the distance to the intersection of the origin (0, 0) and the X axis of the arc A is d, then the following two equations (2) from the equation representing the circle: (3) holds.

(X _max −R) ² + Y _max ² = (R + d) ² (2)
(X _min −R) ² + Y _min ² = (R + d) ² (3)

From these two equations, R can be obtained by the following equation (4) using two position coordinates.

This R is the turning radius R of the vehicle 20 as indicated by the arc B in FIG. That is, the trajectory A of the stationary object and further the trajectory B (turning radius R) of the vehicle can be calculated from the two position coordinates. Thus, according to one embodiment of the present invention, the turning radius R of the host vehicle can be estimated (calculated) basically based only on detection information (two position data) from the radar.

  In step S18, an error (deviation) in the lateral (X) direction between the obtained locus A of the stationary object and the actual position coordinates is calculated. FIG. 8 is a diagram showing an error (deviation) in the horizontal (X) direction between the locus of the stationary object and the actual position coordinates. Arc A is the trajectory of the stationary object calculated in step S17, and arc B is the trajectory (turning radius) of the vehicle. Differences d1 to dn in the X direction between the arc A and n position coordinates from (X1, Y1) to (Xn, Yn) are obtained as shown in the figure.

In step S19, it is determined whether or not the error in the X direction is within a predetermined value based on the differences d1 to dn obtained in step S18. Specifically, for example, it is determined whether or not the following two expressions (5) and (6) are satisfied. Note that dmax is the maximum value of the difference d, and α and β are predetermined threshold values.

Σ (absolute value of d) / n <α (5)
dmax <β (6)

  When this determination is Yes, the process proceeds to the next step S20, and the turning radius R of the vehicle calculated in step S17 is output from the control unit as data used in various controls. Thereby, it is possible to use only the turning radius R whose error is equal to or smaller than a predetermined value, in other words, whose estimation accuracy is equal to or larger than the predetermined value. If this determination is No, the process ends.

  In step S21, it is determined whether or not data on a plurality of detected stationary objects, that is, turning radius R is obtained in parallel. If this determination is No, the process proceeds to the next step S22, and if Yes, the process proceeds to step S23.

In step S22, the obtained turning radius R is converted into a yaw rate. Specifically, yaw rate γ is calculated using the following equation (7). V is the vehicle speed.

γ = V / R (7)

Incidentally, since the unit is γ (rad / s) in the case of R (m) and V (m / s), in order to obtain γ (deg / s), γ (rad / s) obtained from equation (7). ) Multiplied by 180 / π.

  In step S23, the average yaw rate is calculated. FIG. 9 is a block diagram showing the flow leading to the calculation of the average yaw rate. FIG. 9 shows an example in which the eight objects 23 in FIG. 4 are detected. In response to a signal from the radar 10, data (position information) of the eight objects 23 is acquired (block 31). A turning radius R corresponding to an object determined as a stationary object is calculated from each data (block 32). The yaw rate γ is calculated for each turning radius R using the vehicle speed V (block 37) (block 33). The details of the above contents are as described in steps S10 to S22 of FIG.

  In block 34, an average value of the obtained yaw rates γ is calculated. As described above, according to one aspect of the present invention, when a plurality of stationary objects can be detected, by averaging the yaw rate, if an abnormal value is estimated, the abnormal value is smoothed and the effect is reduced. It becomes possible to do.

  Further, if the detected yaw rate value from the yaw rate sensor is available, the detected value is acquired (block 38). Then, the difference between the yaw rate detection value after passing through the low-pass filter (block 39) and the average value of the yaw rate is calculated (block 35). The drift amount of the yaw rate sensor can be obtained from this difference value (block 36). This drift amount can be used to correct the output value of the yaw rate sensor. As described above, according to the embodiment of the present invention, the turning radius R and the yaw rate γ can be estimated, and at the same time, the detected value of the yaw rate sensor can be corrected using the estimated values.

  Returning to FIG. 3, in step S24, it is determined whether or not the object detection by the radar 10 is continued. If this determination is Yes, the process returns to Step S10, and a series of processes at a predetermined time interval is repeated. If No, the process ends.

  The embodiment of the present invention has been described above, but the present invention is not limited to such an embodiment, and can be modified and used without departing from the spirit of the present invention. For example, in the above-described embodiment, the radar 10 is arranged on the front bumper portion of the vehicle. However, the radar 10 is not limited to the place, and for example, the radar 10 is arranged inside the front grill and the radar irradiation range is set to a radar transmission film. You may comprise so that it may be covered with.

10 Radar 12 Control unit 14 Speaker 16 Display device 16a HUD
20 Vehicle 22 Radar detection area 23 Detected object (stationary object)

Claims (3)

An object detection means mounted on the vehicle for detecting an object in front of the vehicle;
Stationary object determination means for determining whether the detected object is a stationary object;
Means for selecting two position data based on the speed of the vehicle from time-series position data of a stationary object projected on two-dimensional coordinates with the vehicle position as an origin;
Means for calculating a trajectory of the stationary object from a circle passing through two selected position data having a center on the X axis on the two-dimensional coordinate;
Means for calculating a turning radius of the vehicle from the trajectory of the stationary object;
A traveling path estimation device for a vehicle. Means for calculating a deviation amount in the X-axis direction between the calculated trajectory of the vehicle and each of the time-series position data of the stationary object;
The vehicle travel path estimation device according to claim 1, further comprising means for determining an accuracy of a turning radius of the vehicle from a comparison between the deviation amount and a predetermined threshold value.   The vehicle further comprises means for calculating the yaw rate of the vehicle from the turning radius obtained for each stationary object when there are a plurality of stationary objects, and estimating the traveling path of the vehicle from the average value of the calculated yaw rates. The vehicle traveling path estimation device according to claim 1.

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