JP5453765B2 - Road shape estimation device - Google Patents

Description

  The present invention relates to a road shape estimation apparatus that estimates the shape of a road.

Conventionally, as a device for estimating the shape of a road, as described in JP-A-2005-172590, a device for detecting an object existing in front of the host vehicle, the road shape data acquired from a map database and A device that acquires road shape data ahead of the host vehicle based on a radar detection result is known. This apparatus attempts to estimate a road shape by grouping detection points corresponding to road shapes detected at the same time.
JP 2005-172590 A

  However, such an apparatus has a problem that it is difficult to increase the estimation accuracy of the road shape. That is, in this apparatus, in order to accurately estimate the road shape, it is preferable to detect a large number of detection points indicating the road shape in a short cycle. However, in an actual driving environment, there are cases where objects cannot be continuously detected by radar, and detection of road structures becomes insufficient due to insufficient information on the objects, and it is difficult to improve the accuracy of estimation of road shapes.

  Therefore, an object of the present invention is to provide a road shape estimation device that can improve the estimation accuracy of the road shape.

That is, the road shape estimation apparatus according to the present invention is provided on a vehicle, based on an object detection unit that detects an object existing on the traveling direction side of the vehicle, and an object detection point detected by the object detection unit. is configured to include an estimation means for estimating a road shape, a pre-Symbol object detecting means performs detection of a detection point of the object is repeated in a predetermined cycle, said estimating means, a detection point of the currently detected object calculates the representative points for each group by performing the grouping for the detection points, including the detection point of an object detected before the previous, it calculates a shape line based on the shape of the point sequence of the plurality of representative points, in the shape line based estimates the road shape, the shape lines being calculated sequentially connecting the representative points adjacent to each other, or shall be calculated as a plurality of approximation lines based on the coordinate values of the representative points.

  According to the present invention, the detection points of the object detected this time are grouped with respect to the detection points including the detection points of the object detected before last time, the representative points are calculated for each group, and the point sequence of a plurality of representative points is obtained. By calculating the shape line based on the shape line and estimating the road shape based on the shape line, the road shape can be estimated from a large amount of detection point information, and the estimation accuracy of the road shape can be greatly improved. In addition, the calculation frequency of the road shape can be increased.

  In the road shape estimation apparatus according to the present invention, it is preferable that the estimation means estimate whether the road is curved based on the shape line when the road shape is estimated.

  According to the present invention, the detection points of the object detected this time are grouped with respect to the detection points including the detection points of the object detected before last time, the representative points are calculated for each group, and the point sequence of a plurality of representative points is obtained. A shape line is calculated based on the shape line, and it is estimated whether the road is curved based on the shape line. Thereby, it is possible to estimate whether or not the road is curved based on a large amount of detection point information, and it is possible to greatly improve the estimation accuracy of the road shape.

  Moreover, in the road shape estimation apparatus according to the present invention, when the non-parallel line that is not parallel to the vehicle traveling direction is calculated as the shape line, the estimating means calculates a parallel straight line and a non-parallel line parallel to the vehicle traveling direction. It is preferable to estimate the road shape based on the position of the intersection.

  According to the present invention, the estimation accuracy of the road shape can be improved by estimating the road shape using the detection point of the object detected before the previous time in addition to the detection point of the object detected this time.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In the description of the drawings, the same elements are denoted by the same reference numerals, and redundant description is omitted.

  FIG. 1 is a schematic configuration diagram of a road shape estimation apparatus according to an embodiment of the present invention.

  As shown in FIG. 1, the road shape estimation apparatus according to the present embodiment is an apparatus that is provided in a vehicle M and estimates the shape of a road on which the vehicle M travels. For example, a pre-crash brake assist system, a pre-crash Used as a road shape estimation means such as a seat belt system.

  The road shape estimation apparatus according to the present embodiment includes a radar 1 and an ECU (Electronic Control Unit) 2. The radar 1 functions as an object detection unit that detects an object existing on the traveling direction side of the vehicle M. The radar 1 is attached to the front portion of the vehicle M and is provided to detect the front of the vehicle. The radar 1 repeatedly detects an object at a predetermined cycle in accordance with a control signal from the ECU 2. The predetermined period is, for example, 10 to 200 ms, preferably 50 ms or 100 ms.

  As the radar 1, for example, a millimeter wave radar is used. That is, the radar 1 transmits a radio wave having a predetermined frequency to the detection area and receives an observation wave reflected by an object or the like. By analyzing the received signal, the relative speed of the object with respect to the vehicle M and the distance from the vehicle M can be detected.

  The ECU 2 controls the entire apparatus of the road shape estimation apparatus, and is configured mainly by a computer including a CPU, a ROM, and a RAM, for example. The ECU 2 functions as an estimation unit that estimates the road shape based on the detection point of the object detected by the radar 1. That is, the ECU 2 inputs detection points that are repeatedly detected by the radar 1 at a predetermined cycle, and uses the detection points of the objects detected before this time in addition to the detection points of the objects detected this time, and the shape of the point sequence of the detection points. Based on the above, the road shape is estimated.

  Specifically, the ECU 2 groups the detection points including the detection point of the object detected this time before the previous detection point of the object. And ECU2 calculates a representative point for every grouped group, and calculates a shape line based on the point sequence of a plurality of representative points. Then, the ECU 2 estimates the road shape based on the shape line.

  The road shape estimation device is provided with a vehicle speed sensor 3. The vehicle speed sensor 3 functions as vehicle speed detection means for detecting the traveling speed of the vehicle M, and for example, a wheel speed sensor is used. The vehicle speed sensor 3 is connected to the ECU 2 and inputs a detection signal to the ECU 2.

  The vehicle M is provided with an output unit 4. When the output unit 4 detects an object approaching the vehicle M, the output unit 4 functions as a notification unit that notifies the driver of the vehicle M of the fact. The output unit 4 may be any device as long as it can notify the driver of the approach of the object. For example, the output unit 4 is a device that notifies the occurrence of a failure through vision, such as lamp lighting, LED lighting, and liquid crystal display. A device for notifying the occurrence of a failure is used. The output unit 4 is connected to the ECU 2 and performs a notification operation when a notification instruction signal is output from the ECU 2.

  Next, the operation of the road shape estimation apparatus according to this embodiment will be described.

  FIG. 2 is a flowchart showing an outline of road shape estimation processing of the road shape estimation apparatus according to the present embodiment. The control process of FIG. 2 is repeatedly executed at a predetermined cycle by the ECU 2, for example.

  First, as shown in S10 of FIG. 2, the sensor output value is read. That is, the detection signal of the radar 1 and the detection signal of the vehicle speed sensor 4 are read.

  Then, the process proceeds to S12, and detection point grouping processing is performed. The grouping process is a process for grouping detection points of objects detected by the radar 1. In this grouping process, calculation of detection points by detection of the current radar 1 is performed, and grouping is performed on detection points including detection points of previous and previous objects in the detection points of the current object. The calculation of the detection point of the object is performed based on the detection signal of the radar 1. As detection points of the object detected before the previous time, for example, past 10 cycles (detection point data 1 to 10 times before this time) are used. The detection point data before the previous time may be shorter or longer than the past 10 cycles.

  Grouping is sequentially performed from an object close to the radar 1. For example, as shown in FIG. 3, grouping ranges g1, g2, g3... Are sequentially set from an object close to the radar 1 installed in the vehicle M, and one detection point exists in the grouping range g (g1 to g6). Set as one group.

  In FIG. 3, the coordinate system in which the detection point d is set may be a two-dimensional one or a three-dimensional one. A grouping range g having a preset size may be used. For example, the grouping range g may have a length of 3 to 6 m and a width of 0.6 to 1.2 m, preferably 5 m, The one with a width of ± 0.875 m is used. The detection points d existing in the same grouping range g are grouped as one group.

  And it transfers to S14 of FIG. 2 and a group selection process is performed. The group selection process is a process of selecting a grouping range g that is effective for estimating the road shape. For example, a grouping range g having a predetermined number or more of object detection points d is selected. For example, 4 is set as the predetermined number. When the number of groups to be selected is greater than a predetermined value, the upper group having the highest number of detection points d is selected from the selected grouping range g. In this case, for example, the top 15 groups are selected.

  In FIG. 3, the grouping ranges g1 to g3, g5, and g6 where the detection point d is a predetermined number or more are selected, and the grouping range g4 where the detection point d is not the predetermined number or more are not selected.

  By performing such a group selection process, detection points that do not contribute to road shape estimation and detection points due to noise can be eliminated, and road shape estimation accuracy can be increased.

  Then, the process proceeds to S16 in FIG. 2, and representative point calculation processing is performed. The representative point calculation process is a process of calculating one representative point among the detection points d in the grouping range g. For example, the representative value is calculated based on the center of gravity of the coordinate value of the detection point d in the grouping range g. At this time, as the weight of the detection point d, it is preferable to determine the center-of-gravity position by weighting the detection point d detected and fixed a predetermined number of times or more than the detection point d not detected a predetermined number of times or more. In addition, when using a long-distance narrow-angle method and a short-distance wide-angle method as the radar 1, the detection point d detected by the long-distance narrow-angle method with high ranging accuracy is detected by the short-distance wide-angle method. It is preferable to determine the position of the center of gravity by weighting more than the detection point d. By determining the center of gravity and calculating the representative point in this way, it is possible to calculate an appropriate representative point based on highly reliable data.

  For example, as shown in FIG. 4, representative points D1 to D3, D5, and D6 are set for the selected grouping ranges g1 to g3, g5, and g6, respectively.

  Then, the process proceeds to S18 in FIG. 2, and connection range setting processing is performed. The connection range setting process is a process of setting a range for connecting representative points. For example, as shown in FIG. 5, predetermined ranges of connection ranges h1 to h3, h5, and h6 are set for the representative points D1 to D3, D5, and D6, respectively. The connection range h is set to a range set in advance with the representative point d as the center, and is set, for example, to a range of ± 10 m vertically and ± 2.625 m horizontally. Other representative points included in the connection range h of the representative point D are set as connection targets.

  And it transfers to S20 of FIG. 2 and the calculation process of a shape line is performed. The shape line calculation process is a process of calculating a shape line indicating a road shape based on a sequence of representative points D. The shape line is set based on the coordinate values of a plurality of representative points that are connected to each other. For example, adjacent representative points may be sequentially connected to form a shape line, or an approximate line based on the coordinate value of the representative point may be calculated and used as the shape line.

  More specifically, as shown in FIG. 6, when the representative points D1 to D3, D5, and D6 are connected, the least square method is used based on the coordinate values of the representative points D1 to D3, D5, and D6. An approximate straight line is calculated as a shape line L.

  Then, the process proceeds to S22 in FIG. 2, and it is determined whether or not there is a straight line in the vehicle traveling direction in the shape line. For example, when one or more shape lines are calculated in S20, it is determined whether or not there is a straight line in the same direction as the traveling direction of the vehicle M. In this case, the same direction includes a direction substantially the same as the vehicle traveling direction, and includes, for example, a direction of ± 5 degrees with respect to the vehicle traveling direction.

  If it is determined in S22 that there is no straight line in the vehicle traveling direction in the shape line, the process proceeds to S26. On the other hand, when it is determined in S22 that there is a straight line in the vehicle traveling direction in the shape line, it is determined whether or not the shape line indicates a curve (S24). For example, as shown in FIG. 6, an intersection point P between the shape line L and the line L1 in the vehicle traveling direction is calculated, and when the intersection point P is located ahead of the position of the vehicle M, the shape line indicates a curve. When the intersection point P is not positioned ahead of the position of the vehicle M, it is determined that the shape line does not indicate a curve.

  In addition, the method for determining whether or not the shape line indicates a curve is not limited to such a method. For example, the determination may be made according to the angle θ formed by the shape line L and the line L1 in the vehicle traveling direction. Good. In FIG. 6, an angle θ between the shape line L and the line L1 in the vehicle traveling direction is calculated, and when the angle θ is larger than a predetermined angle, it is determined that the shape line indicates a curve, and the angle θ Is not larger than the predetermined angle, it is determined that the shape line does not show a curve. For example, 30 degrees is set as the predetermined angle.

  If it is determined in S24 that the shape line indicates a curve, the process proceeds to S26. In S26, a curve recognition process is performed. The curve recognition process is a process for recognizing that the road ahead of the vehicle is curved. For example, a flag indicating curve recognition is set. Then, the process proceeds to S28, where the curve R and the curve center position are calculated. The calculation of the curve R and the curve center position may be performed based on the coordinate value of the shape line L.

  And it transfers to S32 and a filter process is performed. The filtering process is a process of filtering the data of the past curve R and curve center position and the current curve R and curve center position data. When the filter process of S32 is finished, a series of control processes are finished.

  As described above, according to the road shape estimation device according to the present embodiment, the road shape based on the shape of the point sequence of the detection points using the detection point of the object detected this time and the detection point of the object detected before the previous time. , It is possible to make up for the shortage of object information at the present time using past object information. For this reason, it is possible to improve the estimation accuracy of the road shape, and it is possible to suppress a decrease in estimation accuracy due to insufficient object information.

  In addition, the detection points of the object detected this time are grouped with respect to the detection points including the detection point of the object detected before last time, the representative points are calculated for each group, and the shape line based on the point sequence of a plurality of representative points And estimating the road shape based on the shape line, the road shape can be estimated from a large amount of detection point information, and the estimation accuracy of the road shape can be greatly improved. In addition, the calculation frequency of the road shape can be increased.

  In addition, the detection points of the object detected this time are grouped with respect to the detection points including the detection point of the object detected before last time, the representative points are calculated for each group, and the shape line based on the point sequence of a plurality of representative points Is calculated, and it is estimated whether the road is curved based on the shape line. Thereby, it is possible to estimate whether or not the road is curved based on a large amount of detection point information, and it is possible to greatly improve the estimation accuracy of the road shape.

  In addition, embodiment mentioned above shows an example of the road shape estimation apparatus which concerns on this invention. The road shape estimation apparatus according to the present invention is not limited to such a configuration, and the road shape estimation apparatus according to the embodiment is modified or otherwise changed so as not to change the gist described in each claim. It may be applied.

1 is a schematic configuration diagram of a road shape estimation device according to an embodiment of the present invention. It is a flowchart which shows operation | movement of the road shape estimation apparatus of FIG. It is explanatory drawing of the road shape estimation process in the road shape estimation apparatus of FIG. It is explanatory drawing of the road shape estimation process in the road shape estimation apparatus of FIG. It is explanatory drawing of the road shape estimation process in the road shape estimation apparatus of FIG. It is explanatory drawing of the road shape estimation process in the road shape estimation apparatus of FIG.

Explanation of symbols

  DESCRIPTION OF SYMBOLS 1 ... Radar, 2 ... ECU, 3 ... Vehicle speed sensor, 4 ... Output part, M ... Vehicle.

Claims (3)

An object detection means provided on the vehicle for detecting an object present on the traveling direction side of the vehicle;
Estimating means for estimating a road shape based on a detection point of the object detected by the object detecting means;
Configured with
The object detection means repeatedly detects a detection point of an object at a predetermined cycle,
The estimation unit performs grouping on detection points including the detection point of the object detected before the previous detection point of the object detected this time, calculates a representative point for each group, and forms a point sequence of a plurality of representative points A shape line is calculated based on the shape, a road shape is estimated based on the shape line, and the shape line is calculated by sequentially connecting adjacent representative points, or an approximate line based on coordinate values of a plurality of representative points Rukoto is calculated as,
A road shape estimation device characterized by the above. The estimation means estimates whether the road is curved based on the shape line when estimating the road shape.
The road shape estimation apparatus according to claim 1. When the non-parallel line that is not parallel to the vehicle traveling direction is calculated as the shape line, the estimation means estimates the road shape based on the position of the intersection of the parallel straight line parallel to the vehicle traveling direction and the non-parallel line. ,
The road shape estimation apparatus according to claim 1 or 2.

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