JP2021004734A - Route generation device and route generation method - Google Patents

Abstract

To provide a route generation device and a route generation method that can generate an accurate route.SOLUTION: A route generation device of the present invention comprises: a self vehicle information acquisition unit 2 that acquires at least self vehicle information including a self vehicle position, which shows a position of the self vehicle, and a self vehicle azimuth, which shows a driving azimuth direction of the self vehicle; a map information acquisition unit 3 that acquires at least map information including a group of map points, which is a group of a plurality of points along a road on a map; an angle detection unit 4 that detects an angle between the self vehicle azimuth and the direction of each point in front of the self vehicle on the basis of the self vehicle information acquired by the self vehicle information acquisition unit 2 and the map information acquired by the map information acquisition unit 3; a coordinate generation unit 5 that generates n-th order coordinates (n is 2 or bigger) on the basis of the self vehicle information acquired by the self vehicle information acquisition unit 2, the map information acquired by the map information acquisition unit 3, and the angle detected by the angle detection unit 4; and a target route generation unit 6 that generates a target route of the self vehicle on the basis of the coordinates generated by the coordinate generation unit 5.SELECTED DRAWING: Figure 1

Description

The present invention relates to a route generation device and a route generation method for generating a route on which a vehicle travels.

Conventionally, a technique for generating a route on which a vehicle travels has been disclosed (see, for example, Patent Document 1). In Patent Document 1, the center position of the left and right white lines recognized from the image captured by the camera unit in the road width direction is set as the target point, and the target point is identified by a quadratic approximate curve to generate the target route. .. At this time, the coordinates of the candidate points are real spaces in which the vehicle width direction of the own vehicle, that is, the left-right direction is the x-axis, the vehicle height direction of the own vehicle is the y-axis, and the traveling direction of the own vehicle is the z-axis.

Then, in Patent Document 1, the white line candidate points detected on the image and the past white line data estimated based on the movement amount of the own vehicle are combined, and for these data point groups, for example, the least squares method is applied. The trajectory of the white line candidate point represented by the quadratic curve is obtained by applying it. The locus of the white line candidate point is obtained as the left and right curves corresponding to the left and right white lines by the following equation (1). The locus at the center position obtained from each of the left and right curves is used as the target path.

In the formula (1), the coefficients A, B, and C represent the components constituting the path. The coefficient A represents the curvature component of the route, the coefficient B represents the angular component formed by the traveling direction of the vehicle and the route, and the coefficient C represents the position component of the target route with respect to the vehicle in the lateral direction (x-axis direction). There is.

JP-A-2018-154304

Conventionally, a target route is generated by approximating a target point cloud with a curve, but there is a problem that the accuracy of the approximation deteriorates when the road suddenly changes from a straight line to a curve, for example. As described above, conventionally, there is a problem that the accuracy of the approximation may be deteriorated when the point cloud in front of the own vehicle is approximated by a curve, and as a result, an accurate route cannot be generated.

The present invention has been made to solve such a problem, and an object of the present invention is to provide a route generation device and a route generation method capable of generating an accurate route.

In order to solve the above problems, the route generator according to the present invention acquires own vehicle information including at least the own vehicle position indicating the position of the own vehicle and the own vehicle direction indicating the direction in which the own vehicle travels. An information acquisition unit, a map information acquisition unit that acquires map information including a map point group that is a set of at least a plurality of points on a map along a road, a vehicle information acquired by the vehicle information acquisition unit, and a map. Based on the map information acquired by the information acquisition unit, the angle detection unit that detects the angle between the direction of each point in front of the vehicle and the direction of the vehicle, and the vehicle information acquired by the vehicle information acquisition unit. , The coordinate generation unit that generates nth-order (n is 2 or more) coordinates based on the map information acquired by the map information acquisition unit and the angle detected by the angle detection unit, and the coordinates generated by the coordinate generation unit. Based on this, it is provided with a target route generation unit that generates a target route of the own vehicle.

According to the present invention, the route generation device is based on the vehicle information acquired by the vehicle information acquisition unit and the map information acquired by the map information acquisition unit, and the direction and orientation of each point in front of the vehicle. Based on the angle detection unit that detects the angle between the vehicle, the vehicle information acquired by the vehicle information acquisition unit, the map information acquired by the map information acquisition unit, and the angle detected by the angle detection unit, the nth order is obtained. Since it includes a coordinate generation unit that generates coordinates (n is 2 or more) and a target route generation unit that generates a target route of the own vehicle based on the coordinates generated by the coordinate generation unit, an accurate route is generated. It becomes possible.

It is a block diagram which shows an example of the structure of the route generation apparatus by Embodiment 1 of this invention. It is a flowchart which shows an example of the operation of the route generation apparatus by Embodiment 1 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 1 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 1 of this invention. It is a block diagram which shows an example of the structure of the route generation apparatus by Embodiment 2 of this invention. It is a flowchart which shows an example of the operation of the route generation apparatus by Embodiment 2 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 2 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 2 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 2 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 2 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 2 of this invention. It is a block diagram which shows an example of the structure of the route generation apparatus by Embodiment 3 of this invention. It is a flowchart which shows an example of the operation of the route generation apparatus by Embodiment 3 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 3 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 3 of this invention. It is a figure for demonstrating operation | movement of the path generation apparatus by Embodiment 3 of this invention. It is a block diagram which shows an example of the structure of the route generation apparatus according to Embodiment 4 of this invention. It is a flowchart which shows an example of the operation of the route generation apparatus by Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a figure for demonstrating the operation of the route generation apparatus according to Embodiment 4 of this invention. It is a block diagram which shows an example of the structure of the path generation apparatus by the modification of Embodiment 4 of this invention. It is a flowchart which shows an example of the operation of the path generation apparatus by the modification of Embodiment 4 of this invention. It is a block diagram which shows an example of the structure of the route generation apparatus by Embodiment 5 of this invention. It is a flowchart which shows an example of the operation of the route generation apparatus by Embodiment 5 of this invention. It is a block diagram which shows an example of the hardware composition of the route generation apparatus by embodiment of this invention. It is a block diagram which shows an example of the hardware composition of the route generation apparatus by embodiment of this invention. It is a figure for demonstrating the generation of a route by a related technique. It is a figure for demonstrating the generation of a route by a related technique. It is a figure for demonstrating the generation of a route by a related technique.

Embodiments of the present invention will be described below with reference to the drawings.

<Related technology>
Hereinafter, related technologies related to the technologies disclosed in the present specification will be described.

As shown in FIG. 33, in the related technology, for example, when the own vehicle 7 is traveling on the road, the target route is generated by approximating the target point cloud by a curve. The target point group is a set of target points located in the center of the lane.

As shown in FIG. 34, in the related technology, the target point cloud located in the center of the lane in which the own vehicle 7 travels has the position of the own vehicle 7 as the origin, and the traveling direction of the own vehicle 7 coincides with the x-axis. The target point cloud is curve-applied by the rotation calculation as described above.

However, if a general least squares approximation is used when approximating the target point cloud, in the case of a road shape that suddenly curves from a straight line as shown in FIG. 34, for example, the x-axis as shown in FIG. 35. When the amount of change in the y-axis is large with respect to the amount of change in, there is a problem that the accuracy of approximation deteriorates. If the accuracy of the approximation deteriorates in this way, there is a problem that an accurate route cannot be generated as a result.

Embodiments of the present invention have been made to solve such problems of related technology, and will be described in detail below.

<Embodiment 1>
<1-1. Configuration>
FIG. 1 is a block diagram showing an example of the configuration of the route generation device 1 according to the first embodiment.

As shown in FIG. 1, the route generation device 1 includes a vehicle information acquisition unit 2, a map information acquisition unit 3, an angle detection unit 4, a coordinate generation unit 5, and a target route generation unit 6. ..

The own vehicle information acquisition unit 2 uses the positioning information received from the artificial satellite to obtain at least the own vehicle position indicating the position of the own vehicle and the own vehicle information including the own vehicle direction indicating the direction in which the own vehicle travels. get. The vehicle position includes latitude and longitude. Specifically, the own vehicle information acquisition unit 2 corrects the positioning signal, satellite signal, or information obtained by correcting these signals via, for example, GPS (Global Positioning System) or GLONASS (Global Navigation Satellite System). The position of the own vehicle can be acquired by receiving the satellite signal receiver. Further, the configuration is not limited to these signals, and may be a configuration adopting so-called dead reckoning in which the own vehicle position and the own vehicle direction are calculated by combining the detection results of the yaw rate sensor and the vehicle speed sensor. The direction of the own vehicle corresponds to the direction of travel of the own vehicle. In addition, the own vehicle information may include the speed of the own vehicle.

The map information acquisition unit 3 acquires map information including at least a map point cloud which is a set of a plurality of points on a map along a road. Map information includes the latitude, longitude, and altitude of each point. Multiple points are called point clouds. A point cloud is, for example, a set of discrete points located in the center of a lane, and each point has a position coordinate value. The map information acquisition unit 3 acquires map information including point cloud information of the road from the departure point to the destination on which the own vehicle travels, for example. Here, the point group information is represented by latitude, longitude, and altitude. For example, a coordinate conversion method such as the Gauss-Kruger method is used to convert latitude, longitude, and altitude on a plane to obtain a position. The origin may be represented by a metric coordinate system divided into an east-west direction and a north-south direction.

By associating the map point cloud acquired by the map information acquisition unit 3 with the vehicle position and the vehicle orientation acquired by the vehicle information acquisition unit 2, the map point cloud around the vehicle can be obtained. Such a group of map points around the own vehicle is called a group of points near the own vehicle.

The angle detection unit 4 determines the direction of each point in front of the vehicle and the direction of the vehicle based on the vehicle information acquired by the vehicle information acquisition unit 2 and the map information acquired by the map information acquisition unit 3. Detect the angle of formation. Specifically, the angle detection unit 4 detects the angle of the own vehicle neighborhood point cloud located in front of the own vehicle position by using the own vehicle neighborhood point cloud.

The coordinate generation unit 5 is nth-order (n is n) based on the vehicle information acquired by the vehicle information acquisition unit 2, the map information acquired by the map information acquisition unit 3, and the angle detected by the angle detection unit 4. 2 or more) coordinates are generated. Specifically, the coordinate generation unit 5 generates the nth-order coordinates of the own vehicle neighborhood point cloud according to the angle detected by the angle detection unit 4. The group of points near the own vehicle arranged according to the n-th order coordinates generated in this way is called an approximate reference point cloud.

The target route generation unit 6 generates a target route of the own vehicle based on the coordinates generated by the coordinate generation unit 5. Specifically, the target route generation unit 6 generates a target route consisting of a curve or a straight line corresponding to the approximate reference point group by polynomial approximation or the like by using the approximate reference point cloud arranged according to the coordinates generated by the coordinate generation unit 5. To do.

<1-2. Operation>
FIG. 2 is a flowchart showing an example of the operation of the route generation device 1.

In step S101, the own vehicle information acquisition unit 2 acquires the own vehicle information by receiving a positioning signal or the like from the artificial satellite. In step S102, the map information acquisition unit 3 acquires the map information.

In step S103, the angle detection unit 4 links the map point cloud acquired by the map information acquisition unit 3 to the vehicle position and the vehicle orientation acquired by the vehicle information acquisition unit 2, and thereby points near the vehicle. Generate a group. Further, the angle detection unit 4 may acquire road information including information on the lane in which the own vehicle travels. Road information includes, for example, a point cloud located in the center of the lane, the number of lanes, the curvature of the road, and the like.

Further, the angle detection unit 4 may also associate the altitude included in the map information with the own vehicle position and the own vehicle direction. By associating the altitude with the position of the vehicle and the direction of the vehicle, for example, when the area around the vehicle is a mixture of lower roads and highways, the height of the road on which the vehicle is currently traveling can be determined. It is possible to generate a group of points in the vicinity of the own vehicle on the determined road.

In step S104, the angle detection unit 4 detects the angle formed by the direction of the own vehicle neighborhood point group existing in front of the own vehicle position and the own vehicle direction among the own vehicle neighborhood point group generated in step S103. .. As shown in FIG. 3, for example, the angle formed by the direction of the points near the vehicle in front of the vehicle and the direction of the vehicle exists ahead of the position of the vehicle in the x-axis direction, which is the traveling direction of the vehicle 7. at the intersection of the perpendicular and the vehicle near point group through the point x ₁ on any of the x-axis which is obtained by calculating the angle θ between the vehicle near point group and the x-axis. The points in the vicinity of the own vehicle in FIG. 3 are points that form a group of points in the vicinity of the own vehicle.

In step S105, the coordinate generation unit 5 generates the nth-order coordinates of the approximate reference point cloud according to the angle detected by the angle detection unit 4. Specifically, the coordinate generation unit 5 rotates the own vehicle neighborhood point cloud (x, y) by an angle θ about the origin, for example, using the angle θ calculated by the angle detection unit 4 in FIG. The coordinates (X, Y) after rotation can be calculated using the following equation (2). The coordinates after rotation are shown in FIG.

In step S106, the target path generation unit 6 generates a target path composed of a curve or a straight line corresponding to the approximate reference point group by polynomial approximation or the like by using the approximate reference point group arranged according to the coordinates generated by the coordinate generation unit 5. .. Specifically, the target path generation unit 6 generates an approximate curve as a target path by applying a polynomial approximation such as the least squares method to the approximate reference point cloud arranged according to the coordinates generated by the coordinate generation unit 5. ..

Here, the least squares method will be described. The least squares method is a method of finding a function f (X _i ) such that J in the following equation (3) is minimized, where the coordinates of the approximate reference point cloud are (X _i Y _i ).

The curve fitting method used by the target path generation unit 6, that is, the method of generating the target path from the approximate reference point group is not limited to the least squares approximation for obtaining a cubic polynomial or a fifth order polynomial, and is, for example, the least squares method. An approximation method with a weighting coefficient added, or a non-uniform rational B-spline (NURBS) may be used. The target route generation unit 6 may generate a target route by using these methods.

In the above, the case where the point cloud near the vehicle is generated by associating the map point cloud with the position of the vehicle and the direction of the vehicle has been described, but the present invention is not limited to this. For example, a set of candidate points for white lines detected by various sensors that detect white lines on the road may be used as a point cloud near the own vehicle. Further, a point cloud at the center point of the left and right white lines may be generated using only the white lines recognized by the camera, and the target path may be generated by applying the least squares method or the like to the point cloud.

<1-3. Effect>
According to the first embodiment, the angle detection unit 4 detects the angle of the own vehicle neighborhood point cloud located in front of the own vehicle position by using the own vehicle neighborhood point cloud. The coordinate generation unit 5 generates the nth-order coordinates of the approximate reference point cloud according to the angle detected by the angle detection unit 4. The target route generation unit 6 generates an approximate curve as a target route by applying a polynomial approximation such as the least squares method to the approximate reference point cloud arranged according to the coordinates generated by the coordinate generation unit 5. As a result, the accuracy of the approximation in front of the own vehicle can be improved, and as a result, an accurate route can be generated.

<Embodiment 2>
<2-1. Configuration>
FIG. 5 is a block diagram showing an example of the configuration of the route generation device 8 according to the second embodiment. The route generation device 8 according to the second embodiment is characterized by the angle detection unit 4. Since other configurations are the same as those of the route generation device 1 shown in FIG. 1 described in the first embodiment, detailed description thereof will be omitted here.

As shown in FIG. 5, the angle detection unit 4 includes the own vehicle coordinate generation unit 9, the time output unit 10, the front gaze distance calculation unit 11, the front gaze position calculation unit 12, and the center position calculation unit 13. It includes a coordinate axis moving unit 14 and an angle calculating unit 15.

The own vehicle coordinate generation unit 9 generates the own vehicle coordinates, which are the coordinates of the own vehicle, based on the own vehicle information acquired by the own vehicle information acquisition unit 2 and the map information acquired by the map information acquisition unit 3. Specifically, the own vehicle coordinate generation unit 9 uses the own vehicle position and the own vehicle direction acquired by the own vehicle information acquisition unit 2 and the map point group acquired by the map information acquisition unit 3 to obtain the own vehicle position. And generate own vehicle coordinates based on the own vehicle orientation.

The time output unit 10 outputs the prediction time, which is a predetermined time, to the forward gaze distance calculation unit 11.

The forward gaze distance calculation unit 11 multiplies the speed of the own vehicle included in the own vehicle information acquired by the own vehicle information acquisition unit 2 by the foreseeable time acquired from the time output unit 10 to obtain the own vehicle in the foreseeable time. Calculate the forward gaze distance, which is the distance reached by.

The front gaze position calculation unit 12 gazes forward from the vehicle position to the front of the vehicle based on the vehicle coordinates generated by the vehicle coordinate generation unit 9 and the front gaze distance calculated by the front gaze distance calculation unit 11. The forward gaze position, which is the coordinate value of a point separated by a distance, is calculated.

The center position calculation unit 13 is between the vehicle position acquired by the vehicle information acquisition unit 2 and the front gaze position calculated by the front gaze position calculation unit 12 in the vehicle coordinates generated by the vehicle coordinate generation unit 9. Calculate the center position of.

The coordinate axis moving unit 14 translates the coordinate axes so that the center position calculated by the center position calculation unit 13 is the origin in the own vehicle coordinates generated by the own vehicle coordinate generation unit 9.

The angle calculation unit 15 determines the direction and self of each point in front of the vehicle based on the vehicle position in the vehicle coordinates generated by the vehicle coordinate generation unit 9 and the center position calculated by the center position calculation unit 13. Calculate the angle between the vehicle direction and the vehicle direction. Specifically, the angle calculation unit 15 calculates the angle formed by the vehicle proximity point cloud on the y-axis and the vehicle orientation on the coordinate axis after the coordinate axis movement unit 14 has moved. The angle calculation unit 15 outputs the calculated angle to the coordinate generation unit 5.

<2-2. Operation>
FIG. 6 is a flowchart showing an example of the operation of the route generation device 8. Since step S209 in FIG. 6 is the same as step S106 in FIG. 2, description thereof will be omitted here.

In step S201, the own vehicle information acquisition unit 2 acquires the own vehicle information. In addition, the map information acquisition unit 3 acquires map information.

In step S202, the own vehicle coordinate generation unit 9 is based on the own vehicle position and the own vehicle direction by using the own vehicle information acquired by the own vehicle information acquisition unit 2 and the map information acquired by the map information acquisition unit 3. Generate own vehicle coordinates.

Specifically, the own vehicle coordinate generation unit 9 links the map point group acquired by the map information acquisition unit 3 to the own vehicle position and the own vehicle orientation acquired by the own vehicle information acquisition unit 2, and thereby the own vehicle. The coordinates of the own vehicle are generated with the position as the origin, the traveling direction of the own vehicle as the x-axis, and the axis orthogonal to the x-axis as the y-axis. FIG. 7 shows an example of the own vehicle coordinates generated by the own vehicle coordinate generation unit 9. 7, the original coordinates of each point in the map point group map information acquiring section 3 acquires the _{(x 'i, y' i} ), the angle of the vehicle direction and θ _{D [rad],} the vehicle Assuming that the position is (x ₀ , y ₀ ), the coordinates (x _i , y _i ) of each own vehicle neighborhood point in the own vehicle neighborhood point cloud arranged according to the own vehicle coordinates are derived by the following equation (4). ..

In step S203, the forward gaze distance calculation unit 11 gazes forward by multiplying the speed of the own vehicle included in the own vehicle information acquired by the own vehicle information acquisition unit 2 by the prediction time acquired from the time output unit 10. Calculate the distance. Specifically, the speed of the vehicle and v, when a Td foreseeing time, look-ahead distance L _d is derived by the following equation (5).

The forward gaze distance L _d is not limited to the above equation (5), and may be a value on the x-axis of the end point of the vehicle neighborhood point cloud in front of the vehicle from the origin when approximating.

In step S204, the front gaze position calculation unit 12 calculates the front gaze position based on the own vehicle coordinates generated by the own vehicle coordinate generation unit 9 and the front gaze distance calculated by the front gaze distance calculation unit 11. Specifically, the forward gaze position calculation unit 12 calculates the coordinate value (L _d , 0) of the forward gaze position, which is the position of a point on the x-axis advanced by the forward gaze distance L _d from the own vehicle position.

In step S205, the central position calculation unit 13 has the own vehicle position acquired by the own vehicle information acquisition unit 2 and the forward gaze calculated by the forward gaze position calculation unit 12 in the own vehicle coordinates generated by the own vehicle coordinate generation unit 9. Calculate the central position between the positions. Specifically, as shown in FIG. 8, for example, the central position calculation unit 13 calculates the central position between the own vehicle position and the forward gaze position, and calculates the coordinate value of the central position.

In step S206, the coordinate axis moving unit 14 translates the coordinate axes so that the center position calculated by the center position calculation unit 13 is the origin in the own vehicle coordinates generated by the own vehicle coordinate generation unit 9. Specifically, the coordinate axis moving unit 14, for example, as shown in FIG. 9, so that the center position is the origin of the own vehicle near point coordinates (x _{i, y i)} to be offset.

In step S207, the angle calculation unit 15 calculates the angle formed by the vehicle proximity point cloud and the vehicle orientation on the y-axis at the coordinates after the coordinate axis movement unit 14 has moved. Specifically, the angle calculation unit 15 calculates the angle of the point cloud near the own vehicle on the y-axis with respect to the x-axis at the coordinates after the coordinate axis movement unit 14 has moved. More specifically, for example, as shown in FIG. 10, the angle calculation unit 15 calculates an angle using the slope of a straight line connecting the two closest points sandwiching the y-axis. The angle θ is derived by the following equation (6).

Further, the angle calculation unit 15 sets the slope of the vehicle proximity point group used when calculating the angle as a straight line connecting two points sandwiching the y-axis, such as the slope of a straight line connecting two points at both ends of the range used for approximation. Any two points may be used as long as the slope of is. Further, the slope of the straight line connecting all the two points sandwiching the y-axis may be averaged.

In step S208, the coordinate generation unit 5 uses the angle θ calculated by the angle calculation unit 15 to rotate the coordinates (x, y) of the own vehicle neighborhood point cloud and the own vehicle position by the angle θ with respect to the origin. Generate the nth-order coordinates of the approximate reference point cloud. The coordinates (X, Y) after rotation can be calculated using the above equation (2). The coordinates after rotation are shown in FIG.

<2-3. Effect>
According to the second embodiment, the angle calculation unit 15 calculates the angle formed by the own vehicle neighborhood point cloud and the own vehicle direction on the y-axis at the coordinates after the coordinate axis moving unit 14 has moved. The coordinate generation unit 5 uses the angle θ calculated by the angle calculation unit 15 to rotate the coordinates (x, y) of the own vehicle neighborhood point group and the own vehicle position by the angle θ around the origin, and the approximate reference point group. Generates the nth-order coordinates of. The target route generation unit 6 generates an approximate curve as a target route by applying a polynomial approximation such as the least squares method to the approximate reference point cloud arranged according to the coordinates generated by the coordinate generation unit 5. As a result, the accuracy of the approximation in front of the own vehicle can be improved, and as a result, an accurate route can be generated.

<Embodiment 3>
<3-1. Configuration>
FIG. 12 is a block diagram showing an example of the configuration of the route generation device 16 according to the third embodiment. The route generation device 16 according to the third embodiment is characterized by the angle detection unit 4. Since other configurations are the same as those of the route generation device 1 shown in FIG. 1 described in the first embodiment, detailed description thereof will be omitted here.

As shown in FIG. 12, the angle detection unit 4 includes the own vehicle neighborhood point group generation unit 17, the own vehicle neighborhood point group length calculation unit 18, the center position calculation unit 19, the tangent line calculation unit 20, and the angle calculation. It is provided with a unit 21.

The own vehicle neighborhood point group generation unit 17 sets the own vehicle position and the own vehicle orientation as a map point group based on the own vehicle information acquired by the own vehicle information acquisition unit 2 and the map information acquired by the map information acquisition unit 3. Generates a group of points in the vicinity of the own vehicle associated with. Specifically, the own vehicle neighborhood point cloud generation unit 17 generates nth-order (n is 2 or more) coordinates using the own vehicle position and the own vehicle direction acquired by the own vehicle information acquisition unit 2, and the coordinates. The map point cloud acquired by the map information acquisition unit 3 is arranged in. As described above, the map point cloud arranged at this time is a point cloud near the own vehicle.

The vehicle neighborhood point group generation unit 17 is based on the vehicle position and vehicle orientation acquired by the vehicle information acquisition unit 2 and the map point group acquired by the map information acquisition unit 3, for example, FIG. 7. You may use the own vehicle coordinates with the own vehicle position of the own vehicle 7 as the origin, the own vehicle direction which is the traveling direction of the own vehicle 7 as the x-axis, and the axis orthogonal to the x-axis as the y-axis.

The vehicle neighborhood point group length calculation unit 18 is the vehicle neighborhood point group length, which is the total length between each point from the start point to the end point of the vehicle neighborhood point group generated by the vehicle neighborhood point group generation unit 17. Calculate the The center position calculation unit 19 calculates the point cloud center position indicating a position that is half of the vehicle neighborhood point cloud length calculated by the vehicle neighborhood point cloud length calculation unit 18.

The tangent line calculation unit 20 calculates the tangent line of the point cloud near the own vehicle at the point cloud center position calculated by the center position calculation unit 19. The angle calculation unit 21 calculates the angle formed by the tangent line calculated by the tangent line calculation unit 20 and the direction of the own vehicle.

<3-2. Operation>
FIG. 13 is a flowchart showing an example of the operation of the route generation device 16. Since steps S308 and S309 in FIG. 13 are the same as steps S105 and S106 in FIG. 2, description thereof will be omitted here.

In step S301, the own vehicle information acquisition unit 2 acquires the own vehicle information. In addition, the map information acquisition unit 3 acquires map information.

In step S302, the own vehicle neighborhood point cloud generation unit 17 generates nth-order coordinates using the own vehicle position and the own vehicle direction acquired by the own vehicle information acquisition unit 2, and the map acquired by the map information acquisition unit 3. The point cloud is arranged according to the n-th order coordinates. At this time, the map point cloud arranged according to the n-th order coordinates is the own vehicle neighborhood point cloud.

In step S303, the own vehicle neighborhood point cloud length calculation unit 18 calculates the length between each point from the start point to the end point of the own vehicle neighborhood point cloud generated by the own vehicle neighborhood point cloud generation unit 17. Specifically, the own vehicle neighborhood point cloud length calculation unit 18 calculates the distance distance between each point, for example, as shown in FIG. More specifically, as shown in FIG. 15, for example, the own vehicle neighborhood point group length calculation unit 18 has a distance distance ₁ between the start point and the next point of the own vehicle neighborhood point group, the end point and the front end thereof. Distance to points The distance between _n points up to distance _n is calculated using the following formula (7).

In step S304, the own vehicle neighborhood point cloud length calculation unit 18 calculates the own vehicle neighborhood point cloud length, which is the total length between each point from the start point to the end point of the own vehicle neighborhood point cloud. Specifically, the own vehicle neighborhood point cloud length calculation unit 18 calculates the own vehicle neighborhood point cloud length Length, which is the total of the distances between each point from the distance distance ₁ to the distance distance _n shown in FIG. 15, for example. To do.

In step S305, the center position calculation unit 19 calculates the point cloud center position indicating a position that is half the position of the own vehicle neighborhood point cloud length calculation unit 18 calculated by the own vehicle neighborhood point cloud length calculation unit 18. Specifically, as shown in FIG. 16, for example, the center position calculation unit 19 calculates the center position of the point cloud, which is a position moved by half of the length Length of the point cloud near the vehicle from the start point of the point cloud near the vehicle. To do. In the example of FIG. 16, the position moved by half of the length Length of the own vehicle neighborhood point group from the start point of the vehicle neighborhood point group is calculated as the point group center position, but the own vehicle is calculated from the end point of the vehicle neighborhood point group. The position moved by half of the neighborhood point group length Length may be calculated as the point group center position.

In step S306, the tangent line calculation unit 20 calculates the tangent line of the point cloud near the own vehicle at the point cloud center position calculated by the center position calculation unit 19. Specifically, the tangent line calculation unit 20 calculates, for example, the inclination of the point cloud near the own vehicle at the center position of the point cloud shown in FIG. 16 as a tangent line. More specifically, the tangent line calculation unit 20 may calculate the tangent line by using two points in the vicinity sandwiching the center position of the point group. The tangent line calculation unit 20 may calculate the tangent line using any two points as long as the two points sandwich the center position of the point group.

In step S307, the angle calculation unit 21 calculates the angle formed by the tangent line calculated by the tangent line calculation unit 20 and the direction of the own vehicle. Specifically, assuming that the broken line shown in FIG. 10 is a tangent line calculated by the tangent line calculation unit 20, the angle calculation unit 21 sets the angle θ at the intersection of the tangent line and the x-axis which is the direction of the own vehicle. It is calculated using the above formula (6) or the like.

<3-3. Effect>
According to the third embodiment, the tangent line calculation unit 20 calculates the tangent line of the point cloud near the own vehicle at the point cloud center position calculated by the center position calculation unit 19. The angle calculation unit 21 calculates the angle formed by the tangent line calculated by the tangent line calculation unit 20 and the direction of the own vehicle. The coordinate generation unit 5 uses the angle θ calculated by the angle calculation unit 21 to rotate the coordinates (x, y) of the own vehicle neighborhood point group and the own vehicle position by the angle θ about the origin, and the approximate reference point group. Generates the nth-order coordinates of. The target route generation unit 6 generates an approximate curve as a target route by applying a polynomial approximation such as the least squares method to the approximate reference point cloud arranged according to the coordinates generated by the coordinate generation unit 5. As a result, the accuracy of the approximation in front of the own vehicle can be improved, and as a result, an accurate route can be generated.

<Embodiment 4>
<4-1. Configuration>
FIG. 17 is a block diagram showing an example of the configuration of the route generation device 22 according to the fourth embodiment.

As shown in FIG. 17, the route generation device 22 includes a vehicle information acquisition unit 2, a map information acquisition unit 3, an angle output unit 23, a coordinate generation unit 24, an approximation calculation unit 25, and an approximation error calculation unit. 26, an approximation error comparison unit 27, and a first target route generation unit 28 are provided. The own vehicle information acquisition unit 2 and the map information acquisition unit 3 shown in FIG. 17 are the same as the own vehicle information acquisition unit 2 and the map information acquisition unit 3 shown in FIG. 1 described in the first embodiment. The detailed explanation will be omitted.

The angle output unit 23 outputs a plurality of angles to the coordinate generation unit 24. The plurality of angles output by the angle output unit 23 may be, for example, 60 kinds of integer values from 0 ° to 59 °, 360 ways of integer values from 0 ° to 359 °, and 0 ° to 45 °. The angle may include a decimal point, or may be a plurality of irregular angles such as 1 °, 30 °, 45 °, and 67 °.

The coordinate generation unit 24 has a plurality of nth orders (n is 2 or more) according to each angle based on the vehicle information acquired by the vehicle information acquisition unit 2 and the plurality of angles output by the angle output unit 23. Generate the coordinates of. Then, the coordinate generation unit 24 arranges a map point cloud for each of the generated nth-order coordinates. The map point cloud arranged at this time is an approximate reference point cloud.

The approximation calculation unit 25 calculates an approximation curve of each approximation reference point group by polynomial approximation of each approximation reference point group arranged by the coordinate generation unit 24 for each coordinate using the least squares method or the like.

The approximation error calculation unit 26 calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit 25 and the approximation reference point group arranged by the coordinate generation unit 24, for each coordinate.

The approximation error comparison unit 27 compares all the approximation errors calculated by the approximation error calculation unit 26, and calculates the minimum value of the approximation error.

The first target route generation unit 28 generates an approximation curve corresponding to the minimum value of the approximation error calculated by the approximation error comparison unit 27 as the target route of the own vehicle.

<4-2. Operation>
FIG. 18 is a flowchart showing an example of the operation of the route generation device 22.

In step S401, the own vehicle information acquisition unit 2 acquires the own vehicle information. In addition, the map information acquisition unit 3 acquires map information.

In step S402, the angle output unit 23 determines a plurality of angles.

In step S403, the angle output unit 23 outputs a plurality of determined angles to the coordinate generation unit 24.

In step S404, the coordinate generation unit 24 generates an approximate reference point cloud corresponding to each angle. Specifically, for example, when the angle output unit 23 outputs the angle α, the angle β, the angle γ, and the angle δ as a plurality of angles θ, the coordinate generation unit 24, as shown in FIGS. 19 to 22, respectively. Generates four different coordinates depending on the angle of. Then, a group of approximate reference points is arranged based on each coordinate. In this way, the coordinate generation unit 24 generates coordinates corresponding to each of the plurality of angles output by the angle output unit 23, and generates an approximate reference point cloud based on the generated coordinates.

In step S405, the approximation calculation unit 25 calculates the approximation curve of each approximation reference point group by polynomial approximation of each approximation reference point group arranged by the coordinate generation unit 24 for each coordinate using the least squares method or the like. ..

In step S406, the approximation error calculation unit 26 calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit 25 and the approximation reference point group arranged by the coordinate generation unit 24, for each coordinate. Specifically, the approximation error calculation unit 26 calculates the approximation error between the approximation curve and the approximation reference point group for each coordinate, for example, as shown in FIGS. 23 to 26. At this time, the approximation error ε is calculated by the following equation (8). In equation (8), n indicates the number of approximate reference point groups from the start point to the end point, (X _i Y _i ) indicates the coordinates of the approximate reference point group, and f (X _i ) approximates the function of the approximate curve. It is a value obtained by substituting the value of the X-axis of the i-th point of the reference point group.

In step S407, the approximation error comparison unit 27 compares all the approximation errors calculated by the approximation error calculation unit 26, and calculates the minimum value of the approximation error. Specifically, for example, in FIGS. 23 to 26, the approximation error ε _α = 1 at the angle _α , the approximation error ε _β = 0.5 at the angle _β , and the approximation error ε _γ = 1 at the angle γ. When the approximation error ε _δ = 2.5 at 5 and the angle δ, the minimum value of the approximation error is the approximation error ε _β .

In step S408, the first target route generation unit 28 generates an approximation curve corresponding to the minimum value of the approximation error calculated by the approximation error comparison unit 27 as the target route of the own vehicle. Specifically, when the minimum value of the approximation error calculated by the approximation error comparison unit 27 is the approximation error ε _β , the first target path generation unit 28 has the approximation curve f (β) at the angle β shown in FIG. ) Is generated as the target route of the own vehicle.

<4-3. Modification example>
FIG. 27 is a block diagram showing an example of the configuration of the route generation device 29 according to the modified example of the fourth embodiment. The present modification is characterized in that the approximation error comparison unit 27 sets a threshold value used when comparing approximation errors. Specifically, the route generation device 29 is characterized by including a threshold value output unit 30, a minimum value comparison unit 31, and a second target route generation unit 32. Since other configurations are the same as those of the route generation device 22 shown in FIG. 17, detailed description thereof will be omitted here.

The threshold value output unit 30 outputs a predetermined approximation error threshold value to the minimum value comparison unit 31. When setting a threshold value for the error of the approximate curve generated as the target path, the threshold value of the approximate error is set in advance in consideration of the allowable approximate error.

The minimum value comparison unit 31 compares the minimum value of the approximation error calculated by the approximation error comparison unit 27 with the threshold value output by the threshold value output unit 30. Then, when the minimum value of the approximation error is larger than the threshold value, the minimum value comparison unit 31 sets a plurality of angles different from the angles output by the angle output unit 23 to the angle output unit 23 to the coordinate generation unit 24. Instruct to output to. For example, the angle output unit 23 outputs 30 different angles of integer values from 0 ° to 29 °, and when the minimum value of the approximation error of these angles is larger than the threshold value, the next time is from 30 ° to 60 °. Outputs the angle of the integer value of.

Note that the minimum value comparison unit 31 instructs the angle output unit 23 to output different angles when the minimum value of the approximation error is larger than the threshold value, but at this time, a plurality of outputs from the angle output unit 23. The angle of is different from the angle previously output in the range of the angle, the resolution, and the like.

When the minimum value of the approximation error is equal to or less than the threshold value, the second target route generation unit 32 generates an approximation curve corresponding to the minimum value of the approximation error as the target route of the own vehicle.

FIG. 28 is a flowchart showing an example of the operation of the route generation device 29. Since steps S501 to S507 in FIG. 28 are the same as steps S401 to S407 in FIG. 18, detailed description thereof will be omitted here. In the following, step S508 and step S509 will be described.

In step S508, the minimum value comparison unit 31 compares the minimum value of the approximation error calculated by the approximation error comparison unit 27 with the threshold value output by the threshold value output unit 30, and the minimum value of the approximation error is equal to or less than the threshold value. Judge whether or not. If the minimum value of the approximation error is equal to or less than the threshold value, the process proceeds to step S509. On the other hand, if the minimum value of the approximation error is not equal to or less than the threshold value, the process returns to step S502.

In step S509, the second target route generation unit 32 generates an approximation curve corresponding to the minimum value of the approximation error as the target route of the own vehicle.

<4-4. Effect>
According to the fourth embodiment, the coordinate generation unit 24 has a plurality of coordinates corresponding to each angle based on the vehicle information acquired by the vehicle information acquisition unit 2 and the plurality of angles output by the angle output unit 23. The n-th order coordinates of are generated, and a map point cloud is arranged for each coordinate. The approximation calculation unit 25 calculates an approximation curve of each approximation reference point group by polynomial approximation of each approximation reference point group arranged by the coordinate generation unit 24 for each coordinate using the least squares method or the like. The approximation error calculation unit 26 calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit 25 and the approximation reference point group arranged by the coordinate generation unit 24, for each coordinate. The approximation error comparison unit 27 compares all the approximation errors calculated by the approximation error calculation unit 26, and calculates the minimum value of the approximation error. The first target route generation unit 28 generates an approximation curve corresponding to the minimum value of the approximation error calculated by the approximation error comparison unit 27 as the target route of the own vehicle. As a result, the accuracy of the approximation in front of the own vehicle can be improved, and as a result, an accurate route can be generated.

Further, the minimum value comparison unit 31 compares the minimum value of the approximation error calculated by the approximation error comparison unit 27 with the threshold value output by the threshold value output unit 30. When the minimum value of the approximation error is equal to or less than the threshold value, the second target route generation unit 32 generates an approximation curve corresponding to the minimum value of the approximation error as the target route of the own vehicle. Even with such a configuration, the accuracy of approximation in front of the own vehicle can be improved, and as a result, an accurate route can be generated.

<Embodiment 5>
<5-1. Configuration>
FIG. 29 is a block diagram showing an example of the configuration of the route generation device 33 according to the fifth embodiment.

As shown in FIG. 29, the route generation device 33 includes the own vehicle information acquisition unit 2, the map information acquisition unit 3, the angle output unit 34, the coordinate generation unit 35, the approximation calculation unit 36, and the approximation error calculation unit. 37, a threshold output unit 38, an approximation error comparison unit 39, and a target route generation unit 40 are provided. The own vehicle information acquisition unit 2 and the map information acquisition unit 3 shown in FIG. 29 are the same as the own vehicle information acquisition unit 2 and the map information acquisition unit 3 shown in FIG. 1 described in the first embodiment. The detailed explanation will be omitted.

The angle output unit 34 outputs one predetermined angle to the coordinate generation unit 35.

The coordinate generation unit 35 obtains nth-order (n is 2 or more) coordinates according to the angle based on the vehicle information acquired by the vehicle information acquisition unit 2 and the plurality of angles output by the angle output unit 23. Generate. Then, the coordinate generation unit 35 arranges the map point cloud at the generated n-th order coordinates. The map point cloud arranged at this time is an approximate reference point cloud.

The approximation calculation unit 36 calculates an approximation curve of the approximation reference point group by polynomial approximation of the approximation reference point group arranged by the coordinate generation unit 35 using the least squares method or the like.

The approximation error calculation unit 37 calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit 36 and the approximation reference point cloud arranged by the coordinate generation unit 35.

The threshold value output unit 38 outputs a predetermined approximation error threshold value to the approximation error comparison unit 39.

The approximation error comparison unit 39 compares the approximation error calculated by the approximation error calculation unit 37 with the threshold value output by the threshold value output unit 38. Then, when the approximation error is larger than the threshold value as a result of the comparison, the approximation error comparison unit 39 instructs the angle output unit 34 to output an angle different from the angles output so far.

When the approximation error is equal to or less than the threshold value as a result of comparison by the approximation error comparison unit 39, the target route generation unit 40 generates an approximation curve calculated by the approximation calculation unit 36 as the target route of the own vehicle.

<5-2. Operation>
FIG. 30 is a flowchart showing an example of the operation of the route generation device 33.

In step S601, the own vehicle information acquisition unit 2 acquires the own vehicle information. In addition, the map information acquisition unit 3 acquires map information.

In step S602, the angle output unit 34 determines one angle.

In step S603, the angle output unit 34 outputs one determined angle to the coordinate generation unit 35.

In step S604, the coordinate generation unit 35 generates an approximate reference point cloud according to the angle.

In step S605, the approximation calculation unit 36 calculates the approximation curve of the approximation reference point group by polynomial approximation of the approximation reference point group arranged in the coordinates by the coordinate generation unit 35 using the least squares method or the like.

In step S606, the approximation error calculation unit 37 calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit 36 and the approximation reference point cloud arranged by the coordinate generation unit 35.

In step S607, the approximation error comparison unit 39 compares the approximation error calculated by the approximation error calculation unit 37 with the threshold value output by the threshold value output unit 38, and determines whether or not the approximation error is equal to or less than the threshold value. If the approximation error is equal to or less than the threshold value, the process proceeds to step S608. On the other hand, if the approximation error is not equal to or less than the threshold value, the process returns to step S602. In this case, the approximation error comparison unit 39 instructs the angle output unit 34 to output an angle different from the angles output so far.

In step S608, the target route generation unit 40 generates the approximate curve calculated by the approximate calculation unit 36 as the target route of the own vehicle.

From the above, the route generation device 33 outputs one angle without outputting a plurality of angles as in the route generation device 22 described in the fourth embodiment, and outputs until the approximation error at the angle becomes equal to or less than the threshold value. Update the angles to be done one by one.

<5-3. Effect>
According to the fifth embodiment, the coordinate generation unit 35 is the nth order according to the angle based on the vehicle information acquired by the vehicle information acquisition unit 2 and the plurality of angles output by the angle output unit 23. Generate the coordinates of. The approximation calculation unit 36 calculates an approximation curve of the approximation reference point group by polynomial approximation of the approximation reference point group arranged by the coordinate generation unit 35 using the least squares method or the like. The approximation error calculation unit 37 calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit 36 and the approximation reference point cloud arranged by the coordinate generation unit 35. When the approximation error is equal to or less than the threshold value as a result of comparison by the approximation error comparison unit 39, the target route generation unit 40 generates an approximation curve calculated by the approximation calculation unit 36 as the target route of the own vehicle. As a result, the accuracy of the approximation in front of the own vehicle can be improved, and as a result, an accurate route can be generated.

<Hardware configuration>
Each function of the own vehicle information acquisition unit 2, the map information acquisition unit 3, the angle detection unit 4, the coordinate generation unit 5, and the target route generation unit 6 in the route generation device 1 described in the first embodiment is realized by a processing circuit. Will be done. That is, the route generation device 1 includes a processing circuit for acquiring own vehicle information, acquiring map information, detecting an angle, generating coordinates, and generating a target route. The processing circuit is a processor (CPU (Central Processing Unit), central processing unit, processing unit, arithmetic unit, microprocessor, microcomputer, DSP (Digital) that executes programs stored in memory, even if it is dedicated hardware. It may also be called a Signal Processor).

When the processing circuit is dedicated hardware, as shown in FIG. 31, the processing circuit 41 is, for example, a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, an ASIC (Application Specific Integrated Circuit). , FPGA (Field Programmable Gate Array), or a combination of these. Each function of the own vehicle information acquisition unit 2, the map information acquisition unit 3, the angle detection unit 4, the coordinate generation unit 5, and the target route generation unit 6 may be realized by the processing circuit 41, and each function may be collectively 1 It may be realized by one processing circuit 41.

When the processing circuit 41 is the processor 42 shown in FIG. 32, the functions of the own vehicle information acquisition unit 2, the map information acquisition unit 3, the angle detection unit 4, the coordinate generation unit 5, and the target route generation unit 6 are software. It is realized by firmware or a combination of software and firmware. The software or firmware is written as a program and stored in the memory 43. The processor 42 realizes each function by reading and executing the program stored in the memory 43. That is, the route generation device 1 eventually executes a step of acquiring own vehicle information, a step of acquiring map information, a step of detecting an angle, a step of generating coordinates, and a step of generating a target route. A memory 43 for storing a program is provided. Further, it can be said that these programs cause the computer to execute the procedures or methods of the own vehicle information acquisition unit 2, the map information acquisition unit 3, the angle detection unit 4, the coordinate generation unit 5, and the target route generation unit 6. .. Here, the memory is, for example, non-volatile or volatile such as RAM (Random Access Memory), ROM (Read Only Memory), flash memory, EPROM (Erasable Programmable Read Only Memory), and EEPROM (Electrically Erasable Programmable Read Only Memory). It may be a sex semiconductor memory, a magnetic disk, a flexible disk, an optical disk, a compact disk, a DVD (Digital Versatile Disc), or any other storage medium that will be used in the future.

It should be noted that some of the functions of the vehicle information acquisition unit 2, the map information acquisition unit 3, the angle detection unit 4, the coordinate generation unit 5, and the target route generation unit 6 are realized by dedicated hardware, and other parts. May be realized by software or firmware.

In this way, the processing circuit can realize each of the above-mentioned functions by hardware, software, firmware, or a combination thereof.

In the above, the hardware configuration of the route generation device 1 shown in FIG. 1 described in the first embodiment has been described, but the route generation device 8 and the third embodiment shown in FIG. 5 described in the second embodiment have been described. Hardware of the route generation device 16 shown in FIG. 12, the route generation devices 22 and 29 shown in FIGS. 17 and 27 described in the fourth embodiment, and the route generation device 33 shown in FIG. 29 described in the fifth embodiment. The same applies to the configuration.

In the present invention, each embodiment can be freely combined, and each embodiment can be appropriately modified or omitted within the scope of the invention.

1 Route generator, 2 Own vehicle information acquisition unit, 3 Map information acquisition unit, 4 Angle detection unit, 5 Coordinate generation unit, 6 Target route generation unit, 7 Own vehicle, 8 Route generation device, 9 Own vehicle coordinate generation unit, 10-hour output unit, 11 forward gaze distance calculation unit, 12 forward gaze position calculation unit, 13 center position calculation unit, 14 coordinate axis movement unit, 15 angle calculation unit, 16 route generator, 17 own vehicle neighborhood point group generation unit, 18 Own vehicle neighborhood point group length calculation unit, 19 center position calculation unit, 20 tangent line calculation unit, 21 angle calculation unit, 22 route generator, 23 angle output unit, 24 coordinate generation unit, 25 approximation calculation unit, 26 approximation error calculation Unit, 27 Approximate error comparison unit, 28 1st target route generation unit, 29 route generation device, 30 threshold output unit, 31 minimum value comparison unit, 32 2nd target route generation unit, 33 route generation device, 34 angle output unit, 35 coordinate generation unit, 36 approximation calculation unit, 37 approximation error calculation unit, 38 threshold output unit, 39 approximation error comparison unit, 40 target route generation unit, 41 processing circuit, 42 processor, 43 memory.

In order to solve the above problems, the route generator according to the present invention acquires own vehicle information including at least the own vehicle position indicating the position of the own vehicle and the own vehicle direction indicating the direction in which the own vehicle travels. An information acquisition unit, a map information acquisition unit that acquires map information including a group of map points that are a set of at least a plurality of points on a map along a road, a vehicle information acquired by the vehicle information acquisition unit, and a map. Based on the map information acquired by the information acquisition unit, the angle detection unit that detects the angle between the direction of each point in front of the vehicle and the vehicle orientation, and the vehicle information acquired by the vehicle information acquisition unit. Based on the map information acquired by the map information acquisition unit and the angle detected by the angle detection unit, the coordinates generated by the coordinate generation unit and the coordinates generated by the coordinate generation unit are used to generate nth-order (n is 2 or more) coordinates. Therefore, it is provided with a target route generation unit that generates an approximate curve of the arranged map point group as a target route of the own vehicle, and the angle detection unit includes the own vehicle information acquired by the own vehicle information acquisition unit and the map information acquisition unit. Based on the acquired map information, the own vehicle coordinate generator that generates the own vehicle coordinates, which is the coordinates of the own vehicle, and the own vehicle coordinates generated by the own vehicle coordinate generator, the own vehicle position and the front of the own vehicle. The vehicle coordinates generated by the vehicle coordinate generator so that the center position calculated by the center position calculation unit and the center position between the front gaze position indicating the position of the vehicle are the origin. In the coordinate axis moving part that moves the coordinate axes in parallel and the own vehicle coordinates after the coordinate axis moving part moves the coordinate axes in parallel, the inclination of the straight line connecting two points of each point sandwiching the coordinate axis orthogonal to the own vehicle direction and the own and a angle calculator for calculating an angle between the vehicle direction, the coordinate generating unit that generates a coordinate of each point and subject vehicle coordinates is rotated by an angle around the origin.

According to the present invention, the route generation device is based on the vehicle information acquired by the vehicle information acquisition unit and the map information acquired by the map information acquisition unit, and the direction and direction of each point in front of the vehicle. Based on the angle detection unit that detects the angle between the vehicle, the vehicle information acquired by the vehicle information acquisition unit, the map information acquired by the map information acquisition unit, and the angle detected by the angle detection unit. (n is 2 or more) with a coordinate generating unit which generates the coordinates of the approximate curve of the thus map point group disposed in coordinates coordinate generation unit has generated, a target route generation unit for generating a target route of the vehicle , The angle detection unit is a vehicle coordinate generation unit that generates vehicle coordinates, which are the coordinates of the vehicle, based on the vehicle information acquired by the vehicle information acquisition unit and the map information acquired by the map information acquisition unit. And, in the own vehicle coordinates generated by the own vehicle coordinate generation unit, the central position calculation unit and the central position calculation unit that calculate the central position between the own vehicle position and the front gaze position indicating the position in front of the own vehicle. In the coordinate axis moving part that moves the coordinate axes of the own vehicle coordinates generated by the own vehicle coordinate generation unit in parallel so that the center position calculated by is the origin, and in the own vehicle coordinates after the coordinate axis moving part moves the coordinate axes in parallel. , It is equipped with an angle calculation unit that calculates the angle formed by the inclination of the straight line connecting two points of each point that sandwiches the coordinate axis orthogonal to the vehicle direction and the vehicle direction, and the coordinate generation unit is located around the origin. order to generate the coordinates by rotating the point and subject vehicle coordinates by an angle, it is possible to generate an accurate path.

Claims (11)

A vehicle information acquisition unit that acquires vehicle information including at least the vehicle position indicating the position of the vehicle and the vehicle direction indicating the direction in which the vehicle travels.
A map information acquisition unit that acquires map information including a map point cloud that is a set of at least a plurality of points on a map along a road.
Based on the own vehicle information acquired by the own vehicle information acquisition unit and the map information acquired by the map information acquisition unit, the direction of each of the points in front of the own vehicle and the direction of the own vehicle are formed. An angle detector that detects the angle and
Based on the own vehicle information acquired by the own vehicle information acquisition unit, the map information acquired by the map information acquisition unit, and the angle detected by the angle detection unit, the nth order (n is 2 or more). A coordinate generator that generates the coordinates of
A target route generation unit that generates a target route of the own vehicle based on the coordinates generated by the coordinate generation unit, and a target route generation unit.
A route generator comprising. The angle detection unit
A vehicle coordinate generation unit that generates vehicle coordinates, which are the coordinates of the vehicle, based on the vehicle information acquired by the vehicle information acquisition unit and the map information acquired by the map information acquisition unit. ,
In the own vehicle coordinates generated by the own vehicle coordinate generation unit, a central position calculation unit that calculates a central position between the own vehicle position and a forward gaze position indicating a position in front of the own vehicle, and
Based on the vehicle position in the vehicle coordinates generated by the vehicle coordinate generation unit and the center position calculated by the center position calculation unit, the direction of each of the points in front of the vehicle and the vehicle itself. An angle calculation unit that calculates the angle between the vehicle direction and
The route generation device according to claim 1. The angle detection unit
Based on the own vehicle information acquired by the own vehicle information acquisition unit and the map information acquired by the map information acquisition unit, the own vehicle position and the own vehicle orientation are associated with the map point group. A vehicle neighborhood point group generator that generates a vehicle neighborhood point group,
Own vehicle neighborhood point group length for calculating the own vehicle neighborhood point group length, which is the total length between each point from the start point to the end point of the own vehicle neighborhood point group generated by the own vehicle neighborhood point group generation unit. Calculation part and
A center position calculation unit that calculates a point cloud center position indicating a position that is half of the vehicle neighborhood point cloud length calculated by the vehicle neighborhood point cloud length calculation unit.
The tangent line calculation unit that calculates the tangent line of the point cloud near the own vehicle at the point cloud center position calculated by the center position calculation unit,
An angle calculation unit that calculates an angle formed by the tangent line calculated by the tangent line calculation unit and the vehicle direction.
The route generation device according to claim 1. A vehicle information acquisition unit that acquires vehicle information including at least the vehicle position indicating the position of the vehicle and the vehicle direction indicating the direction in which the vehicle travels.
A map information acquisition unit that acquires map information including a map point cloud that is a set of at least a plurality of points on a map along a road.
An angle output unit that outputs multiple angles and
Based on the own vehicle information acquired by the own vehicle information acquisition unit and the plurality of angles output by the angle output unit, a plurality of nth-order coordinates (n is 2 or more) corresponding to each of the angles are obtained. A coordinate generator that generates and arranges the map point cloud as an approximate reference point cloud for each coordinate.
An approximation calculation unit that calculates an approximation curve of each of the approximation reference point groups arranged by the coordinate generation unit for each of the coordinates.
An approximation error calculation unit that calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit and the approximation reference point group arranged by the coordinate generation unit, for each of the coordinates.
Of the approximation errors calculated by the approximation error calculation unit, an approximation error comparison unit that calculates the minimum value of the approximation error, and
A target route generation unit that generates the approximation curve corresponding to the minimum value of the approximation error calculated by the approximation error comparison unit as a target route of the own vehicle.
A route generator comprising. When the minimum value of the approximation error calculated by the approximation error comparison unit is larger than a predetermined threshold value, a plurality of angles different from the plurality of angles output so far are output to the angle output unit. The route generation device according to claim 4, further comprising a minimum value comparison unit that gives an instruction to perform. A vehicle information acquisition unit that acquires vehicle information including at least the vehicle position indicating the position of the vehicle and the vehicle direction indicating the direction in which the vehicle travels.
A map information acquisition unit that acquires map information including a map point cloud that is a set of at least a plurality of points on a map along a road.
An angle output unit that outputs one predetermined angle,
Based on the own vehicle information acquired by the own vehicle information acquisition unit and the angle output by the angle output unit, n-th order (n is 2 or more) coordinates corresponding to the angle are generated, and the coordinates are obtained. A coordinate generator that arranges the map point cloud as an approximate reference point cloud,
An approximation calculation unit that calculates an approximation curve of the approximation reference point cloud arranged by the coordinate generation unit, and
An approximation error calculation unit that calculates an approximation error, which is an error between the approximation curve calculated by the approximation calculation unit and the approximation reference point cloud arranged by the coordinate generation unit.
An approximation error comparison unit that compares the approximation error calculated by the approximation error calculation unit with a predetermined threshold value.
As a result of the comparison by the approximation error comparison unit, when the approximation error is equal to or less than the threshold value, the target route generation unit that generates the approximation curve calculated by the approximation calculation unit as the target route of the own vehicle, and
With
As a result of the comparison, the approximation error comparison unit is characterized in that when the approximation error is larger than the threshold value, it instructs the angle output unit to output an angle different from the angles output so far. A route generator. (A) A process of acquiring at least the own vehicle position indicating the position of the own vehicle and the own vehicle information including the own vehicle direction indicating the direction in which the own vehicle travels.
(B) At least the process of acquiring map information including a map point cloud which is a set of a plurality of points on a map along a road, and
(C) Based on the own vehicle information acquired in the step (a) and the map information acquired in the step (b), the direction of each of the points in front of the own vehicle and the direction of the own vehicle. The process of detecting the angle between the wheels and
(D) Based on the vehicle information acquired in the step (a), the map information acquired in the step (b), and the angle detected in the step (c), the nth order (n is). The process of generating coordinates (2 or more) and
(E) A step of generating the target route of the own vehicle based on the coordinates generated in the step (d), and
A route generation method. The step (c) is
(F) A step of generating the own vehicle coordinates, which are the coordinates of the own vehicle, based on the own vehicle information acquired in the step (a) and the map information acquired in the step (b).
(G) In the vehicle coordinates generated in the step (f), a step of calculating the central position between the vehicle position and the front gaze position indicating the position in front of the vehicle,
(H) Based on the vehicle position in the vehicle coordinates generated in the step (f) and the center position calculated in the process (g), the direction of each of the points in front of the vehicle. The process of calculating the angle formed by the vehicle direction and
7. The route generation method according to claim 7. The step (c) is
(I) Based on the own vehicle information acquired in the step (a) and the map information acquired in the step (b), the own vehicle position and the own vehicle orientation are associated with the map point group. The process of generating a point cloud near the vehicle and
(J) A step of calculating the length of the own vehicle neighborhood point cloud, which is the total length between the points from the start point to the end point of the own vehicle neighborhood point cloud generated in the step (i).
(K) A step of calculating a central position indicating a position of half the length of the own vehicle neighborhood point cloud calculated in the step (j), and
(L) A step of calculating the tangent line of the own vehicle neighborhood point group at the central position calculated in the step (k), and
(M) A step of calculating the angle formed by the tangent line calculated in the step (l) and the direction of the own vehicle,
7. The route generation method according to claim 7. (A) A process of acquiring at least the own vehicle position indicating the position of the own vehicle and the own vehicle information including the own vehicle direction indicating the direction in which the own vehicle travels.
(B) At least the process of acquiring map information including a map point cloud which is a set of a plurality of points on a map along a road, and
(C) A process of outputting a plurality of angles and
(D) Based on the own vehicle information acquired by the step (a) and the plurality of angles output by the step (c), a plurality of nth orders (n is 2 or more) according to each of the angles. And the process of arranging the map point cloud as an approximate reference point cloud for each coordinate of
(E) A step of calculating an approximate curve of each of the approximate reference point groups arranged in (d) for each of the coordinates.
(F) A step of calculating an approximation error, which is an error between the approximation curve calculated in the step (e) and the approximation reference point cloud arranged in the step (d), for each of the coordinates.
(G) Of the approximation errors calculated by the step (f), a step of calculating the minimum value of the approximation error and
(H) A step of generating the approximate curve corresponding to the minimum value of the approximate error calculated in the step (g) as a target route of the own vehicle, and
A route generation method. (I) When the minimum value of the approximation error calculated in the step (g) is larger than a predetermined threshold value, a plurality of angles different from the plurality of angles output so far with respect to the step (c). The route generation method according to claim 10, further comprising a step of giving an instruction to output an angle of.

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