JPWO2018212286A1 - Measuring device, measuring method and program - Google Patents

Abstract

The measuring device obtains output data from the sensor unit for detecting the surrounding road surface line, and calculates the self-position, the positional information of the broken road surface line, and the interval between the solid line portions of the broken road surface line. A predetermined range is determined based on the predetermined range. Then, data corresponding to the detection result of the predetermined range is extracted from the output data, and a predetermined process is performed based on the extracted data.

Description

  The present invention relates to a technique for estimating the position of a moving object based on the position of a feature.

  In an autonomous driving vehicle, it is necessary to highly accurately estimate the position of the own vehicle by matching a feature position measured by a sensor such as LiDAR (Light Detection and Ranging) with a feature position in map information for automatic driving. The features used here include a white line, a sign, a signboard, and the like. Patent Literature 1 describes an example of a method of estimating a position of a vehicle using a feature position detected using LiDAR and a feature position in map information. Patent Document 2 discloses a technique of transmitting an electromagnetic wave to a road surface and detecting a white line based on the reflectance.

JP 2017-72422 A JP 2015-222223 A

  When estimating the position of the vehicle using the white line, there is a difference in the number of data that can be measured by LiDAR depending on the type of the white line (continuous line, broken line, etc.), deterioration of the paint, and the like. For this reason, when the vehicle position is estimated using the white line, the detection accuracy of the white line changes depending on whether the number of LiDAR data used for detecting the white line is small or large, and as a result, the accuracy of the vehicle position estimation changes. Come.

  The problems to be solved by the present invention include those described above as examples. An object of the present invention is to appropriately adjust a range in which a white line is detected according to a situation, and to prevent a decrease in the accuracy of the vehicle position estimation.

  The invention according to claim 1 is a measuring device, and an acquisition unit that acquires output data from a sensor unit for detecting a surrounding road surface line, a self-position, and position information of a dashed road surface line. A determination unit that determines a predetermined range based on the interval between the solid line portions of the dashed road surface line, and an extraction unit that extracts data corresponding to the detection result of the predetermined range from the output data. And a processing unit for performing a predetermined process based on the obtained data.

  The invention according to claim 9 is a measurement method executed by a measurement device, wherein an acquisition step of acquiring output data from a sensor unit for detecting a surrounding road line, a self-position, Determining a predetermined range based on the position information of the road surface line and the interval between the solid lines of the dashed road surface line; and extracting data corresponding to the detection result of the predetermined range from the output data. It is characterized by comprising an extraction step and a processing step of performing a predetermined processing based on the extracted data.

The invention according to claim 10 is a program executed by a measuring device including a computer, the acquisition unit acquiring output data from a sensor unit for detecting a surrounding road line, a self-position, and a dashed line. A determining unit that determines a predetermined range based on the position information of the road surface line and the interval between the solid line portions of the dashed road surface line, and extracting data corresponding to a detection result of the predetermined range from the output data A processing unit that performs a predetermined process based on the extracted data,
And causing the computer to function.

It is a figure explaining a white line extraction method. It is a figure explaining the determination method of a white line prediction range. It is a figure explaining the calculation method of a white line center position. It is a figure explaining the 1st correction method of the white line prediction range of the broken line type white line. It is a figure explaining the 1st correction method of the white line prediction range of the broken line type white line. It is a figure explaining the 2nd correction method of the white line prediction range of the broken line type white line. FIG. 2 is a block diagram illustrating a configuration of a measurement device. It is a flowchart of the own vehicle position estimation process using a white line.

  In one preferred embodiment of the present invention, the measuring device includes an acquiring unit that acquires output data from a sensor unit for detecting a surrounding road line, a self-position, and position information of a dashed road surface line. A determination unit that determines a predetermined range based on the interval between the solid line portions of the dashed road surface line, and an extraction unit that extracts data corresponding to the detection result of the predetermined range from the output data. And a processing unit for performing a predetermined process based on the obtained data.

  The above measuring device obtains output data from a sensor unit for detecting a surrounding road surface line, and determines a self-position, position information of a broken road surface line, and an interval between solid line portions of the broken road surface line. The predetermined range is determined based on the above. Then, data corresponding to the detection result of the predetermined range is extracted from the output data, and a predetermined process is performed based on the extracted data. By determining the predetermined range in consideration of the interval between the solid line portions of the broken road surface line, it is possible to appropriately extract desired data. The “road surface line” in this specification refers to a lane marking such as a white line or a yellow line to be measured, and a linear road marking such as a stop line or a pedestrian crossing.

  In one aspect of the above-described measuring device, the determination unit may be configured to set the plurality of predetermined ranges such that at least one of the plurality of predetermined ranges overlaps with a solid line portion of the dashed road surface line in at least a part of the predetermined range. decide. In this aspect, data can be appropriately extracted in at least a part of the predetermined range.

  In another aspect of the above measuring device, the determination unit determines the plurality of predetermined positions based on the position information of the self-position and the dashed road surface line, all of the determined plurality of predetermined ranges Is moved to at least one position of the plurality of predetermined ranges when the position coincides with the space portion of the dashed road surface line. In this aspect, it is possible to extract appropriate data by moving the predetermined range.

  In another aspect of the above measuring device, the determining unit determines the plurality of predetermined positions based on the position information of the self-position and the dashed road surface line, all of the determined plurality of predetermined positions Is longer than the space portion of the dashed road surface line, at least one of the plurality of predetermined ranges is lengthened. In this aspect, it is possible to extract appropriate data by increasing the length of the predetermined range.

  In another aspect of the measurement device, the determination unit sets the length of the predetermined range to be longer than the length of the space portion of the broken road surface line. Thereby, the predetermined range can be made to overlap the solid line portion of the dashed road surface line.

  In another aspect of the above-described measuring device, the determination unit changes the length of the predetermined range according to a type of a road. In this aspect, the predetermined range can be set to an appropriate length according to the type of the road.

  In a preferred example, the measuring device is mounted on a moving body, and the extraction unit sets the predetermined range at four places of a right front, a right rear, a left front, and a left rear based on the position of the moving body. I do. In a preferred example, the processing unit performs a process of detecting a position of the road surface line and estimating a position of the measuring device based on the position of the road surface line.

  In another preferred embodiment of the present invention, the measuring method executed by the measuring device includes an obtaining step of obtaining output data from a sensor unit for detecting a surrounding road line, a self-position, and a dashed line type. Determining a predetermined range based on the position information of the road surface line and the interval between the solid lines of the dashed road surface line; and extracting data corresponding to the detection result of the predetermined range from the output data. It is characterized by comprising an extraction step and a processing step of performing a predetermined processing based on the extracted data. By determining the predetermined range in consideration of the interval between the solid line portions of the broken road surface line, it is possible to appropriately extract desired data.

  In another preferred embodiment of the present invention, a program executed by a measuring device including a computer includes an acquiring unit that acquires output data from a sensor unit for detecting a surrounding road line, a self-position, and a dashed line type. A determining unit that determines a predetermined range based on the position information of the road surface line and the interval between the solid line portions of the dashed road surface line, and extracting data corresponding to a detection result of the predetermined range from the output data And causing the computer to function as a processing unit that performs a predetermined process based on the extracted data. By executing this program on a computer, the above-described measuring device can be realized. This program can be stored in a storage medium and handled.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.
[White line extraction method]
FIG. 1 is a diagram illustrating a white line extraction method. White line extraction refers to detecting a white line painted on a road surface and calculating a predetermined position thereof, for example, a center position.

(Calculation of white line predicted position)
As illustrated, the vehicle 5 is present map coordinate system _(X m, _{Y m),} the vehicle coordinate system relative to the position of the vehicle 5 _{(X v, Y} v) is defined. Specifically, the traveling direction of the vehicle 5 and X _v-axis of the vehicle coordinate system, a direction perpendicular to it and Y _v axis of the vehicle coordinate system.

  On the left and right sides of the vehicle 5, there are white lines that are lane boundary lines. The position of the white line in the map coordinate system, that is, the position of the white line map is included in the advanced map managed by the server or the like, and is acquired from the server or the like. In the present embodiment, it is assumed that the data of the white line is stored in the advanced map as a sequence of coordinate points. The LiDAR mounted on the vehicle 5 measures scan data along the scan line 2. Note that the scan line 2 indicates the trajectory of scanning by LiDAR.

In FIG. 1, the coordinates of a point forming the white line WL1 on the left side of the vehicle 5, that is, the white line map position WLMP1 is (mx _m1 , my _m1 ), and the coordinates of a point forming the white line WL2 on the right side of the vehicle 5, ie, the white line It is assumed that the map position WLMP2 is (mx _m2 , my _m2 ). Further, the predicted vehicle position PVP in the map coordinate system is given by _{(x 'm, y' m} ), the predicted vehicle azimuth in the map coordinate system is given by [psi _'m.

Here, the white line predicted position WLPP indicating the predicted position of the white line _{(l'x v, l'y v} ) is the white line map position WLMP _{(mx m,} my m) and the predicted vehicle position PVP (x _'m, y 'and _m), the predicted vehicle azimuth [psi' by using the _m, is given by the following equation (1).

よって、式（１）により、白線ＷＬ１について白線予測位置ＷＬＰＰ１（ｌ’ｘ_ｖ１，ｌ’ｙ_ｖ１）が得られ、白線ＷＬ２について白線予測位置ＷＬＰＰ２（ｌ’ｘ_ｖ２，ｌ’ｙ_ｖ２）が得られる。こうして、白線ＷＬ１、ＷＬ２のそれぞれについて、白線ＷＬ１、ＷＬ２に対応する複数の白線予測位置ＷＬＰＰ１、ＷＬＰＰ２が得られる。

Therefore, the equation (1), the white line predicted position _{WLPP1 (l'x v1, l'y} v1) for the white line WL1 is obtained, the white line predicted position for the white line _{WL2 WLPP2 (l'x v2, l'} y v2) is obtained Can be Thus, for each of the white lines WL1 and WL2, a plurality of white line predicted positions WLPP1 and WLPP2 corresponding to the white lines WL1 and WL2 are obtained.

(Determination of white line prediction range)
Next, a white line prediction range WLPR is determined based on the white line prediction position WLPP. The white line prediction range WLPR indicates a range in which a white line is considered to exist based on the predicted own vehicle position PVP. The white line prediction range WLPR is set at a maximum of four places of the front right, the rear right, the front left and the rear left of the vehicle 5.

FIG. 2 shows a method for determining the white line prediction range WLPR. In FIG. 2 (A), set forward reference point to any position in front of the vehicle 5 (distance alpha _v forward position) to (α _{v, 0 v).} Then, based on the front reference point (α _v , 0 _v ) and the white line prediction position WLPP, a white line prediction position WLPP closest to the front reference point (α _v , 0 _v ) is searched. Specifically, the white line WL1 on the basis of the forward reference point (α _{v, 0 v),} a plurality of white lines predicted position WLPP1 constituting the white line WL1 and _{(l'x v1, l'y v1} ), below The distance D1 is calculated by the equation (2), and the white line predicted position WLPP1 at which the distance D1 is the minimum value is set as the prediction range reference point Pref1.

Similarly, for white lines WL2, based on the forward reference point (α _{v, 0 v),} a plurality of white lines predicted position WLPP2 constituting the white line WL2 and _{(l'x v2, l'y v2} ), the following formula The distance D2 is calculated according to (3), and the white line predicted position WLPP2 at which the distance D2 is the minimum value is set as the prediction range reference point Pref2.

Then, as shown in FIG. 2 (B), any range based on the expected range reference point Pref, for example ± [Delta] X from the expected range reference point Pref in X _v-axis direction, a range of ± [Delta] Y to Y _v-axis direction The white line prediction range WLPR is set. Thus, as shown in FIG. 1, the white line prediction ranges WLPR1 and WLPR2 are set at the left and right positions in front of the vehicle 5. Similarly, by setting the rear reference point behind the vehicle 5 and setting the prediction range reference point Pref, the white line prediction ranges WLPR3 and WLPR4 are set at the left and right positions behind the vehicle 5. Thus, four white line prediction ranges WLPR1 to WLPR4 are set for the vehicle 5.

(Calculation of white line center position)
Next, the white line center position WLCP is calculated using the white line predicted position WLPP. FIG. 3 shows a method of calculating the white line center position WLCP. FIG. 3A shows a case where the white line WL1 is a solid line. The white line center position WLCP1 is calculated by the average value of the position coordinates of the scan data forming the white line. Now, as shown in FIG. 3 (A), the white line prediction range WLPR1 is set, among the scan data output from LiDAR, white line scan data exists in the white line expected range WLPR1 WLSD1 (wx _'v, wy ' _v ) is extracted. Since the reflectance on the white line is higher than that on a normal road, the scan data obtained on the white line has high reflection intensity. Among the scan data output from the LiDAR, scan data that exists within the white line prediction range WLPR1 and that is on the road surface and has a reflection intensity of a predetermined value or more is extracted as white line scan data WLSD. When the number of extracted white line scan data WLSD and "n", the following equation (4), the coordinates of the white line center position _WLCP1 (sx _{v1, sy} v1) is obtained.

また、図３（Ｂ）に示すように、白線が破線である場合も同様に白線中心位置ＷＬＣＰ２が算出される。

Also, as shown in FIG. 3B, the white line center position WLCP2 is calculated similarly when the white line is a broken line.

(Determination of white line prediction range when white line is broken line)
As described above, the white line predicted range WLPR is determined based on the white line predicted position WLPP. When the white line is a broken line (hereinafter, such a white line is also referred to as a “dashed white line”), the white line WL is determined. A situation that is not included in the white line prediction range WLPR may occur.

  FIG. 4A shows an example of the white line prediction range WLPR in the case of a dashed white line. The dashed white line WL has solid line portions RP and space portions SP alternately arranged. Here, the solid line portion RP is a portion where the white line is painted, and the space portion SP is a portion between the solid line portions RP where the white line is not painted. Now, as shown in FIG. 4A, when the forward reference point is defined and the white line prediction range WLPR is determined, each of the two white line prediction ranges WLPR1 and WLPR4 corresponds to the position corresponding to the space portion SP of the dashed white line. Thus, the white line prediction ranges WLPR1 and WLPR4 do not include the solid line portion RP of the dashed white line. In such a case, a sufficient number of white line scan data WLSD cannot be obtained from the white line prediction range WLPR, so that the white line center position WLCP cannot be accurately calculated.

(1) First Correction Method As a measure against such a case, in the first correction method, the position of the white line prediction range WLPR is moved. Specifically, as shown in FIG. 4B, the white line prediction range WLPR1 on the left front of the vehicle 5 is moved forward, and the white line prediction range WLPR4 on the left rear is moved backward. As a result, the white line prediction ranges WLPR1 and WLPR4 both overlap the solid line portion RP of the dashed white line, and a sufficient number of white line scan data WLSD can be obtained from the white line prediction range WLPR.

Next, the amount of movement when moving the white line prediction range WLPR will be discussed. FIG. 5A shows a case where both the white line prediction ranges WLPR1 and WLPR4 coincide with the space portion SP of the dashed white line, similarly to FIG. 4A. As described with reference to FIG. 2, the white line prediction range in front of the vehicle sets the front reference point in front of the vehicle 5 and sets the white line prediction position WLPP closest to the front reference point as the prediction range reference point Pref. It is determined within a range of a predetermined distance from the prediction range reference point Pref. Therefore, the white line prediction range WLPR1 can be moved forward by moving the front reference point forward. Similarly, the white line prediction range WLPR behind the vehicle sets a rear reference point behind the vehicle 5, sets the white line prediction position WLPP closest to the rear reference point as the prediction range reference point Pref, and sets a predetermined range from the prediction range reference point Pref. It is determined in the range of the distance. Therefore, the white line prediction range WLPR4 can be moved backward by moving the backward reference point backward. Specifically, by increasing the distance α _v to the front reference point or the rear reference point (hereinafter, also simply referred to as “reference point”), the vehicle moves in the white line prediction range WLPR1 ahead of the vehicle, and the vehicle moves forward. Can be moved backward in the white line prediction range WLPR4.

In FIG. 5A, the length of the solid line portion RP of the dashed white line is “Lw”, and the length of the space portion SP is “Ls”. In this case, the distance α _v to the reference point is
α _v = (Ls + Lw) / 2 (5)
When the condition is satisfied, both the white line prediction ranges WLPR1 and WLPR4 coincide with the space portion SP of the broken white line. Therefore, based on the length Lw of the solid line portion RP and the length Ls of the space portion SP of the dashed white line,
α _v > (Ls + Lw) / 2 (6)
It is determined the distance alpha _v to the reference point so that it is possible to prevent the both two white lines expected range WLPR1, WLP4 to both match the space portion SP. That is, at least one of the two white line prediction ranges WLPR1 and WLPR4 can at least partially overlap the solid line portion RP of the dashed white line.

Further, as shown in FIG. 5B, the distance α _v to the reference point is
α _v = (Ls + Lw) (7)
By setting so that the white line prediction range WLPR can be arranged near the center in the length direction of the solid line portion RP of the dashed white line.

(2) Second Correction Method A second correction method for avoiding a state in which the solid line portion RP of the dashed white line is not included in the white line prediction ranges WLPR1 and WLPR4 is to extend the white line prediction range WLPR, that is, to extend the length. Is to make it longer. As shown in FIG. 6A, when both of the white line prediction ranges WLPR1 and WLPR4 coincide with the space portion SP of the dashed white line, the white line prediction ranges WLPR1 and WLPR4 are changed as shown in FIG. 6B. You can extend it. In the example of FIG. 6B, the front white line prediction range WLPR1 is extended forward, and the rear white line prediction range WLPR4 is extended rearward. Instead, the front white line prediction range WLPR1 is extended rearward. Alternatively, the rear white line prediction range WLPR4 may be extended forward. Further, both of the two white line prediction ranges WLPR1 and WLPR4 may be extended back and forth. By making the length of the white line prediction range WLPR longer than the space portion SP of the dashed white line, at least a part of the white line prediction range WLPR can be overlapped with the solid line portion RP of the dashed white line.

  The length Lw and the length Ls of the solid line portion RP of the dashed white line are usually determined according to the type of road. For example, on an expressway, the length Lw of the solid line part RP is 8 m and the length Ls of the space part SP is 12 m. On a general road, the length Lw of the solid line part RP is 5 m and the length Ls of the space part SP is Ls = 5 m. Therefore, control may be performed to change the length of the white line prediction range WLPR according to the type of the road on which the vehicle 5 is traveling. Specifically, the length of the white line prediction range WLPR is longer than 12 m when the vehicle 5 is traveling on the highway, and the length of the white line prediction range WLPR is longer when the vehicle 5 is traveling on the general road. The length may be longer than 5 m. Accordingly, at least a part of the white line prediction range WLPR overlaps the solid line portion RP of the dashed white line, so that the detection accuracy of the white line center position can be improved. In addition, on a general road, the length of the white line prediction range WLPR does not need to be unnecessarily increased, so that noise when detecting the white line scan data WLSD can be reduced.

(3) Length of solid line portion and space portion of dashed white line As described above, when performing the first and second correction methods, the length Lw of solid line portion RP of dashed white line and space portion SP It is necessary to know the length Ls. Basically, the lengths of the solid line portion RP and the space portion SP of the dashed white line are determined according to the road type as described above. Therefore, by detecting the type of the road on which the vehicle 5 is traveling, the lengths of the solid line part RP and the space part SP can be known.

  As another method, when the attribute data of the road in the map data includes the length of the solid line portion RP and the space portion SP of the dashed white line, it can be referred to. As still another method, the lengths of the solid line portion RP and the space portion SP may be detected by using scan data of LiDAR or analyzing an image captured by a camera. Of course, these methods may be used in combination.

(4) Application Example In the above example, both of the two white line prediction ranges WLPR1 and WLPR4 are moved or extended, but instead, only one of the two white line prediction ranges WLPR1 and WLPR4 is moved or extended. You may do it. In addition, as shown in FIG. 1, when there is a white line on the right side of the vehicle 5, the first or second correction method can be applied to a white line prediction range set on the right side of the vehicle 5. In this case, when the type of the white line is different between the left side and the right side of the vehicle 5, the moving amount or the extending amount of the white line predicted range WLPR may be determined according to the specification of each white line.

[Device configuration]
FIG. 7 shows a schematic configuration of an own-vehicle position estimating device to which the measuring device of the present invention is applied. The vehicle position estimation device 10 is mounted on a vehicle and configured to be able to communicate with a server 7 such as a cloud server by wireless communication. The server 7 is connected to a database 8, and the database 8 stores an advanced map. The advanced map stored in the database 8 stores landmark map information for each landmark. As for the white line, white line map information including a white line map position WLMP indicating the coordinates of a sequence of points constituting the white line is stored. The own-vehicle position estimating device 10 communicates with the server 7 and downloads white line map information on white lines around the own vehicle position of the vehicle. When the white line map information includes information on the lengths of the solid line portion and the broken line portion of the dashed white line, the own-vehicle position estimating device 10 also acquires the information.

  The vehicle position estimating apparatus 10 includes an internal sensor 11, an external sensor 12, an own vehicle position predicting unit 13, a communication unit 14, a white line map information acquiring unit 15, a white line position predicting unit 16, and scan data extraction. And a white line center position calculating unit 18 and a vehicle position estimating unit 19. Note that the own vehicle position predicting unit 13, the white line map information acquiring unit 15, the white line position predicting unit 16, the scan data extracting unit 17, the white line center position calculating unit 18, and the own vehicle position estimating unit 19 are actually a CPU or the like. This is realized by a computer executing a prepared program.

  The inner field sensor 11 is a GNSS (Global Navigation Satellite System) / IMU (Inertia Measurement Unit) hybrid navigation system that measures the position of the vehicle itself, and includes a satellite positioning sensor (GPS), a gyro sensor, a vehicle speed sensor, and the like. Including. The own vehicle position prediction unit 13 predicts the own vehicle position of the vehicle based on the output of the inner field sensor 11 by GNSS / IMU combined navigation, and supplies the predicted own vehicle position PVP to the white line position prediction unit 16.

  The external sensor 12 is a sensor that detects an object around the vehicle, and includes a stereo camera, LiDAR, and the like. The external sensor 12 supplies the scan data SD obtained by the measurement to the scan data extraction unit 17.

  The communication unit 14 is a communication unit for performing wireless communication with the server 7. The white line map information acquisition unit 15 receives white line map information on white lines existing around the vehicle from the server 7 via the communication unit 14 and supplies the white line map position WLMP included in the white line map information to the white line position prediction unit 16. I do.

  Based on the white line map position WLMP and the predicted own vehicle position PVP acquired from the own vehicle position prediction unit 13, the white line position prediction unit 16 calculates the white line predicted position WLPP by the above-described equation (1). In addition, the white line position prediction unit 16 determines the white line prediction range WLPR based on the white line prediction position WLPP by the above-described equations (2) and (3). Note that, as described above, when all the white line prediction ranges WLPR coincide with the dashed white line space portions SP as described above, the white line prediction range WLPR is corrected to move or extend the white line prediction range WLPR. Then, the white line position prediction unit 16 supplies the determined white line prediction range WLPR to the scan data extraction unit 17.

  The scan data extraction unit 17 extracts white line scan data WLSD based on the white line prediction range WLPR supplied from the white line position prediction unit 16 and the scan data SD acquired from the external sensor 12. Specifically, the scan data extraction unit 17 extracts, as the white line scan data WLSD, the scan data included in the white line prediction range WLPR, which is included in the white line prediction range WLPR and has a reflection intensity equal to or more than a predetermined value. Are supplied to the white line center position calculation unit 18.

  As described with reference to FIG. 3, the white line center position calculation unit 18 calculates the white line center position WLCP from the white line scan data WLSD using Expression (4). Then, the white line center position calculation unit 18 supplies the calculated white line center position WLCP to the host vehicle position estimation unit 19.

  The own vehicle position estimating unit 19 estimates the own vehicle position and the own vehicle azimuth of the vehicle based on the white line map position WLMP in the advanced map and the white line center position WLCP which is the white line measurement data of the external sensor 12. . JP-A-2017-72422 describes an example of a method of estimating the position of the own vehicle by matching landmark position information of an advanced map with measurement position information of a landmark by an external sensor.

  In the above configuration, the external sensor 12 is an example of a sensor unit of the present invention, the scan data extracting unit 17 is an example of an acquiring unit and an extracting unit of the present invention, and the white line position predicting unit 16 is a determining unit of the present invention. This is an example, and the vehicle position estimating section 19 is an example of the processing section of the present invention.

[Vehicle position estimation processing]
Next, the own vehicle position estimating process by the own vehicle position estimating device 10 will be described. FIG. 8 is a flowchart of the vehicle position estimation processing. This processing is realized by a computer such as a CPU executing a prepared program and functioning as each component shown in FIG.

  First, the own vehicle position prediction unit 13 acquires the predicted own vehicle position PVP based on the output from the internal sensor 11 (step S11). Next, the white line map information acquiring unit 15 connects to the server 7 through the communication unit 14 and acquires white line map information from the advanced map stored in the database 8 (Step S12). Here, when the white line map information includes information on the lengths of the solid line portion and the space portion of the dashed white line as described above, the white line map information acquisition section 15 also acquires the information. Either of steps S11 and S12 may be performed first.

  Next, the white line position prediction unit 16 calculates the white line predicted position WLPP based on the white line map position WLMP included in the white line position information obtained in step S12 and the predicted own vehicle position PVP obtained in step S11. (Step S13). The white line position prediction unit 16 determines a white line prediction range WLPR based on the white line prediction position WLPP. At this time, the white line position prediction unit 16 performs a correction to move or extend the white line prediction range WLPR when all the white line prediction ranges WLPR coincide with the space SP of the dashed white line as described above. . Then, the white line position prediction unit 16 supplies the white line prediction range WLPR to the scan data extraction unit 17 (Step S14).

  Next, the scan data extraction unit 17 extracts, from the scan data SD obtained from the LiDAR as the external sensor 12, the scan data that belongs to the white line prediction range WLPR, is on the road surface, and has a reflection intensity of a predetermined value or more. It is extracted as scan data WLSD and supplied to the white line center position calculation unit 18 (step S15).

  Next, the white line center position calculation unit 18 calculates the white line center position WLCP based on the white line prediction range WLPR and the white line scan data WLSD, and supplies the white line center position WLCP to the host vehicle position estimation unit 19 (step S16). Then, the own vehicle position estimating unit 19 estimates the own vehicle position using the white line center position WLCP (step S17), and outputs the own vehicle position and the own vehicle azimuth (step S18). Thus, the vehicle position estimation processing ends.

[Modification]
In the above embodiment, the white line, which is the lane boundary line indicating the lane, is used.However, the application of the present invention is not limited to this, and a linear road sign such as a pedestrian crossing or a stop line may be used. Good. Further, a yellow line or the like may be used instead of the white line. These division lines, such as white lines and yellow lines, and road markings are examples of the road surface line of the present invention.

Reference Signs List 5 vehicle 7 server 8 database 10 own vehicle position estimating device 11 inside sensor 12 outside sensor 13 own vehicle position predicting unit 14 communication unit 15 white line map information acquisition unit 16 white line position predicting unit 17 scan data extracting unit 18 white line center position calculating unit 19 own vehicle position estimation unit

Claims (11)

An acquisition unit that acquires output data from a sensor unit for detecting a surrounding road surface line,
A determination unit that determines a predetermined range based on the self-position and the position information of the dashed road surface line and the interval between the solid line portions of the dashed road surface line,
An extracting unit that extracts data corresponding to the detection result of the predetermined range from the output data;
A processing unit that performs predetermined processing based on the extracted data;
A measuring device comprising:   The said determination part determines the said several predetermined range so that at least 1 of several predetermined ranges may overlap with the solid line part of the said broken-line type road surface line in at least one part of the said predetermined range. 2. The measuring device according to 1.   The determining unit determines the plurality of predetermined positions based on the position information of the self-position and the dashed road surface line, and all of the determined plurality of predetermined ranges are space portions of the dashed road surface line. 3. The measuring device according to claim 2, wherein at least one of the plurality of predetermined ranges is moved when they match.   The determination unit determines the plurality of predetermined positions based on the position information of the self-position and the dashed road surface line, and all of the determined plurality of predetermined positions are space portions of the dashed road surface line. The measuring device according to claim 2, wherein, when they match, at least one of the plurality of predetermined ranges is lengthened.   The measuring device according to claim 2, wherein the determination unit makes the length of the predetermined range longer than a length of a space portion of the broken road surface line.   The measuring apparatus according to claim 5, wherein the determining unit changes the length of the predetermined range according to a type of a road. The measurement device is mounted on a moving body,
The said extraction part sets the said predetermined range in four places of a right front, a right rear, a left front, and a left rear on the basis of the position of the said moving body, The one of Claim 1 thru | or 6 characterized by the above-mentioned. The measuring device according to item 1.   The said processing part detects the position of the said road surface line, and performs the process which estimates the position of the said measuring device based on the position of the said road surface line, The Claims 1 to 7 characterized by the above-mentioned. Measuring device. A measurement method performed by a measurement device,
An acquisition step of acquiring output data from a sensor unit for detecting a surrounding road surface line,
A self-position, position information of a dashed road surface line, and a determining step of determining a predetermined range based on an interval between solid line portions of the dashed road surface line,
Extracting, from the output data, data corresponding to the detection result of the predetermined range;
A processing step of performing a predetermined process based on the extracted data,
A measurement method, comprising: A program executed by a measurement device including a computer,
An acquisition unit that acquires output data from a sensor unit for detecting a surrounding road surface line,
A determination unit that determines a predetermined range based on the self-position and the position information of the dashed road surface line, and the interval between the solid line portions of the dashed road surface line;
An extracting unit that extracts data corresponding to the detection result of the predetermined range from the output data;
A processing unit that performs a predetermined process based on the extracted data,
A program for causing the computer to function as a computer.   A storage medium storing the program according to claim 10.

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