JP2018024294A - Own position estimation method and own position estimation apparatus - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an own position estimation method with which a deterioration in the estimation accuracy of an own position can be suppressed even in a case where an error in detecting a shift amount occurs due to a tire slip of a mobile body when estimating the own position of the mobile body.SOLUTION: A method includes the steps of: a target sensor incorporated in a mobile body detecting a relative position of a target relative to a subject vehicle itself, the target existing nearby the mobile body (S11); accumulating target position data that is produced by moving a relative position of the target relative to the subject vehicle by a movement amount of the mobile body (S12, S13); detecting a tire slip section that is a section where a tire of the mobile body has slipped (S14-S16); selecting target position data that has been accumulated in a section other than the tire slip section, among the accumulated target position data (S17): and comparing between the selected target position data and map information that contains target position information of a target existing on a map, thus estimating an own position of the subject vehicle (S18, S19).SELECTED DRAWING: Figure 8

Description

  The present invention relates to a self-position estimation method and a self-position estimation apparatus.

  As a technique for estimating the self-position of a moving body such as a vehicle, the surrounding environment information existing in a predetermined area with respect to the moving body is limited, the limited environment information is compared with the environment map, A technique for estimating the self-position is known (see Patent Document 1). In the technique described in Patent Document 1, when the moving body is a vehicle, the self-position is estimated by a method (odometry) for obtaining the moving amount of the vehicle according to the rotation angle and the rotation angular velocity of the left and right wheels.

JP 2008-250906 A

  However, in the technique described in Patent Document 1, an error occurs in the detected value of the moving amount of the vehicle in a tire slip section where the vehicle tire slips due to a curve or the like in rainy weather. For this reason, an error occurs in the target position detected before the passing position of the tire slip section, and the estimation accuracy of the self-position of the vehicle may be lowered.

  In view of the above problems, the present invention suppresses a decrease in self-position estimation accuracy even when a detection error of a moving amount occurs due to a tire slip of the moving body when estimating the self-position of the moving body. An object of the present invention is to provide a self-position estimation method and a self-position estimation apparatus.

  According to one aspect of the present invention, an object in which a relative position of a target existing around a moving body with respect to the moving body is detected, and the relative position of the detected target with respect to the moving body is moved by the moving amount of the moving body. The target position data is accumulated, and the stored target position data is collated with the map information including the target position information of the target existing on the map to estimate the self-position of the moving object. At this time, the tire slip section is detected on the moving path of the moving body, and the target position data selected in the sections other than the tire slip section is selected from the accumulated target position data, and the selected target position is selected. There is provided a self-position estimation method and a self-position estimation apparatus characterized in that the self-position of a moving object is estimated by collating data with map information.

  According to the present invention, when estimating the self-position of a moving body, even if a detection error of the amount of movement occurs due to tire slip of the moving body, self-position estimation that can suppress a decrease in self-position estimation accuracy. A method and a self-position estimation apparatus can be provided.

It is a block diagram which shows an example of the self-position estimation apparatus which concerns on embodiment of this invention. It is a block diagram which shows an example of the self-position estimation circuit which concerns on embodiment of this invention. It is the schematic which shows the driving scene of the own vehicle which concerns on embodiment of this invention. It is the schematic for demonstrating the accumulation | storage process of the target position data at the time of the tire slip of the own vehicle which concerns on a comparative example. It is the schematic for demonstrating the estimation process of the self position at the time of the tire slip of the own vehicle which concerns on a comparative example. It is the schematic for demonstrating the accumulation | storage process of the target position data at the time of the tire slip of the own vehicle which concerns on embodiment of this invention. It is the schematic for demonstrating the estimation process of the self position at the time of the tire slip of the own vehicle which concerns on embodiment of this invention. It is a flowchart for demonstrating an example of the self-position estimation method which concerns on embodiment of this invention. It is a flowchart for demonstrating an example of the slip area determination process which concerns on embodiment of this invention.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following description of the drawings, the same or similar parts are affixed with the same or similar reference numerals. However, it should be noted that the drawings are schematic, and the relationship between the thickness and the planar dimensions, the ratio of the thickness, and the like are different from the actual ones. Moreover, it is a matter of course that portions having different dimensional relationships and ratios are included between the drawings. The following embodiments of the present invention exemplify apparatuses and methods for embodying the technical idea of the present invention, and the technical idea of the present invention is the material, shape, The structure, arrangement, etc. are not specified below. The technical idea of the present invention can be variously modified within the technical scope defined by the claims described in the claims.

<Self-position estimation device>
As shown in FIG. 1, the self-position estimation apparatus according to the embodiment of the present invention can be mounted on a vehicle (hereinafter referred to as “own vehicle”) MC. The self-position estimation apparatus according to the embodiment of the present invention includes a self-position estimation circuit 1, a target sensor 2, a travel information sensor 5, and a driving support system 9.

  The target sensor 2 detects a target existing around the host vehicle MC such as in front of the host vehicle MC. Here, the target is, for example, a line (lane division line, stop line, etc.) on the road surface R0 on which the host vehicle MC travels, a curb on the road shoulder, a guardrail, a sign, or the like. The target sensor 2 includes, for example, an imaging device 3 such as a wide-angle camera and a distance measuring device 4 such as a laser range finder (LRF). The imaging device 3 is mounted in the passenger compartment of the host vehicle MC, and images the front area of the host vehicle MC. The distance measuring device 4 is mounted outside the passenger compartment of the host vehicle MC, irradiates the front area of the host vehicle MC with electromagnetic waves, and detects the reflected wave. The distance measuring device 4 can be mounted around the hood, bumper, license plate, headlight, or side mirror of the host vehicle MC.

  The travel information sensor 5 detects travel information of the host vehicle MC in order to estimate the movement amount of the host vehicle MC. The travel information sensor 5 includes, for example, a wheel speed sensor 6, a gyro sensor 7, and a steering angle sensor 8. The wheel speed sensor 6 detects a wheel speed pulse generated according to the rotation of the wheel W of the host vehicle MC as travel information of the host vehicle MC. The steering angle sensor 8 is provided, for example, in a steering column (not shown) that rotatably supports a steering wheel (not shown), and is a steering angle that is a rotation angle (steering operation amount) of a steering wheel that is a steering operator. The corner is detected as traveling information of the host vehicle MC. The gyro sensor 7 detects the yaw rate generated in the host vehicle MC as travel information of the host vehicle MC.

  Each of the self-position estimation circuit 1 and the driving support system 9 includes, for example, a central processing unit (CPU), a main storage device, an input / output device, an input / output interface, a data bus, etc. Can be configured. When each of the self-position estimation circuit 1 and the driving support system 9 is configured by a semiconductor integrated circuit, a semiconductor integrated circuit such as a programmable logic device (PLD) such as a field programmable gate array (FPGA) is used. Alternatively, a functional logic circuit or logic block set in a general-purpose semiconductor integrated circuit may be used. The memory included in each of the self-position estimation circuit 1 and the driving support system 9 can be configured by a semiconductor storage device, a magnetic storage device, an optical storage device, or the like, and includes a register, a cache memory, and the like.

  The self-position estimating circuit 1 is a method for determining the moving distance (moving amount) and moving direction of the host vehicle MC according to the rotation angle and the rotation angular velocity of the left and right wheels W of the host vehicle MC when traveling on a road surface without tire slip ( Hereinafter, the self-position of the host vehicle MC is estimated by “Odometry”. As shown in FIG. 2, the self-position estimation circuit 1 includes a target position detection unit 11, a movement amount estimation unit 12, a target position storage unit 13, a tire slip detection unit 14, a target selection unit 15, and a map information acquisition unit. 16 and a self-position estimation unit 17.

  The target position detection unit 11 detects the relative position between the target existing around the host vehicle MC and the host vehicle MC based on the detection result of the target existing around the host vehicle MC by the target sensor 2. To do. The target position detection unit 11 outputs a relative position signal including information on the relative position between the detected target and the host vehicle MC to the target position storage unit 13.

  The movement amount estimation unit 12 uses the rotation angle and rotation angular velocity of the left and right wheels W of the host vehicle MC detected by the wheel speed sensor 6 and the like to determine the movement amount ΔP and the movement direction of the host vehicle MC from the previous processing cycle. presume. The movement amount estimation unit 12 outputs a movement amount signal including information on the estimated movement amount ΔP of the host vehicle MC and the movement direction to the target position accumulation unit 13.

  The target position accumulating unit 13 accumulates the relative positions of the target existing around the host vehicle MC and the host vehicle MC using the relative position signal output from the target position detecting unit 11 as input data. Further, the target position accumulating unit 13 uses the movement amount signal output from the movement amount estimating unit 12 as input data, and stores the relative position data of the target and the vehicle MC accumulated in the past until the previous processing cycle. Using the elapsed time up to the present time and the movement amount ΔP included in the movement amount signal, the current relative position with respect to the host vehicle MC is corrected and accumulated as target position data. That is, the target position accumulation unit 13 reverses the movement direction of the host vehicle MC by the movement amount ΔP of the elapsed time until the present time estimated by the movement amount estimation unit 12 from the relative position data of the target accumulated in the past. The target position data moved to is accumulated.

  When the target position storage unit 13 has already stored the target position data by the previous processing cycle, the target position storage unit 13 updates the stored target position data using the movement amount ΔP included in the movement amount signal. To do. In updating the target position data, the relative position included in the already accumulated target position data is relatively moved by the movement amount ΔP included in the movement amount signal. The target position accumulating unit 13 updates the target position data by overwriting the relative position moved relative to the movement amount ΔP on the accumulated target position data.

  The map information acquisition unit 16 acquires map information including position information of the target existing on the map. For example, the map information acquisition unit 16 can be configured by a car navigation system, a map database, or the like. In addition, the map information acquisition part 16 may acquire map information from the outside via communication systems, such as radio | wireless communication (road-to-vehicle communication or vehicle-to-vehicle communication is also possible). In this case, the map information acquisition unit 16 may periodically acquire the latest map information and update the held map information. The map information acquisition part 16 may accumulate | store the track which the own vehicle MC actually drive | worked as map information.

  The self-position estimating unit 17, when traveling on a road surface without a tire slip, uses the target position data accumulated by the target position accumulating unit 13 on the map acquired by the map information acquiring unit 16. By comparing (matching) with the information, the position and orientation of the host vehicle MC are estimated as the own position.

  The driving support system 9 uses the self-position of the own vehicle MC estimated by the self-position estimation unit 17 to present information to the occupant of the own vehicle MC by an alarm or the like, or to brake the own vehicle MC, if necessary. Provide driving assistance.

  Next, an example of a self-position estimation method by odometry using the self-position estimation apparatus according to the embodiment of the present invention will be described with reference to FIGS. As shown in FIG. 3, there is a lane including an S-shaped curve divided by a road boundary, and targets A1 to A7 are arranged on the right road boundary in the traveling direction of the host vehicle MC (above the paper). Has been. The targets A1 to A7 are white lines, curbs, signs, and the like.

  Tire slip may occur on low μ road surfaces and curves. The travel trajectories R1, R2, and R3 in FIG. 3 indicate that the host vehicle MC traveled by odometry when the host vehicle MC entered the tire slip section L1 while traveling on a normal road surface and a road surface tire slip occurred. Is a travel locus in which On the other hand, the traveling trajectories R1, R4, and R5 indicate actual traveling trajectories in which the host vehicle MC enters the tire slip section L1 while traveling on the normal road surface and then returns to the normal road surface. When the host vehicle MC actually travels along the travel tracks R1, R4, and R5, the target position detection unit 11 detects the relative positions of the targets A1 to A7 existing around the host vehicle MC. The movement amount estimation unit 12 estimates the movement amount ΔP and the movement direction of the host vehicle MC. The target position accumulating unit 13 determines the relative positions of the targets A1 to A7 detected by the target position detecting unit 11 in a direction opposite to the moving direction of the host vehicle MC estimated by the moving amount estimating unit 12. The relative positions of the targets A1 to A7 are moved by the movement amount ΔP of the vehicle MC, accumulated as target position data B1 to B7, and updated.

  As shown in FIG. 3, when tire slip occurs on a low μ road surface, a curve, or the like, an odometry is created from the start position (start point) P1 of the tire slip section L1 to the passing position (end point) P2 of the tire slip section L1. Position errors Xa, Xb, and Xc occur in the travel trajectories R1, R2, and R3 and the actual travel trajectories R1, R4, and R5.

  As shown in FIG. 4, the relative positions of the targets A1 to A7 detected by the target sensor 2 and the host vehicle MC are relative positions with respect to the host vehicle MC along the actual travel paths R1, R4, and R5. On the other hand, the target position data B1 to B7 accumulated by odometry are presumed to have traveled along the travel trajectories R1, R2, and R3 and reached the position of the host vehicle MC indicated by the broken line in FIG. Therefore, no error occurs between the target position data B1 and B2 accumulated in the section before passing through the tire slip section L1 and the target position data B6 and B7 stored in the section after passing through the tire slip section L1. However, an error occurs in the target position data B3 to B5 accumulated while passing through the tire slip section L1.

  When self-position estimation is performed in such a state, a correct solution will be estimated when positioning is performed after passing through the tire slip section L1, but the distance difference due to tire slip is included while passing through the tire slip section L1. Since it is an incorrect solution, for example, when matching is performed with a minimum error, the estimation error may not be reduced. For example, when passing the tire slip section L1 and changing the lane and entering the next lane, etc., it is desired to perform self-position estimation using a target such as a lane or curb of the next lane. Since there is more data for the target before passing the tire slip section L1 for a while until the target after passing is accumulated, the lateral position error before passing is not the target of the lane next to the lane change destination. The target including the will act dominantly in the matching, and the estimation error may increase.

  Further, as shown in FIG. 5, the trajectories of the target position data B1 to B7 have a shape deviating from the trajectories of the target position information C1 to C7 included in the map information, for example, before the start of the tire slip section L1. The object accumulated in the section after passing through the tire slip section L1 with respect to the difference X1, X2 between the target position data B1, B2 accumulated in the section and the target position information C1, C2 included in the map information Differences X6 and X7 between the target position data B6 and B7 and the target position information C6 and C7 included in the map information are increased. Therefore, as shown in a region Ra of FIG. 5, the target position information C1 included in the map information is given priority on the target position data B1 and B2 accumulated in the section before the start of the tire slip section L1 without error. , C2, and as shown in the region Rb of FIG. 5, the target position data B6, B7 accumulated in the section after passing the tire slip section L1 is prioritized and included in the map information. In the case of matching with the position information C6 and C7, there are two estimated self-positions, which are not the only solution. As a result, it may be positioned before the start of the tire slip section L1, positioned after passing the tire slip section L1, or may become unstable.

  Therefore, in the embodiment of the present invention, the tire slip detection unit 14 and the target selection unit 15 shown in FIG. 1 are provided in order to suppress a decrease in the estimation accuracy of the self-position caused by the tire slip section L1. . The tire slip detection unit 14 determines whether or not the travel path on which the host vehicle MC is traveling is the tire slip section L1, and outputs a determination result signal including the determination result to the target selection unit 15.

  As a method for determining the tire slip section L1, for example, the road surface friction coefficient is estimated from the amount of change in the wheel speed data of the four wheels of the host vehicle MC detected by the wheel speed sensor 6. And it can be determined whether it is the tire slip area L1 by determining whether the estimated road surface friction coefficient is more than a predetermined threshold value (for example, 0.5). That is, when the road surface friction coefficient is equal to or greater than a predetermined threshold, it is determined that the vehicle is passing through the tire slip section L1. On the other hand, when the road surface friction coefficient is less than a predetermined threshold value, it is determined that the vehicle is not passing through the tire slip section L1.

  The method for determining the tire slip section L1 is not limited to the method using the road surface friction coefficient, and various methods can be employed. For example, it is possible to determine whether or not the tire slip section L1 is based on a relative relationship between detected values related to vehicle behavior such as a steering angle detected by the steering angle sensor 8 and a yaw rate detected by the gyro sensor 7. Or you may determine the tire slip area L1 by estimating a road surface state from the analysis by the image obtained from the imaging device 3 grade | etc., 3D point cloud flow, odometry etc.

  The tire slip detection unit 14 detects the occurrence of tire slip and estimates the start position (start point) P1 of the tire slip section L1. The tire slip detection unit 14 detects the fit of the tire slip and estimates the passing position (end point) P2 of the tire slip section L1.

  When the tire slip section L1 is detected by the tire slip detection section 14, the target selection section 15 accumulates in sections other than the tire slip section L1 from the target position data accumulated in the target position accumulation section 13. The selected target position data is selected as target position data for self-position estimation at the time of tire slip. For example, as shown in FIG. 4, the target selection unit 15 uses the target position data B1 accumulated before the start of the tire slip section L1 from the target position data B1 to B7 accumulated by the target position accumulation unit 13. , B2 and the target position data B3 to B5 accumulated while passing through the tire slip section L1, and the target position data accumulated in the section after passing through the tire slip section L1, as shown in FIG. Select B6 and B7. In addition, although the case where the target position data B6 and B7 of 2 points | pieces is selected is illustrated here, the number of target position data to select is not limited, What is necessary is just the number which can estimate a self position by matching.

  Immediately after passing through the tire slip section L1, at least target position data existing around the host vehicle MC and target position data existing between the current position of the host vehicle MC and the passing position of the tire slip section L1 are selected. . The target position data around the current position of the host vehicle MC and the tire slip section L1, and the elapsed time is comparatively selected, and the newly accumulated target is selected preferentially for self-position estimation. Use. For example, the periphery of the current position of the host vehicle MC can be set in advance at about 20 m. The target position data around the current position of the host vehicle MC tend to have higher position accuracy because there are few errors in detecting the amount of movement of the host vehicle MC. In particular, the position data of lanes and curbs that are road boundaries have high lateral position accuracy in the runway.

  As shown in FIG. 6, when target position data B6 and B7 for self-position estimation at the time of tire slip are selected by the target selecting section 15, the self-position estimating section 17 is as shown in FIG. The target position data B6, B7 selected by the target selection unit 15 is collated with the position information C6, C7 of the target existing on the map acquired by the map information acquisition unit 16, so that the vehicle MC The current position P3 and the posture are estimated as the self position.

<Self-position estimation method>
Next, an example of the self-position estimation method according to the embodiment of the present invention will be described with reference to the flowchart of FIG. The procedure of the flowchart of FIG. 8 is repeatedly executed at a predetermined processing cycle, and the target position storage unit 13 stores target position data in each processing cycle.

  In step S <b> 11, the target position detection unit 11 detects a relative position between the target existing around the host vehicle MC and the host vehicle MC from the detection result of the target sensor 2. In step S12, the movement amount estimation unit 12 estimates the movement direction and movement amount of the host vehicle MC according to the rotation angle and rotation angular velocity of the left and right wheels W detected by the wheel speed sensor 6 and the like.

  In step S <b> 13, the target position accumulation unit 13 accumulates the relative positions of the target and the vehicle MC present around the host vehicle MC detected by the target position detection unit 11. The target position accumulating unit 13 calculates the relative position between the target and the vehicle MC existing around the host vehicle MC accumulated in the past, the elapsed time from the past accumulation to the present, and the movement amount estimation unit. 12 is corrected to the relative position of the target with respect to the current position of the host vehicle MC, and accumulated as target position data.

  In step S14, the tire slip detection unit 14 detects the tire slip section and determines whether or not the host vehicle MC has passed the tire slip section. When it is determined that the host vehicle MC has not passed the tire slip section, the process proceeds to step S16. On the other hand, when it determines with the own vehicle MC having passed the tire slip area in step S14, it transfers to step S15.

  Here, an example of the details of the tire slip section passage determination process in step S14 of FIG. 8 will be described with reference to the flowchart of FIG.

  In step S21, the tire slip detection unit 14 determines whether or not the host vehicle MC is passing through the tire slip section in the immediately preceding processing cycle. When it is determined that the host vehicle MC is not passing through the tire slip section, the process proceeds to step S22.

  In step S22, for example, it is determined whether or not the host vehicle MC has entered the tire slip section by determining whether or not the road surface friction coefficient is greater than or equal to a predetermined threshold (for example, 0.5). When it is determined that the road surface friction coefficient is equal to or greater than the predetermined threshold value and the vehicle has not entered the tire slip section, the host vehicle MC has not passed the tire slip section, and thus the process proceeds to step S16 in FIG.

  On the other hand, if it is determined in step S22 that the road surface friction coefficient is less than the predetermined threshold value and the host vehicle MC has entered the tire slip section, the process proceeds to step S23, and the host vehicle MC in the current processing cycle is changed. The position is estimated as the start position of the tire slip section. In this case, since the host vehicle MC has not passed through the tire slip section, the process proceeds to step S16 in FIG.

  If it is determined in step S21 that the host vehicle MC is passing the tire slip section in the previous processing cycle, the process proceeds to step S24. In step S24, for example, it is determined whether or not the tire slip section has been passed by determining whether or not the road surface friction coefficient is equal to or greater than a predetermined threshold (for example, 0.5). Note that the predetermined threshold value used in step S24 and the predetermined threshold value used in step S22 may be the same value or different values.

  In step S24, when it is determined that the road surface friction coefficient is equal to or greater than a predetermined threshold value and has passed through the tire slip section, the position of the host vehicle MC in the current processing cycle is estimated as the passing position of the tire slip section. The process proceeds to step S15. On the other hand, if it is determined in step S24 that the road surface friction coefficient is less than the predetermined threshold value and the vehicle is passing through the tire slip section, the host vehicle MC has not passed through the tire slip section, so step S16 in FIG. Migrate to

  In step S15 of FIG. 8, the target selection unit 15 excludes target position data before passing through the tire slip section from the accumulated target position data. Alternatively, when it is necessary to suppress the data capacity, the target selection unit 15 deletes the target position data before passing through the tire slip section from the accumulated target position data.

  In step S <b> 16, the map information acquisition unit 16 acquires map information including target position information of the target existing on the map. In step S <b> 17, the self-position estimation unit 17 compares the map information acquired by the map information acquisition unit 16 with the target position data stored by the target position storage unit 13, so that the host vehicle on the map The position and orientation of the MC are estimated as the self position. When the process proceeds to step S17 via step S15, the self-position estimation unit 17 uses the target position data accumulated in the sections other than the tire slip section to determine the position and orientation of the host vehicle MC on the map. Estimate as self-position.

<Self-position estimation program>
Note that the self-position estimation program according to the embodiment of the present invention is a computer such as the self-position estimation circuit 1 that constitutes the self-position estimation apparatus shown in FIG. Can be executed. The self-position estimation program according to the embodiment of the present invention can be stored in, for example, a memory of the self-position estimation circuit 1.

  As described above, according to the embodiment of the present invention, the target position data accumulated from the sections other than the tire slip section is selected by excluding the target position data in the tire slip section. And the self position of the own vehicle MC is estimated by collating the selected target position data with map information. As a result, it is possible to suppress a decrease in the estimation accuracy of the self-position due to a measurement error of the target position caused by tire slip. For example, when passing through a tire slip section and changing to a lane and entering an adjacent lane, self-position estimation is performed with an accurate target position such as a lane or curb of the lane next to the lane change destination. It can be estimated with high accuracy.

  Further, the target position data accumulated in the section after passing through the tire slip section is selected, and the self position of the host vehicle MC is estimated using the selected target position data. Thereby, even if a detection error of the movement amount occurs due to tire slip, the self-position can be accurately estimated without adversely affecting the target including the distance difference before passing through the tire slip section.

  Further, the accumulated target position data around the current position of the host vehicle MC is selected, and the own position of the host vehicle MC is estimated using the selected target position data. Thereby, the target position data whose self-position estimation accuracy is increased can be appropriately selected.

(First modification)
As a first modification of the embodiment of the present invention, the target selection unit 15 is for self-position estimation at the time of tire slip when the tire slip section detected by the tire slip detection section 14 is longer than a predetermined section length. A case where target position data is selected will be described. The longer the tire slip section becomes, the more the influence on self-position estimation becomes, such as when the road surface becomes low μ during a curve or rain, and the tire slip section becomes longer. On the other hand, when the vehicle MC passes through a puddle, or when the tire of the vehicle MC steps on a stone, when a slip occurs instantaneously and the tire slip section is relatively short, the influence on the self-position estimation. Is relatively small.

  Therefore, the target selection unit 15 determines whether the tire slip section detected by the tire slip detection unit 14 is equal to or longer than a predetermined section length. The predetermined section length can be set as appropriate. For example, the target selection unit 15 determines whether or not the passage time of the tire slip section detected by the tire slip detection unit 14 is equal to or longer than a predetermined time (for example, 1 second). When it is determined that the passing time of the tire slip section is a predetermined time (for example, 1 second) or more, the target selection unit 15 selects target position data for self-position estimation at the time of tire slip. On the other hand, when it is determined that the passing time of the tire slip section is less than a predetermined time (for example, 1 second), the target selection unit 15 does not select the target position data for self-position estimation at the time of tire slip. That is, the self-position estimation is performed using the target position data by the normal process without performing the selection process of the target position data at the time of tire slip. In the normal process, the target position data can be selected under other conditions.

  According to the first modification, when the tire slip section is a predetermined section length (for example, 1 second) or longer, the target position data accumulated from the sections other than the tire slip section is selected for self-position estimation. The target position can be estimated by appropriately excluding the target position data accumulated in the affected tire slip section. On the other hand, when the tire slip section is less than a predetermined section length (for example, 1 second), the calculation load can be reduced by not performing the process of selecting the target position data.

(Second modification)
As a second modification of the embodiment of the present invention, the target position data accumulated in the section before the start of the tire slip section is corrected using the target position data after passing through the tire slip section. explain.

  For example, as shown in FIG. 7, the self-position estimation unit 17 uses the target position data B6 and B7 after passing through the tire slip section L1 selected by the target selection unit 15 to indicate the vehicle MC on the map. The current self position P3 is estimated. The self-position estimating unit 17 is a past self-position of the host vehicle MC on the map estimated using the target position data B1 and B2 accumulated in the section before the start of the tire slip section L1 (here, for example, the host vehicle The past self position of the MC is set as the start position P1 of the tire slip section L1) from the memory of the self position estimation circuit 1. It is assumed that the past self-position P3 of the host vehicle MC is estimated and accumulated by the self-position estimation unit 17 in the previous processing cycle. The self-position estimating unit 17 calculates a relative position between the current self-position P3 of the host vehicle MC and the past self-position P1 of the host vehicle MC.

  The self-position estimating unit 17 is a map of the target position data B1 and B2 before the start of the tire slip section L1 from the relative position between the current self-position P3 of the own vehicle MC and the past self-position P1 of the own vehicle MC. Correct the upper position. This makes it possible to reuse target position data orthogonal to the road, such as an intersection or a stop line before the start of the tire slip section L1, and improve the accuracy of self-position estimation.

  According to the second modification, the self-position estimating unit 17 passes the self-position P1 estimated from the target position data B1 and B2 accumulated from the section before the start of the tire slip section L1, and the tire slip section L1. Based on the relative position with the self-position P3 estimated from the target position data B6 and B7 accumulated from the subsequent section, the accumulated target position data B1 and B2 of the section before the start of the tire slip section L1 are corrected. To do. Then, the self-position estimating unit 17 estimates the self-position using the corrected target position data B1 and B2 in addition to the target position data B6 and B7 accumulated from the section after passing through the tire slip section L1. . Thereby, the accuracy of self-position estimation can be improved.

(Other embodiments)
As mentioned above, although this invention was described by embodiment, it should not be understood that the statement and drawing which form a part of this indication limit this invention. From this disclosure, various alternative embodiments, examples and operational techniques will be apparent to those skilled in the art.

  For example, the target selection unit 15 may include the target position data detected after passing through the tire slip section at the time of accumulation or selection of the target position data in order to increase the accuracy of position estimation and shorten the processing time. Alternatively, a target having a large angle with respect to the traveling direction of the host vehicle MC may be left preferentially, and other target position data may be excluded. Alternatively, the target selection unit 15 may exclude target position data that is separated from the host vehicle MC by a predetermined distance or more. The predetermined distance can be adjusted in accordance with a position estimation error caused by a large measurement error due to a large change in tire slip or the like.

  In the embodiment of the present invention, the case where the self-position estimation device is mounted on the host vehicle MC is exemplified. However, for example, the self-position estimation device can be applied to a moving body other than a vehicle such as a robot having wheels. is there.

  It goes without saying that the present invention includes various embodiments not described herein. Therefore, the technical scope of the present invention is defined only by the invention specifying matters according to the scope of claims reasonable from the above description.

DESCRIPTION OF SYMBOLS 1 ... Self-position estimation circuit 2 ... Target sensor 3 ... Imaging device 4 ... Distance measuring device 5 ... Traveling information sensor 6 ... Wheel speed sensor 7 ... Gyro sensor 8 ... Steering angle sensor 9 ... Driving support system 11 ... Target position detection Unit 12 ... Movement amount estimation unit 13 ... Target position accumulation unit 14 ... Tire slip detection unit 15 ... Target selection unit 16 ... Map information acquisition unit 17 ... Self-position estimation unit

Claims (6)

A target sensor that is mounted on the moving body and detects a relative position of the target existing around the moving body with respect to the moving body;
The target position data obtained by moving the relative position of the detected target relative to the moving body by the moving amount of the moving body is accumulated, and the accumulated target position data and the target object existing on the map are stored. In the self-position estimation method using the self-position estimation circuit that estimates the self-position of the mobile body by collating with map information including the target position information,
Detecting a tire slip section in the moving path of the moving body;
Of the accumulated target position data, selecting target position data accumulated in a section other than the tire slip section;
A self-position estimation method comprising: comparing the selected target position data with the map information to estimate the self-position of the moving object.   2. The self-position estimation method according to claim 1, wherein the step of selecting the target position data selects target position data accumulated in a section after passing through the tire slip section. The step of estimating the self-position includes
A self-position estimated from target position data accumulated in a section after passing through the selected tire slip section; and a self-position estimated from target position data accumulated in a section before the start of the tire slip section; From the relative position of, correct the target position data accumulated in the section before the start of the tire slip section,
The self-position estimation method according to claim 2, wherein the self-position of the moving body is estimated using the selected target position data and the corrected target position data.   The step of selecting the target position data selects the target position data when the tire slip section is equal to or longer than a predetermined section length. Self-position estimation method.   5. The self-position estimation according to claim 1, wherein the step of selecting the target position data selects target position data existing around a current position of the moving body. Method. A target sensor that is mounted on the moving body and detects a relative position of the target existing around the moving body with respect to the moving body;
The target position data obtained by moving the relative position of the detected target relative to the moving body by the moving amount of the moving body is accumulated, and the accumulated target position data and the target object existing on the map are stored. A self-position estimating circuit for estimating the self-position of the mobile body by collating with map information including the target position information,
The self-position estimation circuit detects a tire slip section on the moving path of the moving body, and selects target position data accumulated in a section other than the tire slip section from the accumulated target position data. A self-position estimating apparatus that estimates the self-position of the moving body by collating the selected target position data with the map information.

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