WO2018221456A1

WO2018221456A1 - Route searching device, control method, program, and storage medium

Info

Publication number: WO2018221456A1
Application number: PCT/JP2018/020368
Authority: WO
Inventors: 和紀小山; 加藤　正浩
Original assignee: パイオニア株式会社
Priority date: 2017-05-31
Filing date: 2018-05-28
Publication date: 2018-12-06

Abstract

A server device 2 receives, from an in-vehicle machine 1 in each general vehicle, change point information D1 indicative of the result of matching between an output from a lidar 30 and voxel data in a map DB 10, and determines, on the basis of accumulated change point information D1, a voxel Btag to be measured that is a voxel needed to be measured. The server device 2 then searches for, as a measurement path for a measurement vehicle, a path including, as a via point, a position where the voxel Btag to be measured can be measured, and transmits, to a measurement system 4 of the measurement vehicle, measurement path information D2 including information about the measurement path.

Description

Route search apparatus, control method, program, and storage medium

The present invention relates to route search technology.

Conventionally, a technique for setting a route of a survey vehicle so as to pass through a point where a change to be reflected on a map has been known. For example, in Patent Document 1, when a road whose traffic volume has changed significantly before and after a specific reference date is detected based on probe information from a plurality of probe cars, it is important to affect the road. A road network analysis system that searches for a survey route that passes through a change-related road that is regarded as a change-related road that has undergone a change in the road network is disclosed.

JP 2012-150016 A

When generating and updating a high-accuracy map that can be used for autonomous driving, etc., it is necessary to accurately reflect changes in stationary structures around the road as well as changes in traffic volume. In view of the above, a main object of the present invention is to provide a route search device capable of preferably searching for a route on which a measurement vehicle for map maintenance should travel.

The invention according to claim 1 is a route search device, and a first acquisition unit that acquires first point cloud information about each distance from a reference position to a plurality of positions measured by the measurement unit; Measurement is performed based on a second acquisition unit that acquires map information in which second point group information based on a plurality of position information is recorded for each region, and a comparison result of the first point group information and the second point group information. A search unit that determines a necessary target area and searches for a route that uses a position where the target area can be measured as a transit point.

The invention according to claim 9 is a control method executed by the route search apparatus, wherein the first point cloud information about each distance from the reference position to a plurality of positions measured by the measurement unit, and a map for each region Based on the collation result with the second point cloud information recorded in the information, a determination step for determining the target area that is an area that needs to be measured, and a route that uses the target area as a route from the position where the target area can be measured are searched. And a search step.

The invention according to claim 10 is a program executed by a computer, and is recorded in map information for each area and first point cloud information about each distance from a reference position to a plurality of positions measured by a measurement unit. A determination unit that determines a target region that is a region that needs to be measured based on a collation result with the second point cloud information that has been performed, and a search unit that searches for a route that uses a position where the target region can be measured as a waypoint To make the computer function.

1 is a schematic configuration of a map generation system. The block configuration of a vehicle equipment, a server apparatus, and a measurement system is shown. An example of the schematic data structure of voxel data is shown. A specific example of NDT scan matching will be described. It is a flowchart which shows the process sequence which an onboard equipment performs. It is a flowchart which shows the process sequence which a server apparatus performs. An overhead view around the measurement vehicle when the measurement vehicle travels based on the measurement route is shown.

According to a preferred embodiment of the present invention, there is provided a route search device, the first point group information relating to each distance from the reference position to a plurality of positions measured by the measurement unit, and recorded in the map information for each area. A determination unit that determines a target region that is a region that needs to be measured based on a collation result with the second point cloud information that has been performed, and a search unit that searches for a route that uses a position where the target region can be measured as a waypoint And comprising. According to this aspect, the route search device can identify a target area that needs to be measured based on a result of matching between the first point cloud information measured by the measurement unit and the second point cloud information of the map information, and can measure the target area. It is possible to search for a suitable route.

In one aspect of the route search device, the search unit outputs information on the route in which the lane on which the measurement vehicle should travel is specified at least within a range in which the target area can be measured. According to this aspect, the route search device can output route information of a measurement vehicle in which a lane suitable for measuring the target region is designated.

In another aspect of the route search device, the search unit outputs information related to the route that specifies a speed at which the measurement vehicle should travel at least within a range in which the target area can be measured. According to this aspect, the route search device can output route information of the measurement vehicle that specifies a speed suitable for measuring the target region.

In another aspect of the route search device, the search unit acquires the current position of the measurement vehicle, and searches for the route using the current position as a departure point. According to this aspect, the route search device can suitably search for a route on which a specific measurement vehicle should travel.

In another aspect of the route search device, the first acquisition unit acquires information on measurement conditions when the first point group information is measured together with the first point group information, and the determination unit includes: The target region is determined based on the collation result and information on the measurement condition. According to this aspect, the route search device can determine the target region to be measured in consideration of the measurement conditions when the first point cloud information is measured.

In another aspect of the route search device, the determination unit may use the target region based on at least one of a time zone, day of the week, and weather when the first point cloud information is measured as the measurement condition. To decide. In this aspect, the route search device can determine the target region to be measured in consideration of the time zone at the time of measurement, the day of the week, or the weather.

In another aspect of the route search apparatus, the first acquisition unit receives the verification result from a plurality of vehicles including the measurement unit, and the search unit provides information on the route as driving assistance for the measurement vehicle. Is transmitted to the control device. According to this aspect, the route search device functions as a server device that collects the matching results received from a plurality of vehicles, and transmits information on the route searched based on the collected matching results to the control device of the measurement vehicle. it can.

In another aspect of the route search device, the route search device further includes a drive support unit that is mounted on the measurement vehicle and performs drive support so that the measurement vehicle travels on the route searched by the search unit. Thus, in the aspect mounted on the measurement vehicle, the route search device can search for a route on which the measurement vehicle should travel, and suitably perform driving support so that the measurement vehicle travels on the searched route.

According to another preferred embodiment of the present invention, there is provided a control method executed by the route search apparatus, the first point cloud information about each distance from the reference position to a plurality of positions measured by the measurement unit, A determination step for determining a target region that is a region that needs to be measured based on a collation result with the second point cloud information recorded in the map information for each region, and a location where the target region can be measured And a search step for searching for a route to be performed. By executing this control method, the route search device identifies a target region that needs to be measured based on a result of matching between the first point cloud information and the second point cloud information, and creates a route that can measure the target region. It can search suitably.

According to still another embodiment of the present invention, a program executed by a computer, the first point cloud information regarding each distance from a reference position to a plurality of positions measured by a measurement unit, and a map for each region Based on the collation result with the second point cloud information recorded in the information, a determination unit that determines a target area that is an area that needs to be measured, and a route that uses the position where the target area can be measured as a route The computer is caused to function as a search unit. By executing this program, the computer specifies a target area that needs to be measured based on a result of collation between the first point cloud information and the second point cloud information, and suitably searches for a path that can measure the target area. can do. Preferably, the program is stored in a storage medium.

Hereinafter, preferred embodiments of the present invention will be described with reference to the drawings.

[Overview of map generation system]
(1) System Configuration FIG. 1 is a schematic configuration of a map generation system according to this embodiment. The map generation system includes an in-vehicle device 1 mounted on a general vehicle, a server device 2 that distributes and updates map information, and a measurement system 4 mounted on a measurement vehicle for map maintenance.

The in-vehicle device 1 is electrically connected to an external sensor such as a lidar (Lidal: Light Detection and Ranging, or Laser Illuminated Detection And Ranging), an internal sensor such as a gyro sensor or a vehicle speed sensor, and based on these outputs. The position of a general vehicle on which the in-vehicle device 1 is mounted (also referred to as “own vehicle position”) is estimated. The in-vehicle device 1 stores map data including voxel data. The voxel data is data in which position information of a stationary structure is recorded for each area (also referred to as “voxel”) when the three-dimensional space is divided into a plurality of areas. The voxel data includes data representing the point cloud data measured for the stationary structure in each voxel by a normal distribution. The in-vehicle device 1 performs scan matching based on NDT (Normal Distributions Transform) based on the point cloud data output by the lidar and the voxel data corresponding to the voxel to which the point cloud data belongs. Then, when the degree of matching with the stored voxel data is lower than the threshold, the in-vehicle device 1 determines that the region used for matching has changed significantly, and all of the used in matching at positions where the degree of matching is lower than the threshold. Is transmitted to the server apparatus 2 as change point information “D1”. When the degree of matching is larger than the threshold, the degree of matching for each voxel is calculated. When a voxel whose degree of matching for each voxel is lower than a threshold value is detected, it is determined that the voxel may include a change point at which a change from the map data has occurred, and information regarding the detected voxel is changed point information D1. As shown in FIG. In addition, the function equivalent to the vehicle equipment 1 may be incorporated in the general vehicle.

The server device 2 performs data communication with the in-vehicle device 1 corresponding to a plurality of general vehicles. The server device 2 stores a distribution map DB 20 for distribution to the vehicle-mounted device 1 corresponding to a plurality of vehicles, and the distribution map DB 20 includes voxel data corresponding to each voxel. The server device 2 accumulates the change point information D1 received from the vehicle-mounted device 1, and specifies a voxel (also referred to as “measurement target voxel Btag”) that requires measurement by the measurement vehicle based on the accumulated change point information D1. . Then, the server device 2 determines a route (also referred to as “measurement route”) via a position where the measurement target voxel Btag can be measured, and obtains measurement route information “D2” specifying the measurement route. Transmit to the measurement system 4. The change point information D1 is an example of the “matching result” in the present invention, and the measurement target voxel Btag is an example of the “target region” in the present invention.

The measurement system 4 is a system that generates highly accurate 3D point cloud data, and performs driving such as automatic driving and route guidance so that the measurement vehicle travels along the measurement route indicated by the measurement route information D2 received from the server device 2. Provide support. The measurement system 4 is an example of the “control device” in the present invention.

(2) Configuration of the in-vehicle device FIG. 2A is a block diagram showing a functional configuration of the in-vehicle device 1. As shown in FIG. 2A, the in-vehicle device 1 mainly includes a communication unit 11, a storage unit 12, a sensor unit 13, an input unit 14, a control unit 15, and an output unit 16. The communication unit 11, the storage unit 12, the sensor unit 13, the input unit 14, the control unit 15, and the output unit 16 are connected to each other via a bus line.

The communication unit 11 receives the map information distributed from the server device 2 based on the control of the control unit 15 or transmits the change point information D1 generated by the control unit 15 to the server device 2. The storage unit 12 stores a program executed by the control unit 15 and information necessary for the control unit 15 to execute a predetermined process. In the present embodiment, the storage unit 12 stores a map DB 10 including voxel data.

The sensor unit 13 includes a rider 30, a camera 31, a GPS receiver 32, a gyro sensor 33, and a speed sensor 34. The lidar 30 emits a pulse laser in a predetermined angular range in the horizontal direction and the vertical direction, thereby discretely measuring the distance to an object existing in the outside world, and a three-dimensional point indicating the position of the object Generate group data. In this case, the lidar 30 scans data based on an irradiation unit that emits laser light while changing the irradiation direction, a light receiving unit that receives reflected light (scattered light) of the irradiated laser light, and a light reception signal output by the light receiving unit. Output unit. The scan data is generated based on the irradiation direction corresponding to the laser beam received by the light receiving unit and the response delay time of the laser beam specified based on the above-described received light signal. The lidar 30 is an example of the “measurement unit” in the present invention, and the point cloud data output by the lidar 30 is an example of the “first point cloud information” in the present invention.

The input unit 14 is a button, a touch panel, a remote controller, a voice input device, or the like for a user to operate, and accepts an input for specifying a destination for route search, an input for specifying on / off of automatic driving, and the like. The generated input signal is supplied to the control unit 15. The output unit 16 is, for example, a display or a speaker that performs output based on the control of the control unit 15.

The control unit 15 includes a CPU that executes a program and controls the entire vehicle-mounted device 1. For example, the control unit 15 estimates the host vehicle position by performing scan matching based on NDT based on the point cloud data output from the lidar 30 and the voxel data corresponding to the voxel to which the point cloud data belongs. Do. Further, the control unit 15 detects a voxel that is estimated to have low matching accuracy based on an evaluation value (a comprehensive evaluation function value described later) obtained by scan matching based on NDT and an evaluation value for each voxel. And the control part 15 produces | generates the change point information D1 corresponding to the detected voxel, and transmits the change point information D1 to the server apparatus 2 by the communication part 11. FIG.

(3) Configuration of Server Device FIG. 2B shows a schematic configuration of the server device 2. As illustrated in FIG. 2B, the server device 2 includes a communication unit 21, a storage unit 22, and a control unit 25. The communication unit 21, the storage unit 22, and the control unit 25 are connected to each other via a bus line.

The communication unit 21 communicates various data with the in-vehicle device 1 and the measurement system 4 based on the control of the control unit 25. The storage unit 22 stores a program for controlling the operation of the server device 2 and holds information necessary for the operation of the server device 2. In addition, the storage unit 22 stores the distribution map DB 20 and also stores change point information D1 transmitted from the plurality of in-vehicle devices 1.

The control unit 25 includes a CPU, a ROM, a RAM, and the like (not shown), and performs various controls on each component in the server device 2. In the present embodiment, the control unit 25 accumulates the change point information D1 received from the in-vehicle device 1 in the storage unit 22, and specifies the measurement target voxel Btag based on the accumulated change point information D1. Then, the control unit 25 determines a measurement route including the measurement target voxel Btag in the measurement range, and transmits the measurement route information D2 including the measurement route information to the measurement system 4 of the measurement vehicle by the communication unit 21. The control unit 25 is an example of a “determination unit”, a “search unit” in the present invention, and a “computer” that executes a program in the present invention.

(4) Configuration of Measurement System FIG. 2C shows a schematic configuration of the measurement system 4. As shown in FIG. 2C, the measurement system 4 functionally includes a communication unit 41, a storage unit 42, a sensor unit 43, and a control unit 45. Each of these elements is connected to each other via a bus line.

The communication unit 41 communicates various data with the server device 2 based on the control of the control unit 45. The communication unit 41 transmits a signal for controlling the measurement vehicle to the measurement vehicle, or receives a signal related to the state of the measurement vehicle from the measurement vehicle. The storage unit 42 stores a program executed by the control unit 45 and stores measurement data measured by the sensor unit 43.

The sensor unit 43 includes a lidar 46, an RTK-GPS 47, an IMU (Internal Measurement Unit) 48, and the like. The RTK-GPS 3 generates highly accurate position information indicating the absolute position (for example, the three-dimensional position of latitude, longitude, and altitude) of the measurement vehicle based on the RTK positioning method (that is, the interference positioning method). The IMU 48 generates information on the acceleration and angular velocity (or angle) of the measurement vehicle in the three-axis directions.

The control unit 45 executes a program or the like stored in the storage unit 42 or the like, and controls the entire measurement system 4. In the present embodiment, the control unit 45 receives the measurement route information D2 transmitted from the server device 2, and performs automatic driving control on the measurement vehicle so that the measurement vehicle travels on the route indicated by the received measurement route information D2. Provide driving assistance such as route guidance. Further, the control unit 45 stores the measurement data output from the sensor unit 43 in the storage unit 42 and transmits the stored measurement data to the server device 2.

[Scan matching based on NDT]
Next, scan matching based on NDT executed by the vehicle-mounted device 1 of a general vehicle will be described.

(1) Data structure of voxel data First, voxel data used for scan matching based on NDT will be described. FIG. 3 shows an example of a schematic data structure of voxel data.

The voxel data includes parameter information when the point group in the voxel is expressed by a normal distribution. In this embodiment, as shown in FIG. 3, the voxel ID, voxel coordinates, average vector, and covariance matrix are used. And point cloud number information. Here, “voxel coordinates” indicate absolute three-dimensional coordinates of a reference position such as the center position of each voxel. Each voxel is a cube obtained by dividing the space into a lattice shape, and since the shape and size are determined in advance, the space of each voxel can be specified by the voxel coordinates. The voxel coordinates may be used as a voxel ID.

“Average vector” and “covariance matrix” indicate an average vector and a covariance matrix corresponding to parameters when a point group in the target voxel is expressed by a normal distribution, and an arbitrary vector in any voxel “k” The coordinates of the point "i"

Is defined as, when a point number set in the voxel k to "N _k", mean vector "mu _k" and the covariance matrix "V _k" at the voxel k, respectively the following formulas (1) and ( 2).

The average vector and the covariance matrix included in the voxel data are an example of “second point group information” in the present invention.

“Point cloud number information” is information indicating the number of point clouds used to calculate the corresponding mean vector and covariance matrix. The point group number information may be information indicating the number of specific point groups, or information indicating the level of the number of point groups (for example, large, medium, small, etc.).

(2) Outline of Scan Matching Next, scan matching by NDT using voxel data will be described.

Scan matching by NDT assuming a vehicle is to estimate the following estimated parameter “P” with the amount of movement in the road plane (here, xy coordinates) and the direction of the vehicle as elements.

“T _x ” indicates the amount of movement in the x direction, “t _y ” indicates the amount of movement in the y direction, and “Ψ” indicates the rotation angle (ie, yaw angle) in the xy plane. The vertical movement amount, pitch angle, and roll angle are small enough to be ignored, although they are caused by road gradients and vibrations.

When the coordinates [x _k (i), y _k (i), z _k (i)] ^T of the arbitrary point of the point group data obtained by the lidar 30 are subjected to coordinate conversion using the above-described estimation parameter P, the converted value The coordinates “X ′ _k (i)” are expressed by the following equation (3).

In this embodiment, the in-vehicle device 1 uses the coordinate-converted point group, the average vector μ _k and the covariance matrix V _k included in the voxel data, and the voxel _{k represented} by the following equation (4). A comprehensive evaluation function “E” (also referred to as “overall evaluation function”) for all voxels to be matched indicated by the evaluation function “E _k ” and Expression (5) is calculated.

“M” indicates the number of voxels to be matched. The coordinates of the point cloud data obtained by the lidar 30 are relative coordinates with respect to the vehicle position, and the average vector of the voxel data is an absolute coordinate. Therefore, when calculating the equation (4), for example, the lidar The coordinates of the point cloud data obtained by 30 are converted based on the vehicle position predicted from the output of the GPS receiver 32 or the like.

On the other hand, the evaluation function E _k of the voxel k used in the conventional NDT matching is expressed by the following equation (6).

As is clear from the comparison between the equations (4) and (6), in the present embodiment, the in-vehicle device 1 normalizes the evaluation function E _k by the number of point groups N _k . Thus, the vehicle-mounted device 1 on the basis of the value of the evaluation function E _k, the degree of matching to identify the relatively low voxel.

Thereafter, the vehicle-mounted device 1 calculates an estimation parameter P that maximizes the comprehensive evaluation function E by an arbitrary root finding algorithm such as Newton's method. The in-vehicle device 1 estimates the own vehicle position with high accuracy by applying the estimation parameter P to the own vehicle position predicted from the output of the GPS receiver 32 or the like.

(3) Specific Example of Scan Matching Next, a specific example of NDT scan matching will be described. Hereinafter, for convenience of explanation, the case of a two-dimensional plane will be described as an example.

In FIG. 4A, in four adjacent voxels “B1” to “B4”, point clouds measured by a rider or the like when traveling with a measurement vehicle for map creation are indicated by circles. It is the figure which showed the two-dimensional normal distribution created from Formula (1) and Formula (2) based on gradation based on. The average and variance of the normal distribution shown in FIG. 4A correspond to the average vector and covariance matrix in the voxel data, respectively.

FIG. 4B is a diagram showing the point cloud acquired by the lidar 30 while the vehicle-mounted device 1 is traveling in FIG. The position of the point cloud of the lidar 30 indicated by the asterisk is aligned with the voxels B1 to B4 based on the estimated position based on the output of the GPS receiver 32 or the like. In the example of FIG. 4B, there is a deviation between the point group (circle) measured by the measurement vehicle and the point group (star) acquired by the in-vehicle device 1.

FIG. 4C is a diagram illustrating a state after the point cloud (star) acquired by the vehicle-mounted device 1 is moved based on the matching result of the NDT scan matching. In FIG. 4C, a parameter P that maximizes the evaluation function E shown in the equations (4) and (5) is calculated based on the mean and variance of the normal distribution shown in FIGS. 4 (A) and 4 (B). The calculated parameter P is applied to the star point cloud shown in FIG. In this case, the deviation between the point cloud (circle) measured by the measurement vehicle and the point cloud (star) acquired by the in-vehicle device 1 is suitably reduced.

Here, when the evaluation functions “E1” to “E4” and the comprehensive evaluation function E corresponding to the voxels B1 to B4 are calculated by the general formula (6) conventionally used, these values are as follows: Become.
E1 = 1.3290
E2 = 1.1365
E3 = 1.1100
E4 = 0.9686
E = 4.5441

In this case, since the value of the evaluation function increases as the number of point groups in the voxel increases, it is difficult to compare the degree of matching between voxels. In this example, the evaluation function E1 of the voxel B1 having a large number of point groups is large.

On the other hand, when the evaluation functions E1 to E4 and the comprehensive evaluation function E corresponding to the voxels B1 to B4 are calculated by the equation (4) based on the present embodiment, these values are as follows.
E1 = 0.1208
E2 = 0.136
E3 = 0.1233
E4 = 0.1211
E = 0.4789

In this case, the evaluation functions E1 to E4 and the comprehensive evaluation function E are values that are not easily affected by the number of point groups in the voxel, so that the degree of matching between voxels can be easily compared. Considering the above, in the present embodiment, the in-vehicle device 1 determines whether or not the change point information D1 needs to be transmitted based on the evaluation function E _k calculated based on the equation (4).

[Transmission processing of change point information]
The in-vehicle device 1 identifies a voxel in which a static structure change may occur (that is, the distribution map DB 20 needs to be updated) based on the comprehensive evaluation function E and the evaluation function E _k , and information on the voxel Is transmitted to the server apparatus 2 as the change point information D1. For example, in the vehicle-mounted device 1, when the comprehensive evaluation function E is lower than a predetermined value, the surrounding environment corresponding to all the voxels used for matching at the position where the comprehensive evaluation function E is lower than the predetermined value may be greatly changed. The change point information D1 regarding all the voxels used for matching at that position is transmitted to the server apparatus 2. Further, the vehicle-mounted unit 1, the synthetic evaluation function E is greater than a predetermined value, among the evaluation function E _k, if there is a predetermined value smaller than the evaluation function E _k, the voxel k corresponding to the evaluation function E _k, Judge that there is a possibility that the stationary structure has changed. Therefore, when the in-vehicle device 1 detects such a voxel k, the in-vehicle device 1 transmits the change point information D1 related to the voxel k to the server device 2. Here, the change point information D1 includes, for example, a voxel ID, time information, estimated vehicle position information, a comprehensive evaluation function E, an evaluation function _{Ek, and the} like.

In addition, in-vehicle device 1 detects a voxel with a small number of point groups N _k in the voxel in addition to or instead of detecting an evaluation function E _k that is smaller than other evaluation functions E _k . In this case, the change point information D1 for the voxel may be transmitted to the server device 2. In this embodiment, evaluation for function E _k is normalized by point group number N _k, when the number of point group N _k is low due to the deformation or disappearance or the like of the static structure also, the value of the evaluation function E _k May not be smaller than a predetermined value. Considering the above, when the in-vehicle device 1 detects a voxel having a point cloud number _Nk smaller than a predetermined threshold value, the in-vehicle device 1 transmits change point information D1 for the voxel to the server device 2. In this case, for example, the in-vehicle device 1 may refer to the point cloud number information of the voxel data and set the above threshold value smaller as the point cloud number indicated by the point cloud number information is smaller.

FIG. 5 is an example of a flowchart showing a procedure of transmission processing of the change point information D1 executed by each vehicle-mounted device 1. The in-vehicle device 1 repeatedly executes the process of the flowchart of FIG.

First, the in-vehicle device 1 sets an initial value of the vehicle position based on the output of the GPS receiver 32 or the like (step S101). Next, the vehicle-mounted device 1 acquires the vehicle body speed from the speed sensor 34 and also acquires the angular velocity in the yaw direction from the gyro sensor 33 (step S102). And the vehicle equipment 1 calculates the moving distance of a vehicle and the azimuth | direction change of a vehicle based on the acquisition result of step S102 (step S103).

Thereafter, the vehicle-mounted device 1 adds the movement distance and the azimuth change calculated in step S103 to the estimated host vehicle position one time before, and calculates a predicted position (step S104). And the vehicle equipment 1 acquires the voxel data of the voxel which exists around the own vehicle position with reference to map DB10 based on the estimated position calculated by step S104 (step S105). Further, the in-vehicle device 1 divides the scan data obtained from the lidar 30 for each voxel based on the predicted position calculated in step S104 (step S106). And the vehicle equipment 1 calculates NDT scan matching using an evaluation function (step S107). In this case, the in-vehicle device 1 calculates the evaluation function E _k and the comprehensive evaluation function E based on the equations (4) and (5), and calculates the estimation parameter P that maximizes the comprehensive evaluation function E.

Then, when the in-vehicle device 1 specifies the estimation parameter P that maximizes the comprehensive evaluation function E (step S108; Yes), the in-vehicle device 1 determines whether or not the maximum comprehensive evaluation function E is equal to or greater than a predetermined value (step S109). ). And when the comprehensive evaluation function E is less than a predetermined value (step S109; No), the vehicle-mounted device 1 obtains change point information D1 including voxel IDs, date information, estimated position information, etc. of all voxels used for matching. It transmits to the server apparatus 2 (step S111). On the other hand, when the comprehensive evaluation function E is greater than or equal to a predetermined value (step S109; Yes), the in-vehicle device 1 determines whether there is a voxel whose evaluation function E _k is smaller than the predetermined value (step S110).

Then, when there is a voxel whose evaluation function E _k is smaller than the predetermined value (step S110; Yes), the in-vehicle device 1 receives the change point information D1 including the voxel ID, date information, estimated position information, and the like of the target voxel. And transmitted to the server device 2 (step S111). The in-vehicle device 1 may determine whether or not the change point information D1 needs to be transmitted based on the size of the point cloud number _Nk instead of or in addition to the determination in step S110.

On the other hand, when there is no voxel whose evaluation function E _k is smaller than the predetermined value (step S110; No), the in-vehicle device 1 returns the process to step S102. The in-vehicle device 1 calculates the estimated own vehicle position at the current time by applying the estimated parameter P that maximizes the comprehensive evaluation function E to the predicted position in step S104 after the determination in steps S109 and S110. .

[Measurement route information transmission processing]
Next, the transmission process of the measurement path information D2 by the server device 2 will be described. Schematically, the server apparatus 2 determines the measurement target voxel Btag based on the change point information D1 stored in the storage unit 22, and determines a path that passes through the position where the determined measurement target voxel Btag can be measured as a measurement path. Is transmitted to the measurement system 4.

FIG. 6 is a flowchart showing the procedure of the transmission process of the measurement path information D2. The server device 2 repeatedly executes the processing of the flowchart shown in FIG.

First, the server device 2 receives the change point information D1 from the in-vehicle device 1 of each general vehicle, and stores the received change point information D1 in the storage unit 22 (step S201). Next, the server device 2 determines whether or not it is the measurement route setting timing (step S202). For example, when the server device 2 receives a route search request including the current position information of the measurement vehicle from the measurement system 4 of the measurement vehicle, the server device 2 determines that it is the measurement route setting timing. If it is not the measurement route setting timing (step S202; No), the server apparatus 2 returns the process to step S201 again.

If the server device 2 determines that it is the measurement route setting timing (step S202; Yes), the server device 2 determines the measurement target voxel Btag based on the change point information D1 stored in the storage unit 22 (step S203). In this case, for example, when there is a predetermined number or more of change point information D1 specifying the same voxel ID, the server apparatus 2 is highly likely to have a change in the stationary structure in the voxel indicated by the voxel ID. Then, it is determined that measurement by the measurement vehicle is necessary, and the voxel is determined as the measurement target voxel Btag. Thereby, the server apparatus 2 determines the measurement object voxel Btag which a measurement vehicle should measure.

Next, the server device 2 searches for a measurement route that includes the measurement target voxel Btag in the measurement range (step S204). Here, the server device 2 executes a route search process using the current position of the measurement vehicle as a departure point and a point or road where each measurement target voxel Btag can be measured as a transit point. In this case, for example, the server device 2 starts from the current position of the measurement vehicle and, for each road that uses the required time or distance as an index, among points that can measure each measurement target voxel Btag or a road that passes through the road. The route with the minimum link cost is determined as the measurement route. Then, the server device 2 transmits the measurement route information D2 indicating the measurement route to the measurement system 4 of the measurement vehicle (step S205). At this time, preferably, in addition to the measurement route, the server device 2 may include information specifying the lane or / and the vehicle speed that the measurement vehicle should travel in the measurement route information D2. Thereby, the server apparatus 2 can make a measurement vehicle drive | work suitably so that the measurement object voxel Btag may be measured with high precision. An example of specifying the lane or / and the vehicle speed will be described with reference to FIG.

Thereafter, the server device 2 receives measurement data from the measurement system 4 of the measurement vehicle that has traveled the measurement route specified by the measurement route information D2, and updates the distribution map DB 20 based on the received measurement data. In this case, for example, the server device 2 extracts the point cloud data included in the measurement target voxel Btag from the measurement data, calculates the average vector, the covariance matrix, and the like in each measurement target voxel Btag, and then calculates the calculated average vector and covariance. The voxel data of the measurement target voxel Btag is updated by a dispersion matrix or the like.

FIG. 7 shows an overhead view around the measurement vehicle when the measurement vehicle travels based on the measurement route information D2. An arrow L1 indicates a measurement path designated by the measurement path information D2. A broken line frame 53 indicates the position of the measurement target voxel Btag. Here, since a new stationary structure 52 is generated in the broken line frame 53, the voxel in the broken line frame 53 is determined as the measurement target voxel Btag.

In this case, the server device 2 uses the road 51 in which the measurement target voxel Btag in the broken line frame 53 can be measured as a part of the measurement route, and the left lane that is the lane closest to the measurement target voxel Btag in the road 51 The measurement route information D2 designated as the lane to travel on is generated. Generally, the accuracy of the distance measurement value of the lidar is higher as the distance to the object is shorter, and the accuracy is lower as the distance is longer. Therefore, the server device 2 generates measurement route information D2 that designates the left lane as the travel lane within a range in which at least the measurement target voxel Btag in the broken line frame 53 can be measured by the lidar 46. Thereby, the stationary structure 52 in the measurement target voxel Btag can be measured with high accuracy. Similarly, when the measurement target voxel Btag is present on the right side of the travel road, the server device 2 designates the right lane as the travel lane at least within the range in which the measurement target voxel Btag can be measured by the rider 46. The route information D2 may be generated.

In addition, the server device 2 uses the measurement route information to specify the vehicle speed of the measurement vehicle so that the measurement vehicle moves at a lower speed than the other travel positions at the travel position where the measurement target voxel Btag is the measurement range of the measurement vehicle. It may be included in D2. In the example of FIG. 7, the server device 2 includes the vehicle speed information indicating that the vehicle should travel at a predetermined speed or less in the measurement route information D2 in the broken line portion of the arrow L1. Accordingly, the server device 2 can cause the measurement vehicle to travel at a speed suitable for the measurement of the measurement target voxel Btag at the time of measurement of the measurement target voxel Btag, and generate measurement data necessary for updating the distribution map DB 20 with high accuracy. it can.

As described above, the server device 2 according to the present embodiment receives and accumulates the change point information D1 indicating the collation result between the output of the rider 30 and the voxel data of the map DB 10 from the in-vehicle device 1 of each general vehicle. Based on the change point information D1, a measurement target voxel Btag that is a voxel that needs to be measured is determined. Then, the server device 2 searches for a route that uses a position where the measurement target voxel Btag can be measured as a route for measurement, as a measurement route of the measurement vehicle, and measures measurement route information D2 including information on the measurement route. Send to system 4. Thereby, the server apparatus 2 can determine suitably the measurement path | route which makes a measurement vehicle drive | work.

[Modification]
Hereinafter, modified examples suitable for the embodiments will be described. The following modifications may be applied to the embodiments in combination.

(Modification 1)
The server apparatus 2 may determine the measurement target voxel Btag based on the information regarding the measurement conditions included in the change point information D1.

For example, in step S203 of FIG. 6, the server device 2 extracts change point information D1 (also referred to as “same condition change point information”) measured under conditions that match the measurement conditions of the measurement vehicle from the storage unit 22. A voxel indicated by a predetermined number or more of the condition change point information may be determined as the measurement target voxel Btag. Thereby, the server apparatus 2 measures the measurement target voxel Btag under the measurement conditions common to the measurement conditions when the change point is detected by the general vehicle, and suitably confirms whether there is a change point in the measurement target voxel Btag. To do.

A specific example of the extraction method of the same condition change point information in this case will be described. For example, the server device 2 extracts change point information D1 including date and time information indicating a date and time that coincides with a time zone in which the measurement vehicle is driven, as the same condition change point information. In another example, the server device 2 extracts change point information D1 including date and time information indicating the day of the week that matches the day of the week on which the measurement vehicle is run, as the condition change point information. In yet another example, the change point information D1 includes weather information at the time of measurement, and the server device 2 matches the weather expected when the measurement vehicle is driven (for example, the weather at the departure place). Change point information D1 including weather information indicating the weather is extracted as the same condition change point information. As described above, the server device 2 determines the measurement target voxel Btag based on the change point information D1 generated under the measurement condition common to the measurement condition of the measurement vehicle to be traveled, and thus the measurement target under the same condition as the general vehicle. The voxel Btag is measured, and the presence or absence of a change point can be suitably confirmed by measurement with the measurement vehicle.

(Modification 2)
The measurement system 4 may execute a part of the process to be executed by the server device 2 instead of the server device 2.

For example, the measurement system 4 may execute part of the flowchart of FIG. In this case, when the measurement system 4 determines in step S202 that it is the timing for setting the measurement route, the measurement system 4 receives the change point information D1 corresponding to the voxel within a predetermined distance from the current position of the measurement vehicle from the server device, and receives it. The measurement target voxel Btag is determined based on the changed point information D1 (see step S203). Then, based on step S204, the measurement system 4 searches for a measurement route, and performs driving support so that the measurement vehicle travels on the searched measurement route. Even in this case, the measurement system 4 can preferably determine the measurement path. In the present modification, the measurement system 4 is an example of the “route search device” in the present invention.

(Modification 3)
A function corresponding to the in-vehicle device 1 may be incorporated in a general vehicle. In this case, an electronic control unit (ECU) of a general vehicle executes a process corresponding to the control unit 15 of the in-vehicle device 1 by executing a program stored in the memory of the general vehicle.

(Modification 4)
The index for evaluating the degree of matching for each voxel is not limited to the evaluation function E _k shown in Expression (4).

Instead, for example, the in-vehicle device 1 divides the point cloud data measured by the lidar 30 for each voxel, calculates an average vector and a covariance matrix for each voxel, and calculates the average included in the voxel data of the map DB 10. Direct comparison with vectors and covariance matrices is also possible. In this case, for example, the in-vehicle device 1 transmits, as the change point information D1, information about voxels in which the difference between the average vector to be compared and the covariance matrix is equal to or greater than a predetermined value to the server device 2. In this case, for example, the control unit 25 calculates the distance difference between the average vector of the point cloud data measured by the lidar 30 and the average vector of the voxel data of the map DB 20 as the first difference, and the point cloud measured by the lidar 30 A difference between the data covariance matrix and the covariance matrix of the voxel data in the map DB 20 (for example, a difference between eigenvalues) is calculated as a second difference. And the vehicle equipment 1 transmits the change point information D1 with respect to the target voxel to the server apparatus 2, when a 1st difference and a 2nd difference become more than the threshold value defined with respect to each. Thus, the determination of the transmission necessity of transition data D1 for each voxel, but are not limited to those using the evaluation function E _k.

(Modification 5)
The voxel data is not limited to a data structure including an average vector and a covariance matrix as shown in FIG. For example, the voxel data may include point cloud data measured by a measurement vehicle used when calculating an average vector and a covariance matrix. In this case, the point cloud data included in the voxel data is an example of “second point cloud information” in the present invention.

Further, the present embodiment is not limited to scan matching by NDT, and other scan matching such as ICP (Iterative Closest Point) may be applied. Even in this case, as in the embodiment, the vehicle-mounted device 1 specifies a voxel having a relatively low matching degree by calculating an evaluation function for each voxel for evaluating the matching degree, and changes with respect to the voxel. The point information D1 is transmitted to the server device 2. Thus, the scan matching method applicable to the present invention is not limited to NDT scan matching.

1 In-vehicle device 2 Server device 4 Measurement system 10 Map DB
20 Distribution map DB
11, 21, 41

Communication unit

12, 22, 42

Storage unit

15, 25, 45

Control unit

13, 43 Sensor unit 14 Input unit 16 Output unit

Claims

Measurement is required based on the result of collation between the first point cloud information measured by the measurement unit and each distance from the reference position to a plurality of positions, and the second point cloud information recorded in the map information for each region. A determination unit that determines a target area that is a complex area;
A search unit that searches for a route that uses a position where the target region can be measured as a transit point; and
A route search device comprising:
The route search device according to claim 1, wherein the search unit outputs information on the route in which a lane on which the measurement vehicle should travel is at least within a range in which the target area can be measured.
The route search device according to claim 1 or 2, wherein the search unit outputs information on the route that specifies a speed at which the measurement vehicle should travel at least within a range in which the target region can be measured.
The route search device according to any one of claims 1 to 3, wherein the search unit acquires a current position of the measurement vehicle and searches for the route from the current position as a departure point.
The first acquisition unit acquires information on measurement conditions when measuring the first point cloud information together with the first point cloud information,
The route search device according to any one of claims 1 to 4, wherein the determination unit determines the target region based on the collation result and information on the measurement condition.
The route search according to claim 5, wherein the determination unit determines the target region based on at least one of a time zone, day of the week, and weather when the first point cloud information is measured as the measurement condition. apparatus.
The first acquisition unit receives the verification result from a plurality of vehicles including the measurement unit,
The route search device according to any one of claims 1 to 6, wherein the search unit transmits information on the route to a control device that supports driving of the measurement vehicle.
Mounted on the measurement vehicle,
The route search device according to any one of claims 1 to 6, further comprising a drive support unit that performs drive support so that the measurement vehicle travels on the route searched by the search unit.
A control method executed by a route search device,
Measurement is required based on the result of collation between the first point cloud information measured by the measurement unit and each distance from the reference position to a plurality of positions, and the second point cloud information recorded in the map information for each region. A determination step of determining a target area that is a critical area;
A search step for searching for a route that uses a position where the target area can be measured as a transit point; and
A control method.
A program executed by a computer,
Measurement is required based on the result of collation between the first point cloud information measured by the measurement unit and each distance from the reference position to a plurality of positions, and the second point cloud information recorded in the map information for each region. A determination unit that determines a target area that is a complex area;
A program that causes the computer to function as a search unit that searches for a route that uses a position where the target region can be measured as a transit point.
A storage medium storing the program according to claim 10.