JP7114165B2 - Position calculation device and position calculation program - Google Patents

Description

The present invention relates to a position calculation device, a position calculation program, and a coordinate marker that are used in calculations for identifying the position of an autonomous vehicle.

Self-driving cars are currently under development. When driving an autonomous vehicle, various vehicle sensors installed in the autonomous vehicle detect obstacles and moving objects around the autonomous vehicle, and the autonomous vehicle avoids obstacles if present. In addition, using a three-dimensional high-precision map such as dynamic map data and positioning correction results obtained in the order of several centimeters using positioning information transmitted by positioning satellites such as GPS satellites and quasi-zenith satellites. is being considered.

In recent years, infrastructure-cooperative autonomous driving systems have been studied for the purpose of providing road conditions and traffic information that are difficult to perceive with the vehicle alone. As an example of support from the infrastructure side using a roadside system, there is a technology that distributes driving support information from the infrastructure side to an autonomous vehicle traveling on a highway (for example, Patent Document 1).

International publication 2016/068273 pamphlet

However, in places where it is difficult to obtain positioning information from GNSS (Global Navigation Satellite System) satellites such as GPS satellites and quasi-zenith satellites, and roadside systems are not installed, self-driving cars cannot determine their own position. It is difficult to obtain location information for identification.

An object of the present invention is to provide a device capable of maintaining absolute position accuracy for identifying the vehicle position of an autonomous vehicle even in locations where positioning signals from GNSS satellites cannot be received and roadside systems are not installed. and

The position calculation device of the present invention is
A position calculation device mounted on an automatic driving vehicle,
a camera device for photographing a coordinate marker whose coordinates of the arranged position are registered in three-dimensional high-precision map data such as dynamic map data used for automatic driving of the automatic driving vehicle;
extracting identification information for identifying the coordinate marker based on the image of the coordinate marker captured by the camera device; obtaining the coordinates of the coordinate marker from the map data based on the identification information; and an associated position calculator for calculating the position of the autonomous vehicle based on.

Since the position calculation device of the present invention can specify the position of the automatic driving vehicle from the coordinate markers, even in places where positioning signals from GNSS satellites cannot be received and roadside systems are not installed, the absolute position of the automatic driving vehicle can be determined. Accuracy can be maintained.

FIG. 4 is a diagram of the first embodiment and is a diagram for explaining a coordinate marker 90; FIG. 10 is a diagram of the first embodiment, showing an image of an external environment including a coordinate marker 90 captured by the vehicle-mounted camera 10; FIG. 4 is a diagram of the first embodiment and shows a coordinate marker 90a; FIG. 4 is a diagram of the first embodiment and shows a coordinate marker 90b; FIG. 4 is a diagram of the first embodiment and shows a coordinate marker 90c; FIG. 4 is a diagram of the first embodiment and shows a coordinate marker 90d; FIG. 2 is a diagram of the first embodiment, and is a hardware configuration diagram of the position calculation device 100a; Fig. 10 is a diagram of the first embodiment, showing the flow of data in the position calculation device 100a; FIG. 10 is a diagram of the first embodiment, and is a sequence diagram of the operation of the position calculation device 100a; FIG. 2 is a diagram of the first embodiment, and is a hardware configuration diagram of the position calculation device 100b; Fig. 10 is a diagram of the first embodiment, showing the flow of data in the position calculation device 100b; Fig. 10 is a diagram of the first embodiment and shows another hardware configuration of the position calculation device 100b;

BEST MODE FOR CARRYING OUT THE INVENTION Embodiments of the present invention will be described below with reference to the drawings. In each figure, the same reference numerals are given to the same or corresponding parts. In the description of the embodiments, the description of the same or corresponding parts will be omitted or simplified as appropriate.

Embodiment 1.
First, the outline of Embodiment 1 will be described.
FIG. 1 is a diagram illustrating the coordinate marker 90. FIG.
FIG. 2 shows a photographing state of the external environment image including the coordinate marker 90 by the vehicle-mounted camera 10 . FIG. 2 will be described in detail in the description of the operation that will be described later.
A plurality of coordinate markers 90 recognizable by the vehicle-mounted camera 10 are arranged on the guardrail 8 . The vehicle-mounted camera 10 captures the coordinate marker 90 using either far-infrared rays, near-infrared rays, or visible light, or a combination of a plurality of vehicle-mounted cameras. In Embodiment 1, the coordinate markers 90 are arranged on the guardrail 8, but not limited to the guardrail 8, a plurality of coordinate markers 90 may be arranged in an area along the road such as "a tunnel wall surface or sidewalk." may be The coordinate marker 90 can be identified by an external environment image captured by the vehicle-mounted camera 10 .

The coordinates of each coordinate marker 90 are registered as static information in dynamic map data 71, which will be described later. Dynamic map data 71 is stored in auxiliary storage device 70 .
In FIG. 1, the coordinates of the left coordinate marker 90 are (X1, Y1, Z1), the coordinates of the center coordinate marker 90 are (X2, Y2, Z2), and the coordinates of the right coordinate marker 90 are (X3 , Y3, Z3). The coordinates of the coordinate marker 90 are used as absolute coordinates. After recognizing the coordinate marker 90 drawn on the guardrail 8, the position calculation device 100a of the automatic driving vehicle 200 calculates the relative position between the automatic driving vehicle 200 and the coordinate marker 90 using the coordinate marker 90 and the lane link 7. Identify. This relative position is a vector 6 described later. Identification of the relative position will be described later in the description of the operation.

3-6 show coordinate markers 90. FIG. FIG. 3 shows a coordinate marker 90a. FIG. 4 shows a coordinate marker 90b. FIG. 5 shows a coordinate marker 90c. FIG. 6 shows a coordinate marker 90d. The coordinate markers 90a and 90b consist only of marks. Information such as a two-dimensional bar code 3 or a numerical value 4 may be added to the coordinate marker 90 . A coordinate marker 90c indicates a state where the two-dimensional barcode 3 is attached. A coordinate marker 90d indicates a state with a numerical value of 4 indicated as AA11. The two-dimensional barcode 3 and numerical value 4 can have identification information 91 that identifies the coordinate marker 90 .

*** Configuration description ***
FIG. 7 is a hardware configuration diagram of the position calculation device 100a. The configuration of the position calculation device 100a will be described with reference to FIG. The position calculation device 100 a is mounted on the automatic driving vehicle 200 . The position calculation device 100a is a computer having hardware such as an on-vehicle camera 10, a positioning receiver 20, an inertial measurement device 30, an input/output interface 40, a processor 50, a memory 60, and an auxiliary storage device . These pieces of hardware are connected to each other via signal lines 81 .
Inertial measurement unit 30 is hereinafter referred to as IMU 30 .

The in-vehicle camera 10 captures images of the external environment including the guardrail 8 in front and sides, as shown in FIG. 2 . Data on the mounting position and mounting orientation of the vehicle-mounted camera 10 with respect to the self-driving vehicle 200 is stored in the auxiliary storage device 70 . The auxiliary storage device 70 stores dynamic map data 71 which is map data 901 used for automatic driving of the automatic driving vehicle 200 . The dynamic map data 71 is hereinafter referred to as DMD71. The DMD 71 consists of static information, semi-static information, semi-dynamic information, and dynamic information. The static information of the DMD 71 is three-dimensional high-precision basic map data, including road surface information, lane information, three-dimensional structures, etc., and is composed of three-dimensional position coordinates and linear vector data indicating features. be. The quasi-static information, quasi-dynamic information, and dynamic information are dynamic data that change from time to time, and are data superimposed on the static information based on the location reference base. Quasi-static information includes traffic regulation information, road construction information, wide-area weather information, etc. Quasi-dynamic information includes accident information, traffic congestion information, narrow-area weather information, etc. Dynamic information includes ITS information (surrounding vehicles, walking person, signal information, etc.).
The vehicle-mounted camera 10 is a camera device 902 that captures an image of the coordinate marker 90 . As described above, the coordinates of the position where the coordinate marker 90 is arranged are registered in the static information of the DMD 71 .

The positioning reception unit 20 receives positioning signals transmitted from GNSS satellites, which are positioning satellites, reproduces the positioning signals, and outputs the positioning signals as observation information.

The IMU 30 has an acceleration sensor and a gyro. The IMU 30 generates and outputs observation information from the acceleration sensor and gyro signals.

The input/output interface 40 is an interface device that connects the vehicle-mounted camera 10 , the positioning receiver 20 and the IMU 30 and the processor 50 .

The processor 50 is an IC (Integrated Circuit) that performs arithmetic processing and controls other hardware. For example, the processor 50 is a CPU (Central Processing Unit), a DSP (Digital Signal Processor), or a GPU (Graphics Processing Unit).

Memory 60 is a volatile storage device. Memory 60 is also referred to as main storage or main memory. For example, the memory 60 is RAM (Random Access Memory). The data stored in the memory 60 is saved in the auxiliary storage device 70 as required.

Auxiliary storage device 70 is a non-volatile storage device. For example, the auxiliary storage device 70 is a ROM (Read Only Memory), HDD (Hard Disk Drive), or flash memory. Data stored in the auxiliary storage device 70 is loaded into the memory 60 as required.

The position calculation device 100 a includes functional elements such as an image processing section 51 , a related position calculation section 52 and a position calculation section 53 . The related position calculation unit 52 includes a marker identification unit 52a and a position correction unit 52b. The functions of the image processing unit 51, the related position calculation unit 52, and the position calculation unit 53 are realized by software.

The auxiliary storage device 70 stores a position calculation program that implements the functions of the image processing section 51 , the related position calculation section 52 and the position calculation section 53 . The position calculation program is loaded into memory 60 and executed by processor 50 .
DMD 71 is also loaded into memory 60 and read by processor 50 .
Furthermore, the auxiliary storage device 70 stores an OS (Operating System). At least a portion of the OS is loaded into memory 60 and executed by processor 50 . The processor 50 executes the position calculation program while executing the OS. Data obtained by executing the position calculation program is stored in storage devices such as memory 60 , auxiliary storage device 70 , registers within processor 50 , or cache memory within processor 50 .

The position calculation device 100a may include multiple processors in place of the processor 50. FIG. A plurality of processors share the role of processor 50 .

The position calculation program can be recorded in a computer-readable manner on a non-volatile recording medium such as an optical disc or flash memory.

***Description of operation***
The operation of the position calculation device 100a will be described with reference to FIGS. 2, 8, and 9. FIG.
FIG. 8 shows the data flow of the position calculation device 100a.
FIG. 9 shows the sequence of operations of the position computing device 100a.

In step S11, the positioning reception unit 20 receives positioning signals transmitted from GNSS satellites, reproduces the positioning signals, and outputs the positioning signals as observation information. Also, the IMU 30 generates and outputs observation information from signals from the acceleration sensor and the gyro.

In step S12, the position calculator 53 calculates the self-position of the self-driving vehicle 200 using the positioning signals transmitted by the positioning satellites. At that time, the position calculation unit 53 also uses the observation information of the signal of the IMU 30 in addition to the observation information of the positioning signal. The position calculation unit 53 applies a Kalman filter to the observation information of the positioning signal and the observation information of the IMU 30 to calculate the self-position by composite positioning calculation in which satellite positioning and navigation positioning are tightly coupled. Self-position means the position of the self-driving vehicle 200 .

In step S13, the in-vehicle camera 10 photographs the front and side external environment including the guardrail 8 as image information as shown in FIG.
In step S14, the image processing unit 51 performs image processing such as sharpening processing and clustering processing of the external environment image. The image processing unit 51 outputs the image-processed external environment image. The external environment image output by the image processing section 51 includes the guardrail 8 and the coordinate markers 90 .

In step S<b>15 , the marker specifying section 52 a of the related position calculating section 52 extracts the image of the coordinate marker 90 from the external environment image output from the image processing section 51 .
In step S<b>16 , the marker specifying unit 52 a extracts the identification information 91 from the image of the coordinate marker 90 . The identification information 91 of the coordinate marker 90 is information for identifying the coordinate marker 90 . The identification information 91 is uniquely given to each coordinate marker 90 of the plurality of coordinate markers 90 , and the coordinate marker 90 is uniquely identified by the identification information 91 .
Extraction of the identification information 91 of the coordinate marker 90 is as follows.

<Type 1>
As a type 1, the auxiliary storage device 70 stores correspondence information 72 in which correspondence between images of a plurality of coordinate markers 90 and identification information 91 given to the images is registered. The marker specifying unit 52a extracts the identification information 91 of the coordinate marker 90 by searching the correspondence information 72 using the extracted image of the coordinate marker 90 as a search key.

<Type 2>
Type 2 is a case where the identification information 91 of the coordinate marker 90 is also arranged on the guardrail 8 in addition to the mark of the coordinate marker 90 as shown in FIGS. 5 and 6 . In the case of type 2, the external environment image output from the image processing section 51 also includes the identification information 91 . The marker specifying unit 52 a extracts the identification information 91 by reading the identification information 91 included in the external environment image output from the image processing unit 51 .

Thus, in step S<b>16 , the marker identification unit 52 a of the related position calculation unit 52 extracts the identification information 91 that identifies the coordinate marker 90 based on the image of the coordinate marker 90 captured by the vehicle-mounted camera 10 .

In step S<b>17 , the marker specifying unit 52 a refers to the DMD 71 and acquires the coordinates of the coordinate marker 90 from the DMD 71 based on the identification information 91 of the coordinate marker 90 .
Specifically, it is as follows.
The coordinates of each coordinate marker 90 of the plurality of coordinate markers 90 are associated with identification information 91 and registered in the DMD 71 . The marker specifying unit 52a searches the DMD 71 using the identification information 91 extracted in step S16 as a search key, and acquires the coordinates of the coordinate marker 90 corresponding to the identification information 91. FIG. As described above, the marker specifying unit 52a of the related position calculating unit 52 acquires the coordinates of the coordinate marker 90 from the DMD 71 based on the identification information 91 in step S17.

In step S18, the marker specifying unit 52a calculates the azimuth angle θ of the direction in which the coordinate marker 90 exists based on the image of the coordinate marker 90 specified in step S15.
A method of calculating the azimuth angle θ will be described with reference to FIG.
(1) The mounting position and mounting posture of the vehicle-mounted camera 10 to the automatic driving vehicle 200 are known. The mounting position is coordinates (X, Y, Z) with respect to the reference position of the automatic driving vehicle 200, and the mounting orientation is (roll angle, pitch angle, yaw angle) with respect to the reference orientation of the automatic driving vehicle 200. The mounting position and mounting orientation are stored in the auxiliary storage device 70 .
(2) The automatic driving vehicle 200 is automatically driving.
In the case of automatic driving, the automatic driving vehicle 200 is traveling on a track corresponding to the lane link 7 .
The lane link 7 is data registered in the DMD 71, and data defined in the DMD 71 as the centerline of the roadway. The marker identification unit 52 a can recognize the lane link 7 by referring to the DMD 71 .
(3) Based on the image of the coordinate marker 90 extracted in step S15, the mounting position and mounting posture of the vehicle-mounted camera 10, and the direction of the lane link 7, the marker identification unit 52a determines the coordinate marker in the image of the coordinate marker 90. 90 azimuth angle θ can be calculated. The direction of the lane link 7 is the traveling direction of the self-driving vehicle 200 .

A method of calculating the distance L and the marker-related position P(m) calculated in relation to the coordinates of the coordinate marker 90 will be described with reference to FIG. The marker-related position P(m) is the position of the self-driving vehicle 200 obtained from the coordinate marker 90 captured by the vehicle-mounted camera 10 .
In step S19, the position correction unit 52b of the related position calculation unit 52 calculates L and the marker-related position P(m).
The XYZ coordinate system 5 is shown in FIG.
L=D/tan θ (Formula 1)
P (m) = (Xm, Ym, Zm) + (-D, -L, Zr) (Formula 2)
(Xm, Ym, Zm) are the acquired coordinates of the coordinate marker 90 .
(-D, -L, Zr) is the relative distance between the coordinate marker 90 and the automatic driving vehicle 200;
(-D, -L, Zr) are the components of vector 6 in FIG.
D and L are the distances shown in FIG. 2, specifically as follows.
(1) D is the shortest distance between the lane link 7 and the coordinate marker 90 on the XY plane of the XYZ coordinate system 5 .
(2) L is the distance in the direction of the lane link 7 between the position of the coordinate marker 90 and the vehicle-mounted camera 10 on the XY plane of the XYZ coordinate system 5 .
(3) Zr is the difference between the Z value of the mounting coordinates of the in-vehicle camera 10 and the Z coordinate of the coordinate marker 90, Zm.
(4) A vector 6 is a vector from the coordinates of the coordinate marker 90 to the mounting position of the vehicle-mounted camera 10 .
In the case of Equation 2, the marker-related position P(m) of the automatic driving vehicle 200 is the position of the vehicle-mounted camera 10, but since the reference position of the automatic driving vehicle 200 and the mounting position of the vehicle-mounted camera 10 are known, The reference position of the vehicle 200 can be converted into its own position.

As described above, the position correction unit 52b of the related position calculation unit 52 uses the coordinates of the coordinate marker 90 to calculate the marker related position P(m) indicating the position of the automatic driving vehicle 200. FIG. When calculating the marker-related position P(m), the related position calculation unit 52 determines the azimuth angle θ of the coordinate marker 90 with respect to the reference direction from the image of the coordinate marker 90, and uses the determined azimuth angle θ to A marker relative position indicating the position of the car 200 is calculated. Here, the reference direction is the direction along the lane link 7 . Since the autonomous vehicle 200 is automatically driving, the direction along the lane link 7 is also the traveling direction of the autonomous vehicle 200, as shown in FIG.

In step S<b>20 , the position correction unit 52 b corrects the self-position based on the marker-related position P(m) calculated by Equation 2 and the self-position measured by the position calculation unit 53 . The corrected self-position is used for automatic driving of the automatic driving vehicle 200 . In this way, the related position calculator 52 corrects the position of the self-driving vehicle 200 calculated by the position calculator 53 using the positioning signal, using the marker-related position P(m).

In addition, since the automatic driving vehicle 200 is located in a tunnel or a forest, if the positioning signal of the GNSS satellite cannot be received by the positioning reception unit 20, the position calculation unit 53 calculates the position of the automatic driving vehicle 200 based on the observation information of the IMU 30. Find the self-position to be used for automatic driving. In this case, the position correction unit 52b frequently uses the coordinate markers 90 of the guardrail 8 to correct the self-position so that the accumulation of the bias error of the IMU 30 does not degrade the calculation accuracy of the self-position.
In other words, the position calculator 53 calculates the position of the self-driving vehicle 200 based on the observation information obtained by the IMU 30 . Then, the position correction unit 52b corrects the self-position of the self-driving vehicle 200 calculated by the position calculation unit 53 using the observation information of the IMU 30, using the marker-related position P(m).

***Description of the effects of the first embodiment***
According to Embodiment 1, since the position of the autonomous vehicle 200 can be obtained from the coordinate markers 90, even in areas where positioning signals from GNSS satellites cannot be received and roadside systems are not installed, automatic The absolute position accuracy of the driving vehicle can be maintained.

<Modification 1>
FIG. 10 shows the hardware configuration of a position calculation device 100b, which is a modification of the position calculation device 100a.
FIG. 11 shows the data flow of the position computing device 100b. The position calculation device 100b includes a distance measurement unit 80, such as a radar or lidar, arranged to the side of the automatic driving vehicle 200. As shown in FIG. Distance measurement unit 80 sends a distance measurement signal for distance measurement such as a radar transmission wave or laser beam toward guardrail 8 and measures the distance between distance measurement unit 80 and guardrail 8 . The marker specifying unit 52a can obtain the distance D in FIG. Specifically, since the mounting position and mounting orientation of the distance measuring unit 80 with respect to the automatic driving vehicle 200 are known, the marker specifying unit 52a can obtain the distance D in FIG. 2 from the measurement result of the distance measuring unit 80. . The marker specifying unit 52a may obtain the distance D shown in FIG. 2 between the sensor axis of the vehicle-mounted camera 10 of the self-driving vehicle 200 and the guardrail 8 from the measured distance.

<Modification 2>
Further, the marker specifying unit 52a extracts the white lines, which are lane lanes existing on both sides of the road, from the image captured by the vehicle-mounted camera 10, obtains the inclination angle of the automatic driving vehicle 200 with respect to the extracted lane lanes, and calculates the azimuth angle θ. can be corrected.

***Other Configurations***
In Embodiment 1, the functions of the image processing unit 51, the related position calculation unit 52, and the position calculation unit 53 of the position calculation devices 100a and 100b are implemented by software. may be implemented in hardware. The position calculation device 100b will be described as an example, but the position calculation device 100a is similar to the position calculation device 100a.
FIG. 12 is a diagram showing another configuration of the position calculation device 100b. In the position calculation device 100b of FIG. 12, the electronic circuit 903 realizes the functions of the image processing section 51, the related position calculation section 52, and the position calculation section 53. FIG. Other configurations in FIG. 12 are the same as those of the position calculation device 100b.

Electronic circuit 903 is specifically a single circuit, a composite circuit, a programmed processor, a parallel programmed processor, a logic IC, GA, ASIC, or FPGA. GA is an abbreviation for Gate Array. ASIC is an abbreviation for Application Specific Integrated Circuit. FPGA is an abbreviation for Field-Programmable Gate Array. The functions of the image processing unit 51, the related position calculation unit 52, and the position calculation unit 53 of the position calculation device 100b may be implemented by one electronic circuit, or may be implemented by being distributed among a plurality of electronic circuits. As another modification, part of the functions of the image processing unit 51, the related position calculation unit 52, and the position calculation unit 53 of the position calculation device 100b may be implemented by electronic circuits, and the remaining functions may be implemented by software.

Each of the processor and electronic circuitry is also called processing circuitry. That is, the functions of the image processing section 51, the related position calculation section 52, and the position calculation section 53 are realized by the processing circuitry.

In the position calculation device 100b, the "parts" of the image processing unit 51, the related position calculation unit 52, and the position calculation unit 53 may be replaced with "processes." The operations by the image processing unit 51, the related position calculation unit 52, and the position calculation unit 53 can be regarded as a position calculation method implemented by a position calculation program.

As described above, the position calculation device according to Embodiment 1 is a position calculation device mounted on an automatic driving vehicle, and the coordinates of the arranged position are used for automatic driving of the automatic driving vehicle. extracting identification information for identifying the coordinate marker based on a camera device for capturing an image of the coordinate marker registered in the high-precision map data, and extracting identification information for identifying the coordinate marker based on the image of the coordinate marker captured by the camera device; and a related position calculation unit that acquires the coordinates of the coordinate marker from the three-dimensional high-precision map data and calculates a marker-related position indicating the position of the automatic driving vehicle using the coordinates of the coordinate marker. Characterized by

Further, the related position calculation unit may determine an azimuth angle of the coordinate marker with respect to a reference direction from the image of the coordinate marker, and use the determined azimuth angle to calculate the marker related position.

Further, a position calculation unit that calculates the position of the automatic driving vehicle using a positioning signal transmitted by a positioning satellite, and the related position calculation unit calculates the position of the automatic driving vehicle using the positioning signal by the position calculation unit position using the marker-related position.

Further, an inertial measurement device is provided, the position calculation unit calculates the position of the autonomous vehicle from observation information obtained by the inertial measurement device, and the position correction unit calculates the position of the automatic driving vehicle from the observation information. The calculated position of the autonomous vehicle may be corrected using the marker-related position.

Thus, according to Embodiment 1, since the position of the automatic driving vehicle 200 can be obtained from the coordinate marker 90, even in areas where positioning signals from GNSS satellites cannot be received and roadside systems are not installed. , the absolute position accuracy of the autonomous vehicle can be maintained.

P(m) marker-related position, 3 two-dimensional barcode, 4 numerical value, 5 XYZ coordinate system, 6 vector, 7 lane link, 8 guardrail, 10 onboard camera, 20 positioning receiver, 30 IMU, 40 input/output interface, 50 Processor 51 Image processing unit 52 Related position calculation unit 52a Marker identification unit 52b Position correction unit 53 Position calculation unit 60 Memory 70 Auxiliary storage device 71 DMD 72 Correspondence information 80 Distance measurement unit 81 Signal Lines 90, 90a, 90b, 90c, 90d Coordinate markers 91 Identification information 100a, 100b Position calculation device 200 Self-driving car 901 Map data 902 Camera device 903 Electronic circuit.

Claims (4)

A position calculation device mounted on an automated driving vehicle that automatically operates a track corresponding to a lane link registered as data ,
A coordinate marker is photographed, which is a mark whose coordinates at a position where it is arranged is registered in map data used for automatic driving of the autonomous vehicle, and where identification information for identifying the mark is arranged. a camera device;
a position calculation unit that calculates the position of the automatic driving vehicle using a positioning signal transmitted by a positioning satellite;
extracting the identification information from the image of the coordinate marker captured by the camera device; obtaining the coordinates of the coordinate marker from the map data based on the extracted identification information; and obtaining the lane link from the image of the coordinate marker. determining the azimuth angle of the coordinate marker with respect to a reference direction indicating a direction along the reference direction determined by the determined azimuth angle and the shortest distance between the lane link and the coordinate marker photographed by the camera device; a related position calculation unit that calculates a marker related position indicating the position of the autonomous vehicle using the directional distance and the coordinates of the coordinate marker ;
The related position calculation unit
A position calculation device comprising a position correction unit that corrects, using the marker-related position, the position of the autonomous vehicle calculated by the position calculation unit using the positioning signal . The position computing device further comprises:
Equipped with an inertial measurement device,
The position calculation unit
calculating the position of the autonomous vehicle from the observation information obtained by the inertial measurement device;
The position corrector is
The position calculation device according to claim 1 , wherein the position calculation unit corrects the position of the automatic driving vehicle calculated from the observation information using the marker-related position. 3. The position calculation device according to claim 1 , wherein said map data is a three-dimensional map. to the computer,
A camera that captures a coordinate marker, which is a mark in which the coordinates of the arranged position are registered in map data used for automatic driving of an autonomous vehicle, and in which identification information for identifying the mark is arranged. a process of extracting the identification information from the image of the coordinate marker captured by the device;
a process of acquiring the coordinates of the coordinate marker from the map data based on the extracted identification information;
An azimuth angle of the coordinate marker with respect to a reference direction indicating a direction along the lane link registered as data is determined from the image of the coordinate marker, and the determined azimuth angle, the lane link and the image captured by the camera device are determined. calculating a marker-related position indicating the position of the autonomous vehicle using the shortest distance between the coordinate marker and the distance in the reference direction determined by the coordinates of the coordinate marker ; A position calculation program for executing a process of correcting the position of the self-driving vehicle using the marker-related position .

Images