JP6747160B2 - Vehicle position estimation device - Google Patents

Description

The present disclosure relates to a vehicle position estimation device.

Patent Document 1 describes an apparatus that estimates the position of a vehicle on a road on which the vehicle travels. This device collates the information of the captured image obtained by the image pickup device mounted on the vehicle with the information of the feature on the map (for example, road surface paint), so that the vehicle in the longitudinal direction of the road (road extension direction) Estimate the position of.

JP, 2006-208223, A

By the way, some maps may not include detailed feature information. For example, a map with reduced cost includes information about the type of lane markings (road paint) such as solid lines and broken lines, and a display section, and a display section of characters drawn on the lane (road paint). However, the position of the broken line and the end portion of the road extending direction for each character may not be included. In other words, a map with reduced cost has less information for collating the position of the vehicle in the road extension direction. When such a map is used, it is difficult for the conventional device to accurately estimate the position of the vehicle in the road extension direction. In the present technical field, when the position of a vehicle in the road extension direction is estimated using a map that does not include the position of the end portion in the road extension direction related to road surface painting, the estimation accuracy of the vehicle position is improved. A vehicle position estimation device capable of performing the above is desired.

A vehicle position estimation device according to one aspect of the present invention is a vehicle position estimation device that estimates a position of a vehicle in an extension direction of a road on which a vehicle travels, and estimates a vehicle in the extension direction based on positioning data. A positioning unit that calculates the position, map information about the map, a map database that stores the type of road paint on the map and the boundary position of the section where the road paint is drawn, the type of road paint, and the type of road paint Based on the road surface database that stores the length and interval in the extending direction in association with each other, the environment recognition sensor that recognizes the road surface paint in front of the vehicle, and the road surface paint recognized by the environment recognition sensor, The actual road surface image generator that generates the actual road surface image and the map database are referenced to acquire the type and boundary position of the road surface paint based on the estimated position, and the road surface database is referenced to acquire The length and interval of the road surface paint corresponding to the type of the road surface paint that was acquired, and the map information around the estimated position, and the boundary position, length, and interval of the acquired road surface paint, based on the estimated position A virtual road surface image generation unit that generates a virtual road surface image in which the end portion in the extending direction of the road surface paint is complemented to the image representing the surrounding road surface, and the position of the end portion in the extending direction of the road surface paint of the actual road surface image And a vehicle position correction unit that corrects the estimated position by comparing the position of the end portion of the virtual road surface image in the extending direction of the road surface paint.

ADVANTAGE OF THE INVENTION According to this invention, when estimating the position of the vehicle in a road extension direction using the map which does not contain the position of the edge part of the road extension direction which concerns on road surface painting, the estimation precision of a vehicle position is improved. Can be made.

It is a block diagram which shows the structure of the vehicle provided with the vehicle position estimation apparatus which concerns on 1st Embodiment. It is a figure explaining the process which estimates the position of a vehicle. It is a flowchart of the process which estimates the position of a vehicle. It is a block diagram which shows the structure of the vehicle provided with the vehicle position estimation apparatus which concerns on 2nd Embodiment. It is a figure explaining the process which estimates the position of a vehicle. It is a flowchart of the process which estimates the position of a vehicle. It is a figure explaining the processing content in a phase only correlation method. It is a figure explaining the process which estimates the position of the vehicle which concerns on a modification.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the following description, the same or corresponding elements will be denoted by the same reference symbols, without redundant description.

[First Embodiment]
FIG. 1 is a block diagram showing a configuration of a vehicle 2A including a vehicle position estimation device 1A according to the first embodiment, and FIG. 2 is a diagram illustrating a process of estimating the position of the vehicle 2A. As shown in FIGS. 1 and 2, a vehicle position estimating device 1A is mounted on a vehicle 2A such as a passenger car. The vehicle position estimation device 1A is a device that estimates the position of the vehicle 2A in the extending direction D of the road R on which the vehicle 2A travels (see (a) of FIG. 2 ).

A road surface paint P10 is drawn on the road surface around the vehicle 2A. The road surface paint P10 is a sign that is drawn on the road surface and displays traffic regulations or instructions. In the example shown in FIG. 2, the road surface paint P10 is a division line that indicates the boundary between adjacent lanes. There are a plurality of types of partition lines, such as a solid line P11 and a broken line P12. The broken line P12 in the extending direction D of the road R has a predetermined length and interval according to laws and regulations. As an example, in the motorway, the length of the broken line P12 is 8 m, and the interval between the broken lines P12 is 12 m. In FIG. 2, a boundary position E1 between a section where a solid line P11 is drawn and a section where a broken line P12 is drawn, and an end portion E2 of each broken line P12 in the extending direction D of the road R are shown.

The vehicle 2A includes a vehicle position estimation device 1A and a GPS receiver 11. The vehicle position estimation device 1A has an environment recognition sensor 10 and an ECU 20A.

The GPS receiving unit 11 is a receiving device that receives signals from three or more GPS satellites and acquires distance information (positioning data) between the GPS receiving unit 11 and each GPS satellite. The GPS receiver 11 outputs the acquired distance information of the vehicle 2A to the ECU 20A. The distance information acquired by the GPS receiver 11 includes a positioning error.

The environment recognition sensor 10 is mounted on the vehicle 2A and is a sensor that recognizes the road surface paint P10 in front of the vehicle 2A. The recognition is to acquire information of the road surface paint P10 including the position, shape, length, etc. of the road surface paint P10. The environment recognition sensor 10 includes a camera as an example, and recognizes the road surface paint P10 based on a captured image (see FIG. 2B) in front of the vehicle 2A. The environment recognition sensor 10 outputs the recognition result of the road surface paint P10 to the ECU 20A.

The ECU 20A is an electronic control unit including a CPU (Central Processing Unit), a ROM (Read Only Memory), a RAM (Random Access Memory), a CAN (Controller Area Network) communication circuit, and the like. The ECU 20A is connected to a network that communicates using a CAN communication circuit, and is communicatively connected to the above-described components of the vehicle 2A. The ECU 20A operates the CAN communication circuit to input/output data based on the signal output from the CPU, stores the input data in the RAM, loads the program stored in the ROM into the RAM, and loads the program into the RAM. By executing the program, the functions of the components of the ECU 20A described later are realized.

The ECU 20A includes an actual road surface image generation unit 21, a positioning unit 22A, a virtual road surface image generation unit 23, a map database 24, a road surface database 25, and a vehicle position correction unit 26.

The actual road surface image generation unit 21 generates an actual road surface image (see (c) of FIG. 2) representing the road surface in front of the vehicle 2A based on the road surface paint P10 recognized by the environment recognition sensor 10. The actual road surface image is, for example, a plane image of the road surface in front of the vehicle 2A. The actual road surface image generation unit 21 generates an actual road surface image by performing coordinate conversion (projection) on the captured image including the road surface paint P10. The actual road surface image generation unit 21 outputs the actual road surface image to the vehicle position correction unit 26.

The positioning unit 22A calculates the estimated position of the vehicle 2A in the extending direction D of the road R based on the distance information acquired by the GPS receiving unit 11. Since the distance information acquired by the GPS receiving unit 11 has an error, the estimated position of the vehicle 2A calculated by the positioning unit 22A also has an error. The positioning unit 22A outputs the estimated position of the vehicle 2A to the virtual road surface image generation unit 23.

The map database 24 is a database that stores map information about the map, the type of road surface paint P10 on the map, and the boundary position E1 of the section in which the road surface paint P10 is drawn. The map information includes information about the road R on which the vehicle 2A travels. The type of road surface paint P10 is a classification classified according to the content of regulations or instructions relating to traffic. An example of the type of the road surface paint P10 is “solid line” or “broken line”. The map database 24 stores map information regarding maps whose costs are suppressed. For example, the map database 24 stores the boundary position E1 between the section in which the solid line P11 is drawn and the section in which the broken line P12 is drawn for the road surface paint P10, but saves the position of the end E2 of the broken line P12. I haven't.

The road surface database 25 is a database that stores the type of the road surface paint P10 and the length and interval of the road surface paint P10 in the extending direction D of the road R in association with each other. As an example, the road surface database 25 stores a broken line P12, a length of 8 m, and an interval of 12 m in association with each other.

The virtual road surface image generation unit 23 refers to the map database 24 and the road surface database 25 to generate a virtual road surface image (see (f) in FIG. 2). The virtual road surface image is an image in which the end portion in the extending direction of the road surface paint P10 is complemented with the image representing the road surface around the estimated position estimated by the positioning unit 22A. Specifically, first, the virtual road surface image generation unit 23, based on the map information stored in the map database 24 and the estimated position of the vehicle 2A, an image of the front of the vehicle 2A viewed from the vehicle 2A (see FIG. 2). (See (d)) is virtually generated. The virtual road surface image generation unit 23 refers to the map database 24 and acquires the type of the road surface paint P10 on the road surface and the boundary position E1 based on the estimated position of the vehicle 2A. The virtual road surface image generation unit 23 also refers to the road surface database 25 to acquire the length and the interval of the road surface paint P10 corresponding to the type of the acquired road surface paint P10. Then, the virtual road surface image generation unit 23 determines the area around the estimated position of the vehicle 2A based on the map information around the estimated position of the vehicle 2A and the boundary position E1, the length and the interval of the acquired road surface paint P10. A virtual road surface image (see (f) in FIG. 2) is generated by supplementing the end portion E2 in the extending direction D of the road paint P10 with respect to the image representing the road surface (see (e) in FIG. 2). Specifically, the virtual road surface image generation unit 23 sets one end (end E2) of the broken line P12 at a position spaced by a distance of the broken line P12 from the boundary position E1 between the solid line P11 and the broken line P12, and the broken line P12 from the one end. The other end portion (end portion E2) is defined by a position vacated by the length. In this way, the virtual road surface image generation unit 23 complements the road surface paint P10. The virtual road surface image generation unit 23 outputs the virtual road surface image to the vehicle position correction unit 26.

The vehicle position correction unit 26 corrects the estimated position of the vehicle 2A based on the actual road surface image generated by the actual road surface image generation unit 21 and the virtual road surface image generated by the virtual road surface image generation unit 23. Specifically, the vehicle position correction unit 26 determines the position of the end E2 of the road surface paint P10 of the actual road surface image in the extending direction D of the road R and the road surface paint P10 of the virtual road surface image in the extending direction D of the road R. The estimated position of the vehicle 2A is corrected by comparing the position of the end E2 of the vehicle. More specifically, the vehicle position correction unit 26 matches the end portion E2 of the road surface paint P10 of the actual road surface image with the end portion E2 of the road surface paint P10 of the virtual road surface image, and ends of both road surface paints P10. If there is a difference in the position of E2, the estimated position of the vehicle 2A is corrected by the difference. The vehicle position correction unit 26 outputs the corrected estimated position of the vehicle 2A as vehicle position information.

Next, a process of estimating the position of the vehicle 2A in the extending direction D of the road R by the vehicle position estimation device 1A will be described. FIG. 3 is a flowchart of a process of estimating the position of the vehicle 2A in the extending direction D of the road R. The flowchart shown in FIG. 3 is executed by the vehicle position estimating device 1A, and the process is started at the timing when the driver gives an instruction to start the operation of the vehicle position estimating device 1A, for example.

In step S11, the positioning unit 22A acquires the distance information of the vehicle 2A received by the GPS receiving unit 11. The positioning unit 22A calculates the estimated position of the vehicle 2A in the extending direction D of the road R based on the distance information. The positioning unit 22A outputs the estimated position of the vehicle 2A to the virtual road surface image generation unit 23. When the positioning unit 22A outputs the estimated position of the vehicle 2A to the virtual road surface image generation unit 23, the vehicle position estimation device 1A proceeds to step S12.

In step S12, the environment recognition sensor 10 recognizes the road surface paint P10 in front of the vehicle 2A. Specifically, the environment recognition sensor 10 acquires a captured image in front of the vehicle 2A. The environment recognition sensor 10 outputs the captured image to the actual road surface image generation unit 21. When the environment recognition sensor 10 outputs the captured image to the actual road surface image generation unit 21, the vehicle position estimation device 1A proceeds to step S13.

In step S13, the actual road surface image generation unit 21 generates an actual road surface image representing the road surface in front of the vehicle 2A based on the captured image output by the environment recognition sensor 10. The actual road surface image generation unit 21 outputs the actual road surface image to the vehicle position correction unit 26. When the actual road surface image generation unit 21 outputs the actual road surface image to the vehicle position correction unit 26, the vehicle position estimation device 1A proceeds to step S14.

In step S14, the virtual road surface image generation unit 23 refers to the map database 24 to determine the type of road surface paint P10 on the road surface and the boundary position E1 between the solid line P11 and the broken line P12 based on the estimated position of the vehicle 2A. get. In addition, the virtual road surface image generation unit 23 refers to the road surface database 25 and acquires the length and interval of the broken line P12. Furthermore, the virtual road surface image generation unit 23, based on the map information around the estimated position of the vehicle 2A, the boundary position E1 of the road surface paint P10, the length of the broken line P12, and the interval of the broken line P12 that are acquired, A virtual road surface image in which the end portion E2 of the road surface paint P10 is complemented to the image representing the road surface around the estimated position of the vehicle 2A is generated. The virtual road surface image generation unit 23 outputs the virtual road surface image to the vehicle position correction unit 26. When the virtual road surface image generation unit 23 outputs the virtual road surface image to the vehicle position correction unit 26, the vehicle position estimation device 1A proceeds to step S15.

In step S15, the vehicle position correction unit 26 compares the position of the end portion E2 of the road surface paint P10 of the actual road surface image with the position of the end portion E2 of the road surface paint P10 of the virtual road surface image. Specifically, the vehicle position correction unit 26 extends the road R so that the position of the end E2 of the road surface paint P10 of the actual road surface image and the position of the end E2 of the road surface paint P10 of the virtual road surface image are close to each other. The position of the road surface paint P10 in the present direction D is searched. Thereby, the vehicle position correction unit 26 can accurately estimate the position of the end portion E2 on the actual road surface image. Therefore, the vehicle position correction unit 26 corrects the estimated position of the vehicle 2A to improve the accuracy of the position of the vehicle 2A in the extending direction D of the road R even when using the map whose cost is suppressed. can do. When the vehicle position correction unit 26 estimates the position of the vehicle 2A, the vehicle position estimation device 1A ends the process shown in the flowchart of FIG.

As described above, according to the vehicle position estimating apparatus 1A according to the first embodiment, the position of the vehicle 2A in the road extending direction is calculated using the map that does not include the position of the end E2 in the road extending direction related to the road surface paint P10. When estimating, the virtual road surface image in which the end portion E2 of the road surface paint P10 is complemented with the image representing the road surface around the estimated position of the vehicle 2A can be generated. Therefore, the vehicle position estimation device 1A can sufficiently compare the actual road surface image and the virtual road surface image, and thus the estimation accuracy of the position of the vehicle 2A can be improved.

[Second Embodiment]
A vehicle position estimation device 1B according to the second embodiment will be described. FIG. 4 is a block diagram showing a configuration of a vehicle 2B including a vehicle position estimation device 1B according to the second embodiment, and FIG. 5 is a diagram illustrating a process of estimating the position of the vehicle 2B. As shown in FIGS. 4 and 5, the vehicle position estimation device 1B according to the second embodiment is different from the vehicle position estimation device 1A according to the first embodiment in the estimated position of the vehicle in the positioning unit 22B of the ECU 20B. The calculation process is different. Further, a vehicle 2B including the vehicle position estimation device 1B according to the second embodiment is different from the vehicle 2A in that the vehicle speed sensor 12 is included.

The vehicle speed sensor 12 is a detector that detects the speed of the vehicle 2B. As the vehicle speed sensor 12, a wheel speed sensor that is provided for the wheels of the vehicle 2B or a drive shaft that rotates integrally with the wheels and that detects the rotational speed of the wheels is used. The vehicle speed sensor 12 transmits vehicle speed information to the ECU 20B.

The positioning unit 22B of the vehicle position estimation device 1B calculates the estimated position of the vehicle 2B based on the reference position and the movement amount (positioning data) of the vehicle 2B from the reference position. Specifically, the positioning unit 22B sets, for example, the position of the vehicle 2B estimated by the vehicle position estimation device 1A according to the first embodiment as a reference position. Positioning unit 22B sets time t to t=1 when vehicle 2B is at the reference position. The positioning unit 22B extends the position of the vehicle 2B at time t=2 from the reference position by a distance (moving amount) obtained by time-integrating the vehicle speed detected by the vehicle speed sensor 12 with the moving time to extend the road R. The position is acquired as the position advanced in the direction D (see FIG. 5A). The other configurations of the vehicle position estimation device 1B are the same as the configurations of the vehicle position estimation device 1A according to the first embodiment.

Next, a process of estimating the position of the vehicle 2B by the vehicle position estimation device 1B will be described. FIG. 6 is a flowchart of a process of estimating the position of the vehicle 2B. The flowchart shown in FIG. 6 is executed by the vehicle position estimating device 1A, and the process is started at the timing when the driver gives an instruction to start the operation of the vehicle position estimating device 1B, for example.

In step S1, the positioning unit 22B acquires the reference position based on the position information of the vehicle 2B at a certain time, which is more accurate than the position information of the vehicle 2A input from the GPS receiving unit 11, for example. .. Here, the positioning unit 22B uses the position of the vehicle 2B estimated by the vehicle position estimation device 1A of the first embodiment as the reference position. When the positioning unit 22B acquires the reference position, the vehicle position estimation device 1B proceeds to step S2.

In step S2, the positioning unit 22B receives the information about the vehicle speed of the vehicle 2B from the vehicle speed sensor 12. Then, the positioning unit 22B acquires the distance obtained by time-integrating the vehicle speed of the vehicle 2B input from the vehicle speed sensor 12 as the moving amount of the vehicle 2B. When the positioning unit 22B acquires the movement amount of the vehicle 2B, the vehicle position estimation device 1B proceeds to step S21.

In step S21, the positioning unit 22B calculates, from the reference position acquired in step S1, a position where the vehicle 2B has traveled in the extending direction D of the road R by the movement amount of the vehicle 2B acquired in step S2, and the position is calculated. It is the estimated position of the vehicle 2B. The positioning unit 22B outputs the calculated estimated position of the vehicle 2B to the virtual road surface image generation unit 23. When the positioning unit 22B outputs the estimated position of the vehicle 2B to the virtual road surface image generation unit 23, the vehicle position estimation device 1B proceeds to step S22.

The process after step S22 is the same as the process after step S12 executed in the vehicle position estimating apparatus 1A according to the first embodiment. When the vehicle position correction unit 26 estimates the position of the vehicle 2B, the vehicle position estimation device 1B ends the process shown in the flowchart of FIG.

The vehicle position estimation device 1B according to the second embodiment has the same effects as the vehicle position estimation device 1A.

Although the embodiment of the invention has been described above, the invention is not limited to the embodiment described above. The present invention can be implemented in various forms in which various modifications and improvements are made to the above-described embodiments based on the knowledge of those skilled in the art.

In the above-described embodiment, an example is shown in which the actual road surface image generation unit 21 generates an actual road surface image in which the extending direction D of the road R is the lateral direction ((c) of FIG. 2 ). Similarly, an example is shown in which the virtual road surface image generation unit 23 generates a virtual road surface image in which the extending direction D of the road R is the horizontal direction ((f) in FIG. 2 ). However, in the real road surface image and the virtual road surface image, the extending direction D of the road R does not have to be the lateral direction. For example, the actual road surface image generation unit 21 generates an actual road surface image in which the extension direction D of the road R is an oblique direction, and similarly, the virtual road surface image generation unit 23 sets the extension direction D of the road R in an oblique direction. The virtual road surface image may be generated. In this case, the vehicle position correction unit 26 determines the position of the end E2 of the road surface paint P10 of the actual road surface image and the position of the end E2 of the road surface paint P10 of the virtual road surface image in the vertical and horizontal directions of each image. The estimated position of the vehicle 2A may be corrected by comparing in both directions.

[Modification of vehicle position correction unit 26]
The vehicle position correction unit 26 compares the position of the end E2 of the road surface paint P10 of the actual road surface image with the position of the end E2 of the road surface paint P10 of the virtual road surface image, The boundary position E1 of the paint P10 may be compared with the boundary position E1 of the road surface paint P10 of the virtual road surface image. Specifically, the vehicle position correction unit 26 makes the position of the end E2 of the road surface paint P10 of the actual road surface image close to the position of the end E2 of the road surface paint P10 of the virtual road surface image, and The position of the road surface paint P10 in the extending direction D of the road R may be searched so that the boundary position E1 of the road surface paint P10 of the road surface image and the boundary position E1 of the road surface paint P10 of the virtual road surface image are close to each other. In this case, the number of points for comparing the positions of the road surface paint P10 of the actual road surface image and the road surface paint P10 of the virtual road surface image in the extending direction D of the road R increases. Therefore, the vehicle position correction unit 26 can further improve the estimation accuracy of the position of the vehicle 2A.

その後、車両位置補正部２６は、合成信号Ｈ（ｕ）に逆高速フーリエ変換（IFFT; Inverse Fast Fourier Transform）を行うことで相関分布ｈ（ｘ）を得る。車両位置補正部２６は、相関分布ｈ（ｘ）において相関が最大となる座標の、中心座標からのシフト量（平行移動量）を算出し、当該シフト量に基づいて車両２Ａの推定位置を補正する。 When correcting the estimated position of the vehicle 2A, the vehicle position correction unit 26 may use the phase-only correlation method instead of matching the actual road surface image and the virtual road surface image. That is, the vehicle position correction unit 26, based on the real road surface image generated by the real road surface image generation unit 21 and the pseudo ortho image that is the virtual road surface image generated by the virtual road surface image generation unit 23, the phase-only correlation. The estimated position of the vehicle 2A may be corrected using the method. In this case, the virtual road surface image generation unit 23 determines the road surface around the estimated position of the vehicle 2A based on the map information around the estimated position of the vehicle 2A and the boundary position E1, the length and the interval of the road surface paint P10. Generate a pseudo ortho image to represent. Then, the vehicle position correction unit 26 corrects the estimated position of the vehicle 2A using the phase-only correlation method shown in FIG. Specifically, the vehicle position correction unit 26 obtains an image signal F(u) in the frequency domain by performing a fast Fourier transform (FFT) on the actual road surface image f(x), and also the pseudo ortho image. An image signal G(u) in the frequency domain is obtained by performing a fast Fourier transform on g(x) (x represents a position vector). The vehicle position correction unit 26 obtains a combined signal H(u) by combining the converted phase components of the image signals F(u) and G(u) according to the following equation (1).

After that, the vehicle position correction unit 26 obtains a correlation distribution h(x) by performing an inverse fast Fourier transform (IFFT) on the combined signal H(u). The vehicle position correction unit 26 calculates the shift amount (parallel movement amount) of the coordinate having the maximum correlation in the correlation distribution h(x) from the center coordinate, and corrects the estimated position of the vehicle 2A based on the shift amount. To do.

[Modification of road surface paint]
The road surface paint P10 is not limited to the broken line P12 and may be, for example, a deceleration zone. In addition, the map database 24 has information indicating the type of road surface paint on the map, the type indicating that the road surface paint is a character as the boundary position of the section in which the road surface paint is drawn, and the section in which the character is drawn. May be saved. Further, the road surface database 25 may store the type that the road surface paint is a character and the length and interval of the character in the extending direction D of the road R in association with each other. FIG. 8: is a figure explaining the process which estimates the position of the vehicle 2A which concerns on a modification. In FIG. 8A, the type of the road surface paint P20 is "character", and the boundary position E1 of the section in which the character is drawn is shown. Even in such a case, similar to the processing described in the first and second embodiments, the road surface around the estimated position of the vehicle 2A is determined from the boundary position E1 and the length and interval of the character P22. It is possible to generate a virtual road surface image in which the end portion E2 of the road surface paint P20 is complemented to the image representing (see (c) of FIG. 8 and (d) of FIG. 8). The vehicle position correction unit 26 may correct the estimated position of the vehicle 2A using the end E2 of the road surface paint P20, or as described in the modification of the vehicle position correction unit 26, the boundary position E1 of the road surface paint P20. May be further used to correct the estimated position of the vehicle 2A.

[Modification of reference position]
The positioning unit 22B may acquire the reference position based on the position of the sign, the signboard, etc. on the map and the image acquired by the camera. Further, the estimated position corrected by the vehicle position estimating device 1B according to the second embodiment may be used as the reference position. The positioning unit 22B may acquire the movement amount of the vehicle 2B based on the tracking of the captured image by the environment recognition sensor 10 and the position information acquired from the positioning sensor such as the GPS receiving unit 11 or the like.

[Modification of configuration]
The ECU 20A may be composed of a plurality of electronic control units. The environment recognition sensor 10 includes a rider, and may recognize the road surface paint based on the detection result of the rider. The detection result of the rider includes distance information from the vehicle to the road surface paint and azimuth information.

1A, 1B... Vehicle position estimation device, 2A, 2B... Vehicle, 10... Environment recognition sensor, 21... Real road surface image generation unit, 22A, 22B... Positioning unit, 23... Virtual road surface image generation unit, 24... Map database, 25 ... Road surface database, 26... Vehicle position correction unit, D... Extension direction, E1... Boundary position, E2... End portion, P11... Solid line (road surface paint), P12... Broken line (road surface paint), P22... Character (road surface paint) , R... Road.

Claims (1)

A vehicle position estimating device for estimating the position of the vehicle in the extending direction of a road on which the vehicle travels,
A vehicle speed sensor for detecting the speed of the vehicle,
A positioning unit that calculates an estimated position of the vehicle in the extending direction based on a distance obtained by time-integrating the position of the vehicle at a predetermined time and the speed of the vehicle detected by the vehicle speed sensor ,
A map database that stores map information about a map, a type of road surface paint on the map, and a boundary position of a section in which the road surface paint is drawn,
A road surface database that stores the type of the road surface paint and the length and interval of the road surface paint in the extending direction in association with each other,
An environment recognition sensor that recognizes the road surface paint in front of the vehicle,
An actual road surface image generation unit that generates an actual road surface image representing a road surface in front of the vehicle based on the road surface paint recognized by the environment recognition sensor;
By referring to the map database, the type and boundary position of the road surface paint on the road surface are obtained based on the estimated position, and by referring to the road surface database, the type of the acquired road surface paint is corresponded. Acquiring the length and interval of the road surface paint, based on the map information around the estimated position, and the boundary position, length and interval of the acquired road surface paint, the vicinity of the estimated position. A virtual road surface image generation unit that generates a virtual road surface image in which an end portion in the extending direction of the road surface paint is complemented with respect to an image representing the road surface;
A vehicle that corrects the estimated position by comparing the position of the end portion of the road surface paint in the extending direction of the actual road surface image with the position of the end portion of the virtual road surface image in the extending direction of the road surface paint. A position correction unit,
A vehicle position estimating device comprising:

Images