Parking assistance method and parking assistance device

Abstract

The parking assistance method involves: detecting the own position of a host vehicle (S1); estimating a detection accuracy of the own position (S2); setting, as a first own position, the own position of a point at which the detection accuracy changes from a state of being equal to or greater than a prescribed accuracy to a state of being smaller than the prescribed accuracy (S13); detecting a relative position relationship between a target parking position and a target that is present around a target parking position when the host vehicle is parked at the target parking position after the first own position is set (S10); storing, in a storage device, the first own position in association with trained target data, which represents the relative position relationship, if the detection accuracy is smaller than the prescribed accuracy when the host vehicle stops at the target parking position (S11); and assisting in parking the host vehicle at the target parking position on the basis of the first own position and the trained target data when the first own position is stored in association with the trained target data(S40-S43).

Description

[Technical Field]

[0001] This invention relates to a parking assistance method and a parking assistance device. [Background technology]

[0002] Patent Document 1 below describes a parking assistance device that detects the vehicle's own position based on positioning information and provides parking assistance when it determines that the vehicle's position is approaching a target parking position registered in a storage device in advance. [Prior art documents] [Patent Documents]

[0003] [Patent Document 1] International Publication No. 2017 / 072941 [Overview of the project] [Problems that the invention aims to solve]

[0004] In the technology described in Patent Document 1 above, if the accuracy of detecting the vehicle's own position is low, there is a risk that it will not be possible to determine whether or not a registered target parking position is near the vehicle. The present invention aims to enable the determination of whether or not a registered target parking position is near the vehicle in locations where the accuracy of detecting the vehicle's own position is low. [Means for solving the problem]

[0005] In one embodiment of the present invention, a parking assistance method detects the vehicle's own position, estimates the detection accuracy of the vehicle's own position, sets the point at which the detection accuracy changes from a state of being above a predetermined accuracy to a state of being below a predetermined accuracy as the first vehicle's own position, detects the relative positional relationship between the target parking position and the targets surrounding the target parking position when the vehicle parks at the target parking position after the first vehicle's own position has been set, stores the first vehicle's own position and learned target data, which is data representing the relative positional relationship, in association with each other in a storage device, and when the first vehicle's own position and learned target data are stored in association with each other, the method assists in parking the vehicle at the target parking position based on the first vehicle's own position and the learned target data. [Effects of the Invention]

[0006] According to the present invention, it is possible to determine whether or not there is a registered target parking location near the vehicle in a location where the accuracy of detecting the vehicle's own position is low. [Brief explanation of the drawing]

[0007] [Figure 1] This figure shows a schematic example of a parking assistance system configuration. [Figure 2A] This is an explanatory diagram illustrating an example of the process for registering a target parking position. [Figure 2B] This is an explanatory diagram illustrating an example of the process when parking assistance is implemented. [Figure 3] Figure 1 is a block diagram showing an example of the controller's functional configuration. [Figure 4A] This is a schematic diagram illustrating a situation where the accuracy of self-position detection decreases. [Figure 4B] This is a schematic diagram illustrating a situation where the accuracy of self-position detection decreases. [Figure 5A] This is an explanatory diagram of the process when providing parking assistance to the target parking position. [Figure 5B] This is an explanatory diagram of the process when providing parking assistance to the target parking position. [Figure 6] This is a flowchart illustrating an example of the storage process for learned target data. [Figure 7]This is a flowchart illustrating an example of the process when implementing parking assistance. [Modes for carrying out the invention]

[0008] Refer to Figure 1. The vehicle 1 is equipped with a parking assist device 10 that assists in parking the vehicle 1 at a target parking position. The parking assist device 10 assists in driving the vehicle 1 along a target driving trajectory from its current position to the target parking position. For example, automatic driving may be performed to control the vehicle 1 so that it drives along its target driving trajectory to the target parking position (i.e., control of all or part of the steering angle, driving force, and braking force of the vehicle to automatically perform all or part of driving along the target driving trajectory of the vehicle 1). Parking of the vehicle 1 may also be assisted by displaying the target driving trajectory and the current position of the vehicle 1 on a display device that can be seen by the occupants of the vehicle 1.

[0009] The positioning device 11 measures the current position of the vehicle 1. The positioning device 11 may be equipped with a Global Navigation Satellite System (GNSS) receiver, such as a Global Positioning System (GPS) receiver, or it may measure its own position by receiving position information from a wireless local area network (LAN) access point or a mobile telephone base station. Map data is stored in the map database (map DB) 12. The map data stored in the map DB 12 may be high-precision map data suitable for use as a map for autonomous driving, for example. The human-machine interface (HMI) 13 is an interface device that exchanges information between the parking assist device 10 and the occupant. The shift switch (shift SW) 14 is a switch that allows the occupant of the vehicle 1 (e.g., the driver) or the parking assist device 10 to switch the shift position of the vehicle 1.

[0010] The external sensor 15 detects objects within a predetermined distance range from the vehicle 1. The external sensor 15 detects the surrounding environment of the vehicle 1, such as the relative position of objects around the vehicle 1 and the vehicle 1, the distance between the vehicle 1 and the objects, and the direction in which the objects are located. The external sensor 15 may include, for example, a camera that photographs the surrounding environment of the vehicle 1. In the following description, the camera of the external sensor 15 will be simply referred to as "camera". The external sensor 15 may also include distance measuring devices such as a laser rangefinder, radar, or LiDAR. The vehicle sensor 16 detects various information (vehicle information) of the vehicle 1. The vehicle sensor 16 may include, for example, a vehicle speed sensor, a wheel speed sensor, a 3-axis acceleration sensor, a steering angle sensor, a turning angle sensor, a gyro sensor, and a yaw rate sensor.

[0011] The controller 17 is an electronic control unit that performs parking assistance control. The controller 17 includes a processor 20 and peripheral components such as a storage device 21. The processor 20 may be, for example, a CPU or an MPU. The storage device 21 may include a semiconductor storage device, a magnetic storage device, an optical storage device, etc. The functions of the controller 17 are realized, for example, by the processor 20 executing a computer program stored in the storage device 21. The steering actuator 19a controls the steering direction and amount of the steering mechanism of the vehicle 1 in accordance with the control signal from the controller 17. The accelerator actuator 19b controls the accelerator opening of the drive device, such as the engine or drive motor, in accordance with the control signal from the controller 17. The brake actuator 19c operates the braking device in accordance with the control signal from the controller 17.

[0012] Next, parking support control by the parking support device 10 will be described. When using the parking support by the parking support device 10, a target parking position where the host vehicle 1 should be parked is registered in the parking support device 10. Specifically, objects existing around the target parking position are extracted and stored in the storage device 21 in advance. In the following description, the objects around the target parking position stored in the storage device 21 are referred to as "learned objects". FIG. 2A is an explanatory diagram of an example of the process of registering the target parking position, and the round plots represent the learned objects. When registering the target parking position 30 in the parking support device 10, the occupant performs an operation (hereinafter sometimes referred to as "registration operation") for instructing the registration of the target parking position 30. The registration operation may be, for example, an operation of a "parking position registration switch" provided in the HMI 13.

[0013] For example, when the host vehicle 1 is located near the target parking position 30 (for example, when the occupant parks the host vehicle 1 at the target parking position 30 by manual driving), the parking support device 10 detects objects around the host vehicle 1 with the external sensor 15 and stores them as learned objects. For example, objects may be detected from a surrounding image obtained by photographing the surroundings of the host vehicle 1 with a camera. Objects around the host vehicle 1 may also be detected by a distance measuring device. The parking support device 10 stores learned object data regarding the learned objects in the storage device 21. For example, the learned object data includes data representing the feature amounts of the learned objects (hereinafter referred to as "feature amount data"), data on the relative positional relationship between the learned objects and the target parking position (hereinafter referred to as "relative position data"), and coordinate data of the target parking position 30 (hereinafter referred to as "target parking position coordinate data") in a coordinate system with a fixed point as a reference point (hereinafter referred to as "map coordinate system").

[0014] As relative position data, for example, the relative position of a learned object target based on the target parking position 30 may be memorized. For example, when the host vehicle 1 is located at the target parking position 30, the parking support device 10 can acquire the position of the learned object target detected at that time as the relative position of the learned object target based on the target parking position 30. The coordinates of the learned object target and the target parking position 30 in the map coordinate system may be memorized. As the target parking position coordinate data, the self-position of the host vehicle 1 when the host vehicle 1 is located at the target parking position 30 may be memorized. At this time, when the detection accuracy of the positioning device 11 is equal to or higher than a predetermined accuracy, the self-position of the host vehicle 1 measured by the positioning device 11 may be memorized, and when the detection accuracy of the positioning device 11 is less than the predetermined accuracy, the self-position of the host vehicle 1 estimated by an odometry such as dead reckoning may be memorized.

[0015] FIG. 2B is an explanatory diagram of an example of the process during parking support implementation. When the host vehicle 1 is located near the registered target parking position 30 and an operation by an occupant (hereinafter sometimes referred to as a "start operation") that instructs the start of the parking support control of the host vehicle 1 to the target parking position 30 is performed, the parking support of the host vehicle 1 is started. The start operation may be, for example, an operation of a "parking support start switch" prepared on the HMI 13, or may be a shift operation for switching between forward and reverse of the host vehicle 1.

[0016] The parking assist device 10 extracts objects around the vehicle 1 using the external sensor 15. In the following description, objects around the vehicle 1 extracted during parking assistance will be referred to as "surrounding objects." In Figure 2B, the triangular plots represent surrounding objects. The parking assist device 10 matches learned objects with surrounding objects and associates identical feature points. Then, based on the relative positional relationship between the surrounding objects detected during parking assistance and the vehicle 1, and the relative positional relationship between the learned objects associated with the surrounding objects and the target parking position 30, the parking assist device 10 calculates the relative position of the vehicle 1 with respect to the target parking position 30. For example, the parking assist device 10 calculates the position of the target parking position 30 on a coordinate system (hereinafter referred to as the "vehicle coordinate system") based on the current position of the vehicle 1. Furthermore, if the coordinates of the learned targets and the target parking position 30 in the map coordinate system are stored in the storage device 21, the coordinates of the target parking position 30 in the map coordinate system may be converted to coordinates in the vehicle coordinate system based on the positions of the surrounding targets detected during parking assistance and the positions of the learned targets in the map coordinate system. Alternatively, the self-position of the vehicle 1 in the map coordinate system may be determined based on the positions of the surrounding targets detected during parking assistance and the positions of the learned targets in the map coordinate system, and the relative position of the vehicle 1 with respect to the target parking position 30 may be calculated from the difference between the coordinates of the vehicle 1 in the map coordinate system and the coordinates of the target parking position 30.

[0017] The parking assist device 10 calculates a target driving trajectory 33 from the current position 32 of the vehicle 1 to the target parking position 30, based on the relative position of the vehicle 1 with respect to the target parking position 30. The parking assist device 10 performs parking assist control of the vehicle 1 based on the calculated target driving trajectory 33.

[0018] The functional configuration of the controller 17 will be described in detail below. Refer to Figure 3. When the HMI control unit 40 detects the occupant's operation to register a target parking position 30, the HMI control unit 40 outputs a map generation command to the map generation unit 45 to store the learned target data in the storage device 21. When it detects the operation to activate parking assistance control to the registered target parking position 30, it outputs a control start command to the parking assistance control unit 41 to start parking assistance control to the target parking position 30. The image conversion unit 42 converts the image captured by the camera into an overhead view image seen from a virtual viewpoint directly above the vehicle 1. The image conversion unit 42 converts the captured image into an overhead view image at predetermined intervals and generates an ambient image, which is an image of the area around the vehicle 1, by accumulating the converted overhead view images along the vehicle 1's travel path.

[0019] The self-position calculation unit 43 calculates the current position of the vehicle 1 on the map coordinate system as its own position by odometry (e.g., dead reckoning) based on vehicle information output from the vehicle sensor 16. The self-position calculation unit 43 corrects the calculation result of the self-position based on the detection result of the self-position by the positioning device 11. The self-position calculation unit 43 estimates the detection accuracy of the positioning device 11. For example, if the positioning device 11 is equipped with a GNSS receiver, the self-position calculation unit 43 may estimate the detection accuracy of the positioning device 11 based on the number of navigation satellites it has acquired. If the positioning device 11 performs positioning based on position information from a wireless LAN access point or a mobile phone base station, the detection accuracy of the positioning device 11 may be estimated based on the number of wireless LAN access points or mobile phone base stations it has acquired and the received strength of the position information. The map generation unit 45 and the matching unit 47, described later, may also estimate the detection accuracy of the positioning device 11 in a similar manner. The parking assist device 10 may use high-precision map data to detect the vehicle's own position, either in place of or in addition to the positioning device 11. For example, the parking assist device 10 may detect objects around the vehicle 1 using an external sensor 15 and detect the vehicle's own position by map matching between the detected objects and high-precision map data. In this case, the detection accuracy of positioning based on high-precision map data may be estimated based on the accuracy of the map matching (e.g., matching error).

[0020] The target detection unit 44 detects targets from the surrounding image output from the image conversion unit 42. The target detection unit 44 may detect the position of the target's feature points and their image features. The target detection unit 44 outputs the detected feature point positions and image features as target data to the map generation unit 45 and the matching unit 47. In addition, the self-position obtained from the self-position calculation unit 43 in synchronization with the target detection is output to the map generation unit 45 and the matching unit 47. When the map generation unit 45 receives a map generation command from the HMI control unit 40 (i.e., when the registration operation for the target parking position 30 is performed), it generates learned target data and stores it in the storage device 21 as map data 46. For example, the map generation unit 45 receives target data and the self-position of the vehicle 1 on the map coordinate system synchronized with the target data from the target detection unit 44. The map generation unit 45 acquires the position information of the target parking position 30 in the map coordinate system. The self-position calculated by the self-position calculation unit 43 when the vehicle 1 is located at the target parking position 30 may be acquired as the position information of the target parking position 30. The map generation unit 45 generates relative position data based on the positions of feature points included in the target data, the position information of the vehicle 1 synchronized with these, and the position information of the target parking position 30. The map generation unit 45 also acquires feature data from the target data output from the target detection unit 44. The position information of the target parking position 30 is used as target parking position coordinate data. The trained target data, including this relative position data, feature data, and target parking position coordinate data, is stored in the storage device 21 as map data 46.

[0021] When the parking support control unit 41 receives a control start command from the HMI control unit 40, it outputs a parking position calculation command to the matching unit 47. The matching unit 47 receives the target data output from the target detection unit 44 as target data of surrounding targets, and simultaneously receives the self-position of the vehicle 1 in the map coordinate system. Based on the target parking position coordinate data contained in the learned target data stored in the storage device 21, the matching unit 47 determines whether the vehicle 1 is located near the registered target parking position 30. Alternatively, the matching unit 47 may compare the feature data contained in the learned target data stored in the storage device 21 with the target data of targets around the vehicle 1 output from the target detection unit 44 to determine whether the vehicle 1 is located within a range where targets that can be matched with the learned target data near the target parking position 30 are detected. When the vehicle 1 is located near a registered target parking position 30, or when the vehicle 1 is located within a range where a target that can be matched to the learned target data is detected, the matching unit 47 matches the learned target with the surrounding targets and associates targets with the same feature points. Based on the relative positional relationship between the surrounding targets and the vehicle 1, and the relative positional relationship between the learned target associated with the surrounding targets and the target parking position 30, the matching unit 47 calculates the relative position of the vehicle 1 with respect to the target parking position 30. For example, if the surrounding targets are (x i ,y i ) is written, and surrounding targets (x i ,y i The learned targets associated with (x mi ,y mi ) is denoted as (i=1~N). The abutment section 47 is an affine transformation matrix M based on the least squares method by the following equation. affine Calculate.

[0022]

number

[0023] The abutment portion 47 is located at the position of the target parking position 30 on the map coordinate system stored in the map data 46 (targetx) according to the following formula. m ,targetym ) is converted to the position (targetx, targety) in the vehicle coordinate system.

[0024]

Number

[0025] The target trajectory generation unit 48 calculates a target travel trajectory from the current position of the host vehicle 1 in the vehicle coordinate system to the target parking position 30 and a target vehicle speed profile. The steering control unit 49a controls the steering actuator 19a so that the host vehicle 1 travels along the target travel trajectory. The vehicle speed control unit 49b controls the accelerator actuator 19b and the brake actuator 19c so that the vehicle speed of the host vehicle 1 changes according to the target vehicle speed profile. When the host vehicle 1 reaches the target parking position 30 and the parking support control is completed, the parking support control unit 41 activates the parking brake 18 and switches the shift position to the parking range (P range).

[0026] Next, the process when the detection accuracy of the self-position decreases will be described. For example, when the positioning device 11 detects the self-position of the host vehicle 1 using a GNSS receiver, a wireless LAN access point, etc., there is a possibility that the detection accuracy of the self-position decreases in an indoor parking lot (e.g., an underground parking lot). When detecting the self-position using high-precision map data, there is a possibility that the detection accuracy of the self-position decreases in a place where the high-precision map data is not sufficiently prepared.

[0027] FIGS. 4A and 4B are schematic views of a situation where the target parking position 30 is memorized in the indoor parking lot 50. In the example of FIG. 4A, the target parking position 30 in the parking frame 53n parked along the relatively short travel trajectory 52S after entering the indoor parking lot 50 from the entrance 51 is memorized, and in the example of FIG. 4B, the target parking position 30 in the parking frame 53f parked along the relatively long travel trajectory 52L is memorized.

[0028] If the accuracy of self-position detection by the positioning device 11 or high-precision map data is low, the self-position calculation unit 43 will be unable to correct the self-position calculated by odometry. As a result, as the mileage of the vehicle 1 increases, errors accumulate in the calculation result of the self-position, and the positional accuracy of the target parking position 30, which is stored as target parking position coordinate data in the learned target data, decreases. In addition, the positional accuracy of the self-position at the time parking assistance control is executed also decreases. As a result, when executing parking assistance control, the matching unit 47 may be unable to determine whether the vehicle 1 is located near the registered target parking position 30.

[0029] Therefore, when the map generation unit 45 determines that the detection accuracy of its own position has changed from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy, it sets the position detected at the point where the detection accuracy changes to a state where it is below a predetermined accuracy as the first position P1. For example, the position detected immediately before the change in the detection accuracy of the own position from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy may be set as the first position P1. For example, the position detected immediately before the change in the detection accuracy of the own position from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy may be temporarily stored as the first position P1.

[0030] After setting the first self-position P1, the map generation unit 45 determines whether or not to generate learned target data and store it in the storage device 21. For example, if the detection accuracy was below a certain accuracy when the vehicle 1 stopped at the target parking position 30, the map generation unit 45 may associate the information of the first self-position P1 with the learned target data and store it in the storage device 21. For example, the map generation unit 45 may determine whether or not the occupant performed a registration operation while the detection accuracy was below a predetermined accuracy. If it is determined that the learned target data should be generated and stored in the storage device 21 while the detection accuracy is below a predetermined accuracy, the map generation unit 45 associates the information of the first self-position P1 with the learned target data and stores it in the storage device 21. For example, the map generation unit 45 may determine whether or not to generate learned target data and store it in the storage device 21 when the detection accuracy of the first self-position P1 changes from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy, and the state where the detection accuracy is below a predetermined accuracy continues. For example, the map generation unit 45 may determine whether or not a crew member has performed a registration operation when the state where the detection accuracy is below a predetermined accuracy continues. If it is determined that learned target data should be generated and stored in the storage device 21 when the state where the detection accuracy is below a predetermined accuracy continues, the map generation unit 45 may associate the information of the first self-position P1 with the learned target data and store it in the storage device 21.

[0031] This allows the system to associate learned target object data for a target parking position 30 registered with a detection accuracy below a predetermined accuracy with position information (first self-position P1) detected with an accuracy of the predetermined accuracy or higher, and store this information in the storage device 21. As a result, even in locations where the detection accuracy of the self-position is below a predetermined accuracy, the system can determine whether there is a registered target parking position 30 near the self-position of the vehicle 1 by comparing it with the first self-position P1, and read the learned object data from the storage device 21. For example, the system can temporarily store the point where the detection accuracy of the self-position changes from above a predetermined accuracy to below a predetermined accuracy. When starting parking assistance control, the system can read the learned object data for the registered target parking position 30 by comparing the stored point with the first self-position P1. Also, for example, if multiple target parking positions 30 are registered in the storage device 21, the system can accurately select a target parking position 30 registered in a location where the detection accuracy of the self-position is below a predetermined accuracy.

[0032] Figures 5A and 5B are schematic diagrams illustrating the situation in which parking assistance control to the target parking position 30 is performed after the target parking position 30 has been registered. The positioning device 11 detects the vehicle's own position (sometimes referred to as "second self-position" in the following description) P2 after the target parking position 30 has been registered. The second self-position P2 may be detected by high-precision map data instead of or in addition to the positioning device 11. In Figures 5A and 5B, the dashed line range 54 indicates the range where the distance from the first self-position P1 is less than or equal to the first threshold Dt1. When the distance between the second self-position P2 and the first self-position P1 becomes less than or equal to the first threshold Dt1, the matching unit 47 reads the learned target data stored in association with the first self-position P1 from the storage device 21. This allows the system to verify whether the vehicle 1's own position is near the first self-position P1 and read the learned target data for the target parking position 30 registered in the indoor parking lot 50 from the storage device 21.

[0033] For example, the matching unit 47 may estimate the detection accuracy of the second self-position P2 and determine whether the detection accuracy has changed from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy. If the distance between the second self-position P2 and the first self-position P1 detected immediately before the detection accuracy changed to an accuracy below a predetermined accuracy becomes less than or equal to the first threshold Dt1, the matching unit 47 may read the learned target data stored in association with the first self-position P1 from the storage device 21. For example, when the detection accuracy of the second self-position P2 changes from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy, the abutment unit 47 may determine whether or not the first self-position P1 stored in the storage device 21 exists within a range of the second self-position P2 detected immediately before the change in detection accuracy to below the predetermined accuracy, and within a first threshold Dt1. That is, the first self-position P1 that exists within a range of the second self-position P2 and the first threshold Dt1 may be identified. Subsequently, when a parking position calculation command is received (i.e., when the start operation is accepted), the matching unit 47 may read the learned target data stored in association with the identified first self-position P1 from the storage device 21.

[0034] For example, the matching unit 47 may temporarily store the second self-position P2 when the detection accuracy of the second self-position P2 changes from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy, and the distance between the second self-position P2 and the first self-position P1 detected immediately before the detection accuracy changed to below the predetermined accuracy becomes a first threshold Dt1. Subsequently, when a parking position calculation command is received, the matching unit 47 may read the learned target data stored in association with the first self-position P1 that is within a range of the temporarily stored second self-position P2 and the first threshold Dt1 from the storage device 21.

[0035] As described above, the self-position calculation unit 43 calculates the self-position by odometry, and calculation errors accumulate as the distance traveled by the vehicle 1 increases. Therefore, even if the accuracy of self-position detection by the positioning device 11 or high-precision map data falls below a predetermined accuracy and the calculation result of the self-position can no longer be corrected, the positional accuracy of the self-position calculated by the self-position calculation unit 43 can be expected to be high before the distance traveled by the vehicle 1 increases. For example, in the situation shown in Figure 5A, the distance traveled by the vehicle 1 from the time the self-position detection accuracy falls below the predetermined accuracy until it approaches the registered target parking position 30 is short. Therefore, it is possible to accurately determine whether the vehicle 1 is sufficiently close to the target parking position 30 (i.e., whether the matching unit 47 can match the surrounding targets with the learned targets of the target parking position 30). On the other hand, in the situation shown in Figure 5B, the distance traveled until it approaches the target parking position 30 is long, and the positional accuracy of the self-position calculated by the self-position calculation unit 43 has decreased. Therefore, it is not possible to determine whether or not vehicle 1 has approached the target parking position 30 sufficiently.

[0036] Therefore, the matching unit 47 may calculate the distance traveled by the vehicle 1 after the detection accuracy of the second self-position P2 changes from a state where it is above a predetermined accuracy to a state where it is below a predetermined accuracy. If the calculated distance traveled is less than or equal to the second threshold Dt2, the matching unit 47 may read the learned target data from the storage device 21 based on the self-position of the vehicle 1 calculated from the odometry by the self-position calculation unit 43. For example, the matching unit 47 may compare the self-position of the vehicle 1 calculated from the odometry with the target parking position coordinate data of the learned target data stored in the storage device 21 and read the learned target data for the target parking position 30 near the self-position of the vehicle 1 from the storage device 21.

[0037] For example, the matching unit 47 determines whether the vehicle 1 is located near the registered target parking position 30 by comparing the vehicle's position calculated by the self-position calculation unit 43 from odometry with the target parking position coordinate data of the learned target data stored in the storage device 21. If the vehicle 1 is located near the registered target parking position 30 and a start operation by the occupant is received, the system reads the learned target data for the target parking position 30 near the vehicle 1 from the storage device 21 and provides parking assistance for the vehicle 1.

[0038] On the other hand, if the distance traveled after the detection accuracy of the second self-position P2 falls below a predetermined accuracy exceeds the second threshold Dt2, the learned target data stored in association with the first self-position P1, which is within a distance range of the first threshold Dt1 from the second self-position P2 detected immediately before the detection accuracy changed to below the predetermined accuracy, may be read from the storage device 21 of the learned target data that has features similar to the features of surrounding targets around the vehicle 1. Specifically, the matching unit 47 compares the feature data of a learned target 57 of the learned target data for the target parking position 30, which is stored in the storage device 21 in association with the first self-position P1 located within a distance range of less than or equal to the first threshold Dt1 from the second self-position P2, with the feature data of surrounding targets 56 detected around the vehicle 1 when parking assistance is performed. Based on whether the feature data of the surrounding targets and the feature data are similar, it is determined whether the vehicle 1 is located near the target parking position 30. If there are multiple target parking positions 30 stored in the storage device 21 in association with the first self-position P1 located within a distance range of less than or equal to the first threshold Dt1 from the second self-position P2, it is determined whether the vehicle 1 is located near all of these multiple target parking positions 30. When it is determined that the vehicle 1 is located near the target parking position 30 and a start operation is received from the occupant, the learned target data for the target parking position 30 near the vehicle 1 is read from the storage device 21 and parking assistance for the vehicle 1 is provided.

[0039] Refer to Figure 6. In step S1, the positioning device 11 detects its own position. In step S2, the map generation unit 45 estimates the detection accuracy of its own position. If the detection accuracy is less than a predetermined accuracy (step S3:Y), the process proceeds to step S4. If the detection accuracy is equal to or greater than the predetermined accuracy (step S3:N), the process proceeds to step S7. In step S4, the map generation unit 45 determines whether the value of the first flag FLG1 is True. The first flag FLG1 is a determination value that is set to True or false at a predetermined step in the flowchart. For example, in step S6, the value of FLG1 is False, and in step S7, the value of FLG1 is True. If the value of the first flag FLG1 is True (step S4:Y), the process proceeds to step S5. If the value of the first flag FLG1 is False (step S4:N), the process proceeds to step S9.

[0040] In step S5, the map generation unit 45 temporarily stores the self-position detected in step S1 as the first self-position P1. In step S6, the map generation unit 45 sets the value of the first flag FLG1 to False. The process then proceeds to step S9. In step S7, the map generation unit 45 sets the value of the first flag FLG1 to True. In step S8, the map generation unit 45 erases the first self-position P1 stored in step S5. The process then proceeds to step S9.

[0041] In step S9, the HMI control unit 40 determines whether the occupant has performed a registration operation. If the occupant has performed a registration operation (step S9:Y), the process proceeds to step S10. If the occupant has not performed a registration operation (step S9:N), the process returns to step S1. In step S10, the target detection unit 44 detects targets around the target parking position 30. In step S11, the map generation unit 45 generates learned target data and stores it in the storage device 21. In step S12, the map generation unit 45 determines whether the value of the first flag FLG1 is False. If the value of the first flag FLG1 is False (step S12:Y), the process proceeds to step S13. If the value of the first flag FLG1 is True (step S12:N), the process ends. In step S13, the map generation unit 45 stores the information of the first self-position P1, which was temporarily stored in step S5, in the storage device 21, associating it with the learned target data stored in step S11. After that, the process ends.

[0042] Refer to Figure 7. In step S20, the positioning device 11 detects the second self-position P2. In step S21, the matching unit 47 estimates the detection accuracy of the second self-position P2. If the detection accuracy is less than a predetermined accuracy (step S22:Y), the process proceeds to step S23. If the detection accuracy is equal to or greater than the predetermined accuracy (step S22:N), the process proceeds to step S29. In step S23, the matching unit 47 determines whether the value of the second flag FLG2 is True. The second flag FLG2 is a determination value that is set to True or False at a predetermined step in the flowchart. For example, in step S28, the value of FLG2 becomes False, and in step S29, the value of FLG2 becomes True. If the value of the second flag FLG2 is True (step S23:Y), the process proceeds to step S24. If the value of the second flag FLG2 is False (step S23:N), the process proceeds to step S32.

[0043] In step S24, the abutment unit 47 determines whether the distance between the second self-position P2 and the first self-position P1 is less than or equal to the first threshold Dt1. If the distance between the second self-position P2 and the first self-position P1 is less than or equal to the first threshold Dt1 (step S24:Y), the process proceeds to step S25. If the distance between the second self-position P2 and the first self-position P1 is not less than or equal to the first threshold Dt1 (step S24:N), the process proceeds to step S27. In step S25, the abutment unit 47 temporarily stores the second self-position P2. In step S26, the abutment unit 47 sets the value of the third flag FLG3 to True. The third flag FLG3 is a determination value that is set to True or False at a predetermined step in the flowchart. For example, in step S26, the value of FLG3 is True, and in steps S27 and S31, the value of FLG3 is False. The process then proceeds to step S28. In step S27, the abutment unit 47 sets the value of the third flag FLG3 to False. The process then proceeds to step S28. In step S28, the abutment unit 47 sets the value of the second flag FLG2 to False. The process then proceeds to step S32.

[0044] In step S29, the abutment unit 47 sets the value of the second flag FLG2 to True. In step S30, the abutment unit 47 erases the second self-position P2 that was previously stored in step S25. In step S31, the abutment unit 47 sets the value of the third flag FLG3 to False. The process then proceeds to step S32. In step S32, the target detection unit 44 detects surrounding targets present around the vehicle 1. In step S33, the HMI control unit 40 determines whether or not the occupant has performed the start operation. If the occupant has performed the start operation (step S33:Y), the process proceeds to step S34. If the occupant has not performed the start operation (step S33:N), the process returns to step S20.

[0045] In step S34, the matching unit 47 determines whether the value of the second flag FLG2 is False or not. If the value of the second flag FLG2 is False (step S34: Y), the process proceeds to step S36. If the value of the second flag FLG2 is True (step S34: N), the process proceeds to step S35. In step S35, the matching unit 47 reads the learned target data of the registered target parking position 30 near the second self-position P2, which is the current position of the vehicle 1, from the storage device 21. After that, the process proceeds to step S40. In step S36, the matching unit 47 determines whether the value of the third flag FLG3 is True or not. If the value of the third flag FLG3 is True (step S36: Y), the process proceeds to step S37. If the value of the third flag FLG3 is False (step S36: N), the process ends.

[0046] In step S37, the matching unit 47 determines whether the distance traveled after the detection accuracy of the second self-position P2 falls below a predetermined accuracy is less than or equal to the second threshold Dt2. If the distance traveled is less than or equal to the second threshold Dt2 (step S37:Y), the process proceeds to step S38. If the distance traveled is not less than or equal to the second threshold Dt2 (step S37:N), the process proceeds to step S39. In step S38, the matching unit 47 reads the learned target data from the storage device 21 based on the self-position calculated by the self-position calculation unit 43 using odometry. The process then proceeds to step S40. In step S39, the matching unit 47 reads the learned target data from the storage device 21 of targets that have features similar to the features of surrounding targets, among the learned target data stored in association with the first self-position P1 located within a distance range of less than or equal to the first threshold Dt1 from the second self-position P2 stored in step S25. The process then proceeds to step S40. In step S40, the matching unit 47 matches the surrounding targets with the learned target data to calculate the relative position of the vehicle 1 with respect to the target parking position 30. In step S41, the target trajectory generation unit 48 calculates the target driving trajectory and the target vehicle speed profile. In step S42, the steering control unit 49a and the vehicle speed control unit 49b control the steering actuator 19a, the accelerator actuator 19b, and the brake actuator 19c based on the target driving trajectory and the target vehicle speed profile. In step S43, once the parking assistance control unit 41 has completed the parking assistance control, it activates the parking brake 18 and switches the shift position to the P range. The process then ends.

[0047] (Effects of the embodiment) (1) According to the parking assistance method described in claim 1, even in locations where the self-position detection accuracy is less than a predetermined accuracy, it is possible to determine whether or not there is a registered target parking position near the vehicle 1 and read the learned target data from the storage device. According to the parking assistance method described in claim 2, even in locations where the self-position detection accuracy is less than a predetermined accuracy, the parking of the vehicle 1 to the target parking position can be assisted using the learned target object data of the registered target parking position. According to the parking assistance method described in claim 3, even in locations where the self-position detection accuracy is less than a predetermined accuracy, the parking of the vehicle 1 to the target parking position can be assisted using the learned target object data of the registered target parking position. (2) According to the parking assistance method described in claim 4, even if parking assistance control is started after entering a place where the self-position detection accuracy is less than a predetermined accuracy, the learned target data can be read from the storage device. According to the parking assistance method described in claim 5, even if parking assistance control is started after entering a location where the self-position detection accuracy is less than a predetermined accuracy, the learned target data can be read from the storage device.

[0048] (3) According to the parking assistance method described in claim 6, when the distance traveled after entering a place where the self-position detection accuracy is less than a predetermined accuracy is relatively short, the learned target data can be efficiently read from the storage device. (4) According to the parking assistance method described in claim 7, even if the distance traveled after entering a place where the self-position detection accuracy is less than a predetermined accuracy is relatively long, the learned target data can be read from the storage device. (5) According to the parking assistance method described in claim 8, learned target data of a registered target parking position can be accurately selected at locations where the self-position detection accuracy is less than a predetermined accuracy. [Explanation of symbols]

[0049] 1...Vehicle, 10...Parking assist system, 17...Controller

Claims

1. The controller The vehicle detects its own position, The accuracy of detecting the self-position is estimated, The self-position at the point where the detection accuracy changes from a state where it is above a predetermined accuracy to a state where it is below the predetermined accuracy is set as the first self-position. After the first self-position is set, when the vehicle parks at the target parking position, the relative positional relationship between the target parking position and the objects surrounding the target parking position is detected. If the detection accuracy is less than a predetermined accuracy when the vehicle stops at the target parking position, the first self-position and the learned target data, which is data representing the relative positional relationship, are associated and stored in the storage device. When the first self-position and the learned target data are stored in association, the system assists in parking the vehicle to the target parking position based on the first self-position and the learned target data. A parking assistance method characterized by the following features.

2. The controller is The second self-position of the vehicle at a point in time later than the learning time, which is the time when the learned target data is stored, is detected. When the distance between the second self-position and the first self-position becomes less than or equal to the first threshold, the learned target data stored in association with the first self-position is read from the storage device. The position of surrounding targets, which are targets present around the vehicle, is detected at a time after the aforementioned learning point. Based on the learned target data and the positions of the surrounding targets, the relative positional relationship between the target parking position and the current position of the vehicle is calculated. Based on the relative positional relationship between the target parking position and the current position of the vehicle, the driving trajectory from the current position of the vehicle to the target parking position is calculated. The parking assistance method according to claim 1, characterized in that it assists in parking the vehicle at the target parking position based on the aforementioned driving trajectory.

3. The controller is The detection accuracy of the second self-position is estimated, When the detection accuracy of the second self-position changes from a state where it is equal to or greater than the predetermined accuracy to a state where it is less than the predetermined accuracy, and the distance between the second self-position and the first self-position becomes less than or equal to the first threshold, the learned target data stored in association with the first self-position is read from the storage device. The parking assistance method according to feature 2.

4. The controller is When the detection accuracy of the second self-position changes from a state where it is equal to or greater than the predetermined accuracy to a state where it is less than the predetermined accuracy, the first self-position that is within the range of the second self-position to the first threshold is identified. When an operation to instruct the detection of the target parking position is received from the occupant, the learned target data stored in association with the identified first self-position is read from the storage device. The parking assistance method according to feature 3.

5. The controller is The second self-position of the vehicle at a time later than the learning time, which is the time when the learned target data is stored, is detected, and the second self-position is stored when the detection accuracy of the second self-position changes from a state where it is equal to or greater than the predetermined accuracy to a state where it is less than the predetermined accuracy, and the distance between the second self-position and the first self-position becomes less than or equal to the first threshold. When an operation to instruct the detection of the target parking position is received from the occupant, the learned target data stored in association with the first self-position, which is within a distance range of the second self-position and less than or equal to the first threshold, is read from the storage device. The position of surrounding targets, which are targets present around the vehicle, is detected at a time after the aforementioned learning point. Based on the learned target data and the positions of the surrounding targets, the relative positional relationship between the target parking position and the current position of the vehicle is calculated. Based on the relative positional relationship between the target parking position and the current position of the vehicle, the driving trajectory from the current position of the vehicle to the target parking position is calculated. The parking assistance method according to claim 1, characterized in that it assists in parking the vehicle at the target parking position based on the aforementioned driving trajectory.

6. The learned target data includes the location data of the target parking position, The aforementioned controller, The detection accuracy of the second self-position is estimated, The parking assistance method according to claim 2, characterized in that, if the distance traveled by the vehicle after the detection accuracy of the second self-position changes from a state in which it is equal to or greater than the predetermined accuracy to a state in which it is less than the predetermined accuracy is less than or equal to the second threshold, the learned target data is read from the storage device based on the self-position of the vehicle estimated from the odometry of the vehicle.

7. The aforementioned trained target data includes feature data of targets present around the target parking location. The aforementioned controller, The detection accuracy of the second self-position is estimated, The parking assistance method according to claim 2, characterized in that, if the distance traveled by the vehicle after the detection accuracy of the second self-position changes from a state in which it is equal to or greater than the predetermined accuracy to a state in which it is less than the predetermined accuracy is greater than the second threshold, the learned target data stored in association with the first self-position that has feature quantities similar to the feature quantities of the surrounding targets is read from the storage device.

8. The controller is The learned target data for multiple target parking positions is stored in the storage device. The parking assistance method according to any one of claims 2 to 7, characterized in that when the distance between the second self-position and the first self-position becomes less than or equal to a first threshold, the learned target data stored in association with the first self-position among the plurality of target parking positions is read from the storage device.

9. Memory device and A parking assistance device comprising a controller that performs the following: a process of acquiring position information obtained by determining the current position of the vehicle; a process of estimating the detection accuracy of the vehicle's own position; a process of setting the vehicle's own position at the point in which the detection accuracy changes from a state of being above a predetermined accuracy to a state of being below a predetermined accuracy as the first vehicle's own position; a process of detecting the relative positional relationship between the target parking position and objects present around the target parking position when the vehicle parks at the target parking position after the first vehicle's own position has been set; a process of associating the first vehicle's own position with learned object data, which is data representing the relative positional relationship, and storing it in the storage device if the detection accuracy was below a predetermined accuracy when the vehicle stopped at the target parking position; and a process of assisting the vehicle to park at the target parking position based on the first vehicle's own position and the learned object data, when the first vehicle's own position and the learned object data are stored as an association.

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