Control device, control method, and control program

Abstract

The present invention provides a control device, a control method, and a control program that can reduce power consumption associated with position estimation processing while suppressing a decrease in convenience. [Solution] The system includes a storage unit 54 that stores parking information indicating the starting point 61 for the vehicle 10, the parking space 62 for the vehicle 10, and the vehicle 10's movement path 63 from the starting point 61 to the parking space 62; a position estimation unit 55 that performs a position estimation process including acquiring external information of the vehicle 10, extracting feature points from the external information, and estimating the position of the vehicle 10 based on the feature points and map information; and a movement control unit 56 that performs movement control to move the vehicle 10 from the starting point 61 to the parking space 62 based on the results of the position estimation process and the parking information. The position estimation unit 55 controls the estimation accuracy of the position estimation process based on the distance between the starting point 61 and the vehicle 10.

Description

Technical Field

[0001] The present invention relates to a control device, a control method, and a control program.

Background Art

[0002] In recent years, efforts have been actively made to provide access to a sustainable transportation system that takes into account people in vulnerable positions among transportation participants. Towards this realization, research and development efforts are focused on further improving traffic safety and convenience through research and development related to driving support technologies.

[0003] Conventionally, in an automatic driving system that automatically runs a vehicle without requiring a user's driving operation, when the vehicle reaches a target position by the user's driving operation, the route at that time is memorized, and when traveling to the same target position or the same route, the vehicle is controlled to move based on the memorized route history. Also, it is known to generate route information from the current position to the target position based on information acquired by in-vehicle sensors and control the movement of the vehicle.

[0004] For example, Patent Document 1 describes a parking support device configured to be able to execute parking support control with a registered parking position as a target parking position when the current position of a vehicle acquired by a position acquisition device is a point near the registered parking position memorized in a memory.

Prior Art Documents

Patent Documents

[0005]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0006] Incidentally, when controlling the movement of a vehicle to a target position, a technique is used to estimate the vehicle's position by comparing the stored feature points of the surrounding environment with the feature points of the surrounding environment obtained during the current driving, and then perform the movement control. In order for a vehicle to accurately travel along the path to the stored target position while in motion, it is necessary to, for example, constantly extract feature points of the surrounding environment during driving and compare the extracted feature points with the stored feature points. However, the process of acquiring surrounding environment information, extracting feature points from the acquired surrounding environment information, and comparing the extracted feature points is computationally intensive, resulting in high power consumption. Patent Document 1 does not describe how to reduce power consumption by reducing the computational load of estimating the vehicle's position in the movement control of a vehicle traveling along a path to a target position.

[0007] The present invention aims to provide a control device, a control method, and a control program that can reduce power consumption associated with position estimation processing while suppressing a decrease in convenience. Ultimately, this contributes to the development of sustainable transportation systems. [Means for solving the problem]

[0008] The present invention A control device for a mobile body, A storage unit that stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space, A position estimation unit performs position estimation processing including acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. The system includes a movement control unit that performs movement control to move the moving body from the starting point to the parking space based on the results of the position estimation process and the parking information, The position estimation unit controls the estimation accuracy of the position estimation process based on the distance between the starting point of movement and the moving object. It is a control device.

[0009] The present invention A control method using a control device for a mobile object, The control device, The system stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space. A position estimation process is performed which includes acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. Based on the results of the position estimation process and the parking information, movement control is performed to move the moving body from the starting point to the parking space. The estimation accuracy of the position estimation process is controlled based on the distance between the starting point of movement and the moving object. This is a control method.

[0010] The present invention A control program for a mobile device, The processor of the control device, The system stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space. A position estimation process is performed which includes acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. Based on the results of the position estimation process and the parking information, movement control is performed to move the moving body from the starting point to the parking space. The estimation accuracy of the position estimation process is controlled based on the distance between the starting point of movement and the moving object. This is a control program that executes a process. [Effects of the Invention]

[0011] According to the present invention, it is possible to provide a control device, a control method, and a control program that can reduce power consumption associated with position estimation processing while suppressing a decrease in convenience. [Brief explanation of the drawing]

[0012] [Figure 1] It is a side view showing an example of a vehicle 10 equipped with the control device of the present invention. [Figure 2] It is a top view of the vehicle 10 shown in FIG. 1. [Figure 3] It is a block diagram showing an example of the internal configuration of the vehicle 10 shown in FIG. 1. [Figure 4] It is a diagram showing a first example of controlling the estimation accuracy of the position estimation process. [Figure 5] It is a flowchart showing a first example of the position estimation process. [Figure 6] It is a diagram showing a first example of the change in the estimation accuracy in the position estimation process. [Figure 7] It is a diagram showing a second example of controlling the estimation accuracy of the position estimation process. [Figure 8] It is a flowchart showing a second example of the position estimation process. [Figure 9] It is a diagram showing a second example of the change in the estimation accuracy in the position estimation process. [Figure 10] It is a flowchart showing a third example of the position estimation process.

Mode for Carrying Out the Invention

[0013] Hereinafter, an embodiment of the control device, control method, and control program of the present invention will be described based on the accompanying drawings. In the drawings, the direction of the reference numerals is to be viewed. Also, in this specification and the like, for the sake of simplicity and clarity of explanation, the front, rear, left, and right directions are described according to the directions seen from the driver of the vehicle 10 shown in FIGS. 1 and 2, and in the drawings, the front of the vehicle 10 is shown as Fr, the rear as Rr, the left as L, the right as R, the upper as U, and the lower as D.

[0014] <Vehicle 10 Equipped with the Control Device of the Present Invention> FIG. 1 is a side view showing an example of a vehicle 10 equipped with the control device of the present invention. FIG. 2 is a top view of the vehicle 10 shown in FIG. 1. The vehicle 10 is an example of the "moving body" of the present invention.

[0015] Vehicle 10 is an automobile having a drive source (not shown) and wheels including drive wheels and steerable wheels that are driven by the power of the drive source. In this embodiment, vehicle 10 is a four-wheeled automobile having a pair of left and right front wheels and rear wheels. The drive source of vehicle 10 is, for example, an electric motor. The drive source of vehicle 10 may be an internal combustion engine such as a gasoline engine or a diesel engine, or a combination of an electric motor and an internal combustion engine. Furthermore, the drive source of vehicle 10 may drive a pair of left and right front wheels, a pair of left and right rear wheels, or all four wheels including a pair of left and right front wheels and rear wheels. Both the front wheels and rear wheels may be steerable wheels, or either one of them may be a steerable wheel.

[0016] Vehicle 10 is further equipped with side mirrors 11L and 11R. Side mirrors 11L and 11R are mirrors (rearview mirrors) provided on the outside of the front passenger doors of vehicle 10 for the driver to check the area behind and to the rear side. Side mirrors 11L and 11R are each fixed to the body of vehicle 10 by a vertically extending pivot axis, and can be opened and closed by rotating around this pivot axis.

[0017] Vehicle 10 is further equipped with a front camera 12Fr, a rear camera 12Rr, a left-side camera 12L, and a right-side camera 12R. The front camera 12Fr is an imaging device (e.g., a digital camera) located in front of vehicle 10 that images the area in front of vehicle 10. The rear camera 12Rr is a digital camera located behind vehicle 10 that images the area behind vehicle 10. The left-side camera 12L is a digital camera located on the left side mirror 11L of vehicle 10 that images the area to the left of vehicle 10. The right-side camera 12R is a digital camera located on the right side mirror 11R of vehicle 10 that images the area to the right of vehicle 10.

[0018] <Internal configuration of vehicle 10> Figure 3 is a block diagram showing an example of the internal configuration of the vehicle 10 shown in Figure 1. As shown in Figure 3, the vehicle 10 includes a sensor group 16, a navigation device 18, a control ECU (Electronic Control Unit) 20, an EPS (Electric Power Steering) system 22, and a communication unit 24. The vehicle 10 further includes a drive force control system 26 and a braking force control system 28.

[0019] The sensor group 16 acquires various detection values ​​used for control by the control ECU 20. The sensor group 16 includes a front camera 12Fr, a rear camera 12Rr, a left-side camera 12L, and a right-side camera 12R. The sensor group 16 also includes a front sonar group 32a, a rear sonar group 32b, a left-side sonar group 32c, and a right-side sonar group 32d. Furthermore, the sensor group 16 includes wheel sensors 34a and 34b, a vehicle speed sensor 36, and an operation detection unit 38.

[0020] The front camera 12Fr, rear camera 12Rr, left-side camera 12L, and right-side camera 12R acquire external information (e.g., external images) for recognizing the outside world of the vehicle 10 by imaging the area around the vehicle 10. The external images of the vehicle 10 captured by the front camera 12Fr, rear camera 12Rr, left-side camera 12L, and right-side camera 12R are referred to as the front image, rear image, left-side image, and right-side image, respectively. The image composed of the left-side image and the right-side image may also be referred to as a side image. The image of the vehicle 10 and the outside world generated by combining the images captured by the front camera 12Fr, rear camera 12Rr, left-side camera 12L, and right-side camera 12R is referred to as an overhead view image of the vehicle 10.

[0021] The forward sonar group 32a, the rear sonar group 32b, the left-side sonar group 32c, and the right-side sonar group 32d emit sound waves around the vehicle 10 and receive reflected sound from other objects. The forward sonar group 32a includes, for example, four sonars. The sonars constituting the forward sonar group 32a are located on the left front, front left, front right, and right front of the vehicle 10, respectively. The rear sonar group 32b includes, for example, four sonars. The sonars constituting the rear sonar group 32b are located on the left rear, rear left, rear right, and right rear of the vehicle 10, respectively. The left-side sonar group 32c includes, for example, two sonars. The sonars constituting the left-side sonar group 32c are located on the left front and left rear of the vehicle 10, respectively. The right-side sonar group 32d includes, for example, two sonars. The sonars constituting the right-side sonar group 32d are located on the front right side and the rear right side of the vehicle 10, respectively.

[0022] Wheel sensors 34a and 34b detect the rotation angle of the wheels of the vehicle 10. Wheel sensors 34a and 34b may be composed of angle sensors or displacement sensors. Wheel sensors 34a and 34b output a detection pulse each time the wheel rotates by a predetermined angle. The detection pulses output from wheel sensors 34a and 34b are used to calculate the rotation angle and rotation speed of the wheels. Based on the rotation angle of the wheels, the distance traveled by the vehicle 10 is calculated. Wheel sensor 34a detects, for example, the rotation angle θa of the left rear wheel. Wheel sensor 34b detects, for example, the rotation angle θb of the right rear wheel.

[0023] The vehicle speed sensor 36 detects the speed of the vehicle body 10, i.e., the vehicle speed V, and outputs the detected vehicle speed V to the control ECU 20. The vehicle speed sensor 36 detects the vehicle speed V based, for example, on the rotation of the transmission countershaft.

[0024] The operation detection unit 38 detects the user's operation using the operation input unit 14 and outputs the detected operation to the control ECU 20. The operation input unit 14 includes various user interfaces, such as a side mirror switch for switching the open / closed state of the side mirrors 11L and 11R, and a shift lever (selector lever or selector).

[0025] The navigation device 18 detects the current position (location coordinates) of the vehicle 10, for example, using GPS (Global Positioning System), and guides the user on the route to the destination. The navigation device 18 has a storage device (not shown) equipped with a map information database. The navigation device 18 also has a touch panel 42 and a speaker 44. The touch panel 42 functions as an input device and display device for the control ECU 20. The speaker 44 outputs various guidance information to the user of the vehicle 10 in voice.

[0026] The touch panel 42 is configured to allow input of various commands to the control ECU 20. For example, the user can input commands related to vehicle movement assistance for the vehicle 10 via the touch panel 42. Movement assistance includes parking assistance and exit assistance for the vehicle 10. The touch panel 42 is also configured to display various screens related to the control content of the control ECU 20. For example, the touch panel 42 displays a screen related to vehicle movement assistance for the vehicle 10. Specifically, the touch panel 42 displays a parking assistance button to request parking assistance for the vehicle 10 and an exit assistance button to request exit assistance. The parking assistance buttons include a memory parking button to request parking by automatic steering of the control ECU 20 and an auxiliary parking button to request assistance when parking by the user. The exit assistance buttons include a memory exit button to request exiting by automatic steering of the control ECU 20 and an auxiliary exit button to request assistance when exiting by the user. Note that components other than the touch panel 42, such as information terminals like smartphones and tablets, may be used as input or display devices.

[0027] Note that "parking" is synonymous with "parking," for example. For example, "parking" refers to a stop involving the user getting in and out of the vehicle, excluding temporary stops at traffic lights, etc. Also, "parking space" refers to a space where vehicle 10 is stopped, that is, a space for parking.

[0028] The control ECU 20 includes an input / output unit 50, an arithmetic unit 52, and a storage unit 54. The arithmetic unit 52 is configured, for example, by a CPU (Central Processing Unit). The arithmetic unit 52 performs various controls by controlling each unit based on a program stored in the storage unit 54. The arithmetic unit 52 also inputs and outputs signals to and from each unit connected to the control ECU 20 via the input / output unit 50. The control ECU 20 is an example of the "control device" of the present invention.

[0029] The memory unit 54 stores information related to the memory movement (memory parking / exit) of the vehicle 10. The memory movement information is information for automatically or assisted in moving the vehicle 10 based on previously stored movement information. For example, the memory unit 54 stores parking information indicating the starting point for starting the memory movement, the parking space where the vehicle 10 will be stopped by the memory movement, and the movement path of the vehicle 10 from the starting point to the parking space.

[0030] The calculation unit 52 includes a position estimation unit 55 that performs position estimation processing for the vehicle 10, a movement control unit 56 that controls the movement of the vehicle 10, and a motion detection unit 57 that detects moving objects around the vehicle 10.

[0031] The position estimation unit 55 performs position estimation processing, which includes acquiring external information of the vehicle 10, extracting feature points from the external information, and estimating the position of the vehicle 10 based on the feature points and map information. "Acquisition of external information" means acquiring external information of the vehicle 10 captured by the front camera 12Fr, rear camera 12Rr, left side camera 12L, and right side camera 12R. "Feature points from external information" are characteristic features, such as objects, included in the external information along the vehicle 10's movement path.

[0032] The movement control unit 56 provides automatic steering assistance for the vehicle 10, including memory parking and memory exit assistance, by automatically operating the steering wheel 110 under the control of the movement control unit 56. During memory parking and memory exit assistance, the accelerator pedal (not shown), brake pedal (not shown), and operation input unit 14 are operated automatically. The movement control unit 56 also provides auxiliary parking and auxiliary exit assistance when the user (driver) operates the accelerator pedal, brake pedal, and operation input unit 14 to manually park and exit the vehicle 10. During memory parking and memory exit assistance, the driver may be inside the vehicle 10 or may be outside the vehicle (unoccupied).

[0033] For example, the movement control unit 56 performs movement control to move the vehicle 10 based on the results of the position estimation processing by the position estimation unit 55 and parking information stored in the storage unit 54 that indicates the starting point of movement, the parking space, and the movement route. The movement control is, for example, parking control that moves the vehicle 10 from the starting point to a predetermined parking space (target parking position) and parks it in memory. The movement control unit 56 can execute parking control and exit control based on instruction signals input via the input / output unit 50. The input instruction signals include instruction signals transmitted wirelessly from the user's information terminal or the like. The movement control unit 56 also outputs information related to parking control and exit control to the information terminal or the like via the input / output unit 50.

[0034] The motion detection unit 57 detects moving objects in the vicinity of the vehicle 10 based on external information about the vehicle 10. "Moving objects" include, for example, pedestrians, bicycles, and other vehicles.

[0035] Furthermore, the position estimation unit 55 controls the estimation accuracy of the position estimation process based on the distance between the starting point of movement and the vehicle 10. The "distance" is detected based on, for example, GPS information. The position estimation unit 55 controls the position estimation process to be more accurate the shorter the distance between the starting point of movement and the vehicle 10. For example, the position estimation unit 55 can perform position estimation processing using a first position estimation process and a second position estimation process which has higher estimation accuracy and processing load than the first position estimation process. If the "distance" is greater than or equal to a predetermined value, the first position estimation process is performed, and if the "distance" is less than a predetermined value, the second position estimation process is performed. The estimation accuracy of the position estimation process may be switched between three or more levels, or it may be continuously changed according to the distance.

[0036] "Controlling the estimation accuracy of the position estimation process" means changing at least one of the processes, from the imaging process that captures external information to the matching process that compares the feature points of the external information. For example, "controlling the estimation accuracy of the position estimation process" includes improving the estimation accuracy by increasing the image quality of the camera and decreasing the estimation accuracy by decreasing the image quality. Also, "controlling the estimation accuracy of the position estimation process" includes improving the estimation accuracy by narrowing the range of the camera image being compared and decreasing the estimation accuracy by widening the range. Furthermore, "controlling the estimation accuracy of the position estimation process" includes changing the estimation accuracy by terminating the matching process after a certain period of time. Also, "controlling the estimation accuracy of the position estimation process" includes pre-setting high-priority and low-priority parking lots and prioritizing the position estimation process for high-priority parking lots to reduce the number of matching targets. Generally, increasing the estimation accuracy increases the processing load of the position estimation unit 55 and thus increases power consumption.

[0037] The position estimation unit 55, when certain conditions regarding the starting point of movement are met, increases the estimation accuracy of the position estimation process during the period when the vehicle 10 is traveling in the section immediately preceding the starting point of movement compared to when the conditions are not met. The "section immediately preceding the starting point of movement" is, for example, a section of a predetermined distance before the starting point of movement (for example, 10m before it). "Increasing the estimation accuracy" means, for example, if the estimation accuracy of the position estimation process can be switched between multiple levels, setting it to the highest estimation accuracy. The estimation accuracy does not have to be increased for the entire "immediate section," but may be increased for at least a part of it.

[0038] The predetermined conditions include, for example, that the starting point of movement is set near the boundary between a public road and a non-public road. A "non-public road" may be, for example, a private road, or an area that is not designated as a road. "Near the boundary" means, for example, that the distance from the boundary is below a threshold. The predetermined conditions also include that the starting point of movement is set near the boundary, and that vehicle 10 is traveling on a public road. "Traveling on a public road" means, for example, that the vehicle is about to enter a private road from a public road, not that it is about to exit a private road onto a public road.

[0039] The position estimation unit 55 sets the estimation accuracy for the section immediately preceding the starting point of movement to a predetermined accuracy when predetermined conditions are met, and makes the estimation accuracy variable when the vehicle 10 enters a non-public road. "Predetermined accuracy" refers to a fixed estimation accuracy; for example, if the estimation accuracy can be switched between multiple levels, it means setting it to the highest estimation accuracy. "Variable estimation accuracy" means controlling the estimation accuracy according to the surrounding environment and driving conditions of the vehicle 10, for example, by setting it lower than the predetermined accuracy.

[0040] The position estimation unit 55 controls the estimation accuracy of the position estimation process based on the number of moving objects present around the vehicle 10 detected by the moving object detection unit 57. For example, if the number of moving objects present around the vehicle 10 is greater than or equal to a first predetermined number, the position estimation unit 55 controls the position estimation process to be more accurate than when the number of moving objects is less than the first predetermined number. Also, if the number of moving objects present around the vehicle 10 is greater than or equal to a second predetermined number (more than the first predetermined number), the position estimation unit 55 controls the position estimation process to be less accurate than when the number of moving objects is greater than or equal to the first predetermined number but less than the second predetermined number. "Lowering" means, for example, making the estimation accuracy equivalent to (e.g., the same as) when the number of moving objects is less than the first predetermined number. Note that when the number of moving objects is greater than or equal to the second predetermined number, the estimation accuracy may be lower than when the number is less than the first predetermined number. Specifically, if there are too many pedestrians, etc., present around the vehicle 10 (greater than or equal to the second predetermined number), the estimation accuracy is lowered because the load on feature point matching processing etc. increases.

[0041] The EPS system 22 includes a steering angle sensor 100, a torque sensor 102, an EPS motor 104, a resolver 106, and an EPS ECU 108. The steering angle sensor 100 detects the steering angle θst of the steering 110. The torque sensor 102 detects the torque TQ applied to the steering 110.

[0042] The EPS motor 104 provides driving force or reaction force to the steering column 112 connected to the steering 110, thereby enabling user assistance in operating the steering 110 and automatic steering during parking assistance. The resolver 106 detects the rotation angle θm of the EPS motor 104. The EPS ECU 108 controls the entire EPS system 22. The EPS ECU 108 includes an input / output unit (not shown), a calculation unit (not shown), and a storage unit (not shown).

[0043] The communication unit 24 enables wireless communication with other communication devices 120. Other communication devices 120 include base stations, communication devices in other vehicles, and information terminals such as smartphones or tablets owned by the user of vehicle 10. For example, the communication unit 24 is equipped with a UWB interface that enables UWB (Ultra Wide Band: registered trademark) communication with information terminals. The communication unit 24 can send and receive information regarding the memory parking / exit and auxiliary parking / exit of vehicle 10 with information terminals, etc.

[0044] The drive force control system 26 includes a drive ECU 130. The drive force control system 26 controls the drive force of the vehicle 10. The drive ECU 130 controls the drive force of the vehicle 10 by controlling an engine (not shown) and other components (not shown) based on user operation of an accelerator pedal (not shown).

[0045] The braking force control system 28 includes a braking ECU 132. The braking force control system 28 controls the braking force of the vehicle 10. The braking ECU 132 controls the braking force of the vehicle 10 by controlling a braking mechanism (not shown) and the like based on user operation of a brake pedal (not shown).

[0046] <Example 1 of controlling estimation accuracy> Figure 4 shows a first example of controlling the estimation accuracy of the position estimation process. As shown in Figure 4, the vehicle 10 performs control to change the estimation accuracy of the position estimation process when, for example, the vehicle 10 is parked in memory at a parking facility 60.

[0047] The parking facility 60 is, for example, a parking facility in a shopping mall that is frequently used by the user of vehicle 10. The user of vehicle 10 frequently uses parking space 62 as the place to park vehicle 10 from among the multiple parking spaces in the parking facility 60, and has registered parking space 62 in the storage unit 54 as a parking space on which memory parking is possible. As shown in Figure 4, parking space 62 has both a starting point 61 on which vehicle 10 begins to move when performing memory parking, and a movement path 63 (dashed arrow) on which vehicle 10 travels from the starting point 61 to parking space 62, both of which are registered in the storage unit 54 as parking information for performing memory parking.

[0048] To register parking information, first, the user manually drives the vehicle 10 and stops it at a designated starting point (e.g., starting point 61). Next, the user starts the registration by pressing a button such as "Start Parking Information Registration" (not shown) to begin the registration. The user manually drives the vehicle 10 along a designated route (e.g., travel route 63) and parks the vehicle 10 in a designated parking space (e.g., parking space 62). Next, the user completes the registration by pressing a button such as "Finish Parking Information Registration" (not shown) to end the registration. Note that the travel route 63 shown in this example is a simplified representation, but it may include a turning route, for example, when backing the vehicle 10 into parking space 62. The parking information may also include feature points of external information acquired while driving along the travel route 63.

[0049] <First example of position estimation processing> Figure 5 is a flowchart showing a first example of the position estimation process. This example describes the position estimation process when a vehicle 10 is parked in memory at the parking facility 60 shown in Figure 4. This position estimation process is repeatedly executed while the vehicle 10 is in motion.

[0050] First, the vehicle 10 determines whether or not to start the position estimation process (step S11). The position estimation process is triggered when the vehicle 10 is detected entering a parking facility 60, such as the one shown in Figure 4, where parking information related to memory parking is stored. Alternatively, the position estimation process may be triggered when the distance between the vehicle 10 and the starting point 61 of the parking facility 60 becomes less than or equal to a predetermined distance (for example, 100m). Furthermore, the position estimation process may be triggered when the user activates the memory parking function by pressing, for example, the "parking assistance button". It is assumed that the vehicle 10 is being driven manually by the user.

[0051] If it is determined in step S11 not to start the position estimation process (step S11: No), the vehicle 10 repeats the process of step S11. If it is determined in step S11 to start the position estimation process (step S11: Yes), the vehicle 10 derives the distance from the current position of the vehicle 10 to the starting point 61, for example, based on GPS information (step S12).

[0052] Vehicle 10 sets the parameters for its position estimation process based on the distance derived in step S12 (step S13). These parameters determine the estimation accuracy of the position estimation process and include, for example, camera image quality, camera image range, matching process time and target, and algorithm. The parameters are set according to the distance to the starting point 61, for example, as shown in the change in estimation accuracy described later in Figure 6. Note that increasing the estimation accuracy increases the processing load of the position estimation unit 55, while decreasing the estimation accuracy decreases the processing load of the position estimation unit 55.

[0053] Vehicle 10 starts the position estimation process based on the feature points and map information extracted from external information using the parameters set in step S13 (step S14).

[0054] Next, the vehicle 10 determines whether its driving position has reached the starting point 61 (step S15). For example, the vehicle 10 uses GPS information from the navigation device 18 to determine whether its driving position has reached the starting point 61. Alternatively, the vehicle 10 may determine that it has reached the starting point 61 when the vehicle 10 is stopped by the user and the "parking assist button" that initiates memory parking is pressed.

[0055] If it is determined in step S15 that the starting point 61 has not been reached (step S15: No), the vehicle 10 derives the distance from the current position of the vehicle 10 to the starting point 61, for example, based on GPS information (step S16). The vehicle 10 sets the parameters for the position estimation process based on the distance derived in step S16 (step S17). The vehicle 10 returns to step S15 and performs the position estimation process using the parameters set in step S17.

[0056] On the other hand, if it is determined in step S15 that the vehicle has reached the starting point 61 (step S15: Yes), the vehicle 10 starts memory parking, moving from the starting point 61 to the parking space 62, based on the results of the position estimation process and the parking information stored in the memory unit 54 (step S18).

[0057] Next, the vehicle 10 determines whether or not it has completed parking in the parking space 62 using memory parking (step S19).

[0058] If it is determined in step S19 that parking is not complete (step S19: No), vehicle 10 repeats the process of step S19. If it is determined in step S19 that parking is complete (step S19: Yes), vehicle 10 terminates the position estimation process and memory parking (step S20).

[0059] Furthermore, while memory parking is being performed in steps S18 and S19, the estimation accuracy may be controlled (for example, set to a lower accuracy) according to the surrounding environment and driving conditions of the vehicle 10, or it may be set to a fixed estimation accuracy (for example, the highest accuracy). Also, although the above description assumes that the vehicle 10's movement from entering the parking facility 60 to reaching the starting point 61 is driven by the user's manual driving, it is not limited to this. The vehicle 10's movement may also be automated, for example, where its movement is controlled to reach the starting point 61 based on the results of the position estimation process and the starting point 61.

[0060] <Example 1 of changes in estimation accuracy> Figure 6 shows a first example of the change in estimation accuracy during the position estimation process. The change in estimation accuracy in this example is applied, for example, when performing memory parking at the parking facility 60 shown in Figure 4. In Figure 6, the horizontal axis, time t1, indicates the timing when the position estimation process starts. Time t2 is the timing when the vehicle 10 reaches the starting point 61 of the parking facility 60, and indicates the timing when memory parking starts. Time t3 indicates the timing when the memory parking of the vehicle 10 is completed. The vertical axis indicates the level of estimation accuracy.

[0061] The period T10 from time t1 to t3 is the period during which the vehicle 10's position estimation process is performed. The period T11 from time t1 to t2 is the period during which the user manually drives the vehicle 10 from the time it enters the parking facility 60 until it reaches the starting point 61. The period T12 from time t2 to t3 is the period during which the vehicle 10 is driven from the starting point 61 to the parking space 62 and memory parking is performed based on the results of the position estimation process and the parking information.

[0062] The time t1 at which the position estimation process begins is the timing when it is detected that the vehicle 10 has entered the parking facility 60. Upon entering the parking facility 60, the vehicle 10 begins the position estimation process and gradually increases the estimation accuracy 71 of the position estimation process according to the distance between the vehicle 10 and the starting point 61. In this example, after the start of the position estimation process (time t1), the vehicle 10 increases its estimation accuracy in four stages as the distance from the vehicle 10 to the starting point 61 decreases. In this example, the estimation accuracy is maintained at the highest level after reaching the starting point 61 (time t2), but it may be lowered as appropriate. For example, the estimation accuracy may be increased as the vehicle 10 approaches the starting point 61, reaching the highest level just before reaching the starting point 61, and then lowered after reaching the starting point. By lowering the estimation accuracy, it is possible to reduce the processing load of the position estimation unit 55.

[0063] As described above, the control device of this embodiment controls the estimation accuracy of the position estimation process based on the distance between the starting point 61 and the vehicle 10, increasing the estimation accuracy as the distance decreases. With this configuration, it is possible to accurately estimate the position of the vehicle 10 near the starting point 61. Therefore, it is possible to suppress situations in which memory parking cannot be started along the movement path 63 from the starting point 61 to the parking space 62, and to smoothly start driving the vehicle 10 along the movement path 63. In addition, in sections where the distance to the starting point 61 is not very close, the estimation accuracy of the position estimation process can be controlled to a lower level, thereby reducing the power consumption associated with the position estimation process.

[0064] <Second example of controlling estimation accuracy> Figure 7 shows a second example of controlling the estimation accuracy of the position estimation process. As shown in Figure 7, when the vehicle 10 enters a driveway 83 on private property 82 from a public road 81 and parks the vehicle 10 in a garage 84 on private property 82, control is performed to change the estimation accuracy of the position estimation process. The driveway 83 is an example of a "non-public road" in the present invention.

[0065] The user of vehicle 10 has registered parking space 62 in the garage 84 as a parking space where vehicle 10 can be used for memory parking in the storage unit 54. As shown in Figure 7, parking space 62 is registered in the storage unit 54 as parking information for memory parking, along with the starting point 61 where vehicle 10 begins to move when performing memory parking, and the movement path 63 (dashed arrow) that vehicle 10 travels from the starting point 61 to the parking space 62.

[0066] To register parking information, the user first drives the vehicle 10 manually, entering the driveway 83 of private property 82 from the public road 81 as shown by the solid arrow in Figure 7, and stops the vehicle 10 at a starting point (e.g., starting point 61) that is close to the boundary with the public road 81 (the distance from the boundary is below a threshold). Next, the user starts the registration by pressing a button such as "Start Parking Information Registration" (not shown) to begin the registration of parking information. The user then drives the vehicle 10 manually along the driveway 83 (e.g., travel route 63) and parks the vehicle 10 in the garage 84 (e.g., parking space 62). Finally, the user completes the registration by pressing a button such as "End Parking Information Registration" (not shown) to end the registration of parking information. Note that the parking information may include feature points of external information acquired when driving along the travel route 63.

[0067] <Second example of position estimation processing> Figure 8 is a flowchart illustrating a second example of the position estimation process. This position estimation process is performed as a first modified example of step S17 in the flowchart shown in Figure 5. This position estimation process is also performed when entering private property 82 from a public road 81 as shown in Figure 7 and parking the vehicle 10 in the garage 84.

[0068] The processes from step S11 to step S16 in Figure 5 are performed similarly in this position estimation process. After the vehicle 10 derives the distance from the vehicle 10 to the starting point 61 in step S16, it determines whether the starting point 61 is set near the boundary between the public road 81 and the private road (driveway 83), as shown in Figure 8 (step S17a).

[0069] If it is determined in step S17a that the vehicle is set near the boundary (step S17a: Yes), then the vehicle 10 determines whether or not it is currently traveling on the public road 81 (step S17b).

[0070] Then, in step S17b, if it is determined that the vehicle is traveling on a public road 81 (step S17b: Yes), the vehicle 10 sets the parameters for the position estimation process based on the distance to the starting point 61 derived in step S16 and the first algorithm for changing the estimation accuracy (step S17c). The algorithm referred to here is an algorithm (e.g., a function) that calculates parameters based on the distance to the starting point 61. The first algorithm is an algorithm that provides higher estimation accuracy than the second algorithm, which will be described later. That is, when the distance to the starting point 61 is the same, the first algorithm provides higher estimation accuracy than the second algorithm. However, there may be a distance to the starting point 61 at which the estimated speed is the same for both the first and second algorithms. For example, the cumulative value of the estimation accuracy by the first algorithm over a certain distance to the starting point 61 is higher than the cumulative value of the estimation accuracy by the second algorithm over the same distance. The change in estimation accuracy by the first algorithm according to the distance to the starting point 61 will be described later, for example, in Figure 9. After setting the parameters, vehicle 10 returns to step S15 in Figure 5 and performs position estimation processing using the parameters set in step S17c.

[0071] On the other hand, if it is determined in step S17a that the starting point 61 is not set near the boundary (step S17a: No), or if it is determined in step S17b that the vehicle 10 is not traveling on the public road 81 (step S17b: No), the vehicle 10 sets the parameters for the position estimation process based on the distance to the starting point 61 derived in step S16 and a second algorithm that changes the estimation accuracy (step S17d). For example, the change in estimation accuracy according to the distance to the starting point 61 shown in Figure 6 is due to the second algorithm. After setting the parameters, the vehicle 10 returns to step S15 in Figure 5 and performs the position estimation process using the parameters set in step S17d.

[0072] In this example, the process is described as a first modified example of step S17 in the flowchart shown in Figure 5, but it is not limited to this. For example, the process may be similarly described as a first modified example of step S13 in the flowchart shown in Figure 5. Also, in the above description, the vehicle 10's journey from the public road 81 to the private property 82 and to the starting point 61 of the driveway 83 was described as being driven manually by the user, but it is not limited to this. The vehicle 10's journey may be automated, for example, where its movement is controlled to the starting point 61 based on the results of the position estimation process and the starting point 61.

[0073] <Second example of changes in estimation accuracy> Figure 9 shows a second example of the change in estimation accuracy during the position estimation process. The change in estimation accuracy in this example is applied, for example, when entering private property 82 from a public road 81 as shown in Figure 7 and parking vehicle 10 in garage 84 using memory parking. In this memory parking, the starting point 61 is set near the boundary between public road 81 and driveway 83.

[0074] In the second example in Figure 9, similar to the first example in Figure 6, the horizontal axis, time t1, indicates the timing when the position estimation process begins. Time t2 is when the vehicle 10 reaches the starting point 61 of the parking facility 60, and indicates the timing when memory parking begins. Time t3 indicates when memory parking of the vehicle 10 is completed. The vertical axis indicates the level of estimation accuracy.

[0075] Furthermore, the period T10 from time t1 to t3 is the period during which the vehicle 10's position estimation process is performed. The period T11 from time t1 to t2 is the period during which the user manually drives the vehicle 10 from the public road 81 into private property 82 and reaches the starting point 61 of the driveway 83. The period T12 from time t2 to t3 is the period during which the vehicle 10 is driven from the starting point 61 to the parking space 62 and memory parking is performed based on the results of the position estimation process and parking information.

[0076] However, in this example, a predetermined period before time t2 is set as the "previous section 85" in period T11. This "previous section 85" is, for example, the section shown by the thick solid arrow before the vehicle 10, which is traveling on a public road 81, turns left and enters private property 82, as shown in Figure 7.

[0077] The time t1 at which the position estimation process begins is the timing when the distance between the vehicle 10 traveling on the public road 81 and the starting point 61 on the driveway 83 is detected to be, for example, 100m or less. When the distance to the starting point 61 is 100m or less, the vehicle 10 begins the position estimation process and gradually increases the estimation accuracy 72 of the position estimation process according to the distance between the vehicle 10 and the starting point 61. In this example, after the start of the position estimation process (time t1), the vehicle 10 increases the estimation accuracy in four stages as the distance to the starting point 61 decreases. Since the starting point 61 is set near the boundary between the public road 81 and the driveway 83, the vehicle 10 controls the estimation accuracy when traveling in the section 85 immediately before the starting point 61 (for example, the section of 10m before it) to be higher than the estimation accuracy when traveling in the section before the section 85. In this example, when the vehicle 10 reaches the section 85 immediately before it, it increases the estimation accuracy to the highest level. Furthermore, vehicle 10 is controlled so that the increase in estimation accuracy 72 during the period immediately preceding the preceding section 85 is steep. Note that the estimation accuracy after reaching the starting point 61 (time t2) may be lowered as appropriate. For example, the estimation accuracy for section 85 immediately before reaching the starting point 61 may be set to the highest level, and then lowered after reaching it.

[0078] Thus, when the starting point 61 is set near the boundary between the public road 81 and the driveway 83 within the private property 82, and the vehicle 10 is about to enter the driveway 83 from the public road 81, the control device increases the estimation accuracy of the position estimation process in the section 85 immediately preceding the starting point 61. With this configuration, it is possible to accurately estimate the position of the vehicle 10 near the starting point 61. Therefore, the vehicle 10 can smoothly start traveling along the travel path 63 from the starting point 61, which is set near the boundary, to the parking space 62 in the garage 84. In addition, since the estimation accuracy of the position estimation process can be controlled to be lower when the vehicle 10 is traveling before the section 85 immediately preceding the starting point 61, power consumption associated with the position estimation process can be reduced.

[0079] Furthermore, as described above, the control device increases the accuracy of the position estimation process in the section 85 immediately preceding the starting point 61, and then lowers the estimation accuracy to that of the preceding section 85 depending on the surrounding environment and driving conditions when entering the driveway 83. This allows the vehicle 10 to start moving smoothly along the travel path 63 from the starting point 61 to the parking space 62, and further reduces the power consumption associated with the position estimation process.

[0080] <Third example of position estimation processing> Figure 10 is a flowchart illustrating a third example of the position estimation process. This position estimation process is performed as a second modified example of step S17 in the flowchart shown in Figure 5. This position estimation process is also performed when entering private property 82 from a public road 81 as shown in Figure 7 and parking vehicle 10 in garage 84.

[0081] The processes from step S11 to step S16 in Figure 5 are performed similarly in this position estimation process. After the distance from vehicle 10 to the starting point 61 is derived in step S16, moving objects around vehicle 10 are detected as shown in Figure 10 (step S17A).

[0082] Vehicle 10 determines whether the number of moving objects present around it, as detected in step S17A, is less than a first predetermined value (step S17B).

[0083] In step S17B, if the number of moving objects is less than a first predetermined value (step S17b: Yes), the vehicle 10 sets the parameters for the position estimation process based on the distance to the starting point 61 derived in step S16 and the third algorithm (step S17C). The third algorithm is an algorithm that has lower estimation accuracy than the fourth algorithm described later. That is, if there are few moving objects around the vehicle 10, the position estimation process is performed with relatively low estimation accuracy.

[0084] In step S17B, if the number of moving objects is equal to or greater than a first predetermined value (step S17b: No), the vehicle 10 determines whether the number of moving objects in the vicinity of the vehicle 10 is equal to or greater than a second predetermined value (step S17D). However, the second predetermined value is a value greater than the first predetermined value.

[0085] In step S17D, if the number of moving objects is less than the second predetermined value (step S17b: No), the vehicle 10 sets the parameters for the position estimation process based on the distance to the starting point 61 derived in step S16 and the estimation accuracy of the fourth algorithm (step S17E). The fourth algorithm is an algorithm that provides higher estimation accuracy than the third algorithm. For example, the cumulative value of the estimation accuracy by the fourth algorithm over a certain distance to the starting point 61 is higher than the cumulative value of the estimation accuracy by the fifth algorithm over the same distance. In other words, when there are many moving objects around the vehicle 10, the position estimation process is performed with relatively high estimation accuracy.

[0086] In step S17D, if the number of moving objects is greater than or equal to the second predetermined value (step S17D: Yes), the vehicle 10 sets the parameters for the position estimation process based on the distance to the starting point 61 derived in step S16 and the estimation accuracy of the fifth algorithm (step S17F). The fifth algorithm is an algorithm that has lower estimation accuracy than the fourth algorithm. The fifth algorithm may have the same estimation accuracy as the third algorithm, for example, or it may have lower estimation accuracy (minimum estimation accuracy) than the third algorithm. In other words, if there are too many moving objects around the vehicle 10, the vehicle 10 performs the position estimation process with relatively low estimation accuracy. Alternatively, the vehicle 10 may stop the position estimation process until the number of moving objects falls below the second predetermined value, and refrain from memory parking during that period.

[0087] The level of estimation accuracy achieved by each algorithm depends on the distance to the starting point 61, but it is the level of accuracy when compared, for example, at the same distance. However, it is not necessary to have a difference in estimation accuracy for all distances to the starting point 61. This method of controlling estimation accuracy is also used in the process explained in Figure 8.

[0088] In this example, we have described a second modified example of step S17 in the flowchart shown in Figure 5, but this is not limited to this example. For example, the process may be similarly performed as a second modified example of step S13 in the flowchart shown in Figure 5.

[0089] In this way, the control device lowers the estimation accuracy of the position estimation process when the number of moving objects detected around the vehicle 10 is small (less than the first predetermined number), and increases the estimation accuracy of the position estimation process when the number of moving objects is sufficiently large (greater than or equal to the first predetermined number). With this configuration, the position of the vehicle 10 near the starting point 61 can be accurately estimated, and the vehicle 10 can be smoothly started to travel along the travel path 63 from the starting point 61, which is set near the boundary between the public road 81 and the driveway 83, while paying attention to moving objects.

[0090] The control method described in the above-mentioned embodiment can be implemented by executing a pre-prepared control program on a computer. This control program is recorded on a computer-readable storage medium and executed when read from the storage medium. This control program may also be provided in the form of a non-transient storage medium such as flash memory, or it may be provided via a network such as the Internet. The computer that executes this control program may be included in the control device, included in an electronic device such as a smartphone, tablet terminal, or personal computer that can communicate with the control device, or included in a server device that can communicate with these control devices and electronic devices.

[0091] Although embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, and modifications, improvements, etc., can be made as appropriate.

[0092] In the above embodiment, an example of a four-wheeled automobile was described, but the invention is not limited to this. For example, it may be a two-wheeled vehicle, a Segway, or other vehicle. Furthermore, the concept of the present invention is not limited to vehicles, but can also be applied to robots, ships, aircraft, etc., that are equipped with a drive source and are movable by the power of the drive source.

[0093] Furthermore, this specification includes at least the following information. Note that the components etc. in parentheses indicate those corresponding to the embodiments described above, but are not limited thereto.

[0094] (1) A control device for a mobile body (vehicle 10), A storage unit (storage unit 54) that stores parking information indicating the starting point of the moving body (starting point 61), the parking space for the moving body (parking space 62), and the movement path of the moving body from the starting point to the parking space (movement path 63), A position estimation unit (position estimation unit 55) performs position estimation processing including acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. The system includes a movement control unit (movement control unit 56) that performs movement control to move the moving body from the starting point to the parking space based on the results of the position estimation process and the parking information, The position estimation unit controls the estimation accuracy of the position estimation process based on the distance between the starting point of movement and the moving object. Control device (control ECU20).

[0095] According to (1), by controlling the estimation accuracy of the position estimation process based on the distance between the starting point and the moving object, it is possible to reduce power consumption associated with the position estimation process while suppressing the decrease in convenience caused by the inability to accurately estimate the position of the starting point.

[0096] (2) The control device described in (1), The position estimation unit performs control to increase the estimation accuracy as the distance decreases. Control device.

[0097] As shown in (2), the shorter the distance between the starting point and the moving object, the higher the estimation accuracy of the position estimation process. This allows for accurate estimation of the starting point's position and smoother control of the movement of the moving object starting from that point.

[0098] (3) A control device as described in (1) or (2), The position estimation unit, when a predetermined condition relating to the starting point of movement is met, increases the estimation accuracy during the period when the moving object is traveling in the section immediately preceding the starting point of movement compared to when the predetermined condition is not met. Control device.

[0099] According to (3), when the estimation accuracy of the position estimation process during the period when traveling in the section immediately preceding the starting point of movement is increased, the power consumption associated with the position estimation process can be reduced by setting certain conditions.

[0100] (4) The control device described in (3), The aforementioned predetermined conditions include the fact that the starting point of the movement is set near the boundary between a public road and a non-public road. Control device.

[0101] As described in (4), a preferred condition for increasing estimation accuracy is that the starting point of movement is set near the boundary between a public road and a non-public road.

[0102] (5) The control device described in (4), The predetermined conditions include the fact that the starting point of the movement is set near the boundary, and that the moving body is traveling on the public road. Control device.

[0103] As described in (5), it is preferable that the conditions for increasing estimation accuracy include the situation in which the moving object is traveling on an ordinary road and is about to enter a non-ordinary road.

[0104] (6) The control device described in (5), The position estimation unit, when the predetermined conditions are met, sets the estimation accuracy for the immediately preceding section to a predetermined accuracy, and when the moving object enters the non-public road, it makes the estimation accuracy variable. Control device.

[0105] As shown in (6), by setting the estimation accuracy for the immediately preceding section to a predetermined accuracy and making the estimation accuracy after entering a non-public road variable, the power consumption associated with the position estimation process can be further reduced.

[0106] (7) A control device according to any one of (1) to (6), The system includes a motion detection unit (motion detection unit 57) that detects moving objects around the moving object based on the external information, The position estimation unit controls the estimation accuracy based on the number of detected moving objects. Control device.

[0107] According to (7), the power consumption associated with the position estimation process can be reduced by controlling the estimation accuracy of the position estimation process based on the number of moving objects detected around the moving object.

[0108] (8) The control device described in (7), The position estimation unit performs control to increase the estimation accuracy when the number of moving bodies is greater than or equal to a first predetermined number, compared to when the number of moving bodies is less than the first predetermined number. Control device.

[0109] As in (8), when there are many moving objects detected around the moving object, it is preferable to increase the estimation accuracy of the position estimation process compared to when there are few moving objects.

[0110] (9) The control device described in (8), If the number of moving bodies is greater than or equal to a second predetermined number (which is greater than the first predetermined number), the position estimation unit performs control to lower the estimation accuracy compared to when the number of moving bodies is greater than or equal to the first predetermined number but less than the second predetermined number. Control device.

[0111] As in (9), if the number of moving objects detected around the moving object is too large, it is preferable not to increase the estimation accuracy of the position estimation process.

[0112] (10) A control method using a control device for a mobile body, The control device, The system stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space. A position estimation process is performed which includes acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. Based on the results of the position estimation process and the parking information, movement control is performed to move the moving body from the starting point to the parking space. The estimation accuracy of the position estimation process is controlled based on the distance between the starting point of movement and the moving object. Control method.

[0113] According to (10), by controlling the estimation accuracy of the position estimation process based on the distance between the starting point and the moving object, it is possible to reduce power consumption associated with the position estimation process while suppressing the decrease in convenience caused by the inability to accurately estimate the position of the starting point.

[0114] (11) A control program for a mobile device, The processor of the control device, The system stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space. A position estimation process is performed which includes acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. Based on the results of the position estimation process and the parking information, movement control is performed to move the moving body from the starting point to the parking space. The estimation accuracy of the position estimation process is controlled based on the distance between the starting point of movement and the moving object. A control program that executes a process.

[0115] According to (11), by controlling the estimation accuracy of the position estimation process based on the distance between the starting point and the moving object, it is possible to reduce power consumption associated with the position estimation process while suppressing the decrease in convenience caused by the inability to accurately estimate the position of the starting point. [Explanation of Symbols]

[0116] 10. Vehicles (mobile devices) 20 Control ECU (Control Unit) 54 Storage section 55 Position estimation part 56 Movement Control Unit 57 Motion detection unit 61 Starting point 62 parking spaces 63 Travel Routes

Claims

1. A control device for a mobile body, A storage unit that stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space, A position estimation unit performs position estimation processing including acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. The system includes a movement control unit that performs movement control to move the moving body from the starting point to the parking space based on the results of the position estimation process and the parking information, The position estimation unit controls the estimation accuracy of the position estimation process based on the distance between the starting point of movement and the moving object. Control device.

2. A control device according to claim 1, The position estimation unit performs control to increase the estimation accuracy as the distance decreases. Control device.

3. A control device according to claim 1, The position estimation unit, when certain conditions relating to the starting point of movement are met, increases the estimation accuracy during the period when the moving object is traveling in the section immediately preceding the starting point of movement compared to when the predetermined conditions are not met. Control device.

4. A control device according to claim 3, The aforementioned predetermined conditions include the fact that the starting point of the movement is set near the boundary between a public road and a non-public road. Control device.

5. A control device according to claim 4, The predetermined conditions include the fact that the starting point of the movement is set near the boundary, and that the moving body is traveling on the public road. Control device.

6. A control device according to claim 5, The position estimation unit, when the predetermined conditions are met, sets the estimation accuracy for the immediately preceding section to a predetermined accuracy, and when the moving object enters the non-public road, it makes the estimation accuracy variable. Control device.

7. A control device according to any one of claims 1 to 6, The system includes a motion detection unit that detects moving objects around the moving object based on the external information, The position estimation unit controls the estimation accuracy based on the number of detected moving objects. Control device.

8. A control device according to claim 7, The position estimation unit performs control to increase the estimation accuracy when the number of moving bodies is greater than or equal to a first predetermined number, compared to when the number of moving bodies is less than the first predetermined number. Control device.

9. A control device according to claim 8, The position estimation unit, when the number of moving bodies is greater than or equal to a second predetermined number (which is greater than or equal to the first predetermined number), performs control to lower the estimation accuracy compared to when the number of moving bodies is greater than or equal to the first predetermined number but less than the second predetermined number. Control device.

10. A control method using a control device for a mobile object, The control device, The system stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space. A position estimation process is performed which includes acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. Based on the results of the position estimation process and the parking information, movement control is performed to move the moving body from the starting point to the parking space. The estimation accuracy of the position estimation process is controlled based on the distance between the starting point of movement and the moving object. Control method.

11. A control program for a mobile device, The processor of the control device, The system stores parking information indicating the starting point of the moving body, the parking space for the moving body, and the movement path of the moving body from the starting point to the parking space. A position estimation process is performed which includes acquiring external information of the moving object, extracting feature points from the external information, and estimating the position of the moving object based on the feature points and map information. Based on the results of the position estimation process and the parking information, movement control is performed to move the moving body from the starting point to the parking space. The estimation accuracy of the position estimation process is controlled based on the distance between the starting point of movement and the moving object. A control program that executes a process.

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