Vehicle door control device

Abstract

The invention provides a vehicle door control device capable of determining a door that a user wants to open based on a plurality of conditions and controlling the door. A vehicle door control device (1) calculates use intention values (V1-V4) indicating the possibility (S4) that a user (43) present in the vicinity of a vehicle (2) uses the vehicle (2) for each of a plurality of conditions (1)-(4) having different calculation source objects. On the basis of the calculated use intention values (V1-V4), the vehicle door control device (1) estimates a target door expected to be opened by a user (43) among the doors of the vehicle (2) (S6). The vehicle door control device (1) executes control for unlocking and opening the estimated target door (S7).

Description

Technical Field

[0001] This invention relates to a vehicle door control device for controlling the doors of a vehicle. Background Technology

[0002] Patent Document 1 describes a vehicle that determines the actions of a user located at the rear of the vehicle and unlocks the tailgate based on the determination result. The vehicle control device in Patent Document 1 uses a camera mounted on the vehicle to capture images of the user at the rear of the vehicle and detects the user's actions relative to a predetermined horizontal plane based on the captured images. The control device unlocks the tailgate when it detects an action that involves moving the user's right foot to the right from a stationary position with both feet and knees, and then returning the right foot to its original position.

[0003] Existing technical documents

[0004] Patent documents

[0005] Patent Document 1: Japanese Patent Application Publication No. 2022-134315 ( Figure 3 )

[0006] The control device in Patent Document 1 requires the user to perform the aforementioned actions to unlock the vehicle's tailgate. Therefore, the user needs to perform the determined actions with high precision to unlock the vehicle. Furthermore, vehicle doors come in various types, such as swing doors and sliding doors, but the user's position before opening the door and the user's orientation relative to the vehicle differ depending on the type of door and the direction of opening. Therefore, if the decision to open the vehicle door is based solely on specific conditions, usability may be reduced. Summary of the Invention

[0007] The present invention was made to eliminate the aforementioned problems, and its purpose is to provide a vehicle door control device that can determine the door that a user wants to open based on multiple conditions and control the door.

[0008] To achieve the aforementioned objective, the vehicle door control device according to the present invention comprises: a usage intention value calculation unit that calculates a usage intention value for each of a plurality of conditions different from the calculation source object, the usage intention value representing the likelihood that a user existing in the vicinity of the vehicle will use the vehicle; an object door estimation unit that estimates an object door based on the usage intention value calculated by the usage intention value calculation unit, the object door being a door among the doors of the vehicle that is intended to be opened by the user; and a control unit that performs control on the object door estimated by the object door estimation unit for opening the door.

[0009] Furthermore, the calculation source object in this specification refers to an object that can be used to calculate the intended use value, such as vehicle-related objects like parking facilities, and user-related objects like the user's movement route. Additionally, the calculation source object refers to an object whose intended use value is increased or decreased based on its type and value, thus altering the predicted door. In other words, the calculation source object is an object that can be used to predict the door intended to be opened for the user based on the intended use value. Furthermore, the calculation in this specification includes not only processing to calculate values ​​using formulas, but also processing to determine and set a suitable setting value from a set of pre-set values. Finally, the control for opening the door in this specification includes the concepts of controlling the door to unlock, controlling the door to open, or controlling both.

[0010] According to the vehicle door control device of the present invention having the aforementioned structure, a usage intention value is calculated for each of a plurality of conditions different for the calculation source object, and control for opening the door is executed on the object door estimated based on the calculated usage intention value. Thus, it is possible to determine the object door that the user wants to open based on a plurality of different conditions and control that object door. In the process of determining the door that the user wants to open, it is possible to suppress cases limited to specific conditions and to estimate the object door from multiple perspectives, thereby improving the estimation accuracy of the object door and enhancing usability. Attached Figure Description

[0011] Figure 1 This is a schematic diagram of the vehicle according to the first embodiment.

[0012] Figure 2 This is a block diagram illustrating the structure of the vehicle door control device according to the first embodiment.

[0013] Figure 3 This is a flowchart of the gate control processing procedure involved in the first embodiment.

[0014] Figure 4 This is a diagram illustrating the process from calculating the intended use value according to the first embodiment to determining the threshold.

[0015] Figure 5 This is a diagram illustrating an example of the vehicle parking state and the user's movement path according to the first embodiment.

[0016] Figure 6 This is a flowchart of the gate control processing procedure involved in the second embodiment.

[0017] Figure 7 This is a flowchart of the gate control processing procedure involved in the second embodiment.

[0018] Figure 8This is a diagram illustrating an example of the vehicle parking status and the user's movement path according to the second embodiment.

[0019] Symbol Explanation

[0020] 1. Vehicle door control device; 2. Vehicle (2A); 10. Vehicle control ECU (user intent value calculation unit, target door estimation unit, control unit, obstacle detection unit); 12R, 12L front door; 13R, 13L rear door; 14. Tail door; 31A. User intent value calculation unit; 31B. Target door estimation unit; 31C. Control unit; 31D. Obstacle detection unit; 43, 43A. User; 48, 48A. Obstacle; 51, 52, 51A. Movement path; A1~A4. Weighting coefficients; TH threshold; V, V1~V4. User intent value. Detailed Implementation

[0021] (First Implementation)

[0022] The following is a reference to the appendix. Figure 1 The first embodiment will be described in detail below, which is a specific embodiment of the vehicle door control device according to the present invention. First, a vehicle 2 equipped with the vehicle door control device 1 according to the first embodiment will be described below. Figure 1 This is a schematic diagram of the vehicle 2 according to the first embodiment. Figure 2 This is a block diagram of the vehicle door control device 1 according to the first embodiment. Furthermore, in the following description, the forward / backward direction, the left / right direction, and the up / down direction of the vehicle 2 will be simply referred to as the forward / backward direction, the left / right direction, and the up / down direction, respectively. Additionally, sometimes the symbol R is used to denote devices located on the right side of the vehicle 2, and the symbol L is used to denote devices located on the left side of the vehicle 2. Furthermore, the vehicle 2, in addition to... Figure 1 and Figure 2 In addition to the constituent elements shown, it also has the basic constituent elements of vehicle 2, but in the following description, the structure related to the control of opening and closing the door and the control related to the structure will be mainly described.

[0023] like Figure 1As shown, vehicle 2 is, for example, a vehicle with a steering wheel 3 on the right side, and includes a body 11, a front door 12R on the driver's side, a front door 12L on the passenger side, a rear door 13R on the driver's side, a rear door 13L on the passenger side, and a tailgate 14. Hereinafter, when describing the front doors 12R and 12L, the rear doors 13R and 13L, and the tailgate 14 collectively, they are sometimes referred to as individual doors. Each door is, for example, a swing-type door. Furthermore, vehicle 2 has door locking devices 15A, 15B, 15C, 15D, and 15E for controlling the locking of each door, and door opening and closing devices 16A, 16B, 16C, 16D, and 16E for opening and closing each door. Door locking devices 15A to 15E sequentially control the locking of the front doors 12R and 12L, the rear doors 13R and 13L, and the tailgate 14. Door lock devices 15A to 15E are devices that switch between the locked state and the unlocked state of each door. Door opening and closing devices 16A to 16E are devices that sequentially open and close the front doors 12R and 12L, the rear doors 13R and 13L, and the tail door 14. Door opening and closing devices 16A to 16E may include an electric motor as a drive source, and the doors are opened and closed by driving the electric motor.

[0024] also, Figure 1 The structure of vehicle 2 shown is an example. For example, vehicle 2 is not limited to a vehicle with a steering wheel 3 on the right side, but can also be a vehicle with a steering wheel 3 on the left side. Furthermore, the doors are not limited to swing doors; sliding doors or other opening and closing methods can be used. Additionally, the opening and closing methods of each door can be different. Therefore, it is also possible for only the rear doors 13R and 13L to be sliding doors. Furthermore, the drive source for the door opening and closing devices 16A to 16E is not limited to an electric motor; it can also be a hydraulic cylinder or other drive source. Furthermore, vehicle 2 can be an internal combustion engine vehicle driven by an internal combustion engine (engine, etc.), an electric vehicle driven by an electric motor, a fuel cell vehicle, or a hybrid vehicle with multiple drive sources. Furthermore, there are no particular limitations on the type of vehicle 2, the number of wheels, etc. Furthermore, vehicle 2 can be a vehicle capable of manual driving, a vehicle capable of automatic driving, or a vehicle capable of switching between these two driving methods.

[0025] In addition, such as Figure 1 and Figure 2 As shown, the vehicle door control device 1 includes a front camera 5, side cameras 6R and 6L, a rear camera 7, various sensors 8, a wireless communication device 9, a vehicle control ECU (electronic control unit) 10, and a location information acquisition device 17. Hereinafter, when referring to the front camera 5, side cameras 6R and 6L, and rear camera 7 collectively, they may be referred to as individual cameras.

[0026] Each camera is a camera device with a solid-state imaging element such as a CCD, which captures images of the area around the vehicle. The front camera 5 is mounted, for example, above the front bumper of the vehicle 2 or on the back of the rearview mirror, with its optical axis facing forward of the vehicle 2. The side cameras 6R and 6L are mounted, for example, on the left and right rearview mirrors of the vehicle 2, with their optical axes facing to the sides of the vehicle 2. The rear camera 7 is mounted, for example, above the license plate mounted at the rear of the vehicle 2, with its optical axis facing backward of the vehicle 2.

[0027] Various sensors 8 are sensors used to realize various functions of vehicle 2. As sensors 8, ultrasonic sensors, millimeter-wave radar, laser sensors, etc. can be used as sensors for detecting obstacles around the vehicle. Alternatively, vehicle speed sensors, acceleration sensors, gyroscope sensors, steering sensors, shift position sensors, etc. can be used as sensors for driving vehicle 2.

[0028] The wireless communication device 9 is a device that performs wireless communication with the portable device 41. The portable device 41 is, for example, a so-called electronic key. Alternatively, the portable device 41 can be a smartphone for a digital key system, or other communication terminal capable of wireless communication with the vehicle 2. The portable device 41 has buttons for activating the door lock devices 15A-15E and the door opening and closing devices 16A-16E.

[0029] The location information acquisition device 17 includes, for example, a receiver that receives radio waves from GPS (Global Positioning System) satellites. The location information acquisition device 17 acquires the location information of the vehicle 2 based on the radio waves received at predetermined intervals. The vehicle control ECU 10 can detect the current position and speed of the vehicle 2 based on the location information from the location information acquisition device 17. Furthermore, the vehicle control ECU 10 can also acquire the location information of the vehicle 2 from other devices such as a car navigation system.

[0030] (Regarding vehicle control ECU10)

[0031] The vehicle control ECU (hereinafter referred to as ECU) 10 is an electronic control unit that performs comprehensive control of the entire vehicle 2, including the vehicle door control device 1. In addition to a CPU 31 that serves as a computing and control device, and a RAM 32 that serves as working memory when the CPU 31 performs various calculations and processing, as well as a control program, it also has a door control processing program recorded thereafter (see [reference]). Figure 3 Internal storage devices such as ROM 33, flash memory 34 storing programs and flag values ​​read from ROM 33, etc.

[0032] The ECU 10 implements various functional units by executing programs through the CPU 31. For example, the usage intention value calculation unit 31A is a functional unit that calculates a usage intention value representing the likelihood of a user using the vehicle for each of multiple conditions different from the calculation source object. The object door estimation unit 31B is a functional unit that estimates the object door among the doors of the vehicle that is expected to be opened by the user based on the usage intention value calculated by the usage intention value calculation unit 31A. The control unit 31C is a functional unit that performs control for opening the object door estimated by the object door estimation unit 31B. The obstacle detection unit 31D is a functional unit that detects obstacles existing in the vicinity of the vehicle. That is, the vehicle control ECU 10 is an example of the usage intention value calculation unit, object door estimation unit, control unit, and obstacle detection unit in this specification.

[0033] Additionally, the flash memory 34 stores calculation information DB35. The calculation information DB35 stores information required for the intention value calculation unit 31A to calculate the intention value, and stores values ​​for each of the multiple conditions. Furthermore, the calculation information DB35 stores weighting coefficients for multiplying the intention value calculated by the intention value calculation unit 31A for each of the multiple conditions. Additionally, the calculation information DB35 stores weighting coefficients for, for example, the state of each user, as described later. Furthermore, the flash memory 34 stores facility flag value 36. Facility flag value 36 is a flag value used to determine whether a facility where vehicle 2 is parked is a facility whose target door is estimated based on the intention value.

[0034] Furthermore, the ECU 10 is connected via a vehicle network such as CAN to the aforementioned door lock devices 15A-15E, door opening and closing devices 16A-16E, various cameras (such as the front camera 5), ​​various sensors 8, wireless communication device 9, and location information acquisition device 17. The ECU 10 performs various calculations based on information input from each camera and sensor 8 to control the vehicle 2. For example, the ECU 10 displays a bird's-eye view or overhead view on the monitor (not shown) of the vehicle 2 based on the video data captured by each camera, thus providing driving assistance.

[0035] Furthermore, the ECU 10 drives the door lock devices 15A-15E and the door opening and closing devices 16A-16E to control the locking (key) and opening / closing of each door. Additionally, the ECU 10 communicates wirelessly with the portable device 41 via the wireless communication device 9, and performs key authentication, unlocking of each door, and door opening / closing based on buttons operated on the portable device 41. Alternatively, key authentication and door locking can also be performed by a device other than the ECU 10, such as the wireless communication device 9.

[0036] (Regarding door control processing procedures)

[0037] Next, based on Figure 3 The door control processing procedure executed by ECU10 in the vehicle door control device 1 having the above structure will be described. Figure 3 This is a flowchart of the door control processing procedure according to the first embodiment. Here, when the ECU 10 detects a radio wave from the portable device 41, for example, when the engine of the vehicle 2 is stopped and all doors are locked, the ECU 10 starts the door control processing procedure. The door control processing procedure is as follows: for each of a plurality of conditions different from the calculation source object, a usage intention value (hereinafter referred to as usage intention value V) representing the possibility (probability) of the user using the vehicle is calculated, and based on the calculated usage intention value V, a door that is expected to be opened for the user (hereinafter referred to as the target door) is estimated, and control for opening the estimated target door is executed. In the following description, the case where the control of unlocking and opening the target door is executed as the control for opening the door will be described.

[0038] Furthermore, the calculation source object will be described later in S4. Additionally, the "control for opening doors" in this specification can also refer to the control for unlocking or opening each door. Therefore, ECU10 can also be described later. Figure 3 In S7, only the control to unlock the target door is executed. Furthermore, the conditions for starting the door control program are not limited to the conditions mentioned above. ECU10 can also execute the program while the engine of vehicle 2 is running and the portable device 41 is inside the vehicle. Figure 3 For example, ECU10 can also detect when a user without the portable device 41 approaches a predetermined distance from vehicle 2 after the engine of vehicle 2 has started and all doors of vehicle 2 are locked, and then start processing the request from that user. Figure 3 Alternatively, ECU10 can also execute the following when the engine of vehicle 2 is stopped and all doors are locked, provided that the door locks have been released via portable device 41. Figure 3 The processing. In this case, ECU10 can control the opening of the object door, which has been unlocked, if the user intends to use vehicle 2. That is, as referred to as "control for opening the door" in this specification, it can also only control the opening of the object door. In addition, the meaning of using the vehicle in this specification is not limited to opening each door to ride in the vehicle, but also includes opening the door to load luggage, unloading luggage, etc., and other situations where the doors are opened but not used for work. Therefore, the vehicle door in this specification includes the tailgate 14. In addition, the following Figure 3The program shown in the flowchart is stored in RAM32 or ROM33 of the vehicle door control device 1 and is executed by CPU31.

[0039] First of all, Figure 3 In step S1 (hereinafter referred to as S2), the CPU 31 determines whether the facility where the vehicle 2 is parked is the object facility for the subsequent steps S2 (hereinafter referred to as the object facility), that is, whether it is the object facility for performing the calculation of the usage intention value V, the estimation of the object door, and the control of the estimated object door. In S1, the CPU 31 determines whether the parked facility is the object facility based on the facility flag value 36 stored in the flash memory 34.

[0040] For example, CPU 31 pre-stores facility flag value 36 based on the location information of the last time vehicle 2 was parked. When parking, when the engine of vehicle 2 stops and the auxiliary power is disconnected, CPU 31 obtains location information from location information acquisition device 17, and detects facilities for parking vehicle 2 based on the obtained location information and map information. This map information may be information obtained from the car navigation system installed in vehicle 2, information stored in ROM 33, or information obtained from an external server, etc.

[0041] For example, depending on the user, if vehicle 2 is parked at their own home, they will likely walk around the vicinity of vehicle 2 even when not in use. Therefore, for their own home, as... Figure 3 Besides the objects processed by the door control, there may be situations where the door needs to be opened manually (using an electronic key, etc.). Alternatively, depending on the user, there may be situations where specific facilities such as a work destination or hospital are excluded from the door control processing. Therefore, CPU 31 receives information about facilities excluded from the door control processing. The method for receiving information about facilities excluded from the door control processing is not particularly limited; it can be done using a car navigation system or another user interface of the vehicle 2.

[0042] When the engine of vehicle 2 stops during parking, CPU 31 determines whether the facility where vehicle 2 is parked is an external facility, i.e., whether the parking facility is an external facility. For example, if the parking facility is an external facility, CPU 31 stores a value of "1" in facility flag value 36; if the parking facility is an external facility, it stores a value of "0" in facility flag value 36. Furthermore, CPU 31 starts... Figure 3 After processing, in S1, the facility flag value 36 stored during the last parking is checked to determine whether the parking facility is an object facility.

[0043] If the facility flag value 36 is "1", CPU31 determines that the parking facility is the target facility (S1: Yes) and executes S2. Conversely, if the facility flag value 36 is "0", CPU31 determines that the parking facility is an untargeted facility (S1: No) and terminates the process. Figure 3 The process is shown below. Therefore, it is possible to register external facilities according to user requirements, improving availability. In this case, no further processing is required until vehicle 2 moves and the parking facility is changed. Figure 3 Therefore, CPU31 may not execute the processing until the conditions for changes in current location, updates to facility flag value 36, changes to registered facilities, engine start-up, etc., are met. Figure 3 The processing.

[0044] In S2, CPU 31 determines whether the user has approached below a predetermined threshold distance Lth from vehicle 2. During the period when the user has not approached the threshold distance Lth, i.e., the distance between vehicle 2 and the user holding the portable device 41 is longer than the threshold distance Lth, CPU 31 makes a negative judgment in S2 (S2: No), and repeats the judgment process of S2. Furthermore, when CPU 31 detects that the user has approached below the threshold distance Lth (S2: Yes), CPU 31 executes S3, activating each camera (front camera 5, side cameras 6R and 6L, and rear camera 7). For example, during the period until S3 is executed, CPU 31 stops supplying power to each camera, setting each camera to a stopped state. Then, in S3, CPU 31 starts supplying power to each camera, enabling them to record and acquiring video data from each camera.

[0045] Furthermore, the threshold distance Lth is, for example, several meters. As described later, after the user approaches below the threshold distance Lth (S2: Yes), the CPU 31 calculates the user intent value V based on the video data of each camera after activation, and estimates the target door based on the calculated user intent value V and executes the opening control. Therefore, the threshold distance Lth is preferably a distance such as 5m to 3m, which ensures the time required for calculation or estimation, and the time during which the user approaching the vehicle 2 does not intrude into the swing range of the target door. In addition, as a method for determining whether the user has approached below the threshold distance (Lth) from the vehicle 2, a method based on the location information of the portable device 41 can be used, for example. For example, the location of the portable device 41 (user) can be detected by triangulation based on the distance between the multiple wireless antennas of the wireless communication device 9 and the portable device 41. Alternatively, the location of the portable device 41 can be detected based on the location information of the smartphone in the digital key system. Alternatively, the location of the user can be detected using a millimeter-wave radar mounted on the vehicle 2. In addition, the CPU 31 can also limit the cameras activated based on the user's location. For example, if the user is in front of vehicle 2, the rear camera 7 may not need to be activated. Alternatively, the camera that activates based on the user's position can be changed to save power.

[0046] After executing S3, CPU31 executes S4, which calculates the intended value V for each of the multiple conditions that are different for the computation source object. Figure 4 This describes the process from calculating the intended value V to making a judgment based on the threshold TH. For example... Figure 3 and Figure 4 As shown, in the first embodiment, the use of conditions 1 to 4 will be described as an example. In the following description, the usage intention values ​​V of conditions 1 to 4 will be recorded in that order as usage intention values ​​V1 to V4, and when usage intention values ​​V1 to V4 are collectively referred to as usage intention value V. Furthermore, as... Figure 4 As shown, CPU 31 calculates usage intention values ​​V1 to V4 for conditions 1 to 4 at a rate of, for example, 0% to 100%. CPU 31 calculates usage intention values ​​V1 to V4 for each of the multiple conditions for each door. Furthermore, CPU 31 determines whether the movement path is restricted based on information about obstacles around the vehicle, and if restricted, changes (adjusts) the calculation method for usage intention values ​​V1 to V4 under each condition. First, the case where there are no restrictions on the movement path caused by obstacles will be explained. Furthermore, the number of multiple conditions in this specification is not limited to four; it can also be two, three, or five or more.

[0047] (Condition 1: Combination of facilities and carry-on luggage)

[0048] First, let's explain condition 1. In the calculation of the usage intention value V1 based on condition 1, the information of the "facilities" where the parked vehicle 2 is located and the information of the "personal belongings" carried by the user are used as the calculation source objects. The usage intention value V1 is calculated based on the combination of these two pieces of information. The facility information can be obtained, for example, from the location information acquisition device 17 or map information from a car navigation system. The personal belongings information can be obtained, for example, from video data of the user captured by various cameras. In addition, the personal belongings information can also be obtained from information other than cameras, such as point cloud data from millimeter-wave radar.

[0049] For example, in the case of an airport as the facility and a suitcase as carry-on luggage, there is a high probability that a user will return from a trip to vehicle 2 parked in the airport parking lot and use vehicle 2. Therefore, in such a case, CPU 31 increases the usage intention value V1 calculated in condition 1. On the other hand, for example, if the facility is one's own home and there is no carry-on luggage, there is also a possibility that the user will continuously move around vehicle 2 parked in their own home parking lot for purposes other than taking a ride, and the probability of use may not be high. Therefore, in such a case, CPU 31 decreases the usage intention value V1 calculated in condition 1.

[0050] Additionally, if the carry-on luggage is the size of a handbag, user 43 is more likely to open the back door 14 or the rear doors 13R and 13L. Furthermore, if the carry-on luggage is the size of a suitcase, user 43 is more likely to open the back door 14. Therefore, CPU 31 can, for example, increase the user intent value V1 in the order of front doors 12R and 12L, rear doors 13R and 13L, and back door 14 as the size of the carry-on luggage increases.

[0051] The calculation information DB35 contains usage intention values ​​V1 for each combination of facilities, luggage types, and door types. The CPU31 can set the usage intention value V1 for each door by retrieving combinations from the calculation information DB35 that match the detected facility and carry-on luggage information. Furthermore, correction coefficients for adjusting the usage intention value V1 based on factors such as the size and quantity of carry-on luggage can be set in the calculation information DB35. The CPU31 can then adjust the usage intention value V1 for condition 1 based on these correction coefficients. For example, the larger the carry-on luggage, the higher the likelihood of the user using vehicle 2. Therefore, the CPU31 can perform the following correction: the larger the carry-on luggage, the larger the usage intention value V1 for each door is multiplied by the correction coefficient. Additionally, the more carry-on luggage, the higher the likelihood of the user using vehicle 2. Therefore, the CPU31 can perform a correction that increases the usage intention value V1 the more carry-on luggage. Furthermore, for other conditions 2 to 4, the required correction coefficients can be set in the calculation information DB35 in the same way as for condition 1.

[0052] Furthermore, the combination of condition 1 above is just one example; the relationship between the facility and personal belongings can be appropriately changed. For instance, if the facility is one's own home and the personal belongings are a tote bag, there is a possibility that the user will use a bicycle or other means of transportation other than vehicle 2 to go shopping and return home, and the probability of using vehicle 2 is not necessarily high. Therefore, in the case of such a combination, CPU 31 can decrease the usage intention value V1. On the other hand, if the facility is a shopping mall and the personal belongings are a tote bag, there is a possibility that the user will return to vehicle 2 after completing shopping, and the probability of using vehicle 2 is high. Therefore, in the case of such a combination, CPU 31 can increase the usage intention value V1. In this way, in condition 1, user scenarios can be envisioned and verified based on various facilities and types of personal belongings, and a method for calculating the usage intention value V1 can be set.

[0053] (Condition 2: Combination of movement path and speed change)

[0054] Next, condition 2 will be explained. Furthermore, in the following explanations of conditions 2 through 4, content identical to that in condition 1 will be omitted as appropriate. In the calculation of the user intent value V2 based on condition 2, the information on the user's "movement route" towards vehicle 2 and the information on the user's "speed change" are used as the calculation source objects. The user intent value V2 is calculated based on the combination of these two pieces of information. The information on the movement route and speed change can be obtained from the video data of each camera.

[0055] For example, if a user moves towards vehicle 2 in a straight line and their speed decreases sharply near any door, the likelihood of using vehicle 2 is high. Therefore, in such a combination, CPU 31 increases the usage intention value V2 calculated in condition 2. Furthermore, if the user walks in a straight line towards any door, the likelihood of opening the door to that destination is higher. Therefore, CPU 31 makes the usage intention value V2 of the door located at the destination along the straight line relatively larger than the usage intention value V2 of other doors.

[0056] On the other hand, for example, the likelihood of using vehicle 2 decreases when the user moves forward and decelerates, moves at a constant speed parallel to the side of vehicle 2, or moves away from vehicle 2. Therefore, in such combinations, CPU 31 reduces the usage intention value V2 of condition 2. Additionally, CPU 31 reduces the usage intention value V2 for all doors, for example. The calculation information DB 35 sets the usage intention value V2 for each combination of factors such as the user's position, direction of movement, speed increase / decrease, and door type.

[0057] (Condition 3: Combination of position and body orientation)

[0058] In the calculation of the user intent value V3 based on condition 3, the user's "location" and "body orientation" information are used as the calculation source objects. The user intent value V3 is calculated based on the combination of these two pieces of information. The location and body orientation information can be obtained from the video data of each camera. The body orientation can be detected based on the user's movement direction and trajectory, or based on the user's shoulder, hand, and foot movements.

[0059] CPU31 calculates the user intent value V3 based on a combination of the user's position relative to vehicle 2 and their body orientation relative to vehicle 2. Alternatively, CPU31 can calculate the user intent value V3 based on a combination of the user's position when they decelerate to the point of stopping and their body orientation. Figure 5 An example is shown showing the parking status of vehicle 2 and the movement path of user 43. For example, user 43 may be stationary while riding in the vehicle or loading luggage. Figure 5The possibilities within areas 45A to 45C are shown. Area 45A is the area where user 43 stays when the front door 12R is opened, area 45B is the area where user 43 stays when the rear door 13R is opened, and area 45C is the area where user 43 stays when the tailgate 14 is opened. These areas can be preset based on verification positions such as vehicle model. When user 43 stays within or near areas 45A to 45C, CPU 31 increases the user intent value V3.

[0060] Additionally, if user 43 is positioned in area 45A, CPU 31 makes the usage intent value V3 of front door 12R greater than the usage intent value V3 of other doors. For example, as Figure 5 As shown in the percentages, the following settings are set in the calculation information DB35: when user 43 is in area 45A, the usage intention value V3 of the front door 12R is set to 70%, and the usage intention value V3 of the rear door 13R, which is closer to the front door 12R, is set to 40%. Additionally, 30% is set in the calculation information DB35 as the usage intention value V3 of the tailgate 14 when user 43 is in area 45A. That is, based on the front door 12R corresponding to the area 45A where user 43 is in, the usage intention value V3 of the tailgate 14, which is located further away from the front door 12R than the rear door 13R, is set to a lower value than the usage intention value V3 of the rear door 13R. Furthermore, 1% is set in the calculation information DB35 as the usage intention value V3 of the front door 12L and rear door 13L, which are located on the side opposite to the front door 12R (opposite side of vehicle 2) in the left-right direction when user 43 is in area 45A. Therefore, CPU 31 calculates the usage intent value V3 by referring to calculation information DB 35, and can set the usage intent value V3 corresponding to the location of the user's stay to each door. Similarly, for example, when user 43 stays in area 45B, CPU 31 refers to calculation information DB 35 to maximize the usage intent value V3 of back door 13R, and makes the usage intent value V3 of other doors relatively smaller according to the distance from back door 13R.

[0061] Furthermore, even if user 43 remains in area 45A or similar situations and their body is facing the opposite side of the car door, the likelihood of opening each door decreases depending on the body's orientation. For example, Figure 5The dashed lines represent the movable areas of the front door 12R and the rear door 14 when they are opening and closing. For example, if user 43 enters vehicle 2 through the front door 12R, it is anticipated that the front door 12R will open within the movable area indicated by the dashed lines. Therefore, the likelihood of user 43 standing in area 45A with their body facing slightly to the left (inside the vehicle) is high. Therefore, when CPU 31 detects such a combination of position and body orientation, it increases the usage intention value V3 of the front door 12R. On the other hand, when user 43 is standing in area 45A, the likelihood of user 43 entering the vehicle is lower if user 43 is standing with their body facing the rear of vehicle 2 or facing the right side of vehicle 2. Therefore, in the calculation information DB 35, the value of the usage intention value V3 is adjusted according to the body orientation of user 43. For example, if user 43 is standing in area 45A with their body facing rearward, CPU 31 can decrease the usage intention value V3 of the front door 12R and increase the usage intention value V3 of the rear door 13R.

[0062] Similarly, when user 43 is in area 45C, the likelihood of opening the tailgate 14 to load luggage is lower if user 43 is facing backward. In this case, CPU 31 decreases the usage intention value V3 of the tailgate 14. Furthermore, if the rear door 13R is a sliding door, the body's orientation becomes the orientation opposite to the rear door 13R (the rear door 13R is parallel to the body's surface). Therefore, for example, if the rear door 13R is a sliding door, user 43 is in area 45B, and the body is facing forward towards the vehicle 2, CPU 31 can decrease the usage intention value V3 of the rear door 13R and increase the usage intention value V3 of the front door 12R. In this way, even if user 43 is in or near areas 45A-45C, CPU 31 changes the usage intention value V3 according to the body's orientation.

[0063] The calculation information DB35 contains usage intention values ​​V3 for each combination, such as the user 43's position, body orientation, and door type. The CPU 31 can set the usage intention value V3 for each door by retrieving combinations from the calculation information DB35 that match the detected position and body orientation information. Additionally, a correction factor can be set in the calculation information DB35 to adjust the usage intention value V3 based on the deviation between each area 45A-45C and the actual position of the user 43. Furthermore, a correction factor can be set in the calculation information DB35 to adjust the usage intention value V3 based on the deviation between the set body orientation (angle) and the actual body orientation of the user 43. The CPU 31 can also adjust the usage intention value V3 based on the deviation of position or orientation and the correction factor.

[0064] (Condition 4: Sight and sound)

[0065] In the calculation of the usage intent value V4 based on condition 4, information from at least one of the user 43's "gaze" and the user 43's "voice" is used as the calculation source object, and the usage intent value V4 is calculated based on this information. Gaze information can be obtained, for example, from the video data of each camera. Additionally, voice information can be obtained using the microphones of each camera or a sound recording device separate from the camera.

[0066] For example, it can be pre-registered which part of vehicle 2 should be viewed when the user intends to use vehicle 2. In other words, when user 43 wants to express the intention to use vehicle 2, user 43 can express the intention to use vehicle 2 by viewing the pre-registered part. The part that should be viewed can be, for example, the position of the door handles of each door, the position of the windows of each door, etc. The closer the endpoint of user 43's line of sight is to the pre-registered part, the more the CPU 31 increases the use intention value V4; the farther the endpoint of user 43's line of sight is from the registered part, the more the CPU 31 decreases the use intention value V4. The calculation information DB 35 stores, for example, a formula for calculating the use intention value V4 based on the difference between the coordinates of the part of vehicle 2 that should be viewed and the coordinates of the endpoint of user 43's line of sight. In addition, when the CPU 31 detects that the endpoint of user 43's line of sight is the part of any door that should be viewed (door handle or window), the CPU 31 increases the use intention value V4 of that door (the door that user 43 is looking at) relatively compared with the use intention values ​​V4 of other doors (unviewed doors).

[0067] Furthermore, the above-described method for calculating the usage intention value V4 using the line of sight is an example. For instance, the usage intention value V4 can be increased or decreased based on whether the endpoint of user 43's line of sight is close to vehicle 2. For example, if user 43's face is towards vehicle 2, the likelihood of user 43 using vehicle 2 increases; if user 43's face is facing a different direction from vehicle 2, the likelihood of user 43 using vehicle 2 decreases. Therefore, it is also possible that when user 43's line of sight is towards vehicle 2, the closer the door is to user 43, the greater the usage intention value V4. Conversely, when user 43's line of sight is facing a different direction from vehicle 2, user 43 is more likely to pass by vehicle 2 or retrieve items near vehicle 2. Therefore, CPU 31 could also, for example, make the usage intention value V4 of all doors smaller the further away the endpoint of user 43's line of sight is from vehicle 2.

[0068] Furthermore, regarding sound, it is pre-registered what kind of sound (keywords, etc.) should be emitted when there is an intention to use vehicle 2. In other words, it is best to pre-determine what language should be emitted when user 43 wants to express the intention to use the vehicle. Keywords specifying the door to be opened, such as "Please open the driver's side door," are pre-registered. CPU 31 analyzes the sound data collected from the microphones of each camera. The higher the consistency with the pre-determined keywords, the higher the usage intention value V4 is, and the lower the consistency is, the lower the usage intention value V4 is. In addition, in the above example, since the front door 12R is specified by sound, the higher the consistency with the keywords, the higher the usage intention value V4 of the specified front door 12R is, and the lower the usage intention value V4 of other doors is relatively. The keywords used in the sound comparison are stored in the calculation information DB35.

[0069] Furthermore, the content and calculation method of the above conditions are examples. For instance, in condition 1, the usage intention value V1 can be changed according to the shape of the carry-on luggage. Additionally, in condition 2, the consistency between the straight line connecting vehicle 2 and user 43's current position and user 43's movement path can be judged, and the higher the consistency, the greater the usage intention value V2. Furthermore, in condition 3, the angle of user 43's shoulder when standing in each area 45A-45C can be pre-registered. Moreover, the higher the consistency between the registered shoulder angle and the actually detected shoulder angle, the greater the usage intention value V3. Additionally, in condition 4, the usage intention value V4 can be calculated using only one of line of sight or sound. Furthermore, in condition 4, keywords such as "Please open the car door" without specifying the door to be opened can be pre-registered. In this case, CPU 31 can detect the keyword from the sound data collected by the microphone, and the closer the door is to user 43's current position, the greater the usage intention value V4.

[0070] Alternatively, a combination of "stroller" and "interior conditions" can be added as a condition, either based on or replacing conditions 1 to 4 above. When user 43 pushes a stroller carrying a baby near vehicle 2, user 43 first places the baby in the child seat before boarding. Therefore, CPU 31 can detect the position of the seat with the child seat via the in-vehicle camera when it detects user 43 pushing the stroller near vehicle 2, and increase the usage intention value V of the door closest to that seat. This allows the door to be opened before user 43 reaches the door with the child seat. CPU 31 calculates usage intention values ​​V1 to V4 for each door, but it may not calculate them. In this case, the adjustment of usage intention values ​​V1 to V4 for each door can be performed using weighting coefficients A1 to A4, described later.

[0071] (Restrictions on movement paths caused by obstacles)

[0072] In addition, CPU31 detects obstacles around vehicle 2 in S4. If the detected obstacle is an obstacle to the movement of user 43, CPU31 calculates the usage intention values ​​V1 to V4 by changing the method of calculating the usage intention values ​​V1 to V4 for each of the multiple conditions based on the movement path of user 43 restricted by the obstacle.

[0073] For each door, the user intent values ​​V1 to V4 for each of the above conditions are calculated. These calculated values ​​are then summed for each door to determine which door user 43 wants to open; that is, the target door can be detected. However, the path user 43 moves and the width of the path are altered or restricted by obstacles around the vehicle. When the movement path is altered, user 43's movement route, speed, position, body movements, line of sight, and calculation timing differ from those without obstacles.

[0074] Figure 5 This describes the movement path of user 43 when an obstacle 48 exists around the vehicle. Obstacle 48 could be, for example, a tree planted in a parking lot. Furthermore, obstacles 48 could include various other obstacles such as parking lot walls, materials placed in the parking lot, other vehicles, bicycles, guardrails, and other structures. Additionally, obstacle 48 could also be a moving object such as a pedestrian. CPU 31 can acquire information about obstacles 48 around the vehicle based on camera data from various cameras, or it can use other sensors such as millimeter-wave radar to acquire this information.

[0075] For example, in such Figure 5If the path 51, as shown, is so narrow that only one person can pass at a time, then when walking towards vehicle 2, user 43 must walk in the direction indicated by the arrow on path 51. Path 51 is a straight path leading to the front door 12R. However, this path is a result of path 51 being restricted by obstacle 48. In other words, even if user 43 wants to walk straight to the back door 13R, for example, they must still pass through path 51 due to obstacle 48. Therefore, if user 43 is detected walking through such path 51, in calculating the usage intention value V2 under condition 2, if the usage intention value V2 for the front door 12R is increased based on the point of walking in a straight line to the front door 12R, there is a possibility that the usage intention value V for a door different from the door user 43 wants to open will be increased. That is, the usage intention value V may be calculated incorrectly.

[0076] Therefore, CPU31 detects the positions of obstacle 48 and user 43, and upon detecting that user 43 has passed through the obstacle 48, it will determine the position of the obstacle 48. Figure 5 When the movement path 51 is restricted by an obstacle 48 as shown, or when it is anticipated that the user will traverse the movement path 51, the CPU 31 performs an adjustment, for example, by reducing the usage intention value V2. That is, as a measure of the accuracy of the target door, the usage intention value V2, which is reduced in accuracy due to the obstacle 48, can be intentionally reduced. Alternatively, the CPU 31 can also set the usage intention value V2 of all doors to zero during the period until the user 43 reaches position P1, which is the movement path 51 between the obstacles 48, and calculate the usage intention value V2 based on the change in movement route or speed after reaching position P1. In this way, the method of calculating the usage intention value V2 can also be changed according to the movement path 51 restricted by the obstacle 48.

[0077] Furthermore, for example, if the movement path to the front door 12R, rear door 13R, and back door 14, as shown in movement path 52, is restricted, it is difficult to determine which of the three doors the user 43 is aiming for based on the movement route. On the other hand, if the user 43 is moving through movement path 52, the probability of the user 43 opening the left front door 12L and rear door 13L becomes lower. Therefore, the CPU 31 detects the obstacle 48, and if the user 43 is moving through the movement path 52 restricted by the obstacle 48, for example, until reaching position P2 in area 45A near the front door 12R, the usage intention value V2 of the front door 12R, rear door 13R, and back door 14 is the same, while the usage intention value V2 of the left front door 12L and rear door 13L is zero. In addition, if user 43 has passed position P2 in the movement path 52 and then arrives at position P3 in area 45B near the rear door 13R, CPU 31 can make the usage intention value V2 of the rear door 13R and the back door 14 the same, and make the usage intention value V2 of the front door 12R (which has been passed by user 43 and has a lower probability of being opened) zero, in addition to the front door 12L and the rear door 13L.

[0078] Furthermore, the calculation method for usage intention values ​​V other than V2 can be changed depending on the movement path restricted by obstacle 48. For example, in movement path 51, the usage intention values ​​V1 to V4 of the front door 12R, rear door 13R, and back door 14 can be the same until the user 43 reaches position P1. Also, the calculation of usage intention values ​​V1 to V4 of the front door 12R, rear door 13R, and back door 14 can begin at the moment the user 43 reaches position P1. Additionally, if, for example, there is a movement path where the orientation of the user 43's body is restricted by obstacle 48, such as a path where a person can only walk laterally, the usage intention values ​​V2 to V4 can be set to constant values ​​until the user crosses that path.

[0079] (Regarding the weighting coefficients A1 to A4)

[0080] After executing S4, CPU31 executes S5, calculating for each door of vehicle 2 the sum of the values ​​obtained by multiplying the usage intention values ​​V1 to V4 calculated in S4 for each of the multiple conditions by the weighting coefficient of each of the multiple conditions. For example, the weighting coefficients multiplied by the usage intention values ​​V1 to V4 are set as weighting coefficients A1 to A4. In this case, CPU31 calculates the sum of V1*A1 + V2*A2 + V3*A3 + V4*A4 for each door. In addition, CPU31 changes the weighting coefficients A1 to A4 based on the state of user 43. Furthermore, when weighting coefficients A1 to A4 are summed, they are recorded as weighting coefficient A. The calculation information DB35 stores the weighting coefficients A1 to A4 corresponding to different states of user 43, as described below.

[0081] CPU 31 adjusts weighting coefficients A1 to A4 to increase the weighting of the user intent value V, which more easily reflects the user 43's intention and has higher accuracy in estimating the object gate, based on the determination of the object gate. For example, if user 43 has carry-on luggage, the user intent value V1, based on carry-on luggage, has higher accuracy in estimating the object gate than other user intent values ​​V. For example, different weighting coefficients A1 to A4 are set in the calculation information DB35 depending on whether user 43 has carry-on luggage. The calculation information DB35 is set with a value that makes the weighting coefficient A1 of the user intent value V1 larger than the weighting coefficients A2 to A4 of other user intent values ​​V2 to V4, based on the fact that user 43 has carry-on luggage. Therefore, when CPU 31 detects that user 43 has carry-on luggage based on the video data of each camera, it can make the weighting coefficient A1 of the user intent value V1 larger than the weighting coefficients A2 to A4 based on the calculation information DB35.

[0082] Furthermore, for example, if user 43 is operating a smartphone, even if they suddenly stop in front of any door, there is a possibility that they are stopping to look at their smartphone. In this case, the usage intention value V3 based on the location of the stop, etc., may be less accurate than other usage intention values ​​V1, V2, and V4 in estimating the target door. Different weighting coefficients A1 to A4 are set in the calculation information DB35 according to whether user 43 is carrying a smartphone or operating a smartphone. When CPU 31 detects that user 43 is carrying or operating a smartphone based on the video data of each camera, it makes the weighting coefficient A3 of the usage intention value V3 smaller than the other weighting coefficients A1, A2, and A4 based on the calculation information DB35.

[0083] Furthermore, the position and body orientation of user 43 when standing near vehicle 2 differ between the state of pushing a stroller and the state of not pushing a stroller. For example, if user 43 is not pushing a stroller, they face forward relative to the sliding door; if pushing a stroller, they may be standing with their body facing 90 degrees relative to the sliding door. Additionally, user 43 may be standing at a distance from vehicle 2 that is roughly equivalent to the size of the stroller or carry-on luggage. Therefore, when CPU 31 detects that user 43 is carrying a stroller, suitcase, shopping cart, carry-on luggage, etc., based on the camera data from each camera, it can make the weighting coefficient A3 of the user intent value V3, which is conditioned on user 43's position and body orientation, smaller than the other weighting coefficients A1, A2, and A4. Furthermore, weighting coefficients A1 to A4 can also be different values ​​for each door. Alternatively, fixed values ​​can be used as weighting coefficients A1 to A4. That is, weighting coefficients A1 to A4 can remain unchanged regardless of user 43's state.

[0084] (Comparison of total value and threshold TH)

[0085] In S5, CPU31 calculates the sum of the usage intent values ​​V1 to V4 for each door, multiplied by weighting coefficients A1 to A4 respectively. Then, in S6, CPU31 compares the sum of the values ​​for each door with the threshold TH. CPU31 determines the doors whose sum is above the threshold TH as target doors, that is, the doors that are presumed to be opened by user 43. Figure 4 As shown, the total value is calculated, for example, in the form of 0% to 100%. Figure 4 In the example shown, 85% is set as the threshold TH. Furthermore, the threshold TH can also be a different value depending on the gate.

[0086] If the total value of all gates in S6 is less than the threshold TH (S6: No), CPU31 re-executes the processing from S4 onwards, performing calculations of the intended values ​​V1 to V4, etc. Alternatively, if the total value of at least one gate is greater than or equal to the threshold TH, CPU31 makes a positive judgment in S6 (S6: Yes) and executes S7. If only one gate has a total value greater than or equal to the threshold TH, CPU31 designates that gate as the object gate. Alternatively, if multiple gates have a total value greater than or equal to the threshold TH, CPU31 may designate the gate with the largest total value as the object gate. Or, CPU31 may designate all multiple gates with a total value greater than or equal to the threshold TH as object gates. In this case, multiple gates can be opened simultaneously.

[0087] In S7, CPU31 performs the following control: unlocks the door whose total value is determined to be above the threshold TH in S6, i.e., the target door estimated based on the user intent value V, and opens the door. For example, if the target door is the front door 12R, CPU31 performs the following control: after unlocking the front door 12R by controlling the door lock device 15A, it controls the door opening and closing device 16A to open the front door 12R. Thus, the target door can be estimated based on the user intent values ​​V1 to V4 calculated for each of the multiple conditions for different calculation source objects, and the target door estimated to be opened by user 43 can be opened automatically.

[0088] (Effects of the first implementation method)

[0089] As detailed above, the first embodiment achieves the following effects.

[0090] (1) According to the vehicle door control device 1 of the first embodiment and the computer program executed by the vehicle door control device 1, the CPU 31 of the ECU 10 calculates usage intention values ​​V1 to V4 for each of the multiple conditions 1 to 4 with different calculation source objects. These usage intention values ​​V1 to V4 represent the probability that a user 43 in the vicinity of the vehicle 2 will use the vehicle 2 (S4). Based on the calculated usage intention values ​​V1 to V4, the CPU 31 estimates the door of the vehicle 2 that is expected to be opened by the user 43 (S6). The CPU 31 executes control to unlock and open the estimated door (S7).

[0091] Therefore, it is possible to determine the object door that user 43 wants to open based on multiple different conditions and control that object door. In the process of determining the door that user 43 wants to open, it is possible to suppress situations that are limited to specific conditions and to infer the object door from multiple perspectives, thus improving the accuracy of object door estimation and improving usability.

[0092] (2) In addition, the CPU31 calculates the total value of the usage intention value V1 to V4 based on each of the calculated multiple conditions for each door of the vehicle 2 (an example of the expected value in this specification), and presumes the door with a total value of TH or higher as the target door.

[0093] Therefore, by comparing the sum of the expected values ​​of the usage intent values ​​V1 to V4 based on each of the multiple conditions with the threshold TH, it is possible to comprehensively judge multiple conditions to estimate the object gate.

[0094] (3) In addition, the total value is calculated by multiplying the intended use value V1 to V4 of each of the multiple conditions by the weight coefficients A1 to A4 of each of the multiple conditions.

[0095] Accordingly, by comparing the sum of the values ​​obtained by multiplying the intended use values ​​V1 to V4 of each of the multiple conditions by the weight coefficients A1 to A4 of each of the multiple conditions with the threshold TH, it is possible to comprehensively judge multiple conditions to estimate the object gate.

[0096] (4) Furthermore, CPU 31 changes the weighting coefficients A1 to A4 based on the state of user 43. Accordingly, by calculating the total value for each door of vehicle 2 and changing the weighting coefficients A1 to A4 based on the state of user 43, the total value can be calculated using the weighting coefficients A1 to A4 corresponding to the state of user 43. This improves the accuracy of estimating the target door.

[0097] (5) Furthermore, CPU 31 adjusts the weighting coefficients A1 to A4 based on whether user 43 has carry-on luggage or the type of carry-on luggage. Accordingly, the weighting coefficients A1 to A4 can be adjusted based on whether user 43 has carry-on luggage or the type of carry-on luggage. Carry-on luggage refers to various items that user 43 can carry, such as goods purchased during shopping, user 43's smartphone, and stroller. By adjusting the weighting coefficients A1 to A4 based on the status of such carry-on luggage, the accuracy of the estimated object gate can be improved.

[0098] (6) In addition, the conditions of the first embodiment include condition 1 based on the relationship between the facility of the parked vehicle 2 and the personal luggage carried by the user 43, condition 2 based on the relationship between the user 43’s movement route and the change in the user 43’s movement speed, condition 3 based on the relationship between the user 43’s position and the user 43’s body orientation, and condition 4 based on the relationship between the vehicle 2 and the user 43’s line of sight.

[0099] If condition 1 applies, it is possible to infer whether user 43 intends to use vehicle 2 and, if so, which door they wish to open, based on parking facilities (type of parking facilities, etc.) and personal belongings (presence, size, etc.). If condition 2 applies, it is possible to infer whether user 43 intends to use vehicle 2 based on their movement path and speed changes relative to vehicle 2. If condition 3 applies, it is possible to infer whether user 43 intends to use vehicle 2 based on their position and orientation relative to vehicle 2. If condition 4 applies, it is possible to infer whether user 43 intends to use vehicle 2 based on whether they are looking at vehicle 2 or which part of vehicle 2 they are looking at. Furthermore, by comprehensively judging these conditions 1 through 4, it is possible to accurately infer user 43's intention to use vehicle 2 and the door they wish to open.

[0100] (7) In addition, CPU31 detects obstacle 48 in S4. If the detected obstacle 48 becomes an obstacle to the movement of user 43, it changes the method of calculating the use intention value V for each of the multiple conditions based on the movement path 51, 52 of user 43 restricted by obstacle 48, and calculates the use intention value V.

[0101] When obstacle 48 is present around the vehicle, the movement paths 51 and 52 of user 43 to vehicle 2 are restricted by obstacle 48. User 43's actions differ depending on whether movement paths 51 and 52 are unrestricted or restricted. Therefore, the calculation method for the usage intent value V of each of the multiple conditions needs to be changed according to the different actions of user 43. CPU 31 changes the calculation method for the usage intent value V of each of the multiple conditions based on the restriction of movement paths 51 and 52 caused by obstacle 48, thereby improving the accuracy of the inferred object gate. As a result, usability is improved.

[0102] (Second Implementation)

[0103] Next, while referring to the appendix Figure 1 The second embodiment will be described in detail below. This second embodiment is a specific embodiment of the vehicle door control device involved in the present invention. Figure 6 , Figure 7 This is a flowchart illustrating the gate control processing procedure according to the second embodiment. In the first embodiment described above, in Figure 3 In S4, when user 43 is detected to be using... Figure 5 When the obstacle 48, as shown, restricts the movement path 51, or when it is intended to pass through the movement path 51, the CPU 31 performs an adjustment, for example, reducing the intended use value V2. In contrast, the CPU 31 of the second embodiment restricts the execution of controls for opening the doors while the user 43 approaches the vehicle closer than the location of the obstacle 48, which differs from the first embodiment. In the following description, the same symbols are used for content identical to that of the first embodiment, and their descriptions are omitted as appropriate.

[0104] First, when CPU31 starts Figure 6 During the door control processing shown, CPU 31 executes the processes S1 to S3 in the same manner as in the first embodiment. If the parking facility is an external facility (S1: No), CPU 31 terminates the process. Figure 6The aforementioned processing. On the other hand, when the parking facility is the target facility (S1: Yes) and the user 43 approaches within a threshold distance Lth or less (S2: Yes), the CPU 31 activates each camera (S3). When the CPU 31 activates each camera and begins acquiring camera data, the CPU 31 performs the sensitivity adjustment processing of S9.

[0105] like Figure 7 As shown, when CPU31 begins sensitivity adjustment processing, CPU31, for example, acquires one frame of video data from each camera (S11). Figure 6 As shown, after performing the sensitivity adjustment process in S9, CPU 31 performs the processes in S4, S5, and S6 in the same manner as in the first embodiment. If the total value of all gates is less than the threshold TH (S6: No), the process in S9 is performed again. Therefore, during the period when the total value of all gates is less than the threshold TH (S6: No), CPU 31 repeatedly performs the following process: acquiring one frame of video data, and performing S9, S4 to S6 based on the acquired one frame of video data.

[0106] like Figure 7 As shown, after executing S11, CPU 31 detects the position of user 43 and obstacles 48 around the vehicle based on a frame of camera data acquired in S11 (S12). For example, CPU 31 detects the position of the skeleton of user 43 around the vehicle based on the camera data, specifically the position of the shoulders, the position of the head, etc. In addition, CPU 31 detects the position of the feet of user 43 around the vehicle based on the camera data, for example. CPU 31 detects the position of user 43 based on these skeleton positions and foot positions. Furthermore, the method for detecting the position of user 43 is not limited to the method of detecting skeleton positions and foot positions based on the above-mentioned camera data. Similar to the first embodiment, the method of detection based on the position information of the portable device 41, the method of detection using millimeter-wave radar mounted on vehicle 2, etc., can also be used.

[0107] Furthermore, the CPU 31 uses, for example, AI (Artificial Intelligence) to detect obstacles. For instance, an AI program is stored in the ROM 33. This AI program, for example, is an AI program that has learned a model through machine learning (deep learning) by using images of various camera data captured from the parked vehicle 2 as training data, and performs processing to estimate the position of obstacles 48 within the actual captured images. The CPU 31 executes this AI program to detect obstacles 48 present around the vehicle based on the camera data. The detection range of obstacles 48 is, for example, the same range as the detection range of the user 43. Furthermore, the method for detecting obstacles 48 is not limited to the method described above using AI; it can also be achieved using sensors 8 such as ultrasonic sensors, millimeter-wave radar, or laser sensors. Alternatively, obstacles 48 can be detected by image processing of the camera data. The obstacles 48, similar to those in the first embodiment, include parking lot walls, materials placed in the parking lot, etc.

[0108] After executing S12, CPU31 converts the positions of user 43 and obstacle 48 detected in S12 into overhead coordinates (S13). Figure 8 This is an example illustrating the positional relationship between vehicle 2, obstacle 48, and user 43. In order to... Figure 8 The vehicle 2, obstacle 48, and user 43 are different from those in the first embodiment, and will be referred to as vehicle 2A, obstacle 48A, and user 43A respectively in the following description. Figure 8 As shown, CPU 31 obtains, for example, the distance L1 between the position P5 of vehicle 2A and the position P6 of obstacle 48A, and the distance L2 between the position P5 of vehicle 2A and the position P7 of user 43A, based on the positions detected in S12. Furthermore, the definitions of distances L1 and L2 are not limited to the above definitions. For example, distances L1 and L2 may not be set as the distance to position P5, but rather as the distance between the position of user 43A in area 45A, area 45B, or area 45C before opening each door and the positions P6 and P7.

[0109] Position P5 is, for example, the center of vehicle 2A as viewed from above. Position P6 is, for example, the closest point of obstacle 48A to position P5 of vehicle 2A. Position P7 is, for example, the center of user 43A as viewed from above. CPU 31 sets, for example, the X and Y axes of the overhead coordinate system (S13). CPU 31 sets the XY coordinates, sets the detected positions P6 and P7, and calculates the distance between positions P5 and P6 as distance L1. Additionally, CPU 31 calculates the distance between positions P5 and P7 as distance L2.

[0110] like Figure 7 As shown, CPU 31 executes S15 after executing S13. CPU 31 determines whether the user 43A detected in S12 is at a position farther from vehicle 2A than the obstacle 48A detected in S12 (S15). In the second embodiment, CPU 31 performs, for example, an adjustment of the weight coefficient A2 of "condition 2: combination of movement route and speed change" as a method to adjust the sensitivity of the target door detection. As a result, the execution of control for opening the target door is restricted until the user 43A approaches a position closer to vehicle 2A than the position P6 of obstacle 48A.

[0111] exist Figure 8 Position P7, indicated by the solid line, is, for example, the position where user 43A sandwiches obstacle 48A in the middle, on the opposite side from vehicle 2A. When user 43A is at position P7, distance L2 is greater than distance L1. In this case, CPU 31 makes a positive judgment in S15 (S15: Yes) and executes S16. In S16, CPU 31 executes control that reduces detection accuracy. For example, during the period when CPU 31 makes a positive judgment in S15 (S15: Yes), that is, during the period when user 43A is at a position farther from vehicle 2A than obstacle 48A, it decides to reduce the detection accuracy. Figure 6 The weighting coefficient A2 used in S5 is reduced (S16). Therefore, the value obtained by multiplying the usage intention value V2 calculated in S5 (described later) by the weighting coefficient A2 is reduced, thus decreasing the total value calculated in S5. In S6, the total value is less likely to exceed the threshold TH. In other words, the influence of the usage intention value V2 calculated based on the combination of movement path and speed change in condition 2 on the total value is reduced, making the total value smaller and making it difficult to execute S7. The detection sensitivity of the object door is reduced, making it difficult to open the object door. The CPU 31 can also, for example, set the weighting coefficient A2 to zero. Therefore, by intentionally reducing the weighting coefficient A2 of the usage intention value V2, whose accuracy may be reduced due to the obstacle 48, as the accuracy of the estimated object door, the possibility of opening the wrong door can be suppressed.

[0112] On the other hand, Figure 8The position P8, indicated by the dashed line, is, for example, next to obstacle 48A or a position where user 43A has passed next to obstacle 48A. When user 43A is present at position P8, distance L2 is less than distance L1. In this case, CPU 31 makes a negative judgment in S15 (S15: No) and executes S17. In S17, CPU 31 performs control that does not reduce or increase detection accuracy. For example, during the period when CPU 31 makes a negative judgment in S15 (S15: No), that is, during the period when user 43A is present at a position closer to vehicle 2A than obstacle 48A, it decides to use the weighting coefficient A2 read from calculation information DB35 without change. Figure 6 The weighting coefficient A2 used in S5 (S17) is used. Therefore, the value of the intended use value V2 calculated in S5 by multiplying it by the weighting coefficient A2 is not changed, and the sensitivity of the detection target gate can be maintained as usual. In addition, CPU31 assumes that if no obstacle 48A is detected around the vehicle in S12, a negative judgment can be made in S15.

[0113] Alternatively, CPU31 can decide to increase the weighting coefficient A2 in S17. This increases the value of the intended use value V2 calculated in S5 (condition 2) multiplied by the weighting coefficient A2, thus increasing the total value calculated in S5. In S6, the total value is more likely to exceed the threshold TH. In other words, the influence of the intended use value V2 calculated based on condition 2 (the combination of movement path and speed change) on the total value is increased, making the total value larger and facilitating the execution of S7. This improves the detection sensitivity of the object door, making it easier to open.

[0114] For example, if CPU31 detects an obstacle 48A around the vehicle in S12 and user 43A is located closer to vehicle 2A than obstacle 48A (S15: No), it does not change the weight coefficient A2. On the other hand, if CPU31 does not detect obstacle 48A around the vehicle in S12, it makes a negative judgment in S15 (S15: No), increasing the weight coefficient A2. In this case, since there is no obstacle 48A around the vehicle, the reliability of the usage intent value V2 based on condition 2 increases. Therefore, the influence of the usage intent value V2 on the total value can also be increased, making it easier to open the object door based on the usage intent value V2.

[0115] When CPU31 executes S16 or S17, CPU31 terminates. Figure 7 The sensitivity adjustment process is shown below. Figure 6As shown, when CPU31 executes S9, CPU31 executes S4. CPU31 calculates the usage intent values ​​V1 to V4 in the same way as in the first embodiment. In addition, CPU31 may not execute the "process of calculating the usage intent values ​​V1 to V4 for each of the multiple conditions based on the movement path of user 43A restricted by obstacle 48A" executed in the first embodiment in S4.

[0116] When CPU 31 executes S4, it calculates the total value using weighting coefficients A1 to A4, similar to the first embodiment (S5). At this time, CPU 31 adjusts the weighting coefficient A2 based on the control content determined in S16 or S17 of S9. Furthermore, CPU 31 executes S6, similar to the first embodiment, and if the total value of all gates is less than the threshold TH (S6: No), it executes the processing from S9 onwards again. CPU 31 performs the processing from S9 onwards on the next frame of video data from each camera.

[0117] Furthermore, if the total value of at least one door is above the threshold TH (S6: Yes), the CPU31 performs the following control: unlocks the door whose total value is determined to be above the threshold TH, i.e., the target door estimated based on the user intention value V, and opens the door. Thus, the sensitivity related to the movement route can be adjusted based on the positional relationship between the obstacle 48A and the user 43A, enabling the opening of the appropriate target door.

[0118] Here, as Figure 8 As shown, when an obstacle 48A exists around the vehicle, the user 43A's movement path 51A is restricted due to this obstacle 48A. If the vehicle 2 does not recognize this situation, it incorrectly identifies the door as indicating an intention to board and may open it. Specifically, in Figure 8 In position P7, it is difficult to determine whether user 43A intends to approach vehicle 2A or simply move laterally to avoid obstacle 48A. In this case, as described above, the sensitivity of the door being judged is adjusted based on the positional relationship between obstacle 48A and user 43A.

[0119] While user 43A is positioned away from obstacle 48A, CPU 31 can control the opening of doors to be less aggressive by reducing the weighting coefficient A2. Furthermore, when user 43A reaches a position close to obstacle 48A, CPU 31 restores the weighting coefficient A2 to its original value, thereby reflecting the user intent value V2, which is the estimated result of the object door based on the movement route in condition 2, in the total value. Thus, for example, if there is an obstacle 48A between vehicle 2A and user 43A, the object door can be opened after user 43A avoids obstacle 48A and approaches vehicle 2A, or after user 43A stops in area 45A and it is detected that there is indeed an intention to board the vehicle. The estimation of the object door, the confirmation of the intention to board the vehicle, and the opening and closing of the object door can be performed with high precision.

[0120] Furthermore, a method for restricting the execution of control used to open the aforementioned door, and a method for adjusting the detection sensitivity of the object door, are examples. For instance, in the above description, CPU 31 performed the restriction by changing the value of the weight coefficient A2, but it is not limited to this. For example, if CPU 31 makes a positive judgment in S15 (S15: Yes), it can decide to reduce the usage intention value V2 in S4 to achieve the restriction.

[0121] Alternatively, if weighting coefficients are set for the movement route and speed changes respectively, only the weighting coefficient for the movement route can be adjusted. Furthermore, the presence of an obstacle 48A around the vehicle may affect conditions such as the vehicle's orientation in condition 3, not just condition 2. Therefore, CPU 31 can also change the weighting coefficients of other conditions based on the presence or location of obstacle 48A, not just condition 2.

[0122] Furthermore, if there is an obstacle 48A between user 43A and vehicle 2A, CPU 31 can execute the control to open the target door based on the condition that user 43A is standing in front of the door of vehicle 2A. That is, even if there is an obstacle 48A, the control to open the target door can be executed at a time when the intention to board can be more reliably confirmed.

[0123] (Effects of the second implementation method)

[0124] As explained in detail above, the second embodiment achieves the same effects as the first embodiment. Additionally, the second embodiment achieves the following effects.

[0125] (1) According to the vehicle door control device 1 and the computer program executed by the vehicle door control device 1 in the second embodiment, the CPU 31 of the ECU 10 detects the obstacle 48A present in the periphery of the vehicle 2A in S12, and restricts the execution of the control for opening the target door (S16) until the user 43A approaches to a position closer to the vehicle 2A than the position of the detected obstacle 48A.

[0126] When obstacle 48A is located closer to user 43A, user 43A is more likely to move to avoid obstacle 48A. Therefore, user 43A's movement route, i.e., movement path 51A, is restricted by obstacle 48A. It is unclear whether user 43A is avoiding obstacle 48A towards the target door, or whether user 43A is forced to pass near vehicle 2A due to obstacle 48A (i.e., passing near it without intending to board). Therefore, CPU 31 reduces the weighting coefficient A2 related to the movement route, thereby restricting the control of opening the target door until user 43A is closer to vehicle 2A than obstacle 48A. Thus, if user 43A merely avoids obstacle 48A and passes near vehicle 2A, the possibility of accidentally opening the target door can be suppressed. The estimation of the target door, the confirmation of the intention to board, and the opening and closing of the target door can be performed with high precision.

[0127] (2) In addition, during the period until the user 43A approaches a position closer to the vehicle 2A than the position of the obstacle 48A (S15: Yes), the CPU 31 performs an adjustment to reduce the total value (S16).

[0128] Therefore, by making it difficult for the total value to exceed the threshold TH, it is possible to suppress the situation where the user 43A is located far from the vehicle 2A and there is an obstacle 48A.

[0129] (3) In addition, CPU31 multiplies the usage intention values ​​V1 to V4 of each condition 1 to 4 calculated in S4 by the weight coefficients A1 to A4 of each condition 1 to 4 (S5), and calculates the sum of the multiplied values ​​as the total value for each door. During the period until user 43A approaches a position closer to vehicle 2A than the position of obstacle 48A (S15: Yes), CPU31 performs an adjustment to reduce the weight coefficient A2 of condition 2, which is a condition for the movement route (S16).

[0130] Therefore, by reducing the weighting coefficient A2, the total value is less likely to exceed the threshold TH. This helps to suppress the situation where object doors are accidentally opened.

[0131] Furthermore, the present invention is not limited to the above-described embodiments, and various modifications and variations can be made without departing from the spirit of the present invention.

[0132] For example, the processing content and processing order of the flowcharts in the above embodiments are one example.

[0133] For example, CPU31 may also choose not to accept registrations from external facilities. In this case, CPU31 may also start from S2. Figure 3 , Figure 6 The processing.

[0134] In addition, CPU31 can also receive registrations of the target facility rather than external facilities and make a judgment in S1, or it can receive both external facilities and target facilities and make a judgment in S1.

[0135] In addition, CPU31 can also receive registration information such as the user 43's location while riding in the vehicle and the direction of their body while riding, and perform the calculation of S4 based on the registered information. Thus, it is possible to customize the calculation method of the user intent value V according to the user 43's physical characteristics and requirements.

[0136] In addition, the multiple conditions in this specification may be at least two of conditions 1 to 4, or may include other conditions.

[0137] Furthermore, while the processing in the above embodiments is performed on a walking user 43, it is not limited to this. For example, even if the user 43 is in a wheelchair, the target door can be estimated based on conditions 1 to 4, and the estimated target door can be controlled. Therefore, the change in the user's movement speed in this specification is not limited to changes in walking speed, but can also be a change in the speed of wheelchair movement.

[0138] In addition, CPU31 can also perform adjustments such as stopping the control of the door to be opened or reducing the opening amount when it is difficult to open each door, such as when other vehicles are parked adjacent to vehicle 2.

[0139] In addition, CPU31 can also perform control to open multiple object doors simultaneously or in parallel when multiple object doors are estimated. For example, CPU31 can also perform control to open the sliding rear door 13R while opening the driver's seat front door 12R.

[0140] Furthermore, in the above embodiments, the ECU10 of the vehicle door control device 1 executes the door control processing program. Figure 3 , Figure 6 The processing structure can be modified, but the executing entity can be changed appropriately. For example, it could be the control unit of a navigation device, or other vehicle-mounted devices. Figure 3 , Figure 6 The structure of the processing.

[0141] The structure of the vehicle door control device 1 is not limited to the structure described in the above embodiments. For example, the vehicle door control device 1 may only have an ECU 10, or it may only have an ECU 10 and each camera.

[0142] Next, the technical ideas derived from the above-described embodiments will be described.

[0143] (1) The vehicle door control device according to method 1, wherein...

[0144] The control unit determines whether the parking facility where the vehicle is parked is a target facility. A target facility is a facility that calculates the intended use value and infers the target door.

[0145] If the parking facility is not the target facility, the control unit does not perform the calculation of the usage intention value by the usage intention value calculation unit and the estimation of the target door by the target door estimation unit.

[0146] Therefore, by pre-registering the desired facility with the vehicle door control device, users can prevent the door from automatically opening due to the user's intention to use the facility. The ability to exclude external facilities based on user requirements improves usability.

[0147] (2) The vehicle door control device according to method 1, wherein...

[0148] The control unit determines whether the user has approached below a threshold distance from the vehicle.

[0149] If it is determined that the user has approached below the threshold distance from the vehicle, the camera device installed in the vehicle is activated.

[0150] The usage intent value calculation unit calculates the usage intent value based on the video data captured by the activated camera device.

[0151] Accordingly, the camera device is stopped until the user approaches a certain distance, thereby reducing power consumption. This prevents unnecessary power consumption caused by frequent or continuous camera activation due to the user's proximity to the vehicle. It also helps prevent battery degradation and depletion. Furthermore, the camera device is activated only when the likelihood of the user using the vehicle increases to below a threshold distance, and the user intent value is calculated based on the captured data from the activated camera device.

[0152] (3) The vehicle door control device according to method 7, wherein if the obstacle is not detected by the obstacle detection unit, the object door estimation unit performs an adjustment that increases the weight coefficient of the movement route condition.

[0153] Therefore, when there are no obstacles around the vehicle, the influence of obstacles on the user's movement path disappears. Thus, by increasing the weighting coefficient of the movement path condition, the detection accuracy of the object door can be improved based on the user's movement path.

Claims

1. A vehicle door control device, wherein, have: The intention value calculation unit calculates a usage intention value for each of a plurality of conditions different from the calculation source object, the usage intention value representing the likelihood that a user in the vicinity of the vehicle will use the vehicle. An object door estimation unit estimates an object door based on the usage intention value calculated by the usage intention value calculation unit. The object door is a door among the doors of the vehicle that is intended to be opened by the user. as well as The control unit performs control over the object door estimated by the object door estimation unit to open the door.

2. The vehicle door control device according to claim 1, wherein, The target door estimation unit calculates an expected value of the use intention value based on each of the multiple conditions calculated by the use intention value calculation unit for each door of the vehicle, and estimates doors with expected values ​​above a threshold as the target doors.

3. The vehicle door control device according to claim 2, wherein, The expected value is calculated by multiplying the intended use value for each of the plurality of conditions by the weighting coefficient of each of the plurality of conditions.

4. The vehicle door control device according to claim 3, wherein, The object gate estimation unit changes the weight coefficient based on the user's state.

5. The vehicle door control device according to claim 3, wherein, The object gate estimation unit changes the weighting coefficient based on whether the user has carry-on luggage or based on the user's carry-on luggage.

6. The vehicle door control device according to claim 1 or 2, wherein, The conditions include at least two of the following: a condition based on the relationship between the facility where the vehicle is parked and the personal belongings carried by the user; a condition based on the relationship between the user's movement route and the change in the user's movement speed; a condition based on the relationship between the user's position and the user's body orientation; and a condition based on the relationship between the vehicle and the user's line of sight.

7. The vehicle door control device according to claim 1 or 2, wherein, It also includes an obstacle detection unit that detects obstacles present around the vehicle. When an obstacle detected by the obstacle detection unit becomes an obstacle to the user's movement, the user intent value calculation unit changes the method for calculating the user intent value for each of the multiple conditions based on the user's movement path restricted by the obstacle, and calculates the user intent value.

8. The vehicle door control device according to claim 1 or 2, wherein, It also includes an obstacle detection unit that detects obstacles present around the vehicle. During the period until the user approaches a position closer to the vehicle than the position of the obstacle detected by the obstacle detection unit, the control unit restricts the execution of control for opening the door for the object door estimated by the object door estimation unit.

9. The vehicle door control device according to claim 1 or 2, wherein, It also includes an obstacle detection unit that detects obstacles present around the vehicle. The target door estimation unit calculates the sum of the usage intention values ​​of each of the multiple conditions calculated by the usage intention value calculation unit for each door of the vehicle, and estimates the door with the sum value above a threshold as the target door. Furthermore, it performs an adjustment to reduce the sum value until the user approaches a position closer to the vehicle than the position of the obstacle detected by the obstacle detection unit.

10. The vehicle door control device according to claim 9, wherein, The conditions include a travel route condition, which is a condition based on the user's travel route. The object door estimation unit calculates for each door of the vehicle the sum of the values ​​obtained by multiplying the usage intention value of each of the multiple conditions calculated by the usage intention value calculation unit by the weight coefficient of each of the multiple conditions, and performs an adjustment to reduce the weight coefficient of the movement route condition until the user approaches a position closer to the vehicle than the position of the obstacle detected by the obstacle detection unit.

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