Patent Publication Number: US-11377124-B2

Title: Vehicle control device, vehicle control method, and storage medium

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims priority to and the benefit from Japanese Patent Application No. 2019-041628, filed on Mar. 7, 2019, the contents of which are hereby incorporated by reference into the present application. 
     BACKGROUND OF THE INVENTION 
     Field of the Invention 
     The present invention relates to a vehicle control device, a vehicle control method, and a storage medium. 
     Description of Related Art 
     A technology for acquiring information on baggage to be loaded into a vehicle by an occupant holding a remote key since it is predicted that the occupant is highly likely to board the vehicle when the occupant is approaching the vehicle, and determining whether or not the occupant has gotten off with all baggage carried at the time of boarding, when the occupant gets off is known (see, for example, Japanese Unexamined Patent Application, First Publication No. 2007-1724). In recent years, research on automatically controlling vehicles has progressed. 
     SUMMARY OF THE INVENTION 
     However, in the related art, leaving an object behind in a vehicle at the time of getting off the vehicle is prevented. Preventing forgetting to load an object at the time of boarding the vehicle has not been sufficiently studied. 
     The present invention has been made in view of such circumstances, and an object of the present invention is to provide a vehicle control device, a vehicle control method, and a storage medium capable of preventing forgetting to load baggage and persons to board from being left outside the vehicle at the time of start of automated driving. 
     A vehicle control device, a vehicle control method, and a storage medium according to the present invention have adopted the following configurations. 
     (1) A vehicle control device according to an aspect of the present invention includes: a recognizer configured to recognize at least a surroundings situation and an in-vehicle situation of a vehicle; and a driving controller configured to perform at least one of speed control and steering control of the vehicle on the basis of a recognition result of the recognizer, wherein the recognizer is configured to recognize an object to be loaded including at least any one of an occupant candidate present outside the vehicle and scheduled to board the vehicle and a baggage candidate present outside the vehicle and scheduled to be loaded into the vehicle and to recognize that the object to be loaded has been loaded into the vehicle, and the driving controller is configured to permit start of travel of the vehicle in a case where the recognizer has recognized that the object to be loaded has been loaded into the vehicle. 
     (2) In the aspect (1), the vehicle control device further include a notification controller configured to control an output to notify occupants of the vehicle that the recognizer has recognized that all of objects to be loaded are not loaded into the vehicle in a case where the recognizer has recognized that all of objects to be loaded are not loaded into the vehicle. 
     (3): In the aspect (2), the vehicle control device may further includes: a receiver configured to receive travel start permission from a user, wherein the driving controller is configured to permit the start of travel of the vehicle in a case where the receiver receives a travel start permission of the user after the notification controller controls the output. 
     (4) In any one of the aspects (1) to (3), the recognizer is configured to recognize that the object to be loaded has been loaded into the vehicle on the basis of a detection result of an in-vehicle detector configured to detect an in-vehicle status of the vehicle, and the in-vehicle detector includes at least one of a sensor configured to detect whether or not a seat belt of the vehicle has been used, a camera configured to image the inside of the vehicle, or a pressure sensor mounted on a seat of the vehicle. 
     (5) In any one of the aspects (1) to (4), the recognizer is configured to recognize a non-boarding person performing a predetermined action among persons recognized around the vehicle, and to exclude the non-boarding person from the objects to be loaded. 
     (6) In any one of the aspects (1) to (5), the vehicle control device further includes an outside-vehicle camera configured to image the vicinity of the vehicle, wherein the recognizer is configured to recognize that all of the objects to be loaded have been loaded into the vehicle on the basis of an image of the outside-vehicle camera. 
     (7) In the aspect (6), the recognizer is configured to recognize that all of the objects to be loaded have been loaded into the vehicle on the basis of an image of the vicinity of a door of the vehicle or the vicinity of a baggage compartment of the vehicle. 
     (8): In the aspect (6) or (7), the recognizer is configured to recognize that all of the objects to be loaded have not been loaded into the vehicle in a case where a predetermined item has been recognized near a door of the vehicle after the occupant candidates have boarded. 
     (9) In any one of the aspects (1) to (8), the recognizer is configured to recognize a constantly present object among objects recognized around the vehicle, and to exclude the constantly present object from the objects to be loaded. 
     (10) A vehicle control method using an in-vehicle computer according to an aspect of the present invention includes: recognizing at least a surroundings situation and an in-vehicle situation of a vehicle; performing at least one of speed control and steering control of the vehicle on the basis of the recognition result; recognizing an object to be loaded including at least any one of an occupant candidate present outside the vehicle and scheduled to board the vehicle and a baggage candidate present outside the vehicle and scheduled to be loaded into the vehicle; recognizing that the object to be loaded has been loaded into the vehicle; and permitting start of travel of the vehicle in a case where it has been recognized that the object to be loaded has been loaded into the vehicle. 
     (11) A non-transitory computer-readable storage medium according to an aspect of the present invention stores a program, the program causing an in-vehicle computer to: recognize at least a surroundings situation and an in-vehicle situation of a vehicle; perform at least one of speed control and steering control of the vehicle on the basis of the recognition result; recognize an object to be loaded including at least any one of an occupant candidate present outside the vehicle and scheduled to board the vehicle and a baggage candidate present outside the vehicle and scheduled to be loaded into the vehicle; recognize that the object to be loaded has been loaded into the vehicle; and permit start of travel of the vehicle in a case where it has been recognized that the object to be loaded has been loaded into the vehicle. 
     According to (1) to (11), it is possible to prevent loading of baggage from being forgotten or persons to board from being left outside the vehicle at the start of automated driving. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a configuration diagram of a vehicle system using a vehicle control device according to an embodiment. 
         FIG. 2  is a functional configuration diagram of a first controller and a second controller. 
         FIG. 3  is a diagram schematically showing a scene in which a self-traveling and parking event is executed. 
         FIG. 4  is a diagram showing an example of a configuration of a parking lot management device. 
         FIG. 5  is a flowchart showing an example of a process in which an occupant candidate is recognized by an object-to-be-loaded recognizer. 
         FIG. 6  is a flowchart showing an example of a process in which a baggage candidate is recognized by an object-to-be-loaded recognizer. 
         FIG. 7  is a flowchart showing an example of a process of a loading situation recognizer. 
         FIG. 8  is a flowchart showing another example of the process of the loading situation recognizer. 
         FIG. 9  is a flowchart showing still another example of the process of the loading situation recognizer. 
         FIG. 10  is a diagram showing an example of a hardware configuration of an automated driving control device according to the embodiment. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Hereinafter, embodiments of a vehicle control device, a vehicle control method, and a storage medium of the present invention will be described with reference to the drawings. 
     [Overall Configuration] 
       FIG. 1  is a configuration diagram of a vehicle system  1  using a vehicle control device according to an embodiment. A vehicle in which the vehicle system  1  is mounted is, for example, a vehicle such as a two-wheeled vehicle, a three-wheeled vehicle, or a four-wheeled vehicle. A driving source thereof includes an internal combustion engine such as a diesel engine or a gasoline engine, an electric motor, or a combination thereof. The electric motor operates using power generated by a power generator connected to the internal combustion engine or discharge power of a secondary battery or a fuel cell. 
     The vehicle system  1  includes, for example, an outside-vehicle camera  10 , a radar device  12 , a finder  14 , an object recognition device  16 , a communication device  20 , a human machine interface (HMI)  30 , a vehicle sensor  40 , a navigation device  50 , a map positioning unit (MPU)  60 , a driving operator  80 , an automated driving control device  100 , a travel driving force output device  200 , a brake device  210 , and a steering device  220 . These devices or equipment are connected to each other by a multiplex communication line such as a controller area network (CAN) communication line, a serial communication line, a wireless communication network, or the like. The configuration shown in  FIG. 1  is merely an example, and part of the configuration may be omitted or another configuration may be added. 
     The outside-vehicle camera  10  is, for example, a digital camera using a solid-state imaging device such as a charge coupled device (CCD) or a complementary metal oxide semiconductor (CMOS). The outside-vehicle camera  10  is attached to any place on a vehicle in which the vehicle system  1  is mounted (hereinafter, a host vehicle M). In the case of forward imaging, the outside-vehicle camera  10  is attached to an upper portion of a front windshield, a rear surface of a rearview mirror, or the like. The outside-vehicle camera  10 , for example, periodically and repeatedly images surroundings of the host vehicle M. The outside-vehicle camera  10  may be a stereo camera or a 360-degree camera. The outside-vehicle camera  10  captures a bird&#39;s eye image of a vehicle as if the vehicle is looked down from above. 
     The radar device  12  radiates radio waves such as millimeter waves to the surroundings of the host vehicle M and detects radio waves (reflected waves) reflected by an object to detect at least a position (a distance and orientation) of the object. The radar device  12  is attached to any place on the host vehicle M. The radar device  12  may detect a position and a speed of the object using a frequency modulated continuous wave (FM-CW) scheme. 
     The finder  14  is a light detection and ranging (LIDAR). The finder  14  radiates light to the surroundings of the host vehicle M and measures scattered light. The finder  14  detects a distance to a target on the basis of a time from light emission to light reception. The radiated light is, for example, pulsed laser light. The finder  14  is attached to any place on the host vehicle M. 
     The object recognition device  16  performs a sensor fusion process on detection results of some or all of the outside-vehicle camera  10 , the radar device  12 , and the finder  14  to recognize a position, type, speed, and the like of the object. The object recognition device  16  outputs recognition results to the automated driving control device  100 . The object recognition device  16  may output the detection results of the outside-vehicle camera  10 , the radar device  12 , and the finder  14  as they are to the automated driving control device  100 . The object recognition device  16  may be omitted from the vehicle system  1 . 
     The communication device  20 , for example, communicates with another vehicle or a parking lot management device (to be described below) present around the host vehicle M, or various server devices using a cellular network, a Wi-Fi network, Bluetooth (registered trademark), dedicated short range communication (DSRC), or the like. 
     The HMI  30  presents various types of information to an occupant of the host vehicle M and receives an input operation from the occupant. The HMI  30  includes various display devices, speakers, buzzers, touch panels, switches, keys, and the like. The HMI  30  may receive an instruction from the user through a manual operation of the user, or may receive an instruction from the user by recognizing a voice of the user. 
     The vehicle sensor  40  includes, for example, a vehicle speed sensor that detects a speed of the host vehicle M, an acceleration sensor that detects an acceleration, a yaw rate sensor that detects an angular speed around a vertical axis, and an orientation sensor that detects a direction of the host vehicle M. 
     The navigation device  50  includes, for example, a global navigation satellite system (GNSS) receiver  51 , a navigation HMI  52 , and a route determiner  53 . The navigation device  50  holds first map information  54  in a storage device such as a hard disk drive (HDD) or a flash memory. The GNSS receiver  51  specifies a position of the host vehicle M on the basis of a signal received from a GNSS satellite. The position of the host vehicle M may be specified or supplemented by an inertial navigation system (INS) using an output of the vehicle sensor  40 . The navigation HMI  52  includes a display device, a speaker, a touch panel, keys, and the like. The navigation HMI  52  may be partly or wholly shared with the HMI  30  described above. The route determiner  53 , for example, determines a route (hereinafter, an on-map route) from the position of the host vehicle M specified by the GNSS receiver  51  (or any input position) to a destination input by the occupant using the navigation HMI  52  by referring to the first map information  54 . The first map information  54  is, for example, information in which a road shape is represented by links indicating roads and nodes connected by the links. The first map information  54  may include a curvature of the road, point of interest (POI) information, and the like. The on-map route is output to the MPU  60 . The navigation device  50  may perform route guidance using the navigation HMI  52  on the basis of the on-map route. The navigation device  50  may be realized, for example, by a function of a terminal device such as a smartphone or a tablet terminal possessed by the occupant. The navigation device  50  may transmit a current position and a destination to a navigation server via the communication device  20  and acquire the same route as the on-map route from the navigation server. 
     The MPU  60  includes, for example, a recommended lane determiner  61 , and holds second map information  62  in a storage device such as an HDD or a flash memory. The recommended lane determiner  61  divides the on-map route provided from the navigation device  50  into a plurality of blocks (for example, divides the route every 100 [m] in a traveling direction of the vehicle), and determines a recommended lane for each block by referring to the second map information  62 . The recommended lane determiner  61  determines in which lane from the left the host vehicle M travels. The recommended lane determiner  61  determines the recommended lane so that the host vehicle M can travel on a reasonable route for progression to a branch destination when there is a branch place in the on-map route. 
     The second map information  62  is map information with higher accuracy than the first map information  54 . The second map information  62  includes, for example, information on a center of the lane or information on a boundary of the lane. Further, the second map information  62  may include road information, traffic regulation information, address information (an address and postal code), facility information, telephone number information, and the like. The second map information  62  may be updated at any time by the communication device  20  communicating with another device. 
     The in-vehicle detector  70  detects a status of the inside of the vehicle. The inside of the vehicle includes a space in which seats or the like are disposed for person boarding, a baggage compartment for placement of baggage, and the like. The in-vehicle detector  70  includes, for example, at least one of a sensor that detects whether a seat belt is used, a camera that images the inside of the vehicle, and a pressure sensor mounted on the seat. The in-vehicle detector  70  outputs a detection result to the automated driving control device  100 . 
     The driving operator  80  includes, for example, an accelerator pedal, a brake pedal, a shift lever, a steering wheel, a variant steer, a joystick, and other operators. A sensor that detects the amount of operation or the presence or absence of operation is attached to the driving operator  80 , and a detection result thereof is output to the automated driving control device  100  or some or all of the travel driving force output device  200 , the brake device  210 , and the steering device  220 . 
     The automated driving control device  100  includes, for example, a first controller  120 , and a second controller  160 . The first controller  120  and the second controller  160  are realized, for example, by a hardware processor such as a central processing unit (CPU) or a graphics processing unit (GPU) executing a program (software). Some or all of these components may be realized by hardware (a circuit portion; including circuitry) such as a large scale integration (LSI), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or a graphics processing unit (GPU) or may be realized by software and hardware in cooperation. The program may be stored in a storage device (a storage device having a non-transitory storage medium) such as an HDD or a flash memory of the automated driving control device  100  in advance or may be stored in a detachable storage medium such as a DVD or a CD-ROM and installed in the HDD or the flash memory of the automated driving control device  100  by the storage medium (the non-transitory storage medium) being mounted in a drive device. 
       FIG. 2  is a functional configuration diagram of the first controller  120  and the second controller  160 . The first controller  120  includes, for example, a recognizer  130 , an action plan generator  140 , and a notification controller  150 . The first controller  120  realizes, for example, a function using artificial intelligence (AI) and a function using a previously given model in parallel. For example, a function of “recognizing an intersection” may be realized by recognition of the intersection using deep learning or the like and recognition based on previously given conditions (there is a signal which can be subjected to pattern matching, a road sign, or the like) being executed in parallel and scored for comprehensive evaluation. Accordingly, the reliability of automated driving is guaranteed. 
     The recognizer  130  recognizes a status such as a position, a speed, or an acceleration of an object around the host vehicle M on the basis of information input from the outside-vehicle camera  10 , the radar device  12 , and the finder  14  via the object recognition device  16 . The position of the object, for example, is recognized as a position at absolute coordinates with a representative point (a centroid, a drive shaft center, or the like) of the host vehicle M as an origin and is used for control. The position of the object may be represented by a representative point such as a centroid or a corner of the object or may be represented by a represented area. The “status” of the object may include an acceleration or jerk of the object, or an “action status” (for example, whether or not the object is changing lanes or is about to change lanes). 
     The recognizer  130  recognizes, for example, a lane in which the host vehicle M is traveling (travel lane). For example, the recognizer  130  compares a pattern of a road marking line (for example, an arrangement of a solid line and a broken line) obtained from the second map information  62  with a pattern of a road marking line around the host vehicle M recognized from an image captured by the outside-vehicle camera  10  to recognize the travel lane. The recognizer  130  may recognize not only the road marking lines but also a traveling road boundary (a road boundary) including the road marking line, a road shoulder, a curb, a median strip, a guard rail, or the like to recognize the travel lane. In this recognition, the position of the host vehicle M acquired from the navigation device  50  or a processing result of an INS may be additionally considered. Further, the recognizer  130  may recognize a temporary stop line, an obstacle, a red light, a toll gate, and other road events. 
     The recognizer  130  recognizes a position or posture of the host vehicle M with respect to a travel lane when recognizing the travel lane. The recognizer  130  may recognize, for example, a deviation of a reference point of the host vehicle M from a center of the lane and an angle formed between a traveling direction of the host vehicle M and a line connecting the center of the lane as the relative position and posture of the host vehicle M with respect to the travel lane. Instead, the recognizer  130  may recognize, for example, a position of the reference point of the host vehicle M with respect to any one of side end portions (the road marking line or the road boundary) of the travel lane as the relative position of the host vehicle M with respect to the travel lane. 
     The recognizer  130  includes, for example, a parking space recognizer  132 , an object-to-be-loaded recognizer  134 , and a loading situation recognizer  136 . Configurations thereof are activated in a self-traveling and parking event to be described below. Details thereof will be described below. 
     In principle, the action plan generator  140  generates a target trajectory along which the host vehicle M will travel in the future automatically (without depending on an operation of a driver) so that the host vehicle M can travel on the recommended lane determined by the recommended lane determiner  61  and cope with a surroundings situation of the host vehicle M. The target trajectory includes, for example, a speed element. For example, the target trajectory is represented as a sequence of points (trajectory points) to be reached by the host vehicle M. The trajectory point is a point that the host vehicle M is to reach for each predetermined travel distance (for example, several meters) at a road distance, and a target speed and a target acceleration at every predetermined sampling time (for example, every several tenths of a [sec]) are separately generated as a part of the target trajectory. The trajectory point may be a position that the host vehicle M is to reach at the sampling time at every predetermined sampling time. In this case, information on the target speed or the target acceleration is represented by the interval between the trajectory points. 
     When the action plan generator  140  generates the target trajectory, the action plan generator  140  may set an event of automated driving. Examples of the automated driving event include a constant speed traveling event, a low speed following driving event, a lane changing event, a branching event, a merging event, a takeover event, and a self-traveling and parking event in which a vehicle travels in an unmanned manner and is parked in valet parking or the like. The action plan generator  140  generates a target trajectory according to an activated event. The action plan generator  140  includes an autonomous parking controller  142  that is activated when the self-traveling and parking event is performed. Details of a function of the autonomous parking controller  142  will be described below. 
     The second controller  160  controls the travel driving force output device  200 , the brake device  210 , and the steering device  220  so that the host vehicle M passes through the target trajectory generated by the action plan generator  140  at a scheduled time. 
     The second controller  160  includes, for example, an acquirer  162 , a speed controller  164 , and a steering controller  166 . The acquirer  162  acquires information on the target trajectory (trajectory points) generated by the action plan generator  140  and stores the information on the target trajectory in a memory (not shown). The speed controller  164  controls the travel driving force output device  200  or the brake device  210  on the basis of the speed element incidental to the target trajectory stored in the memory. The steering controller  166  controls the steering device  220  according to a degree of bend of the target trajectory stored in the memory. Processes of the speed controller  164  and the steering controller  166  are realized by, for example, a combination of feedforward control and feedback control. For example, the steering controller  166  executes a combination of feedforward control according to a curvature of a road in front of the host vehicle M and feedback control based on a deviation from the target trajectory. 
     The travel driving force output device  200  outputs a travel driving force (torque) for traveling of the vehicle to the driving wheels. The travel driving force output device  200  includes, for example, a combination of an internal combustion engine, an electric motor, a transmission, and the like, and an electronic control unit (ECU) that controls these. The ECU controls the above configuration according to information input from the second controller  160  or information input from the driving operator  80 . 
     The brake device  210  includes, for example, a brake caliper, a cylinder that transfers hydraulic pressure to the brake caliper, an electric motor that generates hydraulic pressure in the cylinder, and a brake ECU. The brake ECU controls the electric motor according to information input from the second controller  160  or information input from the driving operator  80  so that a brake torque according to a braking operation is output to each wheel. The brake device  210  may include a mechanism that transfers the hydraulic pressure generated by the operation of the brake pedal included in the driving operator  80  to the cylinder via a master cylinder, as a backup. The brake device  210  is not limited to the configuration described above and may be an electronically controlled hydraulic brake device that controls the actuator according to information input from the second controller  160  and transfers the hydraulic pressure of the master cylinder to the cylinder. 
     The steering device  220  includes, for example, a steering ECU and an electric motor. The electric motor, for example, changes a direction of the steerable wheels by causing a force to act on a rack and pinion mechanism. The steering ECU drives the electric motor according to information input from the second controller  160  or information input from the driving operator  80  to change the direction of the steerable wheels. 
     [Autonomous Parking Event—at Time of Vehicle Entry] 
     The autonomous parking controller  142  parks the host vehicle M in the parking space on the basis of information acquired from the parking lot management device  400  by the communication device  20 , for example.  FIG. 3  is a diagram schematically showing a scene in which the self-traveling and parking event is executed. Gates  300 -in and  300 -out are provided on a route from a road Rd to a visit destination facility. The host vehicle M advances to a stop area  310  through the gate  300 -in according to manual driving or automated driving. The stop area  310  faces a boarding and alighting area  320  connected to the visit destination facility. An eave for avoiding rain or snow is provided in the boarding and alighting area  320 . 
     After the occupant alights in the stop area  310 , the host vehicle M starts unmanned automated driving and starts the self-traveling and parking event to move to the parking space PS in a parking lot PA. A start trigger of the self-traveling and parking event may be, for example, any operation of an occupant, or may be wireless reception of a predetermined signal from the parking lot management device  400 . When the autonomous parking controller  142  starts the self-traveling and parking event, the autonomous parking controller  142  controls the communication device  20  such that a parking request is transmitted to the parking lot management device  400 . The host vehicle M moves from the stop area  310  to the parking lot PA according to guidance of the parking lot management device  400  or while performing its own sensing. 
       FIG. 4  is a diagram showing an example of a configuration of the parking lot management device  400 . The parking lot management device  400  includes, for example, a communicator  410 , a controller  420 , and a storage  430 . The storage  430  stores information such as parking lot map information  432  and a parking space status table  434 . 
     The communicator  410  wirelessly communicates with the host vehicle M or other vehicles. The controller  420  guides the vehicle to the parking space PS on the basis of the information acquired by communicator  410  and the information stored in storage  430 . The parking lot map information  432  is information that geometrically represents a structure of the parking lot PA. The parking lot map information  432  includes coordinates for each parking space PS. The parking space status table  434  is, for example, a table in which a status indicating whether the parking space is in an empty status or a full (parked) status and a vehicle ID that is identification information of parked vehicles when the parking space is full are associated with a parking space ID, which is identification information of the parking space PS. 
     When the communicator  410  receives the parking request from the vehicle, the controller  420  extracts the parking space PS that is in an empty status by referring to the parking space status table  434 , acquires a position of the extracted parking space PS from the parking lot map information  432 , and transmits a suitable route to the acquired position of the parking space PS to the vehicle using the communicator  410 . The controller  420  instructs a specific vehicle, for example, to stop or slow down, as necessary, on the basis of positional relationships between a plurality of vehicles so that the vehicles do not advance to the same position at the same time. 
     In a vehicle (hereinafter, referred to as the host vehicle M) that has received the route, the autonomous parking controller  142  generates a target trajectory based on the route. When the host vehicle M approaches the parking space PS, which is a target, the parking space recognizer  132  recognizes parking frame lines or the like that partition the parking space PS, recognizes a specific position of the parking space PS, and provides the position to the autonomous parking controller  142 . The autonomous parking controller  142  receives the position, corrects the target trajectory, and parks the host vehicle M in the parking space PS. 
     [Autonomous Parking Event—at Time of Exit] 
     The autonomous parking controller  142  and the communication device  20  remain in an operating state even when the host vehicle M is parked. The autonomous parking controller  142  activates a system of the host vehicle M and moves the host vehicle M to the stop area  310 , for example, when the communication device  20  receives a vehicle pick-up request from a terminal device of the occupant. In this case, the autonomous parking controller  142  controls the communication device  20  such that a start request is transmitted to the parking lot management device  400 . The controller  420  of the parking lot management device  400  instructs a specific vehicle, for example, to stop or slow down, as necessary, on the basis of positional relationships between a plurality of vehicles so that the vehicles do not advance to the same position at the same time, similar to the time of vehicle entrance. When the host vehicle M is moved to the stop area  310  and an occupant boards the host vehicle M, the autonomous parking controller  142  stops an operation, and then, manual driving or automated driving by another functional unit is started. 
     The present invention is not limited to the above, and the autonomous parking controller  142  may find a parking space in an empty status by itself on the basis of detection results of the outside-vehicle camera  10 , the radar device  12 , the finder  14 , or the object recognition device  16  without depending on communication, and park the host vehicle M in the found parking space. 
     [Autonomous Parking Event-when Boarding and Loading] 
     The object-to-be-loaded recognizer  134  recognizes the object to be loaded when an occupant boards the host vehicle M that has automatically exited or when baggage is loaded into the host vehicle M that has automatically exited. For example, the object-to-be-loaded recognizer  134  recognizes the object to be loaded on the basis of an image obtained by imaging the surroundings of the host vehicle M or an image obtained by imaging the vicinity of a door of the host vehicle M. The object to be loaded includes any one of an occupant candidate and a baggage candidate. The occupant candidate is a person who is present outside the host vehicle M and a person scheduled to board the host vehicle M (a person likely to board the vehicle). The baggage candidate is an object that is present outside the host vehicle M and is baggage to be loaded into the host vehicle M. 
     For example, the object-to-be-loaded recognizer  134  recognizes a person satisfying conditions of a regular user among persons standing in the stop area  310  and persons approaching the host vehicle M, as the occupant candidate. When the conditions of a regular user are satisfied, this indicates that a person is a regular user who is permitted to get on the host vehicle M. When the conditions of a regular user are satisfied, for example, the person is recognized as a user of the host vehicle M using a face authentication technology based on feature information registered in advance. The present invention is not limited thereto, and when the conditions of a regular user are satisfied, the person may possess an electronic key for remotely operating a key of the door of the host vehicle M and the person may execute a gesture or action registered in advance. In the former case, the object-to-be-loaded recognizer  134  authenticates the person as a regular user on the basis of, for example, a result of comparison between information received from the electronic key and information registered in advance. In the latter case, the object-to-be-loaded recognizer  134  authenticates the person as a regular user by analyzing an image using, for example, a pattern matching technology. 
     The object-to-be-loaded recognizer  134  recognizes not only a person satisfying the conditions of a regular user but also a person who is together with the person satisfying the conditions of a regular user (hereinafter referred to as a regular companion) as the occupant candidate. For example, the object-to-be-loaded recognizer  134  may recognize, as occupant candidates, a person within a predetermined range from a person satisfying the conditions of a regular user, a person walking in the same direction as the person satisfying the conditions of a regular user, a person walking at the same speed as the person satisfying the conditions of a regular user, a person likely to have a conversation with the person satisfying the conditions of a regular user, and the like. 
     On the other hand, the object-to-be-loaded recognizer  134  may exclude, from the occupant candidates, persons taking an action likely not to be taken by a person who is with a person satisfying the conditions of a regular user, such as a person away from the host vehicle M, a person turning his or her back to the host vehicle M, or a person standing alone (for example, a clerk) even though such a person is in the vicinity in a predetermined range including persons satisfying the conditions of a regular user. A person who is not a companion of such a regular user is described as an exclusion target. 
     The object-to-be-loaded recognizer  134  may recognize a person performing a predetermined non-boarding action (hereinafter referred to as a non-boarding person) among the persons recognized around the host vehicle, and exclude the non-boarding person from the occupant candidates. The non-boarding persons include a person who is seeing off, a person who has placed baggage in a host vehicle M, a staff member who has provided guidance, and the like. The predetermined non-boarding action includes, for example, an operation of waving a hand, for example, to point in a travel start direction of the host vehicle M, and an operation of standing in the same place around the host vehicle M during a predetermined time or more. 
     When the occupant candidates have been recognized, the object-to-be-loaded recognizer  134  derives the number of occupant candidates. For example, the object-to-be-loaded recognizer  134  derives a total number of persons included in the occupant candidates. Here, the object-to-be-loaded recognizer  134  may derive the number of persons for each attribute of the persons. For example, the object-to-be-loaded recognizer  134  may derive the respective numbers of babies, children, adults, elderly persons, and the like included in the occupant candidates. The present invention is not limited thereto, and the object-to-be-loaded recognizer  134  may derive the number of persons for each type of clothing. For example, the object-to-be-loaded recognizer  134  may derive the number of persons wearing black clothes, persons wearing whitish clothes, persons wearing warm colored clothes, and persons wearing cool-colored clothes. Thus, the object-to-be-loaded recognizer  134  may extract features of the occupant candidates and classify the occupant candidates for each feature (attribute). 
     When the object-to-be-loaded recognizer  134  has recognized the occupant candidate, the object-to-be-loaded recognizer  134  recognizes, for example, that baggage held by the occupant candidate is baggage candidate. The present invention is not limited thereto, and the object-to-be-loaded recognizer  134  may recognize that baggage held by the occupant candidate, baggage loaded on a cart pushed by the occupant candidate, or the like is the baggage candidate. The object-to-be-loaded recognizer  134  may recognize that baggage placed around a predetermined range including the occupant candidate is also the baggage candidate. 
     On the other hand, the object-to-be-loaded recognizer  134  may exclude an object present near the occupant candidate or the host vehicle M, which is a constantly present object (hereinafter referred to as an “installed object”) from the baggage candidates. The installed object includes, for example, a bollard, a sign, a pole, and a post. For example, the object-to-be-loaded recognizer  134  excludes an installed object included in an image captured by the outside-vehicle camera  10  from the baggage candidates on the basis of feature information of the installed object registered in advance. 
     When the baggage candidates have been recognized, the object-to-be-loaded recognizer  134  derives the number of baggage candidates. For example, the object-to-be-loaded recognizer  134  derives a total number of baggage included in the baggage candidates. Here, the object-to-be-loaded recognizer  134  may derive the number of baggage for each container or form such as a bag or a box. The present invention is not limited thereto, and the object-to-be-loaded recognizer  134  may derive the number for each of colors or sizes of the baggage. Thus, the object-to-be-loaded recognizer  134  may extract features of the baggage candidates and classify the baggage candidates for each of features (attributes). 
     The loading situation recognizer  136  recognizes that all of the objects to be loaded recognized by the object-to-be-loaded recognizer  134  have been loaded into the host vehicle M on the basis of, for example, information indicating a situation of the outside of the vehicle (for example, the image captured by the outside-vehicle camera  10 ) and information indicating a situation of the inside of the vehicle (for example, a detection result of the in-vehicle detector  70 ). Here, the loading situation recognizer  136  recognizes baggage not loaded into the host vehicle M as a forgotten thing. The loading situation recognizer  136  recognizes a person not loaded into the host vehicle M as a person left outside the vehicle. 
     For example, the loading situation recognizer  136  recognizes occupants who have boarded the host vehicle M on the basis of the detection result of the in-vehicle detector  70 . The loading situation recognizer  136  derives the number of occupants (hereinafter referred to as the number of detected persons inside the vehicle) who have boarded between a time when the boarding start operation has been executed and a time when a boarding completion operation is executed. The boarding start operation includes, for example, unlocking a door, and opening the door. The boarding completion operation includes locking a door, closing the door, and the like. The boarding start operation and the boarding completion operation may be an operation that is executed under the control of the automated driving control device  100  or an operation that is executed by an occupant. For example, the loading situation recognizer  136  derives the number of seats in use as the number of detected persons inside the vehicle on the basis of a detection result of a sensor that detects whether or not a seat belt is used or a seat pressure sensor. The loading situation recognizer  136  may recognize persons on the basis of an image obtained by imaging the inside of the vehicle, and set the number of recognized persons as the number of detected persons inside the vehicle. 
     When the number of occupant candidates (the number of detected persons outside the vehicle) derived by the object-to-be-loaded recognizer  134  matches the number of detected persons inside the vehicle, the loading situation recognizer  136  recognizes that all the occupant candidates have boarded. On the other hand, when the number of detected persons outside the vehicle does not match the number of detected persons inside the vehicle, the loading situation recognizer  136  recognizes that all of the occupant candidates have not boarded. Here, the loading situation recognizer  136  may determine whether persons included in the occupant candidates match persons who have boarded the host vehicle M on the basis of features classified by the object-to-be-loaded recognizer  134 . For example, when the number of detected persons outside the vehicle includes two adults and three children, the loading situation recognizer  136  may determine whether or not the number of detected persons inside the vehicle is 5 and the number of detected persons inside the vehicle matches the number of detected persons outside the vehicle. 
     The loading situation recognizer  136  recognizes the baggage loaded into the host vehicle M on the basis of the detection result of the in-vehicle detector  70 . The loading situation recognizer  136  derives the number of baggage (hereinafter referred to as the number of detected objects inside the vehicle) loaded between a time when the boarding operation has been executed and a time when the boarding complete operation is executed. For example, the loading situation recognizer  136  recognizes baggage on the basis of an image obtained by imaging the inside of the vehicle, and sets the number of recognized baggage as the number of detected objects inside the vehicle. 
     When the number of baggage candidates (the number of detected objects outside the vehicle) derived by the object-to-be-loaded recognizer  134  matches the number of detected objects inside the vehicle, the loading situation recognizer  136  recognizes that all the baggage candidates have been loaded. On the other hand, when the number of detected objects outside the vehicle does not match the number of detected objects inside the vehicle, the loading situation recognizer  136  recognizes that all the baggage candidates have not been loaded. Here, the loading situation recognizer  136  may determine whether the baggage included in the baggage candidates match the baggage loaded into the host vehicle M on the basis of the features classified by the object-to-be-loaded recognizer  134 . For example, when the number of detected objects outside the vehicle includes two paper bags and one cardboard object, the loading situation recognizer  136  may determine whether the number of detected objects inside the vehicle is 3 and matches the number of detected objects outside the vehicle. 
     The notification controller  150  controls the output so that the output notifies the occupant of the host vehicle M that the loading situation recognizer  136  has recognized that all of the objects to be loaded have not been loaded when the loading situation recognizer  136  has recognized that all of the objects to be loaded have not been loaded. For example, the notification controller  150  notifies the occupant, for example, that all of the occupant candidates have not boarded or that all the baggage candidates have not been loaded. The notification controller  150  causes the HMI  30  to output the fact to the inside of the vehicle by voice or image. By doing so, it is possible to notify the occupants that all the occupants are not present or that loading of baggage is likely to be forgotten. 
     The autonomous parking controller  142  permits the start of travel of the host vehicle M when the loading situation recognizer  136  has recognized that all the necessary objects have been loaded into the host vehicle M. After the autonomous parking controller  142  has permitted the start of travel of the host vehicle M, the autonomous parking controller  142  may start travel of the host vehicle M according to automated driving, or the travel driving force output device  200  or the like may start the travel of the host vehicle M on the basis of an operation amount input using the driving operator  80 . 
     Even when the loading situation recognizer  136  has recognized that all of the objects to be loaded have not been loaded, the autonomous parking controller  142  performs the start of travel of the host vehicle M in a case in which the start of travel of the host vehicle M has been permitted by the occupant of the host vehicle M. For example, when a travel start permission by the HMI  30  has been received from the occupant after the inside of the vehicle has been notified that all of the objects to be loaded have not been loaded by a voice or image using the HMI  30 , the autonomous parking controller  142  permits start of travel of the host vehicle M. The “travel start permission by the occupant” includes, for example, a case in which a button instructing the fact has been touched and a case in which speech such as “It is not my baggage” has been detected. 
     [Process Flow] 
       FIG. 5  is a flowchart showing an example of a process in which the occupant candidate is recognized by the object-to-be-loaded recognizer  134 . First, the object-to-be-loaded recognizer  134  determines whether a person satisfying the conditions of a regular user has been recognized (step S 101 ). When the person satisfying the conditions of a regular user is recognized, the object-to-be-loaded recognizer  134  adds the recognized person to the occupant candidates (step S 103 ). Then, the object-to-be-loaded recognizer  134  determines whether or not a regular companion has been recognized (step S 105 ). When the regular companion has been recognized, the object-to-be-loaded recognizer  134  adds the recognized regular companion to the occupant candidates (step S 107 ). The object-to-be-loaded recognizer  134  determines whether or not an exclusion target is included in the occupant candidates (step S 109 ). When an exclusion target is included in the occupant candidates, the object-to-be-loaded recognizer  134  excludes the exclusion target from the occupant candidates (step S 111 ). 
     Then, the object-to-be-loaded recognizer  134  determines whether or not the boarding completion operation has been executed (step S 113 ). When the boarding completion operation has not been executed, the object-to-be-loaded recognizer  134  returns to the process of step S 101  and repeats the process. When the boarding completion operation has been executed, the object-to-be-loaded recognizer  134  derives the number of occupant candidates (step S 115 ). The object-to-be-loaded recognizer  134  may further classify the occupant candidates according to features or attributes (step S 117 ). 
       FIG. 6  is a flowchart showing an example of a process in which the object-to-be-loaded recognizer  134  recognizes baggage candidates. This process is executed in parallel with the process described above with reference to  FIG. 5 . 
     First, the object-to-be-loaded recognizer  134  determines whether the occupant candidate has been recognized (step S 201 ). When the occupant candidate has been recognized, the object-to-be-loaded recognizer  134  adds, to the baggage candidates, an object considered to be loaded into the host vehicle M (step S 203 ). Then, the object-to-be-loaded recognizer  134  determines whether an installed object is included in the baggage candidates (step S 205 ). When the installed object is included in the baggage candidates, the object-to-be-loaded recognizer  134  excludes the installed object from the baggage candidates (step S 207 ). Then, the object-to-be-loaded recognizer  134  determines whether or not the baggage excluded as an exclusion target is included in the recognized baggage candidates (step S 209 ). When the baggage excluded as an exclusion target is included in the baggage candidates, the object-to-be-loaded recognizer  134  excludes the baggage relevant to the exclusion target (for example, baggage present around the exclusion target and added as the baggage candidate) from the baggage candidates (step S 211 ). 
     Then, the object-to-be-loaded recognizer  134  determines whether or not the boarding completion operation has been executed (step S 213 ). When the boarding completion operation has not been executed, the object-to-be-loaded recognizer  134  returns to the process of step S 201  and repeats the process. When the boarding completion operation has been executed, the object-to-be-loaded recognizer  134  derives the number of baggage candidates (step S 215 ). The object-to-be-loaded recognizer  134  may further classify the baggage candidates according to features or attributes (step S 217 ). 
       FIG. 7  is a flowchart showing an example of a process of the loading situation recognizer  136 . This process is executed in parallel with the process described above with reference to  FIGS. 5 and 6 . 
     The loading situation recognizer  136  determines whether or not the boarding start operation has been executed (step S 301 ). For example, when the host vehicle M stops at a stop position and the door is opened, the loading situation recognizer  136  determines that the boarding start operation has been executed. When the boarding start operation has been executed, the loading situation recognizer  136  recognizes an occupant who has boarded and baggage that has been loaded, on the basis of the detection result of the in-vehicle detector  70  (step S 303 ). The loading situation recognizer  136  determines whether or not the boarding completion operation has been executed (step S 305 ). When the boarding completion operation has not been executed, the loading situation recognizer  136  returns to step S 301  and repeats the process. When the boarding completion operation has been executed, the loading situation recognizer  136  derives each of the number of detected occupants inside the vehicle and the number of detected baggage inside the vehicle (step S 307 ). 
     The loading situation recognizer  136  determines whether or not the derived the number of detected persons inside the vehicle matches the number of detected persons outside the vehicle derived by the object-to-be-loaded recognizer  134  (step S 309 ). Here, the loading situation recognizer  136  may determine whether or not the number of detected persons inside the vehicle matches the number of detected persons outside the vehicle for each of the features or attributes of the persons. When the number of detected persons inside the vehicle matches the number of detected persons outside the vehicle, the loading situation recognizer  136  permits the autonomous parking controller  142  to start travel of the host vehicle M (step S 311 ). 
     On the other hand, when the number of detected persons inside the vehicle does not match the number of detected persons outside the vehicle in step S 311 , the notification controller  150  notifies the inside of the vehicle that all the persons are not present (step S 313 ). The loading situation recognizer  136  determines whether or not the occupant of the host vehicle M has permitted to the start of travel (step S 315 ). When the start of travel of the host vehicle M has been permitted by the occupant of the host vehicle M in step S 315 , the loading situation recognizer  136  determines whether the derived number of detected baggage inside the vehicle matches the number of detected baggage outside the vehicle derived by the object-to-be-loaded recognizer  134  (step S 317 ). Here, the loading situation recognizer  136  may determine whether or not the derived number of detected baggage inside the vehicle matches the number of detected baggage outside the vehicle for each of features or attributes of the baggage. When the derived number of detected baggage inside the vehicle matches the number of detected baggage outside the vehicle, the loading situation recognizer  136  permits the autonomous parking controller  142  to start travel of the host vehicle M (step S 311 ). 
     On the other hand, when the derived number of detected baggage inside the vehicle does not match the number of detected baggage outside the vehicle in step S 317 , the notification controller  150  notifies the inside of the vehicle that loading of baggage is likely to be forgotten (step S 319 ). Then, the loading situation recognizer  136  determines whether or not the occupant of the host vehicle M has permitted to the start of travel (step S 321 ). When the start of travel of the host vehicle M has been permitted by the occupant of the host vehicle M in step S 321 , the loading situation recognizer  136  instructs the autonomous parking controller  142  to start of travel of the host vehicle M (step S 311 ). The present invention is not limited to this process flow, and the loading situation recognizer  136  has performed confirmation of matching of the numbers of persons and matching of the baggage in parallel, and then, the notification controller  150  may notify the inside of the vehicle that persons or baggage is not present, such that an operation of permitting the start of travel from the occupant can be performed once. 
     The present invention is not limited thereto, and the loading situation recognizer  136  may recognize that all of the objects to be loaded have not been loaded into the host vehicle M, on the basis of, for example, the image captured by the outside-vehicle camera  10 . For example, the loading situation recognizer  136  recognizes that all the objects to be loaded have been loaded into the host vehicle M on the basis of information indicating the surroundings situation of the outside of the vehicle before the boarding and information indicating the surroundings situation of the outside of the vehicle after the boarding completion operation. The loading situation recognizer  136  recognizes a person or baggage present in a wide range around the host vehicle M as the surroundings situation of the host vehicle M before the boarding and recognizes a person or baggage present in a narrow range around the host vehicle M as the surroundings situation of the host vehicle M after the boarding completion operation. The loading situation recognizer  136  recognizes the surroundings situation of the host vehicle M after the boarding completion operation on the basis of, for example, an image obtained by imaging the vicinity of the door of the host vehicle M. When a person or baggage having the same feature as the occupant candidate or baggage candidate recognized before boarding has not been recognized near the door after the boarding completion operation, the loading situation recognizer  136  recognizes that all of the objects to be loaded are loaded into the host vehicle M. A recognition target of the loading situation recognizer  136  is not limited thereto. For example, when the person or baggage having the same feature as the occupant candidate or baggage candidate recognized before boarding has been recognized near the door after the boarding completion operation, the loading situation recognizer  136  may recognize that the occupant has not boarded or that the baggage has not been loaded. 
     In the above-described process, the loading situation recognizer  136  determines whether or not the boarding or loading of the occupant candidate or the baggage candidate recognized outside the vehicle has been completed on the basis of a detection result of an in-vehicle situation. The present invention is not limited thereto, and the loading situation recognizer  136  may determine whether or not the boarding or loading of the occupant candidate or baggage candidate recognized outside the vehicle has been completed on the basis of a recognition result of the outside of the vehicle without referring to a detection result of the in-vehicle situation. Hereinafter, an example of this process will be described with reference to  FIG. 8 .  FIG. 8  is a flowchart showing another example of the process of the loading situation recognizer  136 . This process is executed in parallel with the process described above with reference to  FIGS. 5 and 6 . 
     The loading situation recognizer  136  determines whether or not the boarding completion operation has been executed (step S 401 ). When the boarding completion operation has been executed, the loading situation recognizer  136  recognizes a surroundings situation of the outside of the vehicle after the boarding completion operation (step S 403 ). The loading situation recognizer  136  determines whether or not the occupant candidate or the baggage candidate recognized by the object-to-be-loaded recognizer  134  has been recognized outside the vehicle after the boarding completion operation (step S 405 ). When the occupant candidate or the baggage candidate has not been recognized outside the vehicle, the loading situation recognizer  136  instructs the autonomous parking controller  142  to start of travel of the host vehicle M (step S 407 ). 
     On the other hand, when the occupant candidate or the baggage candidate has been recognized outside the vehicle in step S 405 , the notification controller  150  notifies the inside of the vehicle of the fact (for example, all the occupants are not present or that loading of baggage is likely to be forgotten) (step S 409 ). The loading situation recognizer  136  determines whether or not the occupant of the host vehicle M has permitted the start of travel (step S 411 ). When the start of travel of the host vehicle M has been permitted by the occupant of the host vehicle M in step S 411 , the autonomous parking controller  142  permits the start of travel of the host vehicle M (step S 407 ). 
     The present invention is not limited thereto, and the loading situation recognizer  136  may recognize the surroundings situation of the host vehicle M on the basis of an image at the same viewpoint. The image at the same viewpoint includes, for example, an image captured by the outside-vehicle camera  10 , which is a bird&#39;s eye image of the host vehicle M as if the host vehicle M is looked down from above. 
     The loading situation recognizer  136  recognizes the surroundings situation of the host vehicle M on the basis of, for example, a bird&#39;s eye image captured immediately before the host vehicle M stops at the stop position or between the stop of the host vehicle M and arrival of the occupant candidate. The loading situation recognizer  136  recognizes the surroundings situation of the host vehicle M after the boarding completion operation on the basis of, for example, a bird&#39;s eye image captured after the occupant has boarded the host vehicle M. When a person or baggage, which is not present in a surroundings situation of the host vehicle M before boarding, appears in the surroundings situation of the host vehicle M after the boarding completion operation, the loading situation recognizer  136  recognizes whether all of the objects to be loaded have not been loaded. 
       FIG. 9  is a flowchart showing another example of the process of the loading situation recognizer  136 . The loading situation recognizer  136  determines whether or not the host vehicle M has approached the stop position (step S 501 ). For example, when the vehicle has entered the stop area  310 , the loading situation recognizer  136  determines that the host vehicle M has approached the stop position. 
     When the host vehicle M has approached the stop position, the loading situation recognizer  136  recognizes the surroundings situation of the outside of the vehicle on the basis of a bird&#39;s eye image before boarding (step S 503 ). For example, the loading situation recognizer  136  recognizes an installed object, baggage, or the like around the host vehicle M. Then, the loading situation recognizer  136  determines whether or not the host vehicle M has stopped (step S 505 ). The loading situation recognizer  136  repeats the process of step S 503  until the host vehicle M stops. 
     When the host vehicle M stops, the loading situation recognizer  136  determines whether or not the boarding completion operation has been executed (step S 507 ). When the boarding completion operation has been executed, the loading situation recognizer  136  recognizes the surroundings situation of the outside of the vehicle on the basis of a bird&#39;s eye image after the boarding completion operation (step S 509 ). The loading situation recognizer  136  determines whether or not there is a person or an object left outside the vehicle after the boarding completion operation on the basis of a comparison result between a recognition result before the boarding in step S 503  and a recognition result after the boarding completion operation in step S 509  (step S 511 ). The loading situation recognizer  136  may extract a difference between the bird&#39;s eye images and detect a remaining person or object and may determine whether a person or object recognized after the boarding completion operation is present before the boarding. When there is no person or object left outside the vehicle after the boarding completion operation, the autonomous parking controller  142  permits start of travel of the host vehicle M (step S 513 ). 
     On the other hand, when there is a person or object left outside the vehicle after the boarding completion operation in step S 511 , the notification controller  150  notifies the inside of the vehicle of the fact (for example, all the occupants are not present or that loading of baggage is likely to be forgotten) (step S 515 ). The loading situation recognizer  136  determines whether or not the occupant of the host vehicle M has permitted the start of travel (step S 517 ). When the start of travel of the host vehicle M has been permitted by the occupant of the host vehicle M in step S 517 , the autonomous parking controller  142  permits the start of travel of the host vehicle M (step S 513 ). 
     When a specific item has been recognized near the door of the host vehicle M after the boarding completion operation, the loading situation recognizer  136  may recognize that all of the objects to be loaded have not been loaded. The specific item includes, for example, shoes, socks, hats, gloves, and umbrellas. The specific item may be registered in advance or set by the user. Baggage recognized as a “left-behind object” before a previous time may be registered as the specific item. 
     Conclusion of Embodiment 
     As described above, the automated driving control device  100  according to the present embodiment includes a recognizer  130  configured to recognize at least a surroundings situation and an in-vehicle situation of a vehicle; a driving controller ( 140 ,  160 ) configured to perform at least one of speed control and steering control of the vehicle on the basis of a recognition result of the recognizer  130 , wherein the recognizer  130  recognizes an object to be loaded including at least any one of an occupant candidate present outside the vehicle and scheduled to board the vehicle and a baggage candidate present outside the vehicle and scheduled to be loaded into the vehicle, and recognizes that the object to be loaded has been loaded into the vehicle, and the driving controller permits start of travel of the vehicle when the recognizer  130  has recognized that the object to be loaded has been loaded into the vehicle, thereby preventing forgetting to load baggage or persons to board from being left outside the vehicle at the start of automated driving. 
     [Hardware Configuration] 
       FIG. 10  is a diagram showing an example of a hardware configuration of the automated driving control device  100  according to the embodiment. As shown in  FIG. 14 , the automated driving control device  100  has a configuration in which a communication controller  100 - 1 , a CPU  100 - 2 , a random access memory (RAM)  100 - 3  that is used as a working memory, a read only memory (ROM)  100 - 4  that stores a boot program or the like, a storage device  100 - 5  such as a flash memory or a hard disk drive (HDD), a drive device  100 - 6 , and the like are connected to each other by an internal bus or a dedicated communication line. The communication controller  100 - 1  communicates with components other than the automated driving control device  100 . A program  100 - 5   a  to be executed by the CPU  100 - 2  is stored in the storage device  100 - 5 . This program is developed in the RAM  100 - 3  by a direct memory access (DMA) controller (not shown) or the like and executed by the CPU  100 - 2 . Thereby, one or both of the first controller  120  and the second controller  160  are realized. 
     The embodiments described above can be represented as follows. 
     A vehicle control device includes a storage device storing a program, and a hardware processor configured to execute the program to recognize at least a surroundings situation of a vehicle, perform speed control and steering control of the vehicle without depending on an operation of an occupant on the basis of a recognition result, recognize an object to be loaded including at least any one of an occupant candidate to board the vehicle and a baggage candidate p scheduled to be loaded into the vehicle, recognize that the object to be loaded has been loaded into the vehicle, and permit start of travel of the vehicle when it has been recognized that the object to be loaded has been loaded into the vehicle. 
     While forms for carrying out the present invention have been described using the embodiments, the present invention is not limited to these embodiments at all, and various modifications and substitutions can be made without departing from the gist of the present invention.