Patent Publication Number: US-2022212630-A1

Title: Information processing device, vehicle control device, information processing method, and program

Description:
TECHNICAL FIELD 
     The present invention relates to an information processing device, a vehicle control device, an information processing method, and a program. 
     BACKGROUND ART 
     A technique of deterring vehicle theft by, on condition that a hood that opens and closes a battery housing chamber is closed, capturing an image of the outside of the closed hood with an in-vehicle camera and transmitting the image captured by the in-vehicle camera to a database of a theft tracking service provider or the like is known (see, for example, Patent Literature 1). 
     CITATION LIST 
     Patent Literature 
     [Patent Literature 1] 
     Japanese Unexamined Patent Application, First Publication No. 2016-52847 
     SUMMARY OF INVENTION 
     Technical Problem 
     However, in the related art, unauthorized use of a vehicle such as theft cannot be accurately detected in some cases. 
     The present invention was contrived in view of such circumstances, and one object thereof is to provide an information processing device, a vehicle control device, an information processing method, and a program that make it possible to accurately detect unauthorized use of a vehicle. 
     Solution to Problem 
     The following configurations are adopted in an information processing device, a vehicle control device, an information processing method, and a program according to the present invention. 
     (1) According to an aspect of the present invention, an information processing device is provided including: an acquirer that acquires first data indicating a use situation of a target vehicle and second data indicating a use situation of a battery mounted in the target vehicle; and a determiner that, when the first data and the second data of a certain vehicle are input, inputs the first data and the second data acquired by the acquirer into a classifier learned to output third data indicating the presence or absence of unauthorized use of the certain vehicle and determines whether the target vehicle has been unauthorized used on the basis of the third data output by the classifier into which the first data and the second data are input. 
     (2) The information processing device according to the aspect of the above (1) further includes: a communicator that communicates with a terminal device of an owner of the target vehicle; and a communication controller that, in a case where the determiner determines that the target vehicle has been unauthorized used, transmits first information prompting the owner to confirm the target vehicle to the terminal device through the communicator. 
     (3) The information processing device according to the aspect of the above (2) further includes a remote controller that remotely controls the target vehicle through the communicator in a case where the communicator does not receive second information which is a response to the first information from the terminal device after the first information is transmitted to the terminal device and before a predetermined time elapses. 
     (4) In the information processing device according to the aspect of the above (2) or (3), the acquirer further acquires biometric information of a user who uses the target vehicle, the information processing device further comprises an authenticator that authenticates that the user who uses the target vehicle is an owner of the target vehicle on the basis of the biometric information acquired by the acquirer, and the communication controller transmits the first information to the terminal device in a case where the authenticator does not authenticate that the user is the owner and the determiner determines that the target vehicle has been unauthorized used, and does not transmit the first information to the terminal device in a case where the authenticator authenticates that the user is the owner or a case where the determiner does not determine that the target vehicle has been unauthorized used. 
     (5) The information processing device according to the aspect of the above (1) further includes: a communicator that communicates with the target vehicle; and a remote controller that remotely controls the target vehicle through the communicator in a case where the determiner determines that the target vehicle has been unauthorized used. 
     (6) The information processing device according to any aspect of the above (1) to (5) further includes a learner that learns the classifier on the basis of the first data and the second data of an unauthorized used vehicle. 
     (7) According to another aspect of the present invention, a vehicle control device is provided including: at least one battery mounted in a target vehicle; a controller that causes the target vehicle to travel using electric power accumulated in the battery; an acquirer that acquires first data indicating a use situation of the target vehicle and second data indicating a use situation of the battery; and a determiner that, when the first data and the second data of a certain vehicle are input, inputs the first data and the second data acquired by the acquirer into a classifier learned to output third data indicating the presence or absence of unauthorized use of the certain vehicle and determines whether the target vehicle has been unauthorized used on the basis of the third data output by the classifier into which the first data and the second data are input. 
     (8) According to another aspect of the present invention, an information processing method is provided including causing a computer to: acquire first data indicating a use situation of a target vehicle and second data indicating a use situation of a battery mounted in the target vehicle; and when the first data and the second data of a certain vehicle are input, input the acquired first data and second data into a classifier learned to output third data indicating the presence or absence of unauthorized use of the certain vehicle and determine whether the target vehicle has been unauthorized used on the basis of the third data output by the classifier into which the first data and the second data are input. 
     (9) According to another aspect of the present invention, a program is provided for causing a computer to execute: a process of acquiring first data indicating a use situation of a target vehicle and second data indicating a use situation of a battery mounted in the target vehicle; and a process of, when the first data and the second data of a certain vehicle are input, inputting the acquired first data and second data into a classifier learned to output third data indicating the presence or absence of unauthorized use of the certain vehicle and determining whether the target vehicle has been unauthorized used on the basis of the third data output by the classifier into which the first data and the second data are input. 
     Advantageous Effects of Invention 
     According to any aspect of (1) to (9), it is possible to accurately detect unauthorized use of a vehicle. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG. 1  is a diagram illustrating a configuration example of an unauthorized use detection system  1  including an information processing device and a vehicle control device according to a first embodiment. 
         FIG. 2  is a diagram illustrating an example of a configuration of a vehicle  10  according to the first embodiment. 
         FIG. 3  is a diagram illustrating an interior configuration of the vehicle  10  according to the first embodiment. 
         FIG. 4  is a diagram illustrating an example of a configuration of a center server  100  according to the first embodiment. 
         FIG. 5  is a flowchart illustrating a flow of a series of processes of runtime performed by a controller  120  in the first embodiment. 
         FIG. 6  is a diagram schematically illustrating a classifier MDL. 
         FIG. 7  is a flowchart illustrating a flow of a series of processes of training performed by the controller  120  in the first embodiment. 
         FIG. 8  is a diagram illustrating an example of a PCU  30 X according to a second embodiment. 
         FIG. 9  is a diagram illustrating an example of hardware configurations of a PCU  30  and the center server  100  according to an embodiment. 
     
    
    
     DESCRIPTION OF EMBODIMENTS 
     Hereinafter, embodiments of an information processing device, a vehicle control device, an information processing method, and a program of the present invention will be described with reference to the accompanying drawings. In the following description, a vehicle  10  is assumed to be an electric automobile, but the vehicle  10  is preferably a vehicle equipped with a secondary battery that supplies electric power for traveling, and may be a hybrid automobile or a vehicle equipped with a fuel cell. 
     First Embodiment 
     [Overall Configuration] 
       FIG. 1  is a diagram illustrating a configuration example of an unauthorized use detection system  1  including an information processing device and a vehicle control device according to a first embodiment. The unauthorized use detection system  1  is a system that detects that the vehicle  10  which is an electric automobile has been unauthorized used. Unauthorized use includes, for example, stealing the vehicle  10 , removing a battery (which is hereinafter assumed to be synonymous with a secondary battery) from the vehicle  10 , driving the vehicle  10  without an owner&#39;s permission, or the like. 
     As shown in  FIG. 1 , the unauthorized use detection system  1  includes a plurality of vehicles  10 , a plurality of terminal devices  200 , and a center server  100 . The vehicle  10 , the center server  100 , and the terminal device  200  communicate with each other through a network NW. The network NW includes, for example, the Internet, a wide area network (WAN), a local area network (LAN), a provider device, a wireless base station, or the like. 
     The center server  100  detects that each of the plurality of vehicles  10  has been unauthorized used on the basis of information transmitted by each of the vehicles  10 . 
     Each of the plurality of terminal devices  200  is a terminal device that can be used by an owner of each of the vehicles  10 . Typically, the terminal device  200  is a mobile phone or a tablet terminal including a touch panel that also serves as a user interface and a display, a wireless communication interface having an antenna or the like, a storage, and an arithmetic unit such as a central processing unit (CPU). 
     In the terminal device  200 , a user agent (UA) such as a web browser or an application program is started up. The terminal device  200  in which the UA is started up accepts various input operations from a user and performs various processes in accordance with the accepted input operations. The terminal device  200  may include devices such as a fingerprint sensor, a microphone, and a camera. In this case, the terminal device  200  may transmit biometric information such as an owner&#39;s fingerprint detected by a fingerprint sensor, the owner&#39;s voice collected by a microphone, or the owner&#39;s face image captured by a camera to the center server  100  through the network NW. 
     [Configuration of Vehicle] 
       FIG. 2  is a diagram illustrating an example of a configuration of the vehicle  10  according to the first embodiment. As shown in  FIG. 2 , the vehicle  10  includes, for example, a motor  12 , a driving wheel  14 , a brake device  16 , a vehicle sensor  20 , a driving operation sensor  22 , a biometric sensor  24 , a power control unit (PCU)  30 , a battery  40 , a battery sensor  42 , a communication device  50 , a display device  60 , a charging port  70 , and a converter  72 . 
     The motor  12  is, for example, a three-phase AC electric motor. The rotor of the motor  12  is connected to the driving wheel  14 . The motor  12  outputs motive power to the driving wheel  14  using electric power to be supplied. The motor  12  generates power using kinetic energy of the vehicle during deceleration of the vehicle. 
     The brake device  16  includes, for example, a brake caliper, a cylinder that transfers hydraulic pressure to the brake caliper, and an electric motor that generates hydraulic pressure in the cylinder. The brake device  16  may include a mechanism that transfers hydraulic pressure generated by the operation of a brake pedal to the cylinder through a master cylinder as a backup. The brake device  16  is not limited to the above-described configuration and may be an electronic control hydraulic brake device that transfers hydraulic pressure of the master cylinder to the cylinder. 
     The vehicle sensor  20  includes, for example, an accelerator position sensor, a vehicle speed sensor, a brake stepping amount sensor, a steering sensor, a global navigation satellite system (GNSS) sensor, a yaw rate sensor, an orientation sensor, or the like. 
     The accelerator position sensor is attached to an accelerator pedal, and detects the amount of operation of the accelerator pedal. The accelerator position sensor outputs a signal indicating the detected amount of operation as an accelerator position to a controller  36 . 
     The vehicle speed sensor includes, for example, a plurality of wheel speed sensors and a speed calculator. Each of the plurality of wheel speed sensors is attached to one wheel. The wheel speed sensor detects the speed or acceleration of the attached wheel. The speed calculator statistically calculates the speed or acceleration detected by the plurality of wheel speed sensors and calculates the speed or acceleration of the vehicle  10 . The vehicle speed sensor outputs a signal indicating the calculated speed or acceleration of the vehicle  10  to the controller  36  and the display device  60 . 
     The brake stepping amount sensor is attached to the brake pedal and detects the amount of operation of the brake pedal. The brake stepping amount sensor outputs a signal indicating the detected amount of operation as a brake stepping amount to the controller  36 . 
     The steering sensor is attached to a steering wheel and detects the amount of operation of the steering wheel. For example, the steering sensor detects a weak electrical current generated by an occupant touching the steering wheel. The steering sensor may detect a steering torque generated around the rotating shaft (shaft) of the steering wheel. When the steering sensor detects a current or steering torque, it outputs a signal indicating the detection result to the controller  36 . 
     The GNSS sensor receives a signal from a GNSS satellite such as a Global Positioning System (GPS) satellite, and detects the position of the vehicle  10  on the basis of the received signal. The GNSS sensor may correct the detected position of the vehicle  10  using an inertial navigation system (INS) that uses the output of the vehicle speed sensor, the yaw rate sensor, or the like. The GNSS sensor outputs a signal indicating the detected position of the vehicle  10  to the controller  36 . 
     The yaw rate sensor detects the angular velocity of the vehicle  10  around its vertical axis. The yaw rate sensor outputs a signal indicating the detected angular velocity as a yaw rate to the controller  36 . 
     The orientation sensor detects the direction of the vehicle  10 . The orientation sensor outputs a signal indicating the detected direction as an orientation to the controller  36 . 
     The biometric sensor  24  detects biometric information of a driver of the vehicle  10 . For example, the biometric sensor  24  detects information such as a fingerprint, palm print, iris, vein, face image, or voice of the driver. In the case where a fingerprint or a palm print is detected, the biometric sensor  24  may be provided on the steering wheel. The biometric sensor  24  outputs the detected biometric information to the controller  36 . 
     The PCU  30  includes, for example, a converter  32 , a voltage control unit (VCU)  34 , the controller  36 , and a storage  38 . In the shown example, these components are configured as one unit as the PCU  30 , but the present invention is not limited to this, and a plurality of components may be disposed in a distributed manner. 
     The converter  32  is, for example, an AC-DC converter. The direct-current side terminal of the converter  32  is connected to a direct-current link DL. The battery  40  is connected to the direct-current link DL through the VCU  34 . The converter  32  converts an alternating current generated by the motor  12  into a direct current and outputs the converted current to the direct-current link DL. 
     The VCU  34  is, for example, a DC-DC converter. The VCU  34  boosts electric power which is supplied from the battery  40  and outputs the boosted electric power to the direct-current link DL. 
     The controller  36  includes, for example, a motor controller  36 A, a brake controller  36 B, a battery/VCU controller  36 C, and a communication controller  36 D. The motor controller  36 A, the brake controller  36 B, the battery/VCU controller  36 C, and the communication controller  36 D may be replaced with separate control devices. The separate control devices are, for example, a motor electronic control unit (ECU), a brake ECU, and a battery ECU. 
     Some or all of the components of the controller  36  are realized by a processor such as, for example, a central processing unit (CPU) or a graphics processing unit (GPU) executing a program (software). In addition, some or all of these components may be realized by hardware (circuit unit; including circuitry) such as a large scale integration (LSI), an application specific integrated circuit (ASIC), or a field-programmable gate array (FPGA) and may be realized by software and hardware in cooperation. The program may be stored in an HDD, a flash memory, or the like of the storage  38  in advance or may be stored in a detachable storage medium such as a DVD or a CD-ROM and be installed in the storage  38  by the storage medium being mounted in a drive device. 
     The motor controller  36 A controls the motor  12  on the basis of the output of the vehicle sensor  20 . The brake controller  36 B controls the brake device  16  on the basis of the output of the vehicle sensor  20 . 
     The battery/VCU controller  36 C calculates the state of charge (SOC) of the battery  40  on the basis of the output of the battery sensor  42  attached to the battery  40 . In the case where the calculated SOC of the battery  40  is equal to or higher than a threshold, the battery/VCU controller  36 C instructs the VCU  34  to increase the voltage of the direct-current link DL. 
     The communication controller  36 D controls the communication device  50  and transmits data indicating a feature of behavior of the vehicle  10  under manual driving (hereinafter referred to as vehicle feature data), data indicating a feature of operation of the battery  40  used under manual driving (hereinafter referred to as battery feature data), and biometric information detected by the biometric sensor  24  to the center server  100  through the network NW. 
     The vehicle feature data includes information such as, for example, the detection result of the vehicle sensor  20 , a vehicle ID for identifying the vehicle  10 , the vehicle model of the vehicle  10 , the size of the vehicle  10 , position information of the vehicle  10 , and the time. The battery feature data includes information such as, for example, the SOC of the battery  40  calculated by the battery/VCU controller  36 C, the detection result of the battery sensor  42 , a battery ID for identifying the battery  40 , the capacity of the battery  40 , the nominal voltage of the battery  40 , the type of battery  40 , and the time. 
     The storage  38  is realized by, for example, an HDD, a flash memory, electrically erasable programmable read only memory (EEPROM), read only memory (ROM), random access memory (RAM), or the like. The storage  38  stores, for example, a program or the like which is read out and executed by a processor. 
     The battery  40  is a secondary battery such as, for example, a lithium-ion battery. The battery  40  accumulates electric power introduced from a charger  210  outside of the vehicle  10  and discharges electric power accumulated for traveling of the vehicle  10 . 
     The battery sensor  42  includes, for example, a current sensor, a voltage sensor, and a temperature sensor. The battery sensor  42  detects, for example, the current value, voltage value, and temperature of the battery  40 . The battery sensor  42  outputs the detected current value, voltage value, temperature, and the like to the controller  36 . 
     The communication device  50  includes a wireless module for connection to the network NW. The communication device  50  transmits various types of information such as the vehicle feature data or the battery feature data to the center server  100  in accordance with an instruction of the controller  36 . The communication device  50  receives information from the center server  100  through the network NW. The communication device  50  outputs the received information to the controller  36  or the display device  60 . 
     The display device  60  includes a first display  60 A and a second display  60 B. 
     The first display  60 A and the second display  60 B are, for example, liquid crystal displays (LCDs), organic electro luminescence (EL) display devices, or the like. The first display  60 A and the second display  60 B display information output by the controller  36  or information received from the center server  100  by the communication device  50 . 
     The charging port  70  is provided toward the outside of the body of the vehicle  10 . The charging port  70  is connected to the charger  210  through a charging cable  220 . The charging cable  220  includes a first plug  222  and a second plug  224 . The first plug  222  is connected to the charger  210 , and the second plug  224  is connected to the charging port  70 . Electricity supplied from the charger  210  is supplied to the charging port  70  through the charging cable  220 . 
     In addition, the charging cable  220  includes a signal cable attached to a power cable. The signal cable mediates communication between the vehicle  10  and the charger  210 . Therefore, each of the first plug  222  and the second plug  224  is provided with a power connector and a signal connector. 
     The converter  72  is provided between the charging port  70  and the battery  40 . The converter  72  converts a current introduced from the charger  210  through the charging port  70 , for example, an alternating current into a direct current. The converter  72  outputs the converted direct current to the battery  40 . 
       FIG. 3  is a diagram illustrating an interior configuration of the vehicle  10  according to the first embodiment. As shown in  FIG. 3 , the vehicle  10  is provided with, for example, a steering wheel  91 , a front windshield  92 , and an instrument panel  93 . The front windshield  92  is a light-transmissive member. 
     The first display  60 A is provided in the vicinity of the front of a driver&#39;s seat (a seat closest to the steering wheel  91 ) in the instrument panel  93  and is installed at a position that can be visually recognized by an occupant from a gap in the steering wheel  91  or over the steering wheel  91 . 
     The second display  60 B is installed, for example, at the center of the instrument panel  93 . The second display  60 B, for example, displays a navigation result of a navigation device (not shown) as an image, displays a television program, plays a DVD, or displays content such as a downloaded movie. 
     [Configuration of Center Server] 
       FIG. 4  is a diagram illustrating an example of a configuration of the center server  100  according to the first embodiment. As shown in  FIG. 4 , the center server  100  includes, for example, a communicator  110 , a controller  120 , and a storage  150 . 
     The communicator  110  includes a communication interface such as, for example, an antenna or a network interface card (NIC). The communicator  110  communicates with each of the plurality of vehicles  10  through the network NW. For example, the communicator  110  receives the vehicle feature data and the battery feature data from each of the vehicles  10 . 
     The controller  120  includes, for example, an acquirer  122 , an authenticator  124 , a determiner  126 , a communication controller  128 , a remote controller  130 , and a learner  132 . Processing of each of these components will be described later. 
     Some or all of these components of the controller  120  are realized by a processor such as, for example, a CPU or a GPU executing a program (software). In addition, some or all of these components may be realized by hardware (a circuit unit; 
     including circuitry) such as an LSI, an ASIC, or an FPGA, or may be realized by software and hardware in cooperation. 
     The program may be stored in the HDD, flash memory, or the like of the storage  150  in advance, may be stored in a detachable storage medium such as a DVD or a CD-ROM or may be installed in the storage  150  by the storage medium being mounted in a drive device. 
     The storage  150  is realized by, for example, an HDD, a flash memory, an EEPROM, a ROM, a RAM, or the like. The storage  150  stores, for example, authentication information  152 , classifier information  154 , or the like in addition to a program which is read out and executed by a processor. 
     The authentication information  152  is, for example, a database in which biometric information of a user (such as, for example, an owner of the vehicle  10 ) determined in advance is registered with respect to a vehicle ID of each of the vehicles  10 . 
     The classifier information  154  is information (a program or data structure) that defines a classifier MDL for performing pattern classification as to whether the vehicle  10  is being unauthorized used or not being unauthorized used. The details of the classifier MDL will be described later. 
     [Process Flow at Runtime] 
     Hereinafter, a flow of a series of processes of the controller  120  at runtime will be described with reference to a flowchart. The term “runtime” refers to a time at which various processes are executed using the already learned classifier MDL.  FIG. 5  is a flowchart illustrating a flow of a series of processes of runtime performed by the controller  120  in the first embodiment. The processing of the present flowchart may be repeatedly performed, for example, at a predetermined cycle. 
     First, the acquirer  122  acquires the vehicle feature data, the battery feature data, and the biometric information from the vehicle  10  through the communicator  110  (step S 100 ). The acquirer  122  may acquire the biometric information from the terminal device  200  owned by the owner of the vehicle  10  or the like instead of acquiring the biometric information from the vehicle  10 . In the following description, the vehicle  10  that has transmitted at least the vehicle feature data and the battery feature data to the center server  100  is referred to as a target vehicle  10 T. 
     Next, the authenticator  124  determines whether the biometric authentication of a driver of the target vehicle  10 T is successful on the basis of the biometric information acquired by the acquirer  122  and the authentication information  152  (step S 102 ). 
     For example, the authenticator  124  determines whether the biometric information acquired by the acquirer  122  and biometric information included in the authentication information  152  coincide with each other. In a case where the biometric information acquired by the acquirer  122  and the biometric information included in the authentication information  152  coincide with each other, the authenticator  124  determines that the biometric authentication of the driver of the target vehicle  10 T is successful. 
     On the other hand, in a case where the biometric information acquired by the acquirer  122  and the biometric information included in the authentication information  152  do not coincide with each other, or a case where the biometric information is not acquired by the acquirer  122 , the authenticator  124  determines that the biometric authentication of the driver of the target vehicle  10 T has failed. 
     In a case where the biometric authentication of the driver of the target vehicle  10 T is successful, the controller  120  ends the processing of the present flowchart. 
     On the other hand, in a case where the biometric authentication of the driver of the target vehicle  10 T has failed, the determiner  126  inputs the vehicle feature data and the battery feature data acquired by the acquirer  122  into the classifier MDL indicated by the classifier information  154  (step S 104 ). 
       FIG. 6  is a diagram schematically illustrating the classifier MDL. As in the shown example, the classifier MDL may be realized using a deep neural network. The classifier MDL is not limited to a deep neural network, and may be realized by other models such as logistic regression, Support Vector Machine (SVM), k-Nearest Neighbor algorithm (k-NN), decision tree, Naïve Bayes classifier, or Random Forest. 
     In a case where the classifier MDL is realized by a deep neural network, the deep neural network may be, for example, a convolutional neural network or a recurrent neural network. 
     In a case where the classifier MDL is a deep neural network, the classifier information  154  includes various types of information such as, for example, connection information on how neurons (units) included in an input layer, one or more hidden layers (intermediate layers), and an output layer that constitute each neural network are connected to each other, or connection coefficients imparted to data which is input and output between connected neurons. 
     The connection information includes, for example, the number of neurons included in each layer, information for designating the type of neuron to which each neuron is connected, an activation function of realizing each neuron, and information such as a gate provided between neurons in the hidden layer. 
     The activation function of realizing neurons may be, for example, a rectified linear unit function (ReLU function), a sigmoid function, a step function, other functions, or the like. 
     The gate selectively passes or weights data transferred between neurons, for example, in accordance with a value (for example,  1  or  0 ) returned by the activation function. 
     The connection coefficient is a parameter of the activation function and includes a weight imparted to output data when data is output from a neuron in a certain layer to a neuron in a deeper layer, for example, in a hidden layer of a neural network. In addition, the connection coefficient may include a bias component or the like peculiar to each layer. 
     For example, when the vehicle feature data and the battery feature data as described above are input, the classifier MDL outputs a probability indicating the likelihood of the target vehicle  10 T having been unauthorized used. Specifically, in a case where a probability indicating that the target vehicle  10 T is unauthorized used is P1, a probability indicating that the target vehicle  10 T is not unauthorized used is P2, and the sum of P1 and P2 is 1, the classifier MDL outputs a vector V (=[e1, e2]) in which the probability P1 is included as an element e1 and the probability P2 is included as an element e2. The vector V is an example of “third data.” 
     The flowchart of  FIG. 5  will be described again. Next, the determiner  126  acquires the classification result (vector V) from the classifier MDL into which the vehicle feature data and the battery feature data of the target vehicle  10 T are input (step S 106 ). 
     Next, the determiner  126  determines whether the target vehicle  10 T has been unauthorized used on the basis of the classification result of the classifier MDL (step S 108 ). 
     For example, when the vector V indicating the probability of unauthorized use is output by the classifier MDL, the determiner  126  determines whether unauthorized use has occurred on the basis of the value of each element included in the vector V. Specifically, in a case where the value of the element e1, that is, the probability P1, is equal to or greater than a threshold, the determiner  126  determines that the target vehicle  10 T has been unauthorized used. 
     In a case where the determiner  126  determines that the target vehicle  10 T has been unauthorized used, the communication controller  128  transmits confirmation information to the terminal device  200  owned by the owner of the target vehicle  10 T through the communicator  110  (step S 110 ). The confirmation information is information for prompting the owner of the target vehicle  10 T to confirm whether the target vehicle  10 T has been unauthorized used. The confirmation information is an example of “first information.” 
     Next, the remote controller  130  determines whether the communicator  110  has received reply information from the terminal device  200  to which the confirmation information has been transmitted after the confirmation information is transmitted to the terminal device  200  owned by the owner of the target vehicle  10 T and before a predetermined time (for example, an hour) elapses (step S 112 ). The reply information is information indicating that the owner of the target vehicle  10 T has made some kind of reply (for example, a reply that the target vehicle  10 T has not been unauthorized used) to the confirmation information. The reply information is an example of “second information.” 
     For example, in a case where the communicator  110  does not receive the reply information before a predetermined time elapses, the remote controller  130  remotely controls the target vehicle  10 T by transmitting a control command to the target vehicle  10 T through the communicator  110  (step S 114 ). This concludes the processing of the present flowchart. 
     For example, the remote controller  130  transmits a stop command for stopping the target vehicle  10 T or a function restriction command for restricting some functions of the target vehicle  10 T to the target vehicle  10 T. 
     For example, in a case where the stop command is received by the communication device  50 , the controller  36  of the target vehicle  10 T controls the motor  12 , the brake device  16 , the converter  32 , the VCU  34 , or the like to decelerate and stop the target vehicle  10 T. 
     In addition, for example, in a case where the function restriction command is received by the communication device  50 , the controller  36  of the target vehicle  10 T restricts displaying various types of information on the display device  60  or controls the converter  72  to restrict charging the battery  40  with electric power supplied from the charging port  70 . 
     [Process Flow of Training] 
     Next, a flow of a series of processes of the controller  120  during training will be described with reference to a flowchart. The term “training” refers to the time to train the classifier MDL used at runtime.  FIG. 7  is a flowchart illustrating a flow of a series of processes of training performed by the controller  120  in the first embodiment. The processing of the present flowchart may be repeatedly performed, for example, at a predetermined cycle. 
     First, the learner  132  inputs training data into the classifier MDL in order to train the classifier MDL (step S 200 ). The training data is, for example, data in which, when an owner&#39;s consent is obtained and then the owner is not using the vehicle  10 , information of the vehicle having been unauthorized used is associated with vehicle feature data and battery feature data obtained when a third party drives the vehicle  10 , that is, vehicle feature data and battery feature data obtained under the same situation as unauthorized use such as theft, as a training level. The training level may be, for example, a vector V in which e1 is 1 and e2 is 0. 
     Next, the learner  132  acquires the vector V which is a classification result from the classifier MDL into which the training data is input (step S 202 ). 
     Next, the learner  132  calculates an error between the vector V acquired from the classifier MDL and the vector V associated with the vehicle feature data and the battery feature data as a training level (step S 204 ). 
     Next, the learner  132  determines whether the calculated error is within a threshold (step S 206 ), and learns parameters of the classifier MDL on the basis of a gradient method such as reverse error propagation in a case where the error exceeds the threshold (step S 208 ). The parameters are, for example, a weight coefficient, a bias component, or the like. This concludes the processing of the present flowchart. 
     By learn the classifier MDL in this way, for example, in a case where a third party other than the owner drives the vehicle  10 , the driving is determined to be unauthorized. For example, in a case where the owner is a user who frequently steps on the accelerator pedal, a large amount of current is supplied from the battery  40  to the motor  12 . On the other hand, in a case where a third party steps on the accelerator pedal less often or less than the owner per unit time, the current supplied from the battery  40  to the motor  12  tends to be smaller than when the owner drives. Therefore, by learning the classifier MDL in advance using characteristic data in which such driving habits, individual differences, and the like are clearly reflected, it is possible to detect unauthorized use without monitoring with a camera or requiring biometric authentication. 
     According to the first embodiment described above, the center server  100  acquires vehicle feature data indicating the feature of behavior when the target vehicle  10 T is used and battery feature data indicating the feature of operation of the battery  40  mounted in the target vehicle  10 T, inputs the acquired vehicle feature data and battery feature data into the classifier MDL learned in advance, and determines whether the target vehicle  10 T has been unauthorized used on the basis of the output result of the classifier MDL into which these pieces of data are input, whereby it is possible to accurately detect the unauthorized use of the vehicle. 
     In addition, according to the above-described first embodiment, the owner of a vehicle that has been unauthorized used (or has a high probability of being unauthorized used) is caused to confirm his/her own vehicle or remotely control the vehicle, and thus it is possible to more effectively prevent the vehicle from being unauthorized used. 
     Second Embodiment 
     Hereinafter, a second embodiment will be described. In the above-described first embodiment, a case where the center server  100  determines the unauthorized use of the vehicle  10  has been described. On the other hand, the second embodiment is different from the above-described first embodiment in that the controller  36  of the PCU  30  determines the unauthorized use of a vehicle  10  in which the PCU is mounted (hereinafter referred to as a host vehicle  10 S). Hereinafter, a description will be given with focus on differences from the first embodiment, and common functions and the like with respect to those in the first embodiment will not be described. 
       FIG. 8  is a diagram illustrating an example of a PCU  30 X according to the second embodiment. A controller  36 X of the PCU  30 X according to the second embodiment further includes an acquirer  36 E, an authenticator  36 F, and a determiner  36 G in addition to the motor controller  36 A, the brake controller  36 B, the battery/VCU controller  36 C, and the communication controller  36 D which are described above. 
     A storage  38 X of the PCU  30 X according to the second embodiment stores the authentication information  152  and the classifier information  154  described above in addition to a program which is read out and executed by a processor. For example, as for the classifier information  154 , when the classifier MDL is learned by the center server  100 , information of the learned classifier MDL is installed in the storage  38 X as the classifier information  154 . 
     The acquirer  36 E acquires various detection results such as accelerator position, vehicle speed, the amount of brake stepping, the amount of operation of a steering wheel, position information, yaw rate, or orientation, as the vehicle feature data, from the vehicle sensor  20 . In addition, the acquirer  36 E acquires the calculation result of SOC as the battery feature data from the battery/VCU controller  36 C, or acquires detection results such as the current value, voltage value, and temperature of the battery  40  as the battery feature data from the battery sensor  42 . 
     When the biometric information is acquired by the acquirer  36 E, the authenticator  36 F determines whether the biometric authentication of the driver of the host vehicle  10 S is successful on the basis of the biometric information and the authentication information  152 . 
     The determiner  36 G inputs the vehicle feature data and the battery feature data of the host vehicle  10 S acquired by the acquirer  36 E into the classifier MDL indicated by the classifier information  154 . The determiner  36 G determines whether the host vehicle  10 S has been unauthorized used on the basis of the classification result of the classifier MDL into which the vehicle feature data and the battery feature data of the host vehicle  10 S are input. 
     In a case where the determiner  36 G determines that the host vehicle  10 S has been unauthorized used, the communication controller  36 D transmits the confirmation information to the terminal device  200  owned by the owner of the host vehicle  10 S through the communication device  50 . 
     In addition, in a case where the determiner  36 G determines that the host vehicle  10 S has been unauthorized use, the motor controller  36 A may control the motor  12 , the brake controller  36 B may control the brake device  16 , and the battery/VCU controller  36 C may control the VCU  34  to thereby stop the host vehicle  10 S. 
     According to the second embodiment described above, the PCU  30 X acquires vehicle feature data indicating the feature of behavior when the host vehicle  10 S is used and battery feature data indicating the feature of operation of the battery  40  mounted in the host vehicle  10 S, inputs the acquired vehicle feature data and battery feature data into the classifier MDL learned in advance, and determines whether the host vehicle  10 S has been unauthorized used on the basis of the output result of the classifier MDL into which these pieces of data are input. As a result, similarly to the above-described first embodiment, it is possible to accurately detect unauthorized use of a vehicle. 
     [Hardware Configuration] 
       FIG. 9  is a diagram illustrating an example of hardware configurations of the PCU  30  and the center server  100  according to an embodiment. 
     As shown in the drawing, the PCU  30  is configured such that a communication controller  30 - 1 , a CPU  30 - 2 , a RAM  30 - 3  used as a working memory, a ROM  30 - 4  that stores a boot program or the like, a storage device  30 - 5  such as a flash memory or an HDD, a drive device  30 - 6 , and the like are connected to each other through an internal bus or a dedicated communication line. The communication controller  30 - 1  communicates with other devices mounted in the vehicle  10 . The storage device  30 - 5  stores a program  30 - 5   a  executed by the CPU  30 - 2 . This program  30 - 5   a  is developed into the RAM  30 - 3  by a direct memory access (DMA) controller (not shown) or the like, and is executed by the CPU  30 - 2 . Thereby, the controller  36  is realized. 
     The center server  100  is configured such that a communication controller  100 - 1 , a CPU  100 - 2 , a RAM  100 - 3  used as a working memory, a ROM  100 - 4  that stores a boot program or the like, a storage device  100 - 5  such as a flash memory or an HDD, a drive device  100 - 6 , and the like are connected to each other through an internal bus or a dedicated communication line. The communication controller  100 - 1  communicates with the communication device  50  mounted in the vehicle  10  or the terminal device  200 . The storage device  100 - 5  stores a program  100 - 5   a  executed by the CPU  100 - 2 . This program  100 - 5   a  is developed into the RAM  100 - 3  by a DMA controller (not shown) or the like, and is executed by the CPU  100 - 2 . Thereby, the controller  120  is realized. 
     The above-described embodiment can be represented as follows. 
     An information processing device including: 
     at least one memory having at least one program stored therein; and 
     at least one processor, 
     wherein the processor executes the program, to thereby 
     acquire first data indicating a use situation of a target vehicle and second data indicating a use situation of a battery mounted in the target vehicle, and 
     when the first data and the second data of a certain vehicle are input, input the acquired first data and second data into a classifier learned to output third data indicating the presence or absence of unauthorized use of the certain vehicle and determine whether the target vehicle has been unauthorized used on the basis of the third data output by the classifier into which the first data and the second data are input. 
     While preferred embodiments of the invention have been described and illustrated above, it should be understood that these are exemplary of the invention and are not to be considered as limiting. Additions, omissions, substitutions, and other modifications can be made without departing from the spirit or scope of the present invention. Accordingly, the invention is not to be considered as being limited by the foregoing description, and is only limited by the scope of the appended claims. 
     REFERENCE SIGNS LIST 
     
         
           1  Unauthorized use detection system 
           10  Vehicle 
           12  Motor 
           14  Driving wheel 
           16  Brake device 
           20  Vehicle sensor 
           22  Driving operation sensor 
           24  Biometric sensor 
           30  PCU 
           32  Converter 
           34  VCU 
           36  Controller 
           38  Storage 
           40  Battery 
           42  Battery sensor 
           50  Communication device 
           60  Display device 
           70  Charging port 
           72  Converter 
           100  Center server 
           110  Communicator 
           120  Controller 
           122  Acquirer 
           124  Authenticator 
           126  Determiner 
           128  Communication controller 
           130  Remote controller 
           132  Learner 
           150  Storage 
           200  Terminal device