Patent Publication Number: US-2023150516-A1

Title: Vehicle behavior estimation system and vehicle behavior estimation method

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims priority to Japanese Patent Application No. 2021-188161 filed on Nov. 18, 2021, incorporated herein by reference in its entirety. 
     BACKGROUND 
     1. Technical Field 
     The present disclosure relates to a vehicle behavior estimation system and a vehicle behavior estimation method. 
     2. Description of Related Art 
     Japanese Unexamined Patent Application Publication No. 2001-71925 (JP 2001-71925 A) discloses an embodiment in which a vehicle is controlled by using a detection value of a steering angle sensor that detects a steering angle of a steering wheel. In this disclosure, when the pulse output by the steering angle sensor is interrupted, the actual steering angle of the vehicle which is measured by the steering angle sensor before the pulse is interrupted is compared with the estimated steering angle estimated from the actual yaw rate and the vehicle speed of the vehicle. When the actual steering angle and the estimated steering angle do not match, the control of the vehicle using the steering angle sensor is prohibited. 
     SUMMARY 
     The diameter of the wheels is different for each vehicle. Further, the amount of change in the steered angle of the steered wheel when the steering angle of the steering wheel changes by a unit angle differs for each vehicle. The relationship between the detection value of the steering angle sensor and the behavior of the vehicle caused by the steering of the steering wheel thus differs for each vehicle. Therefore, the driving diagnosis of each vehicle related to steering cannot be executed based on one criterion that defines the relationship between the detection value of the steering angle sensor and the behavior of the vehicle caused by the steering of the steering wheel. 
     In consideration of the above facts, an object of the present disclosure is to obtain a vehicle behavior estimation system and a vehicle behavior estimation method capable of executing a driving diagnosis related to steering of a plurality of vehicles based on one criterion. 
     A vehicle behavior estimation system described in claim  1  includes: a yaw rate sensor that detects a yaw rate of a diagnosis target vehicle; a vehicle speed sensor that detects a vehicle speed of the diagnosis target vehicle; and a processor. The processor acquires a first curvature that is a curvature of a traveling locus of the diagnosis target vehicle based on the yaw rate and the vehicle speed, and performs a driving diagnosis related to steering of the diagnosis target vehicle based on a criterion and a curvature-related value. The criterion defines a relationship between a steering angle-related value that is a value based on a steering angle of a steering wheel of a reference vehicle that is a vehicle different from the diagnosis target vehicle and a behavior of the reference vehicle caused by steering. The curvature-related value is a value based on the first curvature. 
     The processor of the vehicle behavior estimation system described in claim  1  acquires a first curvature that is a curvature of a traveling locus of the diagnosis target vehicle based on the yaw rate and the vehicle speed. The processor further performs a driving diagnosis related to steering of the diagnosis target vehicle based on a criterion and a curvature-related value. The criterion defines a relationship between a steering angle-related value that is a value based on a steering angle of a reference vehicle that is a vehicle different from the diagnosis target vehicle and a behavior of the reference vehicle caused by steering. The curvature-related value is a value based on the first curvature. The relationship between the curvature of the traveling locus when the vehicle is steered and the behavior of the vehicle caused by the steering of the steering wheel is substantially the same for all vehicles. Furthermore, there is a correlation between the curvature and the steering angle of the vehicle. A driving diagnosis related to the steering of the diagnosis target vehicle can therefore be executed based on the criterion that defines the relationship between the steering angle-related value of the reference vehicle and the behavior of the vehicle caused by the steering, and the curvature-related value of the diagnosis target vehicle. In other words, the vehicle behavior estimation system described in claim  1  and the vehicle behavior estimation method can execute the driving diagnosis related to the steering of the reference vehicle and the diagnosis target vehicle based on one criterion. 
     In the disclosure described in claim  1 , the vehicle behavior estimation system according to the disclosure described in claim  2  includes: a first map showing a relationship between a detection value of a first steering angle sensor that is a steering angle sensor of the diagnosis target vehicle and the first curvature; and a second map showing a relationship between a detection value of a second steering angle sensor that is a steering angle sensor of the reference vehicle and a second curvature that is a curvature of a traveling locus of the reference vehicle. The processor applies the first curvature to the second map as an argument to acquire a corrected steering angle that is a corrected value of a steering angle of the diagnosis target vehicle. The first curvature is acquired by applying the detection value of the first steering angle sensor to the first map. The processor performs a driving diagnosis related to the steering of the diagnosis target vehicle based on a corrected curvature-related value that is a value based on the corrected steering angle and the criterion. 
     In the disclosure described in claim  2 , the processor applies the first curvature to the second map as an argument to acquire a corrected steering angle that is a corrected value of a steering angle of the diagnosis target vehicle. The first curvature is acquired by applying the detection value of the first steering angle sensor to the first map. Further, the processor performs a driving diagnosis related to the steering of the diagnosis target vehicle based on a corrected curvature-related value that is a value based on the corrected steering angle and the criterion. It is known that there is a correlation between the curvature and the steering angle of the vehicle. The first map and the second map represent this correlation. Further, the behavior caused by the steering of the diagnosis target vehicle when the steering angle of the diagnosis target vehicle corresponds to a predetermined curvature is substantially the same as the behavior caused by the steering of the reference vehicle when the steering angle of the reference vehicle corresponds to the above curvature. This makes it possible to perform a driving diagnosis related to the steering of the diagnosis target vehicle based on the criterion and the corrected curvature-related value. Further, the detection accuracy of the steering angle sensor is generally higher than the detection accuracy of the yaw rate sensor. Therefore, the vehicle behavior estimation system according to the disclosure described in claim  2  can execute a driving diagnosis related to the steering of the diagnosis target vehicle with higher accuracy than the vehicle behavior estimation system according to the disclosure described in claim  1 . 
     In the disclosure described in claim  2 , in the vehicle behavior estimation system according to the disclosure described in claim  3 , the first map is created based on an average value of values obtained by the first curvature and the detection value of the first steering angle sensor, and the second map is created based on an average value of values obtained by the second curvature and the detection value of the second steering angle sensor. 
     In the disclosure described in claim  3 , the first map is created based on the average value of the values obtained by the first curvature and the detection value of the first steering angle sensor. Generally, the detection accuracy of the yaw rate sensor is not high. However, the first map created in this way more accurately represents the relationship between the steering angle and the curvature of the diagnosis target vehicle as compared with the first map created not based on the average value. Therefore, the reliability of the first map of the disclosure described in claim  3  is high. 
     In the disclosure described in claim  2  or  3 , in the vehicle behavior estimation system according to the disclosure described in claim  4 , the processor creates the first map based on detection values of the yaw rate sensor, the vehicle speed sensor, and the first steering angle sensor of the diagnosis target vehicle. 
     In the disclosure described in claim  4 , the processor creates the first map based on detection values of the yaw rate sensor, the vehicle speed sensor, and the first steering angle sensor of the diagnosis target vehicle. Accordingly, the processor can update the first map based on the detection values of the yaw rate sensor, the vehicle speed sensor, and the first steering angle sensor. The latest state of the parts that affect the curvature of the diagnosis target vehicle is thus incorporated in the first map. Therefore, the reliability of the first map of the disclosure described in claim  4  is high. 
     In a vehicle behavior estimation method according to the disclosure described in claim  5 , a processor provided in a diagnosis target vehicle acquires a first curvature that is a curvature of a traveling locus of the diagnosis target vehicle based on a yaw rate and a vehicle speed of the diagnosis target vehicle, and performs a driving diagnosis related to steering of the diagnosis target vehicle based on a criterion and a curvature-related value. The criterion defines a relationship between a steering angle-related value that is a value based on a steering angle of a steering wheel of a reference vehicle that is a vehicle different from the diagnosis target vehicle and a behavior of the reference vehicle caused by steering. The curvature-related value is a value based on the first curvature. 
     As described above, the vehicle behavior estimation system and the vehicle behavior estimation method according to the present disclosure have an excellent effect that a driving diagnosis related to steering of a plurality of vehicles can be executed based on one criterion. 
    
    
     
       BRIEF DESCRIPTION I/F THE DRAWINGS 
       Features, advantages, and technical and industrial significance of exemplary embodiments of the disclosure will be described below with reference to the accompanying drawings, in which like signs denote like elements, and wherein: 
         FIG.  1    is a schematic diagram showing a vehicle behavior estimation system according to a first embodiment; 
         FIG.  2    is a schematic diagram showing a diagnosis target vehicle and a reference vehicle of the vehicle behavior estimation system according to the first embodiment; 
         FIG.  3    is a control block diagram of an electronic control unit (ECU) of the diagnosis target vehicle and the reference vehicle; 
         FIG.  4    is a functional block diagram of the ECU; 
         FIG.  5    is a functional block diagram of an external server of the vehicle behavior estimation system; 
         FIG.  6    is a diagram showing a conversion map recorded in a read-only memory (ROM) of the ECU of the diagnosis target vehicle; 
         FIG.  7    is a diagram showing a steering diagnosis map recorded in the external server; 
         FIG.  8    is a flowchart showing a process executed by the ECU of the diagnosis target vehicle; 
         FIG.  9    is a flowchart showing a process executed by the external server; 
         FIG.  10    is a flowchart showing a process executed by a mobile terminal; 
         FIG.  11    is a functional block diagram of an ECU of a diagnosis target vehicle and a reference vehicle according to a second embodiment; 
         FIG.  12    is a functional block diagram of an external server according to the second embodiment; 
         FIG.  13    is a diagram showing a first map according to the second embodiment; 
         FIG.  14    is a diagram showing a second map according to the second embodiment; 
         FIG.  15    is a diagram illustrating a method of creating the first map and the second map according to the second embodiment; 
         FIG.  16    is a flowchart showing a process executed by the ECU of the diagnosis target vehicle and the reference vehicle according to the second embodiment; and 
         FIG.  17    is a flowchart showing a process executed by the external server according to the second embodiment. 
     
    
    
     DETAILED DESCRIPTION I/F EMBODIMENTS 
     Hereinafter, a first embodiment of a vehicle behavior estimation system  10  and a vehicle behavior estimation method according to the present disclosure will be described with reference to  FIGS.  1  to  10   . As shown in  FIG.  1   , the vehicle behavior estimation system  10  includes a diagnosis target vehicle  20 , a reference vehicle  40 , an external server  60 , and a mobile terminal  70 . 
     The vehicle behavior estimation system  10  has a plurality of diagnosis target vehicles  20 . For the sake of convenience, only one diagnosis target vehicle  20  is shown in  FIG.  1   . The diagnosis target vehicle  20  can perform data communication with the external server  60  via a network. The network includes a communication network of a telecommunications carrier and the Internet network. 
     As shown in  FIG.  2   , the diagnosis target vehicle  20  capable of receiving the diagnosis by the vehicle behavior estimation system  10  has four wheels, an electronic control unit (ECU)  21 , a vehicle speed sensor  30 , a steering wheel  31 , a steering angle sensor  32  (first steering angle sensor), a global positioning system (GPS) receiver  33 , a yaw rate sensor  34 , and an ignition switch  35 . A vehicle identification (ID) is assigned to each diagnosis target vehicle  20 . Two front wheels  20 FW are steered wheels. Thus, when the steering angle of the steering wheel  31  changes, the steered angles of the right and left steered wheels  20 FW change. The vehicle speed sensor  30 , the steering angle sensor  32 , the GPS receiver  33 , the yaw rate sensor  34 , and the ignition switch  35  are connected to the ECU  21 . When the ignition switch  35  is in the OFF state, the drive source of the diagnosis target vehicle  20  is inoperable, and when the ignition switch  35  is in the ON state, the drive source is operable. The drive source includes, for example, at least one of an engine and an electric motor. Therefore, the “ignition switch  35 ” in the present specification includes an ignition switch operated by a key and other switches. The other switches include, for example, a push-type start button. 
     When the ignition switch  35  is in the ON state, the vehicle speed sensor  30  acquires the vehicle speed V1 of the diagnosis target vehicle  20  and transmits the acquired vehicle speed V1 to the ECU  21  every time a predetermined time elapses. When the ignition switch  35  is in the ON state, the steering angle sensor  32  acquires the steering angle ST1 that is the rotation angle of the steering wheel  31  and transmits the acquired steering angle ST1 to the ECU  21  every time a predetermined time elapses. When the ignition switch  35  is in the ON state, the GPS receiver  33  receives the GPS signal transmitted from a GPS satellite every time a predetermined time elapses. That is, the GPS receiver  33  acquires information related to the position where the diagnosis target vehicle  20  is traveling (hereinafter referred to as “position information”). When the ignition switch  35  is in the ON state, the yaw rate sensor  34  acquires the yaw rate YR1 of the diagnosis target vehicle  20  and transmits the acquired yaw rate YR1 to the ECU  21  every time a predetermined time elapses. The detection values of the vehicle speed sensor  30 , the steering angle sensor  32 , and the yaw rate sensor  34  which are transmitted to the ECU  21  are recorded in a storage  25  described later in association with the ID information of the diagnosis target vehicle  20 , the position information described above, and the time information. 
     The ECU  21  shown in  FIG.  3    includes a central processing unit (CPU: processor)  22 , a read-only memory (ROM)  23 , a random access memory (RAM)  24 , the storage  25 , a communication interface (I/F)  26 , and an input-output I/F  27 . The CPU  22 , the ROM  23 , the RAM  24 , the storage  25 , the communication I/F  26 , and the input-output I/F  27  are connected to each other so as to be able to communicate with each other via a bus  28 . The ECU  21  can acquire information related to the date and time from a timer (not shown). 
     The CPU  22  is a central processing unit, and executes various programs and controls various units. In other words, the CPU  22  reads the program from the ROM  23  or the storage  25  and executes the program using the RAM  24  as a work area. The CPU  22  controls each configuration and executes various arithmetic processes (information processes) in accordance with the program recorded in the ROM  23  or the storage  25 . 
     The ROM  23  stores various programs and various data. The RAM  24  temporarily stores a program or data as a work area. The storage  25  is composed of a storage device such as a hard disk drive (HDD) or a solid state drive (SSD), and stores various programs and various data. The communication I/F  26  is an interface capable of communicating with a device located outside the diagnosis target vehicle  20 . For example, the communication I/F  26  can wirelessly communicate with the external server  60 . Communication standards such as Bluetooth (registered trademark) and Wi-Fi (registered trademark) are used for the communication I/F  26 . Further, the communication I/F  26  can communicate with an ECU different from the ECU  21  provided in the diagnosis target vehicle  20  via an external bus. 
     As shown in  FIG.  4   , the ECU  21  has a curvature calculation unit  221 , an estimated steering angle calculation unit  222 , and a communication control unit  223  as functional configurations. The curvature calculation unit  221 , the estimated steering angle calculation unit  222 , and the communication control unit  223  are realized as the CPU  22  of the ECU  21  reads and executes the program stored in the ROM  23 . 
     The curvature calculation unit  221  calculates “the curvature Cv1 of the traveling locus of the diagnosis target vehicle  20 =the yaw rate YR1÷the vehicle speed V1” based on the yaw rate YR1 detected by the yaw rate sensor  34  and the vehicle speed V1 detected by the vehicle speed sensor  30 . 
     The estimated steering angle calculation unit  222  calculates the estimated steering angle STe1 of the diagnosis target vehicle  20  based on the curvature Cv1 calculated by the curvature calculation unit  221  and a conversion map  38  shown in  FIG.  6   . The vertical axis of the conversion map  38  represents the steering angle ST1, and the horizontal axis represents the curvature Cv1. The sign of the steering angle ST1 when the steering wheel  31  is steered in the clockwise direction is +(plus), and the sign of the steering angle ST1 when the steering wheel  31  is steered in the counterclockwise direction is−(minus). Further, the sign of the curvature Cv1 when the diagnosis target vehicle  20  turns to the right is +(plus), and the sign of the curvature Cv1 when the diagnosis target vehicle  20  turns to the left is−(minus). The conversion map  38  is created based on a large amount of data representing the vehicle speed V1 detected by the vehicle speed sensor  30  of the traveling diagnosis target vehicle  20  and a large amount of data representing the steering angle ST1 detected by the steering angle sensor  32  of the traveling diagnosis target vehicle  20 . It is known that the steering angle of the vehicle and the curvature of the traveling locus are almost proportional to each other. The line in the graph shown in the conversion map  38  is therefore substantially linear. The estimated steering angle calculation unit  222  acquires the steering angle ST1 as the estimated steering angle STe1 by applying the calculated curvature Cv1 to the conversion map  38  as an argument. Further, the estimated steering angle calculation unit  222  records the acquired estimated steering angle STe1 in the storage  25  in association with the ID information of the diagnosis target vehicle  20 , the position information described above, and the time information. 
     The communication control unit  223  controls the communication I/F  26  so as to wirelessly transmit the vehicle speed V1, the yaw rate YR1, the curvature Cv1 and the estimated steering angle STe1 recorded in the storage  25  to the external server  60  every time a predetermined time elapses. 
     The vehicle behavior estimation system  10  has one reference vehicle  40 . The reference vehicle  40  can perform data communication with the external server  60  via a network. 
     As shown in  FIG.  2   , the reference vehicle  40  includes four wheels including two steered wheels (front wheels)  40 FW, an ECU  41 , a vehicle speed sensor  30 , a steering wheel  31 , a steering angle sensor (second steering angle sensor)  32 , a GPS receiver  33 , a yaw rate sensor  34 , and an ignition switch  35 . A vehicle ID is assigned to the reference vehicle  40 . The vehicle speed sensor  30 , the steering angle sensor  32 , the GPS receiver  33 , the yaw rate sensor  34 , and the ignition switch  35  are connected to the ECU  41 . When the steering angle of the steering wheel  31  changes, the steered angle of the right and left steered wheels  40 FW changes. 
     As shown in  FIG.  3   , the ECU  41  includes a CPU (processor)  42 , a ROM  43 , a RAM  44 , a storage  45 , a communication I/F  46 , and an input-output I/F  47 . The CPU  42 , the ROM  43 , the RAM  44 , the storage  45 , the communication I/F  46 , and the input-output I/F  47  are connected to each other so as to be able to communicate with each other via a bus  48 . The specifications of the CPU  42 , the ROM  43 , the RAM  44 , the storage  45 , the communication I/F  46 , and the input-output I/F  47  are the same as those of each of the CPU  22 , the ROM  23 , the RAM  24 , the storage  25 , the communication I/F  26 , and the input-output I/F  27 . 
     The external server  60  shown in  FIG.  1    includes a CPU (processor), a ROM, a RAM, a storage, a communication I/F, and an input-output I/F as hardware configurations. The CPU, the ROM, the RAM, the storage, the communication I/F, and the input-output I/F are connected to each other so as to be able to communicate with each other via a bus. The CPU of the external server  60  can acquire information related to the time from the timer. 
     As shown in  FIG.  5   , the hardware of the external server  60  has a driving diagnosis unit  601  and a communication control unit  602  as functional configurations. The driving diagnosis unit  601  and the communication control unit  602  are realized as the CPU of the external server  60  reads and executes the program stored in the ROM or the storage. 
     The driving diagnosis unit  601  acquires the steering angular acceleration (curvature-related value) STa1, which is the acceleration of the estimated steering angle STe1, by subjecting the estimated steering angle STe1 received from the diagnosis target vehicle  20  to differentiation of second order. The driving diagnosis unit  601  also records the acquired steering angular acceleration STa1 in the storage of the external server  60  in association with the ID information of the diagnosis target vehicle  20 , the position information described above, and the time information. 
     A steering diagnosis map (criterion)  65  shown in  FIG.  7    is recorded in the ROM or the storage of the external server  60 . The steering diagnosis map  65  defines the vehicle speed V2 of the reference vehicle  40 , the steering angular acceleration STa2 (steering angle-related value) that is the second-order differentiation value of the steering angle ST2, and the score related to the steering. The vehicle speed V2 is a detection value of the vehicle speed sensor  30  of the reference vehicle  40 . The steering angle ST2 is a detection value of the steering angle sensor  32  of the reference vehicle  40 . The score is defined based on the behavior caused by the steering of the reference vehicle  40 . That is, the steering diagnosis map  65  defines the relationship between the steering angular acceleration of the reference vehicle  40  and the behavior caused by the steering of the reference vehicle  40  for each vehicle speed. Therefore, by applying the steering angular acceleration STa2 to the steering diagnosis map  65 , it is possible to obtain the score representing the behavior caused by the steering of the reference vehicle  40 . 
     The steering diagnosis map  65  of the first embodiment defines the vehicle speed V2 by dividing it into three regions. These three regions are a region of less than A (km/h), a region of A or more and less than B (km/h), and a region of B or more. The magnitude relationship is represented by B&gt;A and A and B are positive values. As shown in the steering diagnosis map  65 , in the case where the vehicle speed V2 is less than A, the score when the steering angular acceleration STa2 is less than X1 is 10 points, and the score when the steering angular acceleration STa2 is X1 or more is 1 point. In the case where the vehicle speed V2 is A or more and less than B, the score when the steering angular acceleration STa2 is less than X2 is 10 points, and the score when the steering angular acceleration STa2 is X2 or more is 1 point. In the case where the vehicle speed V2 is B or more, the score when the steering angular acceleration STa2 is less than X3 is 10 points, and the score when the steering angular acceleration STa2 is X3 or more is 1 point. It should be noted that the magnitude relationship is represented by X1&lt;X2&lt;X3. X1, X2, and X3 are absolute values. By applying the vehicle speed V1 and the steering angular acceleration STa1 to the steering diagnosis map  65 , the driving diagnosis unit  601  acquires the score related to the steering of each diagnosis target vehicle  20 . For example, when the vehicle speed V1 is less than A and the steering angular acceleration STa1 is less than X1, the score is 10 points. The driving diagnosis unit  601  also records the acquired score in the storage of the external server  60  in association with the ID information of the diagnosis target vehicle  20 , the position information, and the time information. 
     The communication control unit  602  controls the communication I/F of the external server  60  so as to wirelessly transmit information related to the score of the diagnosis target vehicle  20 , which is recorded in the storage and associated with the position information described above and the time information, to the mobile terminal  70  carried by an occupant of the diagnosis target vehicle  20  to which the score is given. 
     The mobile terminal  70  shown in  FIG.  1    includes a CPU, a ROM, a RAM, a storage, a communication I/F, and an input-output I/F as hardware configurations. The mobile terminal  70  is, for example, a smartphone or a tablet computer. The CPU, the ROM, the RAM, the storage, the communication I/F, and the input-output I/F of the mobile terminal  70  are connected to each other so as to be able to communicate with each other via a bus. The communication I/F of the mobile terminal  70  can wirelessly communicate with the communication I/F of the external server  60 . The mobile terminal  70  can acquire information related to the date and time from a timer (not shown). The mobile terminal  70  is provided with a display  71  having a touch panel. Further, map data is recorded in the storage of the mobile terminal  70 . The mobile terminal  70  is carried by, for example, the driver of the diagnosis target vehicle  20 . A predetermined driving diagnosis display application is installed on the mobile terminal  70 . 
     Operation and Effects 
     Next, the operation and effects of the first embodiment will be described. 
     First, the flow of a process performed by the ECU  21  of each diagnosis target vehicle  20  will be described with reference to a flowchart shown in  FIG.  8   . The ECU  21  repeatedly executes the process of the flowchart shown in  FIG.  8    every time a predetermined time elapses. 
     First, in step S 10 , the curvature calculation unit  221  of the ECU  21  calculates the curvature Cv1 based on the yaw rate YR1 detected by the yaw rate sensor  34  and the vehicle speed V1 detected by the vehicle speed sensor  30 . 
     The ECU  21  that has completed the process of step S 10  proceeds to step S 11 . In step S 11 , the estimated steering angle calculation unit  222  of the ECU  21  acquires the estimated steering angle STe1 by applying the curvature Cv1 to the conversion map  38  as an argument. 
     The ECU  21  that has completed the process of step S 11  proceeds to step S 12 . In step S 12 , the communication control unit  223  of the ECU  21  controls the communication I/F  26  so as to wirelessly transmit the vehicle speed V1, the yaw rate YR1, the curvature Cv1, and the estimated steering angle STe1 recorded in the storage  25  and associated with the position information and the time information to the external server  60 . 
     When the process of step S 12  is completed, the ECU  21  temporarily ends the process of the flowchart shown in  FIG.  8   . 
     Next, the flow of the process executed by the external server  60  will be described with reference to the flowchart shown in  FIG.  9   . The external server  60  repeatedly executes the process of the flowchart shown in  FIG.  9    every time a predetermined time elapses. 
     First, in step S 20 , the communication control unit  602  of the external server  60  determines whether the communication I/F has received the vehicle speed V1, the yaw rate YR1, the curvature Cv1, and the estimated steering angle STe1 from the diagnosis target vehicle  20 . 
     The external server  60  that has determined Yes in step S 20  proceeds to step S 21 , and the driving diagnosis unit  601  calculates the steering angular acceleration STa1 that is the acceleration of the estimated steering angle STe1. Further, the driving diagnosis unit  601  acquires the score related to the steering of the diagnosis target vehicle  20  by applying the vehicle speed V1 and the steering angular acceleration STa1 to the steering diagnosis map  65 . The driving diagnosis unit  601  also records the acquired score in the storage of the external server  60  in association with the ID information of the diagnosis target vehicle  20 , the position information, and the time information. 
     The external server  60  that has completed the process of step S 21  proceeds to step S 22 . In step S 22 , the communication control unit  602  of the external server  60  controls the communication I/F  46  so as to wirelessly transmit the information related to the score recorded in the storage and associated with the position information and the time information to the mobile terminal  70 . 
     When the determination is No in step S 20  or when the process in step S 22  is completed, the external server  60  temporarily ends the process of the flowchart shown in  FIG.  9   . 
     Next, the flow of the process executed by the mobile terminal  70  will be described with reference to a flowchart shown in  FIG.  10   . The mobile terminal  70  repeatedly executes the process of the flowchart shown in  FIG.  10    every time a predetermined time elapses. 
     In step S 30 , the CPU of the mobile terminal  70  determines whether the driving diagnosis display application is running. 
     The mobile terminal  70  that has determined Yes in step S 30  proceeds to step S 31 , and determines whether the communication I/F of the mobile terminal  70  has received the score information related to the diagnosis target vehicle  20  on which the person who carries the mobile terminal  70  rides from the communication I/F of the external server  60 . 
     The mobile terminal  70  that has determined Yes in step S 31  proceeds to step S 32 , and the CPU causes the display  71  to display an image showing the score (not shown). At this time, the display  71  may display a map image represented by the map data recorded in the storage of the mobile terminal  70 , and may display the position where the steering operation corresponding to the score was performed as a specific image superimposed on the map image. Further, the display  71  may display information indicating the time when the steering operation corresponding to the score was performed in association with the score. 
     When the determination is NO in step S 30  or when the process of step S 32  is completed, the mobile terminal  70  temporarily ends the process of the flowchart shown in  FIG.  10   . 
     As described above, in the vehicle behavior estimation system  10  and the vehicle behavior estimation method of the first embodiment, the curvature Cv1 of the traveling locus of the diagnosis target vehicle  20  is obtained based on the yaw rate YR1 and the vehicle speed V1 of the diagnosis target vehicle  20 . Further, a driving diagnosis related to the steering of the diagnosis target vehicle  20  is performed based on the steering angular acceleration STa1 (curvature-related value) that is a value based on the steering diagnosis map  65  and the curvature Cv1. As described above, the steering diagnosis map  65  defines the relationship between the steering angular acceleration of the reference vehicle  40  and the behavior of the reference vehicle  40 . In other words, the steering diagnosis map  65  does not define the relationship between the steering angular acceleration STa1 of the diagnosis target vehicle  20  and the behavior of the diagnosis target vehicle  20 . However, it is known that the relationship between the curvature of the traveling locus and the behavior caused by the steering of the vehicle is substantially the same regardless of the vehicle type (specification) of the vehicle. Further, as described above, the steering angle of the vehicle can be obtained from the curvature of the traveling locus. Accordingly, the score obtained by applying the steering angular acceleration STa1 that is a value based on the curvature Cv1 of the diagnosis target vehicle  20  to the steering diagnosis map  65  represents the behavior caused by the steering of the diagnosis target vehicle  20 . Therefore, the vehicle behavior estimation system  10  and the vehicle behavior estimation method of the first embodiment can execute the driving diagnosis related to the steering of the diagnosis target vehicle  20  based on the steering diagnosis map  65  (criterion) and the steering angular acceleration STa1 (curvature-related value) of the diagnosis target vehicle  20 . Further, by applying the steering angular acceleration STa2 to the steering diagnosis map  65 , it is possible to execute the driving diagnosis related to the steering of the reference vehicle  40 . That is, the vehicle behavior estimation system  10  and the vehicle behavior estimation method of the first embodiment can execute the driving diagnosis related to the steering of the reference vehicle  40  and the diagnosis target vehicle  20  based on one criterion. 
     Next, a second embodiment of the vehicle behavior estimation system  10  and the vehicle behavior estimation method according to the present disclosure will be described with reference to  FIGS.  11  to  17   . The same configurations and functions as those in the first embodiment are designated by the same reference signs, and detailed description thereof will be omitted. 
     As shown in  FIG.  11   , the ECU  21  of each diagnosis target vehicle  20  of the second embodiment has the curvature calculation unit  221  and the communication control unit  223  as functional configurations. Further, the ECU  41  of the reference vehicle  40  of the second embodiment has a curvature calculation unit  421  and a communication control unit  423  as functional configurations. The functions of the curvature calculation unit  421  and the communication control unit  423  are the same as the functions of each of the curvature calculation unit  221  and the communication control unit  223 . The curvature calculation unit  421  and the communication control unit  423  are realized as the CPU  42  of the ECU  41  reads and executes the program stored in the ROM  43 . 
     The curvature calculation unit  221  calculates the curvature Cv1 based on the yaw rate YR1 detected by the yaw rate sensor  34  of the diagnosis target vehicle  20  and the vehicle speed V1 detected by the vehicle speed sensor  30  of the diagnosis target vehicle  20 , and records the calculated curvature Cv1 in the storage  25  in association with the ID information of the diagnosis target vehicle  20 , the position information, and the time information. 
     The communication control unit  223  controls the communication I/F  26  so as to wirelessly transmit the vehicle speed V1, the steering angle ST1, the yaw rate YR1, and the curvature Cv1 recorded in the storage  25  and associated with the position information described above and the time information to the external server  60  every time a predetermined time elapses. 
     The curvature calculation unit  421  calculates “the curvature Cv2 of the traveling locus of the reference vehicle  40 =the yaw rate YR2÷the vehicle speed V2” based on the yaw rate YR2 detected by the yaw rate sensor  34  of the reference vehicle  40  and the vehicle speed V2 detected by the vehicle speed sensor  30  of the reference vehicle  40 . 
     The communication control unit  423  controls the communication I/F  46  so as to wirelessly transmit the vehicle speed V2, the steering angle ST2, the yaw rate YR2, and the curvature Cv2 recorded in the storage  45  and associated with the position information described above and the time information to the external server  60  every time a predetermined time elapses. 
     As shown in  FIG.  12   , the hardware of the external server  60  of the second embodiment has a driving diagnosis unit  601 , a communication control unit  602 , and a map creation unit  603  as functional configurations. 
     The map creation unit  603  creates a first map  75  shown in  FIG.  13    based on the steering angle ST1 and the curvature Cv1 received from each diagnosis target vehicle  20 . The vertical axis of the first map  75  represents the steering angle ST1, and the horizontal axis represents the curvature Cv1. The external server  60  receives a large amount of data representing the steering angle ST1 and the curvature Cv1 from each diagnosis target vehicle  20 . The map creation unit  603  plots the received data representing all the steering angles ST1 and the curvatures Cv1 on the first map  75 . The map creation unit  603  then creates the first map  75  based on all the plotted data. At this time, the map creation unit  603  averages the data. That is, for example, as shown in  FIG.  15   , it is assumed that the steering angle ST1 corresponding to P1 that is a predetermined value of the curvature Cv1 includes four steering angles ST1 represented by circles. In this case, the map creation unit  603  regards the average value of the four steering angles ST1 represented by a square as the value Q1 of the steering angle ST1 corresponding to P1. 
     Further, in the same manner, the map creation unit  603  creates a second map  80  shown in  FIG.  14    based on the steering angle ST2 and the curvature Cv2 received from the reference vehicle  40 . Generally, the detection accuracy of the yaw rate sensor  34  is not high. However, the first map  75  and the second map  80  created in this way more accurately represents the relationship between the steering angle and the curvature of the diagnosis target vehicle  20  and the reference vehicle  40  as compared with the first map  75  and the second map  80  created not based on the average value. Therefore, the reliability of the first map  75  and the second map  80  created in this way is high. 
     Operation and Effects 
     Next, the operation and effects of the second embodiment will be described. 
     First, the flow of a process performed by the ECU  21  of each diagnosis target vehicle  20  and the ECU  41  of the reference vehicle  40  will be described with reference to a flowchart shown in  FIG.  16   . The ECUs  21 ,  41  repeatedly execute the process of the flowchart shown in  FIG.  16    every time a predetermined time elapses. 
     First, in step S 10 , the curvature calculation units  221 ,  421  of the ECUs  21 ,  41  calculate the curvatures Cv1, Cv2. 
     The ECUs  21 ,  41  that have completed the process of step S 10  proceed to step S 12 . In step S 12 , the communication control unit  223  of the ECU  21  controls the communication I/F  26  so as to wirelessly transmit the vehicle speed V1, the steering angle ST1, the yaw rate YR1, and the curvature Cv1 associated with the ID information, the position information, and the time information to the external server  60 . In step S 12 , the communication control unit  423  of the ECU  41  controls the communication I/F  46  so as to wirelessly transmit the vehicle speed V2, the steering angle ST2, the yaw rate YR2, and the curvature Cv2 associated with the ID information, the position information, and the time information to the external server  60 . 
     When the process of step S 12  is completed, the ECUs  21 ,  41  temporarily end the process of the flowchart shown in  FIG.  16   . 
     Next, the flow of the process executed by the external server  60  will be described with reference to the flowchart shown in  FIG.  17   . The external server  60  repeatedly executes the process of the flowchart shown in  FIG.  17    every time a predetermined time elapses. 
     First, in step S 40 , the communication control unit  602  of the external server  60  determines whether the communication I/F has received the vehicle speed V1, the steering angle ST1, the yaw rate YR1, and the curvature Cv1 from the diagnosis target vehicle  20 , or whether the communication I/F has received the vehicle speed V2, the steering angle ST2, the yaw rate YR2, and the curvature Cv2 from the reference vehicle  40 . 
     The external server  60  that has determined Yes in step S 40  proceeds to step S 41 , and the map creation unit  603  creates (updates) the first map  75  based on the steering angle ST1 and the curvature Cv1 that were received. 
     The external server  60  that has completed the process of step S 41  proceeds to step S 42 . In step S 42 , the map creation unit  603  determines whether the first map  75  satisfies the usable condition. That is, the map creation unit  603  determines whether the number of the steering angles ST1 and the curvatures Cv1 constituting the first map  75  is equal to or greater than a predetermined number and the steering angles ST1 and the curvatures Cv1 constituting the first map  75  include values having absolute values of various magnitudes. 
     The external server  60  that has determined Yes in step S 42  proceeds to step S 43 , and the map creation unit  603  sets the first map flag to “1”. The initial value of the first map flag is “0”. 
     The external server  60  that has determined No in step S 42  proceeds to step S 44 , and the map creation unit  603  sets the first map flag to “0”. 
     The external server  60  that has completed the process of step S 43  or step S 44  proceeds to step S 47 , and the map creation unit  603  creates (updates) the second map  80  based on the steering angle ST2 and the curvature Cv2 that have been received. 
     The external server  60  that has completed the process of step S 47  proceeds to step S 48 . In step S 48 , the map creation unit  603  of the external server  60  determines whether the second map  80  satisfies the usable condition. That is, the map creation unit  603  determines whether the number of the steering angles ST2 and the curvatures Cv2 constituting the second map  80  is equal to or greater than a predetermined number and the steering angles ST2 and the curvatures Cv2 constituting the second map  80  include values having absolute values of various magnitudes. 
     The external server  60  that has determined Yes in step S 48  proceeds to step S 49 , and the map creation unit  603  sets the second map flag to “1”. The initial value of the second map flag is “0”. 
     The external server  60  that has determined No in step S 48  proceeds to step S 50 , and the map creation unit  603  sets the second map flag to “0”. 
     The external server  60  that has completed the process of step S 49  or step S 50  proceeds to step S 53 , and the map creation unit  603  determines whether the first map flag and the second map flag are “1”. 
     The external server  60  that has determined Yes in step S 53  proceeds to step S 54  and calculates the corrected steering angle Stc1 of the diagnosis target vehicle  20  using the first map  75  and the second map  80 . More specifically, the map creation unit  603  acquires the curvature Cv1 corresponding to the steering angle ST1 by applying the steering angle ST1 of the diagnosis target vehicle  20  to the first map  75  as an argument. At this time, the map creation unit  603  executes the interpolation process of the first map  75  as necessary. For example, it is assumed that the magnitude of the steering angle ST1 is the steering angle ST-A shown in  FIG.  13   . The magnitude of the curvature Cv1 acquired by applying the steering angle ST-A to the first map  75  as an argument is the curvature Cv-A. Further, the map creation unit  603  acquires the steering angle ST-B, which is the steering angle ST2 of the reference vehicle  40  corresponding to the curvature Cv-A, by applying the curvature Cv-A to the second map  80  as an argument. At this time, the map creation unit  603  executes the interpolation process of the second map  80  as necessary. The steering angle ST-B is the corrected steering angle Stc1 of the diagnosis target vehicle  20 . 
     The external server  60  that has completed the process of step S 54  proceeds to step S 55 , and the driving diagnosis unit  601  calculates the steering angular acceleration (curvature-related value) (corrected curvature-related value) STca1 that is the acceleration of the corrected steering angle Stc1. Further, the driving diagnosis unit  601  acquires the score related to the steering of the diagnosis target vehicle  20  by applying the vehicle speed V1 and the steering angular acceleration STca1 to the steering diagnosis map  65 . The driving diagnosis unit  601  also records the acquired score in the storage of the external server  60  in association with the ID information of the diagnosis target vehicle  20 , the position information, and the time information. 
     The external server  60  that has completed the process of step S 55  proceeds to step S 56 . In step S 56 , the communication control unit  602  of the external server  60  controls the communication I/F  46  so as to wirelessly transmit the information related to the score recorded in the storage and associated with the ID information, the position information, and the time information to the mobile terminal  70 . 
     When the determination is No in steps S 40 , S 53  or when the process in step S 56  is completed, the external server  60  temporarily ends the process of the flowchart shown in  FIG.  17   . 
     Further, the mobile terminal  70  repeatedly executes the process of the flowchart shown in  FIG.  10    every time a predetermined time elapses. Thus, when the CPU of the mobile terminal  70  proceeds to step S 32 , the CPU causes the display  71  to display an image showing the score (not shown). 
     As described above, the external server  60  of the vehicle behavior estimation system  10  and the vehicle behavior estimation method of the second embodiment acquires the curvature (curvature Cv-A) by applying the detection value (steering angle ST-A) of the steering angle sensor  32  of the diagnosis target vehicle  20  to the first map  75  as an argument. Further, the external server  60  acquires the corrected steering angle STc1, which is the corrected value of the steering angle of the steering wheel  31  of the diagnosis target vehicle  20 , by applying the curvature Cv-A to the second map  80  as an argument. The external server  60  also performs a driving diagnosis related to the steering of the diagnosis target vehicle  20  based on the steering angular acceleration STca1, which is the second-order differentiation value of the corrected steering angle STc1, and the steering diagnosis map  65 . As shown in the first map  75  and the second map  80 , there is a correlation between the steering angle ST1 and the curvature Cv1 of the diagnosis target vehicle  20 , and between the steering angle ST2 and the curvature Cv2 of the reference vehicle  40 . The steering angle ST-A of the diagnosis target vehicle  20  and the steering angle ST-B of the reference vehicle  40  are values corresponding to the common curvature Cv-A. That is, the behavior of the diagnosis target vehicle  20  when the steering angle of the diagnosis target vehicle  20  is the steering angle ST-A is substantially the same as the behavior of the reference vehicle  40  when the steering angle of the reference vehicle  40  is the steering angle ST-B. Accordingly, the score obtained by applying the steering angular acceleration STca1 of the diagnosis target vehicle  20  to the steering diagnosis map  65  accurately represents the behavior of the diagnosis target vehicle  20 . Therefore, the vehicle behavior estimation system  10  and the vehicle behavior estimation method of the second embodiment can execute the driving diagnosis related to the steering of the diagnosis target vehicle  20  based on the steering diagnosis map  65  (criterion) and the steering angle ST1 of the diagnosis target vehicle  20 . 
     Further, the detection accuracy of the steering angle sensor is generally higher than the detection accuracy of the yaw rate sensor. Accordingly, the steering angular acceleration STca1 of the second embodiment is more likely to represent the acceleration of the steering angle of the diagnosis target vehicle  20  more accurately than the steering angular acceleration STa1 of the first embodiment. Therefore, the driving diagnosis result of the diagnosis target vehicle  20  of the second embodiment is more reliable than the driving diagnosis result of the diagnosis target vehicle  20  of the first embodiment. 
     Further, the external server  60  creates the first map  75  based on the steering angle ST1 and the curvature Cv1 of the diagnosis target vehicle  20 , and creates the second map  80  based on the steering angle ST2 and the curvature Cv2 of the reference vehicle  40 . Therefore, the external server  60  can easily create the first map  75  and the second map  80 . 
     Further, the external server  60  updates the first map  75  and the second map  80  based on the latest data received from the diagnosis target vehicle  20  and the reference vehicle  40 . Thus, the latest state of the parts affecting the curvature Cv1 of the diagnosis target vehicle  20  is incorporated in the first map  75 , and the latest state of the parts affecting the curvature Cv2 of the reference vehicle  40  is incorporated in the second map  80 . These parts include, for example, tires. Therefore, the reliability of the first map  75  and the second map  80  of the second embodiment is high. 
     The vehicle behavior estimation system  10  and the vehicle behavior estimation method according to the first and second embodiments have been described above, but the design of the vehicle behavior estimation system  10  and the vehicle behavior estimation method can be appropriately changed within a range that does not deviate from the gist of the present disclosure. 
     For example, the steering diagnosis map  65  of the first embodiment may be a map defining the relationship between the second-order differentiation value (steering angle-related value) of the curvature Cv2 of the reference vehicle  40  and the behavior caused by the steering for each vehicle speed. In this case, the external server  60  calculates the score related to the driving operation of the diagnosis target vehicle  20  by applying the second-order differentiation value (curvature-related value) of the curvature Cv1 of the diagnosis target vehicle  20  to the steering diagnosis map  65 . 
     The steering diagnosis map  65  of the second embodiment may be a map defining the relationship between the second-order differentiation value of the curvature Cv2 of the reference vehicle  40  and the behavior caused by the steering for each vehicle speed. In this case, the external server  60  calculates the score related to the driving operation of the diagnosis target vehicle  20  by applying the second-order differentiation value (curvature-related value) of the curvature Cv1 of the diagnosis target vehicle  20  acquired based on the first map  75  and the steering angle ST1 to the steering diagnosis map  65 . 
     The vehicle behavior estimation system  10  of the first and second embodiments does not have to be connected to the Internet. In this case, for example, the detection value data group acquired from the diagnosis target vehicle  20  and the reference vehicle  40  is recorded on a portable recording medium (for example, a universal serial bus (USB)), and the detection value data group in the recording medium is copied and stored in the storage of the external server  60 . 
     The external server  60  of the first and second embodiments may wirelessly transmit the diagnosis result to the diagnosis target vehicle  20 , and the display (not shown) provided on the diagnosis target vehicle  20  may display the diagnosis result. 
     The ECU  21  of the diagnosis target vehicle  20  of the first and second embodiments may have the function of the external server  60 . In this case, the external server  60  can be omitted from the vehicle behavior estimation system  10 . 
     The external server  60  of the first and second embodiments may have functions corresponding to the curvature calculation unit  221  and the estimated steering angle calculation unit  222 , and may calculate the curvature of the traveling locus of the diagnosis target vehicle  20  and the estimated steering angle based on information wirelessly transmitted from the diagnosis target vehicle  20 . 
     The content of the created second map  80  does not have to be updated after it is created. 
     Instead of the GPS receiver  33 , the diagnosis target vehicle  20  and the reference vehicle  40  may include a receiver capable of receiving information from satellites of a global navigation satellite system (for example, Galileo) other than the GPS.