Vehicle behavior estimation system and vehicle behavior estimation method

Abstract

The present disclosure relates to a vehicle behavior estimation system and a vehicle behavior estimation method. The vehicle behavior estimation system includes: a yaw rate sensor, which detects the yaw rate of a diagnostic target vehicle; a vehicle speed sensor, which detects the vehicle speed of the diagnostic target vehicle; and a processor. The processor acquires a first curvature as the curvature of a driving trajectory of the diagnostic target vehicle based on the yaw rate and the vehicle speed, and performs driving diagnosis related to the steering of the diagnostic target vehicle based on a standard and a curvature-related value. The standard defines a relationship between a steering angle-related value and a behavior of a reference vehicle caused by steering, the steering angle-related value being a value based on a steering angle of a steering wheel of the reference vehicle, the reference vehicle being a vehicle different from the diagnostic target vehicle. The curvature-related value is a value based on the first curvature.

Description

Technical Field

[0001] The invention relates to a vehicle behavior estimation system and a vehicle behavior estimation method. Background Art

[0002] Japanese Unexamined Patent Application Publication No. 2001-71925 (JP 2001-71925 A) discloses an invention 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 the invention, when a pulse output by the steering angle sensor is interrupted, an actual steering angle of the vehicle measured by the steering angle sensor before the pulse is interrupted is compared with an estimated steering angle estimated based on an actual yaw rate and a vehicle speed of the vehicle. When the actual steering angle and the estimated steering angle do not match, control of the vehicle using the steering angle sensor is prohibited. Summary of the invention

[0003] The wheel diameters of individual vehicles are different. Furthermore, when the steering angle of the steering wheel changes by one unit angle, the amount of change in the steering angle of the steering wheel is different for each vehicle. Therefore, 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 is different for each vehicle. Therefore, driving diagnosis of each vehicle related to steering cannot be performed based on one standard 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.

[0004] In view of the above facts, an object of the present invention is to achieve a vehicle behavior estimation system and a vehicle behavior estimation method capable of performing driving diagnosis related to steering of a plurality of vehicles based on one criterion.

[0005] The vehicle behavior estimation system described in the first aspect of the present invention includes: a yaw rate sensor that detects the yaw rate of a diagnosis target vehicle; a vehicle speed sensor that detects the vehicle speed of the diagnosis target vehicle; and a processor. The processor acquires a first curvature as the curvature of a driving trajectory of the diagnosis target vehicle based on the yaw rate and the vehicle speed, and performs driving diagnosis related to the steering of the diagnosis target vehicle based on a standard and a curvature-related value. The standard defines a relationship between a steering angle-related value and a behavior of a reference vehicle caused by steering, the steering angle-related value being a value based on a steering angle of a steering wheel of the reference vehicle, the reference vehicle being a vehicle different from the diagnosis target vehicle. The curvature-related value is a value based on the first curvature.

[0006] The processor of the vehicle behavior estimation system described in the first aspect obtains a first curvature as the curvature of the driving trajectory of the diagnosis target vehicle based on the yaw rate and the vehicle speed. The processor also performs driving diagnosis related to the steering of the diagnosis target vehicle based on the standard and the curvature-related value. The standard defines the relationship between the steering angle-related value and the behavior of the reference vehicle caused by steering, which is based on the value of the steering angle of the reference vehicle, and the reference vehicle is a vehicle different from the diagnosis target vehicle. The curvature-related value is based on the value of the first curvature. The relationship between the curvature of the driving trajectory when the vehicle turns and the behavior of the vehicle caused by the steering of the steering wheel is basically the same for all vehicles. In addition, there is a correlation between the curvature and the steering angle of the vehicle. Therefore, the driving diagnosis related to the steering of the diagnosis target vehicle can be performed based on the standard that defines the relationship between the steering angle-related value of the reference vehicle and the behavior of the vehicle caused by steering and the curvature-related value of the diagnosis target vehicle. In other words, the vehicle behavior estimation system and the vehicle behavior estimation method described in the first aspect of the present invention can perform driving diagnosis related to the steering of the reference vehicle and the diagnosis target vehicle based on one standard.

[0007] In the invention described in the first aspect, the vehicle behavior estimation system according to the invention described in the second aspect includes: a first map showing the relationship between the detection value of the first steering angle sensor as the steering angle sensor of the diagnosis target vehicle and the first curvature; and a second map showing the relationship between the detection value of the second steering angle sensor as the steering angle sensor of the reference vehicle and the second curvature as the curvature of the driving trajectory of the reference vehicle. The processor applies the first curvature as an independent variable to the second map to obtain a corrected steering angle as a correction value of the steering angle of the diagnosis target vehicle. The first curvature is obtained by applying the detection value of the first steering angle sensor to the first map. The processor performs the driving diagnosis related to the steering of the diagnosis target vehicle based on a correction curvature related value, which is a value based on the correction steering angle and the standard.

[0008] In the invention described in the second aspect, the processor applies the first curvature as an independent variable to the second map to obtain a corrected steering angle as a correction value of the steering angle of the diagnosis target vehicle. The first curvature is obtained by applying the detection value of the first steering angle sensor to the first map. In addition, the processor performs driving diagnosis related to the steering of the diagnosis target vehicle based on the correction curvature related value, which is a value based on the correction steering angle and the standard. 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. In addition, 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 driving diagnosis related to the steering of the diagnosis target vehicle based on the standard and the correction curvature related value. In addition, 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 of the invention described in the second aspect can perform driving diagnosis related to the steering of the diagnosis target vehicle with higher accuracy than the vehicle behavior estimation system according to the first aspect of the invention.

[0009] In the invention described in the second aspect, in the vehicle behavior estimation system according to the invention described in the third aspect, the first mapping is created based on the average value of the values ​​obtained based on the first curvature and the detection value of the first steering angle sensor, and the second mapping is created based on the average value of the values ​​obtained based on the second curvature and the detection value of the second steering angle sensor.

[0010] In the invention described in the third aspect, the first map is created based on the average value of the values ​​obtained from the detection values ​​of the first curvature and the first steering angle sensor. Generally speaking, 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 than the first map created not based on the average value. Therefore, the reliability of the first map of the invention described in the third aspect is high.

[0011] In the invention described in the second or third aspect, in the vehicle behavior estimation system according to the invention described in the fourth aspect, 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.

[0012] In the invention described in the fourth aspect, the processor creates the first map based on the detection values ​​of the yaw rate sensor, the vehicle speed sensor, and the first steering angle sensor of the diagnosis target vehicle. Therefore, 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. Therefore, the latest state of the components that affect the curvature of the diagnosis target vehicle is incorporated into the first map. Therefore, the reliability of the first map of the invention described in the fourth aspect is high.

[0013] In the vehicle behavior estimation method of the present invention according to the fifth aspect, a processor provided in a diagnosis target vehicle acquires a first curvature as a curvature of a driving trajectory of the diagnosis target vehicle based on a yaw rate and a vehicle speed of the diagnosis target vehicle, and performs driving diagnosis related to steering of the diagnosis target vehicle based on a standard and a curvature-related value. The standard defines a relationship between a steering angle-related value and a behavior of a reference vehicle caused by steering, the steering angle-related value being a value based on a steering angle of a steering wheel of the reference vehicle, the reference vehicle being a vehicle different from the diagnosis target vehicle. The curvature-related value is a value based on the first curvature.

[0014] As described above, the vehicle behavior estimation system and the vehicle behavior estimation method according to the present invention have an excellent effect of being able to perform driving diagnosis related to steering of a plurality of vehicles based on one criterion. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Features, advantages, and technical and industrial significance of exemplary embodiments of the present invention will be described below with reference to the accompanying drawings, wherein like symbols represent like elements, and wherein:

[0016] Figure 1 is a schematic diagram showing a vehicle behavior estimation system according to a first embodiment;

[0017] Figure 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;

[0018] Figure 3 is a control block diagram of an electronic control unit (ECU) of a diagnostic target vehicle and a reference vehicle;

[0019] Figure 4 It is the functional block diagram of ECU;

[0020] Figure 5 is a functional block diagram of an external server of a vehicle behavior estimation system;

[0021] Figure 6 is a diagram showing a conversion map recorded in a read-only memory (ROM) of an ECU of a diagnosis target vehicle;

[0022] Figure 7 is a diagram showing a steering diagnostic map recorded in an external server;

[0023] Figure 8 is a flowchart showing a process executed by the ECU of a diagnosis target vehicle;

[0024] Fig. 9 is a flow chart showing a process performed by an external server;

[0025] Fig.10 is a flowchart showing a process performed by a portable terminal;

[0026] Fig.11 is a functional block diagram of the ECUs of the diagnosis target vehicle and the reference vehicle according to the second embodiment;

[0027] Fig.12 is a functional block diagram of an external server according to a second embodiment;

[0028] Fig.13 is a diagram showing a first mapping according to the second embodiment;

[0029] Fig.14 is a diagram showing a second mapping according to the second embodiment;

[0030] Fig.15 is a diagram illustrating a method of creating a first mapping and a second mapping according to a second embodiment;

[0031] Fig.16 is a flowchart showing processing executed by ECUs of a diagnosis target vehicle and a reference vehicle according to the second embodiment; and

[0032] Fig.17 is a flowchart illustrating processing performed by an external server according to the second embodiment. DETAILED DESCRIPTION

[0033] In the following, reference will be made to Figures 1 to 10 A first embodiment of the vehicle behavior estimation system 10 and the vehicle behavior estimation method according to the present invention is described. Figure 1 As shown, 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 .

[0034] The vehicle behavior estimation system 10 has a plurality of diagnosis target vehicles 20. Figure 1 Only one diagnosis target vehicle 20 is shown in FIG. 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 operator and an Internet network.

[0035] like Figure 2 As shown, the diagnosis target vehicle 20 capable of receiving 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. Vehicle identification (ID) is assigned to each diagnosis target vehicle 20. The two front wheels 20FW are steering wheels. Therefore, when the steering angle of the steering wheel 31 changes, the steering angles of the left and right steering wheels 20FW 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 an off state, the driving source of the diagnosis target vehicle 20 cannot work, and when the ignition switch 35 is in an on state, the driving source can work. The driving source includes, for example, at least one of an engine and a motor. Therefore, the "ignition switch 35" in this specification includes an ignition switch operated by a key and other switches. The other switch includes, for example, a push-type start button.

[0036] 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 predetermined time. When the ignition switch 35 is in the on state, the steering angle sensor 32 acquires the steering angle ST1 which is the rotation angle of the steering wheel 31, and transmits the acquired steering angle ST1 to the ECU 21 every predetermined time. When the ignition switch 35 is in the on state, the GPS receiver 33 receives the GPS signal transmitted from the GPS satellite every predetermined time. 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 predetermined time. The detection values ​​of the vehicle speed sensor 30 , the steering angle sensor 32 , and the yaw rate sensor 34 sent to the ECU 21 are recorded in the memory 25 described later in association with the ID information of the diagnosis target vehicle 20 , the above-mentioned position information, and time information.

[0037] Figure 3The ECU 21 shown includes a central processing unit (CPU: processor) 22, a read-only memory (ROM) 23, a random access memory (RAM) 24, a memory 25, a communication interface (I / F) 26, and an input-output I / F 27. The CPU 22, the ROM 23, the RAM 24, the memory 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 date and time from a timer (not shown).

[0038] The CPU 22 is a central processing unit and executes various programs and controls various units. In other words, the CPU 22 reads a program from the ROM 23 or the memory 25 and executes the program using the RAM 24 as a work area. The CPU 22 controls each configuration and performs various arithmetic processing (information processing) according to the program recorded in the ROM 23 or the memory 25.

[0039] ROM 23 stores various programs and various data. RAM 24 temporarily stores programs or data as a work area. Memory 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. Communication I / F 26 is an interface capable of communicating with a device located outside the diagnostic target vehicle 20. For example, communication I / F 26 is capable of wireless communication with an external server 60. Communication standards such as Bluetooth (registered trademark) and Wi-Fi (registered trademark) are used for communication I / F 26. In addition, communication I / F 26 is capable of communicating with an ECU different from ECU 21 set in the diagnostic target vehicle 20 through an external bus.

[0040] like Figure 4 As shown, the ECU 21 has a curvature calculation unit 221, an estimated steering angle calculation unit 222, and a communication control unit 223 as a functional configuration. The curvature calculation unit 221, the estimated steering angle calculation unit 222, and the communication control unit 223 are implemented by the CPU 22 of the ECU 21 reading and executing a program stored in the ROM 23.

[0041] The curvature calculation unit 221 calculates “curvature Cv1 of the travel trajectory of the diagnosis target vehicle 20 = yaw rate YR1 ÷ 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 .

[0042] The estimated steering angle calculation unit 222 calculates the curvature Cv1 and Figure 6The conversion map 38 shown is used to calculate the estimated steering angle STe1 of the diagnosis target vehicle 20. 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 turned in the clockwise direction is + (positive), and the sign of the steering angle ST1 when the steering wheel 31 is turned in the counterclockwise direction is - (negative). In addition, the sign of the curvature Cv1 when the diagnosis target vehicle 20 turns right is + (positive), and the sign of the curvature Cv1 when the diagnosis target vehicle 20 turns left is - (negative). 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 well known that the steering angle of the vehicle and the curvature of the driving trajectory are almost proportional to each other. The line in the curve diagram shown in the conversion map 38 is therefore substantially linear. The estimated steering angle calculation unit 222 acquires the steering angle STe1 as the estimated steering angle STe1 by applying the calculated curvature Cv1 as an independent variable to the conversion map 38. Furthermore, the estimated steering angle calculation unit 222 records the acquired estimated steering angle STe1 in the memory 25 in association with the ID information of the diagnosis target vehicle 20, the above-mentioned position information and the time information.

[0043] 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 memory 25 to the external server 60 every time a predetermined time elapses.

[0044] The vehicle behavior estimation system 10 has a reference vehicle 40. The reference vehicle 40 can perform data communication with an external server 60 via a network.

[0045] like Figure 2 As shown, a reference vehicle 40 includes four wheels including two steering wheels (front wheels) 40FW, 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 steering angles of the left and right steering wheels 40FW change.

[0046] like Figure 3As shown, the ECU 41 includes a CPU (processor) 42, a ROM 43, a RAM 44, a memory 45, a communication I / F 46, and an input-output I / F 47. The CPU 42, the ROM 43, the RAM 44, the memory 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 memory 45, the communication I / F 46, and the input-output I / F 47 are the same as the specifications of each of the CPU 22, the ROM 23, the RAM 24, the memory 25, the communication I / F 26, and the input-output I / F 27.

[0047] Figure 1 The external server 60 shown includes a CPU (processor), ROM, RAM, memory, communication I / F, and input-output I / F as a hardware configuration. The CPU, ROM, RAM, memory, communication I / F, and 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 obtain time-related information from a timer.

[0048] like Figure 5 As shown, the hardware of the external server 60 has a driving diagnosis unit 601 and a communication control unit 602 as a functional configuration. The driving diagnosis unit 601 and the communication control unit 602 are implemented by the CPU of the external server 60 reading and executing a program stored in a ROM or a memory.

[0049] The driving diagnosis unit 601 obtains the steering angle acceleration (curvature-related value) STa1 as the acceleration of the estimated steering angle STe1 by performing a second-order differentiation on the estimated steering angle STe1 received from the diagnosis target vehicle 20. The driving diagnosis unit 601 also records the obtained steering angle acceleration STa1 in the memory of the external server 60 in association with the ID information of the diagnosis target vehicle 20, the above-mentioned position information, and the time information.

[0050] Figure 7The shown steering diagnosis map (standard) 65 is recorded in the memory of the ROM or 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) which is the second-order differential value of the steering angle ST2, and a score related to steering. The vehicle speed V2 is the detected value of the vehicle speed sensor 30 of the reference vehicle 40. The steering angle ST2 is the detected 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, a score representing the behavior caused by the steering of the reference vehicle 40 can be obtained.

[0051] The steering diagnosis map 65 of the first embodiment defines the vehicle speed V2 by dividing the vehicle speed V2 into three regions. These three regions are the region less than A (km / h), the region of A or more and less than B (km / h), and the region of B or more. The magnitude relationship is represented by B > A, and A and B are positive values. As shown in the steering diagnosis map 65, when the vehicle speed V2 is less than A, the score is 10 when the steering angular acceleration STa2 is less than X1, and the score is 1 when the steering angular acceleration STa2 is X1 or more. When the vehicle speed V2 is A or more and less than B, the score is 10 when the steering angular acceleration STa2 is less than X2, and the score is 1 when the steering angular acceleration STa2 is X2 or more. When the vehicle speed V2 is B or more, the score is 10 when the steering angular acceleration STa2 is less than X3, and the score is 1 when the steering angular acceleration STa2 is X3 or more. It should be noted that the magnitude relationship is represented by X1 < X2 < 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 obtains a score related to the steering of each diagnostic 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. The driving diagnosis unit 601 also records the obtained score in the memory of the external server 60 in association with the ID information, location information, and time information of the diagnostic target vehicle 20.

[0052] The communication control unit 602 controls the communication I / F of the external server 60 to wirelessly send the information related to the score of the diagnostic target vehicle 20 to the portable terminal 70 carried by the occupant of the diagnostic target vehicle 20 to which the score is given. This information is recorded in the memory and is associated with the above-mentioned location information and time information.

[0053] Figure 1The mobile terminal 70 shown includes a CPU, a ROM, a RAM, a memory, a communication I / F, and an input-output I / F as a hardware configuration. The mobile terminal 70 is, for example, a smart phone or a tablet computer. The CPU, ROM, RAM, memory, communication I / F, and input-output I / F of the mobile terminal 70 are interconnected so as to be able to communicate with each other via a bus. The communication I / F of the mobile terminal 70 is capable of wireless communication with the communication I / F of the external server 60. The mobile terminal 70 is capable of obtaining information related to date and time from a timer (not shown). The mobile terminal 70 is provided with a display 71 having a touch panel. In addition, mapping data is recorded in the memory of the mobile terminal 70. The mobile terminal 70 is carried by, for example, a driver of the diagnostic target vehicle 20. A predetermined driving diagnosis display application is installed on the mobile terminal 70.

[0054] Operation and Effect

[0055] Next, the operation and effects of the first embodiment will be described.

[0056] First, refer to Figure 8 The flowchart shown describes the flow of processing executed by the ECU 21 of each diagnosis target vehicle 20. The ECU 21 repeatedly executes the processing every predetermined time. Figure 8 Processing of the flowchart shown.

[0057] First, in step S10 , 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 .

[0058] The ECU 21 having completed the processing of step S10 proceeds to step S11. In step S11, the estimated steering angle calculation unit 222 of the ECU 21 acquires the estimated steering angle STe1 by applying the curvature Cv1 as an argument to the conversion map 38.

[0059] The ECU 21 having completed the processing of step S11 proceeds to step S12. In step S12, the communication control unit 223 of the ECU 21 controls the communication I / F 26 to wirelessly transmit the vehicle speed V1, yaw rate YR1, curvature Cv1, and estimated steering angle STe1 recorded in the memory 25 and associated with the position information and time information to the external server 60.

[0060] When the process of step S12 is completed, the ECU 21 temporarily ends Figure 8 Processing of the flowchart shown.

[0061] Next, we will refer to Fig. 9The flowchart shown in the figure describes the flow of processing performed by the external server 60. The external server 60 repeatedly executes Fig. 9 Processing of the flowchart shown.

[0062] First, in step S20 , the communication control unit 602 of the external server 60 determines whether the communication I / F receives the vehicle speed V1 , the yaw rate YR1 , the curvature Cv1 , and the estimated steering angle STe1 from the diagnosis target vehicle 20 .

[0063] The external server 60 that determines "yes" in step S20 proceeds to step S21, and the driving diagnosis unit 601 calculates the steering angle acceleration STa1 as the acceleration of the estimated steering angle STe1. In addition, the driving diagnosis unit 601 acquires a score related to the steering of the diagnosis target vehicle 20 by applying the vehicle speed V1 and the steering angle acceleration STa1 to the steering diagnosis map 65. The driving diagnosis unit 601 also records the acquired score in the memory of the external server 60 in association with the ID information, position information, and time information of the diagnosis target vehicle 20.

[0064] The external server 60 having completed the processing of step S21 proceeds to step S22. In step S22, the communication control unit 602 of the external server 60 controls the communication I / F 46 to wirelessly transmit the score-related information recorded in the memory and associated with the position information and the time information to the mobile terminal 70.

[0065] When the determination in step S20 is "No" or when the processing in step S22 is completed, the external server 60 temporarily ends the Fig. 9 Processing of the flowchart shown.

[0066] Next, we will refer to Fig.10 The flowchart shown in FIG. 1 is used to describe the process flow executed by the mobile terminal 70. The mobile terminal 70 repeats the process every predetermined time. Fig.10 Processing of the flowchart shown.

[0067] In step S30 , the CPU of the mobile terminal 70 determines whether the driving diagnosis display application is running.

[0068] The mobile terminal 70 that determines "Yes" in step S30 proceeds to step S31 and determines whether the communication I / F of the mobile terminal 70 has received score information related to the diagnosis target vehicle 20 in which the person carrying the mobile terminal 70 is riding from the communication I / F of the external server 60.

[0069] The mobile terminal 70 determined as "yes" in step S31 proceeds to step S32, and the CPU causes the display 71 to display an image (not shown) showing the score. At this time, the display 71 can display a mapping image represented by mapping data recorded in the memory of the mobile terminal 70, and can display the position where the steering operation corresponding to the score is performed as a specific image superimposed on the mapping image. In addition, the display 71 can display information indicating the time when the steering operation corresponding to the score is performed in association with the score.

[0070] When the determination in step S30 is "No" or when the processing of step S32 is completed, the mobile terminal 70 temporarily ends the Fig.10 Processing of the flowchart shown.

[0071] 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 driving trajectory of the diagnostic target vehicle 20 is obtained based on the yaw rate YR1 and the vehicle speed V1 of the diagnostic target vehicle 20. In addition, the driving diagnosis related to the steering of the diagnostic target vehicle 20 is performed based on the steering angular acceleration STa1 (curvature-related value), which is based on the steering diagnostic map 65 and the value of the curvature Cv1. As described above, the steering diagnostic 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 diagnostic map 65 does not define the relationship between the steering angular acceleration STa1 of the diagnostic target vehicle 20 and the behavior of the diagnostic target vehicle 20. However, it is known that the relationship between the curvature of the driving trajectory and the behavior caused by the steering of the vehicle is basically the same, regardless of the vehicle type (specification) of the vehicle. In addition, as described above, the steering angle of the vehicle can be obtained from the curvature of the driving trajectory. Therefore, the score obtained by applying the steering angular acceleration STa1, which is a value based on the curvature Cv1 of the diagnosis target vehicle 20, to the steering diagnostic 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 are capable of performing driving diagnosis related to the steering of the diagnosis target vehicle 20 based on the steering diagnostic map 65 (standard) and the steering angular acceleration STa1 (curvature-related value) of the diagnosis target vehicle 20. In addition, by applying the steering angular acceleration STa2 to the steering diagnostic map 65, driving diagnosis related to the steering of the reference vehicle 40 can be performed. That is, the vehicle behavior estimation system 10 and the vehicle behavior estimation method of the first embodiment are capable of performing driving diagnosis related to the steering of the reference vehicle 40 and the diagnosis target vehicle 20 based on one standard.

[0072] Next, we will refer to Figures 11 to 17A second embodiment of the vehicle behavior estimation system 10 and the vehicle behavior estimation method according to the present invention is described. The same configuration and functions as those of the first embodiment are denoted by the same reference numerals, and detailed description thereof is omitted.

[0073] like Fig.11 As shown, the ECU 21 of each diagnosis target vehicle 20 of the second embodiment has a curvature calculation unit 221 and a communication control unit 223 as a functional configuration. In addition, 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 a functional configuration. 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 by the CPU 42 of the ECU 41 reading and executing the program stored in the ROM 43.

[0074] 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 memory 25 in association with the ID information, position information and time information of the diagnosis target vehicle 20.

[0075] The communication control unit 223 controls the communication I / F 26 so as to wirelessly transmit the vehicle speed V1, steering angle ST1, yaw rate YR1 and curvature Cv1 recorded in the memory 25 and associated with the above-mentioned position information and time information to the external server 60 every predetermined time.

[0076] The curvature calculation unit 421 calculates “curvature Cv2 of the travel trajectory of the reference vehicle 40 = yaw rate YR2 ÷ 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 .

[0077] The communication control unit 423 controls the communication I / F 46 so that the vehicle speed V2, steering angle ST2, yaw rate YR2 and curvature Cv2 recorded in the memory 45 and associated with the above-mentioned position information and time information are wirelessly transmitted to the external server 60 every predetermined time.

[0078] like Fig.12 As shown, 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 a functional configuration.

[0079] The map creation unit 603 creates a map based on the steering angle ST1 and the curvature Cv1 received from each diagnosis target vehicle 20. Fig.13 The first map 75 shown. 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 curvature Cv1 on the first map 75. Then, the map creation unit 603 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, Fig.15 As shown, it is assumed that the steering angle ST1 corresponding to the predetermined value P1 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 squares as the value Q1 of the steering angle ST1 corresponding to P1.

[0080] Furthermore, in the same manner, the map creation unit 603 creates the map based on the steering angle ST2 and the curvature Cv2 received from the reference vehicle 40. Fig.14 The second map 80 shown. In general, 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 represent the relationship between the steering angle and the curvature of the diagnosis target vehicle 20 and the reference vehicle 40, compared with the first map 75 and the second map 80 that are not created based on the average value. Therefore, the reliability of the first map 75 and the second map 80 created in this way is high.

[0081] Operation and Effect

[0082] Next, the operation and effects of the second embodiment will be described.

[0083] First, refer to Fig.16 The flowchart shown describes the flow of processing executed by the ECU 21 of each diagnosis target vehicle 20 and the ECU 41 of the reference vehicle 40. The ECU 21, 41 repeatedly executes the processing every time a predetermined time elapses. Fig.16 Processing of the flowchart shown.

[0084] First, in step S10 , the curvature calculation unit 221 , 421 of the ECU 21 , 41 calculates the curvatures Cv1 , Cv2 .

[0085] The ECU 21, 41 having completed the process of step S10 proceeds to step S12. In step S12, the communication control unit 223 of the ECU 21 controls the communication I / F 26 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 S12, the communication control unit 423 of the ECU 41 controls the communication I / F 46 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.

[0086] When the process of step S12 is completed, the ECU 21, 41 temporarily ends the Fig.16 Processing of the flowchart shown.

[0087] Next, we will refer to Fig.17 The flowchart shown in the figure describes the flow of processing performed by the external server 60. The external server 60 repeatedly executes Fig.17 Processing of the flowchart shown.

[0088] First, in step S40, the communication control unit 602 of the external server 60 determines whether the communication I / F has received the vehicle speed V1, steering angle ST1, yaw rate YR1 and curvature Cv1 from the diagnostic target vehicle 20, or whether the communication I / F has received the vehicle speed V2, steering angle ST2, yaw rate YR2 and curvature Cv2 from the reference vehicle 40.

[0089] The external server 60 that determines “YES” in step S40 proceeds to step S41 , and the map creation unit 603 creates (updates) the first map 75 based on the received steering angle ST1 and curvature Cv1 .

[0090] The external server 60 having completed the processing of step S41 proceeds to step S42. In step S42, 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 steering angles ST1 and curvatures Cv1 constituting the first map 75 is equal to or greater than a predetermined number, and whether the steering angles ST1 and curvatures Cv1 constituting the first map 75 include values ​​having absolute values ​​of various sizes.

[0091] The external server 60 that determines "yes" in step S42 proceeds to step S43, and the mapping creation unit 603 sets the first mapping flag to "1." The initial value of the first mapping flag is "0."

[0092] The external server 60 determined as “No” in step S42 proceeds to step S44 , and the mapping creation unit 603 sets the first mapping flag to “0”.

[0093] The external server 60 having completed the process of step S43 or step S44 proceeds to step S47, 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.

[0094] The external server 60 having completed the processing of step S47 proceeds to step S48. In step S48, the map creation unit 603 of the external server 60 determines whether the second map 80 satisfies the use condition. That is, the map creation unit 603 determines whether the number of steering angles ST2 and curvatures Cv2 constituting the second map 80 is equal to or greater than a predetermined number, and whether the steering angles ST2 and curvatures Cv2 constituting the second map 80 include values ​​having absolute values ​​of various sizes.

[0095] The external server 60 that determines "yes" in step S48 proceeds to step S49, and the mapping creation unit 603 sets the second mapping flag to "1." The initial value of the second mapping flag is "0."

[0096] The external server 60 determined as "NO" in step S48 proceeds to step S50, and the mapping creation unit 603 sets the second mapping flag to "0".

[0097] The external server 60 having completed the process of step S49 or step S50 proceeds to step S53, and the mapping creation unit 603 determines whether the first mapping flag and the second mapping flag are "1".

[0098] The external server 60 that determines "yes" in step S53 proceeds to step S54, and calculates the correction steering angle Stc1 of the diagnosis target vehicle 20 using the first map 75 and the second map 80. 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 as an independent variable to the first map 75. At this time, the map creation unit 603 performs interpolation processing of the first map 75 as needed. For example, assuming that the magnitude of the steering angle ST1 is Fig.13The magnitude of the curvature Cv1 obtained by applying the steering angle ST-A as an independent variable to the first map 75 is the curvature Cv-A. In addition, 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 as an independent variable to the second map 80. At this time, the map creation unit 603 performs interpolation processing of the second map 80 as needed. The steering angle ST-B is the correction steering angle Stc1 of the diagnosis target vehicle 20.

[0099] The external server 60 having completed the processing of step S54 proceeds to step S55, and the driving diagnosis unit 601 calculates the steering angle acceleration (curvature related value) (corrected curvature related value) STca1 as the acceleration of the corrected steering angle Stc1. In addition, the driving diagnosis unit 601 acquires a score related to the steering of the diagnosis target vehicle 20 by applying the vehicle speed V1 and the steering angle acceleration STca1 to the steering diagnosis map 65. The driving diagnosis unit 601 also records the acquired score in the memory of the external server 60 in association with the ID information, position information, and time information of the diagnosis target vehicle 20.

[0100] The external server 60 having completed the processing of step S55 proceeds to step S56. In step S56, the communication control unit 602 of the external server 60 controls the communication I / F 46 to wirelessly transmit the score-related information recorded in the memory and associated with the ID information, position information and time information to the mobile terminal 70.

[0101] When the determination in steps S40 and S53 is "No" or when the processing in step S56 is completed, the external server 60 temporarily ends the Fig.17 Processing of the flowchart shown.

[0102] In addition, the mobile terminal 70 repeatedly executes Fig.10 Therefore, when the CPU of the mobile terminal 70 proceeds to step S32, the CPU causes the display 71 to display an image (not shown) showing the score.

[0103] As described above, the external server 60 and the vehicle behavior estimation method of the vehicle behavior estimation system 10 of the second embodiment acquire 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 independent variable. In addition, the external server 60 acquires the correction steering angle STc1 as a correction value of the steering angle of the steering wheel 31 of the diagnosis target vehicle 20 by applying the curvature Cv-A as an independent variable to the second map 80. The external server 60 also performs driving diagnosis related to the steering of the diagnosis target vehicle 20 based on the steering angle acceleration STca1 as a second-order differential value of the correction 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 of the diagnosis target vehicle 20 and the curvature Cv1, and between the steering angle ST2 of the reference vehicle 40 and the curvature Cv2. 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. Therefore, the score obtained by applying the steering angular acceleration STca1 of the diagnosis target vehicle 20 to the steering diagnostic 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 perform driving diagnosis related to the steering of the diagnosis target vehicle 20 based on the steering diagnostic map 65 (standard) and the steering angle ST1 of the diagnosis target vehicle 20.

[0104] In addition, the detection accuracy of the steering angle sensor is generally higher than the detection accuracy of the yaw rate sensor. Therefore, the steering angle acceleration STca1 of the second embodiment more accurately represents the acceleration of the steering angle of the diagnosis target vehicle 20 than the steering angle 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.

[0105] Furthermore, 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.

[0106] In addition, 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. Therefore, the latest status of the components that affect the curvature Cv1 of the diagnosis target vehicle 20 is included in the first map 75, and the latest status of the components that affect the curvature Cv2 of the reference vehicle 40 is included in the second map 80. These components include, for example, tires. Therefore, the reliability of the first map 75 and the second map 80 of the second embodiment is high.

[0107] 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 designs of the vehicle behavior estimation system 10 and the vehicle behavior estimation method may be appropriately changed within a scope not departing from the gist of the present invention.

[0108] For example, the steering diagnostic map 65 of the first embodiment may be a map that defines the relationship between the second-order differential value (steering angle related value) of the curvature Cv2 of the reference vehicle 40 and the behavior caused by the steering at each vehicle speed. In this case, the external server 60 calculates a score related to the driving operation of the diagnosis target vehicle 20 by applying the second-order differential value (curvature related value) of the curvature Cv1 of the diagnosis target vehicle 20 to the steering diagnostic map 65.

[0109] The steering diagnostic map 65 of the second embodiment may be a map that defines the relationship between the second-order differential value of the curvature Cv2 of the reference vehicle 40 and the behavior caused by the steering at each vehicle speed. In this case, the external server 60 calculates a score related to the driving operation of the diagnosis target vehicle 20 by applying the second-order differential 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 diagnostic map 65.

[0110] The vehicle behavior estimation system 10 of the first and second embodiments does not need 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 (e.g., a universal serial bus (USB)), and the detection value data group in the recording medium is copied and stored in the memory of the external server 60.

[0111] The external server 60 of the first and second embodiments may wirelessly transmit the diagnosis result to the diagnosis target vehicle 20 , and a display (not shown) provided on the diagnosis target vehicle 20 may display the diagnosis result.

[0112] 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.

[0113] 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 and estimated steering angle of the travel trajectory of the diagnosis target vehicle 20 based on information wirelessly transmitted from the diagnosis target vehicle 20 .

[0114] The content of the created second map 80 does not have to be updated after creation.

[0115] 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 a satellite of a global navigation satellite system (eg, Galileo) other than GPS.

Claims

1. A vehicle behavior estimation system, include: a yaw rate sensor that detects a yaw rate of a diagnostic target vehicle; A vehicle speed sensor, which detects the speed of the diagnosis target vehicle; as well as processor, wherein the processor acquiring a first curvature as a curvature of a travel track of the diagnosis target vehicle based on the yaw rate and the vehicle speed, and Driving diagnosis related to the steering of the diagnosis target vehicle is performed based on a standard and a curvature-related value, the standard being a standard that defines a relationship between a steering angle-related value and a behavior of a reference vehicle caused by steering, the steering angle-related value being a value based on a steering angle of a steering wheel of the reference vehicle, the reference vehicle being a vehicle different from the diagnosis target vehicle, and the curvature-related value being a value based on the first curvature.

2. The vehicle behavior estimation system according to claim 1, further comprising: include: a first map showing a relationship between a detection value of a first steering angle sensor as a steering angle sensor of the diagnosis target vehicle and the first curvature; as well as a second map showing a relationship between a detection value of a second steering angle sensor as a steering angle sensor of the reference vehicle and a second curvature as a curvature of a driving trajectory of the reference vehicle, wherein the processor applies the first curvature as an independent variable to the second map to obtain a corrected steering angle as a correction value of the steering angle of the diagnosis target vehicle, and performs the driving diagnosis related to the steering of the diagnosis target vehicle based on a corrected curvature-related value, the first curvature being a curvature obtained by applying the detection value of the first steering angle sensor to the first map, the corrected curvature-related value being a value based on the corrected steering angle and the standard.

3. The vehicle behavior estimation system according to claim 2, wherein The first map is created based on an average value of values ​​obtained from 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 from the second curvature and the detection value of the second steering angle sensor.

4. The vehicle behavior estimation system according to claim 2 or 3, in, 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.

5. A vehicle behavior estimation method, wherein a processor is provided in a diagnosis target vehicle, the processor acquiring a first curvature as a curvature of a travel track of the diagnosis target vehicle based on a yaw rate and a vehicle speed of the diagnosis target vehicle, and Driving diagnosis related to the steering of the diagnosis target vehicle is performed based on a standard and a curvature-related value, the standard being a standard that defines a relationship between a steering angle-related value and a behavior of a reference vehicle caused by steering, the steering angle-related value being a value based on a steering angle of a steering wheel of the reference vehicle, the reference vehicle being a vehicle different from the diagnosis target vehicle, and the curvature-related value being a value based on the first curvature.

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