Information Processing Apparatus, Vehicle, Information Processing System, Information Processing Method, and Program

Abstract

To efficiently evaluate features of a driver in driving.SOLUTION: A brake ECU executes processing including: a step (S100) of acquiring input information; a step (S102) of determining whether or not a predetermined condition is established; a step (S104) of acquiring vehicle speed data when the predetermined condition is established (YES in S102); a step (S106) of updating a vehicle speed frequency distribution with the use of the acquired vehicle speed data; and a step (S108) of transmitting the updated vehicle speed frequency distribution to a data center.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus.

Background Art

[0002] A technique for determining whether a driver is in a distracted state using data related to the driving state of a vehicle driver is known. For example, Japanese Unexamined Patent Application Publication No. 2017-215654 (Patent Document 1) discloses a technique for determining whether the time during which the driver's line of sight direction deviates from the determination range has continued for the determination time using data such as the driver's line of sight state and vehicle speed, and determining whether the driver is in a distracted state.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the above-mentioned Patent Document 1, a technique for determining the driving characteristics of a driver based on whether the driver's line of sight direction is within a determination range corresponding to any of the driving scenes of straight driving, turning, and left / right turning is disclosed. However, further improvement is required to efficiently evaluate the driving characteristics of the driver.

[0005] The present disclosure has been made to solve the above-mentioned problems, and an object thereof is to provide an information processing apparatus, a vehicle, an information processing system, an information processing method, and a program for efficiently evaluating the driving characteristics of a driver.

Means for Solving the Problems

[0006] An information processing apparatus according to an aspect of the present disclosure is an information processing apparatus that calculates a feature amount related to a driving characteristic of a driver of a vehicle. This information processing apparatus includes an acquisition unit that acquires an operation amount of the vehicle, a first processing unit that specifies a predetermined driving state during traveling of the vehicle using the acquired operation amount, and a second processing unit that calculates a feature amount in the predetermined driving state.

[0007] By doing so, by calculating the feature amount in the specified predetermined driving state, it is possible to efficiently evaluate the characteristics of the driver's driving.

[0008] In one embodiment, the predetermined driving state includes a steady driving state. By doing so, by specifying the steady driving state and calculating the feature amount in the specified driving state, it is possible to efficiently evaluate the characteristics of the driver's driving in that driving state.

[0009] Furthermore, in one embodiment, the acquisition unit acquires the accelerator opening of the vehicle. The first processing unit specifies, as the predetermined driving state, a driving state in which the change amount of the accelerator opening is equal to or less than a threshold value during traveling of the vehicle.

[0010] By doing so, it is possible to specify the predetermined driving state without using a complicated device.

[0011] Furthermore, in one embodiment, the feature amount includes a history of the speed of the vehicle. By doing so, it is possible to efficiently evaluate the characteristics of the driving, such as whether the vehicle is driving in harmony with the surroundings in the driving state where the vehicle is traveling at a constant speed and whether there is a tendency to comply with the speed limit, from the history of the speed of the vehicle.

[0012] Furthermore, in one embodiment, the information processing apparatus further includes a third processing unit that calculates the frequency distribution of the speed of the vehicle.

[0013] By doing so, it is possible to efficiently evaluate driving characteristics such as whether the driver is driving in harmony with the surroundings among the vehicle group and whether the driver tends to comply with the speed limit from the frequency distribution of the vehicle speed.

[0014] Furthermore, in a certain embodiment, the predetermined driving state includes a driving state in which steering is performed while the vehicle is going straight.

[0015] By doing so, by specifying the driving state in which steering is performed while the vehicle is going straight and calculating the feature amount in the specified driving state, it is possible to efficiently evaluate the driving characteristics of the driver in the driving state.

[0016] Furthermore, in a certain embodiment, the feature amount includes a time integral value of the difference between a first steering amount estimated from the behavior of the vehicle and a second steering amount actually performed.

[0017] By doing so, it is possible to efficiently evaluate driving characteristics such as the presence or absence of unnecessary steering wheel operation and the presence or absence of proficiency in steering wheel operation from the time integral value of the difference between the first steering amount and the second steering amount in the driving state in which an operation is performed while the vehicle is going straight.

[0018] Furthermore, in a certain embodiment, the information processing apparatus further includes a third processing unit that calculates a frequency distribution of the time integral value.

[0019] By doing so, it is possible to efficiently evaluate driving characteristics such as the presence or absence of unnecessary steering wheel operation and the presence or absence of proficiency in steering wheel operation from the frequency distribution of the time integral value.

[0020] Furthermore, in a certain embodiment, the predetermined driving state includes a driving state until the traveling vehicle is stopped.

[0021] By doing so, by specifying the driving state until the vehicle in motion stops and calculating the feature amount in the specified driving state, it is possible to efficiently evaluate the driving characteristics of the driver in that driving state.

[0022] Furthermore, in a certain embodiment, the feature amount includes the difference between the peak value of the brake hydraulic pressure and the average value of the brake hydraulic pressure after the peak.

[0023] By doing so, it is possible to efficiently evaluate driving characteristics such as whether the driver is accustomed to the braking operation from the difference between the peak value and the average value of the brake hydraulic pressure.

[0024] Furthermore, in a certain embodiment, the information processing device further includes a third processing unit that specifies which of a plurality of sections divided in the order of the magnitude of the difference the difference corresponds to.

[0025] By doing so, it is possible to efficiently evaluate driving characteristics such as whether the driver is accustomed to the braking operation by specifying which of the plurality of sections the difference corresponds to.

[0026] A vehicle according to another aspect of the present disclosure is a vehicle including an information processing device that calculates a feature amount related to a driving characteristic of a driver. The information processing device includes an acquisition unit that acquires an operation amount of the vehicle, a first processing unit that specifies a predetermined driving state during traveling of the vehicle using the acquired operation amount, and a second processing unit that calculates a feature amount in the predetermined driving state.

[0027] An information processing system according to still another aspect of the present disclosure includes an information processing device that calculates a feature amount related to a driving characteristic of a driver of a vehicle, and a server that manages information transmitted from the information processing device. The information processing device includes an acquisition unit that acquires an operation amount of the vehicle, a first processing unit that specifies a predetermined driving state during traveling of the vehicle using the acquired operation amount, and a second processing unit that calculates a feature amount in the predetermined driving state.

[0028] A vehicle information processing method according to still another aspect of the present disclosure is an information processing method for calculating a feature amount related to the driving characteristics of a driver of a vehicle. This information processing method includes a step of acquiring an operation amount of the vehicle, a step of specifying a predetermined driving state during running of the vehicle using the acquired operation amount, and a step of calculating a feature amount in the predetermined driving state.

[0029] A program according to still another aspect of the present disclosure causes a computer to execute a step of acquiring an operation amount of a vehicle, a step of specifying a predetermined driving state during running of the vehicle using the acquired operation amount, and a step of calculating a feature amount related to the driving characteristics of a driver of the vehicle in the predetermined driving state.

Advantages of the Invention

[0030] According to the present disclosure, it is possible to provide an information processing apparatus, a vehicle, an information processing system, an information processing method, and a program that can efficiently evaluate the driving characteristics of a driver.

Brief Description of the Drawings

[0031]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Figure 11

Mode for Carrying Out the Invention

[0032] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the drawings, the same or corresponding parts are denoted by the same reference numerals and their description will not be repeated.

[0033] FIG. 1 is a diagram for explaining an example of the configuration of the information processing system 1. As shown in FIG. 1, in the present embodiment, the information processing system 1 includes a plurality of vehicles 2 and 3, a communication network 6, a base station 7, and a data center 100.

[0034] The vehicles 2 and 3 only need to be able to communicate with the data center 100. For example, they may be vehicles with an engine as a drive source, or electric vehicles with an electric motor as a drive source, or hybrid vehicles equipped with an engine and an electric motor and using at least one of them as a drive source. In FIG. 1, for the sake of convenience of explanation, only two vehicles 2 and 3 are shown, but the number of vehicles is not particularly limited to two and may be three or more.

[0035] The information processing system 1 is configured to acquire predetermined information from the vehicles 2 and 3 configured to be able to communicate with the data center 100 and manage the acquired information.

[0036] The data center 100 includes a control device 11, a storage device 12, and a communication device 13. The control device 11, the storage device 12, and the communication device 13 are connected to each other communicably via a communication bus 14.

[0037] Although not shown in the figures, the control device 11 includes a CPU (Central Processing Unit), a memory (such as a ROM (Read Only Memory) and a RAM (Random Access Memory)), and an input / output port for inputting and outputting various signals. Various controls executed by the control device 11 are software processes, that is, executed by a program stored in the memory being read by the CPU. Various controls by the control device 11 can also be realized by a general-purpose server (not shown) executing a program stored in a storage medium. However, various controls by the control device 11 are not limited to software processes and may be processed by dedicated hardware (electronic circuits).

[0038] The storage device 12 stores predetermined information regarding a plurality of vehicles 2 and 3 configured to be communicable with the data center 100. The predetermined information includes, for example, information regarding feature amounts calculated in each of the vehicles 2 and 3 described later, information for identifying the vehicles 2 and 3 (hereinafter referred to as vehicle IDs), and information for identifying the positions of the vehicles 2 and 3. The vehicle ID is unique information set for each vehicle. The data center 100 can identify the transmitting vehicle by the vehicle ID.

[0039] The communication device 13 realizes two-way communication between the control device 11 and the communication network 6. The data center 100 enables communication with a plurality of vehicles including the vehicles 2 and 3 via a base station 7 provided on the communication network 6 using the communication device 13.

[0040] Next, the specific configurations of the vehicles 2 and 3 will be described. Since the vehicles 2 and 3 basically have a common configuration, the configuration of the vehicle 2 will be typically described below.

[0041] The vehicle 2 includes front wheels 50 that are driving wheels and rear wheels 52 that are driven wheels. By rotating the front wheels 50 by the operation of a drive source, a driving force acts on the vehicle 2 and the vehicle 2 travels.

[0042] The vehicle 2 further includes an ADAS-ECU (Electronic Control Unit) 10, a brake ECU 20, a DCM (Data Communication Module) 30, and a central ECU 40.

[0043] The ADAS-ECU 10, the brake ECU 20, and the central ECU 40 are all computers having a processor that executes a program such as a CPU, a memory, and an input / output interface.

[0044] The ADAS-ECU 10 includes a driving assistance system having functions related to the driving assistance of the vehicle 2. The driving assistance system is configured to realize various functions for assisting the driving of the vehicle 2 including at least any one of the steering control, the drive control, and the braking control of the vehicle 2 by executing the applications to be implemented. Examples of the applications implemented in the driving assistance system include an application that realizes the function of an autonomous driving system (AD), an application that realizes the function of an automatic parking system, and an application that realizes the function of an advanced driver assistance system (ADAS).

[0045] Each application of this driving assistance system outputs a request for an action plan that ensures the commercial value (function) of the application alone to the brake ECU 20 based on information on the surrounding situation of the vehicle obtained (input) from a plurality of sensors (not shown) and the assistance request of the driver. The plurality of sensors include, for example, vision sensors such as a forward camera, radar, LiDAR (Light Detection And Ranging), or a position detection device.

[0046] Each application acquires information on the surrounding situation of the vehicle, which integrates the detection results of one or more sensors, as recognition sensor information, and also acquires a driver's assistance request via a user interface (not shown) such as a switch. Each application can recognize other vehicles, obstacles, or people around the vehicle by, for example, image processing using artificial intelligence (AI) or an image processing processor for images or videos of the surroundings of the vehicle acquired by a plurality of sensors.

[0047] The brake ECU 20 controls a brake actuator that generates a braking force for the vehicle 2 using the detection results from the sensors. Further, the brake ECU 20 sets a motion requirement for the vehicle 2 to realize the request for the action plan from the ADAS-ECU 10. The motion requirement for the vehicle 2 set in the brake ECU 20 is realized by an actuator system (not shown) provided in the vehicle 2. The actuator system includes, for example, a plurality of types of actuator systems such as a power train system, a brake system, and a steering system.

[0048] Connected to the brake ECU 20 are, for example, a wheel speed sensor 54, a steering angle sensor 60 that detects the steering angle (operation angle of the steering wheel), a brake hydraulic pressure sensor 62 that detects the master cylinder hydraulic pressure (brake hydraulic pressure), an accelerator opening sensor 64 that detects the depression amount of the accelerator pedal (accelerator opening), a yaw rate sensor 66, and a G sensor 68.

[0049] The wheel speed sensor 54 detects the rotational speed (revolution speed) of the front wheel 50 as the wheel speed. The wheel speed sensor 54 transmits a signal indicating the detected rotational speed of the front wheel 50 to the brake ECU 20.

[0050] The steering angle sensor 60 detects the angle at which the steering wheel is operated as the steering angle (steering amount). The steering angle sensor 60 transmits a signal indicating the detected steering angle to the brake ECU 20.

[0051] The brake hydraulic pressure sensor 62 is connected to a brake hydraulic circuit that supplies hydraulic pressure to a braking device provided for each wheel, and detects the hydraulic pressure in the hydraulic pressure chamber of a master cylinder configured to increase the hydraulic pressure in the brake hydraulic circuit according to the depression amount of the brake pedal as the brake hydraulic pressure. The brake hydraulic pressure sensor 62 transmits a signal indicating the detected brake hydraulic pressure to the brake ECU 20.

[0052] The accelerator opening sensor 64 detects the depression amount of the accelerator pedal as the accelerator opening. The accelerator opening sensor 64 transmits a signal indicating the detected accelerator opening to the brake ECU 20.

[0053] The yaw rate sensor 66 detects the rotational angular velocity (yaw rate) in the turning direction of the vehicle 2 (hereinafter also referred to as the yaw direction). The yaw rate sensor 66 transmits a signal indicating the detected rotational angular velocity in the yaw direction to the brake ECU 20.

[0054] The G sensor 68 detects the acceleration in the longitudinal direction of the vehicle 2 and the acceleration in the lateral direction of the vehicle 2. The G sensor transmits signals indicating the detected acceleration in the longitudinal direction of the vehicle 2 and the detected acceleration in the lateral direction of the vehicle 2 to the brake ECU 20.

[0055] In FIG. 1, as an example, the wheel speed sensor 54, the steering angle sensor 60, the brake hydraulic pressure sensor 62, the accelerator opening sensor 64, the yaw rate sensor 66, and the G sensor 68 are each connected to the brake ECU 20 and configured to directly transmit the detection results to the brake ECU 20. However, at least any one of the wheel speed sensor 54, the steering angle sensor 60, the brake hydraulic pressure sensor 62, the accelerator opening sensor 64, the yaw rate sensor 66, and the G sensor 68 may be connected to another ECU, and the detection results may be input to the brake ECU 20 via a communication bus or the central ECU 40.

[0056] Furthermore, the brake ECU 20 receives, for example, information regarding the operating states of various applications, information regarding other driving operations such as the shift range, information regarding the behavior of the vehicle 2, and information regarding the position information of the vehicle 2, in addition to information regarding the action plan from the ADAS-ECU 10.

[0057] The DCM 30 is a communication module configured to enable two-way communication with the data center 100.

[0058] The central ECU 40 is configured to be communicable with, for example, the brake ECU 20 and is also configured to be communicable with the data center 100 using the DCM 30. The central ECU 40 transmits, for example, the information received from the brake ECU 20 to the data center 100 via the DCM 30.

[0059] In the present embodiment, the central ECU 40 has been described as transmitting the information received from the brake ECU 20 to the data center 100 via the DCM 30. However, for example, it may have a function (gateway function) such as relaying communication between various ECUs, or it may include a memory (not shown) capable of updating the stored content using the update information from the data center 100, and predetermined information including the update information stored in the memory from various ECUs may be read out when the system of the vehicle 2 is started.

[0060] In the vehicle 2 having the configuration as described above, the brake ECU 20 is required to efficiently evaluate, for example, the characteristics of the driving by the driver during the running of the vehicle 2 using the information obtained from the sensors provided in the vehicle 2.

[0061] Therefore, in the present embodiment, the brake ECU 20 acquires the operation amount of the vehicle 2, specifies a predetermined driving state during the running of the vehicle 2 using the acquired operation amount, and calculates a feature amount in the specified predetermined driving state. In the present embodiment, the predetermined driving state includes a steady running state. Further, the feature amount includes the history of the speed of the vehicle 2.

[0062] By doing so, by specifying the steady running state of the vehicle 2 and calculating the history of the vehicle speed as a feature amount in the specified driving state, it is possible to efficiently evaluate the characteristics of the driving, such as whether the vehicle is driving in harmony with the surroundings in the vehicle group and whether it tends to comply with the restricted vehicle speed.

[0063] FIG. 2 is a diagram for explaining the configuration of an example of the information processing apparatus according to the present embodiment. The information processing apparatus according to the present embodiment is realized by the brake ECU 20.

[0064] The brake ECU 20 includes a first processing unit 22, a second processing unit 24, and a third processing unit 26. The first processing unit 22 receives information indicating the detection results from various sensors as information related to the behavior of the vehicle 2. The first processing unit 22 outputs the input information received during a period in which a predetermined condition is satisfied during the period of receiving the input information to the second processing unit 24.

[0065] The second processing unit 24 calculates a feature amount related to the operation of the vehicle 2 using the input information received during a period in which a predetermined condition is satisfied during the period of receiving the input information.

[0066] FIG. 3 is a diagram for explaining an example of the processing executed in the second processing unit 24. As shown in FIG. 3, the rotation speed of the front wheels 50, the depression amount of the accelerator pedal (accelerator opening), the master cylinder hydraulic pressure (brake hydraulic pressure), the steering angle, the yaw rate (the turning speed of the vehicle 2 in the yaw direction), and the acceleration in the longitudinal and lateral directions of the vehicle 2 are input as input information to the second processing unit 24 from the first processing unit 22. The second processing unit 24 determines whether or not a predetermined condition for specifying a predetermined driving state is satisfied using these input information.

[0067] In the present embodiment, the predetermined conditions include the condition that the vehicle 2 is in motion and the condition that the magnitude of the change amount of the accelerator opening per predetermined time is equal to or less than a threshold value. The second processing unit 24 determines that the predetermined condition is satisfied, for example, when the vehicle speed of the vehicle 2 is greater than the threshold value and the magnitude of the change amount of the accelerator opening per predetermined time is equal to or less than the threshold value. The predetermined time may be, for example, a time corresponding to the time interval at which the vehicle speed is acquired, or a time longer than the time interval.

[0068] When it is determined that the predetermined condition is satisfied, the second processing unit 24 turns on the establishment flag. The second processing unit 24 outputs a signal indicating the state of this establishment flag as a scene identification signal.

[0069] When it is determined that the predetermined condition is satisfied, the second processing unit 24 calculates a feature amount related to the driving characteristics of the driver of the vehicle 2 using the input information received during the period in which the predetermined condition is satisfied.

[0070] In this embodiment, the feature amount includes, for example, the history of the speed (vehicle speed) of the vehicle 2. In this embodiment, the second processing unit 24 outputs, as a feature amount, the history of the vehicle speed calculated using, for example, the rotational speed of the front wheel 50 acquired while a predetermined condition is satisfied. The second processing unit 24 outputs, for example, a feature amount indicating the history of the vehicle speed in association with time together with the scene identification signal while a predetermined condition is satisfied.

[0071] The third processing unit 26 generates information about the driving characteristics of the driver using, for example, the information output from the second processing unit 24 when the state of the establishment flag included in the scene identification signal is a predetermined state (for example, on state). In this embodiment, the third processing unit 26 generates a frequency distribution of the vehicle speed updated using the information output from the second processing unit 24.

[0072] FIG. 4 is a diagram for explaining an example of the processing executed in the third processing unit 26. As shown in FIG. 4, information indicating the scene identification signal, the feature amount, and the time is input to the third processing unit 26 from the second processing unit 24. The third processing unit 26 outputs information about the driving characteristics of the driver to the central ECU 40.

[0073] Note that the third processing unit 26 may generate a frequency distribution of the vehicle speed updated every time it receives information from the second processing unit 24, or may generate a frequency distribution of the vehicle speed updated every time a state changes from a state where a predetermined condition is satisfied to a non-satisfied state, or may generate a frequency distribution of the vehicle speed updated for each trip.

[0074] The central ECU 40 transmits the information input from the third processing unit 26 to the data center 100 via the DCM 30.

[0075] The data center 100 evaluates whether the driving by the driver is a driving that harmonizes with the vehicles around the vehicle 2 among the vehicle group using the output value of the third processing unit 26, and also evaluates whether the driving by the driver is a driving that obeys the speed limit.

[0076] The information transmitted from the DCM 30 to the data center 100 includes, for example, the processing time, the vehicle position information, and the information about the frequency distribution of the vehicle speed. Therefore, the data center 100 stores the information input from the DCM 30 in the storage device 12 as a set of data. As a result, the data center 100 can obtain information about the driving characteristics of the driver who drives the vehicle 2 capable of communicating with the data center 100. Similarly, the data center 100 can obtain information about the driving characteristics of the driver who drives the vehicle 3 capable of communicating with the data center 100.

[0077] Next, with reference to FIG. 5, an example of the processing executed by the brake ECU 20 of the vehicle 2 will be described. FIG. 5 is a flowchart showing an example of the processing executed by the brake ECU 20. The series of processes shown in this flowchart are repeatedly executed by the brake ECU 20 at predetermined control cycles.

[0078] In step (hereinafter, steps are described as S) 100, the brake ECU 20 acquires data corresponding to the input information. Specifically, the brake ECU 20 acquires, for example, data corresponding to the input information including information about the rotational speed of the front wheels 50, information about the accelerator opening, information about the brake hydraulic pressure, information about the steering angle, information about the yaw rate, and information about the acceleration in the longitudinal and lateral directions of the vehicle 2. The brake ECU 20 may acquire data corresponding to the input information from various sensors, or may acquire data corresponding to the input information from a memory in which the detection results by various sensors are stored. The subsequent process proceeds to S102.

[0079] In S102, the brake ECU 20 determines whether or not a predetermined condition is satisfied. Since the predetermined condition is as described above, a detailed description thereof will not be repeated. If it is determined that the predetermined condition is satisfied (YES in S102), the process proceeds to S104.

[0080] In S104, the brake ECU 20 acquires vehicle speed data indicating the history of the vehicle speed. For example, the brake ECU 20 reads and acquires from a memory or the like data indicating the history of the vehicle speed acquired after the update of the previous vehicle speed frequency distribution. Then the process proceeds to S106.

[0081] In S106, the brake ECU 20 updates the vehicle speed frequency distribution. The brake ECU 20 creates a vehicle speed frequency distribution for each trip. Specifically, for example, the brake ECU 20 creates a new vehicle speed frequency distribution at the timing when the IG is turned on, and updates the vehicle speed frequency distribution using the vehicle speed data indicating the history of the vehicle speed acquired during a period in which a predetermined condition is satisfied. The vehicle speed frequency distribution is set with, for example, a plurality of non-overlapping speed regions at predetermined speed intervals (for example, 5 km / h). The brake ECU 20 determines in which speed region among the plurality of speed regions the acquired vehicle speed is, and increases the value indicating the frequency corresponding to the determined speed region. When the vehicle speed is acquired at predetermined time intervals and the value indicating the frequency indicates, for example, the cumulative time in that speed region, a predetermined time is added to the value indicating the frequency corresponding to the determined speed region. The brake ECU 20 executes the above-described process using the vehicle speed data indicating the history of the vehicle speed that was not used for the update of the previous vehicle speed frequency distribution. For example, the brake ECU 20 ends the creation of the vehicle speed frequency distribution at the timing when the IG is turned off and stores it in a memory or the like. The brake ECU 20 creates a vehicle speed frequency distribution for each trip by executing such a process.

[0082] In S108, the brake ECU 20 transmits the updated vehicle speed frequency distribution to the data center 100. The brake ECU 20 transmits information about the updated vehicle speed frequency distribution to the central ECU 40. The central ECU 40 transmits the received information to the data center 100 via the DCM 30. Then this process ends. Note that if it is determined that a predetermined condition is not satisfied (NO in S102), this process ends.

[0083] The processing of S100, the processing of S102, the processing of S104, and the processing of S106 described above are included in the processing executed by the second processing unit 24. Further, the processing of S108 described above is included in the processing executed by the third processing unit 26.

[0084] The data center 100 can evaluate the driving characteristics of the driver of the vehicle 2 using the received information. Since the information transmitted to the data center 100 and the processing executed in the data center 100 are as described above, detailed descriptions thereof will not be repeated.

[0085] The operation of the brake ECU 20, which is an information processing apparatus according to the present embodiment based on the above structure and flowchart, will be described with reference to FIGS. 6 and 7.

[0086] For example, when input information is acquired during the running of the vehicle 2 (S100), it is determined whether a predetermined condition is satisfied (S102). When the vehicle 2 is running and the magnitude of the change in the accelerator opening per predetermined time is equal to or less than the threshold value, it is determined that the predetermined condition is satisfied (YES in S102). Therefore, vehicle speed data is acquired (S104), and the vehicle speed frequency distribution is updated (S106). That is, if there is vehicle speed data acquired while a predetermined condition that was not reflected in the previous update of the vehicle speed frequency distribution is satisfied during the same trip, it is determined to which of a plurality of speed ranges the vehicle speed included in the vehicle speed data corresponds, and a predetermined time is added to the cumulative time corresponding to the determined speed range. In this way, the vehicle speed frequency distribution is updated by calculating the cumulative time in at least one of the plurality of speed ranges. The updated vehicle speed frequency distribution is transmitted to the data center 100 (S108).

[0087] The data center 100 can evaluate the driving characteristics of the driver of the vehicle 2 based on the received vehicle speed frequency distribution.

[0088] FIG. 6 is a diagram showing an example of the vehicle speed frequency distribution during one trip. The vertical axis of FIG. 6 indicates the cumulative time. The horizontal axis of FIG. 6 indicates the vehicle speed. In FIG. 6, the cumulative time in each of a plurality of speed ranges during one trip is shown as a bar graph. For example, assume that the highest speed limit on the route driven by the driver of vehicle 2 during one trip is V(0). In this case, the driver of vehicle 2 is traveling at a speed that is lower by a certain amount than the speed limit V(0) on at least the route including the point where the speed limit becomes V(0).

[0089] The data center 100 compares, for example, the vehicle speed frequency distribution of other vehicles with the same time period as the time period when vehicle 2 traveled on the route including the point where the speed limit becomes V(0). When other vehicles are also traveling at a speed that is lower by a certain amount than the speed limit V(0) in their vehicle speed frequency distributions, it becomes possible to evaluate that the driver of vehicle 2 was driving in harmony with the surrounding vehicles in the vehicle group. On the other hand, when the frequency (cumulative time) of traveling near the speed limit V(0) is high in the vehicle speed frequency distribution of other vehicles, it becomes possible to evaluate that the driver of vehicle 2 was driving in a speed range slower than other vehicles in the vehicle group. In this way, it becomes possible to evaluate the driving characteristics and driving proficiency of the driver of vehicle 2.

[0090] FIG. 7 is a diagram showing another example of the vehicle speed frequency distribution during one trip. The vertical axis of FIG. 7 indicates the cumulative time. The horizontal axis of FIG. 7 indicates the vehicle speed. In FIG. 7, the cumulative time in each of a plurality of speed ranges during one trip is shown as a bar graph. Similar to the case described in FIG. 6, for example, assume that the highest speed limit on the route driven by the driver of vehicle 2 during one trip is V(0). In this case, the driver of vehicle 2 is traveling at a speed near the speed limit V(0) on at least the route including the point where the speed limit becomes V(0).

[0091] The data center 100 can evaluate from such a vehicle speed frequency distribution that the driver of vehicle 2 was driving while observing the speed limit V(0).

[0092] As described above, according to the information processing apparatus according to the present embodiment, it is possible to determine whether or not the vehicle is in a steady running state based on the accelerator opening without using a complicated device such as a radar, and by calculating the vehicle speed in the steady running state during the driving of the vehicle 2 as a feature amount, it is possible to efficiently evaluate whether the driving of the driver in the steady running state is in harmony with the surroundings or whether the speed limit is observed. Therefore, it is possible to provide an information processing apparatus, a vehicle, an information processing system, an information processing method, and a program that efficiently evaluate the characteristics of the driver's driving.

[0093] Furthermore, when calculating the feature amount and the vehicle speed frequency distribution inside the vehicle, it is not necessary to transmit the information for calculating the feature amount and the vehicle speed frequency distribution to the outside. Therefore, in the case where the amount of information for calculating the feature amount and the vehicle speed frequency distribution is large, etc., unnecessary information is suppressed from being transmitted outside the vehicle, and an increase in communication load, the storage capacity, and the processing cost in the data center 100 are suppressed.

[0094] Furthermore, by separately performing the calculation of the feature amount and the calculation of the vehicle speed frequency distribution by the second processing unit 24 and the third processing unit 26, for example, only the method of calculating the vehicle speed frequency distribution in the third processing unit 26 can be changed and used for the evaluation of other driving characteristics. Such a change can be realized, for example, by the brake ECU 20 reading the update information received from the data center 100 and stored in the memory of the central ECU 40.

[0095] Hereinafter, modified examples will be described. In the above-described embodiment, as an example, the case where the input information input to the brake ECU 20 is used to calculate the feature amount and the vehicle speed frequency distribution by executing the processing shown in the flowchart of FIG. 5 inside the brake ECU 20 has been described, but the processing may be executed in the data center 100.

[0096] Furthermore, in the above-described embodiment, the brake ECU 20 has been described as transmitting the vehicle speed frequency distribution to the data center 100 every time it is updated. However, for example, the vehicle speed frequency distribution updated immediately before the timing of the end of a trip (when the IG is turned off) may be transmitted to the data center 100.

[0097] Furthermore, in the above-described embodiment, the case where the brake ECU 20 calculates a feature amount while in a steady running state and updates the vehicle speed frequency distribution has been described as an example. However, the brake ECU 20 may update the vehicle speed frequency distribution using, for example, the history of the vehicle speed during the period when the vehicle was in a steady running state when it changed from a steady running state to a non-steady running state.

[0098] Furthermore, in the above-described embodiment, as an example of a predetermined driving state, the history of the vehicle speed in the steady running state is calculated as a feature amount, and the driving characteristics of the driver are evaluated by calculating the vehicle speed frequency distribution using the calculated feature amount. However, the predetermined driving state and feature amount are not limited to those described above. The predetermined driving state may include a driving state in which steering is performed while the vehicle is going straight, and the feature amount related to the driving characteristics of the driver may include the time integral value of the difference between the steering angle estimated from the behavior of the vehicle 2 and the actual steering angle.

[0099] Hereinafter, with reference to FIG. 8, an example of the processing executed by the brake ECU 20 of the vehicle 2 in this modification will be described. FIG. 8 is a flowchart showing an example of the processing executed by the brake ECU 20 in the modification. The series of processes shown in this flowchart are repeatedly executed by the brake ECU 20 at a predetermined control cycle.

[0100] In S200, the brake ECU 20 acquires data corresponding to the input information. Since the processing in S200 has the same content as the processing in S100 described above, a detailed description thereof will not be repeated. The subsequent processing proceeds to S202.

[0101] At S202, the brake ECU 20 determines whether a predetermined condition is satisfied. The predetermined condition includes a condition for determining whether the driving state is such that steering is performed until the final steering angle is reached while the vehicle is going straight. The predetermined condition includes, for example, the condition that the vehicle 2 is in motion and the condition that the steering state is such that the operation of the steering wheel is started and ended while the vehicle 2 is going straight. The brake ECU 20 determines whether the vehicle 2 is in motion by using the rotational speed of the front wheels 50 as described above. Further, the brake ECU 20 determines that it is in a steering state when the steering angle is not zero and the magnitude of the change amount of the steering angle is greater than a threshold value. If it is determined that the predetermined condition is satisfied (YES at S202), the process proceeds to S204.

[0102] At S204, the brake ECU 20 calculates an estimated steering angle. The brake ECU 20 calculates, for example, the steering angle estimated from the behavior of the vehicle 2 as the estimated steering angle. More specifically, the brake ECU 20 calculates the estimated steering angle by using the rotational angular velocity in the yaw direction of the vehicle 2, the acceleration in the left - right direction of the vehicle 2, and the vehicle speed. The brake ECU 20 acquires the rotational angular velocity in the yaw direction from the yaw rate sensor 66. Further, the brake ECU 20 acquires the acceleration in the left - right direction of the vehicle 2 from the G - sensor 68. Regarding the method for calculating the estimated steering angle using the rotational angular velocity in the yaw direction, the acceleration in the left - right direction of the vehicle 2, and the vehicle speed, a known technique may be used and its detailed description will not be given. Then the process proceeds to S206.

[0103] At S206, the brake ECU 20 calculates the time - integrated value of the difference between the estimated steering angle and the actual steering angle. FIG. 9 is a diagram for explaining the method of calculating the time - integrated value of the difference between the estimated steering angle and the actual steering angle. The vertical axis of FIG. 9 indicates the steering angle. The horizontal axis of FIG. 9 indicates time. LN1 in FIG. 9 indicates the change in the actual steering angle. LN2 in FIG. 9 indicates the change in the steering angle estimated from the behavior of the vehicle 2.

[0104] As shown in LN2 of FIG. 9, the steering angle estimated from the behavior of the vehicle 2 starts to change from the steering angle (zero) corresponding to the straight-ahead state at time t(0) and changes without fluctuating until it reaches the final steering angle S(0) at time t(2).

[0105] On the other hand, since there is play and backlash in the steering wheel mechanism and there are variations in the driver's operation, as shown in LN1 of FIG. 9, the actual steering angle of the vehicle 2 increases earlier than time t(0) and fluctuates such as becoming larger than the final steering angle S(0).

[0106] Therefore, the time integral value of the difference between the estimated steering angle and the actual steering angle corresponds to the area of the figure surrounded by LN1 and LN2 in FIG. 9. That is, for example, when the brake ECU 20 calculates the time integral value of the difference between the estimated steering angle and the actual steering angle at time t(1), the area surrounded by LN1 in FIG. 9, LN2 in FIG. 9, and a point indicating time t(1) is calculated. The brake ECU 20 finally calculates the area of the figure surrounded by LN1 and LN2 in FIG. 9 until the steering state is canceled as the time integral value of the difference. The subsequent process proceeds to S208.

[0107] At S208, the brake ECU 20 updates the frequency distribution. For example, the brake ECU 20 determines which range among a plurality of ranges divided in the order of the magnitude of the value the time integral value of the difference calculated from the start of the steering state to the cancellation of the steering state corresponds to, and increases the frequency (number of times) corresponding to the determined range by a predetermined value (for example, 1). In this frequency distribution, the smaller the time integral value of the difference, the larger the frequency, indicating that the difference between the actual steering angle and the estimated steering angle is small, that is, the driver is less likely to perform wasteful steering operations. Also, the larger the frequency of the range with a large time integral value of the difference, the larger the difference between the actual steering angle and the estimated steering angle, indicating that the driver is more likely to perform wasteful steering operations. The subsequent process proceeds to S210.

[0108] In S210, the brake ECU 20 transmits the updated frequency distribution to the data center 100. The brake ECU 20 transmits information about the updated frequency distribution to the data center 100 via the central ECU 40 and the DCM 30. Then this process ends. Note that if it is determined that a predetermined condition is not satisfied (NO in S202), this process ends.

[0109] The above processes of S200, S202, S204, S206, and S208 are included in the processes executed by the second processing unit 24. Also, the above process of S210 is included in the processes executed by the third processing unit 26.

[0110] The data center 100 can evaluate the driving characteristics of the driver of the vehicle 2 using the information received from the DCM 30 of the vehicle 2. That is, the data center 100 can evaluate whether the driving of the vehicle 2 (especially the operation of the steering wheel) is by a driver accustomed to driving or by a driver not accustomed to driving using the received frequency distribution.

[0111] The information transmitted from the DCM 30 to the data center 100 includes, for example, information about the processing time, the position information of the vehicle 2, and the time integral value of the difference between the estimated steering angle and the actual steering angle.

[0112] The data center 100 may evaluate the driving characteristics of the driver of the vehicle 2, for example, by comparing the frequency distribution of the time integral value of the difference between the estimated steering angle and the actual steering angle during the driving of a skilled driver. The data center 100, for example, when the magnitude of the difference between the first average value of the time integral value of the difference between the estimated steering angle and the actual steering angle during the driving of a skilled driver and the second average value of the time integral value of the difference between the estimated steering angle and the actual steering angle during the driving of the driver of the vehicle 2 is equal to or less than a threshold value, may evaluate that the driver of the vehicle 2 is a driver who is accustomed to driving. Alternatively, the data center 100, for example, when the magnitude of the difference between the first average value and the second average value is greater than the threshold value, may evaluate that the driver of the vehicle 2 is a driver who is not accustomed to driving.

[0113] The operation of the brake ECU 20 in this modification example based on the above structure and flowchart will be described.

[0114] For example, when input information is acquired during the running of the vehicle 2 (S200), it is determined whether a predetermined condition is satisfied (S202). When it is determined that the predetermined condition is satisfied while the vehicle 2 is running and in a steering state (YES in S202). Therefore, the estimated steering angle is calculated (S204), and the time integral value of the difference between the calculated estimated steering angle and the actual steering angle is calculated (S206). The frequency distribution is updated using the calculated time integral value of the difference (S208). The updated frequency distribution is transmitted to the data center 100 (S210).

[0115] The data center 100 can evaluate the characteristics of the driving by the driver of the vehicle 2 based on the received frequency distribution. Since the evaluation method based on the frequency distribution is as described above, a detailed description thereof will not be repeated.

[0116] As described above, according to the information processing apparatus according to this modification example, it is possible to determine whether or not the vehicle is in a steering state during traveling without using a complicated apparatus, and by calculating the time integral value of the difference between the estimated steering angle and the actual steering angle in the steering state during traveling as a feature amount, it is possible to efficiently evaluate whether the driver of the vehicle 2 is a driver accustomed to driving or a driver not accustomed to driving.

[0117] In the above-described modification example, the brake ECU 20 has been described as transmitting the frequency distribution to the data center 100 every time it is updated. However, for example, the frequency distribution updated immediately before the timing of the end of the trip (when the IG is turned off) may be transmitted to the data center 100.

[0118] Also, in the above-described modification example, the case where the brake ECU 20 calculates the feature amount and updates the frequency distribution while the vehicle is in the steering state during traveling has been described as an example. However, the brake ECU 20 may update the frequency distribution using, for example, the time integration value of the difference between the estimated steering angle and the actual steering angle during the period when the vehicle was in the steering state when it changed from the steering state to a non-steering state during traveling.

[0119] Furthermore, in the above-described embodiment, as an example of a predetermined driving state, the history of the vehicle speed in the steady running state is calculated as a feature amount, and the evaluation of the driving characteristics of the driver is performed by calculating the frequency distribution using the calculated feature amount. However, the predetermined driving state and feature amount are not limited to those described above. The predetermined driving state includes a driving state in which a braking operation is performed during the traveling of the vehicle, and the feature amount related to the driving characteristics of the driver may include the difference between the peak value of the brake hydraulic pressure immediately after the start of braking and the average value of the brake hydraulic pressure in a predetermined period after the peak.

[0120] Next, with reference to FIG. 10, another example of the processing executed by the brake ECU 20 of the vehicle 2 in this modification will be described. FIG. 10 is a flowchart showing another example of the processing executed by the brake ECU 20 in the modification. A series of processes shown in this flowchart are repeatedly executed by the brake ECU 20 at predetermined control cycles.

[0121] At S300, the brake ECU 20 acquires data corresponding to the input information. Since the process of S300 has the same processing content as the process of S100 described above, its detailed description will not be repeated. The subsequent process proceeds to S302.

[0122] At S302, the brake ECU 20 determines whether or not a predetermined condition is satisfied. The predetermined condition includes a condition for determining whether or not a braking operation has been performed during the running of the vehicle 2. For example, the brake ECU 20 determines that the predetermined condition is satisfied when there is a history of brake hydraulic pressure indicating that braking has started and a history of brake hydraulic pressure indicating that braking has ended during the running of the vehicle 2. For example, when the rotational speed of the front wheel 50 is equal to or higher than a threshold value, the brake hydraulic pressure increases from a threshold value (the upper limit value of the range of brake hydraulic pressure at which the braking force of the vehicle 2 does not act), and the brake hydraulic pressure is zero during a predetermined period before the time when the brake hydraulic pressure increases, the brake ECU 20 determines that there is a history of brake hydraulic pressure indicating that braking has started during the running of the vehicle 2. The brake ECU 20 then determines that there is a history of brake hydraulic pressure indicating that braking has ended when the brake hydraulic pressure becomes equal to or lower than the threshold value. If it is determined that the predetermined condition is satisfied (YES at S302), the process proceeds to S304.

[0123] In S304, the brake ECU 20 calculates the peak value from the history of the brake hydraulic pressure during the period when the braking operation is performed. FIG. 11 is a diagram showing an example of changes in vehicle speed, brake hydraulic pressure, and acceleration during the braking operation. The upper part of FIG. 11 shows the change in vehicle speed, the middle part of FIG. 11 shows the change in brake hydraulic pressure, and the lower part of FIG. 11 shows the change in the acceleration of the vehicle 2. The vertical axis in the upper part of FIG. 11 indicates the vehicle speed, and the horizontal axis indicates time. The vertical axis in the middle part of FIG. 11 indicates the brake hydraulic pressure, and the horizontal axis indicates time. The vertical axis in the lower part of FIG. 11 indicates the acceleration, and the horizontal axis indicates time. LN3 in FIG. 11 shows the change history of the vehicle speed. LN4 in FIG. 11 shows the change history of the brake hydraulic pressure. LN5 in FIG. 11 shows the change history of the acceleration. FIG. 11 shows the changes in vehicle speed, brake hydraulic pressure, and acceleration by the following series of operations. That is, when the brake pedal is depressed during the running of the vehicle 2 and braking is started, the vehicle speed decreases, and the brake hydraulic pressure and the deceleration increase. Then, after the brake hydraulic pressure is kept constant by adjusting the depressing force of the driver's brake pedal, the vehicle 2 stops. When the vehicle 2 stops, the depression of the brake pedal is released.

[0124] The brake ECU 20 calculates, for example, the maximum value of the brake hydraulic pressure during the period when the braking operation is performed as the peak value. The brake ECU 20 calculates, for example, the brake hydraulic pressure at time t(3) in the history of the brake hydraulic pressure shown in LN4 of FIG. 11 as the peak value. The subsequent process proceeds to S306.

[0125] In S306, the brake ECU 20 calculates the average value of the brake hydraulic pressure during the pedal force adjustment. The brake ECU 20 calculates the average value of the brake hydraulic pressure during the period of pedal force adjustment (the period from time t(4) to time t(5) in FIG. 11) from the history of the brake hydraulic pressure during the period when the braking operation is performed. The brake ECU 20 calculates, for example, the average value of the brake hydraulic pressure during the period in which the magnitude of the change amount of the brake hydraulic pressure per unit time is equal to or less than the threshold value as the period of pedal force adjustment. The subsequent process proceeds to S308.

[0126] In S308, the brake ECU 20 updates the frequency distribution of the difference between the peak value and the average value of the brake hydraulic pressure. The brake ECU 20 determines which of a plurality of ranges (for example, four levels of extra-large, large, medium, and small) into which the difference magnitudes are classified in the order of the value magnitudes the difference magnitude corresponds to, and increases the frequency (number of times) corresponding to the determined range by a predetermined value (for example, 1). In this frequency distribution, for example, the larger the frequency of the range where the difference magnitude is small, the more likely it indicates that the braking operation was not performed (that is, not accustomed to the braking operation) so that a large braking force is generated at the initial stage of starting the braking operation. Also, in this frequency distribution, for example, the larger the frequency of the range where the difference magnitude is large, the more likely it indicates that the braking operation was performed (that is, accustomed to the braking operation) so that a large braking force is generated at the initial stage of starting the braking operation. The subsequent process proceeds to S310.

[0127] In S310, the brake ECU 20 transmits the updated frequency distribution to the data center 100. The brake ECU 20 transmits information about the updated frequency distribution to the data center 100 via the central ECU 40 and the DCM 30. Then this process ends. Note that when it is determined that a predetermined condition is not satisfied (NO in S302), this process ends.

[0128] The above processes of S300, S302, S304, S306, and S308 are included in the processes executed by the second processing unit 24. Also, the above process of S310 is included in the process executed by the third processing unit 26.

[0129] The data center 100 can evaluate the driving characteristics of the driver of the vehicle 2 using the information received from the DCM 30 of the vehicle 2. That is, the data center 100 can evaluate whether the driving of the vehicle 2 (especially the braking operation) is by a driver accustomed to driving or by a driver not accustomed to driving using the received frequency distribution.

[0130] The information transmitted from DCM30 to the data center 100 includes, for example, the processing time, the position information of vehicle 2, and information about the difference between the peak value and the average value.

[0131] The data center 100 may evaluate the driving characteristics of the driver of vehicle 2, for example, by comparing with the frequency distribution of the magnitude of the difference between the peak value and the average value by a skilled driver. The data center 100 may, for example, evaluate that the driver of vehicle 2 is a driver accustomed to driving when the magnitude of the difference between the first average value of the magnitude of the difference between the peak value and the average value by a skilled driver and the second average value of the magnitude of the difference between the peak value and the average value by the driver of vehicle 2 is less than or equal to the threshold value. Alternatively, the data center 100 may, for example, evaluate that the driver of vehicle 2 is a driver not accustomed to driving when the magnitude of the difference between the first average value and the second average value is greater than the threshold value.

[0132] The operation of the brake ECU 20 in this modification based on the above structure and flowchart will be described.

[0133] For example, when input information is acquired during the running of vehicle 2 (S300), it is determined whether a predetermined condition is satisfied (S302). When a braking operation is started during the running of vehicle 2 and it is determined that the predetermined condition is satisfied when the braking operation ends thereafter (YES in S302). Therefore, the peak value of the brake hydraulic pressure is calculated from the history of the brake hydraulic pressure during the period when the braking operation is performed (S304), and the average value of the brake hydraulic pressure during the pedal force adjustment is calculated (S306). The frequency distribution is updated using the magnitude of the difference between the calculated peak value and the average value (S308). The updated frequency distribution is transmitted to the data center 100 (S310).

[0134] The data center 100 can evaluate the characteristics of the driving by the driver of vehicle 2 based on the received frequency distribution. Since the evaluation method based on the frequency distribution is as described above, the detailed description thereof will not be repeated.

[0135] As described above, according to the information processing apparatus according to this modification example, it is possible to determine whether or not a braking operation has been performed during traveling without using a complicated apparatus, and by calculating, as a feature amount, the magnitude of the difference between the peak value of the brake hydraulic pressure during the period when braking is performed and the average value of the brake hydraulic pressure during the pedal force adjustment, it is possible to efficiently evaluate whether the driver of the vehicle 2 is a driver accustomed to driving or a driver not accustomed to driving.

[0136] In the above-described modification example, the brake ECU 20 has been described as transmitting the frequency distribution to the data center 100 every time it is updated. However, for example, the frequency distribution updated immediately before the timing of the end of a trip (when the IG is turned off) may be transmitted to the data center 100.

[0137] Note that all or part of the above-described modification examples may be implemented in appropriate combination. The embodiments disclosed this time should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is shown not by the above description but by the scope of the claims, and it is intended that all modifications within the meaning and scope equivalent to the scope of the claims are included.

Explanation of Reference Numerals

[0138] 1 Information processing system, 2, 3 Vehicles, 6 Communication network, 7 Base station, 11 Control device, 12 Storage device, 13 Communication device, 14 Communication bus, 20 Brake ECU, 22 First processing unit, 24 Second processing unit, 26 Third processing unit, 30 DCM, 40 Central ECU, 50 Front wheels, 52 Rear wheels, 54 Wheel speed sensor, 60 Steering angle sensor, 62 Brake hydraulic pressure sensor, 64 Accelerator opening sensor, 66 Yaw rate sensor, 68 G sensor, 100 Data center.

Claims

1. An information processing device that calculates a feature quantity related to the driving characteristics of a driver of a vehicle, comprising: an acquisition unit that acquires an operation amount of the vehicle; a first processing unit that specifies a predetermined driving state during traveling of the vehicle using the acquired operation amount; a second processing unit that calculates the feature quantity in the predetermined driving state, wherein the predetermined driving state includes a driving state in which steering is performed while the vehicle is going straight; the feature quantity includes a time integral value of a difference between a first steering amount estimated from the behavior of the vehicle and a second steering amount actually performed, the information processing device.

2. The information processing device according to claim 1, further comprising a third processing unit that calculates a frequency distribution of the time integral value.

3. An information processing device that calculates a feature quantity related to the driving characteristics of a driver of a vehicle, comprising: an acquisition unit that acquires an operation amount of the vehicle; a first processing unit that specifies a predetermined driving state during traveling of the vehicle using the acquired operation amount; a second processing unit that calculates the feature quantity in the predetermined driving state, wherein the predetermined driving state includes a driving state until the traveling vehicle is stopped; the feature quantity includes a difference between a peak value of brake hydraulic pressure and an average value of the brake hydraulic pressure after the peak, the information processing device.

4. The information processing device according to claim 3, further comprising a third processing unit that specifies to which of a plurality of sections divided in descending order of magnitude the difference corresponds.

5. A vehicle provided with an information processing device that calculates a feature quantity related to the driving characteristics of a driver, wherein the information processing device includes an acquisition unit that acquires an operation amount of the vehicle; a first processing unit that specifies a predetermined driving state during traveling of the vehicle using the acquired operation amount; a second processing unit that calculates the feature quantity in the predetermined driving state, wherein the predetermined driving state includes a driving state in which steering is performed while the vehicle is going straight; the feature quantity includes a time integral value of a difference between a first steering amount estimated from the behavior of the vehicle and a second steering amount actually performed, the vehicle.

6. A vehicle provided with an information processing device that calculates a feature quantity related to the driving characteristics of a driver, wherein the information processing device includes an acquisition unit that acquires an operation amount of the vehicle; a first processing unit that specifies a predetermined driving state during traveling of the vehicle using the acquired operation amount; including a second processing unit that calculates the feature amount in the predetermined operating state; the predetermined operating state includes an operating state until the vehicle in motion is stopped; the feature amount includes a difference between a peak value of the brake hydraulic pressure and an average value of the brake hydraulic pressure after the peak, for a vehicle. **Claim 7** An information processing apparatus that calculates a feature amount related to a driving characteristic of a driver of a vehicle, and a server that manages information transmitted from the information processing apparatus, wherein the information processing apparatus includes an acquisition unit that acquires an operation amount of the vehicle, a first processing unit that specifies a predetermined operating state during traveling of the vehicle using the acquired operation amount, and a second processing unit that calculates the feature amount in the predetermined operating state; the predetermined operating state includes an operating state in which steering is performed while the vehicle is going straight; the feature amount includes a time integral value of a difference between a first steering amount estimated from the behavior of the vehicle and a second steering amount actually performed, for an information processing system. **Claim 8** An information processing apparatus that calculates a feature amount related to a driving characteristic of a driver of a vehicle, and a server that manages information transmitted from the information processing apparatus, wherein the information processing apparatus includes an acquisition unit that acquires an operation amount of the vehicle, a first processing unit that specifies a predetermined operating state during traveling of the vehicle using the acquired operation amount, and a second processing unit that calculates the feature amount in the predetermined operating state; the predetermined operating state includes an operating state until the vehicle in motion is stopped; the feature amount includes a difference between a peak value of the brake hydraulic pressure and an average value of the brake hydraulic pressure after the peak, for an information processing system. **Claim 9** An information processing method for calculating a feature amount related to a driving characteristic of a driver of a vehicle, the method including steps in which a computer acquires an operation amount of the vehicle, specifies a predetermined operating state during traveling of the vehicle using the acquired operation amount, and calculates the feature amount in the predetermined operating state; the predetermined operating state includes an operating state in which steering is performed while the vehicle is going straight; the feature amount includes a time integral value of a difference between a first steering amount estimated from the behavior of the vehicle and a second steering amount actually performed, for an information processing method. **Claim 10** An information processing method for calculating a feature amount related to a driving characteristic of a driver of a vehicle, A step in which a computer acquires the operation amount of the vehicle; A step of specifying a predetermined driving state during the running of the vehicle using the acquired operation amount; Including a step in which the computer calculates the feature amount in the predetermined driving state; The predetermined driving state includes a driving state until the running vehicle is stopped; The feature amount includes the difference between the peak value of the brake hydraulic pressure and the average value of the brake hydraulic pressure after the peak, an information processing method.

11. To a computer, A step of acquiring the operation amount of the vehicle; A step of specifying a predetermined driving state during the running of the vehicle using the acquired operation amount; Executing a step of calculating a feature amount related to the driving characteristics of the driver of the vehicle in the predetermined driving state; The predetermined driving state includes a driving state in which steering is performed while the vehicle is going straight; The feature amount includes the time integral value of the difference between a first steering amount estimated from the behavior of the vehicle and a second steering amount actually performed, a program.

12. To a computer, A step of acquiring the operation amount of the vehicle; A step of specifying a predetermined driving state during the running of the vehicle using the acquired operation amount; Executing a step of calculating a feature amount related to the driving characteristics of the driver of the vehicle in the predetermined driving state; The predetermined driving state includes a driving state until the running vehicle is stopped; The feature amount includes the difference between the peak value of the brake hydraulic pressure and the average value of the brake hydraulic pressure after the peak, a program.

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