Information processing device, information processing system, information processing method, and program

Abstract

To provide an information processing device, information processing system, information processing method and program which can suitably analyze a driving behavior based on measurement data in a change in stepping of a pedal.SOLUTION: An information processing device 10 comprises: an acquisition unit 11 which acquires time-series measurement data about a movement state of a sole of a driver; a section specification unit 13 which specifies a section having a high frequency component whose frequency is equal to or greater than a prescribed value as a stepping change section from the measurement data; an analysis unit 14 which analyzes a driving behavior of a driver on the basis of at least features of the measurement data in the stepping change section; and an output unit 16 which outputs a result of analysis.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to an information processing device, an information processing system, an information processing method, and a program. [Background technology]

[0002] For transportation companies, the social and economic losses from accidents are huge, so managing the driving behavior of drivers is important. For example, transportation companies that own five or more commercial vehicles are required to appoint a safe driving manager. The safe driving manager assesses the driving skills of the drivers and provides safe driving guidance.

[0003] For example, Patent Document 1 discloses a method of generating instruction information based on detection data of an in-vehicle device and measuring the viewing time of the instruction information by the driver. The detection data includes the position, time, speed, etc. of the vehicle. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] JP 2020-102040 A Summary of the Invention [Problem to be solved by the invention]

[0005] However, the method described in the above-mentioned Patent Document 1 cannot take into consideration the characteristics of the driver when changing pedal positions in the driving behavior.

[0006] In view of the above-mentioned problems, an object of the present disclosure is to provide an information processing device, an information processing system, an information processing method, and a program that can suitably analyze driving behavior based on measurement data during pedal change-over. [Means for solving the problem]

[0007] An information processing device according to one aspect of the present disclosure includes an acquisition unit that acquires time-series measurement data regarding the movement state of the soles of the driver's feet, a section identification unit that identifies, from the measurement data, a section having high-frequency components whose frequency is equal to or higher than a predetermined value as a step-change section, an analysis unit that analyzes the driving behavior of the driver based at least on characteristics of the measurement data in the step-change section, and an output unit that outputs the results of the analysis.

[0008] According to an aspect of the present disclosure, an information processing system includes an inertial sensor that measures a movement state of a sole of a driver's foot, and an information processing device. The information processing device includes an acquisition unit that acquires time-series measurement data measured by the inertial sensor, a section identification unit that identifies a section having a high-frequency component equal to or higher than a predetermined frequency as a step-change section from the measurement data, an analysis unit that analyzes the driving behavior of the driver based at least on features of the measurement data in the step-change section, and an output unit that outputs a result of the analysis.

[0009] An information processing method according to one aspect of the present disclosure acquires time-series measurement data regarding the movement state of the soles of a driver's feet, identifies from the measurement data a section having high-frequency components above a predetermined frequency as a step-change section, analyzes the driving behavior of the driver based at least on characteristics of the measurement data in the step-change section, and outputs the results of the analysis.

[0010] A program according to one aspect of the present disclosure causes a computer to realize an acquisition function for acquiring time-series measurement data regarding the movement state of the soles of the driver's feet, an identification function for identifying, from the measurement data, a section having high-frequency components above a predetermined frequency as a step-change section, an analysis function for analyzing the driving behavior of the driver based at least on characteristics of the measurement data in the step-change section, and an output function for outputting the results of the analysis. Effect of the Invention

[0011] The present disclosure makes it possible to provide an information processing device, an information processing system, an information processing method, and a program that can appropriately analyze driving behavior based on measurement data when changing pedal positions. [Brief description of the drawings]

[0012] [Figure 1] 1 is a block diagram showing a configuration of an information processing device according to a first embodiment. [Diagram 2] FIG. 11 is a block diagram showing a schematic configuration of an information processing system according to a second embodiment. [Diagram 3] FIG. 11 is a diagram showing a usage state of the sensor according to the second embodiment. [Figure 4] FIG. 11 is a diagram showing an example of measurement data according to the second embodiment. [Diagram 5] 11A and 11B are diagrams for explaining the behavior of the sole of the foot when changing pedals. [Figure 6] FIG. 11 is a block diagram showing a configuration of a server according to the second embodiment. [Figure 7] FIG. 11 is a diagram for explaining an example of section identification and analysis by the server according to the second embodiment. [Figure 8] 11 is a flowchart showing the flow of an information processing method by a server according to a second embodiment. [Figure 9] FIG. 11 is a block diagram showing a configuration of an administrator terminal according to the second embodiment. [Figure 10] FIG. 11 is a diagram showing an example of an image displayed on an administrator terminal according to the second embodiment. [Figure 11] FIG. 11 is a block diagram showing a configuration of an information processing system according to a third embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0013] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In each drawing, the same or corresponding elements are denoted by the same reference numerals, and duplicated descriptions will be omitted as necessary for clarity of explanation.

[0014] <Embodiment 1> First, a first embodiment of the present disclosure will be described. Fig. 1 is a block diagram showing a configuration of an information processing device 10 according to the first embodiment. The information processing device 10 is a computer that analyzes the driving behavior of a driver. The information processing device 10 includes an acquisition unit 11, a section identification unit 13, an analysis unit 14, and an output unit 16.

[0015] The measurement data used as the basis of the analysis in the present embodiment 1 is time-series data obtained by measuring physical quantities representing the movement state of the sole of the driver's foot. The physical quantity representing the movement state of the sole of the foot is at least one of the displacement, speed, and acceleration of the sole of the foot. The measurement data shows the behavior of the sole of the foot not only when the driver places the sole of the foot on the pedal and presses it down, but also in the step-change section. The step-change section is the section from when the sole of the foot leaves the pedal after pressing it down, after the sole of the foot leaves the pedal, and until the sole of the foot presses down again. The step-change section is divided into a section where the driver switches from the accelerator pedal to the brake pedal and a section where the driver switches from the brake pedal to the accelerator pedal.

[0016] By analyzing the behavior of the soles of the feet in the changeover section, it is possible to obtain driving behavior in the changeover section that cannot be obtained from vehicle information such as mileage and speed recorded by digital tachographs, etc.

[0017] First, the acquisition unit 11 acquires measurement data.

[0018] Next, the section identification unit 13 identifies a step-changing section from the measurement data acquired by the acquisition unit 11. Specifically, the section identification unit 13 identifies a section having high-frequency components as a step-changing section. The high-frequency components refer to data of the measurement data whose waveform frequency is equal to or higher than a predetermined value.

[0019] Next, the analysis unit 14 analyzes the driving behavior of the driver based on at least the characteristics of the measurement data of the step-change section. For example, the analysis unit 14 analyzes the number of occurrences of the step-change section, the time interval between the step-change sections, or the amplitude or frequency of the step-change section as the characteristics of the measurement data of the step-change section, and analyzes the driving behavior of the driver based on at least one of these. The driving behavior is, for example, sudden acceleration, sudden braking, unstable driving, roughness, etc.

[0020] Next, the output unit 16 outputs the analysis results.

[0021] As described above, according to the first embodiment, the information processing device 10 can appropriately analyze the driving behavior of the driver based on the behavior of the sole of the foot in the pedal change section. This allows the safety driving manager to accurately grasp the driving operation of the driver and provide appropriate driving guidance.

[0022] <Embodiment 2> Next, a description will be given of embodiment 2 of the present disclosure. Fig. 2 is a block diagram showing a schematic configuration of an information processing system 1 according to embodiment 2. The information processing system 1 is a system including one or more computers for supporting driving instruction by a safe driving manager.

[0023] The information processing system 1 includes a sensor 20, a communication control device 30, a server 40, and an administrator terminal 50. The communication control device 30, the server 40, and the administrator terminal 50 are connected to a network N.

[0024] The network N is a communication network such as the Internet.

[0025] The sensor 20 is an inertial sensor that measures the displacement of the sole of the driver's foot. As an example, the sensor 20 is an acceleration sensor, particularly a three-axis acceleration sensor. The sensor 20 may include a gyro sensor in addition to the acceleration sensor. The sensor 20 transmits measurement data to the communication control device 30. The communication between the sensor 20 and the communication control device 30 may be wired communication or wireless communication. For example, the sensor 20 supplies the measurement data to the communication control device 30 using short-range wireless communication such as Bluetooth (registered trademark).

[0026] The communication control device 30 is an in-vehicle communication device. For example, the communication control device 30 is an in-vehicle navigation device, a dedicated communication device, or a smartphone or tablet terminal used by the driver. The communication control device 30 relays data transmission from the sensor 20 to the server 40. Specifically, the communication control device 30 receives measurement data from the sensor 20 and transmits the measurement data to the server 40 via the network N.

[0027] The server 40 is an example of the information processing device 10 of the first embodiment. The server 40 receives the measurement data of the sensor 20 from the communication control device 30 via the network N. Next, the server 40 analyzes the driving behavior of the driver based on the measurement data. Then, the server 40 transmits the analysis result to the manager terminal 50.

[0028] The manager terminal 50 is an information terminal used by the safety driving manager. The manager terminal 50 receives the analysis results of the driver's driving behavior from the server 40 via the network N, and outputs the analysis results. As an example of the output, the manager terminal 50 displays the analysis results on a display unit (not shown). By viewing the output analysis results, the safety driving manager can understand the driving operation of the driver and use them for driving guidance.

[0029] 3 is a diagram showing a usage state of the sensor 20 according to the second embodiment. The sensor 20 is mounted on a part that is linked to the movement of the sole SL of the driver. For example, the sensor 20 is mounted on an insole 310 of the driver's shoe 300. As an example, the sensor 20 is mounted on a part of the insole 310 that comes into contact with the heel of the driver. The sensor 20 may be mounted on a midsole or outsole of the shoe 300, or may be attached to the driver's sock or the sole SL itself.

[0030] Here, the X-axis direction of the sensor 20 is the width direction of the sole SL. The Y-axis direction of the sensor 20 is the length direction of the sole SL. The Z-axis direction of the sensor 20 is perpendicular to the X-axis and Y-axis, that is, the normal direction of the surface of the sole SL. The sensor 20 detects acceleration in each axial direction and measures displacement in each axial direction based on the acceleration. Of the measurement data, the displacement in the X-axis direction is referred to as X-axis data, the displacement in the Y-axis direction is referred to as Y-axis data, and the displacement in the Z-axis direction is referred to as Z-axis data.

[0031] Fig. 4 is a diagram showing an example of measurement data according to embodiment 2. The vertical axis of Fig. 4 is sensor output, and the horizontal axis is time. In Fig. 4, a solid line represents X-axis data, a diagonal line represents Y-axis data, and a dashed line represents Z-axis data.

[0032] Here, from the value of the X-axis data, it can be ascertained whether the sole of the driver's foot SL is located on the brake pedal in the positive direction of the X-axis, or on the accelerator pedal in the negative direction of the X-axis. For example, in section 1, the X-axis data indicates a positive value, so the driver is depressing the brake pedal. Also, in section 3, the X-axis data indicates a negative value, so the driver is depressing the accelerator pedal. Therefore, section 2 between sections 1 and 3 is a change-over section where the driver changes his / her foot from the brake pedal to the accelerator pedal. Similarly, section 4 is a change-over section where the driver changes his / her foot from the accelerator pedal to the brake pedal.

[0033] Fig. 5 is a diagram for explaining the behavior of the sole SL when changing pedals. As shown in Fig. 5(a), the driver releases the sole SL from the pedal before changing pedals. At this time, the sole SL moves in the negative direction of the Y axis and then in the positive direction of the Z axis. Also, as shown in Fig. 5(b), the driver places the sole SL on the pedal while moving the sole SL in the X axis direction or after moving the sole SL. At this time, the sole SL moves in the positive direction of the Y axis and then in the negative direction of the Z axis.

[0034] Therefore, as shown in Figure 4, in the step-change section, the Y-axis data and Z-axis data values ​​fluctuate significantly between positive and negative. If the driver's step-change is rough, the Y-axis data and Z-axis data values ​​will be larger and will change in a shorter period of time. By utilizing this phenomenon, it is possible to detect step-change sections from the measurement data, and ultimately to analyze the driver's driving behavior.

[0035] 6 is a block diagram showing the configuration of the server 40 according to the embodiment 2. The server 40 includes a communication unit 41, a control unit 42, an output unit 46, and a storage unit 47.

[0036] The communication unit 41 is a communication interface for connecting to the network N, and is an example of the acquisition unit 11 of the first embodiment. The communication unit 41 receives measurement data of the sensor 20 from the communication control device 30 via the network N. The measurement data includes X-axis data, Y-axis data, and Z-axis data. The communication unit 41 supplies the acquired measurement data to a section identification unit 43 of the control unit 42.

[0037] The communication unit 41 is an example of the output unit 16 of the first embodiment. The communication unit 41 receives the analysis result from the output control unit 45, and transmits it to the manager terminal 50 via the network N.

[0038] The control unit 42 controls the hardware of the server 40. The control unit 42 includes a section determination unit 43, an analysis unit 44, and an output control unit 45.

[0039] The section identification unit 43 is an example of the section identification unit 13 of the embodiment 1. The section identification unit 43 identifies a step-changing section from at least one of the Y-axis data and the Z-axis data among the measurement data acquired by the communication unit 41.

[0040] The analysis unit 44 is an example of the analysis unit 14 of the embodiment 1. The analysis unit 44 analyzes the driving behavior of the driver based on at least one of the features of the Y-axis data and the Z-axis data of the pedal change section.

[0041] The output control unit 45 converts the analysis results into a predetermined output format and outputs them via the communication unit 41 or the output unit 46.

[0042] The output unit 46 is an example of the output unit 16 in the embodiment 1. The output unit 46 receives the analysis result from the output control unit 45 and outputs it to the outside.

[0043] The storage unit 47 is a storage device that stores information necessary for processing by the control unit .

[0044] Fig. 7 is a diagram for explaining an example of section identification and analysis by the server 40 according to the embodiment 2. Fig. 7 shows an example of Y-axis data for the analysis target period from time T0 to T1.

[0045] In FIG. 7, the section identification unit 43 identifies a section having high-frequency components from the Y-axis data acquired by the communication unit 41, and determines this section as a step-changing section.

[0046] For example, the section identification unit 43 performs frequency analysis on the waveform of the Y-axis data using a Fourier transform or the like. The section identification unit 43 then identifies a section having a high-frequency component whose amplitude is equal to or greater than a predetermined value and whose frequency is equal to or greater than a predetermined value f0. Note that the section identification unit 43 also performs frequency analysis on the frequency f n After removing noise above (≫f0) using a low-pass filter or similar, a section having a frequency above f0 may be identified from the remaining waveform.

[0047] Alternatively, for example, the section identification unit 43 detects peaks whose maximum values ​​are equal to or greater than a predetermined value from the waveform of the Y-axis data, and identifies, among the detected peaks, a section in which a peak whose peak width or half-width is equal to or less than a predetermined width exists as a section having high-frequency components. Here, too, the section identification unit 43 may perform noise removal on the waveform of the Y-axis data before detecting the peaks.

[0048] In FIG. 7, the section identification unit 43 detects sections 2, 4, and 6 as step-change sections.

[0049] The analysis unit 44 then analyzes the driving behavior of the driver based on at least the characteristics of the Y-axis data of the pedal change section.

[0050] For example, the analysis unit 44 calculates the number of occurrences of pedal change sections included in the analysis target period. In Fig. 7, there are three pedal change sections included in the period from time T0 to T1. If the number of occurrences is a predetermined number or more, the analysis unit 44 determines that the driving behavior is abnormal. Note that the analysis unit 44 may determine that the more the number of occurrences, the rougher the driver's driving operation.

[0051] Furthermore, for example, the analysis unit 44 calculates the time intervals between adjacent step-change sections included in the analysis target period. In Fig. 7, the analysis unit 44 calculates the period between section 2 and section 4, i.e., the duration of section 3, and the period between section 4 and section 6, i.e., the duration of section 5.

[0052] The analysis unit 44 then determines whether the driving behavior is abnormal based on the average of the calculated time intervals or the variance of the time intervals. Specifically, the analysis unit 44 may determine that the driver's driving operation is inappropriate if the average of the calculated time intervals is equal to or less than a predetermined threshold. Furthermore, the analysis unit 44 may determine that the driver's driving operation tends to be rough, that the driver is engaging in abnormal driving such as tailgating, or that the driver is engaging in unstable driving such as drunk driving or drowsy driving if the variance of the calculated time intervals is equal to or greater than a predetermined threshold.

[0053] Also, for example, the analysis unit 44 calculates the amplitude in each step-changing section of the Y-axis data. The amplitude calculated here may be the maximum value minus the minimum value of the amplitude of the waveform included in one step-changing section. In the case where frequency analysis has been performed, it may be the maximum value or average value of the amplitude of the high-frequency component extracted by frequency analysis for one step-changing section. In the case where peaks have been detected, it may be the maximum value or average value of the peak height detected for one step-changing section.

[0054] The analysis unit 44 then determines whether the driving behavior is abnormal based on the amplitude calculated for each step-change section. Specifically, the analysis unit 44 may determine that the driver's driving operation is rough when the average of the amplitudes calculated for multiple step-change sections is equal to or greater than a predetermined threshold. The analysis unit 44 may also determine that the driver is driving unstably when the variation in the amplitudes calculated for multiple step-change sections is equal to or greater than a predetermined threshold.

[0055] Furthermore, for example, the analysis unit 44 calculates the frequency of the Y-axis data included in the measurement data in each step-changing section. When a frequency analysis is performed, the frequency calculated here may be the maximum or average frequency of the high-frequency components extracted by the frequency analysis for one step-changing section. When a peak is detected, the frequency calculated here may be the reciprocal of the maximum or average of the peak width or half-width detected for one step-changing section.

[0056] The analysis unit 44 then determines whether the driving behavior is abnormal based on the frequency. Specifically, the analysis unit 44 may determine that the driver's driving operation is rough when the average of the frequencies calculated in multiple pedal change sections is equal to or greater than a predetermined threshold. The analysis unit 44 may also determine that the driver is driving unstably when the variation in the frequencies calculated in multiple pedal change sections is equal to or greater than a predetermined threshold.

[0057] In this way, by performing various analyses on the step-change sections, the driving behavior can be analyzed in detail. The analysis unit 44 may perform a comprehensive analysis of the driving behavior by combining the above-mentioned analysis items such as the number of occurrences of the step-change sections, the time interval, and the amplitude.

[0058] Although an example of analysis using Y-axis data has been described in Fig. 7, analysis using Z-axis data may also be performed. The analysis method using Z-axis data is similar to the analysis method using Y-axis data, and therefore a description thereof will be omitted. Furthermore, the analysis unit 44 may perform a comprehensive analysis by combining the analysis using Y-axis data and the analysis using Z-axis data.

[0059] In addition, the type of step-change indicating whether the step-change is from the accelerator pedal to the brake pedal or from the brake pedal to the accelerator pedal may be used for the analysis. In this case, the section identification unit 43 first identifies the type of each step-change section, whether it is a step-change from the accelerator pedal to the brake pedal or from the brake pedal to the accelerator pedal, based on the value of the X-axis data before and after each step-change section. Then, the analysis unit 44 analyzes the driving behavior of the driver based on the type of step-change corresponding to each step-change section. This allows the driving habits of the driver to be understood in more detail.

[0060] In addition, vehicle information of the vehicle driven by the driver may be used for the analysis. The vehicle information is data obtainable from a digital tachograph or various sensing data obtainable via a CAN (Controller Area Network), and includes at least one of the following: mileage, driving speed, driving time, information on sudden acceleration or sudden deceleration, information on door opening and closing, and idling information. In this case, the communication control device 30 may obtain vehicle information from the digital tachograph or other in-vehicle sensors and transmit the vehicle information to the server 40.

[0061] The analysis unit 44 of the server 40 may analyze the driving behavior of the driver based on various characteristics of the step-change section in the measurement data and the vehicle information of the vehicle driven by the driver. By comparing the characteristics obtained from the vehicle information with the characteristics of the step-change section in the measurement data, the driving behavior can be analyzed from multiple perspectives. Such a multiple perspective analysis can also be applied to the analysis of the situation at the time of the occurrence of a traffic accident.

[0062] 8 is a flowchart showing the flow of an information processing method by the server 40 according to the second embodiment. First, the communication unit 41 of the server 40 acquires measurement data from the sensor 20 (S20). Next, the section identification unit 43 of the control unit 42 detects high-frequency components by performing frequency analysis and peak analysis (S21). Next, the section identification unit 43 identifies a section having the detected high-frequency components as a step-change section (S22).

[0063] Next, the analysis unit 44 analyzes the characteristics of the step-change section (for example, the number of occurrences, time intervals, amplitude, or frequency of the step-change section) (S23). Then, the analysis unit 44 determines whether the driving behavior is abnormal based on the characteristics of the step-change section (S24).

[0064] Finally, the output control unit 45 transmits the analysis result including the determination result to the manager terminal 50 via the communication unit 41 (S25).

[0065] 9 is a block diagram showing the configuration of the manager terminal 50 according to the embodiment 2. The manager terminal 50 includes a communication unit 51, a control unit 52, a display unit 56, and a storage unit 57.

[0066] The communication unit 51 is a communication interface for connecting to the network N. The control unit 52 controls hardware included in the administrator terminal 50. The display unit 56 is a display device such as a liquid crystal display or an organic EL display. The display unit 56 displays the analysis results received by the communication unit 51 from the server 40 via the network N. The memory unit 57 is a storage device that stores information necessary for processing by the control unit 52.

[0067] 10 is a diagram showing an example of an image 500 displayed on the administrator terminal 50 according to the second embodiment. The image 500 shows the driving behavior status of each driver as an analysis result. For example, the image 500 shows that the driver A suddenly accelerated three times in one hour and drove abnormally. On the other hand, the image 500 shows that the drivers B and C did not show any abnormal driving behavior in one hour and drove safely.

[0068] The safe driving manager can grasp the driving skills of each driver based on the image 500. This makes it easy to make individual driving instruction plans for each driver.

[0069] In this way, according to the second embodiment, the server 40 can analyze the stability of the sole of the foot movement in the pedal change section, thereby analyzing the driving situation at that time and the driving tendency of the driver in detail. This allows for more suitable support for driving instruction.

[0070] <Embodiment 3> Next, a third embodiment of the present disclosure will be described. In the third embodiment, an administrator terminal instead of a server analyzes the driving behavior of a driver. Fig. 11 is a block diagram showing a configuration of an information processing system 1a according to the third embodiment. The information processing system 1a includes an external storage device 25 and an administrator terminal 50a.

[0071] The external storage device 25 is a storage device that stores measurement data of the sensor 20. The external storage device 25 is, for example, an SD card or a flash memory such as a USB memory.

[0072] The administrator terminal 50a is an example of the information processing device 10 of the first embodiment. The administrator terminal 50a is similar to the administrator terminal 50 in that it includes a communication unit 51, a display unit 56, and a storage unit 57. However, the administrator terminal 50a differs from the administrator terminal 50 in that it includes an input unit 58 and a control unit 52a instead of the control unit 52. Note that the communication unit 51 is not essential to the administrator terminal 50a.

[0073] The input unit 58 reads out the measurement data from the external storage device 25, and supplies the measurement data to the section specification unit 53 of the control unit 52a.

[0074] The control unit 52a controls the hardware of the manager terminal 50a. The control unit 52a includes a section determination unit 53, an analysis unit 54, and an output control unit 55.

[0075] The section determination unit 53, the analysis unit 54, and the output control unit 55 have the same functions as the section determination unit 43, the analysis unit 44, and the output control unit 45 of the server 40. The output control unit 55 displays the analysis results by the analysis unit 54 on the display unit 56.

[0076] Even when the analysis is performed offline in this manner, the same effects as those of the second embodiment can be achieved.

[0077] Although the above-described embodiment has been described as a hardware configuration, the present disclosure is not limited to this. Any process of the present disclosure can be realized by causing a processor to execute a computer program.

[0078] In the above examples, the program includes instructions (or software code) that, when loaded into a computer, cause the computer to perform one or more functions described in the embodiments. The program may be stored in a non-transitory computer-readable medium or a tangible storage medium. By way of example and not limitation, the computer-readable medium or tangible storage medium includes random-access memory (RAM), read-only memory (ROM), flash memory, solid-state drive (SSD) or other memory technology, CD-ROM, digital versatile disc (DVD), Blu-ray® disk or other optical disk storage, magnetic cassette, magnetic tape, magnetic disk storage or other magnetic storage device. The program may be transmitted on a transitory computer-readable medium or communication medium. By way of example and not limitation, the transitory computer-readable medium or communication medium includes electrical, optical, acoustic, or other forms of propagated signals.

[0079] In addition, the present disclosure is not limited to the above embodiment, and can be appropriately modified without departing from the spirit of the present disclosure. For example, although the sensor 20 measures the displacement of the sole of the foot, the measurement target may be the speed or acceleration.

[0080] A part or all of the above-described embodiments can be described as, but is not limited to, the following supplementary notes. (Appendix 1) An acquisition unit that acquires time-series measurement data relating to the movement state of the soles of the driver; a section identification unit that identifies a section having a high-frequency component having a frequency equal to or higher than a predetermined value as a step-changing section from the measurement data; an analysis unit that analyzes a driving behavior of the driver based at least on features of the measurement data in the pedal change section; an output unit for outputting the results of the analysis; An information processing device comprising: (Appendix 2) The analysis unit includes: Calculating the number of occurrences of the step-change section included in a predetermined period of time; If the number of occurrences is equal to or greater than a predetermined number, it is determined that the driving behavior is abnormal. 2. An information processing device according to claim 1. (Appendix 3) The analysis unit includes: Calculating time intervals between adjacent change sections included in a predetermined period, Determining whether the driving behavior is abnormal based on the average of the time intervals or the variance of the time intervals 3. The information processing device according to claim 1 or 2. (Appendix 4) The measurement data includes X-axis data relating to a movement state of the sole in a width direction, Y-axis data relating to a movement state of the sole in a length direction, and Z-axis data relating to a state in a normal direction of the sole, The section identification unit identifies the step-change section from at least one of the Y-axis data and the Z-axis data. 4. The information processing device according to claim 1 . (Appendix 5) The analysis unit includes: Calculating the amplitude of at least one of the Y-axis data and the Z-axis data included in the measurement data in each changeover section; Based on the amplitude in each pedal change section, it is determined whether the driving behavior is abnormal. 5. The information processing device according to claim 4. (Appendix 6) The analysis unit includes: Calculating a frequency of at least one of Y-axis data and Z-axis data included in the measurement data in the step-change section; Based on the frequency, it is determined whether the driving behavior is abnormal. 6. The information processing device according to claim 4 or 5. (Appendix 7) the section identification unit identifies a type of each step-change section, whether it is a step-change from the accelerator pedal to the brake pedal or a step-change from the brake pedal to the accelerator pedal, based on values ​​of the X-axis data before and after each step-change section; The analysis unit analyzes the driving behavior of the driver further based on a type of pedal change corresponding to each pedal change section. 7. The information processing device according to claim 4, (Appendix 8) The analysis unit analyzes a driving behavior of the driver based on characteristics of the measurement data in the pedal change section and vehicle information of the vehicle driven by the driver. 8. An information processing device according to any one of claims 1 to 7. (Appendix 9) an inertial sensor that measures the movement state of the soles of the driver's feet; Information processing device Equipped with The information processing device includes: an acquisition unit that acquires time-series measurement data measured by the inertial sensor; a section identification unit that identifies a section having a high-frequency component equal to or higher than a predetermined frequency as a step-changing section from the measurement data; an analysis unit that analyzes a driving behavior of the driver based at least on features of the measurement data in the pedal change section; an output unit for outputting the results of the analysis; have Information processing system. (Appendix 10) The inertial sensor is mounted in the insole of the driver's shoe. 10. The information processing system according to claim 9. (Appendix 11) The information processing system further includes an administrator terminal, The output unit outputs a result of the analysis to a display unit of the administrator terminal. 11. The information processing system according to claim 9 or 10. (Appendix 12) Acquire time-series measurement data regarding the movement state of the soles of the driver's feet; Identifying a section having a high-frequency component equal to or higher than a predetermined frequency as a step-change section from the measurement data; Analyzing a driving behavior of the driver based at least on characteristics of the measurement data in the step-change section; Outputting the results of the analysis Information processing methods. (Appendix 13) An acquisition function for acquiring time-series measurement data regarding the movement state of the soles of the driver's feet; A function of identifying a section having a high-frequency component equal to or higher than a predetermined frequency as a step-change section from the measurement data; An analysis function that analyzes the driving behavior of the driver based at least on the characteristics of the measurement data in the pedal change section; an output function for outputting the results of the analysis; A program to make the above happen on a computer. [Explanation of symbols]

[0081] 1,1a Information Processing System 10. Information processing device 11 Acquisition Department 13 Section Identification Section 14 Analysis Department 16 Output section 20 Sensors 25 External storage device 30 Communication control device 40 Servers 41 Communications Department 42 Control section 43 Section Identification Section 44 Analysis Department 45 Output control section 46 Output section 47 Memory section 50 Administrator terminal 51 Communications Department 52, 52a Control section 53 Section Identification Section 54 Analysis Department 55 Output control section 56 Display section 57 Memory section 58 Input section 120 Pedal 140 Matt 300 Shoes 310 Insole 500 images N Network SL Sole

Claims

1. An acquisition unit that acquires time-series measurement data relating to the movement state of the soles of the driver; a section identification unit that identifies a section having a high-frequency component having a frequency equal to or higher than a predetermined value as a step-changing section from the measurement data; an analysis unit that analyzes a driving behavior of the driver based at least on features of the measurement data in the pedal change section; An output unit that outputs a result of the analysis, The analysis unit includes: Calculating the number of occurrences of the step-change section included in a predetermined period of time; If the number of occurrences is equal to or greater than a predetermined number, the driving behavior is determined to be abnormal. Information processing device.

2. An acquisition unit that acquires time-series measurement data relating to the movement state of the soles of the driver; a section identification unit that identifies a section having a high-frequency component having a frequency equal to or higher than a predetermined value as a step-changing section from the measurement data; an analysis unit that analyzes a driving behavior of the driver based at least on features of the measurement data in the pedal change section; An output unit that outputs a result of the analysis, The analysis unit includes: Calculating time intervals between adjacent change sections included in a predetermined period, Determining whether the driving behavior is abnormal based on the average of the time intervals or the variance of the time intervals Information processing device.

3. The measurement data is X-axis data relating to the movement state in the width direction of the sole; Y-axis data relating to the movement state in the length direction of the sole of the foot; Z-axis data relating to a state in a normal direction of the sole of the foot; The section identification unit identifies the step-changing section from at least one of the Y-axis data and the Z-axis data.

3. The information processing device according to claim 1 or 2.

4. The analysis unit includes: Calculating an amplitude of at least one of the Y-axis data and the Z-axis data included in the measurement data in each changeover section; Based on the amplitude in each pedal change section, it is determined whether the driving behavior is abnormal. The information processing device according to claim 3 .

5. The analysis unit analyzes a driving behavior of the driver based on characteristics of the measurement data in the pedal change section and vehicle information of the vehicle driven by the driver. The information processing device according to claim 1 .

6. an inertial sensor that measures the movement state of the soles of the driver's feet; The information processing device according to any one of claims 1 to 5, Information processing system.

7. The inertial sensor is mounted in the insole of the driver's shoe.

7. The information processing system according to claim 6.

8. An information processing device comprising: A step of acquiring time-series measurement data regarding a movement state of the soles of the driver's feet; identifying a section having a high-frequency component equal to or higher than a predetermined frequency from the measurement data as a step-changing section; Analyzing a driving behavior of the driver based at least on characteristics of the measurement data in the change section; and outputting a result of the analysis, The information processing device, In the analyzing step, Calculating the number of occurrences of the step-change section included in a predetermined period of time; If the number of occurrences is equal to or greater than a predetermined number, the driving behavior is determined to be abnormal. Information processing methods.

9. An information processing device comprising: A step of acquiring time-series measurement data regarding a movement state of the soles of the driver's feet; identifying a section having a high-frequency component equal to or higher than a predetermined frequency from the measurement data as a step-changing section; Analyzing a driving behavior of the driver based at least on characteristics of the measurement data in the change section; and outputting a result of the analysis, The information processing device, In the analyzing step, Calculating time intervals between adjacent change sections included in a predetermined period, Determining whether the driving behavior is abnormal based on the average of the time intervals or the variance of the time intervals Information processing methods.

10. A program that causes the information processing device to execute the information processing method described in claim 8 or 9.

Images