WO2015146045A1 - Dispositif de traitement de signal de capteur de véhicule et programme de traitement de signal de capteur de véhicule - Google Patents

Dispositif de traitement de signal de capteur de véhicule et programme de traitement de signal de capteur de véhicule Download PDF

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WO2015146045A1
WO2015146045A1 PCT/JP2015/001384 JP2015001384W WO2015146045A1 WO 2015146045 A1 WO2015146045 A1 WO 2015146045A1 JP 2015001384 W JP2015001384 W JP 2015001384W WO 2015146045 A1 WO2015146045 A1 WO 2015146045A1
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Prior art keywords
vehicle
acceleration
detection value
signal processing
sensor signal
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PCT/JP2015/001384
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English (en)
Japanese (ja)
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拡基 鵜飼
寧 難波
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株式会社デンソー
ローベルト ボツシュ ゲゼルシヤフト ミツト ベシュレンク
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Publication of WO2015146045A1 publication Critical patent/WO2015146045A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P21/00—Testing or calibrating of apparatus or devices covered by the preceding groups
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01P—MEASURING LINEAR OR ANGULAR SPEED, ACCELERATION, DECELERATION, OR SHOCK; INDICATING PRESENCE, ABSENCE, OR DIRECTION, OF MOVEMENT
    • G01P15/00—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration
    • G01P15/18—Measuring acceleration; Measuring deceleration; Measuring shock, i.e. sudden change of acceleration in two or more dimensions

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  • the present invention relates to a vehicle sensor signal processing device that detects a physical quantity that is used in a vehicle and generates the vehicle, and performs signal processing on a detected value, and a vehicle sensor signal processing program used in the device.
  • a drive recorder is known as a device that is used in a vehicle and detects a physical quantity generated in the vehicle.
  • the drive recorder detects acceleration or the like as a physical quantity generated in the vehicle.
  • Patent Document 1 discloses a technique for removing, from acceleration detected by a drive recorder, acceleration caused by a traveling road being a slope and gravity acceleration caused by the drive recorder being tilted from an installation posture. Specifically, in Patent Document 1, acceleration data is integrated twice to obtain an estimated position of the vehicle, and acceleration applied to the acceleration sensor by running on a hill is removed from the difference between the estimated position and the GPS positioning position. Yes.
  • the sensitivity to acceleration varies depending on the model. Even if the installation posture itself is different, the sensitivity to acceleration is different. Even if the acceleration applied to the acceleration sensor or the gravitational acceleration caused by tilting from the installation posture is removed from the detected value by the technique of Patent Document 1, the sensitivity difference due to the difference in the model or the sensitivity difference due to the installation posture is not detected. It has not been removed.
  • the difference in sensitivity due to the difference in model and the difference in sensitivity due to detection conditions such as the installation posture are not limited to the acceleration sensor, but also occur in sensors that detect other physical quantities as long as they are sensors used in vehicles.
  • temperature can be considered as a detection condition other than the installation posture.
  • the present invention has been made based on this situation, and the object of the present invention is for a vehicle that can reduce the influence of sensitivity differences due to differences in models and sensitivity differences due to detection conditions such as installation postures.
  • a sensor signal processing device and a vehicle sensor signal processing program are provided.
  • the invention according to the vehicle sensor signal processing device (1) for achieving the above object provides a vehicle sensor signal processing device used in a vehicle.
  • the vehicle sensor signal processing device includes a sensor (12) that outputs a detection value that changes according to a physical quantity generated in the vehicle, a detection value acquisition unit (21) that acquires a detection value output by the sensor, and a detection value acquisition. And a detection value correction unit (22) for normalizing the detection value acquired by the detection unit based on the detection value acquired by the detection value acquisition unit so far.
  • the sensor used in the vehicle outputs a detection value that changes according to the physical quantity generated in the vehicle.
  • This detection value is a value affected by a sensitivity difference due to a difference in sensor type and a sensitivity difference due to a difference in detection conditions such as the installation posture of the sensor.
  • the detection value correction unit normalizes the detection value based on the detection values acquired so far. By this normalization, it is possible to reduce the influence of the sensitivity difference due to the difference in model and the sensitivity difference due to the detection condition such as the installation posture.
  • the invention according to the vehicle sensor signal processing program for achieving the above object provides a vehicle sensor signal processing that causes a computer to function as the detection value acquisition unit and the detection value correction unit of the invention according to the vehicle sensor signal processing device. It is a program.
  • the apparatus including the computer and the sensor can be used as a vehicle sensor signal processing apparatus.
  • a tablet computer or a multi-function mobile phone can be used as a vehicle sensor signal processing device.
  • FIG. 2 is a block diagram showing a configuration of a smartphone 1.
  • FIG. It is a flowchart which shows a process when CPU of the control part 20 performs the drive recorder program 16a and the vehicle sensor signal processing program 16b. It is a figure which shows the state in which the smart phone 1 was installed so that the y-axis of the acceleration sensor 12 with which the smart phone 1 was built became a perpendicular direction. It is a figure which shows the state in which the smart phone 1 was inclined and installed. It is a figure which shows the state which the smart phone 1 inclined further from the attitude
  • FIG. 4 It is a flowchart which shows the acceleration real time correction process of FIG. 4 in detail. It is a figure which illustrates the acceleration detection value acquired by step S41 of FIG. 7, and the waveform of the acceleration alternating current component AAC obtained by the process of step S43. It is a figure which shows an example of the waveform obtained by the process of step S46. 10 is a graph for explaining an effect in Modification 1; 10 is a graph for explaining an effect in Modification 1; 10 is a graph for explaining an effect in Modification 1; 10 is a graph for explaining an effect in Modification 1; 10 is a graph for explaining an effect in Modification 1;
  • a smartphone 1 serving as an embodiment of the vehicle sensor signal processing device of the present invention is installed at, for example, the position shown in FIG. In FIG. 1, the smartphone 1 is installed in the vehicle interior. More specifically, the smartphone 1 is installed on the upper surface of the dashboard 100 and in the center in the vehicle width direction. Although not shown, the smartphone 1 is detachably installed on the dashboard 100 by a well-known in-vehicle holder for smartphones.
  • FIG. 2 shows the configuration of the smartphone 1. Note that the smartphone 1 is also called a multi-function mobile phone and has a telephone function, but FIG. 2 omits a configuration that is not necessary for describing the present embodiment.
  • the smartphone 1 includes a camera (CAM) 11, an acceleration sensor (G-SEN) 12, a position sensor (P-SEN) 13, a display unit (DISP) 14, an input unit (INPT) 15, a storage Unit (MEM) 16, communication unit (COMM) 17, and control unit (CONT) 20.
  • CAM camera
  • G-SEN acceleration sensor
  • P-SEN position sensor
  • DISP display unit
  • IPT input unit
  • MEM storage Unit
  • COMP communication unit
  • CONT control unit
  • the camera 11 is installed on the back surface of the smartphone 1, and in the state shown in FIG. 1, the camera 11 images the front of the vehicle.
  • the acceleration sensor 12 is a triaxial acceleration sensor.
  • the acceleration sensor 12 outputs acceleration detection values Ax, Ay, Az, which are detection values of the accelerations of these three axes, to the control unit 20.
  • acceleration detection values A when it is not necessary to distinguish the three-axis acceleration detection values, they are simply referred to as acceleration detection values A.
  • the position sensor 13 includes a GNSS receiver that receives radio waves from a satellite included in a GNSS (Global Navigation Satellite System). Based on the signal received by the GNSS receiver, the current position is sequentially detected.
  • GNSS Global Navigation Satellite System
  • the display unit 14 is a liquid crystal display, for example, and displays an operation screen for causing the smartphone 1 to execute the drive recorder function. Further, during execution of the drive recorder function, an image taken by the camera 11 is displayed.
  • the input unit 15 includes a touch panel stacked on the display screen of the display unit 14. The user operates the input unit 15 when causing the smartphone 1 to execute various functions such as a drive recorder function.
  • the storage unit 16 is a rewritable storage unit such as a flash memory
  • the smartphone 1 includes various devices such as a drive recorder program (DRV-REC-PROGRAM) 16a and a vehicle sensor signal processing program (SIG-PROCESSING-PROGRAM) 16b.
  • a program for executing the function is stored.
  • the drive recorder program 16a is a program for causing the smartphone 1 to function as a drive recorder.
  • the vehicle sensor signal processing program 16b is used together with the drive recorder program, and is a program for correcting the acceleration detection value A output from the acceleration sensor 12.
  • the storage unit 16 also stores moving image data (MOVIE-DATA) 16c and vehicle behavior data (BEHAVIOR-DATA) 16d.
  • the moving image data 16 c is data indicating a moving image in front of the vehicle imaged by the camera 11.
  • the vehicle behavior data 16d is data indicating vehicle behavior detected or calculated during imaging of the moving image data 16c.
  • the moving image data 16c and the vehicle behavior data 16d are stored in the storage unit 16 when the drive recorder program is being executed.
  • the communication unit 17 communicates with other smartphones via a public telephone line network. Moreover, you may be provided with the near field communication function which communicates directly between terminals.
  • the control unit 20 is a computer including a CPU, a ROM, a RAM, and the like, and the CPU executes various programs by executing programs stored in the ROM or the storage unit 16 while using a temporary storage function of the RAM. Perform the function.
  • the CPU executes a drive recorder program 16a and a vehicle sensor signal processing program 16b stored in the storage unit 16.
  • the storage unit 16 provides a non-transitional physical storage medium that stores a computer-readable program.
  • the control unit 20 includes a detection value acquisition unit (VALUE-INPUT) 21, an acceleration correction unit (G-CORRECT) 22, a sudden acceleration determination unit (ACCL-DET) 23, and a sudden deceleration determination unit (DECL-DET) 24.
  • the acceleration correction unit 22 provides a detection value correction unit. Note that some or all of the functions executed by the control unit 20 may be configured by hardware using one or a plurality of ICs.
  • FIG. 3 is a flowchart showing processing when the CPU of the control unit 20 executes the drive recorder program 16a and the vehicle sensor signal processing program 16b. Among the processes of FIG. 3, the process of step S4 is shown in detail in FIG. 7, and the process of FIG. 7 is a process performed by executing the vehicle sensor signal processing program 16b.
  • Steps S1 to S3 and S6 are processes executed by the detection value acquisition unit 21, the speed calculation unit 27, and the history storage processing unit 28.
  • Step S4 is a process executed by the acceleration correction unit 22
  • step S5 is a process executed by the sudden acceleration determination unit 23, the sudden deceleration determination unit 24, the bump spot determination unit 25, and the sudden turn determination unit 26.
  • step S1 it is determined whether or not an operation for starting use of the drive recorder function has been performed. For example, the start icon of the drive recorder function is displayed in advance on the display unit 14, and the determination of step S1 is YES when the position corresponding to the start icon is touched on the touch panel. If judgment of step S1 becomes YES, it will progress to step S2. If the determination in step S1 is NO, the determination in step S1 is repeated.
  • step S2 the drive recorder function is started. Specifically, images are continuously captured by the camera 11. The captured image is temporarily stored in the RAM. Along with storing the latest image in the RAM, the oldest image among the images stored in the RAM is deleted. Thereby, the latest moving image data for a certain period is stored in the RAM while the drive recorder function is being executed.
  • the acceleration detection value A is acquired from the acceleration sensor 12 at a constant cycle.
  • the detection value acquisition unit 21 acquires the acceleration detection value A.
  • the acquisition period of the acceleration detection value A is, for example, 100 msec.
  • the speed calculation unit 27 sequentially calculates the speed of the vehicle from the time change of the position sequentially detected by the position sensor 13.
  • the history storage processing unit 28 performs the other processes.
  • the history storage processing unit 28 also temporarily stores the acceleration detection value A in the predetermined acceleration detection value storage area of the RAM for the predetermined period. Further, the speed calculated by the speed calculation unit 27 is also stored in the RAM for the certain period. Further, the display unit 14 displays a screen when the drive recorder function is executed. On this screen, a function end button is displayed. Further, an image captured by the camera 11 may be displayed.
  • step S3 it is determined whether or not an operation for ending use of the drive recorder function has been performed. This operation is, for example, an operation of touching a position corresponding to the above-described function end button on the touch panel. If the determination in step S3 is YES, the process in FIG. 3 is terminated. If judgment of step S3 is NO, it will progress to step S4.
  • step S4 acceleration real-time correction processing is performed. As described above, this process is performed by executing the vehicle sensor signal processing program 16b.
  • the vehicle sensor signal processing program 16b is executed in parallel with the drive recorder program 16a, for example, by interruption processing.
  • the acceleration real-time correction process is a process of sequentially correcting the acceleration detection value A output from the acceleration sensor 12. Before describing the details of the acceleration real-time correction process, the reason why the acceleration detection value A output from the acceleration sensor 12 needs to be corrected will be described.
  • FIG. 4 conceptually shows the case where the smartphone 1 is installed so that the y-axis of the acceleration sensor 12 built in the smartphone 1 is in the vertical direction.
  • the x-axis direction of the acceleration sensor 12 is parallel to the vehicle width direction.
  • the z-axis direction of the acceleration sensor 12 is parallel to the vehicle front-rear direction and is also parallel to the horizontal axis 110.
  • VH-Fr indicates the front of the vehicle
  • VH-Rr indicates the rear of the vehicle.
  • the smartphone 1 is rarely installed in the posture shown in FIG. 4, and is installed in a posture inclined with respect to the posture shown in FIG.
  • the smartphone 1 is in a posture in which the upper end is on the front side of the vehicle with respect to the lower end. Therefore, the y axis of the acceleration sensor 12 is inclined by ⁇ 1 with respect to the vertical direction. Accordingly, the z axis of the acceleration sensor 12 is also inclined with respect to the horizontal axis 110, and the angle between the horizontal axis 110 and the z axis is ⁇ 1.
  • g is the acceleration of gravity.
  • g is about 9.8 m / s2.
  • the detection value Az is gsin ⁇ 1 and does not become zero.
  • the acceleration sensor 12 is a sensor whose detection value changes due to a change in posture.
  • FIG. 6 is a diagram illustrating an example of the inclination of the smartphone 1 during deceleration.
  • the alternate long and short dash line indicates the posture of the smartphone 1 in FIG. 4
  • the alternate long and two short dashes line indicates the posture of the smartphone 1 in FIG. 5.
  • a solid line is an example of the inclination of the smartphone 1 during deceleration.
  • the posture of the smartphone 1 is a posture in which the upper end is further lowered than in FIG. Assuming that the angle between the y-axis direction and the vertical direction of the acceleration sensor 12 in FIG. 6 is ⁇ 2, ⁇ 2> ⁇ 1.
  • the gravitational acceleration component in the z-axis direction detected by the acceleration sensor 12 is gsin ⁇ 2, as shown in FIG. 6, and is larger than gsin ⁇ 1, which is a value detected at rest. Further, at the time of deceleration, the acceleration generated by the deceleration is included in the z-axis acceleration detection value Az of the acceleration sensor 12. In the example of FIG. 6, since the z axis of the acceleration sensor 12 is inclined by ⁇ 2 with respect to the horizontal axis 110, when acceleration ⁇ occurs in the vehicle due to deceleration, the acceleration of ⁇ cos ⁇ 2 is present on the z axis of the acceleration sensor 12. Arise.
  • the z-axis acceleration detection value Az detected by the acceleration sensor 12 is a value obtained by adding noise N to gsin ⁇ 2 and ⁇ cos ⁇ 2, that is, gsin ⁇ 2 + ⁇ cos ⁇ 2 + N.
  • This value varies with ⁇ 2 even if the acceleration ⁇ generated in the vehicle by deceleration is the same. Therefore, it is not necessary to make a determination such as sudden acceleration or sudden deceleration with the same value. Therefore, acceleration real-time correction is performed in order to remove the influence caused by the posture of the smartphone 1 from the acceleration detection value A output by the acceleration sensor 12.
  • acceleration real-time correction processing is also performed on the acceleration detection value A on the x-axis and y-axis of the acceleration sensor 12.
  • FIG. 7 shows acceleration real-time correction processing. Note that the processing in FIG. 7 is performed separately for the triaxial acceleration detection value A of the acceleration sensor 12.
  • step S41 the latest acceleration detection value A and the acceleration detection value A for the past one minute are acquired from the acceleration detection value storage area of the RAM. That is, the acceleration detection value A from one minute before the latest time is acquired.
  • the broken line waveform shown in FIG. 8 is an example of the z-axis acceleration detection value Az stored in the RAM.
  • One minute is an example, and the acceleration detection value A for a time longer than one minute or shorter than one minute may be acquired.
  • step S42 the low-frequency component Grav (n) is extracted from the acceleration detection value A acquired in step S41 by passing the acceleration detection value A acquired in step S41 through a low-pass filter. This process provides a DC component removal process.
  • the process in step S42 is a process for performing the following equation 1, for example.
  • n is an integer whose value changes by 1 for each signal acquisition.
  • step S43 the low frequency component Grav extracted in step S42 is subtracted from the acceleration detection value A acquired in step S41.
  • the subtracted value will be referred to as an acceleration AC component AAC.
  • the solid line waveform shown in FIG. 8 indicates the waveform of the acceleration alternating current component AAC.
  • step S44 the effective value AACe (n) of the acceleration alternating current component AAC is updated.
  • (n) of the effective value AACe (n) is omitted.
  • This effective value AACe is also called a root mean square, and calculates a root mean square of acceleration alternating current component AAC for a certain period.
  • Expression 2 is an example of an expression for calculating the effective value AACe.
  • step S45 normalization is performed on the latest acceleration alternating current component AAC. Specifically, the latest acceleration AC component AAC is divided by the effective value AACe updated in step S44.
  • step S46 a high-cut filter process is performed on the waveform composed of the value obtained in the process in step S45 and the value obtained in the process in the previous step S45 to remove high-frequency noise components.
  • the process of step S46 provides a high frequency removal process.
  • the waveform shown by the solid line in FIG. 9 is an example of the waveform obtained by the process of step S46.
  • the waveform of the broken line and the waveform of the alternate long and short dash line are the same as those in FIG.
  • step S47 the latest value in the waveform obtained in the process of step S46 is output as a corrected acceleration to the rapid acceleration determination unit 23, the rapid deceleration determination unit 24, the bump point determination unit 25, and the rapid turn determination unit 26.
  • the rapid acceleration determination unit 23, the rapid deceleration determination unit 24, the bump point determination unit 25, and the sudden turn determination unit 26 have thresholds for determining sudden acceleration, sudden deceleration, bump point, and sudden turn, respectively.
  • step S5 of FIG. 3 the sudden acceleration determination unit 23, the rapid deceleration determination unit 24, the bump spot determination unit 25, and the sudden turn determination unit 26 are set to the preset threshold value and the corrected acceleration determined in step S4. And compare.
  • the rapid acceleration determination unit 23 and the rapid deceleration determination unit 24 compare the z-axis corrected acceleration with a threshold value
  • the bump point determination unit 25 compares the y-axis corrected acceleration with a threshold value
  • the sudden turn determination unit 26 Compares the x-axis and the corrected acceleration of the axis with a threshold value.
  • step S5 is performed. The determination becomes YES. If the determination in step S5 is YES, the process proceeds to step S6, and if NO, the process returns to step S3.
  • step S6 the moving image data for a preset period is stored in the storage unit 16 from the moving image data stored in the RAM. This period is, for example, 20 seconds before and after the time point when the determination in step S6 is YES. Further, from the vehicle behavior data stored in the RAM, data for the same period as the moving image data is stored in the storage unit 16 in association with the moving image data. The vehicle behavior here is acceleration and speed. After executing step S6, the process returns to step S3.
  • the acceleration AC component AAC is obtained by subtracting the low frequency component Grav from the acceleration detection value A (S43), and the acceleration detection value A is normalized by the effective value AACe of the acceleration AC component AAC (S44, S45).
  • normalization may be performed first, and then the low frequency component Grav may be subtracted. That is, the effective value Ae of the acceleration detection value A before subtracting the low frequency component Grav is updated, the acceleration detection value A is normalized by the effective value Ae, and then the normalized low frequency component Grav is obtained.
  • the low frequency component Grav may be subtracted from the normalized value. Even if the order of normalization and subtraction of the low-frequency component Grav is changed, the same effect as the above-described embodiment can be obtained.
  • FIG. 10 is a graph for explaining the effect in the first modification. This graph shows the result of setting two smartphones 1 of different models on the same vehicle and detecting the acceleration detection value Az at the same time, and the corrected acceleration after correcting the acceleration detection value Az.
  • the 10 is a graph showing the acceleration detection value Az on the z axis and the change in normalized acceleration obtained by normalizing the acceleration detection value Az with the effective value of the acceleration detection value Az.
  • the lower graph is a graph showing changes in the normalized acceleration, the low-frequency component GravZ of the normalized acceleration, and the corrected acceleration.
  • the right graph and the left graph are different from each other in the model of the smartphone 1.
  • the z-axis acceleration detection value Az is higher than 10 in the left graph, even though the same vehicle is measuring simultaneously.
  • the peak value is about 9. That is, the peak values are different.
  • the time T during which these peak values are detected is also different.
  • the first reason for this difference is that the installation posture of the smartphone 1 is different.
  • the second reason is that the type of the acceleration sensor 12 used differs depending on the model of the smartphone 1, and the sensitivity to the same acceleration is different if the type of the acceleration sensor 12 is different.
  • the third reason is that the mixed noise differs if the smartphone 1 is different.
  • the acceleration detection value Az is normalized by an effective value to obtain a normalized acceleration, and a low frequency component GravZ of the normalized acceleration is extracted.
  • the corrected acceleration obtained by subtracting the low-frequency component GravZ from the normalized acceleration has substantially the same waveform in the left and right graphs.
  • the peak value is about 5.5 for both the left and right graphs, and the time T during which the peak value is reached is substantially the same.
  • the acceleration sensor 12 outputs the acceleration detection value A that changes due to the acceleration generated in the vehicle.
  • This acceleration detection value A is a value affected by a sensitivity difference due to a difference in the type of the acceleration sensor 12 and a sensitivity difference due to a difference in the installation posture of the smartphone 1.
  • the acceleration correction unit 22 normalizes the acceleration detection value A by dividing it by the effective value AACe calculated from the acceleration detection value A for the past one minute. By this normalization, it is possible to reduce the influence of the sensitivity difference due to the difference in the model and the sensitivity difference due to the detection condition such as the installation posture.
  • the low frequency component Grav is removed from the acceleration detection value A (S42, S43).
  • the corrected acceleration (S47) is a value in which the influence of the installation posture of the smartphone 1 is further reduced. This effect can also be obtained in the first modification in which the order of normalization and the subtraction of the low-frequency component Grav is switched with the embodiment.
  • the low frequency component Grav is subtracted from the acceleration detection value A (S43).
  • position of the smart phone 1 can be reduced more. Since this process is also performed in the first modification, it will be described that the influence of the installation posture of the smartphone 1 can be reduced using FIGS. 10 to 13 as an example.
  • the broken line indicates the acceleration detection value Az.
  • the alternate long and short dash line indicates the normalized acceleration.
  • the two-dot chain line indicates the low frequency component GravZ.
  • the solid line shows the corrected acceleration.
  • the vertical axis represents acceleration and the horizontal axis represents time.
  • the low frequency component Grav can be removed to some extent.
  • the waveform of the acceleration detection value A is dull, and the waveform level may not decrease to the corrected acceleration level of FIG. 11 or FIG.
  • the fact that the waveform level does not decrease to the corrected acceleration level shown in FIG. 11 or FIG. 13 means that the influence of the low frequency component Grav has not been sufficiently removed.
  • the low frequency component Grav is subtracted from the acceleration detection value A as in the above-described embodiment, the influence of the low frequency component Grav can be sufficiently removed.
  • the waveform of the acceleration detection value Az is greatly different between the examples. Nevertheless, the corrected acceleration waveforms are almost identical in shape between the examples.
  • the influence of the installation posture of the smartphone 1 can be further reduced. Since the smartphone 1 is a portable device, the smartphone 1 is detachably installed in the vehicle interior. For this reason, the smart phone 1 has a high possibility that the change in the installation posture differs for each use. Therefore, it is significant to reduce the influence of the installation posture as in the above-described embodiment and Modification 1.
  • the high cut filter process (S46) since the high cut filter process (S46) is performed, the high frequency noise is also removed from the acceleration detection value A.
  • the acceleration sensor 12 is exemplified as the sensor, but the sensor to which the present invention can be applied is not limited to the acceleration sensor.
  • an angular velocity sensor that detects an angular velocity as a physical quantity can be used.
  • the bump point determination unit 25 and the sudden turn determination unit 26 use the angular velocity corrected in the same manner as in the above-described embodiment and modification 1 together with the corrected acceleration, or replace the corrected acceleration. To make a decision.
  • sensors other than the acceleration sensor 12 and the angular velocity sensor for example, a gyro sensor may be used.
  • the smartphone 1 is exemplified as the vehicle sensor signal processing device.
  • a drive recorder may be used as the vehicle sensor signal processing device.
  • This drive recorder may be installed by the user of the vehicle in the vehicle interior (Modification 3), or may be installed in a part of the vehicle outside the vehicle compartment such as a cargo compartment at the time of vehicle shipment (Modification 4).
  • the installation posture is highly likely to be different for each vehicle, and therefore, the significance of applying the present invention is great.
  • a tablet computer may be used as a vehicle sensor signal processing device (Modification 5).
  • the tablet computer or the smartphone 1 can realize various functions by installing a program by the user. Therefore, if the vehicle sensor signal processing program 16b is installed, various types of tablet computers and smartphones 1 can be used as the vehicle sensor signal processing device.
  • sensors such as an acceleration sensor built in the tablet computer or the smartphone 1 are likely to have various types.
  • the installation posture when used in a vehicle is likely to change every time it is installed in the vehicle. Therefore, it is particularly significant to apply the present invention that can reduce the influence of the sensitivity difference due to the difference in model and the sensitivity difference due to the detection condition such as the installation posture.
  • the high cut filter process (S45) is performed on the value after normalization, but the high cut filter process may be performed before normalization.
  • normalization is performed using an effective value, but normalization may be performed using a representative value other than the effective value instead of the effective value.
  • representative values other than the effective value include a median value, a mode value, and an average value.
  • the low-frequency component Grav (n) is extracted from the acceleration detection value A by Equation 1, but the low-frequency component Grav (n) may be extracted by a frequency analysis method such as Fourier transform. Good.

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Abstract

La présente invention concerne un dispositif de traitement de signal de capteur de véhicule qui est utilisé dans un véhicule. Le dispositif de traitement de signal de capteur de véhicule est pourvu d'un capteur d'accélération, d'une unité d'acquisition de valeur détectée pour acquérir des valeurs d'accélération détectées transmises en sortie par le capteur d'accélération, et une unité de correction d'accélération pour normaliser les valeurs d'accélération détectées acquises par l'unité d'acquisition de valeur détectée sur la base de valeurs quadratiques moyennes. Les valeurs d'accélération détectées transmises en sortie par le capteur d'accélération sont influencées par les différences de sensibilité résultant de différences de type et de différences d'orientation d'installation et d'autres conditions de détection. La normalisation des valeurs d'accélération détectées sur la base des valeurs quadratiques moyennes permet de réduire l'influence de différences de sensibilité résultant des différences de type et des différences d'orientation d'installation et d'autres conditions de détection.
PCT/JP2015/001384 2014-03-25 2015-03-12 Dispositif de traitement de signal de capteur de véhicule et programme de traitement de signal de capteur de véhicule WO2015146045A1 (fr)

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WO2018088041A1 (fr) * 2016-11-11 2018-05-17 ソニー株式会社 Dispositif de traitement d'informations
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