JP2015161580A - road surface inspection system and road surface inspection method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To easily measure an index of an accurate road surface independently of a measurement condition of an installation position or the like of an acceleration sensor in a road surface inspection system using the acceleration sensor.SOLUTION: A measurement device removably installed in a vehicle acquires a measurement condition and stores it into a first storage unit, measures vibration data of the vehicle during travel using a vibration measurement unit, measures position data of the vehicle using a position measurement unit and stores the vibration data and the position data into the first storage unit. A computer for calculating an index accepts the measurement condition, the vibration data, and the position data stored in the first storage unit and converts the vibration data into an acceleration displacement of sprung mass of a vibration model and converts the acceleration displacement of sprung mass into the index and stores the index and the position data into a second storage unit in association with each other.

Description

  The present invention relates to an inspection technique for maintaining and managing a road, and relates to a road surface inspection system using an acceleration sensor.

  The road surface inspection system periodically measures road surface unevenness displacement (hereinafter referred to as a road surface profile) with a road surface property measuring vehicle and determines when to perform road maintenance. As a method for measuring a road surface profile, a method using a laser profiler or vibration measurement is known.

  The laser profiler is expensive, and when the road surface gets wet during rainy weather, the laser of the laser profiler is irregularly reflected, making it difficult to accurately measure the road surface profile. For this reason, a technique is known in which vibration is measured by an acceleration sensor installed in a vehicle, and a road surface profile is measured from vibration on the vehicle (for example, Patent Document 1).

  Patent Document 1 discloses a vibration measurement means (acceleration sensor) that measures vibrations in a vertical direction in a vehicle body floor portion traveling on a road in time series, and the vehicle measured in time series by the vibration measurement means. A road surface comprising data conversion means for converting vertical vibration data of the main body floor into road surface displacement data of the road, and data output means for outputting road surface displacement data obtained by the data conversion means. A diagnostic device is described. In addition, the prior art described in Patent Document 1 can diagnose the road surface condition on a daily and quantitative basis at a low cost, and does not require a special specification vehicle as a vehicle. It is described that a road surface diagnosis method that does not cost can be provided.

JP 2004-108988 A

  In the conventional example, a vibration measuring device (acceleration sensor) is attached to the upper part of the floor of the vehicle, and a controller and a GPS receiver made up of a portable personal computer are mounted on the vehicle. The machine is connected to each other with a communication cable. The vibration measuring instrument needs to be installed at a preset position. When the installation position is changed, the vibration measuring instrument needs to be reset. This resetting, for example, is to measure and set specifications relating to the position of the acceleration sensor again, and requires a great deal of labor.

  Furthermore, in the above-mentioned conventional example, since a controller comprising a personal computer, a GPS receiver, and a vibration measuring instrument are brought into the vehicle and then connected by a communication cable, a road surface profile (or an index indicating the degree of unevenness of the road surface) is measured. There was a problem that it took time and effort to get started.

  In view of the above, an object of the present invention is to easily measure an accurate road surface index with respect to a road surface inspection system using an acceleration sensor regardless of measurement conditions such as an installation position of the acceleration sensor.

  The present invention is a road surface inspection system for measuring an index indicating the degree of unevenness of a road surface, the measurement device detachable from a vehicle, the vibration data, the position data and the measurement conditions acquired by the measurement device, A calculator that calculates an index indicating the degree of unevenness of the measuring device, wherein the measuring device includes a measurement condition input unit that acquires measurement conditions, a vibration measurement unit that measures vibration data, and a position that measures vehicle position data. A measurement unit; and a first storage unit that stores the measurement condition, the vibration data, and the position data. The computer includes a processor, a second storage unit, and the first storage unit. A data input unit that receives the stored measurement conditions, the vibration data, and the position data; a vibration data conversion unit that converts the vibration data into an acceleration displacement of a sprung mass of a vibration model; An index conversion unit that converts acceleration displacement of the upper mass into the index, and a second storage unit that stores the index and the position data in association with each other, and the vibration data conversion unit stores the vibration data A conversion parameter for converting to an acceleration displacement of a sprung mass is set in advance for each of the plurality of measurement conditions, the conversion parameter corresponding to the received measurement condition is selected, and the vibration data is selected using the selected conversion parameter. Convert to acceleration displacement of sprung mass.

  According to the present invention, it is possible to evaluate road surface indices at low cost and with high frequency. In addition, it is possible to easily measure and evaluate an accurate road surface index regardless of measurement conditions such as the installation position of the acceleration sensor.

1 is a block diagram illustrating an example of a road surface inspection system according to a first embodiment of this invention. It is a block diagram which shows a 1st Example of this invention and shows an example of an IRI converter. It is a flowchart which shows a 1st Example of this invention and shows an example of the process performed with a road surface inspection system. It is a flowchart which shows a 1st Example of this invention and shows an example of the prior learning process which produces | generates the conversion parameter of vibration data. It is a flowchart which shows a 1st Example of this invention and shows an example of the measurement process performed with a road surface inspection system. 1 is a quarter car model showing an example of a vehicle vibration model according to the first embodiment of the present invention. FIG. 2 is a screen image of a measurement condition input unit in the first embodiment of the present invention. It is a screen image which shows the 1st Example of this invention and shows an example of the input screen of the installation state of a measuring apparatus. It is a block diagram which shows a 2nd Example of this invention and shows an example of the measuring apparatus which inputs measurement conditions automatically. It is a figure which shows the 2nd Example of this invention and shows the measurement axis | shaft of the geomagnetic sensor of a measuring apparatus. It is a block diagram which shows a 3rd Example of this invention and shows an example of the measuring apparatus which inputs an installation position automatically. 4 shows a fourth embodiment of the present invention, which is an example of a road surface repair necessity determination method using only the current IRI. It is a flowchart which shows the 41st Example of this invention and shows an example of the necessity determination process of the road surface repair using the present and past IRI. It is a figure which shows the 4th Example of this invention and shows an example of the prediction graph of future IRI.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings. Note that components having the same function are denoted by the same reference symbols throughout the drawings for describing the embodiment, and the repetitive description thereof will be omitted.

  FIG. 1 is a block diagram showing an example of the configuration of a road surface inspection system 2000 according to the present invention. As shown in FIG. 1, a road surface inspection system 2000 is installed in a vehicle 800 such as an automobile to measure vibration data, and is installed in an office 200 that manages roads to transmit vibration data internationally. And an IRI converter 206 for converting into an roughness index (International Roughness Index: hereinafter IRI). The IRI conversion device 206 includes an input / output device 202 that records the output in the database 201 and browses the IRI 500. A road administrator or the like refers to the IRI with the input / output device 202 to determine whether or not the road surface needs to be repaired. The IRI is an evaluation index related to the uneven displacement of the road surface proposed by the World Bank in 1989. In the following description, an example in which IRI is used as the road surface profile is shown, but the present invention is not limited to this, and any value indicating the uneven displacement of the road surface may be used.

  The measuring device 810 can be carried as a mobile terminal and is detachable from the vehicle 800. The measuring device 810 includes a processor 80, a memory 803, a display 901 having a touch panel function, a GPS (Global Positioning System) receiver 802, an acceleration sensor (vibration measuring unit) 801, and a data output unit 804. .

  The IRI conversion device 206 acquires data measured by the measurement device 810 via the data transfer unit 220. The data transfer unit 220 can be configured by wireless communication such as WiFi, wired communication such as USB, or a nonvolatile storage medium. Therefore, the data input unit 207 of the IRI conversion device 206 and the data output unit 804 of the measurement device 810 are configured with an interface corresponding to the data transfer unit 220.

  The measuring device 810 measures time-series vibration data 600 with the built-in acceleration sensor 801 and records it in the memory 803. Note that the acceleration sensor 801 is constituted by, for example, a triaxial acceleration sensor, but it is sufficient that at least acceleration in the vertical (vertical) direction of the vehicle body can be measured. A GPS receiver (position measuring unit) 802 built in the measuring device 810 measures latitude and longitude (hereinafter referred to as position data) and records them in the memory 803.

  In addition to the measurement data (vibration data 600, position data 610), the road surface property measuring unit 90 including the measurement condition input unit 900 is loaded as a program in the memory 803, and the road surface property measuring unit 90 is executed by the processor 80. Thus, the vibration data 600 is measured.

  The measurement condition input unit 900 receives input of the measurement condition 700 such as the installation position of the measurement apparatus 810 in the vehicle, and records the measurement condition 700 in the memory 803. The data output unit 804 outputs the vibration data 600, the position data 610, and the measurement conditions 700 recorded in the memory 803 to the IRI converter 206.

  The vibration data 600, the position data 610, and the measurement condition 700 are transferred to the IRI conversion device 206 via wireless communication or a nonvolatile storage medium. The position data 610 indicates the position where the vibration data 600 is measured, and the position data 610 is associated with the vibration data 600.

As the measuring device 810, for example, a multifunctional mobile terminal (smart phone or tablet) incorporating a plurality of sensors such as an acceleration sensor and a geomagnetic sensor can be used.
Here, each functional unit of the road surface property measuring unit 90 and the measurement condition input unit 900 is loaded into the memory 803 as a program.

  The processor 80 operates as a functional unit that provides a predetermined function by performing processing according to the program of each functional unit. For example, the processor 80 functions as the road surface property measuring unit 90 by performing processing according to the road surface property measuring program. The same applies to other programs. Furthermore, the processor 80 also operates as a function unit that provides each function of a plurality of processes executed by each program. A computer and a computer system are an apparatus and a system including these functional units.

  The data input unit 207 of the IRI conversion device 206 reads the vibration data 600, the position data 610, and the measurement condition 700 output from the measurement device 810, and transmits them to the vibration data conversion unit 208.

  The vibration data conversion unit 208 uses the vibration data 600 measured under the measurement condition 700 (for example, the measurement device 810 is installed on the floor of the rear seat) as the spring of the quarter car (QC) model of the vehicle shown in FIG. The acceleration displacement (z1 ″) of the upper mass is converted into the acceleration displacement (z1 ″) of the upper mass. The IRI conversion unit 209 converts the acceleration displacement (z1 ″) of the sprung mass into the IRI 500 using the QC simulation, and associates it with the position data 610 in the database 201. Record.

  FIG. 2 is a block diagram illustrating an example of the IRI conversion device 206. The IRI conversion device 206 includes a processor 20, a memory 21, a data input unit 207, a storage device 22, and an input / output device 202. The input / output device 202 can be composed of a display and a mouse, keyboard or touch panel.

  A vibration data conversion unit 208 and an IRI conversion unit 209 are loaded in the memory 21 as programs and executed by the processor 20. The processor 20 operates as a functional unit that provides a predetermined function by processing according to a program of each functional unit. For example, the processor 20 functions as the vibration data conversion unit 208 by performing processing according to the vibration data conversion program. The same applies to other programs. Furthermore, the processor 20 also operates as a functional unit that provides each function of a plurality of processes executed by each program. A computer and a computer system are an apparatus and a system including these functional units.

  The data input unit 207 receives the measurement data output from the measurement device 810 and transfers it to the vibration data conversion unit 208. The vibration data conversion unit 208 converts the vibration data 600 measured according to the measurement condition 700 into the acceleration displacement (z1 ″) of the sprung mass of the QC model in FIG. 6. The IRI conversion unit 209 performs the spring analysis by QC simulation. The acceleration displacement (z1 ″) of the upper mass is converted into IRI 500 and recorded in the database 201 of the storage device 22 in association with the position data 610.

  Information such as programs and tables for realizing the functions of the vibration data conversion unit 208 and the IRI conversion unit 209 includes storage devices 22, nonvolatile semiconductor memories, hard disk drives, storage devices such as SSDs (Solid State Drives), Alternatively, it can be stored in a computer-readable non-transitory data storage medium such as an IC card, SD card, or DVD.

  The storage device 22 stores a database 201 that manages the IRI 500 and the position data 610, and a conversion parameter list 300 having a plurality of conversion parameters. In the illustrated example, an example of the local storage device 22 of the IRI conversion device 206 is shown, but an external storage device connected via a network can be used.

  FIG. 3 is a flowchart illustrating an example of a road surface inspection process performed by the road surface inspection system 2000. First, the measurement device 810 is installed in the vehicle 800, the vehicle 800 travels on a road surface with a known road surface profile (IRI 500), and the parameters of the measurement device 810 are generated while changing the measurement condition 700 (installation position, etc.). Measure data for. Then, the IRI converter 206 generates a parameter (hereinafter referred to as a conversion parameter) for converting the vibration data 600 that varies depending on the measurement condition 700 into the acceleration displacement (z1 ″) of the sprung mass of the QC model (step S100). That is, in step S100, a learning process for generating a conversion parameter for each position where the measuring device 810 is mounted is performed by traveling on a road (road surface) of a known IRI 500 (road surface profile).

  Next, the vehicle 800 travels on the road surface subject to the IRI evaluation, and the measurement device 810 measures the vibration data 600 and the position data 610. Then, the IRI conversion device 206 converts the vibration data 500 measured under the measurement condition 700 into the acceleration displacement (z1 ″) of the sprung mass using the conversion parameter. The IRI conversion device 206 then converts the acceleration displacement of the sprung mass. Based on (z1 ″), the IRI 500 of the road surface is calculated (step S200). Finally, the IRI conversion device 206 outputs the IRI to the input / output device 202, and the road manager or the like determines whether or not the road surface needs to be repaired with reference to the IRI (step S300).

  The IRI conversion device 206 determines whether or not the IRI has been calculated for all road surfaces (or roads) to be evaluated for the measurement data (vibration data 600, position data 610, and measurement conditions 700) received from the measurement device 810. (Step S400). If there is still a road surface on which IRI should be calculated, the process proceeds to step S500, and measurement data of a different road surface is selected, and the process returns to step S200. On the other hand, if the calculation of IRI is completed for all road surface measurement data, the process ends.

  As described above, the IRI conversion device 206 executes the series of steps (S200 to S500) for all road surfaces to be evaluated by the IRI using the measurement data acquired from the measurement device 810.

  FIG. 6 is a quarter car (QC) model showing an example of a vehicle vibration model. Hereinafter, the conversion process from the vibration data 600 to the IRI 500 performed by the IRI converter 206 will be described with reference to the QC model.

  As processing of the IRI conversion unit 205, a road surface profile is converted into IRI using QC (Quarter Car) simulation. Specifically, a virtual vehicle model (referred to as a QC model) obtained by taking out only one of the two-axle four-wheel vehicle 800 shown in FIG. Calculate motion displacement. The ratio between the cumulative value (mm) of the vertical movement displacement received by the vehicle 800 and the travel distance L (m) is defined as IRI.

  As shown in FIG. 6, the sprung mass (vehicle weight supported by one wheel) is m1, the suspension damping factor is c1, the suspension spring constant is k1, and the unsprung mass (wheel and tire weight and suspension 1/2 weight of the axle) is m2, the spring coefficient of the tire is k2, the road profile is zp, the displacement of the sprung mass is z1, and the displacement of the unsprung mass is z2. Further, a value obtained by dividing the parameter of the QC model by the sprung mass m1 is defined by the following equations (1) to (4).

c1 / m1 = 6.0 (1)
k1 / m1 = 653 (2)
k2 / m1 = 63.3 (3)
m2 / m1 = 0.15 (4)

  Then, the IRI is calculated from the equations of motion (5) and (6) of the QC model and the following equations (7) to (11). Note that v is a traveling speed (for example, 80 km / hour).

m2z2 ″ + c1 (z2′−z1 ′) + k1 (z2−z1) + k2 (z2−zp) = 0 (5)
m1z1 ″ + c1 (z1′−z2 ′) + k1 (z1−z2) = 0 (6)
z2 ″ = d2z2 / dt2 (7)
z1 ″ = d2z1 / dt2 (8)
z2 ′ = dz2 / dt (9)
z1 ′ = dz1 / dt (10)

  FIG. 4 is a flowchart showing an example of a pre-learning process for generating vibration data conversion parameters. This process shows details of the process performed in step S100 of FIG. As shown in FIG. 7, the road surface inspection person installs the measuring device 810 at an arbitrary position (for example, the floor portion of the rear seat) in the vehicle 800 (step S101).

  Then, a road surface inspection person activates the road surface property measuring unit 90 of the measuring device 810 and inputs a measurement condition 700 such as an installation position (for example, the installation position of the measuring device 810 is a floor portion of the rear seat). Input is performed by the unit 900 (step S102). The measurement apparatus 810 sets the input received by the measurement condition input unit 900 as the measurement condition 700.

  Then, the road surface inspection person activates the acceleration sensor 801 and the GPS receiver 802 to start measurement of the vibration data 600 and the position data 610 (step S103).

  Next, the road surface inspection person drives the vehicle 800 and travels at a predetermined speed on the road surface whose road surface profile zp is known. During this time, the measuring device 810 acquires the vibration data 600 detected by the acceleration sensor 801 and the position data 610 detected by the GPS receiver and records them in the memory 803 (step S104). After the traveling, the road surface inspection person in charge outputs the vibration data 600, the position data 610, and the measurement condition 700 from the data output unit 804 (step S105). When the data transfer unit 220 is a nonvolatile storage medium (such as an SD card or a USB memory), the data input unit 207 and the data output unit 804 are configured by a reader / writer of a nonvolatile storage medium, and the measuring device 810 is stored in the memory 803. The recorded measurement data and measurement conditions 700 are written from the data output unit 804 to the nonvolatile storage medium.

  Then, in the office 200, the person in charge of road surface inspection reads the vibration data 600, the position data 610, and the measurement conditions 700 recorded in the nonvolatile storage medium from the data input unit 207 of the IRI conversion device 206 (step S106).

  Then, the vibration data conversion unit 208 calculates a frequency response | fm | of the vibration data 600 measured under the measurement condition 700. Further, the vibration data conversion unit 208 uses QC simulation to derive the acceleration displacement (z1 ″) of the sprung mass when the known road surface profile zp is input. The frequency response | fq | A conversion parameter | H | for converting the vibration data 600 measured under the measurement condition 700 into z1 ″ is obtained by the following equation (12) (step S107).

  | H | = | fm | / | fq | (12)

  Then, the vibration data conversion unit 208 holds the conversion parameter list 300 in which the measurement condition 700 and the conversion parameter | H | are linked (step S108). The conversion parameter list 300 can be stored in the storage device 22.

  As described above, the measurement apparatus 810 and the IRI conversion apparatus 206 execute the processing of steps S101 to S108 described above while changing the measurement condition 700. When the above processing is completed for all measurement conditions 700, the conversion parameter | H | for each measurement condition 700 is set in the conversion parameter list.

  For example, as shown in FIG. 7, the installation position of the measurement device 810, which is one of the measurement conditions 700, is on the passenger seat floor (L2), the rear seat floor (L4, C4, R4), and on the dashboard. (L1, C1, R1), front passenger seat (L3), rear seats (L5, C5, R5) and all other positions where measurement devices 810 can be installed can be targeted.

  FIG. 7 is a screen image 905 that the measurement condition input unit 900 outputs to the display 901.

  As shown in FIG. 7, the measurement condition input unit 900 displays a measurement condition input screen such as an interior plan view of the vehicle 800 on the display 901. In the illustrated example, the display 901 of the multi-function mobile terminal as the measuring device 810 functions as an input / output device because it has a touch panel function. The touch panel function detects a position touched with a finger on the display 901. Then, the processor 80 of the measurement apparatus 810 executes the process of the measurement condition input unit 900 and updates the display content of the display 901 according to the position touched on the display 901.

  As a procedure for inputting measurement conditions by the measurement condition input unit 900, a road surface inspector in a plan view (905) of the vehicle 800 displayed on the display 901 installs the measurement device 810 (for example, Touch the floor L2) of the passenger seat with your finger. Then, the touch panel function of the multi-function mobile terminal detects a position touched with a finger (passenger seat floor L2). Thereafter, the measurement condition input unit 900 determines the installation position of the measurement device 810 as the passenger seat floor L2 and records it as one of the measurement conditions 700 in the memory 803.

  FIG. 8 is a screen image 906 showing an example of an input screen for the installation state of the measuring apparatus 810. Next, when the input of the installation position is completed, the measurement condition input unit 900 displays a screen image 906 for inputting the installation state of the measurement device 810 on the display 901.

  As shown in FIG. 8, the road surface inspector touches the installation state selection unit 904 with the installation state of the measurement device 810 (for example, the installation state A in which the display 901 of the measurement device 810 faces the ceiling of the vehicle). To do. The installation state B indicates a state in which the display 901 of the measuring device 810 is directed toward the rear of the vehicle.

  Then, the touch panel function of the measuring device 810 detects a position (installation state A) touched with a finger. Thereafter, the measurement condition input unit 900 receives the installation state of the measurement apparatus 810 from the installation state selection unit 904 and records it as one of the measurement conditions 700 in the memory 803.

  As described above, when the measurement condition is input, the installation position and the installation state of the measurement apparatus 810 can be input to the measurement apparatus 810 as the measurement condition 700.

  In addition, the measurement condition input unit 900 allows a road surface inspection person to input other measurement conditions using a screen (not shown). Other measurement conditions include vehicle characteristics (vehicle weight, axle weight, wheel weight, tire weight, suspension weight, suspension damping rate and spring constant), vehicle travel speed, weather, and the like.

  When the acceleration sensor 801 is a three-axis acceleration sensor, the installation state included in the measurement condition 700 is XY when the IRI conversion device 206 converts the vibration data 600 into the acceleration displacement z1 ″ of the sprung mass of the QC model. -It becomes an index for selecting which acceleration (vibration) data of the Z axis is used.

  FIG. 5 is a flowchart illustrating an example of measurement processing performed in the road surface inspection system 2000. This process shows details of the process executed in step S200 of FIG.

  As shown in FIG. 5, steps S101 to S103 are the same as steps S101 to S103 in FIG. 4, and the measuring device 810 is installed at an arbitrary position in the vehicle, and the measuring device 810 is activated to start the acceleration sensor 801. The GPS receiver 802 is caused to function, and the measurement condition 700 is input by the measurement condition input unit 900.

  Next, the road surface checker drives the vehicle 800 and travels at a predetermined speed on the road surface subject to the IRI evaluation (S201). During this time, the measurement device 810 acquires the vibration data 600 detected by the acceleration sensor 801 and the position data 610 detected by the GPS receiver and records them in the memory 803 (step S202). After the traveling is finished, the road surface inspector outputs the vibration data 600, the position data 610, and the measurement condition 700 from the data output unit 804, and transfers the measurement data and the measurement condition 700 to the IRI converter 206 (step S203). . The IRI conversion device 206 reads measurement data and measurement condition 700 data via the data input unit 207.

  In the IRI conversion device 206, the vibration data conversion unit 208 converts the conversion parameter | H associated with the measurement condition 700 from the conversion parameter list 300 generated in advance by the generation processing of the conversion parameter | H | of FIG. Select |. For example, the vibration data conversion unit 208 selects a conversion parameter | H | that matches the installation position of the measurement device 810 in the vehicle and the measurement state from among the read measurement conditions 700.

  Then, the vibration data conversion unit 208 converts the vibration data 600 (Am) into the acceleration displacement z1 ″ of the sprung mass of the QC model by the following equation (13) (step S204).

  z1 ″ = Am / | H | (13)

  Next, using the above-described QC simulation, the IRI conversion unit 209 converts the acceleration displacement z1 ″ of the sprung mass of the QC model into the IRI 500 (step S205), and associates the IRI 500 with the position data 610 in the database 201. Recording is performed (step S206).

  From the above, when the installation position of the measuring device 810 incorporating the acceleration sensor is changed by the operation of installing and removing the acceleration sensor for each road inspection, the road inspection system 2000 does not depend on the measurement conditions such as the installation position of the acceleration sensor. It is possible to evaluate an accurate IRI (road surface profile). In addition, it is possible to evaluate IRI at low cost and high frequency without using a road surface property measuring vehicle having high equipment costs and maintenance costs.

  In the first embodiment, by using the measuring device 810 composed of a multi-function mobile terminal with a built-in acceleration sensor 801 and GPS receiver 802, installation and removal from the vehicle 800 can be performed extremely quickly. Can do. Thereby, the labor and time required for preparation for road surface inspection and the like can be greatly reduced.

  That is, in the conventional example, the acceleration sensor is attached to a predetermined position of the vehicle, the controller of the portable personal computer and the GPS receiver are installed in the vehicle, and the controller, the acceleration sensor, and the receiver are respectively connected by communication cables. It was. On the other hand, in the present invention, the measuring device 810 of the multifunctional portable terminal is installed at an arbitrary position in the vehicle, and then the road surface property measuring unit 90 is only activated. The efficiency of inspection work can be greatly improved.

  In the first embodiment, the example in which the acceleration sensor 801 is used to measure the vibration data 600 has been described. However, the present invention is not limited to this, and the displacement of the road surface may be measured by a laser profiler or the like.

  In the first embodiment, the GPS receiver 802 is used to measure the position data 610. However, the present invention is not limited to this, and the latitude and longitude may be measured by an inertial navigation device or the like.

  In order to simplify the input of the measurement condition 700 (installation position and installation state of the measurement apparatus) in the first embodiment, a measurement apparatus 820 that enables automatic input of the measurement condition 700 is shown as a second embodiment in FIG. . FIG. 9 is a block diagram illustrating an example of a measurement apparatus that automatically inputs measurement conditions.

  As shown in FIG. 9, the measurement device 820 includes a measurement condition estimation unit 910 and a geomagnetic sensor 920 instead of the measurement condition input unit 900 of the measurement device 810 of the first embodiment that manually inputs the measurement condition 700. The measurement condition estimation unit 910 may be included in the measurement condition input unit 900.

  Note that the measuring device 820 uses, for example, a multi-function mobile terminal (smart phone or tablet) incorporating a plurality of sensors such as an acceleration sensor 801 and a geomagnetic sensor 920. Further, the geomagnetic sensor (direction measuring unit) 920 measures the directions of three orthogonal axes (X axis, Y axis, Z axis) as shown in FIG. The geomagnetic sensor 920 may acquire the direction of a reference axis (for example, the X axis).

  FIG. 10 is a diagram illustrating a measurement axis of the geomagnetic sensor 920 of the measurement apparatus 820. The measurement condition estimation unit 910 records the installation state (direction) measured by the geomagnetic sensor 920 as one of the measurement conditions 700 in the memory 803.

  Note that there is no direction information for the axis in the ceiling direction of the vehicle (Z-axis in FIG. 10). Therefore, the measurement condition estimation unit 910 can determine the direction in which the vertical vibration (vibration data 600) of the vehicle 800 can be acquired as the Z-axis direction of the geomagnetic sensor 920. Therefore, if the three axes of the acceleration sensor 801 are in the same direction as the three axes of the geomagnetic sensor 920, the axis of the acceleration sensor 801 capable of acquiring vertical vibration (vibration data 600) is the Z axis. In the illustrated example, the Y-axis direction is set to 0 degrees, the X-axis direction is set to 90 degrees, and the Z-axis direction is set to none.

  Next, as an automatic input method of the installation position which is one of the measurement conditions 700, the measurement condition estimation unit 910 is based on the frequency response of the vibration data 600 at the installation position of the acceleration sensor 801 (measurement device 810). The installation position inside can be estimated.

  Specifically, as a preliminary preparation for road surface inspection, the measuring device 820 is installed at a specific installation position, and the vehicle 800 travels on the specific road surface 301. The specific road surface 301 is a road surface on which the vehicle 800 travels every time before the road surface inspection is started (for example, a road surface in front of the garage of the vehicle 800).

  Then, the measurement condition estimation unit 910 calculates the frequency response | f1 | from the vibration data 600 acquired from the acceleration sensor 801, and associates it with the installation position of the measurement device 820 and records it in the memory 803. Similarly, the installation positions of the measurement devices 820 are changed, and the frequency responses | f1 | at all the installation locations are calculated, linked to the installation locations of the measurement devices 820, and recorded in the memory 803. The traveling speed is constant. In addition, all the installation positions of the measuring apparatus 820 were L1-L6, C1-C6, and R1-R6 shown in FIG.

  Immediately before the inspection on the road surface inspection day, the road surface inspection person installs the measuring device 820 at an arbitrary installation position and travels on the specific road surface 301 by the vehicle 800. Then, the measurement condition estimating unit 910 calculates a frequency response | f2 | from the vibration data 600 detected by the acceleration sensor 801. Thereafter, the measurement condition estimation unit 910 searches for a frequency response having the highest correlation with the calculated frequency response | f2 | from a plurality of frequency responses | f1 | recorded in the memory 803. Then, the measurement condition estimating unit 910 estimates the installation position associated with the frequency response | f1 | of the maximum correlation value as the installation position of the measurement device 820. Then, the measurement condition estimation unit 910 records the installation position estimated as one of the measurement conditions 700 in the memory 803. Thereby, the installation position on the vehicle 800 of the measuring apparatus 820 is set.

  As described above, in the second embodiment, the measurement condition 700 (installation position and installation state of the measurement apparatus) can be automatically input (set). Therefore, in the second embodiment, it is not necessary for the road surface inspection person to manually input the measurement condition 700, and the input of the measurement condition 700 can be simplified.

  Note that the timing at which the measurement condition estimation unit 910 calculates the frequency response | f2 | from the vibration data 600 is, for example, when the GPS receiver 802 detects that the specific road surface 301 is passed, or when the specific road surface 301 is detected. As long as the person in charge of road surface inspection inputs a predetermined command to the measuring device 820, etc. In this case, the coordinates (start position and end position) of the specific road surface 301 may be set in the measurement device 820 in advance.

  FIG. 11 shows an example in which a method for automatically inputting the installation position of the measuring device 830 is realized by a method different from that in the second embodiment. FIG. 11 is a block diagram illustrating an example of a measuring device 830 that automatically inputs an installation position.

  As illustrated in FIG. 11, the measurement apparatus 830 adds a short-range wireless device 930 to the measurement apparatus 820 of the second embodiment. Other configurations are the same as those of the first embodiment. The short-range wireless device 930 is a device that supports, for example, IEEE 802.15.1 or wireless LAN wireless communication, and the strength of transmission radio waves of a short-range wireless communication device built in a car navigation or the like mounted on the vehicle 800 ( Measure RSSI (Received Signal Strength Indicator).

  Moreover, the measuring apparatus 830 uses, for example, a multi-function mobile terminal (smart phone) that includes an acceleration sensor, a geomagnetic sensor, or a short-range wireless device.

  A method of automatically inputting an installation position as one of the measurement conditions 700 is based on the radio field strength of short-range wireless communication detected by the short-range wireless device 930 at the installation position of the measurement apparatus 830 by the measurement condition estimation unit 910. Estimate the installation position in the car. The measurement condition estimation unit 910 may be included in the measurement condition input unit 900 of the first embodiment.

  Specifically, as a preliminary preparation for road surface inspection, the measurement device 830 is installed at a specific installation position, the measurement condition estimation unit 910 acquires the radio field intensity RSSI1 from the short-range wireless device 930, and the specific installation position It is linked and recorded in the memory 803. Similarly, the installation position of the measuring device 830 is changed, and the radio field intensity RSSI1 at all installation positions is measured. Then, the radio field intensity RSSI1 measured for each installation position is recorded in the memory 803 in association with the specific installation position.

  On the day of the road surface inspection, the road surface inspection person installs the measuring device 830 at an arbitrary position. Then, the measurement condition estimation unit 910 acquires the radio field intensity RSSI2 from the short-range wireless device 930. The timing at which the measurement condition estimation unit 910 measures the radio field intensity RSSI2 is, for example, the time when the installation of the measurement device 830 is completed and the start of the road surface property measurement unit 90 is completed, or a road surface inspection person or the like contacts the measurement device 830. The radio field intensity RSSI2 may be measured at a predetermined timing, such as when a predetermined command is input.

  Thereafter, the measurement condition estimation unit 910 searches the radio field strength RSSI3 closest to the currently measured radio field strength RSSI2 from the plurality of radio field strengths RSSI1 recorded in the memory 803. Then, the measurement condition estimation unit 910 acquires the installation position of the measurement device 830 that measured the radio field intensity RSSI3 from the memory 803, and estimates the installation position of the measurement device 830. Then, the measurement condition estimation unit 910 records the installation position estimated as one of the measurement conditions 700 in the memory 803.

  As described above, in the third embodiment, the measurement condition 700 (installation position of the measurement apparatus) can be automatically input using the near field radio field strength RSSI of the vehicle 800 detected by the near field wireless device 930. Therefore, according to the second and third embodiments, it is unnecessary to manually input the installation position and the installation state among the measurement conditions 700 by the road surface inspection person, and the measurement conditions 700 can be easily input.

  In the first to third embodiments, the road administrator (or road surface inspection person) browses the current and past IRI 500 recorded in the database 201 by the input / output device 202 and determines whether or not the road surface needs to be repaired. . The IRI conversion device 206 adds the date and time when the position data 610 is measured when storing the IRI 500 and the position data 610 in the database 201.

  First, FIG. 12 shows a method for determining whether or not a road surface needs to be repaired using only the current IRI 500. As shown in FIG. 12, the evaluation result of IRI 500 is displayed as a circle for each position data P <b> 1 to P <b> 5 on the travel locus of vehicle 800. Further, the larger the IRI 500 in each position data, the larger the circle is displayed. Therefore, the larger the radius of the circle, the larger the IRI of the road surface. A circle drawn with a dotted line means that IRI is equal to or greater than a specified value (a value exceeding a threshold value).

  Therefore, the road administrator views the current IRI 500 recorded in the database 201 by the input / output device 202, and determines that the positions (P2, P3) of the circles drawn with dotted lines are in need of repair. Further, it is determined that the higher the circle mark, the higher the repair priority of the road surface.

  Next, FIG. 13 is a flowchart showing an example of processing for determining whether or not road surface repair is required using the current and past IRI 500. This process is executed by the IRI conversion device 206 in response to a command from the input / output device 202.

  The IRI conversion device 206 receives the road surface data at the position (position data) designated by the road manager using the input / output device 202, and acquires the current (or most recent) IRI 500 and the past (before the most recent) IRI 500 from the database 201. Then, the process of FIG. 13 is executed. Note that the IRI conversion device 206 may acquire a plurality of past IRIs 500 at the designated road surface position.

  The IRI conversion device 206 determines whether or not the current IRI 500 is equal to or greater than a preset specified value (step S401). If the current IRI 500 is greater than or equal to the specified value, it is determined that the road surface needs to be repaired (step S406).

  On the other hand, if the current IRI 500 is less than the specified value, the process proceeds to step S402. In step S402, the IRI conversion apparatus 206 compares the past IRI 500 with the current IRI 500, and predicts the future IRI 500 (step S402). Specifically, as shown in FIG. 14, an approximate function is created based on the past and present IRI 500 to estimate the future IRI. FIG. 14 is a diagram illustrating an example of a future IRI prediction graph. For example, the IRI converter 206 calculates the future IRI 500 based on the amount of change (for example, a proportional coefficient) of the IRI 500 with respect to the time (date and time) of the approximate function. That is, the future IRI 500 is estimated from the recorded date / time (time series) change amount of the IRI 500. The future refers to a predetermined date and time in the future such as one year or two years from the present.

  Then, the IRI conversion device 206 determines whether or not the future IRI 500 is greater than or equal to a specified value (step S403). If the future IRI 500 is less than the predetermined value, the IRI conversion device 206 determines that the repair is unnecessary (step S405).

  On the other hand, if the future IRI 500 is greater than or equal to the specified value, the IRI conversion device 206 determines whether or not repair is necessary on the road surface at the adjacent position (step S404). This determination may be performed by reading the IRI 500 of the road surface at an adjacent position from the database 201 and performing the same determination as in step S401.

  When the IRI conversion device 206 determines that the future IRI 500 is equal to or greater than the specified value and the road surface at the adjacent position needs to be repaired, the IRI conversion device 206 determines that the road surface needs to be repaired (step S405). On the other hand, if it is determined that the repair of the road surface at the adjacent position is unnecessary even if the future IRI 500 is equal to or greater than the specified value, the IRI conversion device 206 determines that the repair of the road surface is not necessary (step S405).

  Therefore, according to the fourth embodiment, the current and past IRIs 500 can be used for determining whether or not road surface repair is necessary. Further, by using the past IRI 500, the future IRI 500 can be predicted. Therefore, when the road surface A that requires road surface repair in the near future is adjacent to the road surface B that currently requires road surface repair, the road surfaces A and B are repaired simultaneously. Therefore, it is possible to reduce the construction cost by repairing the road surface A and the road surface B at the same time, rather than repairing the road surface A and the road surface B at different times (closer times).

  As mentioned above, the invention made by the present inventor has been specifically described based on the embodiment. However, the present invention is not limited to the embodiment, and various modifications can be made without departing from the scope of the invention. Needless to say.

  In the first to fourth embodiments, an example in which IRI is used as an index indicating the degree of unevenness on the road surface is shown, but other indexes such as a road surface profile and a road surface displacement may be used instead of IRI.

  The configuration of the computer, the processing unit, the processing unit, and the like described in the present invention may be partially or entirely realized by dedicated hardware.

  In addition, the various software exemplified in the present embodiment can be stored in various recording media (for example, non-transitory storage media) such as electromagnetic, electronic, and optical, and through a communication network such as the Internet. It can be downloaded to a computer.

<Supplement>
A calculator that calculates an index indicating the degree of unevenness on the road surface,
A processor;
A second storage unit;
A data input unit for receiving vehicle vibration data, position data, and measurement conditions;
A vibration data converter for converting the vibration data into an acceleration displacement of a sprung mass of a vibration model;
An index conversion unit that converts acceleration displacement of the sprung mass into the index;
A second storage unit that stores the index and the position data in association with each other,
The vibration data converter is
A conversion parameter for converting the vibration data into an acceleration displacement of a sprung mass is preset for each of the plurality of measurement conditions, the conversion parameter corresponding to the received measurement condition is selected, and the selected conversion parameter is used. A computer which converts the vibration data into an acceleration displacement of a sprung mass.

20, 80 Processor 21, 803 Memory 22 Storage device 201 Database 202 Input / output device 206 IRI converter 207 Data input unit 208 Vibration data converter 209 IRI converter 300 Road surface 500 IRI
600 Vibration data 610 Position data 800 Vehicle 801 Acceleration sensor 802 GPS receiver 804 Data output unit 810, 820, 830 Measurement device 900 Measurement condition input unit 901 Display 2000 Road surface inspection system

Claims (15)

A road surface inspection system for measuring an index indicating the degree of unevenness of a road surface,
A measuring device detachable from the vehicle;
A computer that reads vibration data, position data, and measurement conditions acquired by the measurement device, and calculates an index indicating the degree of unevenness on the road surface,
The measuring device is
A measurement condition input unit for acquiring measurement conditions;
A vibration measurement unit for measuring vibration data;
A position measuring unit for measuring vehicle position data;
A first storage unit that stores the measurement conditions, the vibration data, and the position data;
The calculator is
A processor;
A second storage unit;
A data input unit for receiving the measurement conditions, the vibration data, and the position data stored in the first storage unit;
A vibration data converter for converting the vibration data into an acceleration displacement of a sprung mass of a vibration model;
An index conversion unit that converts acceleration displacement of the sprung mass into the index;
A second storage unit that stores the index and the position data in association with each other,
The vibration data converter is
A conversion parameter for converting the vibration data into an acceleration displacement of a sprung mass is preset for each of the plurality of measurement conditions, the conversion parameter corresponding to the received measurement condition is selected, and the selected conversion parameter is used. A road surface inspection system, wherein the vibration data is converted into an acceleration displacement of a sprung mass. The road surface inspection system according to claim 1,
The measuring device is
Vibration data measured by running the vehicle on a road surface with a known road surface profile is obtained for each of a plurality of measurement conditions,
The vibration data converter is
A road surface inspection system that generates and holds conversion parameters corresponding to each measurement condition from the vibration data acquired for each of the plurality of measurement conditions. The road surface inspection system according to claim 1,
The calculator is
A road surface inspection system that compares the index with a predetermined reference value and determines that repair is necessary on the road surface of the position data corresponding to the index when the index is equal to or greater than the reference value. . The road surface inspection system according to claim 1,
The measurement condition input unit
The measurement conditions include at least one of the installation position of the measurement device, the installation state of the measurement device, vehicle weight, axle weight, wheel weight, tire weight, suspension weight, suspension damping rate and spring constant, and vehicle traveling speed. A road surface inspection system characterized by selecting one. The road surface inspection system according to claim 1,
The measuring device is
A direction measuring unit that measures the direction of a predetermined axis of the measuring device;
The measurement conditions are:
Including the installation state of the measuring device;
The measurement condition input unit
The road surface inspection system, wherein the direction of the axis measured by the direction measuring unit is set as the installation state. The road surface inspection system according to claim 1,
The measurement conditions are:
Including the installation position of the measuring device;
The measurement condition input unit
A first frequency response when traveling on a specific road surface is set in advance for each of the plurality of installation positions,
After the measurement device is installed in the vehicle, vibration data is acquired when traveling on the specific road surface, a second frequency response is calculated from the vibration data, and the second frequency response corresponding to the second frequency response is obtained. A road surface inspection system including a measurement condition estimation unit that estimates an installation position of the measurement apparatus from the frequency response of 1 and sets the measurement apparatus as the installation position. The road surface inspection system according to claim 1,
The vehicle is
A wireless communication device;
The measurement conditions are:
Including the installation position of the measuring device;
The measuring device is
Including a wireless device for measuring the intensity of a transmission radio wave of the wireless communication device,
The measurement condition input unit
For each of the plurality of installation positions, the intensity measured by the wireless device is set in advance as a first intensity, and when the predetermined timing is reached, the second intensity is measured by the wireless device, A road surface inspection system including a measurement condition estimating unit that estimates an installation position of the measurement apparatus from the first intensity corresponding to a second intensity and sets the measurement apparatus as the installation position. The road surface inspection system according to claim 1,
The calculator is
The index, the position data, and the measured date and time are associated with each other and stored in the second storage unit, the index is acquired for specific position data, and a predetermined future time is determined from the time-series change of the acquired index. Road surface inspection system characterized by estimating date and time indicators. A road surface inspection method for measuring an index indicating the degree of unevenness of a road surface,
A first step in which a measurement device installed in the vehicle detachably acquires measurement conditions and stores the measurement conditions in a first storage unit;
The measurement device measures vibration data of the vehicle while traveling by a vibration measurement unit, measures position data of the vehicle by a position measurement unit, and stores the vibration data and position data in the first storage unit. A second step;
A computer comprising a processor and a second storage unit for calculating the index, a third step of receiving the measurement conditions, the vibration data and the position data stored in the first storage unit;
A fourth step in which the calculator converts the vibration data into an acceleration displacement of a sprung mass of a vibration model;
A fifth step in which the calculator converts acceleration displacement of the sprung mass into the index;
A sixth step in which the calculator stores the index and the position data in association with each other in a second storage unit;
The fourth step includes
A conversion parameter for converting the vibration data into an acceleration displacement of a sprung mass is preset for each of the plurality of measurement conditions, the conversion parameter corresponding to the received measurement condition is selected, and the selected conversion parameter is used. A road surface inspection method, wherein the vibration data is converted into acceleration displacement of a sprung mass. The road surface inspection method according to claim 9,
The conversion parameter is:
Vibration data measured by the measurement device while traveling on a road surface with a known road surface profile is acquired for each of a plurality of measurement conditions, and the vibration data is acquired from the measurement device for each of the plurality of measurement conditions. A road surface inspection method characterized in that a conversion parameter corresponding to each measurement condition is generated and set in advance. The road surface inspection method according to claim 9,
A seventh step in which the computer compares the index with a predetermined reference value, and determines that repair is necessary on the road surface of the position data corresponding to the index when the index is equal to or greater than the reference value; The road surface inspection method characterized by further including. The road surface inspection method according to claim 9,
The first step includes
The measurement conditions include at least one of the installation position of the measurement device, the installation state of the measurement device, vehicle weight, axle weight, wheel weight, tire weight, suspension weight, suspension damping rate and spring constant, and vehicle traveling speed. A road surface inspection method characterized by selecting one. The road surface inspection method according to claim 9,
The measuring device further includes a direction measuring unit that measures a direction of a predetermined axis of the measuring device,
The measurement conditions include an installation state of the measurement device,
The first step includes
A road surface inspection method, wherein the direction of the axis measured by the direction measuring unit is set as the installation state. The road surface inspection method according to claim 9,
The measurement condition includes an installation position of the measurement device,
The first step includes
A first frequency response when traveling on a specific road surface is set in advance for each of the plurality of installation positions, and vibration is generated when traveling on the specific road surface after the measurement device is installed in a vehicle. Data is acquired, a second frequency response is calculated from the vibration data, an installation position of the measurement device is estimated from the first frequency response corresponding to the second frequency response, and set as the installation position A road surface inspection method characterized by that. The road surface inspection method according to claim 9,
The vehicle has a wireless communication device,
The measurement condition includes an installation position of the measurement device,
The measurement apparatus includes a wireless device that measures the intensity of a transmission radio wave of the wireless communication apparatus,
The first step includes
For each of the plurality of installation positions, the intensity measured by the wireless device is set in advance as a first intensity, and when the predetermined timing is reached, the second intensity is measured by the wireless device, A road surface inspection method, wherein an installation position of the measuring device is estimated from the first intensity corresponding to a second intensity and set as the installation position.

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