Method and related system for estimating an international roughness index of a road segment

Abstract

The present invention relates to a method for estimating an international roughness index (IRI) of a road or road segment, said method comprising a preliminary step (1) and an international roughness index estimation step (10). The preliminary step (1) comprises: collecting (2) values of the vehicle tire damping and stiffness coefficients (C t , K t ); and collecting (3): vehicle vertical acceleration values (Az vehicle ) measured on a vehicle driven at a constant speed along a road segment associated with a known international roughness index value or a known road profile r , as well as vehicle georeferencing data and speed data indicative of a given constant speed associated with the measured vertical acceleration values (Az vehicle ).

Description

Technical Field

[0001] This invention generally relates to the field of automotive and road surface monitoring. More specifically, the invention relates to systems and methods for estimating the International Roughness Index (IRI). In particular, according to aspects of the invention, the IRI is estimated based on physical quantities related to the motion of the vehicle (e.g., vertical acceleration) and to the vehicle itself (e.g., the damping coefficients and stiffness coefficients of the vehicle's suspension and the tires mounted on the vehicle).

[0002] This invention can be applied to any type of road vehicle used for transporting people, such as cars, buses, campervans, etc., or for transporting goods, such as industrial vehicles (trucks, tractor-trailers, etc.) or light or medium-sized commercial vehicles (such as vans, etc.). Without loss of generality, reference will be made to motorized vehicles equipped with internal combustion engines and / or hybrid and / or (one or more) electric types, such as one or more cars and / or buses and / or trucks and / or motorcycles. Background Technology

[0003] As is well known, road surfaces need to be designed to ensure that the rolling surface is substantially regular and has minimal deformation to meet the safety and comfort requirements of motor vehicles driven on road surfaces. Indeed, impacts of a motor vehicle's wheels against obstacles on the road surface (such as potholes or bumps) can damage the tires, particularly the tire carcass (i.e., the shell). For example, an external bulge on the tire sidewall typically indicates that the cords inside the tire carcass have ruptured due to impact relative to or on an obstacle, as driving on objects such as bumps and potholes can cause individual cord ruptures. If a damaged tire (e.g., a tire with some damaged cords) is not detected in time and therefore not repaired / replaced promptly, there is a risk that if the driver continues to drive with the damaged tire (e.g., in the event of further impacts of the damaged tire relative to or on other obstacles), the tire carcass may completely rupture / break down, or even damage the rim and / or suspension.

[0004] Currently, the regularity / smoothness level of individual roads is periodically monitored, primarily for the purpose of planning maintenance works. Typically, this monitoring is based on calculations of the International Roughness Index (IRI), which is the most commonly used roughness index for road surface irregularities. The IRI is typically obtained by measuring longitudinal road profiles (more specifically, longitudinal sections of road surface elevation), particularly using either a quarter-car mathematical model (also known as a quarter-car model, abbreviated as QCM) or a full-car mathematical model (also known as a full-car model, abbreviated as FCM). The responses of these models are accumulated to produce a roughness index in units of gradient (in / m, m / km, etc.).

[0005] Unfortunately, IRI measurements are actually quite expensive and difficult to implement on a large scale across an entire road network managed by a company.

[0006] Therefore, in the fields of automotive and road surface monitoring, there is a significant need for innovative technological solutions to enable faster and easier detection of road surface irregularities / unevenness.

[0007] For example, patent application WO 2020 / 225699 A1 discloses examples of known solutions, wherein the patent application discloses a method and system for identifying irregularities in road surface. Specifically, WO 2020 / 225699 A1 relates to a method comprising:

[0008] a) Preliminary testing steps, including the following in sequence:

[0009] - Sub-step, in which the test is performed by driving the pneumatic tire through and / or colliding with different irregular objects at different speeds of the motor vehicle;

[0010] - Sub-step, wherein vertical acceleration is acquired during the test (conveniently at a sampling rate of at least 10Hz); and

[0011] - A sub-step for constructing at least one first model to correlate the standard deviation of vertical acceleration associated with the test performed with irregularities on the road surface; and

[0012] b) The actual identification steps include, in sequence:

[0013] - Sub-step, in which vertical acceleration is obtained (conveniently at a sampling rate of at least 10Hz);

[0014] - Sub-step, wherein high-pass filtering of vertical acceleration is implemented, wherein the minimum filtering threshold of the high-pass filter is preferably less than or equal to 0.1 Hz, and wherein the filtering sub-step is performed on a reference segment of a road surface of variable length between 2 and 25 meters (preferably between 5 and 10 meters);

[0015] - Sub-step, in which vertical acceleration is processed by Fast Fourier Transform (FFT);

[0016] - Sub-step, wherein the standard deviation of the processed vertical acceleration is calculated by FFT at the relevant frequencies, wherein the relevant frequencies include the vibration frequencies of the motor vehicle suspension system preferably in a first range between 1.5 Hz and 3 Hz; and

[0017] - Identify the presence and size of irregularities on the road surface by comparing the first model with the standard deviation of the vertical acceleration processed by FFT at the relevant frequency.

[0018] According to WO 2020 / 225699 A1, the relevant frequencies conveniently include the second range of vibration frequencies of the vehicle chassis, step b) conveniently includes the further sub-step of acquiring information related to the vehicle's location via GPS signals and locating arbitrary irregularities based on the vehicle's location, and step a) conveniently includes the further sub-steps of: conducting tests by driving through and / or impacting different types of tires on different types of motor vehicles, and constructing multiple models to correlate the standard deviation of vertical acceleration with the type of tires and / or motor vehicle.

[0019] Furthermore, according to WO 2020 / 225699 A1, step a) preferably also includes:

[0020] - Sub-step, wherein, during the test, wheel speed and vehicle speed are acquired, and wherein a normalized wheel speed associated with the test is calculated by the ratio between the wheel speed and the corresponding speed of the vehicle; and

[0021] - Sub-step, which is used to construct at least one second model for correlating the standard deviation of normalized wheel speed with irregularities on the road surface.

[0022] Finally, according to WO 2020 / 225699 A1, step b) preferably includes:

[0023] - Sub-step, wherein the steering angle of the wheels of the motorized vehicle is obtained;

[0024] - Sub-step, wherein the steering angle of the wheels of the motorized vehicle is obtained by FFT;

[0025] - Sub-step, in which a minimum threshold is determined within the frequency content of the steering angle of the wheel processed by FFT;

[0026] - Sub-step, where the wheel speed is obtained;

[0027] - Sub-step, in which the rate of the motorized vehicle is obtained;

[0028] - Sub-step, where the normalized wheel rate is calculated by the ratio between the wheel rate and the corresponding rate of the motor vehicle;

[0029] - Sub-step, wherein a high-pass filter is performed on the wheel rate or normalized wheel rate when the minimum threshold is applied; and

[0030] - Sub-step, in which the standard deviation of the normalized wheel rate is calculated;

[0031] The sub-step for identifying the presence of irregularities on the road surface conveniently means comparing the standard deviation of the vertical acceleration processed by FFT at the relevant frequency using the first model, and comparing the standard deviation of the normalized wheel rate using the second model. Summary of the Invention

[0032] In view of the foregoing, the applicant felt the need to conduct in-depth research in an attempt to develop innovative technical solutions for achieving generally faster and easier quantification of road surface roughness, particularly IRI-like estimation, which is easier to perform and can be executed more frequently than conventional IRI measurements, thereby realizing the present invention.

[0033] Therefore, the object of the present invention is to provide a technical solution for achieving generally faster and easier quantification of road surface roughness, particularly IRI-like estimation, which is easier to perform and can be executed more frequently than conventional IRI measurements.

[0034] The reason for achieving this and other objectives through this invention is that it relates to systems and methods for estimating IRI. Attached Figure Description

[0035] To better understand the invention, preferred embodiments, which are used purely as non-limiting examples, will now be described with reference to the accompanying drawings (all not to scale), in which:

[0036] • Figure 1 and Figure 2 The preliminary steps and the IRI estimation steps of the IRI estimation method according to a preferred embodiment of the present invention are illustrated schematically.

[0037] • Figure 3 The steps for determining the preliminary parameters for a vehicle are illustrated schematically.

[0038] • Figure 4 The trend of vertical acceleration values ​​is schematically shown according to different road profiles;

[0039] • Figure 5 The steps for the preliminary process of validating parameters for a vehicle are illustrated schematically.

[0040] • Figure 6 A diagram illustrating the correlation between the root mean square values ​​of vertical acceleration of each vehicle obtained from actual data and digital road profiles is shown.

[0041] • Figure 7 A graph schematically illustrates the correlation between IRI values ​​and the root mean square values ​​of the vehicle's vertical acceleration at different constant vehicle speeds; and

[0042] • Figures 8-10 A preferred embodiment of the IRI estimation system is illustrated schematically. Detailed Implementation

[0043] The invention will now be described in detail with reference to the accompanying drawings to enable those skilled in the art to make and use it. Various modifications to the described embodiments will be readily apparent to those skilled in the art, and the general principles described can be applied to other embodiments and applications without departing from the scope of the invention. Therefore, the invention should not be considered limited to the embodiments described and illustrated herein, but should be given the broadest scope of protection consistent with the described and claimed features.

[0044] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly used by one of ordinary experience in the field related to this invention. In the event of any conflict, this specification (including the definitions provided) shall be binding. Furthermore, the examples provided are for illustrative purposes only and should not be considered restrictive.

[0045] In particular, the block diagrams included in the accompanying drawings and described below are not intended as representations of structural characteristics or construction limitations, but must be interpreted as representations of functional characteristics (i.e., inherent properties of the device), and are defined by the effects or functional limitations obtained, and can be implemented in different ways to protect the same function (the possibility of function).

[0046] To facilitate understanding of the embodiments described herein, reference will be made to specific embodiments, and specific language will be used to describe these embodiments. The terminology used herein is for the purpose of describing specific embodiments only and is not intended to limit the scope of the invention.

[0047] The present invention relates to a method for estimating the International Roughness Index (IRI), particularly based on physical quantities related to the motion of the vehicle (e.g., vertical acceleration) and the damping and stiffness coefficients of the vehicle itself (e.g., the suspension of the vehicle and the tires mounted on the vehicle).

[0048] refer to Figure 1 and Figure 2 The method according to the invention includes a preliminary step 1 and an IRI estimation step 10. Furthermore, the following will refer to motorized vehicles equipped with internal combustion engines and / or hybrid and / or (one or more) electric types of internal combustion engines, such as one or more cars and / or buses and / or trucks and / or motorcycles, etc.

[0049] In particular, Figure 1 The preliminary step 1 of the method for estimating IRI according to the present invention is illustrated schematically. Specifically, the preliminary step 1 includes:

[0050] - Collect (box 2) the vehicle tire damping coefficient C of one or more tires (not shown) of one or more motorized vehicles. t and stiffness coefficient K t The value;

[0051] - Collection (box 3):

[0052] a) Vertical acceleration value Az of the first vehicle vehicle It is along the known international roughness index value or the known first road profile. r Measurements taken on one or more motor vehicles traveling at one or more given constant speeds on one or more roads or road segments associated with the vehicle.

[0053] b) Geographic reference data of the first vehicle, which is compared with the measured first vertical acceleration value Az vehicle Related; and

[0054] (c) First vehicle speed data, which indicates the measured first vertical acceleration value Az vehicle Associated (one or more) given constant rates; and

[0055] - Based on the vehicle tire damping coefficient C t and stiffness coefficient K tThe first value, the georeferenced data of the first vehicle, the velocity data of the first vehicle, and the vertical acceleration value Az of the first vehicle vehicle Determine (box 4) the second road profile d ,

[0056] Preliminary step 1 also includes:

[0057] - Based on the second road profile d The second vertical acceleration value Az output The second vehicle georeferenced data, indication, and measured first vertical acceleration value Az of -f(c, k) vehicle Associated (one or more) second vehicle speed data at a given constant rate and vehicle tire damping coefficient C t and stiffness coefficient K t The value determines (box 5) the vertical acceleration value Az of the second vehicle. output -f(c, k);

[0058] - Determine (Box 6) the vehicle suspension damping coefficient C of one or more suspensions of one or more vehicles. s and stiffness coefficient K s The value;

[0059] - Determine the vertical acceleration value Az of the first vehicle (box 7) respectively. vehicle The first root mean square value and the second vehicle vertical acceleration value Az output The second root mean square value of -f(c, k); and

[0060] - Based on known international roughness index values ​​or first road profile r Based on the vertical acceleration value Az of the second vehicle output The second root mean square value of -f(c, k), based on the georeferenced data of the second vehicle, and based on the rate data of the second vehicle, are used to determine (Box 8) the mathematical value of the vertical acceleration Az of the second vehicle at (one or more) a given constant rate. output One or more vehicle transfer functions associated with the second root mean square value of -f(c, k) and the international roughness index value.

[0061] Figure 2 An IRI estimation step 10 of the method for estimating IRI according to the present invention is illustrated schematically. Specifically, the IRI estimation step 10 includes:

[0062] - Obtain (box 11) the vertical acceleration value Az of a third vehicle measured on a given motor vehicle driving at a given driving speed on a given road or road segment, the georeferenced data of the third vehicle associated with the vertical acceleration value Az of the third vehicle, and the third vehicle speed data indicating the given driving speed of the motor vehicle.

[0063] - Calculate (box 12) the third root mean square value of the vertical acceleration Az of the third vehicle; and

[0064] - Estimate the International Roughness Index (IRI) value for a given road or road segment based on one or more vehicle transfer functions determined in preliminary step 1, the third root mean square value based on the third vehicle vertical acceleration value Az, and the associated third vehicle georeference data and third vehicle rate data (Box 13).

[0065] According to an aspect of the invention, the third vehicle georeference data for a given mobile vehicle is data indicating the 2D / 3D location (e.g., GPS location) of the given mobile vehicle.

[0066] According to an aspect of the invention, in steps a), b), and c), for a given vehicle type and / or a given vehicle model, along the international roughness index value or the first road profile... r One or more motorized vehicles traveling at one or more given constant speeds on one or more roads or road segments are known. The vertical acceleration value Az of the first vehicle is collected. vehicle Geographic reference data and speed data of the first vehicle; in addition, a second road profile. d It is specific to the given vehicle type and / or model.

[0067] According to another aspect of the invention, in steps a), b), and c), for each of one or more mobile vehicles of different given vehicle types and / or different given vehicle models, the vertical acceleration value Az of the first vehicle is collected. vehicle Geographic reference data and speed data of the first vehicle; in addition, a second road profile. d It is specific to each of the given vehicle type and / or model.

[0068] Therefore, according to an aspect of the invention, the international roughness index value is estimated (box 13) by using a vehicle transfer function specific to a given motor vehicle type / model, determined in preliminary step 1.

[0069] Refer again Figure 1 In preliminary step 1, for example, the vehicle tire damping coefficient C t and stiffness coefficient K t It is determined through tire testing (such as a dedicated deflection test).

[0070] Furthermore, according to an aspect of the invention, the vertical acceleration value Az of the first vehicle is collected (box 3). vehicle The steps of acquiring georeferenced data and velocity data for the first vehicle include acquiring telemetry data of the vehicle, wherein the vehicle is conveniently equipped with a data logger unit that acquires the vertical acceleration value Az of the first vehicle at a predetermined acquisition frequency. vehicle The first vehicle's georeferenced data includes its GPS location and the vehicle's georeferenced location. Furthermore, telemetry data is automatically transmitted to a remote computing system (e.g., a cloud computing system) via a wireless connection (e.g., based on 2G, 3G, 4G, or 5G cellular technology). Specifically, the georeferenced data for the first vehicle is acquired at a frequency greater than, for example, 1 Hz. Additionally, to determine the vertical acceleration value Az of the first vehicle... vehicle The vehicle drives at low speeds (e.g., up to 40 km / h) through known geometries (i.e., according to, for example, a first road profile). r The bulge; more specifically, the vertical acceleration value Az of the first vehicle. vehicle The acquisition frequency is higher than or equal to 10 Hz. Furthermore, a predetermined time period (e.g., three months) for acquiring vehicle telemetry data can be conveniently considered, wherein the predetermined time period preferably includes the measurement date of the IRI value.

[0071] According to an aspect of the invention, in preliminary step 1, this is based on the corresponding first road profile. r Determine the road-related IRI value, first road profile r It is determined according to standardized procedures; for example, the first road profile. r This was determined by interpolating previously measured vertical acceleration values ​​in the first road profile. r It is determined based on certain conditions specific to the type / model of the vehicle for a given motorized vehicle (e.g., low speed and at a predetermined acquisition frequency).

[0072] According to another aspect of the invention, GPS is used to locate vehicles on roads, wherein measurements are performed in preliminary step 1 and IRI estimation step 10.

[0073] refer to Figure 1In preliminary step 1, the vertical acceleration value Az of the second vehicle is determined (box 5). output The steps of -f(c, k) include determining:

[0074] - Vertical acceleration value Az of the fourth vehicle output It is when the input is the vehicle tire damping coefficient C t and stiffness coefficient K t The value is obtained through the second road profile. d The output acceleration value; and

[0075] - The vertical acceleration function of the vehicle is f(c, k), which depends on the parameters c and k.

[0076] Specifically, parameters c and k are the damping and stiffness coefficients of one or more suspensions (not shown) of the vehicle under consideration. Therefore, the second road profile... d The output (which is the value of the vehicle's vertical acceleration) depends directly on the values ​​of the vehicle suspension damping coefficient c and stiffness coefficient k of one or more suspensions of the motorized vehicle under consideration.

[0077] refer to Figure 3 Determine (Box 6) the vehicle suspension damping coefficient C of one or more suspensions of one or more vehicles. s and stiffness coefficient K s The steps to obtain the value include:

[0078] - For the second road profile d The input values ​​of the vehicle suspension damping coefficient c0 and stiffness coefficient k0 are used to determine the corresponding second vehicle vertical acceleration value Az (box 21). output -f(c, k) (also known as Az) output -f(c0, k0)); and

[0079] - Verify (box 22) the vertical acceleration value Az from the second vehicle. output Does the second acceleration distribution generated by -f(c0, k0) correlate with the vertical acceleration value Az from the first vehicle? vehicle The generated first acceleration distribution is fitted.

[0080] In addition, determine (Box 6) the vehicle suspension damping coefficient C of one or more suspensions of one or more vehicles. s and stiffness coefficient K s The steps for determining the value also include:

[0081] - If the vertical acceleration value Az from the second vehicle output The second acceleration distribution generated by -f(c0, k0) is related to the vertical acceleration value Az from the first vehicle. vehicle If the generated first acceleration distribution is fitted, then (box 23) is determined as the test vehicle suspension damping coefficient value c0 and stiffness coefficient value k0, which are the vehicle suspension damping coefficient C. s and stiffness coefficient K s ;or

[0082] - If the vertical acceleration value Az from the second vehicle output The second acceleration distribution generated by -f(c0, k0) is related to the vertical acceleration value Az from the first vehicle. vehicle If the generated first acceleration distribution does not fit, then determine (Box 24) new values ​​for the suspension damping coefficient c0 and stiffness coefficient k0 of the test vehicle.

[0083] Therefore, according to an aspect of the invention, the steps of determining (box 21) and verifying (box 22) are repeated until the test vehicle suspension damping coefficient value c0 and stiffness coefficient value k0 meet the requirements of the verification (box 22) step, and thus can be defined as the vehicle suspension damping coefficient C. s and stiffness coefficient K s .

[0084] At the end of step (box 6), the vehicle suspension damping coefficient C of one or more suspensions of one or more vehicles is determined. s and stiffness coefficient K s The value is determined as the second road profile. d The output of .

[0085] Figure 4 The vertical acceleration value Az from the first vehicle is schematically shown. vehicle The vertical acceleration value Az of the second vehicle output Examples of the first and second acceleration distributions generated by -f(c, k), where c and k are equal to the vehicle suspension damping coefficient C. s and stiffness coefficient value K s .

[0086] In addition, refer to Figure 5 In preliminary step 1, the vertical acceleration value Az of the first vehicle is determined (box 7). vehicle The first root mean square value and the second vehicle vertical acceleration value Az output The steps for obtaining the second root mean square value of -f(c, k) include:

[0087] - Based on the first road profile r Furthermore, for motorized vehicles traveling at known speeds on known roads, calculate (box 31) the vertical acceleration value Az of the first vehicle. vehicle The first root mean square value;

[0088] - Based on the second road profile d The damping coefficient C of the vehicle suspension s and stiffness coefficient value K s Furthermore, for motorized vehicles traveling at the same known speeds but different speeds on the same known road, determine (box 32) the vertical acceleration value Az of the second vehicle. output The second root mean square value of -f(c, k); and

[0089] -Vertical acceleration value Az relative to the second vehicle output -f(c, k) (also referred to below as Az) output -f(C s K s The second root mean square value is used to plot (box 33) the vertical acceleration value Az of the first vehicle. vehicle The first root mean square value is used to verify the second road profile. d Is the fit good enough to match the first road profile? r The result.

[0090] Specifically, by the vertical acceleration value Az relative to the second vehicle output -f(C s K s The second RMSVA, together with the known IRI values ​​of the road under consideration, plots the first vehicle's vertical acceleration value Az. vehicle The first RMSVA is used to perform the drawing (box 33) step. Figure 6 The graph obtained by drawing (box 33) is shown, where the vertical acceleration value Az relative to the second vehicle is represented. output -f(C s K s The second RMSVA, plotted with the first vehicle's vertical acceleration value Az filtered at 1.5Hz. vehicle The first RMSVA is used to perform the drawing (box 33) step. For example... Figure 6 As can be seen, different speeds have been taken into account.

[0091] Furthermore, in preliminary step 1, based on known international roughness index values ​​or the first road profile... r Based on the vertical acceleration value Az of the second vehicle outputThe second root mean square value of -f(c, k), based on the georeferenced data of the second vehicle and the speed data of the second vehicle, determines (Box 8) the mathematical value of the vertical acceleration Az of the second vehicle at (one or more) a given constant speed. output One or more vehicle transfer functions associated with the second root mean square value of -f(c, k) and the International Roughness Index (IRI) value include: identifying the IRI value and the second vehicle vertical acceleration value Az. output -f(C s K s The mathematical correlation between the second RMSVA and the vehicle transfer function is used to determine the vehicle transfer function. .in this regard, Figure 7 It shows the different constant vehicle speeds. The example figure shows the IRI values ​​at different constant vehicle speeds, and also shows the vertical acceleration value Az from the second vehicle. output -f(C s K s The second RMSVA is determined; in particular, Figure 7 The following is an example of a transfer function:

[0092]

[0093] Where v represents the vehicle speed.

[0094] Refer again Figure 2 In IRI estimation step 10, and regarding the third vehicle's vertical acceleration value Az, the following steps are performed by inverse calculation: estimating the International Roughness Index (IRI) value for a given road or road segment based on one or more vehicle transfer functions determined in preliminary step 1, and based on the third root mean square value of the third vehicle's vertical acceleration value Az and associated third vehicle georeferenced data and third vehicle rate data (box 13). In fact, once at least one transfer function is determined in preliminary step 1, the third root mean square value determined from the third vehicle's vertical acceleration value Az, and the driving speed v of the given vehicle on a general road are known, the estimated IRI value can be calculated.

[0095] The present invention also relates to a system designed for performing the above-described IRI estimation method. In this respect, Figure 8 The functional architecture of the IRI estimation system 50 according to a preferred embodiment of the present invention is illustrated schematically by means of a block diagram.

[0096] Specifically, the IRI estimation system 50 includes an acquisition device 51, which:

[0097] - Onboard a motor vehicle equipped with an internal combustion engine or a hybrid / electric type internal combustion engine (such as a car, bus, truck, or motorcycle). Figure 8 (not shown in the middle) Above;

[0098] - A vehicle bus 60 coupled to the motorized vehicle (e.g., based on a standard Controller Area Network (CAN) bus); and

[0099] - Configured to acquire vehicle vertical acceleration, vehicle georeference, and rate data from the vehicle bus 60.

[0100] According to a preferred embodiment of the present invention, the corresponding acquisition device 51 is installed in:

[0101] - On each mobile vehicle used to perform preliminary step 1, to obtain the first vehicle vertical acceleration value Az from the corresponding vehicle bus 60 of the mobile vehicle. vehicle The vertical acceleration value Az of the second vehicle output -f(c, k) and the first vehicle georeference and the second vehicle georeference, as well as the first vehicle rate data and the second vehicle rate data; and

[0102] - In IRI estimation step 10, for each given mobile vehicle, the third vehicle vertical acceleration value Az and the third vehicle georeference and rate data are obtained from the corresponding vehicle bus 60 of the given mobile vehicle.

[0103] In addition, the IRI estimation system 50 also includes a processing unit 52, which is connected, via wired or wireless means, to (one or more) an acquisition device 51 to receive the first vehicle vertical acceleration value Az from the acquisition device 51. vehicle The vertical acceleration value Az of the second vehicle output -f(c, k) and the vertical acceleration value Az of the third vehicle, as well as the geographic references of the first, second, and third vehicles, and the rate data of the first, second, and third vehicles, and the processing unit 52 is programmed to:

[0104] - Calculate the first root mean square value and the second root mean square value Az vehicle Az output -f(c, k), and determine (box 8) (one or more) vehicle transfer functions; and

[0105] - Calculate the third root mean square value and estimate (one or more) IRI values ​​(Box 13).

[0106] Figure 9 and Figure 10 The schematic illustration illustrates the method used to implement Figure 8 A further preferred embodiment of the processing component 52 of the system 50.

[0107] Specifically, refer to Figure 9 In the first preferred embodiment (represented generally as 70), the processing unit 52 is implemented / executed by a cloud computing system 72, which (e.g., via one or more cellular technologies such as GSM, GPRS, EDGE, HSPA, UMTS, LTE, LTE Advanced, 5G, etc.) is wirelessly and remotely connected to (one or more) the acquisition device 51 and conveniently used to perform both the preliminary step 1 and the IRI estimation step 10.

[0108] Alternatively, refer to Figure 10 In the second preferred embodiment (generally indicated by 100), the processing unit 52 is implemented / executed by an (automotive) electronic control unit (ECU) 102 mounted on the motor vehicle 110, wherein the ECU 102 may conveniently be an ECU dedicated to IRI estimation or an ECU dedicated to several tasks that also include IRI estimation.

[0109] Preferably, the cloud computing system 72 is used to perform the preliminary step 1, while the ECU 102 is used to perform the IRI estimation step 10. In particular, each ECU 102 can be conveniently mounted on each given mobile vehicle 110 involved in the IRI estimation step 10 to acquire the vertical acceleration value of the second vehicle and the georeference and rate data of the second vehicle from the corresponding acquisition device 51.

[0110] In summary, the technical advantages and innovative features of this invention are quite obvious to those skilled in the art.

[0111] In particular, this method enables the measurement of preliminary IRI values ​​on a driving road at a higher frequency than the normal methods used in road surveying, by utilizing the vehicle's vertical acceleration value at a given constant rate.

[0112] Furthermore, this method features a wider and more widespread measurement network, which will allow road management companies to prioritize more accurate measurements on specific road sections.

[0113] Furthermore, this method enables faster and easier quantification of road surface roughness, particularly IRI-like estimation, which is easier to perform and can be executed more frequently than traditional IRI measurements.

[0114] In summary, it is evident that numerous modifications and variations can be made to this invention, all of which fall within the scope of this invention.

Claims

1. A method for estimating the international roughness index of a road, the method comprising a preliminary step and an international roughness index estimation step; The preliminary steps include: Collect the values ​​of the vehicle tire damping coefficient and stiffness coefficient for one or more tires of one or more motorized vehicles; collect: a) The vertical acceleration value of the first vehicle is measured on one or more motor vehicles traveling at one or more given constant speeds along one or more roads associated with known international roughness index values ​​or known first road profiles. b) Geographic reference data of the first vehicle, which is correlated with the measured first vertical acceleration value; as well as (c) First vehicle speed data, indicating one or more given constant speeds associated with a measured first vertical acceleration value; and The second road profile is determined based on the values ​​of the vehicle's tire damping coefficient and stiffness coefficient, the first vehicle's georeferenced data, the first vehicle's speed data, and the first vehicle's vertical acceleration value. The preliminary steps also include: The second vehicle vertical acceleration value is determined based on the second road profile, second vehicle georeference data of the second vehicle vertical acceleration value, second vehicle speed data indicating one or more given constant rates associated with the measured first vertical acceleration value, and the values ​​of the vehicle tire damping coefficient and stiffness coefficient. Determine the values ​​of the vehicle suspension damping coefficient and stiffness coefficient for one or more suspensions of one or more vehicles; Determine the first root mean square value of the vertical acceleration of the first vehicle and the second root mean square value of the vertical acceleration of the second vehicle, respectively; and Based on known international roughness index values ​​or the first road profile, based on the second root mean square value of the vertical acceleration of the second vehicle, based on georeferenced data of the second vehicle, and based on the speed data of the second vehicle, determine one or more vehicle transfer functions that mathematically correlate the second root mean square value of the vertical acceleration of the second vehicle with the international roughness index value at one or more given constant speeds; and The international roughness index estimation step includes: Acquire a third vehicle vertical acceleration value measured on a given motor vehicle driving at a given driving speed on a given road, third vehicle georeference data associated with the third vehicle vertical acceleration value, and third vehicle speed data indicating the given driving speed of the motor vehicle; Calculate the third root mean square value of the vertical acceleration of the third vehicle; and The international roughness index value of the given road is estimated based on one or more vehicle transfer functions determined in the preliminary steps, the third root mean square value based on the vertical acceleration value of the third vehicle, and the associated georeferenced data and velocity data of the third vehicle.

2. The method for estimating the international roughness index of roads according to claim 1, wherein, In steps a), b), and c), for one or more motorized vehicles of the same given vehicle type or model, traveling at one or more given constant speeds along one or more roads associated with known international roughness index values ​​or the first road profile, the vertical acceleration values ​​of the first vehicle, the georeferenced data of the first vehicle, and the speed data of the first vehicle are collected; and The second road profile is specific to the given vehicle type or model.

3. The method for estimating the international roughness index of roads according to claim 1, wherein, In steps a), b), and c), for one or more mobile vehicles of different given vehicle types or models, the vertical acceleration value of the first vehicle, the georeferenced data of the first vehicle, and the speed data of the first vehicle are collected respectively; and The second road profile is specific to each of the given vehicle types or models.

4. The method for estimating the international roughness index of roads according to claim 2 or 3, wherein, The international roughness index value is estimated by using the vehicle transfer function determined in the preliminary step, wherein the vehicle transfer function is specific to the vehicle type or model of the given motorized vehicle.

5. The method for estimating the international roughness index of roads according to any one of claims 1-3, wherein, The steps for determining the values ​​of the damping coefficient and stiffness coefficient of one or more suspensions for one or more vehicles include: Based on the test vehicle suspension damping coefficient and stiffness coefficient values ​​input in the second road profile, determine the corresponding vertical acceleration value of the second vehicle; and Verify whether the second acceleration distribution generated from the vertical acceleration value of the second vehicle matches the first acceleration distribution generated from the vertical acceleration value of the first vehicle; and The step of determining the values ​​of the vehicle suspension damping coefficient and stiffness coefficient for one or more suspensions of one or more vehicles further includes: If the second acceleration distribution generated from the vertical acceleration value of the second vehicle matches the first acceleration distribution generated from the vertical acceleration value of the first vehicle, then the test vehicle damping coefficient and stiffness coefficient values ​​of the vehicle suspension are determined to be the vehicle suspension damping coefficient and stiffness coefficient; or If the second acceleration distribution generated from the vertical acceleration value of the second vehicle does not fit the first acceleration distribution generated from the vertical acceleration value of the first vehicle, then new values ​​for the suspension damping coefficient and stiffness coefficient of the test vehicle are determined.

6. The method for estimating the international roughness index of roads according to any one of claims 1-3, wherein, The steps for determining the first root mean square value of the vertical acceleration of the first vehicle and the second root mean square value of the vertical acceleration of the second vehicle respectively include: Based on the first road profile and for motor vehicles driving at known speeds on known roads, calculate the first root mean square value of the vertical acceleration of the first vehicle. Based on the second road profile, the suspension damping coefficient and stiffness coefficient of the vehicle, and for motorized vehicles traveling at the same known speeds on the same known road, determine the second root mean square value of the vertical acceleration of the second vehicle; and The first root mean square value of the vertical acceleration of the first vehicle is plotted relative to the second root mean square value of the vertical acceleration of the second vehicle, thereby verifying whether the second road profile has fitted well enough to match the results of the first road profile.

7. A system for estimating international roughness indices, said system being designed to perform the method for estimating international roughness indices for roads according to any one of claims 1 to 6.

8. The system for estimating international roughness indices according to claim 7, For each mobile vehicle used to perform the preliminary step of the method for estimating the international roughness index of roads, the system includes a corresponding first acquisition device, the first acquisition device being: Installed on motorized vehicles, The corresponding vehicle bus coupled to the mobile vehicle, and Configured to acquire vehicle vertical acceleration, vehicle georeference data, and rate data from the corresponding vehicle bus; For each given motorized vehicle involved in the international roughness index estimation step of the method for estimating the international roughness index of roads, the system includes a corresponding second acquisition device, the second acquisition device being: Installed on the given motorized vehicle, The corresponding vehicle bus coupled to the given mobile vehicle, and Configured to acquire the vertical acceleration value of the third vehicle, as well as the georeferenced data and third rate data of the third vehicle, from the corresponding vehicle bus; and The system includes a processing unit connected to the first acquisition device and the second acquisition device to receive from the first acquisition device and the second acquisition device a first vehicle vertical acceleration value, a second vehicle vertical acceleration value, and a third vehicle vertical acceleration value, as well as first vehicle georeferenced data, second vehicle georeferenced data, and third vehicle georeferenced data, and first vehicle speed data, second vehicle speed data, and third vehicle speed data, and the processing unit is configured to: Calculate the first root mean square value and the second root mean square value and determine one or more of the vehicle transfer functions; and Calculate the third root mean square value and estimate one or more of the international roughness index values.

9. The system for estimating international roughness indices according to claim 8, wherein, The processing component includes a cloud computing system that is remotely connected to one or more of the acquisition devices and is used to perform both the preliminary step and the international roughness index estimation step.

10. The system for estimating international roughness indices according to claim 8, wherein, The processing component includes: A cloud computing system, remotely connected to one or more of the first acquisition devices and configured to perform the preliminary steps; and For each given mobile vehicle involved in the international roughness index estimation step, the processing unit includes a corresponding electronic control unit mounted on the given mobile vehicle, the electronic control unit being connected to a corresponding second acquisition device and configured to perform the international roughness index estimation step.

11. A cloud computing system configured to perform both the preliminary step and the international roughness index estimation step of the method for estimating the international roughness index of a road according to any one of claims 1 to 6, or only the preliminary step of the method for estimating the international roughness index.

12. An electronic control unit designed to be mounted on a motor vehicle and configured to perform the international roughness index estimation step of the method for estimating the international roughness index of a road according to any one of claims 1 to 6.

13. A computer program product comprising one or more software and / or firmware code portions, said software and / or firmware code portions: It can be loaded onto the processing unit; and When loaded, the processing unit is configured to perform the preliminary step and / or the international roughness index estimation step of the method for estimating the international roughness index of a road according to any one of claims 1 to 6.

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