How to determine road surface conditions

Abstract

To provide a determination method of a road surface condition which easily sets a threshold value and accurately determines the road surface condition.SOLUTION: A determination method of road surface condition on which a vehicle travels comprises the steps of: acquiring rotational speeds of installed tires on the vehicle in order; acquiring drive forces thereof for the vehicle in order; calculating slip ratio based on the rotational speeds of the tires acquired in order; calculating a regression equation and a reliable width regarding the relation between the slip ratio and the drive forces based on a lot of pieces of data set of the slip ratio and the drive forces in a prescribed section; and determining the road surface condition on which the vehicle travels based on the reliable width calculated in the prescribed section.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a method, an apparatus, and a program for determining the condition of a road surface on which a vehicle is traveling. [Background technology]

[0002] Patent Document 1 discloses a device for determining the condition of the road surface on which a vehicle is traveling. In Patent Document 1, a linear regression coefficient K1 of the slip ratio to the vehicle acceleration and a linear regression coefficient K2 of the vehicle acceleration to the slip ratio are calculated from data on the slip ratio calculated from the average wheel speed of the driving wheels and the vehicle speed, and the acceleration of the vehicle. The slip ratio and acceleration data used at this time are data acquired when the turning radius of the vehicle is larger than a predetermined value. Then, when the correlation coefficient obtained by multiplying these coefficients is equal to or larger than a predetermined threshold value, the value of the regression coefficient K1 is updated, and it is determined whether the road surface is slippery or not based on the value of the regression coefficient K1. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2002-362345 A Summary of the Invention [Problem to be solved by the invention]

[0004] In the device disclosed in Patent Document 1, when the turning radius of the vehicle is larger than a predetermined value while the vehicle is traveling, it is necessary to first store the regression coefficient when the correlation coefficient is equal to or greater than the predetermined value. That is, in the device disclosed in Patent Document 1, as long as the vehicle travels under conditions where the correlation coefficient does not become a predetermined value, it is not possible to obtain an appropriate regression coefficient K1 for determining the state of the road surface. In other words, when the state of the road surface on which the vehicle travels changes one after another from the start of the vehicle's travel and the data varies, it is possible that the state of the road surface cannot be determined because the regression coefficient K1 for determining the state of the road surface cannot be obtained.

[0005] An object of the present invention is to provide a determination method, device, and program that are capable of determining the state of a road surface without acquiring threshold values ​​of parameters for determination while the vehicle is traveling. [Means for solving the problem]

[0006] A determination method according to a first aspect of the present invention is a method for determining a condition of a road surface on which a vehicle is traveling, and includes the following. - Sequentially acquiring the rotational speeds of the tires mounted on the vehicle. - Sequentially obtaining the driving force of said vehicle. Calculating a slip ratio based on the rotational speeds of the tires that are sequentially acquired. Calculating a regression equation and a confidence interval for the relationship between the slip ratio and the driving force based on multiple data sets of the slip ratio and the driving force in a predetermined section. Determining the condition of the road surface on which the vehicle is traveling based on the confidence width calculated for the specified section.

[0007] A determination method according to a second aspect of the present invention is the determination method according to the first aspect, in which calculating the confidence width includes calculating confidence widths for a plurality of vehicles in the predetermined section, and determining the road surface condition includes determining that the road surface is in a slippery state when an average value of the confidence widths calculated in the predetermined section is equal to or greater than a predetermined threshold.

[0008] A determination method according to a third aspect of the present invention is the determination method according to the first or second aspect, wherein calculating the confidence width includes calculating confidence widths for a plurality of vehicles in the predetermined section, and determining the road surface condition includes determining that the road surface is in a slippery state when a variance of the confidence widths calculated in the predetermined section is equal to or greater than a predetermined threshold.

[0009] A determination method according to a fourth aspect of the present invention is a determination method according to any one of the first to third aspects, further comprising performing filtering to remove measurement errors between the slip ratio and the driving force before calculating a regression equation and a confidence width for the relationship between the slip ratio and the driving force.

[0010] A determination device according to a fifth aspect of the present invention is a device for determining the condition of a road surface on which a vehicle travels, and includes a rotational speed acquisition unit, a driving force acquisition unit, a slip ratio calculation unit, a confidence width calculation unit, and a determination unit. The rotational speed acquisition unit sequentially acquires the rotational speeds of tires mounted on the vehicle. The driving force acquisition unit sequentially acquires the driving force of the vehicle. The slip ratio calculation unit calculates a slip ratio based on the rotational information speeds of the tires that are sequentially acquired. The confidence width calculation unit calculates a regression equation and confidence width that express a relationship between the slip ratio and the driving force, based on multiple data sets of the slip ratio and the driving force in a predetermined section. The determination unit determines the condition of the road surface based on the confidence width calculated for the predetermined section.

[0011] A determination program according to a sixth aspect of the present invention is a determination program for determining a state of a road surface on which a vehicle is traveling, and causes a computer to execute the following. - Sequentially acquiring the rotational speeds of the tires mounted on the vehicle. - Sequentially obtaining the driving force of said vehicle. Calculating a slip ratio based on the rotational speeds of the tires that are sequentially acquired. Calculating a regression equation and a confidence interval for the relationship between the slip ratio and the driving force based on a large number of data sets of the slip ratio and the driving force in a predetermined section. Determining the condition of the road surface on which the vehicle is traveling based on the confidence width calculated for the specified section. Effect of the Invention

[0012] It is known that the regression analysis of the driving force and the slip ratio is stable on a non-slip road surface and unstable on a slippery road surface. The present invention utilizes this property to determine the road surface condition. Therefore, even if data that allows stable regression analysis cannot be obtained from the beginning of the vehicle's travel, the road surface condition can be determined. [Brief description of the drawings]

[0013] [Figure 1] 1 is a schematic diagram showing a state in which a control unit serving as a determination device according to the present embodiment is mounted on a vehicle; [Diagram 2] FIG. 2 is a block diagram showing an electrical configuration of a control unit according to the embodiment. [Diagram 3] 5 is a flowchart showing a flow of a process for determining a road surface condition according to the embodiment. [Figure 4A] FIG. 13 is a diagram for explaining a calculation process of a confidence width. [Figure 4B] FIG. 13 is a diagram for explaining a calculation process of a confidence width. [Diagram 5] FIG. 11 is a block diagram showing an electrical configuration of a road surface condition determination system according to a modified example. [Figure 6] Graph showing the experimental results. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0014] DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, a determination device, a method, and a program according to an embodiment of the present invention will be described with reference to the drawings.

[0015] <1. Configuration of the determination device> FIG. 1 is a schematic diagram showing a state in which a control unit 2 as a determination device according to this embodiment is mounted on a vehicle 1. The vehicle 1 is a four-wheel vehicle, and has a left front wheel FL, a right front wheel FR, a left rear wheel RL, and a right rear wheel RR. Each of the wheels FL, FR, RL, and RR is provided with a tire T FL ,T FR ,T RL ,T RR The vehicle 1 according to this embodiment is a front-engine, front-drive vehicle (FF vehicle), and has front tires T FL,T FR are the driving wheel tires, and the rear wheel tires T RL ,T RR are the driven wheel tires.

[0016] The control unit 2 detects the tire T FL ,T FR ,T RL ,T RR Based on the information on the rotation speed of the tire T FL ,T FR ,T RL ,T RR The slip ratio S, which indicates the tendency of the tire T to slip, is calculated, and the condition of the road surface on which the vehicle 1 is traveling is judged based on the confidence interval of the regression analysis of the slip ratio S and the driving force F. FL ,T FR ,T RL ,T RR The purpose of the present invention is to determine whether a road surface is slippery or not. An example of a slippery road surface is dry asphalt, and an example of a slippery road surface is frozen road surface, snowy road surface, wet road surface, etc. Information on the road surface condition can be applied to various uses, for example, various controls for controlling the running of a vehicle, and the creation of a road map of the road surface condition, etc. Examples of various controls for controlling the running of a vehicle include warning the driver about hydroplaning, control of the brake system, control of the distance between vehicles, etc.

[0017] Vehicle 1 tire T FL ,T FR ,T RL ,T RR (More precisely, each of the wheels FL, FR, RL, and RR) is fitted with a wheel speed sensor 6, which detects the rotational speeds (i.e., wheel speeds) V1 to V4 of the tires attached to the wheel to which the wheel speed sensor 6 is fitted. FL ,T FR ,T RL ,T RRThe wheel speed sensor 6 may be any type capable of detecting the wheel speeds of the wheels FL, FR, RL, and RR during running. For example, a sensor of a type that measures the wheel speed from the output signal of an electromagnetic pickup may be used, or a sensor of a type that generates electricity using the rotation like a dynamo and measures the wheel speed from the voltage generated. The mounting position of the wheel speed sensor 6 is not particularly limited, and may be appropriately selected according to the type of sensor as long as the wheel speed can be detected. The wheel speed sensor 6 is connected to the control unit 2 via a communication line 5. Information on the rotation speeds V1 to V4 detected by the wheel speed sensor 6 is transmitted to the control unit 2 in real time.

[0018] Further, the vehicle 1 is fitted with a wheel torque sensor 4 (hereinafter also simply referred to as torque sensor 4) that detects a wheel torque WT of the vehicle 1. The structure and mounting position of the torque sensor 4 are not particularly limited as long as it can detect the acceleration α of the vehicle 1. The torque sensor 4 is connected to the control unit 2 via a communication line 5. Information on the wheel torque WT detected by the torque sensor 4 is transmitted to the control unit 2 in real time, similar to information on the rotational speeds V1 to V4.

[0019] FIG. 2 is a block diagram showing an electrical configuration of the control unit 2. The control unit 2 is mounted on the vehicle 1, and includes an I / O interface 11, a CPU 12, a ROM 13, a RAM 14, and a non-volatile rewritable storage device 15, as shown in FIG. 2. The I / O interface 11 is a communication device for communicating with external devices such as the wheel speed sensor 6, the acceleration sensor 7, and the display device 3. The ROM 13 stores a program 9 for controlling the operation of each part of the vehicle 1. The CPU 12 reads out and executes the program 9 from the ROM 13, thereby virtually operating as a rotation speed acquisition unit 21, a driving force acquisition unit 22, a slip ratio calculation unit 23, a confidence width calculation unit 24, and a determination unit 25. The operation of each part 21 to 25 will be described in detail later. The storage device 15 is composed of a hard disk, a flash memory, or the like. The program 9 may be stored in the storage device 15 instead of the ROM 13. The RAM 14 and the storage device 15 are used as appropriate for the calculations of the CPU 12.

[0020] The display 3 can output various information including warnings to a user (mainly the driver) and can be realized in any form, for example, a liquid crystal display element, a liquid crystal monitor, a plasma display, an organic EL display, etc. The mounting position of the display 3 can be appropriately selected, but it is preferable to provide it in a position that is easy for the driver to see, for example, on an instrument panel. When the control unit 2 is connected to a car navigation system, it is also possible to use a monitor for the car navigation as the display 3. When a monitor is used as the display 3, the warning can be an icon or text information displayed on the monitor.

[0021] <2. Determining road surface conditions> Referring to Figure 3, the tire T FL ,T FR ,T RL ,T RRThe following describes a determination process for determining the condition of the road surface on which the vehicle 1 is traveling, based on a regression analysis of the slip ratio S and the driving force F of the vehicle 1. This determination process is executed while the electric system of the vehicle 1 is powered on.

[0022] In step S1, the rotation speed acquisition unit 21 acquires the rotation speed of the tire T FL ,T FR ,T RL ,T RR The rotation speed acquisition unit 21 receives output signals from the wheel speed sensors 6 at a predetermined sampling period, and converts these into rotation speeds V1 to V4.

[0023] In step S2, the driving force acquisition unit 22 acquires the driving force F of the vehicle 1. The driving force acquisition unit 22 first receives an output signal from the torque sensor 4 at a predetermined sampling period, and converts it into a wheel torque WT.

[0024] In step S3, the slip ratio calculation unit 23 judges whether the data of the rotation speeds V1 to V4 and the wheel torque WT are valid for judging the road surface condition. This is a step in which the acquired data is judged to be invalid when there is a possibility that the accuracy of the judgment of the road surface condition is adversely affected, and the acquired data is judged to be valid in other cases. An example of a case in which the accuracy of the judgment of the road surface condition is likely to be adversely affected is when the brakes of the vehicle 1 are operating. The slip ratio calculation unit 23 can judge whether the brakes are operating based on an output signal from a brake control system, for example. If the slip ratio calculation unit 23 judges that the data is valid, the process proceeds to step S4. On the other hand, if the slip ratio calculation unit 23 judges that the data is invalid, the data of the rotation speeds V1 to V4 and the wheel torque WT thus far is discarded, and the process returns to step S1.

[0025] In step S4, the driving force acquisition unit 22 calculates the driving force F of the vehicle 1 from the converted wheel torque WT. FL,T FR ,T RL ,T RR It can be calculated by dividing by the radius of the

[0026] In the next step S5, the slip ratio calculation unit 23 calculates the slip ratio S based on the rotation speeds V1 to V4. In this embodiment, the slip ratio S is calculated as (speed of driving wheels-vehicle body speed) / vehicle body speed, and the speed of the driven wheels is used as the vehicle body speed. In this embodiment, the slip ratio S is defined as follows. S = {(V1 + V2) - (V3 + V4)} / (V3 + V4)

[0027] After steps S4 and S5 have been executed and before the next process is executed, the driving force F calculated in step S4 and the slip ratio S calculated in step S5 may be filtered to remove measurement errors.

[0028] The data of the rotation speeds V1 to V4, the wheel torque WT, the slip ratio S, and the driving force F acquired in steps S1 to S5 which are executed successively are treated as a data set acquired at the same time or approximately the same time, and are stored in the RAM 14 or the storage device 15. In step S6, the confidence width calculation unit 24 judges whether or not a data set for a predetermined section has been stored in the RAM 14 or the storage device 15. Here, the predetermined section is a section divided every predetermined distance L, and the confidence width calculation unit 24 judges whether or not a data set for the distance L traveled by the vehicle 1 has been accumulated in the RAM 14 or the storage device 15. The distance traveled by the vehicle 1 may be derived from the rotation speeds V3 and V4, or may be derived from a positioning signal such as a Global Positioning System (GPS) received by a car navigation system or the like mounted on the vehicle 1.

[0029] When it is determined that the vehicle 1 has traveled a further distance L since it was determined that a data set for the predetermined section was last accumulated, the confidence width calculation unit 24 determines that the latest data set for the predetermined section has been stored in the RAM 14 or the storage device 15. In this case, the process proceeds to step S7. On the other hand, when it is determined that the distance traveled by the vehicle 1 is less than distance L since it was determined that a data set for the predetermined section was last accumulated, the confidence width calculation unit 24 determines that the latest data set for the predetermined section stored in the RAM 14 or the storage device 15 is insufficient, and the process returns to step S1.

[0030] In step S7, the confidence width calculation unit 24 calculates the regression equation and confidence width Y of the driving force F and the slip ratio S based on multiple data sets of the driving force F and the slip ratio S for a predetermined section. The multiple data sets of the driving force F and the slip ratio S are multiple data sets of the slip ratio S and the driving force F at the present time when the road surface condition is judged and a period prior to that time. Hereinafter, the number of multiple data sets for the predetermined section is represented by N. The confidence width calculation unit 24 first calculates regression coefficients a and b that specify the regression equation of the data sets of the driving force F and the slip ratio S for the predetermined section, assuming that the driving force F and the slip ratio S are in a linear relationship represented by the following formula (1). a is the slope of the slip ratio S with respect to the driving force F, and b is the intercept of the slip ratio S with respect to the driving force F. The regression coefficients a and b can be calculated, for example, by a method such as the least squares method. S=aF+b (1)

[0031] The confidence interval calculation unit 24 calculates the confidence interval Y according to the following procedure. The confidence interval Y in this embodiment represents the width of the confidence interval for the distribution of the residual of the regression equation obtained, and is used as an index reflecting the stability of the regression analysis, as described later. First, the driving force F n (n=1,2,…,N) are substituted into the above equation (1) to obtain the driving force F n Predicted slip ratio S for (aF n Next, the slip ratio S included in the N data sets is calculated in sequence (see FIG. 4A). nThe difference between the calculated N slip ratios S and the predicted value, i.e., the residual e n (n=1,2,…,N) are calculated (see Figure 4B). n is {S n -(aF n + b)} and is assumed to follow a normal distribution. Next, the residual e n Variance of s 2 Calculate the following: ave is the residual e n Represents the average of.

number

number

[0032] The reason why the confidence width calculation unit 24 calculates the confidence width Y is as follows. FL ,TFR ,T RL ,T RR When the vehicle 1 is traveling on a road surface that is not slippery (such a road surface is also called a high μ road), the variation in the slip ratio S with respect to the driving force F is small. Therefore, the regression analysis based on the data set of the driving force F and the slip ratio S is stable, and the confidence interval Y is relatively small. In contrast, when the vehicle 1 is traveling on a road surface that is not slippery (such a road surface is also called a high μ road), the variation in the slip ratio S with respect to the driving force F is small. FL ,T FR ,T RL ,T RR When a vehicle travels on a slippery road surface (such road surfaces are also called low μ roads), the variation in the slip ratio S relative to the driving force F becomes large. For this reason, regression analysis based on a data set of the driving force F and the slip ratio S is not stable, and the confidence interval Y becomes relatively large. Experiments described later in the examples support the above, and it was found that a clear difference appears in the confidence interval Y between high μ roads and low μ roads. For this reason, it is easy to set a judgment threshold for the road surface condition, and improved judgment accuracy is also expected.

[0033] Incidentally, in order to accurately calculate the regression coefficient of the formula (1), it is desirable that the variation of the data set of the slip ratio S and the driving force F is equal to or greater than a certain value. However, in a period in which the driving force F does not change much, such as a period in which the vehicle is traveling at a constant speed downhill, the data set does not show much variation. In step S8, the confidence width calculation unit 24 judges whether the variation of the driving force F included in the data set in the predetermined section is equal to or greater than a certain value. In other words, the confidence width calculation unit 24 judges whether the multiple data sets of the driving force F and the slip ratio S for the predetermined section are suitable for calculating the confidence width Y. In this embodiment, the width and variance of the multiple values ​​of the driving force F acquired while the vehicle 1 travels a predetermined distance L are calculated, and if these are equal to or greater than a predetermined threshold, it is determined that the variation is equal to or greater than a certain value, and the process proceeds to step S9.

[0034] On the other hand, if at least one of the range and variance of the values ​​of the multiple driving forces F is smaller than a predetermined threshold, it is determined that the variation is not equal to or greater than a certain value, and the data set of the driving forces F acquired in that section and the slip ratio S corresponding to that driving force F are discarded. Additionally, the data sets of the wheel torque WT used to calculate the driving force F and the rotational speeds V1 to V4 used to calculate the slip ratio S are also discarded, and may be erased from the RAM 14 or the storage device 15. After that, the process returns to step S1.

[0035] The determination in step S8 described above may be performed before step S7, rather than after step S7. In other words, as long as the data of the driving force F for a predetermined section is obtained, the timing of determining whether the variation in the driving force F is equal to or greater than a certain value is not particularly limited, and the determination whether the variation in the driving force F is equal to or greater than a certain value may be performed before the regression coefficients a and b are calculated.

[0036] In step S9, the determination unit 25 compares the confidence width Y calculated in step S8 with a predetermined threshold. If the confidence width Y is equal to or greater than the predetermined threshold, the process proceeds to step S10, where the determination unit 25 determines that the road surface is slippery. When the process proceeds to step S10, the determination unit 25 may be configured to generate an alarm signal and cause the display device 3 to display an alarm indicating that the road surface is slippery. On the other hand, if the confidence width Y is less than the predetermined threshold, the process proceeds to step S11, where the road surface is determined to be non-slip. Here, the predetermined threshold in step S9 may be a value calculated in advance by experiment or simulation and stored in the storage device 15 or ROM 13.

[0037] After step S10 or step S11, the process proceeds to step S12, where the determination unit 25 determines whether or not the vehicle 1 has stopped traveling. If it is determined that the vehicle 1 has not stopped traveling and is continuing to travel, the process returns to step S1, and the same procedure is repeated. On the other hand, if it is determined that the vehicle 1 has stopped traveling, the process ends.

[0038] <3. Modifications> Although one embodiment of the present invention has been described above, the present invention is not limited to the above embodiment, and various modifications are possible without departing from the spirit of the present invention. For example, the following modifications are possible. In addition, the gist of the following modifications can be combined as appropriate.

[0039] <3-1> The function of determining the road surface condition using the confidence interval of the regression analysis of the slip ratio S and the driving force F according to the above embodiment can be applied to rear-wheel drive vehicles and also to four-wheel drive vehicles. Furthermore, this function is not limited to four-wheel vehicles, but can also be applied appropriately to three-wheel vehicles or six-wheel vehicles.

[0040] <3-2> The method of acquiring the driving force F is not limited to the one described in the above embodiment. For example, if an acceleration sensor is attached to the vehicle 1, the output value of the acceleration sensor can be used as the driving force F. In addition, the driving force F can be derived from the engine torque and engine speed acquired from the control device of the engine of the vehicle 1, or can be derived from the tire rotation speeds V1 to V4.

[0041] <3-3> The method of calculating the slip ratio S is not limited to the one described in the above embodiment. For example, when the slip ratio S is defined as (speed of driving wheels-vehicle speed) / vehicle speed, the slip ratio S may be calculated by taking the vehicle speed as an integrated value of the acceleration α acquired by an acceleration sensor. Also, for example, the vehicle speed may be acquired from a satellite positioning system such as a GPS that is connected to the vehicle 1 via communication.

[0042] <3-4> The order in which steps S1 to S12 in Fig. 3 are performed is not limited to the order in the above embodiment, and may be partially changed. For example, step S1 may be performed after step S2, or steps S1 and S2 may be performed simultaneously in parallel. Similarly, step S4 may be performed after step S5, or steps S4 and S5 may be performed simultaneously in parallel. Similarly, step S7 may be performed after step S8.

[0043] <3-5> The confidence interval Y calculated in step S7 is not limited to that in the above embodiment. The confidence interval Y may be an index that reflects the stability of the regression analysis and becomes smaller as the regression analysis becomes more stable and becomes larger as the regression analysis becomes more unstable, and may be, for example, the width of the confidence interval and the width of the prediction interval of the regression line for a predetermined driving force F. The width of the confidence interval is the width of the α% confidence interval and can be calculated by the following formula. Note that α can be appropriately selected, for example, 0.95.

number

number

[0044] Moreover, the width of the α % prediction interval for a given driving force F can be calculated by the following formula: Here, α can be appropriately selected, for example, 0.95.

number

[0045] As described above, on high μ roads, the variation in slip ratio S relative to driving force F is small, and regression analysis based on the data set of driving force F and slip ratio S is stable. As a result, the width of the confidence interval and the width of the prediction interval of the regression interval tend to be small on high μ roads. On the other hand, on low μ roads, the variation in slip ratio S relative to driving force F is large, and regression analysis based on the data set of driving force F and slip ratio S becomes unstable. As a result, the width of the confidence interval and the width of the prediction interval of the regression interval tend to be large on low μ roads. Therefore, the width of the confidence interval and the width of the prediction interval of the regression interval can be calculated as the confidence width Y, and it can be determined whether the road surface is a high μ road or a low μ road.

[0046] Furthermore, the confidence width Y may be the width of the confidence interval for at least one of the probability distributions followed by the estimates of the regression coefficients a and b.

[0047] <3-6> The road surface can be determined not only by comparing the confidence width Y with a predetermined threshold value, but also by comparing the variance or average value of the confidence width Y with a predetermined threshold value. In this case, the confidence width calculation unit 24 may be configured to calculate at least one of the variance and average value of the confidence width Y calculated for a plurality of predetermined driving forces F. The determination unit 25 may also be configured to determine the state of the road surface by comparing at least one of the variance and average value of the calculated confidence width Y with a predetermined threshold value previously stored in the storage device 15 or ROM 13. If the road surface is a low μ road, the variance and average value of the confidence width Y are each equal to or greater than the predetermined threshold value, and if the road surface is a high μ road, the variance and average value of the confidence width Y are each less than the predetermined threshold value. <3-7> The method according to the embodiment is executed by one determination device (control unit) 2. However, the method according to the embodiment may be executed by a system 100 including a plurality of determination devices 2 mounted on a plurality of vehicles 1, and a server device 101. FIG. 5 is a block diagram showing an electrical configuration of the system 100 for determining the state of a road surface. Each of the determination devices 2 is communicatively connected to a satellite positioning system such as a GPS, and is also communicatively connected to the server device 101. The server device 101 is, for example, a general-purpose computer as hardware, and includes an I / O interface 110, a CPU 120, a ROM 130, a RAM 140, and a non-volatile rewritable storage device 150. The I / O interface 110 is a communication device for communicating with an external device such as the determination device 2. The ROM 130 stores a program 90 for providing a cloud service to the determination device 2. The CPU 120 reads out and executes the program 90 from the ROM 130, thereby virtually operating as a database (DB) creation unit 210, a statistical processing unit 220, a determination unit 230, and an information providing unit 240.

[0048] In the system 100, the determination device 2 is configured to transmit the reliability width Y calculated by the method according to the above embodiment to the server device 101 together with the positioning signal of the satellite positioning system. The DB creation unit 210 of the server device 101 saves the reliability width Y transmitted from each determination device 2 in the storage device 150 or the RAM 140. The storage device 150 stores road map data in advance. The DB creation unit 210 creates a database by associating the reliability width Y with sections on the road map based on the positioning signal of the satellite positioning system transmitted from the determination device 2.

[0049] When a predetermined number of data are accumulated in the database, the statistical processing unit 220 of the server device 101 calculates at least one of the variance and the average value of the confidence width Y in the same section on the road map. The determination unit 230 compares the variance of the confidence width Y with a predetermined threshold, and if the variance is equal to or greater than the predetermined threshold, determines that the section has a slippery road surface, and if the variance is less than the predetermined threshold, determines that the section has a non-slippery road surface. Alternatively, the determination unit 230 compares the average value of the confidence width Y with a predetermined threshold, and if the average value is equal to or greater than the predetermined threshold, determines that the section has a slippery road surface, and if the variance is less than the predetermined threshold, determines that the section has a non-slippery road surface. The predetermined threshold may be a value that is determined in advance by experiments using one or more types of vehicles 1 and stored in the ROM 130 or the storage device 150. The determination result by the determination unit 230 may be associated with the section on the road map and further stored in the storage device 150 or overwritten.

[0050] The fact that the regression analysis of the driving force F and the slip ratio S is stable on high μ roads and unstable on low μ roads is considered to show a similar tendency even if the type of vehicle 1 and the tires mounted thereon are different. Therefore, by evaluating at least one of the variance and the average value of the confidence width Y of multiple vehicles 1 in the same section, a more versatile road surface judgment can be performed. In addition, the server device 101 can also monitor changes in the road surface condition over time in a specified section by updating the judgment result by the judgment unit 230 associated with the section on the road map at a specified time interval.

[0051] The information providing unit 240 can provide the determination device 2 with information indicating the road surface condition of the section in which the vehicle 1 equipped with the determination device 2 is traveling or a section in the vicinity of the section. The determination device 2 may be configured to access the server device 101 and acquire information on the road surface condition for the section in which the vehicle 1 is currently traveling when the determination device 2 is unable to determine the road surface condition by itself for some reason. Examples of such cases include a case where valid data of the rotation speeds V1 to V4 or the wheel torque WT cannot be acquired for a certain period of time or more, a case where a data set for a predetermined section has not been sufficiently accumulated, and a case where the variation in the acquired driving force F is insufficient. In this way, in the system 100, even when the individual determination device 2 itself cannot determine the road surface condition, the determination result of the road surface condition can be seamlessly acquired by using the information accumulated in the server device 101. EXAMPLES

[0052] <Experiment> A vehicle was driven round trip on a test course with a mixture of slippery and non-slippery road surfaces, and the confidence interval was calculated for each 50 m section according to the method of the above embodiment. The vehicle was an RX200t, and the tires mounted on the vehicle were 235 / 55R20 DUNLOP SPORT MAXX 050. The test course (owned by the Japan Automobile Research Institute, a general incorporated foundation) was a roughly flat straight road with dry asphalt (high μ road) from the start of the run (0 m) to 850 m, an artificial low μ road from 850 m to 1050 m, and dry asphalt from 1050 m to 1350 m. The vehicle made four round trips around the test course, turning back and forth between the 0 m point and the 1350 m point at various vehicle speeds.

[0053] <Result> The results are shown in the graph in Figure 6. The horizontal axis of the graph is the distance from the starting point of the journey, and the vertical axis is the average confidence width for four round trips in each section. As can be seen from the graph, the average confidence width is large in the artificial low μ road section (850m - 1050m), while the average confidence width is small in the dry asphalt sections (0m - 850m, 1050m - 1350m), and the two are clearly distinguishable. This demonstrates that the method of determining road surface conditions using the confidence width in the regression analysis of slip ratio S and driving force F is effective. [Explanation of symbols]

[0054] 1 vehicle 2 Control unit (judgment device) 3 Display 4 Wheel Torque Sensor 6 Wheel Speed ​​Sensor 9. Program 21 Rotational speed acquisition unit 22 Driving force acquisition unit 23 Slip ratio calculation section 24 Confidence Range Calculation Section 25 Judgment section FL left front wheel FR right front wheel RL Left rear wheel RR Right rear wheel V1~V4 Tire rotation speed

Claims

1. A method for determining a state of a road surface on which a vehicle is traveling, comprising: Sequentially acquiring rotational speeds of tires mounted on the vehicle; Sequentially acquiring driving forces of the vehicle; Calculating a slip ratio based on the rotational speeds of the tires that are sequentially acquired; Calculating a regression equation and a confidence width for the relationship between the slip ratio and the driving force based on multiple data sets of the slip ratio and the driving force in a predetermined section; determining a condition of a road surface on which the vehicle is traveling based on the confidence width calculated for the predetermined section; Including, Judgment method.

2. calculating the confidence width includes calculating a confidence width for a plurality of vehicles in the predetermined section; determining the road surface condition includes determining that the road surface is slippery when at least one of an average value and a variance of the confidence width calculated in the predetermined section is equal to or greater than a predetermined threshold value; The method according to claim 1 .

3. The method further includes performing filtering to remove measurement errors between the slip ratio and the driving force before calculating a regression equation and a confidence width for the relationship between the slip ratio and the driving force. The method for determining whether or not a substance is oxidized according to claim 1 .

4. A determination device for determining a state of a road surface on which a vehicle is traveling, comprising: A rotation speed acquisition unit that sequentially acquires the rotation speeds of tires mounted on the vehicle; a driving force acquisition unit that sequentially acquires driving forces of the vehicle; a slip ratio calculation unit that calculates a slip ratio based on the rotational speeds of the tires that are sequentially acquired; a confidence width calculation unit that calculates a regression equation and a confidence width that represent a relationship between the slip ratio and the driving force based on a large number of data sets of the slip ratio and the driving force in a predetermined section; a determination unit that determines a state of the road surface based on the confidence width calculated for the predetermined section; Equipped with Judgment device.

5. A determination program for determining a state of a road surface on which a vehicle is traveling, Sequentially acquiring rotational speeds of tires mounted on a vehicle; Sequentially acquiring driving forces of the vehicle; Calculating a slip ratio based on the rotational speeds of the tires that are sequentially acquired; Calculating a regression equation and a confidence width for the relationship between the slip ratio and the driving force based on multiple data sets of the slip ratio and the driving force in a predetermined section; determining a condition of a road surface on which the vehicle is traveling based on the confidence width calculated for the predetermined section; to cause a computer to execute Judging program.

Images