Processing device, motorcycle, and processing method

Abstract

To provide a processing device which is mounted on a motorcycle and can reduce the cost of the motorcycle capable of determining the wetting of a road surface.SOLUTION: A processing device according to the present invention is mounted on a motorcycle. The processing device includes: an acquisition section for acquiring the traveling characteristic of the motorcycle on the basis of an output from an inertial measurement sensor used for the control of the behavior of the motorcycle; and a determination section for comparing the traveling characteristic acquired by the acquisition section and reference data to determine the wetting of a road surface.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a processing device mounted on a motorcycle, a motorcycle equipped with the processing device, and a processing method used on a motorcycle. [Background technology]

[0002] The behavior of a motorcycle while in motion is more susceptible to the influence of the road surface than is the case with other automobiles. For this reason, information on whether the road surface is wet or not is extremely useful for a motorcycle. For this reason, conventional motorcycles have been proposed that are equipped with a raindrop sensor that directly detects rain and determine whether the road surface is wet based on the output of the raindrop sensor (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2018-118569 Summary of the Invention [Problem to be solved by the invention]

[0004] Conventional motorcycles have had to be equipped with a raindrop sensor that directly detects rain to determine if the road surface is wet, which has led to the problem that conventional motorcycles capable of detecting wetness on the road are expensive.

[0005] The present invention has been made in light of the above-mentioned problems, and has an object to provide a processing device to be mounted on a motorcycle that can determine whether a road surface is wet, thereby reducing the cost of the motorcycle. Another object of the present invention is to provide a motorcycle equipped with such a processing device. Another object of the present invention is to provide a processing method for use on a motorcycle that can determine whether a road surface is wet, thereby reducing the cost of the motorcycle. [Means for solving the problem]

[0006] The processing device of the present invention is a processing device mounted on a motorcycle, and includes an acquisition unit that acquires the driving characteristics of the motorcycle based on the output of an inertial measurement sensor used to control the behavior of the motorcycle, and a determination unit that compares the driving characteristics acquired by the acquisition unit with reference data to determine whether the road surface is wet.

[0007] A motorcycle according to the present invention is equipped with the processing device according to the present invention.

[0008] Furthermore, the processing method according to the present invention is a processing method used for a motorcycle, and includes an acquisition step of acquiring the running characteristics of the motorcycle based on the output of an inertial measurement sensor used to control the behavior of the motorcycle, and a determination step of comparing the running characteristics acquired in the acquisition step with reference data to determine whether the road surface is wet. [Effects of the Invention]

[0009] Motorcycles whose behavior is controlled are equipped with inertial measurement sensors, and their behavior is controlled based on the output of the inertial measurement sensors. The present invention can determine whether a road surface is wet based on the output of the inertial measurement sensors used to control the behavior of the motorcycle. Therefore, by employing the present invention in motorcycles whose behavior is controlled, the cost of motorcycles that can determine whether a road surface is wet can be reduced. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a side view of a motorcycle according to an embodiment of the present invention. [Figure 2] 1 is a block diagram illustrating a processing device according to an embodiment of the present invention. [Figure 3] 10A and 10B are diagrams for explaining an example of a method for determining wetness of a road surface, which is performed by a determination unit of a processing device according to an embodiment of the present invention. [Figure 4] 10A and 10B are diagrams for explaining an example of a method for determining wetness of a road surface, which is performed by a determination unit of a processing device according to an embodiment of the present invention. [Figure 5] 10 is a diagram for explaining a suitable period when a determination unit of a processing device according to an embodiment of the present invention determines that a road surface is wet. FIG. [Figure 6] FIG. 4 is a diagram showing a control flow of an example of the operation of the processing device according to the embodiment of the present invention. [Figure 7] FIG. 10 is a block diagram showing a modified example of the processing device according to the embodiment of the present invention. [Figure 8] FIG. 10 is a block diagram showing another modified example of the processing device according to the embodiment of the present invention. [Figure 9] FIG. 9 is a side view of a motorcycle equipped with the processing device shown in FIG. 8. [Figure 10] FIG. 10 is a block diagram showing yet another modified example of the processing device according to the embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0011] The processing device, motorcycle, and processing method according to the present invention will be described below with reference to the drawings.

[0012] The configuration and operation described below are an example of the present invention, and the present invention is not limited to such configuration and operation.

[0013] For example, in the following, a motorcycle is exemplified as a motorcycle. However, a motorcycle is not limited to a motorcycle. A motorcycle refers to a two-wheeled or three-wheeled vehicle that is a straddle-type vehicle on which a rider sits astride. Motorcycles include motorcycles or three-wheeled vehicles that use an engine as a propulsion source, and motorcycles or three-wheeled vehicles that use a motor as a propulsion source, such as motorcycles, scooters, and electric scooters.

[0014] In the following, descriptions of identical or similar parts are appropriately simplified or omitted. In addition, in each drawing, reference numerals are omitted for identical or similar parts or components, or the same reference numerals are used. In addition, illustrations of detailed structures are appropriately simplified or omitted.

[0015] Embodiment The following describes a processing device according to an embodiment, a motorcycle equipped with the processing device, and a processing method according to an embodiment.

[0016] <Motorcycle and processing device configuration>

[0017] Fig. 1 is a side view of a motorcycle according to an embodiment of the present invention. The Z axis shown in Fig. 1 is an axis extending in the vertical direction of the body of the motorcycle 1. The X axis shown in Fig. 1 is an axis extending in the straight direction of the motorcycle 1. The Y axis shown in Fig. 1 is an axis perpendicular to the body of the motorcycle 1 and perpendicular to the X and Z axes.

[0018] The motorcycle 1 includes an inertial measurement sensor 2 and a processing device 10. In other words, the motorcycle 1 is equipped with an inertial measurement sensor 2 and a processing device 10.

[0019] The inertial measurement sensor 2 detects three-axial accelerations and three-axial (roll, pitch, and yaw) angular velocities occurring on the motorcycle 1. Specifically, the inertial measurement sensor 2 detects, for example, accelerations in the X-axis, Y-axis, and Z-axis directions. Furthermore, for example, the inertial measurement sensor 2 detects angular velocity around the X-axis as roll angular velocity, angular velocity around the Y-axis as pitch angular velocity, and angular velocity around the Z-axis as yaw angular velocity. The inertial measurement sensor 2 may also detect other physical quantities that can be substantially converted into three-axial accelerations and three-axial angular velocities occurring on the motorcycle 1. The inertial measurement sensor 2 may also detect some of the three-axial accelerations and three-axial angular velocities.

[0020] The inertial measurement sensor 2 is used to control the behavior of the motorcycle 1. In other words, the behavior of the motorcycle 1 is controlled by a control device (not shown) based on the output of the inertial measurement sensor 2. Various specific methods for controlling the behavior of a motorcycle have been proposed in the past. There are no particular limitations on the method for controlling the behavior of the motorcycle 1 by a control device (not shown), and various conventionally proposed methods can be used.

[0021] The processing device 10 determines whether the road surface is wet based on the output of the inertial measurement sensor 2. For example, part or all of the processing device 10 is configured with a microcomputer, a microprocessor unit, or the like. Also, for example, part or all of the processing device 10 may be configured with updatable components such as firmware, or may be a program module executed by commands from a CPU, or the like. The processing device 10 may be, for example, a single device or may be divided into multiple devices. Also, at least part of the processing device 10 may be integrated with at least part of the above-mentioned control device (not shown). The processing device 10 can be configured, for example, as follows.

[0022] FIG. 2 is a block diagram showing a processing device according to an embodiment of the present invention. The processing device 10 according to this embodiment includes an acquisition unit 11 and a determination unit 12 as functional units.

[0023] The acquisition unit 11 is a functional unit that acquires the riding characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2. The riding characteristics are vectors whose axes are at least one of the physical quantities (or physical quantities converted from the physical quantities) output from the inertial measurement sensor 2 and the Mahalanobis distance (described later). In other words, the riding characteristics can also be considered as coordinates on a graph whose axes are at least one of the physical quantities (or physical quantities converted from the physical quantities) output from the inertial measurement sensor 2 and the Mahalanobis distance (described later). Note that, hereinafter, a vector whose axis is at least one of the physical quantities (or physical quantities converted from the physical quantities) output from the inertial measurement sensor 2 is referred to as riding state information. Here, the physical quantities (or physical quantities converted from the physical quantities) output from the inertial measurement sensor 2 include the accelerations on three axes, the roll angular velocity, the roll angle (the integral of the roll angular velocity), the yaw angular velocity, the yaw angle (the integral of the yaw angular velocity), the pitch angular velocity, and the pitch angle (the integral of the pitch angular velocity). Of these physical quantities, physical quantities in the roll direction, such as the roll angular velocity and the roll angle, may hereinafter be collectively referred to as roll information. Also, of these physical quantities, physical quantities in the yaw direction, such as the yaw angular velocity and the yaw angle, may hereinafter be collectively referred to as yaw information. The acquisition unit 11 acquires, for example, values ​​of physical quantities that are axes of driving characteristics at a certain time. This allows the acquisition unit 11 to acquire driving characteristics at a certain time.

[0024] The determination unit 12 is a functional unit that compares the driving characteristics acquired by the acquisition unit 11 with reference data to determine whether the road surface is wet. The determination unit 12 determines whether the road surface is wet, for example, as follows.

[0025] 3 and 4 are diagrams for explaining an example of a method for determining whether a road surface is wet, which is performed by the determining unit of the processing device according to the embodiment of the present invention.

[0026] FIG. 3 shows the riding characteristics of the motorcycle 1 acquired by the acquisition unit 11, which are represented by vectors whose axis is one of the physical quantities x1 output from the inertial measurement sensor 2. The black squares in FIG. 3 represent the riding characteristics RQ of the motorcycle 1 at a given time. Because the riding characteristics RQ shown in FIG. 3 are vectors whose axis is the physical quantity output from the inertial measurement sensor 2, they can also be said to represent riding condition information of the motorcycle 1 at a given time. Here, FIG. 3 shows a reference sample group of vectors whose axis is the physical quantity x1, among the reference sample groups of riding condition information of the motorcycle 1. A reference sample group is a collection of multiple reference samples. A reference sample is riding condition information of the motorcycle 1 acquired when it is known whether the road surface is wet or not. The small black circles in FIG. 3 represent reference samples when the road surface is not wet. The black triangles in FIG. 3 represent reference samples when the road surface is wet.

[0027] The behavior of the motorcycle 1 differs depending on whether the road surface is wet. In other words, the physical quantities that indicate the riding state information of the motorcycle 1 also differ depending on whether the road surface is wet. For this reason, the area Ad where the reference sample group exists when the road surface is not wet and the area Aw where the reference sample group exists when the road surface is wet are located in different positions. Note that depending on the type of physical quantity, the areas Ad and Aw may partially overlap.

[0028] Therefore, for example, the determination unit 12 can determine whether the road surface is wet using the above-mentioned reference sample group as reference data, in other words, using the areas Ad and Aw as reference data. Specifically, suppose that the riding characteristics RQ of the motorcycle 1 at a certain time are in the area Ad. In this case, the determination unit 12 can determine that the road surface is not wet at the time when the riding characteristics RQ are acquired. Also, suppose that the riding characteristics RQ of the motorcycle 1 at a certain time are in the area Aw. In this case, the determination unit 12 can determine that the road surface is wet at the time when the riding characteristics RQ are acquired.

[0029] Furthermore, for example, the reference data may include a boundary B that separates the reference sample group when the road surface is not wet from the reference sample group when the road surface is wet. In other words, the reference data may include a boundary B that separates the riding characteristics of the motorcycle 1 when the road surface is not wet from the riding characteristics of the motorcycle 1 when the road surface is wet. The determination unit 12 may then determine whether the road surface is wet based on the boundary B. Specifically, it is assumed that the riding characteristics RQ of the motorcycle 1 at a certain time are on the side of the riding characteristics of the motorcycle 1 when the road surface is not wet, with the boundary B as the reference. In this case, the determination unit 12 can determine that the road surface is not wet at the certain time when the riding characteristics RQ are acquired. It is also assumed that the riding characteristics RQ of the motorcycle 1 at a certain time are on the side of the riding characteristics of the motorcycle 1 when the road surface is wet, with the boundary B as the reference. In this case, the determination unit 12 can determine that the road surface is wet at the certain time when the riding characteristics RQ are acquired. As shown in FIG. 3, when the acquisition unit 11 acquires the driving characteristics that are vectors with one physical quantity x1 as an axis, the boundary B becomes a boundary point.

[0030] FIG. 4 shows the riding characteristics of the motorcycle 1 acquired by the acquisition unit 11, which are represented by vectors whose axes are two of the physical quantities x1 and x2 output from the inertial measurement sensor 2. The black squares in FIG. 4 represent the riding characteristics RQ of the motorcycle 1 at a given time. Because the riding characteristics RQ shown in FIG. 4 are vectors whose axes are the physical quantities output from the inertial measurement sensor 2, they can also be said to represent riding state information of the motorcycle 1 at a given time. FIG. 4 also shows a group of reference samples of vectors whose axes are the physical quantities x1 and x2. The small black circles in FIG. 4 represent reference samples when the road surface is not wet. The black triangles in FIG. 4 represent reference samples when the road surface is wet.

[0031] Even when the acquisition unit 11 acquires driving characteristics that are vectors with two physical quantities x1 and x2 as axes, the determination unit 12 can compare the driving characteristics acquired by the acquisition unit 11 with reference data to determine whether the road surface is wet, as described above. For example, the determination unit 12 can determine whether the road surface is wet by using the reference sample group shown in FIG. 4 as reference data, in other words, the areas Ad and Aw shown in FIG. 4 as reference data. Specifically, assume that the driving characteristics RQ of the motorcycle 1 at a certain time are located in the area Ad. In this case, the determination unit 12 can determine that the road surface is not wet at the time when the driving characteristics RQ are acquired. Also assume that the driving characteristics RQ of the motorcycle 1 at a certain time are located in the area Aw. In this case, the determination unit 12 can determine that the road surface is wet at the time when the driving characteristics RQ are acquired.

[0032] Furthermore, even when the acquisition unit 11 acquires driving characteristics that are vectors with the two physical quantities x1 and x2 as their axes, the reference data may have a boundary B that separates a reference sample group when the road surface is dry from a reference sample group when the road surface is wet. In other words, the reference data may have a boundary B that separates the driving characteristics of the motorcycle 1 when the road surface is dry from the driving characteristics of the motorcycle 1 when the road surface is wet. Even when the acquisition unit 11 acquires driving characteristics that are vectors with the two physical quantities x1 and x2 as their axes, the determination unit 12 can determine whether the road surface is wet based on the boundary B, as described above.

[0033] Specifically, it is assumed that the riding characteristics RQ of the motorcycle 1 at a certain time are on the side of the riding characteristics of the motorcycle 1 when the road surface is not wet, with boundary B as the reference. In this case, the determination unit 12 can determine that the road surface is not wet at the time when the riding characteristics RQ are acquired. It is also assumed that the riding characteristics RQ of the motorcycle 1 at a certain time are on the side of the riding characteristics of the motorcycle 1 when the road surface is wet, with boundary B as the reference. In this case, the determination unit 12 can determine that the road surface is wet at the time when the riding characteristics RQ are acquired. Note that, as shown in FIG. 4, when the acquisition unit 11 acquires riding characteristics that are vectors with two physical quantities x1 and x2 as their axes, boundary B becomes a boundary line. This boundary line may be a straight line or a line other than a straight line (such as a curve or a broken line).

[0034] 3 and 4, the reference sample group when the road surface is dry and the reference sample group when the road surface is wet do not overlap. However, even if the reference sample group when the road surface is dry and the reference sample group when the road surface is wet overlap, it is possible to set boundary B in the reference data using a method such as a support vector machine.

[0035] 3 and 4, the method for determining whether the road surface is wet by the determination unit 12 has been described using an example of driving characteristics that are vectors with two or less physical quantities as axes. However, the acquisition unit 11 may acquire driving characteristics that are vectors with three or more physical quantities as axes. Then, the determination unit 12 may determine whether the road surface is wet, for example, as described above, based on the driving characteristics. The more physical quantities used to determine whether the road surface is wet, the more accurate the determination of whether the road surface is wet by the determination unit 12. On the other hand, the fewer physical quantities used to determine whether the road surface is wet, the less processing load the processing device 10 needs to perform, which reduces the cost of the processing device 10.

[0036] Here, at least one axis of the riding characteristics is preferably a physical quantity of at least one of roll information and yaw information. In other words, the acquisition unit 11 preferably acquires riding characteristics based on roll information of the motorcycle 1 output from the inertial measurement sensor 2. The acquisition unit 11 also preferably acquires riding characteristics based on yaw information of the motorcycle 1 output from the inertial measurement sensor 2. The turning behavior of the motorcycle 1 is likely to differ significantly between wet and dry road conditions. Specifically, on wet road conditions, the driver of the motorcycle 1 tends to suppress slippage of the motorcycle 1, resulting in gentler turns and a smaller lean of the motorcycle 1 compared to when the road is dry. For this reason, the values ​​of roll information and yaw information are likely to differ between wet and dry road conditions. Therefore, acquiring riding characteristics based on at least one of roll information and yaw information of the motorcycle 1 improves the accuracy of the determination unit 12 in determining whether the road is wet.

[0037] The acquisition unit 11 may acquire the distance between the riding state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group, and acquire the riding characteristics of the motorcycle 1 based on this distance. In other words, the acquisition unit 11 may acquire the distance between the riding state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group, and acquire the riding characteristics of the motorcycle 1 based on this distance. That is, this distance may be used as one of the axes of the riding characteristics. For example, suppose the acquisition unit 11 acquires the distance between the riding state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group when the road surface is not wet. In this case, the larger the distance, the higher the likelihood that the road surface is wet. Conversely, the smaller the distance, the higher the likelihood that the road surface is not wet. Therefore, this distance can be used as one of the axes of the riding characteristics. When acquiring this distance, the acquisition unit 11 may calculate this distance based on a stored calculation formula, or may calculate this distance using a table that associates parameters in the calculation formula with the distance.

[0038] Euclidean distance, Mahalanobis distance, etc. can be used as the distance between the riding state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group. In this case, it is preferable to use Mahalanobis distance as the distance between the riding state information of the motorcycle 1 output from the inertial measurement sensor 2 and the reference sample group. This is for the following reason, for example. In Figures 3 and 4, attention is focused on the reference sample group when the road surface is clean and the reference sample group when the road surface is wet. In the reference sample group, the reference samples are not evenly distributed from the center of gravity of the reference sample group (or the average of each reference sample), but are widely distributed in one direction. In such cases, even if the distance between the riding state information of the motorcycle 1 and the center of gravity of the reference sample group is the same, the reference samples may be located inside or outside the reference sample group. For this reason, depending on the distribution of each reference sample in the reference sample group, Euclidean distance may not be suitable as one of the axes of riding characteristics. On the other hand, the Mahalanobis distance indicates the distance from the reference sample group, and becomes larger the further away from the reference sample group. For this reason, it is preferable to use the Mahalanobis distance as the distance between the reference sample group and the riding state information of the motorcycle 1 output from the inertial measurement sensor 2.

[0039] Furthermore, when the acquisition unit 11 acquires the riding characteristics of the motorcycle 1 based on the Mahalanobis distance, the reference sample set used to acquire the Mahalanobis distance is preferably a reference sample set of riding condition information of the motorcycle 1 when the road surface is not wet. For example, one possible use of the determination result of the determination unit 12 is to control the behavior of the motorcycle 1. In such a case, the behavior of the motorcycle 1 is controlled so that fluctuations are more gradual when the road surface is determined to be wet than when the road surface is determined to be not wet. In this case, it is assumed that, due to some influence, the riding condition information of the motorcycle 1 output from the inertial measurement sensor 2 deviates from the reference sample set when the road surface is not wet and the reference sample set when the road surface is wet. In such a case, if the acquisition unit 11 is configured to acquire the riding characteristics of the motorcycle 1 based on the reference sample set of riding condition information of the motorcycle 1 when the road surface is not wet, the determination unit 12 will determine that the road surface is wet. This means that the behavior of the motorcycle 1 is controlled so that fluctuations in the behavior of the motorcycle 1 are gradual. Therefore, if the acquisition unit 11 is configured to acquire the riding characteristics of the motorcycle 1 based on a reference sample group of riding state information of the motorcycle 1 when the road surface is not wet, the safety of the motorcycle 1 is improved.

[0040] Fig. 5 is a diagram illustrating a suitable period when the determination unit of the processing device according to the embodiment of the present invention determines whether the road surface is wet. The horizontal axis of Fig. 5 represents time. The vertical axis of Fig. 5 represents the speed of the motorcycle 1. That is, Fig. 5 shows how the motorcycle 1 begins to decelerate from time T0.

[0041] When the road surface is wet, the driver of the motorcycle 1 tends to decelerate the motorcycle 1 more gradually to prevent the motorcycle 1 from slipping, compared to when the road surface is not wet. This means that the behavior of the motorcycle 1 when decelerating is likely to differ between wet and dry roads. Specifically, the physical quantities (or physical quantities converted from these physical quantities) output from the inertial measurement sensor 2 when the motorcycle 1 decelerates are likely to differ between wet and dry roads. Therefore, while there are no particular limitations on the timing at which the determination unit 12 determines whether the road surface is wet, it is preferable that the determination unit 12 determine whether the road surface is wet based on the output of the inertial measurement sensor 2 when the motorcycle 1 is decelerating. This improves the accuracy with which the determination unit 12 determines whether the road surface is wet. For example, when the motorcycle 1 exhibits the behavior shown in FIG. 5, it is preferable that the determination unit 12 determine whether the road surface is wet after time T0.

[0042] The configuration in which the determination unit 12 determines whether the motorcycle 1 is decelerating is not particularly limited. For example, the determination unit 12 can determine whether the motorcycle 1 is decelerating based on whether the brakes of the motorcycle 1 are applied, whether the throttle opening of the motorcycle 1 is reduced, or whether the vehicle speed of the motorcycle 1 is slowed down. The configuration in which the determination unit 12 acquires the vehicle speed of the motorcycle 1 is also not particularly limited. For example, the determination unit 12 is not limited to acquiring the vehicle speed of the motorcycle 1 itself, and may acquire the vehicle speed based on other physical quantities that can be substantially converted into vehicle speed (wheel speed, GPS position information, etc.).

[0043] Furthermore, when the motorcycle 1 is traveling at a slow speed, the difference in behavior of the motorcycle 1 between when the road surface is wet and when it is not. That is, when the motorcycle 1 is traveling at a slow speed, the difference in the values ​​of the physical quantities (or physical quantities converted from the physical quantities) output from the inertial measurement sensor 2 between when the road surface is wet and when it is not wet becomes smaller. For this reason, it is preferable for the determination unit 12 to determine whether the road surface is wet based on the output of the inertial measurement sensor 2 when the motorcycle 1 is traveling at or above a specified speed. This reduces erroneous determinations of whether the road surface is wet by the determination unit 12, improving the accuracy of the determination. For example, when the motorcycle 1 exhibits the behavior shown in FIG. 5, it is preferable for the determination unit 12 to determine whether the road surface is wet based on the output of the inertial measurement sensor 2 when the motorcycle 1 is traveling at or above specified speed V1. This effect is not limited to when the determination unit 12 starts determining whether the road surface is wet while the motorcycle 1 is decelerating.

[0044] The determination unit 12 may be configured to determine whether the motorcycle 1 is traveling at or above a specified speed without any particular limitations. For example, the determination unit 12 may determine whether the motorcycle 1 is traveling at or above a specified speed based on the vehicle speed of the motorcycle 1 or another physical quantity that can be substantially converted into vehicle speed. Alternatively, the determination unit 12 may determine whether the motorcycle 1 is traveling at or above a specified speed based on the time elapsed since the motorcycle 1 began to decelerate.

[0045] <Operation of the processing device> The operation of the processing device 10 according to the embodiment will be described.

[0046] FIG. 6 is a diagram showing a control flow of an example of the operation of the processing device according to the embodiment of the present invention. When the conditions for initiating control are met, in step S1 the processing device 10 starts the control shown in Figure 6. An example of a condition for initiating control is when the motorcycle 1 begins to decelerate. In this embodiment, the determination unit 12 determines whether the start condition is met. Step S2 is an acquisition step. In step S2, the acquisition unit 11 of the processing device 10 acquires the riding characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2 used to control the behavior of the motorcycle 1. Note that the acquisition unit 11 may periodically repeat the operation of acquiring the riding characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2, even before the conditions for initiating control are met.

[0047] Step S3 after step S2 is a determination step. In step S3, the determination unit 12 of the processing device 10 compares the driving characteristics acquired in the acquisition step with reference data to determine whether the road surface is wet. Step S4 after step S3 is an end determination step. In step S4, the processing device 10 determines whether a control end condition has been met. An example of the control end condition is when the motorcycle 1 becomes slower than a specified speed. In this embodiment, the determination unit 12 determines whether the end condition is met. If the control end condition has been met, the processing device 10 proceeds to step S5 and ends the control shown in FIG. 6. On the other hand, if the control end condition has not been met, the processing device 10 repeats steps S2 to S4.

[0048] <Effects of the treatment device> The processing device 10 is mounted on the motorcycle 1. The processing device 10 includes an acquisition unit 11 and a determination unit 12. The acquisition unit 11 acquires the riding characteristics of the motorcycle 1 based on the output of the inertial measurement sensor 2 used to control the behavior of the motorcycle 1. The determination unit 12 compares the riding characteristics acquired by the acquisition unit 11 with reference data to determine whether the road surface is wet.

[0049] Conventional motorcycles require a raindrop sensor that directly detects rain to determine whether the road surface is wet. This makes conventional motorcycles capable of determining whether the road surface is wet expensive. In contrast, the processing device 10 according to this embodiment can determine whether the road surface is wet based on the output of the inertial measurement sensor 2. Conventionally, motorcycles whose behavior is controlled are equipped with an inertial measurement sensor used to control the behavior of the motorcycle. This allows the cost of the motorcycle 1 to be reduced when a motorcycle whose behavior is controlled is converted into one that can determine whether the road surface is wet.

[0050] <Modification> FIG. 7 is a block diagram showing a modified example of the processing device according to the embodiment of the present invention. The processing device 10 shown in Fig. 7 includes a control unit 13 in addition to the components shown in Fig. 2. The control unit 13 is a functional unit that uses the determination results of the determination unit 12 to control the behavior of the motorcycle 1. This control unit 13 may be part of the configuration of the control device (not shown) described above that controls the behavior of the motorcycle 1 based on the output of the inertial measurement sensor 2, or may be a separate component from the configuration of the control device.

[0051] The processing device 10 configured as shown in Figure 7 can reflect whether or not the road surface is wet in controlling the behavior of the motorcycle 1. For example, when it is determined that the road surface is wet, the control unit 13 can control the behavior of the motorcycle 1 so that the changes in behavior of the motorcycle 1 are more gradual than when it is determined that the road surface is not wet. Specifically, the control unit 13 can control the torque, throttle opening, etc. of the motorcycle 1 to gently control the changes in behavior of the motorcycle 1. Therefore, configuring the processing device 10 as shown in Figure 7 improves the safety of a motorcycle 1 equipped with the processing device 10.

[0052] Fig. 8 is a block diagram showing another modified example of the processing device according to the embodiment of the present invention, and Fig. 9 is a side view of a motorcycle equipped with the processing device shown in Fig. 8. The motorcycle 1 shown in FIG. 9 is equipped with a display device 3, which is an example of a notification device.

[0053] The processing device 10 shown in FIG. 8 includes an announcing operation execution unit 14 in addition to the configuration shown in FIG. 2. The announcing operation execution unit 14 is a functional unit that outputs a signal to cause the annunciation device to notify the determination result of the determination unit 12. Specific content to be notified may be, for example, whether or not the road surface is wet. As described above, the motorcycle 1 shown in FIG. 9 uses the display device 3 as the annunciation device. Therefore, in the motorcycle 1 shown in FIG. 9, the annunciation operation execution unit 14 outputs a signal to cause the display device 3 to display the determination result of the determination unit 12. As a result, the determination result of the determination unit 12 is displayed on the display device 3.

[0054] The notification device is not limited to the display device 3. For example, a speaker or the like provided on the motorcycle 1 may be used as the notification device to notify the determination result of the determination unit 12 by sound. In this case, the notification operation execution unit 14 outputs a notification signal that causes the notification device to emit a sound indicating the determination result of the determination unit 12. Furthermore, the notification device that receives the notification signal output from the notification operation execution unit 14 is not limited to a configuration provided on the motorcycle 1. It may also be an accessory attached to the motorcycle 1, such as a helmet and gloves worn by the driver of the motorcycle 1. In other words, the notification operation execution unit 14 may output a notification signal to an accessory attached to the motorcycle 1, and the accessory may issue the notification.

[0055] The processing device 10 configured as shown in Figure 8 can make the driver of the motorcycle 1 aware of whether the road surface is wet or not. Therefore, configuring the processing device 10 as shown in Figure 8 improves the safety of the motorcycle 1 equipped with the processing device 10. The processing device 10 shown in Figure 8 may also be equipped with the control unit 13 shown in Figure 7.

[0056] FIG. 10 is a block diagram showing yet another modified example of the processing device according to the embodiment of the present invention. The processing device 10 shown in FIG. 10 includes a memory unit 15 in addition to the configuration shown in FIG. 2. The memory unit 15 is a functional unit that stores the determination result of the determination unit 12. By configuring the processing device 10 as shown in FIG. 10, the determination result of the determination unit 12 can be used for post-analysis of the driver's driving and skill determination, etc. Therefore, by configuring the processing device 10 as shown in FIG. 10, the convenience of the processing device 10 is improved. Note that the processing device 10 shown in FIG. 10 may include the control unit 13 shown in FIG. 7 or the notification operation execution unit 14 shown in FIG. 8.

[0057] The processing device 10 according to this embodiment has been described above, but the processing device according to the present invention is not limited to the description of this embodiment, and only a part of this embodiment may be implemented. [Explanation of symbols]

[0058] 1 Motorcycle, 2 Inertial measurement sensor, 3 Display device, 10 Processing device, 11 Acquisition unit, 12 Determination unit, 13 Control unit, 14 Notification operation execution unit, 15 Storage unit

Claims

1. A processing device (10) mounted on a motorcycle (1), an acquisition unit (11) that acquires driving characteristics of the motorcycle (1) based on the output of an inertial measurement sensor (2) used to control the behavior of the motorcycle (1); a determination unit (12) that compares the running characteristics acquired by the acquisition unit (11) with reference data to determine whether the road surface is wet, the acquisition unit (11) is configured to acquire the driving characteristics based on yaw information of the motorcycle (1) output from the inertial measurement sensor (2); a boundary (B) that separates the driving characteristics when the road surface is not wet from the driving characteristics when the road surface is wet is set in the reference data; The determination unit (12) is configured to determine whether the road surface is wet based on the boundary (B). A processing device (10).

2. The acquisition unit (11) is configured to acquire the riding characteristics based on roll information of the motorcycle (1) output from the inertial measurement sensor (2). The processing device (10) of claim 1.

3. The acquisition unit (11) is configured to acquire a Mahalanobis distance for a reference sample group of the running state information of the motorcycle (1) output from the inertial measurement sensor (2), and acquire the running characteristics based on the Mahalanobis distance. The processing device (10) of claim 1.

4. The reference sample group is a reference sample group of the driving state information when the road surface is not wet. The processing device (10) of claim 3.

5. The determination unit (12) is configured to determine the wetness of the road surface based on the output of the inertial measurement sensor (2) when the motorcycle (1) is decelerating. The processing device (10) of claim 1.

6. The determination unit (12) is configured to determine whether the road surface is wet based on the output of the inertial measurement sensor (2) when the motorcycle (1) is traveling at a specified speed (V1) or higher. The processing device (10) of claim 1.

7. A control unit (13) is provided that uses the determination result of the determination unit (12) to control the behavior of the motorcycle (1). The processing device (10) of claim 1.

8. The system is provided with an informing operation execution unit (14) that outputs a signal to an informing device (3) of the determination result of the determination unit (12). The processing device (10) of claim 1.

9. A storage unit (15) is provided for storing the determination result of the determination unit (12). The processing device (10) of claim 1.

10. The processing device (10) according to any one of claims 1 to 9 is provided. Motorcycle (1).

11. A treatment method for use on a motorcycle (1), comprising: an acquisition step (S2) of acquiring driving characteristics of the motorcycle (1) based on an output of an inertial measurement sensor (2) used to control the behavior of the motorcycle (1); a determination step (S3) of comparing the running characteristics acquired in the acquisition step (S2) with reference data to determine whether the road surface is wet, The acquisition step (S2) acquires the running characteristics based on yaw information of the motorcycle (1) output from the inertial measurement sensor (2), a boundary (B) that separates the driving characteristics when the road surface is not wet from the driving characteristics when the road surface is wet is set in the reference data; The determination step (S3) determines whether the road surface is wet based on the boundary (B). Processing method.

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