Fouling estimation device, fouling estimation method, and program

Abstract

To accurately estimate the contamination level of millimeter-wave radar. [Solution] The dirt estimation device 16 includes an acquisition unit 3A that acquires information about a target located in front of the vehicle 1 detected by a millimeter-wave radar 11 mounted on the vehicle 1; a determination unit 3B that determines whether the target indicated by the information acquired by the acquisition unit 3A is a road surface reflective target corresponding to the unevenness of the road surface in front of the vehicle 1 that reflects radio waves emitted from the millimeter-wave radar 11; and an estimation unit 3C that estimates the dirt on the millimeter-wave radar 11 based on the reflected waves from the road surface reflective target received by the millimeter-wave radar 11 when the target indicated by the information acquired by the acquisition unit 3A is a road surface reflective target.

Description

Technical Field

[0001] The present disclosure relates to a stain estimation device, a stain estimation method, and a program.

Background Art

[0002] Patent Document 1 describes a stain determination device for an obstacle detection sensor (radar). In the technique described in Patent Document 1, the number of obstacles detected by the obstacle detection sensor is used to determine the presence or absence of stains on the obstacle detection sensor.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] By the way, the number of obstacles detected by the obstacle detection sensor (radar) not only decreases when the number of actual obstacles is small, but also decreases when the number of actual obstacles is large but the actual obstacles are not detected by the obstacle detection sensor due to stains on the obstacle detection sensor. Therefore, in the technique described in Patent Document 1, in order to ensure the determination accuracy of the presence or absence of stains on the obstacle detection sensor, when at least one of the conditions that the travel distance is a predetermined value or more and the steering continuous period is a predetermined value or more is satisfied and the undetected period of the obstacle is a predetermined value or more, it is determined that there are stains on the obstacle detection sensor.

[0005] That is, in the technique described in Patent Document 1, it takes time from the state where there are stains on the obstacle detection sensor until it is determined that there are stains on the obstacle detection sensor. That is, in the technique described in Patent Document 1, the stains on the obstacle detection sensor cannot be appropriately estimated.

[0006] In view of the above, the purpose of this disclosure is to provide a fouling estimation device, a fouling estimation method, and a program that can appropriately estimate fouling on a millimeter-wave radar. [Means for solving the problem]

[0007] (1) One aspect of the present disclosure is a dirt estimation device comprising: an acquisition unit that acquires information relating to an object located in front of a vehicle detected by a millimeter-wave radar mounted on the vehicle; a determination unit that determines whether the object indicated by the information acquired by the acquisition unit is a road surface reflective object corresponding to irregularities on the road surface in front of the vehicle that have reflected radio waves emitted from the millimeter-wave radar; and an estimation unit that, if the object indicated by the information acquired by the acquisition unit is a road surface reflective object, estimates the dirt on the millimeter-wave radar based on reflected waves from the road surface reflective object received by the millimeter-wave radar.

[0008] (2) In the dirt estimation device of (1), the estimation unit may estimate the dirt on the millimeter-wave radar based on the number of road surface reflective markers detected per unit time by the millimeter-wave radar while the vehicle is moving forward.

[0009] (3) In the dirt estimation device of (1), the estimation unit may estimate the dirt on the millimeter-wave radar based on the magnitude of the reflected power per unit time, which indicates the intensity of the radio waves emitted by the millimeter-wave radar while the vehicle is moving forward, reflected by the road surface reflective markers, and received by the millimeter-wave radar.

[0010] (4) One aspect of the present disclosure is a dirt estimation method comprising: an acquisition step of acquiring information about a target located in front of a vehicle detected by a millimeter-wave radar mounted on the vehicle; a determination step of determining whether the target indicated by the information acquired in the acquisition step is a road surface reflective target corresponding to irregularities on the road surface in front of the vehicle that have reflected radio waves emitted from the millimeter-wave radar; and an estimation step of estimating the dirt on the millimeter-wave radar based on reflected waves from the road surface reflective target received by the millimeter-wave radar, if the target indicated by the information acquired in the acquisition step is a road surface reflective target.

[0011] (5) One aspect of the present disclosure is a program for causing a processor to perform an acquisition step of acquiring information about a target located in front of a vehicle detected by a millimeter-wave radar mounted on the vehicle; a determination step of determining whether the target indicated by the information acquired in the acquisition step is a road surface reflective target corresponding to irregularities on the road surface in front of the vehicle that have reflected radio waves emitted from the millimeter-wave radar; and an estimation step of estimating the contamination of the millimeter-wave radar based on reflected waves from the road surface reflective target received by the millimeter-wave radar, if the target indicated by the information acquired in the acquisition step is a road surface reflective target. [Effects of the Invention]

[0012] According to this disclosure, the contamination of millimeter-wave radar can be appropriately estimated. [Brief explanation of the drawing]

[0013] [Figure 1] This figure shows an example of a vehicle 1 to which the dirt estimation device 16 of the first embodiment is applied. [Figure 2] Figure 1 shows an example of the data flow within vehicle 1. [Figure 3]This figure shows an example of the relationship between the number of road surface reflective objects detected per unit time by the millimeter-wave radar 11 while the vehicle 1 is moving forward and the amount of contamination of the millimeter-wave radar 11 estimated by the estimation unit 3C. [Figure 4] This is a flowchart illustrating an example of processing performed by the processor 163 of the dirt estimation device 16 of the first embodiment. [Figure 5] This figure illustrates a specific example of the process shown in Figure 4. [Figure 6] This figure shows an example of the relationship between the reflected power per unit time from road surface reflective targets detected by the millimeter-wave radar 11 while the vehicle 1 is moving forward, and the amount of contamination of the millimeter-wave radar 11 estimated by the estimation unit 3C. [Modes for carrying out the invention]

[0014] Hereinafter, embodiments of the dirt estimation apparatus, dirt estimation method, and program of this disclosure will be described with reference to the drawings.

[0015] <First Embodiment> Figure 1 shows an example of a vehicle 1 to which the dirt estimation device 16 of the first embodiment is applied. Figure 2 shows an example of the data flow within the vehicle 1 shown in Figure 1. In the example shown in Figures 1 and 2, vehicle 1 is equipped with a millimeter-wave radar 11, an HMI (Human Machine Interface) 12, a vehicle condition sensor 13, a position information acquisition device 14, an obstacle recognition device 15, a dirt estimation device 16, a vehicle control device 17, a steering actuator 17A, a braking actuator 17B, and a drive actuator 17C. The millimeter-wave radar 11 is positioned, for example, at the front of the vehicle 1. The millimeter-wave radar 11 detects targets TG1 to TG6 (see Figure 5) located in front of the vehicle 1 and transmits information (sensor data) regarding targets TG1 to TG6 to the obstacle recognition device 15 and the dirt estimation device 16.

[0016] In their intensive research, the inventors have found that while the vehicle 1 is moving forward on an unpaved road, the millimeter-wave radar 11 not only detects a large rock as a target TG5 (see FIG. 5) that requires the vehicle 1 to avoid a collision (i.e., requires control of the steering actuator 17A and the braking actuator 17B), or detects another vehicle as a target TG6 (see FIG. 5), but also detects unevenness on the road surface (specifically, small unevenness on the road surface that the vehicle 1 can pass over, and the unevenness on the road surface includes, for example, small stones) as targets TG1 to TG4 (see FIG. 5) (road surface reflection targets). That is, the millimeter-wave radar 11 receives radio waves (reflected waves) that are emitted by the millimeter-wave radar 11 and reflected by the unevenness on the road surface in front of the vehicle 1. Further, the inventors have found that the unevenness on the road surface is detected by the millimeter-wave radar 11 as targets TG1 to TG4 when it exists within a first area AR1 (area near the vehicle 1) (see FIG. 5) that is an area where the distance from the moving vehicle 1 is less than a predetermined value, but is not detected by the millimeter-wave radar 11 as targets TG1 to TG4 when it exists within a second area AR2 (area at a long distance from the vehicle 1) (see FIG. 5) that is an area where the distance from the moving vehicle 1 is greater than or equal to the predetermined value. Therefore, in the examples shown in FIGS. 1 and 2, in order to distinguish between targets TG1 to TG4 for which the vehicle 1 does not need to avoid a collision and targets TG5 and TG6 for which the vehicle 1 needs to avoid a collision, the countermeasures described later are taken.

[0017] In the examples shown in FIGS. 1 and 2, the HMI 12 has a function of receiving various operations of the user of the vehicle 1 and transmits a signal indicating the operation of the user of the vehicle 1 to the vehicle control device 17. The operations of the user of the vehicle 1 received by the HMI 12 include, for example, an operation to cause the vehicle control device 17 to execute automatic driving of the vehicle 1, an operation to switch the automatic driving of the vehicle 1 to manual driving, and the like. The vehicle state sensor 13 includes, for example, a vehicle speed sensor and the like. The vehicle state sensor 13 transmits information indicating the state of the vehicle 1 (such as vehicle speed) to the obstacle recognition device 15, the dirt estimation device 16, and the vehicle control device 17.

[0018] The position information acquisition device 14 acquires information indicating the position of the vehicle 1. The position information acquisition device 14 includes, for example, a GPS (Global Positioning System) device that measures the position of the vehicle 1. The position information acquisition device 14 may perform well-known self-position estimation processing (localization) to improve the accuracy of the information indicating the position of the vehicle 1. The position information acquisition device 14 transmits the information indicating the position of the vehicle 1 to the obstacle recognition device 15, the dirt estimation device 16, and the vehicle control device 17.

[0019] The vehicle control device 17 is constituted by, for example, a vehicle control ECU (Electronic Control Unit). The vehicle control device 17 controls the steering actuator 17A, the brake actuator 17B, and the drive actuator 17C based on the information (signals) transmitted from, for example, the HMI 12, the vehicle state sensor 13, the position information acquisition device 14, and the obstacle recognition device 15. The vehicle control device 17 has a function of executing the automatic driving of the vehicle 1.

[0020] The obstacle recognition device 15 acquires, from the millimeter-wave radar 11, information (specifically, time-series data) regarding the targets TG1 to TG6 (see FIG. 5) existing in front of the vehicle 1 detected by the millimeter-wave radar 11. The information regarding the targets TG1 to TG6 includes target position information (information indicating the relative positions of the targets TG1 to TG6 with respect to the vehicle 1) and tracking information. The tracking information is information that can distinguish whether the targets TG1 to TG6 output from the millimeter-wave radar 11 in time series are the same. In the example shown in FIG. 5 described later, based on the tracking information output from the millimeter-wave radar 11, it can be recognized that each of the targets TG5 and TG6 detected by the millimeter-wave radar 11 at the past time point shown in FIG. 5(A) and each of the targets TG5 and TG6 detected by the millimeter-wave radar 11 at the current time point shown in FIG. 5(B) are the same.

[0021] Furthermore, the obstacle recognition device 15 performs a determination (first determination) based on the acquired information about targets TG1 to TG6 (see Figure 5(B)) to determine whether or not targets TG1 to TG6 are located within the first area AR1 (see Figure 5(B)). In addition, the obstacle recognition device 15 performs a determination (second determination) based on the acquired information about targets TG1 to TG6 (see Figures 5(A) and 5(B)) to determine whether or not targets TG1 to TG5 (see Figure 5(B)), which were determined to be located within the first area AR1 (see Figure 5(B)) in the first determination, were detected by the millimeter-wave radar 11 when they were located within the second area AR2 (see Figure 5(A)).

[0022] Furthermore, if the obstacle recognition device 15 determines in the first determination that targets TG1 to TG4 (see Figure 5(B)) are located within the first area AR1 (see Figure 5(B)), and in the second determination that targets TG1 to TG4 (see Figure 5(A)) were located within the second area AR2 (see Figure 5(A)) but were not detected by the millimeter-wave radar 11, it discards information regarding targets TG1 to TG4. Also, if the obstacle recognition device 15 determines in the first determination that target TG5 (see Figure 5(B)) is located within the first area AR1 (see Figure 5(B)), and in the second determination that target TG5 (see Figure 5(A)) was located within the second area AR2 (see Figure 5(A)) but was detected by the millimeter-wave radar 11, it outputs information regarding target TG5 to the vehicle control device 17. The vehicle control device 17 performs control to activate the steering actuator 17A and / or braking actuator 17B based on information about the target TG5 output from the obstacle recognition device 15 in order to avoid a collision between the vehicle 1 and the target TG5. On the other hand, unnecessary control such as activating the steering actuator 17A and / or braking actuator 17B to avoid a collision between vehicle 1 and targets TG1 to TG4 is not performed by the vehicle control device 17.

[0023] Furthermore, in the examples shown in Figures 1 and 2, the contamination estimation device 16 estimates the contamination of the millimeter-wave radar 11 (presence or absence of contamination, amount of contamination, etc.). The contamination estimation device 16 is composed of a microcomputer equipped with a communication interface (I / F) 161, memory 162, and processor 163. The communication interface 161 has an interface circuit for connecting the dirt estimation device 16 to the millimeter-wave radar 11, HMI 12, vehicle condition sensor 13, position information acquisition device 14, obstacle recognition device 15, and vehicle control device 17. Memory 162 stores programs and various data used in processing executed by processor 163. The data stored in memory 162 includes, for example, judgment area information (see Figure 2). Judgment area information is information that defines parameters (e.g., size, etc.) related to the first area AR1 (see Figure 5) where targets TG1 to TG4 (road surface reflective targets) that vehicle 1 does not need to avoid colliding with may exist. The range in which targets TG1 to TG4 (road surface reflective targets) that vehicle 1 does not need to avoid colliding with are detected by the millimeter-wave radar 11 varies depending on the condition and material of the road surface on which vehicle 1 is traveling. Therefore, the parameters related to the first area AR1 are adjusted according to the usage environment of vehicle 1, for example, by the user of vehicle 1. In other words, memory 162 stores judgment area information that has been adjusted according to the usage environment of vehicle 1, for example, by the user of vehicle 1. The processor 163 has the functions of an acquisition unit 3A, a determination unit 3B, and an estimation unit 3C.

[0024] The acquisition unit 3A acquires information (specifically, time-series data) from the millimeter-wave radar 11 regarding targets TG1 to TG6 (see Figure 5) located in front of the vehicle 1 as detected by the millimeter-wave radar 11. As described above, the information regarding targets TG1 to TG6 includes target position information (information indicating the relative position of targets TG1 to TG6 with respect to the vehicle 1) and tracking information. The information regarding targets TG1 to TG6 also includes information indicating the intensity of reflected waves from targets TG1 to TG6 detected by the millimeter-wave radar 11.

[0025] The determination unit 3B determines whether the targets TG1 to TG6 (see Figure 5(B)) indicated by the information acquired by the acquisition unit 3A are road surface reflective targets corresponding to the irregularities on the road surface in front of the vehicle 1 that reflected the radio waves emitted from the millimeter-wave radar 11. Specifically, the determination unit 3B performs a determination (first determination by the determination unit 3B) based on the information about the target acquired by the acquisition unit 3A to determine whether or not the target is located within the first area AR1 (see Figure 5(B)). The determination unit 3B also performs a determination (second determination by the determination unit 3B) based on the information about the target acquired by the acquisition unit 3A to determine whether or not the target, which was determined to be located within the first area AR1 in the first determination, was detected by the millimeter-wave radar 11 when it was located within the second area AR2 (see Figure 5(A)). Furthermore, if the target is located within the first area AR1, and the target, which was determined to be located within the first area AR1 in the first determination by the determination unit 3B, was detected by the millimeter-wave radar 11 when it was located within the second area AR2, the determination unit 3B determines that the target is not a road surface reflective target. On the other hand, the determination unit 3B determines that a target is a road surface reflective target if the target is located within the first area AR1, and the target, which was determined to be located within the first area AR1 in the first determination of the determination unit 3B, was not detected by the millimeter-wave radar 11 when it was located within the second area AR2. In the example shown in Figure 5, which will be described later, the determination unit 3B determines that targets TG1 to TG4 are road surface reflective targets, and determines that targets TG5 and TG6 are not road surface reflective targets.

[0026] When the determination unit 3B determines that the target is a road surface reflective target, the estimation unit 3C estimates the contamination of the millimeter-wave radar 11 based on the reflected waves from the road surface reflective target received by the millimeter-wave radar 11. Specifically, the estimation unit 3C estimates the contamination of the millimeter-wave radar 11 based on the number of road surface reflective objects detected per unit time by the millimeter-wave radar 11 while the vehicle 1 is moving forward.

[0027] Figure 3 shows an example of the relationship between the number of road surface reflective objects detected per unit time by the millimeter-wave radar 11 while the vehicle 1 is moving forward and the amount of contamination of the millimeter-wave radar 11 estimated by the estimation unit 3C. In the example shown in Figure 3, the fewer road surface reflective objects detected per unit time by the millimeter-wave radar 11 while the vehicle 1 is moving forward, the greater the amount of contamination of the millimeter-wave radar 11 estimated by the estimation unit 3C. In detail, in the example shown in Figure 3, the estimation unit 3C estimates that the millimeter-wave radar 11 is dirty if the number of road surface reflective objects detected per unit time by the millimeter-wave radar 11 while the vehicle 1 is moving forward is less than the threshold TH1.

[0028] In the examples shown in Figures 1 and 2, when the estimation unit 3C estimates that the millimeter-wave radar 11 is dirty, it outputs information indicating that the millimeter-wave radar 11 is dirty to the vehicle control device 17. The vehicle control device 17 then outputs information indicating that the millimeter-wave radar 11 is dirty to the HMI 12 and requests the user of the vehicle 1 to clean the millimeter-wave radar 11.

[0029] Figure 4 is a flowchart illustrating an example of the process performed by the processor 163 of the dirt estimation device 16 of the first embodiment. The process shown in Figure 4 is executed, for example, while vehicle 1 is moving (more specifically, while moving forward).

[0030] In the example shown in Figure 4, in step S10, the acquisition unit 3A acquires information from the millimeter-wave radar 11 regarding a target located in front of the vehicle 1 that was detected by the millimeter-wave radar 11. In steps S11 and S12, the determination unit 3B determines whether the target indicated by the information acquired in step S10 is a road surface reflective target corresponding to the irregularities on the road surface in front of the vehicle 1 that reflected the radio waves emitted from the millimeter-wave radar 11. In detail, in step S11, the determination unit 3B performs a determination (first determination) to determine whether or not the target is located within the first area AR1 (see Figure 5(B)) based on the target information acquired in step S10 (specifically, the current data from the time-series data). If the result is YES, the process proceeds to step S12; if the result is NO, the process shown in Figure 4 is terminated.

[0031] In step S12, the determination unit 3B performs a second determination (second determination) based on the target information acquired in step S10 (specifically, time-series data including current data and data from a point in time prior to the current time) to determine whether the target determined to be in the first area AR1 in step S11 was detected by the millimeter-wave radar 11 when it was in the second area AR2 (see Figure 5(A)). If the result is YES (the target indicated by the information acquired in step S10 is not a road surface reflective target), the process shown in Figure 4 is terminated, and if the result is NO (the target indicated by the information acquired in step S10 is a road surface reflective target), the process proceeds to step S13. In step S13, the estimation unit 3C estimates the contamination of the millimeter-wave radar 11 based on the information indicating reflected waves from road surface reflective targets acquired in step S10.

[0032] Figure 5 is a diagram illustrating a specific example of the process shown in Figure 4. Specifically, Figure 5(A) shows an example of the positional relationship between vehicle 1, targets TG1-TG6, first area AR1, and second area AR2 at a past point in time, and Figure 5(B) shows an example of the positional relationship between vehicle 1, targets TG1-TG6, first area AR1, and second area AR2 at the present time. In the example shown in Figure 5, in step S10 of Figure 4, the acquisition unit 3A acquires information from the millimeter-wave radar 11 regarding targets TG1 to TG6 located in front of the vehicle 1 as detected by the millimeter-wave radar 11. This includes, for example, time-series data of targets TG1 to TG6 detected by the millimeter-wave radar 11 from a past point in time shown in Figure 5(A) to the present time shown in Figure 5(B), and information indicating reflected waves from targets TG1 to TG6 detected by the millimeter-wave radar 11. In step S11 of Figure 4, the determination unit 3B determines, based on the data of targets TG1 to TG6 detected by the millimeter-wave radar 11 at the present time shown in Figure 5(B) from the time-series data acquired in step S10, that targets TG1 to TG5 are located within the first area AR1, and that target TG6 (another vehicle) is not located within the first area AR1.

[0033] Furthermore, in the example shown in Figure 5, in step S12 of Figure 4, the determination unit 3B determines, based on the time-series data of targets TG1 to TG6 detected by the millimeter-wave radar 11 from the past time shown in Figure 5(A) to the present time shown in Figure 5(B), that target TG5 (a large rock), which is determined to be in the first area AR1 at the present time shown in Figure 5(B), was also detected by the millimeter-wave radar 11 at the past time shown in Figure 5(A) when it was in the second area AR2.

[0034] On the other hand, in the example shown in Figure 5, in step S12 of Figure 4, the determination unit 3B determines, based on the time-series data of targets TG1 to TG6 detected by the millimeter-wave radar 11 from the past time shown in Figure 5(A) to the present time shown in Figure 5(B), that targets TG1 to TG4, which are determined to be in the first area AR1 at the present time shown in Figure 5(B), were not detected by the millimeter-wave radar 11 at the past time shown in Figure 5(A) when they were in the second area AR2. In other words, the determination unit 3B determines that targets TG1 to TG4 are road surface reflective targets corresponding to the irregularities on the road surface in front of the vehicle 1 that reflected the radio waves emitted from the millimeter-wave radar 11.

[0035] Furthermore, in the example shown in Figure 5, in step S13 of Figure 4, the estimation unit 3C estimates the contamination of the millimeter-wave radar 11 based on the information showing the reflected waves from targets TG1 to TG4 (road surface reflective targets) acquired in step S10. Specifically, in the example shown in Figure 5, if the millimeter-wave radar 11 is not contaminated, in step S10 information is obtained indicating reflected waves from, for example, four targets TG1 to TG4 (road surface reflective targets) that are above the threshold TH1 (see Figure 3) detected by the millimeter-wave radar 11, and in step S12 it is estimated that the millimeter-wave radar 11 is not contaminated. On the other hand, if the millimeter-wave radar 11 is contaminated, in step S10 information is obtained indicating reflected waves from, for example, one target TG1 (road surface reflective target) that is below the threshold TH1 detected by the millimeter-wave radar 11, and in step S12 it is estimated that the millimeter-wave radar 11 is contaminated.

[0036] For example, when millimeter-wave radar is used in an autonomous vehicle that operates in an environment with few surrounding structures, such as a mine, if existing obstacles are used to estimate the contamination of the millimeter-wave radar, as in the technology described in Patent Document 1, then in an environment such as a mine, where there are few existing obstacles, it is not possible to estimate the contamination of the millimeter-wave radar appropriately (with high accuracy). As described above, in the examples shown in Figures 1 to 5, actual obstacles (target TG5) are not used to estimate the contamination of the millimeter-wave radar 11. Instead, reflected waves from the irregularities of the road surface in front of the vehicle 1 detected by the millimeter-wave radar 11 (targets TG1 to TG4) (i.e., irregularities that are always present on unpaved roads) are used, allowing for an appropriate (highly accurate) estimation of the contamination of the millimeter-wave radar 11.

[0037] <Second Embodiment> Vehicle 1 to which the dirt estimation device 16 of the second embodiment is applied is configured in the same way as vehicle 1 to which the dirt estimation device 16 of the first embodiment is applied, except for the points described later.

[0038] As described above, in a vehicle 1 to which the dirt estimation device 16 of the first embodiment described above is applied, the estimation unit 3C estimates the dirt on the millimeter-wave radar 11 based on the number of road surface reflective objects detected per unit time by the millimeter-wave radar 11 while the vehicle 1 is moving forward. On the other hand, in a vehicle 1 to which the dirt estimation device 16 of the second embodiment is applied, the estimation unit 3C estimates the dirt on the millimeter-wave radar 11 based on the magnitude of the reflected power per unit time, which indicates the intensity of the radio waves emitted by the millimeter-wave radar 11 while the vehicle 1 is moving forward, reflected by the road surface reflective targets TG1 to TG4 (see Figure 5), and received by the millimeter-wave radar 11.

[0039] Figure 6 shows an example of the relationship between the reflected power per unit time from road surface reflective targets detected by the millimeter-wave radar 11 while the vehicle 1 is moving forward and the amount of contamination of the millimeter-wave radar 11 estimated by the estimation unit 3C. In the example shown in Figure 6, the smaller the reflected power per unit time from road surface reflective targets detected by the millimeter-wave radar 11 while the vehicle 1 is moving forward (specifically, the average reflected power from road surface reflective targets TG1 to TG4), the greater the amount of contamination of the millimeter-wave radar 11 estimated by the estimation unit 3C. In detail, in the example shown in Figure 6, the estimation unit 3C estimates that the millimeter-wave radar 11 is dirty if the reflected power per unit time from a road surface reflective target detected by the millimeter-wave radar 11 while the vehicle 1 is moving forward is less than the threshold TH2.

[0040] <Third Embodiment> A vehicle 1 to which the dirt estimation device 16 of the third embodiment is applied is configured in the same way as a vehicle 1 to which the dirt estimation device 16 of the first or second embodiment described above is applied, except for the points described later.

[0041] As described above, in a vehicle 1 (autonomous vehicle) to which the dirt estimation device 16 of the first or second embodiment is applied, the vehicle control device 17 performs control to activate the steering actuator 17A and / or braking actuator 17B based on information about the target TG5 output from the obstacle recognition device 15 in order to avoid a collision between the vehicle 1 and the target TG5. On the other hand, in the vehicle 1 to which the dirt estimation device 16 of the third embodiment is applied, the vehicle control device 17 causes the HMI 12 to output a warning indicating that an operation is required to avoid a collision between the vehicle 1 and the target TG5, based on the information about the target TG5 output from the obstacle recognition device 15.

[0042] As described above, embodiments of the stain estimation device, stain estimation method, and program of this disclosure have been explained with reference to the drawings. However, the stain estimation device, stain estimation method, and program of this disclosure are not limited to the embodiments described above, and can be modified as appropriate without departing from the spirit of this disclosure. The configurations of each example of the embodiments described above may be combined as appropriate. In each example of the embodiments described above, the processing performed in the stain estimation device 16 was described as software processing performed by executing a program. However, the processing performed in the stain estimation device 16 may be hardware processing. Alternatively, the processing performed in the stain estimation device 16 may be a combination of software and hardware processing. Furthermore, the program stored in the memory 162 of the stain estimation device 16 (the program that realizes the functions of the processor 163 of the stain estimation device 16) may be recorded on a computer-readable storage medium such as a semiconductor memory, magnetic recording medium, or optical recording medium and provided and distributed. [Explanation of Symbols]

[0043] 1...Vehicle, 11...Millimeter-wave radar, 12...HMI, 13...Vehicle status sensor, 14...Position information acquisition device, 15...Obstacle recognition device, 16...Dirt estimation device, 161...Communication interface, 162...Memory, 163...Processor, 3A...Acquisition unit, 3B...Determination unit, 3C...Estimation unit, 17...Vehicle control device, 17A...Steering actuator, 17B...Brake actuator, 17C...Drive actuator

Claims

1. An acquisition unit that acquires information about a target located in front of the vehicle, detected by a millimeter-wave radar mounted on the vehicle, A determination unit determines whether the target indicated by the information acquired by the acquisition unit is a road surface reflective target corresponding to the irregularities on the road surface in front of the vehicle that reflected radio waves emitted from the millimeter-wave radar, A dirt estimation device comprising: an estimation unit that estimates the dirt on the millimeter-wave radar based on reflected waves from the road surface reflective object received by the millimeter-wave radar when the object indicated by the information acquired by the acquisition unit is the road surface reflective object.

2. The dirt estimation device according to claim 1, wherein the estimation unit estimates the dirt on the millimeter-wave radar based on the number of road surface reflective markers detected per unit time by the millimeter-wave radar while the vehicle is moving forward.

3. The dirt estimation device according to claim 1, wherein the estimation unit estimates the dirt on the millimeter-wave radar based on the magnitude of the reflected power per unit time, which indicates the intensity of radio waves emitted by the millimeter-wave radar while the vehicle is moving forward, reflected by the road surface reflective marker, and received by the millimeter-wave radar.

4. The dirt estimation device acquires information about an object located in front of the vehicle, which is detected by a millimeter-wave radar mounted on the vehicle. The dirt estimation device includes a determination step in which it determines whether the target indicated by the information acquired in the acquisition step is a road surface reflective target corresponding to the irregularities on the road surface in front of the vehicle that reflected radio waves emitted from the millimeter-wave radar, A dirt estimation method comprising: an estimation step in which, when the dirt estimation device is the road surface reflective marker indicated by the information acquired in the acquisition step, the dirt on the millimeter-wave radar is estimated based on the reflected waves from the road surface reflective marker received by the millimeter-wave radar.

5. In the processor, An acquisition step of acquiring information about an object located in front of the vehicle, which is detected by a millimeter-wave radar mounted on the vehicle, A determination step to determine whether the target indicated by the information acquired in the acquisition step is a road surface reflective target corresponding to the irregularities on the road surface in front of the vehicle that reflected radio waves emitted from the millimeter-wave radar, A program for performing an estimation step, in which, if the target indicated by the information acquired in the acquisition step is the road surface reflective target, the program performs an estimation step of estimating the contamination of the millimeter-wave radar based on the reflected waves from the road surface reflective target received by the millimeter-wave radar.

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