JP6901982B2 - Road surface condition detector - Google Patents

Description

The present invention relates to a road surface condition detection device, and more particularly to a technique for determining whether a road surface on which a work vehicle such as a dump truck operating in a mine travels is in a state in which dust is likely to be generated.

In a mine, when a work vehicle such as a dump truck runs, the road surface is scraped by wheels and dust is generated. Dust obstructs the view of the operator who drives the work vehicle, and deteriorates the recognition performance of the outside world sensor mounted on the work vehicle for detecting other vehicles, bollards, and the like.

Therefore, as a technique for reducing the influence of dust on the external sensor, Patent Document 1 states that "a pixel having a brightness value higher than the brightness value for identifying dust from each pixel of image data is defined as a high-brightness pixel. Detected, one pixel of the image data is set as the center pixel, and the center pixel whose difference in brightness value between the surrounding pixels is lower than the difference in brightness value detected as the edge of the ground is detected as a non-edge pixel. However, overlapping pixels in which high-brightness pixels and non-edge pixels overlap are detected, and the area formed by the overlapping pixels is defined as the overlapping pixel area, and the overlapping pixel area is larger than the area for identifying dust. Occasionally, an overlapping pixel region is generated as a dust region, and a screen drawn so as to specify the dust region with respect to the image data is created (summary excerpt). "

Further, Patent Document 2 states, "Image information that compares a stereo camera device and a two-dimensional camera acquired image acquired by each camera, and specifies a region without parallax between these two camera-acquired images as a parallax-free region. It is provided with an acquisition unit and a vehicle presence area detection unit that identifies the no-parallax area as a vehicle possibility area in which another vehicle is likely to exist when the number of pixels in the no-parallax area in the parallax image is larger than a predetermined value. (Abstract excerpt) ”Structure is disclosed.

International Publication No. 2013/153863 Japanese Unexamined Patent Publication No. 2016-24685

If a work vehicle running in the mine winds up dust, it will affect the following vehicles. Here, if it is possible to detect whether the road surface on which the own vehicle is traveling is in a state where dust is likely to be generated, it is possible to take measures such as sprinkling water on the road surface to suppress the generation of dust before a large amount of dust is generated. it can. However, in Patent Documents 1 and 2, although the influence of dust generated in the front of the own vehicle in the traveling direction can be reduced, it is not possible to confirm whether or not the own vehicle is winding up the dust.

The present invention has been made in view of the above circumstances, and an object of the present invention is to determine whether or not dust is generated by the traveling of the own vehicle.

In order to solve the above problems, for example, the configuration described in the claims is adopted. The present application includes a plurality of means for solving the above problems. For example, a drive wheel, a vehicle body frame mounted on the drive wheel, and a vehicle body frame installed on the vehicle body frame, and the drive wheel is mounted on a road surface. Installed on a work vehicle equipped with a front sensor that detects the road surface condition before the wheel contact point that touches the ground and a rear sensor that is installed on the vehicle body frame and detects the road surface condition behind the wheel ground point. The road surface condition detection device is composed of a controller connected to each of the front sensor and the rear sensor, and the controller is a front output and a front output output from the front sensor. The rear output output from the rear sensor is acquired, the difference between the output values of the front output and the rear output is calculated, and the difference in the output values and the dust determination threshold for determining whether or not dust is generated are set. By comparison, when the difference between the output values is equal to or greater than the dust determination threshold value, it is determined that the road surface is in a state where dust is likely to be generated.

According to the present invention, it is possible to determine whether or not dust is generated by the traveling of the own vehicle. Issues, configurations and effects other than the above will be clarified by the following description of the embodiments.

External view of the dump truck according to the first embodiment A diagram showing a state in which a dump truck is running while hoisting dust. Hardware configuration diagram of the dump truck according to the first embodiment Functional block diagram of the road surface condition detection device and the road surface condition monitoring device according to the first embodiment Flowchart showing the flow of dust detection processing The figure which shows the laser incident angle αi The figure which shows the calculation method of the laser incident angle αi in the case where the angle formed by a scan surface and a road surface is vertical. A diagram showing the relationship between the front left measurement point and the rear left measurement point, the vehicle speed, and the scan distance Ti. A diagram showing the relationship between the front left measurement point and the rear left measurement point, the vehicle speed, and the scan distance Ti. The figure which shows the laser incident angle in the state which the body frame is pitching External view of the dump truck according to the second embodiment Hardware configuration diagram of the dump truck according to the second embodiment Functional block diagram of the road surface condition detection device and the road surface condition monitoring device according to the second embodiment Hardware configuration diagram of the dump truck according to the third embodiment Functional block diagram of the road surface condition detection device and the road surface condition monitoring device according to the third embodiment The figure which shows the example of the mounting position of a rider

Hereinafter, embodiments of the present invention will be described with reference to the drawings and the like. The following description shows specific examples of the contents of the present invention, and the present invention is not limited to these descriptions, and various works by those skilled in the art will be made within the scope of the technical ideas disclosed in the present specification. It can be changed and modified. Further, in all the drawings for explaining the present invention, those having the same function may be designated by the same reference numerals, and the repeated description thereof may be omitted.

In the following description, a dump truck 1 traveling in the mine will be used as an example of the work vehicle, but the work vehicle is not limited to the dump truck 1, and may be a grader or a wheel loader.

<First Embodiment>
In the first embodiment, one LIDAR (Light Detection and Ringing) is used, and a set of measurement data that can be regarded as having the same laser incident angle is extracted from the measurement results obtained in one scan cycle, and the reflected light intensity is determined. In this embodiment, it is determined whether or not dust is generated based on the difference. LIDAR is a sensor that irradiates an object with a laser, receives the reflected light of the irradiated laser, and outputs the reflected light intensity of the reflected light. Hereinafter, the first embodiment will be described with reference to the drawings.

FIG. 1 is an external view of the dump truck 1 according to the first embodiment. FIG. 2 is a diagram showing a state in which the dump truck 1 is traveling while winding up the dust C.

As shown in FIG. 1, the dump truck 1 includes a left front wheel 5FL, a right front wheel 5FR, a left rear wheel 6RL, and a right rear wheel, and a vehicle frame (vessel frame) 2 is provided on these wheels via a suspension. A vessel 3 provided on the vehicle body frame 2 so as to be undulating is mounted. Further, a driver's cab 4 is provided above the front side of the vehicle body frame 2. Further, the GPS antenna 7 is provided on the deck at the front upper part of the vehicle body frame 2. The dump truck 1 is a rear-wheel drive vehicle, in which the left front wheel 5FL, the right front wheel 5FR are the driven wheels, the left rear wheel 6RL, and the right rear wheel are the driving wheels.

Further, the dump truck 1 is located near the left rear wheel 6RL on the left side surface of the vehicle body frame 2, and the left LIDAR 10L is placed at a position where the road surface A from the front to the rear of the wheel contact point of the left rear wheel 6RL is included in the scanning range. Be prepared. Further, the right LIDAR 10R is provided at a position near the right rear wheel on the right side surface of the vehicle body frame 2 and in which the road surface A from the front to the rear of the wheel contact point of the right rear wheel is included in the scanning range.

The left LIDAR 10L and the right LIDAR 10R are sensors provided by the dump truck 1 for measuring the road shoulder and surrounding obstacles. In the present embodiment, the LIDAR will be used, but a camera or a distance image sensor may be used. In the present embodiment, the dump truck 1 is provided with two units, a left LIDAR 10L and a right LIDAR 10R, but for the purpose of detecting whether the road surface A is in a state where dust C is likely to be generated, either the left LIDAR 10L or the right LIDAR 10R. You only need one. Therefore, in the following description, the process of detecting the road surface condition using only the output of the left LIDAR 10L will be described, but the road surface condition may be detected only by the output of the right LIDAR 10R. Hereinafter, the left LIDAR10L will be mainly described as an example, but the same effect can be obtained even if the left LIDAR10L is replaced with the right LIDAR10R.

As shown in FIG. 2, when the road surface A is dry soil, dust C is scattered between the left LIDAR 10L and the road surface by the rotation of the left rear wheel 6RL. The dust C is also wound up by the rotation of the left front wheel 5FL, which is a driven wheel, but more dust C is wound up by the left rear wheel 6RL and the right rear wheel, which are driving wheels. That is, more dust C is wound up behind the wheel contact point of the drive wheels, that is, the left rear wheel contact point C_RL. Therefore, in the present embodiment, the generation of dust C is determined based on the output difference of the left LIDAR 10L before and after the left rear wheel ground contact point C_RL.

In the left LIDAR 10L, the front end of the left road surface straight line XL formed by the intersection of the scan surface 11L consisting of the laser irradiation surface of the left LIDAR 10L and the road surface A is dumped from the left rear wheel ground contact point C_RL where the left rear wheel 6RL is in contact with the road surface A. It is attached to the vehicle body frame 2 so that it is in front of the truck 1 in the traveling direction and its rear end is behind the dump truck 1 in the traveling direction with respect to the left rear wheel ground contact point C_RL. The front left measurement point 11L_i in front of the left rear wheel contact point C_RL corresponds to the front measurement point, and the rear left measurement point 11L_i + m behind the left rear wheel contact point C_RL corresponds to the rear measurement point. That is, in the first embodiment, the left LIDAR 10L outputs both the front output and the rear output, and realizes the functions of both the front sensor and the rear sensor.

As a result, one left LIDAR10L measures the road surface A that is less or less affected by the dust C in front of the left rear wheel contact point C_RL, and winds up when traveling behind the left rear wheel contact point C_RL. The road surface A can also be measured through the dust C.

Further, if the left LIDAR 10L is installed under the dump truck 1, the detection surface of the left LIDAR 10L may become dirty. However, by attaching the dump truck 1 to the upper part of the left side surface, particularly the upper part of the left rear wheel 6RL on the left side surface, it is possible to suppress the frequency of the rising dust C adhering to the detection window of the left LIDAR 10L.

Similarly for the right LIDAR 10R, the right road surface straight line XR is from the right front measurement point 11R_i before the right wheel contact point where the right front wheel 5FR touches the road surface A to the right rear right behind the dump truck 1 in the traveling direction from the right wheel contact point. It is attached to the vehicle body frame 2 so as to have a position and a scan angle including the measurement point 11R_i + m.

FIG. 3 is a hardware configuration diagram of the dump truck 1. The dump truck 1 travels on a transport path provided in the mine. A control center 200 is installed in the mine to control the traffic of work vehicles traveling in the mine including the dump truck 1.

The dump truck 1 is a vehicle that communicates with the left LIDAR 10L, the right LIDAR 10R, the vehicle speed sensor 20, the road surface condition detection device 100, the self-position calculation device 120 that measures the position / orientation of the dump truck 1, and the control center 200. The communication device 130 is mounted.

The road surface condition detection device 100 includes a CPU 101, a ROM 102, a RAM 103, an HDD 104, an input interface (I / F) 105, and an output I / F 106, and is configured by using a controller (computer) in which these are connected to each other via a bus 107. Will be done. The control center 200 also includes the same configuration as described above. Further, in the present embodiment, the clock 108 is included as the hardware configuration of the road surface condition detection device 100. The clock 108 may be configured by using, for example, an RTC (Real-Time Clock) and may use Coordinated Universal Time as the time data, as long as the laser irradiation time can be measured.

The left LIDAR 10L and the right LIDAR 10R, the vehicle speed sensor 20, and the self-position calculation device 120 are connected to the input I / F 105 of the road surface condition detection device 100.

Further, an in-vehicle communication device 130 is connected to the output I / F 106 of the road surface condition detection device 100.

The self-position calculation device 120 may be configured by either GPS (Global Positioning System) 121 or IMU (Inertial Measurement Unit) 122, or a combination thereof. The present embodiment further includes a position corrector 123 which is equipped with GPS 121 and IMU 122 and corrects absolute coordinates (or referred to as external coordinates) output by GPS 121 by using the output of IMU 122. Since the vehicle body frame 2 is mounted on the wheels via the suspension, the vehicle body posture shifts due to the expansion and contraction of the suspension with respect to the road surface A. Therefore, the output of the IMU 122 includes the vehicle body posture data defined by the pitch angle, yaw angle, and roll angle of the vehicle body frame 2 with respect to the road surface A, and the vehicle body attitude data is output to the input I / F 105.

The control center 200 includes a center-side communication device 230 for receiving dust generation data from the vehicle-mounted communication device 130, and a road surface condition monitoring device 210 for monitoring the road surface condition based on the dust generation data.

FIG. 4 is a functional block diagram of the road surface condition detection device 100 and the road surface condition monitoring device 210. The left LIDAR 10L, the right LIDAR 10R, the vehicle speed sensor 20, and the self-position calculation device 120 are connected to the input I / F 105. The road surface condition detection device 100 includes an input I / F 105, a clock 108, a sensor output acquisition unit 111, a laser incident angle calculation unit 112, an output difference calculation unit 113, a dust generation determination unit 114, an output I / F 106, and the same point output identification. Includes part 117.

Further, the road surface condition detection device 100 includes a road surface condition data storage unit 115, a dust determination threshold value storage unit 116, and a sensor-to-sensor distance storage unit 142. These may be configured in a part area of the RAM 103 or the HDD 104.

The road surface condition monitoring device 210 includes an input I / F 211, a road surface condition map creation unit 212, and a road surface condition map storage unit 213.

The functions of each part of the road surface condition detection device 100 and the road surface condition monitoring device 210 will be described later with reference to the processing flow of FIG. Each part is composed of software that realizes each function and hardware shown in FIG. 3 in cooperation with each other.

As another configuration example, the road surface condition detection device 100 and the road surface condition monitoring device 210 may be configured by using one or more microcomputer devices that realize the functions shown in FIG.

Hereinafter, with reference to FIG. 5, a process of detecting the road surface condition, particularly the susceptibility to dust C, while the dump truck 1 is traveling will be described. FIG. 5 is a flowchart showing the flow of dust detection processing.

While the dump truck 1 is traveling, the left LIDAR 10L gradually changes the laser irradiation angle θi at a predetermined angle, for example, every 0.25 degrees, from the front to the back of the left rear wheel contact point C_RL. The laser is periodically and sequentially irradiated to form a fan-shaped scan range, and the reflected light from the measurement point on the road surface A is received.

In the first embodiment, the left LIDAR 10L measures the front left measurement point 11L_i in front of the left rear wheel ground contact point C_RL and the rear left measurement point 11L_i + m behind the left rear wheel contact point C_RL in one scan cycle. Here, the time difference between the scan times of the front left measurement point 11L_i and the rear left measurement point 11L_i + m is the measurement of the self position by the self position calculation device 120 in step S2 described later and the scan cycle of the vehicle body posture (for example, approximately once /). Since it is smaller than (seconds), the front left measurement point 11L_i and the rear left measurement point 11L_i + m will be described as being able to be measured at almost the same time, that is, in the same step S1 in the following description.

More specifically, in step S1, the laser is irradiated toward the front left measurement point 11L_i, and the laser reflected light reflected at the front left measurement point 11L_i is received. The left LIDAR 10L is the laser irradiation direction when the laser is irradiated toward the front left measurement point 11L_i, the measurement distance D from the left LIDAR 10L calculated based on the received laser reflected light to the front left measurement point 11L_i, and the laser. The reflected light intensity is measured and output to the road surface condition detection device 100. Similarly, the same applies to the rear left measurement point 11L_i + m (S1). The sensor output acquisition unit 111 acquires the front output obtained by measuring the front left measurement point 11L_i and the rear output obtained by measuring the rear left measurement point 11L_i + m.

In step S2, the self-position calculation device 120 calculates the self-position and outputs the self-position data. The sensor output acquisition unit 111 acquires the self-position data and the vehicle body posture data measured by the IMU 122 (S2).

In step S3, the sensor output acquisition unit 111 determines the position of the measurement point on the road surface A by the left LIDAR 10L in the external coordinate system from the self-position data and the vehicle body attitude data, the installation position and the mounting angle of the left LIDAR 10L with respect to the vehicle body frame 2. Is calculated, and the calculated position is associated with the laser reflected light intensity (corresponding to the sensor output) included in the front output and the rear output, and recorded in the road surface state data storage unit 115 (S3). The sensor output acquisition unit 111 acquires time data from the clock 108, associates the sensor output with the acquired time, and outputs the time data to the laser incident angle calculation unit 112. Therefore, the time data is linked to the sensor output after this step. The time when the sensor output acquisition unit 111 acquired the sensor output from the left LIDAR 10L and the right LIDAR 10R, the time when each of the left LIDAR 10L and the right LIDAR 10R irradiated the laser, and the time when each of the left LIDAR 10L and the right LIDAR 10R output the sensor output. Although the times are strictly different, the time difference between these times is slightly different from the time when the behavior of the dump track 1 changes, and these times are regarded as the same time when considering the behavior of the dump track 1. You may. Therefore, in the present embodiment, the time data associated with the sensor output by the sensor output acquisition unit 111 will be described as the same as the time when the left LIDAR 10L and the right LIDAR 10R each irradiate the laser and measure the road surface.

In step S4, the laser incident angle calculation unit 112 obtains the left road surface straight line XL, which is the line of intersection between the scan surface 11L of the left LIDAR 10L and the road surface A, from the measurement point cloud composed of a set of a plurality of measurement points. Then, the laser incident angle calculation unit 112 determines the laser incident angle αi from the angle formed by the left road surface straight line XL and the straight line from the sensor origin to each measurement point, and the angle formed by the scan surface 11L and the road surface A at the front left measurement point 11L_i. Is calculated and added to the laser reflected light intensity in step S3, and the laser incident angle αi and the measurement distance D on the road surface at the measurement point by the left LIDAR 10L are recorded in the road surface state data storage unit 115 (S4).

FIG. 6 shows a method of calculating the laser incident angle αi.

As shown in FIG. 6, the laser incident angle αi is defined as the angle formed by the normal line ε of the road surface A (which is a flat surface) and the laser irradiated to the road surface A. The distance from the laser irradiation point of the left LIDAR 10L to the front left measurement point 11L_i and the rear left measurement point 11L_i + m is expressed as the measurement distance D.

As shown in FIG. 7, assuming that the left road surface straight line XL obtained from the measurement point cloud on the road surface A measured by the left LIDAR 10L is XL: y = ax + b, the road surface inclination β with respect to the X axis of the sensor coordinate system is calculated by the following equation ( It can be expressed by 1).

Therefore, the laser incident angle αi with respect to the road surface A at the front left measurement point 11L_i of the laser irradiation angle θi can be expressed by the following equation (2).

In step S5, the same point output specifying unit 117 acquires the vehicle speed V measured by the vehicle speed sensor 20 via the input I / F 105. Then, the same point output specifying unit 117 is the difference between the position of the measurement point and the measurement distance D from the front left measurement point 11L_i and the rear left measurement point 11L_i + m among the measurement points stored in the road surface condition data storage unit 115. , And a set of measurement points where the difference between the laser incident angles αi is equal to or less than the threshold value is extracted (S5).

In the same point output specifying unit 117, the value obtained by multiplying the time from the first time when the front left measurement point 11L_i is measured to the second time when the rear left measurement point 11L_i + m is measured by the vehicle speed V is the same as or the same as the distance between the sensors. The pair of the front left measurement point 11L_i and the rear left measurement point 11L_i + m within the range that can be regarded as is specified.

8 and 9 are diagrams showing the relationship between the front left measurement point 11L_i and the rear left measurement point 11L_i + m, the vehicle speed V [m / s], and the scan distance Ti. When the left LIDAR 10L is installed downward at the height H [m] position of the upper part of the left front wheel as shown in FIGS. 8 and 9, the measurement in the laser irradiation angle θi direction of the dump truck 1 traveling on the plane at the vehicle speed V is measured. After 2 Htan θ / V, in the measurement in the laser irradiation angle −θi + m direction, the position of the measurement point, the measurement distance D (see FIG. 6), and the laser incident angle αi (see FIG. 6) are all the same. The pair will be extracted in step S5.

Next, in step S6, the output difference calculation unit 113 obtains the difference in laser reflected light intensity for each set of measurement points extracted in step S5. Here, the amount of dust is estimated by the difference in the reflected light intensity when the road surface A (laser reflectance) at the measurement point, the measurement distance D, and the laser incident angle αi are the same, the laser reflected light intensity is on the optical path. This is because it depends on the amount of light attenuation by the dust C, and the larger the amount of dust C, the larger the amount of light attenuation and the smaller the intensity of the reflected light from the laser. By using this characteristic, it is possible to determine the magnitude of the amount of dust based on the difference in the intensity of the reflected light from the laser.

In step S7, the dust generation determination unit 114 determines whether the difference in laser reflected light intensity obtained in step S6 is equal to or greater than the dust generation threshold stored in advance in the dust determination threshold storage unit 116 (S7). The dust generation threshold may be set based on, for example, the amount of attenuation of the laser reflected light intensity when the amount of dust generated is such that the recognition performance of the external sensor is reduced.

If the difference in laser reflected light intensity obtained in step S6 is equal to or greater than the dust generation threshold value (S7 / Yes), the dust generation determination unit 114 serves as a basis for calculating the difference in output values that exceeds the dust generation determination threshold value. The self-position data associated with at least one of the left measurement point 11L_i or the rear left measurement point 11L_i + m is read out. Then, data indicating that dust is generated, for example, a flag having a value of "1" when it is determined that dust has been generated, and a position of a measurement point where the difference in laser reflected light intensity is equal to or greater than the dust threshold. Dust generation data including (corresponding to the above-readed self-position data) is generated and output to the in-vehicle communication device 130. The dust generation data may include the laser incident angle αi, the measurement distance D, and the laser reflected light intensity. The in-vehicle communication device 130 transmits dust generation data to the control center 200.

The center-side communication device 230 of the control center 200 receives the dust generation data. In the road surface condition monitoring device 210, the road surface condition map creation unit 212 acquires the dust generation data via the input I / F 211, reads the position of the measurement point from the dust generation data, and maps the position of the measurement point to the road surface condition map. create. Then, the road surface condition map creation unit 212 writes the road surface condition map in the road surface condition map storage unit 213.

As described above, in the left LIDAR10L, the laser irradiation angle θi is gradually changed for each predetermined angle to scan the measurement point, and the distance to the road surface A for each predetermined angle and the laser reflection are obtained. Measure the light intensity. Therefore, when the left LIDAR 10L is installed on the vehicle body frame 2 so that the scanning surface 11L of the left LIDAR 10L is parallel to the traveling direction of the dump truck 1, the measurement distance D of the measurement point and the laser incident angle αi are the same. There is a set of measurement points, which leads to improved reliability of dust detection.

FIG. 10 is a diagram showing a laser incident angle αi in a state where the vehicle body frame 2 is pitched. As shown in FIG. 10, even when the vehicle body frame 2 has an angle P with respect to the road surface A and pitches, the scan surface 11L of the left LIDAR 10L is parallel to the traveling direction of the dump truck 1. When the left LIDAR 10L is installed on the vehicle body frame 2, there is a set of measurement points in which the measurement distance D of the measurement points and the laser incident angle αi are the same.

In the above, since the influence of the dust C on the laser reflected light intensity differs depending on the laser incident angle αi and the measurement distance D, it is preferable that the dust determination threshold value in S7 is changed depending on the laser incident angle αi and the measurement distance D.

Further, in step S7, it was determined that dust C was generated if there was even one set in which the difference in laser reflected light intensity was equal to or greater than the dust generation threshold value. However, by comparing the average value or the maximum value with the threshold value, it was determined that dust C was generated. The generation of dust may be determined.

According to the present embodiment, the road surface condition is dust C due to the difference in the reflected light intensity of the radar from the measurement points on the road surface A in front of the wheel contact point of the drive wheel of the work vehicle and the road surface A behind. It is possible to determine whether or not the condition is likely to occur. Then, the road surface condition map is created by transmitting the determination result to the control center 200. As a result, the operator can respond by allocating a sprinkler vehicle by referring to the road surface condition map and restricting the traveling in the dust generation area.

In the first embodiment, the position of the measurement point is obtained based on the position and orientation of the dump truck 1, and the road surface A at the same point is measured before and after the wheel passes, respectively, and the laser reflected light intensity is determined. The generation of dust C was determined based on the difference. However, if the road surface A is flat and the characteristics with respect to the laser such as reflectance can be considered to be uniform at any point, it is not necessary to measure the same point, and a set of measurement in which the laser incident angle αi and the measurement distance D are almost the same. On the other hand, the generation of dust C may be determined based on the difference in laser reflected light intensity. This eliminates the need to record and use past measurement data such as laser reflected light intensity, and makes it possible to detect the generation status of dust C in real time.

<Second Embodiment>
In the second embodiment, it is determined whether or not dust C is generated based on the difference in the laser reflected light intensity of the measurement data obtained by scanning the same point twice at different times using a plurality of LIDARs. It is an embodiment.

FIG. 11 is an external view of the dump truck 1a according to the second embodiment. In the second embodiment, the front lidar21F for measuring the road surface A in front of the left rear wheel contact point C_RL (in front of the left front wheel contact point C_FL in this embodiment) and behind the left rear wheel contact point C_RL. A plurality of lidars including a rear lidar 21R for measuring the road surface A are provided. In the example of FIG. 11, the front LIDAR 21F is installed on the deck installed at the front of the vehicle body frame 2. Further, the rear LIDAR 21R is a side surface of the vehicle body frame 2 and is installed behind the left rear wheel 6RL.

FIG. 12 is a hardware configuration diagram of the dump truck 1a according to the second embodiment. FIG. 13 is a functional block diagram of the road surface condition detection device 100 and the road surface condition monitoring device 210 according to the second embodiment. In the second embodiment, the front LIDAR 21F and the rear LIDAR 21R are each connected to the input I / F 105. The front LIDAR 21F and the rear LIDAR 21R may be sensors in which the laser irradiation direction is one direction, that is, only one point on the road surface can be measured.

Then, based on the measurement data (front output and rear output) output by each of the front LIDAR 21F and the rear LIDAR 21R, as in the first embodiment, the front LIDAR 21F and the rear LIDAR 21R in which the same point output specifying unit 117 is composed of different sensors. From the measurement data output by each, a set of measurement data measured at the same point on the road surface A is specified. The output difference calculation unit 113 calculates the difference between the measurement data (front output and rear output) included in this set, and the dust generation determination unit 114 determines the generation of dust based on the difference. The road surface condition detection device 100 according to the present embodiment may have the same configuration as the road surface condition detection device 100 of the first embodiment, and the difference is that the same point output identification unit 117 extracts from the road surface condition data storage unit 115. In the first embodiment, the measurement data to be measured is a set of measurement data obtained by measuring the same point at different times by the same sensor, whereas in the second embodiment, different sensors measure the same point at different times. This is a set of measurement data obtained in this way. However, the processing in the other road surface condition detection device 100 is the same as that in the first embodiment, except that the sensors that output the measurement data of each set are different.

According to the present embodiment, the generation of dust C is determined based on the data measured at the same point on the road surface A at different times as in the first embodiment by using a plurality of sensors whose laser irradiation direction is one direction. Can be done.

<Third Embodiment>
The third embodiment is an embodiment in which the rear LIDAR 21R is actively measured at the same point as the point measured by the front LIDAR 21F, and it is determined whether or not dust C is generated. The lidar used in the first embodiment and the second embodiment has been described using a sensor that outputs data at regular intervals, but the lidar used in the present embodiment sends a signal (command) instructing laser irradiation. It is a sensor that receives and irradiates a laser.

Since the appearance of the dump truck 1b according to the third embodiment is the same as that of the second embodiment, the description thereof will be omitted.

A third embodiment will be described with reference to FIGS. 14 and 15. FIG. 14 is a hardware configuration diagram of the dump truck 1b according to the third embodiment. FIG. 15 is a functional block diagram of the road surface condition detection device 100b and the road surface condition monitoring device 210 according to the third embodiment.

As shown in FIG. 14, in the present embodiment, the front LIDAR 21F and the rear LIDAR 21R are connected to the output I / F 106.

Further, as shown in FIG. 15, the road surface condition detection device 100b according to the present embodiment includes a timing calculation unit 141 and a laser irradiation signal generation unit 143.

In the present embodiment, each of the front LIDAR 21F and the rear LIDAR 21R measures one point on the road surface A. The front measurement point 22F of the front LIDAR 21F and the rear measurement point 22R of the rear LIDAR 21R are such that the straight line connecting the front measurement point 22F and the rear measurement point 22R is parallel to the traveling direction when the dump truck 1 is traveling straight. The front LIDAR 21F and the rear LIDAR 21R are attached to the vehicle body frame 2. The distance between the position where the front LIDAR 21F is attached to the vehicle body frame 2 and the position where the rear LIDAR 21R is attached to the vehicle body frame 2 (inter-sensor distance) is stored in the inter-sensor distance storage unit 142.

The timing calculation unit 141 acquires the sensor output of the forward LIDAR 21F associated with the time data obtained from the clock 108 via the input I / F 105. At the same time, the vehicle speed V is also acquired.

Next, the timing calculation unit 141 reads the inter-sensor distance from the inter-sensor distance storage unit 142. Assuming that the dump truck 1b travels on the horizontal plane and the scanning angles of the front LIDAR 21F and the rear LIDAR 21R are the same with respect to the horizontal plane or the vehicle body frame 2, the distance between the sensors is the front measurement point 22F and the rear on the horizontal plane. It may be regarded as the same as the interval (scan distance) Ti of the measurement points 22R. Therefore, in the present embodiment, the distance between the sensors will be described as the scan distance Ti.

Assuming that the vehicle speed V of the dump truck 1 is the vehicle speed V, the timing calculation unit 141 calculates the timing lag Δt by dividing the scan distance Ti by the vehicle speed V, and corresponds to the timing lag Δt from the first time when the front LIDAR 21F measures the front measurement point 22F. The second time, which is later in time, is calculated as the laser irradiation timing of the rear LIDAR21R, and the calculation result is output to the laser irradiation signal generation unit 143.

The laser irradiation signal generation unit 143 measures the road surface A at the second time on the rear LIDAR 21R via the output I / F 106, that is, outputs a signal for irradiating the laser.

The rear LIDAR 21R outputs the sensor output obtained by measuring the road surface A at the second time to the input I / F 105.

The road surface condition data storage unit 115 stores the measurement data measured on the road surface by the front LIDAR 21F at the first time and the measurement data measured by the rear LIDAR 21R at the same point with a Δt time delay at any time. Therefore, the same point output specifying unit 117 extracts a set of measurement data measured at the same point at different times and outputs the set to the output difference calculation unit 113. Subsequent processing is the same as in the first and second embodiments. The laser irradiation signal generation unit 143 also outputs a signal for irradiating the front LIDAR 21F with the laser at the first time. The method in which the laser irradiation signal generation unit 143 determines the first time may be arbitrary, and the feature of the present embodiment is that the second time is determined based on the first time.

According to the present embodiment, the accuracy of determining the generation of dust can be improved by actively controlling the rear LIDAR 21R so as to measure the same point as the point measured by the front LIDAR 21F.

The present invention is not limited to the above-described embodiment, and includes various modifications. The above-described embodiments are for explaining the present invention in an easy-to-understand manner, and the present invention is not necessarily limited to those having all the configurations described.

For example, when the road surface condition detection device 100 executes the dust detection process using both the left LIDAR 10L and the right LIDAR 10R, if it is determined that dust is generated in at least one of the left LIDAR 10L or the right LIDAR 10R, It may be configured to output dust generation data.

Further, in the above, the clock 108 is provided and the above processing is executed using the time data, but the time data may be a time in a state where there is an offset such as the startup time of the CPU 101. In addition to the clock of the CPU 101, a time stamp of data output from each LIDAR may be used. In this case, the time data is the data from the sensor activation.

Further, in the above, the vehicle speed sensor 20 is provided and the same point is specified using the vehicle speed V. However, when the self-position calculation device 120 is present, the same point is specified based on the self-position calculated by the self-position calculation device 120. May be done. In this case, the vehicle speed sensor is not essential.

Further, in the present embodiment, the front and rear of the wheel contact point of the drive wheel is measured by utilizing the characteristic that dust C is more likely to be generated from the drive wheel than the driven wheel. May be compared to detect the generation status of dust C.

Further, a rider as a rear sensor, for example, the left rider 10L in the first embodiment is attached to the vehicle body frame 2 so that the front and rear of the left rear wheel contact point C_RL can be measured. An example of the mounting position may be the rear part of the deck or the side surface of the hydraulic oil tank, as shown in FIG. 16, for example. It may also be the rear part of the vehicle body frame 2.

1: Dump truck 100: Road surface condition detection device 120: Self-position calculation device 130: In-vehicle communication device 200: Control center 210: Road surface condition monitoring device 230: Center side communication device A: Road surface

Claims (9)

A drive wheel, a vehicle body frame mounted on the drive wheel, a front sensor installed on the vehicle body frame and detecting a road surface state before the wheel contact point where the drive wheel touches the road surface, and the vehicle body frame. A road surface condition detection device mounted on a work vehicle equipped with a rear sensor for detecting a road surface condition behind the wheel contact point.
The road surface condition detection device is composed of a controller connected to each of the front sensor and the rear sensor.
The controller
The front output output from the front sensor and the rear output output from the rear sensor are acquired, and the rear output is acquired.
Calculate the difference between the output values of the front output and the rear output,
Compare the difference in the output values and the dust determination threshold value for determining whether dust is generated, and compare them.
When the difference between the output values is equal to or greater than the dust determination threshold value, it is determined that the road surface is in a state where dust is likely to be generated.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 1.
The drive wheels are the rear wheels of the work vehicle.
The controller acquires a front output that detects a road surface condition before the wheel contact point of the rear wheel and a rear output that detects a road surface condition behind the wheel contact point of the rear wheel.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 1.
Each of the front sensor and the rear sensor is configured by using a sensor that irradiates a laser toward the road surface, receives the reflected light of the irradiated laser, and outputs the reflected light intensity of the reflected light.
The rear sensor is installed at the same height as the height from the front sensor to the road surface.
The controller calculates the difference between the reflected light intensity indicated by the front output and the reflected light intensity indicated by the rear output as the difference between the output values.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 3.
The front sensor is installed in front of the wheel contact point on the vehicle body frame.
The rear sensor is installed behind the wheel contact point on the vehicle body frame.
In the controller, the front output obtained by measuring the front measurement point on the road surface in front of the wheel contact point by the front sensor and the first time when the front sensor measures the front measurement point At a late second time, the rear sensor acquires the rear output obtained by measuring the rear measurement point on the road surface behind the wheel contact point.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 4.
Each of the front sensor and the rear sensor is a sensor that periodically irradiates a laser.
The controller is further connected to a vehicle speed sensor mounted on the work vehicle to measure the vehicle speed of the work vehicle, and includes a clock for measuring the irradiation time of the laser irradiated periodically.
The distance between the sensors from the position of the front sensor attached to the vehicle body frame to the position of the rear sensor attached to the vehicle body frame is stored.
The value obtained by multiplying the time from the first time when the front output is measured to the second time when the rear output is measured by the vehicle speed acquired from the vehicle speed sensor is the same as the distance between the sensors of the front sensor. Identify the set of outputs and the outputs of the rear sensor
Calculate the difference between the front output and the rear output included in the set.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 4.
The work vehicle further includes a vehicle speed sensor that measures the vehicle speed of the work vehicle.
Each of the front sensor and the rear sensor is a sensor that irradiates the laser to perform measurement in response to a signal that irradiates the laser.
The controller is further connected to the vehicle speed sensor and includes a clock for measuring the irradiation time at which the front sensor and the rear sensor irradiate the laser.
The timing lag is calculated by dividing the distance between the position of the front sensor attached to the vehicle body frame and the position of the rear sensor attached to the vehicle body frame by the vehicle speed obtained from the vehicle speed sensor.
The second time, which is a time corresponding to the timing lag from the first time measured by the front sensor, is calculated as the timing at which the rear sensor irradiates the laser.
At the second time, an irradiation signal for irradiating the rear sensor with a laser is generated and output to the rear sensor.
The rear sensor receives the irradiation signal and irradiates the laser.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 1.
Each of the front sensor and the rear sensor sequentially irradiates the road surface with a laser from the front to the rear, and the vehicle body is oriented so that the scanning surface formed by the laser irradiation surface is parallel to the traveling direction of the work vehicle. Composed using one rider installed on the frame,
The front end of the road surface straight line where the scan surface of the rider and the road surface intersect is in front of the wheel contact point, and the rear end of the road surface straight line is behind the wheel contact point.
The controller measures the front output obtained by measuring the front measurement point before the wheel contact point during one scan of the rider, and the laser when measuring the front measurement point with respect to the road surface. The rear output obtained by measuring the rear measurement point behind the wheel ground contact point at the same laser incident angle as the incident angle is acquired.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 7.
The controller is further connected to a vehicle speed sensor mounted on the work vehicle to measure the vehicle speed of the work vehicle, and includes a clock for measuring the irradiation time of the laser irradiated periodically.
The rider outputs the result of measuring the front measurement point at the first time as the front output, and outputs the result of measurement at the second time after the drive wheels pass the front measurement point as the rear output. Output and
The controller
The distance between the sensors from the position of the front sensor attached to the vehicle body frame to the position of the rear sensor attached to the vehicle body frame is stored in advance.
The value obtained by multiplying the time from the first time when the front output is measured to the second time when the rear output is measured by the vehicle speed acquired from the vehicle speed sensor is the same as the distance between the sensors of the front sensor. Identify the set of outputs and the outputs of the rear sensor
Calculate the difference between the front output and the rear output included in the set.
A road surface condition detection device characterized by the above. The road surface condition detecting device according to claim 1.
The work vehicle includes a self-position calculation device that calculates its own position and outputs self-position data.
An in-vehicle communication device that transmits to a road surface condition monitoring device that monitors the road surface condition on which the work vehicle travels is further provided.
The controller is connected to each of the self-position calculation device and the in-vehicle communication device.
The controller
The self-position data of the work vehicle is acquired from the self-position calculation device, and the self-position data is acquired.
The road surface condition data associated with the front output, the rear output, and the self-position data is recorded.
When it is determined that the difference between the output values is equal to or greater than the dust determination threshold value, the front output or the rearward output, which is the basis for calculating the difference between the output values that exceeds the dust determination threshold value, is referred to. Read the self-position data associated with at least one of the outputs,
Dust generation data including the data indicating that the difference between the output values is equal to or greater than the dust determination threshold value and the read self-position data is generated and output to the in-vehicle communication device.
A road surface condition detection device characterized by the above.

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