Lidar system, information processing device and program

Abstract

To estimate a waiting time of a queue with a simple configuration.SOLUTION: An information processing device detects the number of waiting objects waiting in a waiting queue among objects existing within a prescribed first area S1 on the basis of point group data from a LiDAR device, calculates a transit time being a time interval when a second waiting object P2 among a plurality of waiting objects move from a first area S1 to a prescribed second area S2 after a first waiting object P1 among the plurality of waiting objects moves from the first area S1 to the second area S2, and calculates a waiting time in a waiting queue M from a value based on an integrated value of the number of waiting objects and the transit time.SELECTED DRAWING: Figure 4

Description

[Technical field]

[0001] The present invention relates to a LiDAR system, an information processing device, and a program. [Background technology]

[0002] A system has been proposed that acquires point cloud data detected three-dimensionally using a LiDAR (Light Detection And Ranging) device and measures the length of a queue from the acquired point cloud data. The system determines that people staying within a specified distance from a person staying at the same location are people who are part of the same queue. Patent Document 1 below discloses such a system. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2021-149836 Summary of the Invention [Problem to be solved by the invention]

[0004] When using a LiDAR device to estimate the waiting time of a queue, the waiting time can be estimated by constantly tracking the objects in the queue and measuring the time it takes for an object at the end of the queue to reach the front of the queue. However, complex algorithms are required to improve the accuracy of this estimation.

[0005] Therefore, the present invention provides a LiDAR system, an information processing device, and a program that can estimate the waiting time of a queue with a simple configuration. [Means for solving the problem]

[0006] In order to solve the above problems, the LiDAR system of the present invention comprises a LiDAR device that supplies a signal related to point cloud data obtained by measuring the distance to an object in a specified measurement area, and an information processing device, and the information processing device detects the number of waiting objects waiting in a waiting line among the objects present in a specified first area based on the point cloud data, calculates a passing time, which is the time interval from when a first waiting object among the multiple waiting objects moves from the first area to a specified second area to when a second waiting object among the multiple waiting objects moves from the first area to the second area, based on the point cloud data, and calculates the waiting time in the first area from a value based on an integrated value of the number of waiting objects and the passing time.

[0007] The LiDAR system calculates the waiting time of the queue by multiplying the number of waiting objects in the first area by the time it takes for the objects to pass from the first area to the second area. Therefore, it is not necessary to track all waiting objects from the beginning to the end of the queue, which can simplify the processing of the information processing device.

[0008] In addition, in the above LiDAR system, the information processing device may store a predetermined number of the passing times, calculate a statistical passing time which is a statistical value of the stored passing times, and calculate a waiting time in the waiting line from a value based on an integrated value of the number of waiting objects and the statistical passing time.

[0009] With this configuration, the LiDAR system calculates the waiting time by multiplying the number of waiting objects in the first area by the average time it takes for a plurality of objects to pass from the first area to the second area, etc. Therefore, the variation and large fluctuations in the waiting time are suppressed, and the waiting time can be calculated appropriately.

[0010] In addition, in the LiDAR system, the information processing device may count, among the objects in the first area, objects whose moving speed within a predetermined determination time is equal to or greater than a first threshold and equal to or less than a second threshold as the number of pre-detection objects.

[0011] With this configuration, the LiDAR system determines that an object that is moving within a predetermined speed range among objects present in the first area is a waiting object. Therefore, it is possible to prevent an object that is simply stationary outside the waiting line in the first area or an object that simply passes through the first area from being counted as a waiting object. Therefore, it is possible to appropriately calculate the waiting time.

[0012] In the LiDAR system, the information processing device may set the determination time based on the passing time.

[0013] With this configuration, the LiDAR system determines an object that is moving within a predetermined speed range during the time it takes for the object to pass from the first area to the second area as a waiting object, and can therefore appropriately determine the waiting object.

[0014] The information processing device of the present invention has a sensor interface connected to a LiDAR device that supplies a signal related to point cloud data obtained by measuring the distance to an object in a specified measurement area, detects the number of waiting objects, which is the number of moving objects present in a specified first area, calculates a passing time, which is the time it takes for the moving object to enter a specified second area from the first area and exit the second area, based on the point cloud data, and calculates the waiting time in the first area based on the number of waiting objects and the passing time.

[0015] The information processing device calculates the waiting time of the queue by multiplying the number of waiting objects in the first area by the time it takes for the objects to pass from the first area to the second area, which eliminates the need to track all waiting objects from the beginning to the end of the queue, making it possible to simplify the processing of the information processing device.

[0016] The program of the present invention is stored in a memory of an information processing device connected to a LiDAR device that supplies a signal related to point cloud data obtained by measuring a distance to an object in a predetermined measurement area, The number of waiting objects, which is the number of moving objects present in a specified first area, is detected, and a passing time, which is the time it takes for the moving object to enter a specified second area from the first area and exit the second area, is calculated based on the point cloud data, and a waiting time in the first area is calculated based on the number of waiting objects and the passing time.

[0017] The information processing device calculates the waiting time of the queue by multiplying the number of waiting objects in the first area by the time it takes for the objects to pass from the first area to the second area, which eliminates the need to track all waiting objects from the beginning to the end of the queue, making it possible to simplify the processing of the information processing device.

[0018] Another embodiment of the present invention is also a LiDAR system including a LiDAR device that detects an object and a speed of the object in a predetermined first area, and an information processing device that outputs a waiting time of a queue by inputting information from the LiDAR, the information processing device outputs the waiting time as short when an object existing around the predetermined area among the objects constituting the queue is moving fast, and outputs the waiting time as long when an object existing around the predetermined area among the objects constituting the queue is moving slow.

[0019] Another embodiment of the present invention is also a LiDAR system including a LiDAR device that detects an object in a predetermined first region and the speed of the object, and an information processing device that outputs a queue waiting time by inputting information from the LiDAR, the information processing device outputs a short waiting time when an object that is outside the queue and in the first region moves at a speed equal to or less than a first threshold or equal to or more than a second threshold, and outputs a long waiting time when the object moves at a speed faster than the first threshold and less than the second threshold. Effect of the Invention

[0020] As described above, according to the present invention, a LiDAR system, an information processing device, and a program capable of measuring the waiting time of a queue with a simple configuration are provided. [Brief description of the drawings]

[0021] [Figure 1] FIG. 1 is a diagram illustrating an installation state of a LiDAR system according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a block diagram showing the configuration of the LiDAR system shown in FIG. 1. [Diagram 3] 3 is a flowchart showing an operation of the information processing device shown in FIG. 2. [Figure 4] 3 is a diagram illustrating an operation of the information processing device shown in FIG. 2 for setting a standby time. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022] Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings. The embodiments exemplified below are intended to facilitate understanding of the present invention, and are not intended to limit the present invention. The present invention can be modified and improved without departing from the spirit of the present invention.

[0023] The LiDAR system according to the embodiment predicts the waiting time at the rear of the waiting line from the number of waiting objects constituting the waiting line in a predetermined first area and the passing time, which is the frequency at which the waiting objects pass through a predetermined second area. Here, the waiting object is an object that satisfies a predetermined condition among the objects detected by the LiDAR. Specifically, the predetermined condition is whether or not the moving speed in a certain period of time is included in a certain speed range. This certain speed range is set to be slower than an object that is walking normally and faster than an object that is completely stationary. As a result, the determination of the waiting object does not require complex processing such as tracking the moving trajectory of the object, and the system can be realized with a simple configuration. In addition, the moving speed here is an index indicating the frequency of exiting from the waiting queue. In order to calculate this moving speed, the LiDAR system tracks only the objects that pass from the first area to the predetermined second area among the objects constituting the waiting line. As a result, it is not necessary to track all the objects constituting the waiting line to calculate the waiting time, and the system can be realized with a simple configuration.

[0024] Fig. 1 shows an example of a LiDAR system 1 according to this embodiment being applied to a real environment, such as a waiting line at a security checkpoint at an airport. As shown in Fig. 1, the LiDAR system 1 scans a measurement area S to acquire point cloud data. The LiDAR system 1 detects objects P1 to Pn included in a first area S1 arbitrarily set within the measurement area S.

[0025] Fig. 2 shows the configuration of the LiDAR system 1 according to this embodiment. As shown in Fig. 2, the LiDAR system 1 mainly includes an information processing device 110, a LiDAR device 120, and a monitor device 130. The information processing device 110 mainly includes a memory 111, a sensor interface 112, and a monitor interface 113. The sensor interface 112 is electrically connected to the LiDAR device 120. The monitor interface 113 is electrically connected to the monitor device 130.

[0026] The LiDAR device 120 irradiates the measurement area S with light and acquires information on the coordinates of the detection points detected in the measurement area S in accordance with a control signal from the information processing device 110. In this embodiment, the LiDAR device 120 manipulates light two-dimensionally in the measurement area S to measure the distance between the detection point where the light is reflected and the LiDAR device 120 itself. The LiDAR device 120 calculates the coordinates of the detection points based on the measured distances and the like. When the LiDAR device 120 scans the measurement area S once, it generates a signal related to point cloud data indicating the coordinates of the detection points for each frame as a measurement result and supplies the signal to the information processing device 110.

[0027] For example, the LiDAR device 120 includes a light source that emits light and a sensor that receives reflected light from a detection point. The number, wavelength, scanning method, etc. of the light sources and sensors included in the LIDAR device 120 are not limited to a specific configuration. The LiDAR device 120 may also irradiate the entire measurement area S with light at once.

[0028] The monitor device 130 displays various information in accordance with a control signal from the information processing device 110. For example, the monitor device 130 includes a liquid crystal monitor or an organic EL (Electro Luminescence) display.

[0029] The sensor interface 112 outputs a control signal for starting or ending measurement to the LiDAR device 120. In addition, the sensor interface 112 acquires a signal related to point cloud data from the LiDAR device 120.

[0030] The monitor interface 113 supplies the monitor device 130 with a signal related to an image to be displayed on the monitor device 130 .

[0031] The information processing device 110 may be, for example, a microcontroller, an integrated circuit such as an IC (Integrated Circuit), an LSI (Large-scale Integrated Circuit), or an ASIC (Application Specific Integrated Circuit), or a Numerical Control (NC) device. The information processing device 110 may also be a central processing unit such as a CPU (Central Processing Unit). The information processing device 110 executes a program stored in the memory 111 to realize various functions.

[0032] The memory 111 is, for example, a non-transitory storage medium, and is preferably a semiconductor recording medium such as a random access memory (RAM) or a read only memory (ROM), but may include any type of recording medium such as an optical recording medium or a magnetic recording medium. Note that the term "non-transitory" recording medium includes all computer-readable recording media except for transient, propagating signals, and does not exclude volatile recording media. The memory 111 prestores programs that cause the information processing device 110 to realize various functions. Furthermore, the memory 111 temporarily stores data generated by the execution of a program, data acquired from other devices, and the like.

[0033] Next, the operation of the LiDAR system 1 of this embodiment will be described. Fig. 3 is a flowchart showing the operation of the information processing device 110 in this embodiment. The information processing device 110 realizes the following operations by executing a program stored in the memory 111. As shown in Fig. 3, the flowchart includes steps SP11 to SP17.

[0034] (Step SP11) This step is a step in which the information processing device 110 acquires a signal related to point cloud data from the LiDAR device 120. For example, the information processing device 110 transmits a control signal for starting measurement to the LiDAR device 120 via the sensor interface 112 in accordance with a control signal from an external device (not shown) or an operation by an operator. Note that the information processing device 110 does not need to transmit the control signal to the LiDAR device 120 in step SP11 from the second time onward.

[0035] The LiDAR device 120 scans the measurement area S to measure the distance between the detection point and itself in accordance with a control signal from the information processing device 110, and acquires the coordinates of the detection point. When the LiDAR device 120 acquires a signal related to point cloud data indicating the coordinates of the detection point in one frame, the LiDAR device 120 proceeds to step SP12.

[0036] (Step SP12) This step is a step in which the information processing device 110 calculates the position and velocity of the object from the point cloud data.

[0037] The information processing device 110 detects an object from the point cloud data. In this embodiment, the information processing device 110 sets an area in which an object in the current frame exists in a predetermined projection plane onto which an object existing in the first area S1 is projected. The projection plane is a plane in which the measurement area S is viewed from a predetermined point. For example, the information processing device 110 detects an object by calculating a difference between the point cloud data and point cloud data obtained by measuring a background prepared in advance. The information processing device 110 may also detect an object by a clustering process. The method by which the information processing device 110 detects an object is not limited to a specific method, and a classifier constructed by machine learning of point cloud data may be used.

[0038] Fig. 4 shows a state in which objects detected by the information processing device 110 are set on the projection plane. In the example shown in Fig. 4, the information processing device 110 detects objects P1 to Pn and Q1 to Q3 that exist in a first area S1 that is arbitrarily set within the measurement area S, and sets them on the projection plane.

[0039] The information processing device 110 calculates the moving speed of the object during a predetermined determination period that is arbitrarily set. For example, the moving speed is calculated by dividing the difference between the position of the object in a first predetermined frame and the position of the object in a second frame that follows the first frame by the number of seconds between the frames.

[0040] When the information processing device 110 detects the moving speed of the object, the process proceeds to step SP13.

[0041] (Step SP13) This step is a step in which the information processing device 110 compares the moving speed of the detected object with a predetermined first threshold and a second threshold.

[0042] The information processing device 110 determines whether the moving speed of the object is equal to or higher than a first threshold and equal to or lower than a second threshold, and counts an object that falls within this speed range as a waiting object in step SP14, which will be described later.

[0043] The first threshold is a threshold for excluding objects that are not in a waiting line and are stationary in the first area. In this embodiment, the first threshold is, for example, 0 km / h, but is not particularly limited and can be set appropriately depending on the usage environment of the LiDAR system 1.

[0044] The second threshold is a threshold for excluding objects that are not in a waiting line in the first area and are passing through the first area. In this embodiment, the second threshold is, for example, 2 km / h, which is lower than the average walking speed of a human, but is not particularly limited and can be set appropriately depending on the usage environment of the LiDAR system 1.

[0045] After comparing the moving speeds of all objects in the first area with the first threshold and the second threshold, the information processing device 110 proceeds to step SP14.

[0046] (Step SP14) In this step, the information processing device 110 counts the waiting objects.

[0047] The information processing device 110 counts as waiting objects an object whose moving speed in a predetermined period is equal to or greater than a first threshold and equal to or less than a second threshold. An object waiting in line stays in place for a certain period, and starts moving as the line advances. The average speed of an object that constitutes the line from staying in place to moving is faster than an object that is completely stationary, and slower than an object that is walking normally. Therefore, an object that falls within this speed range can be counted as a waiting object that constitutes the line.

[0048] 4, objects P1 to Pn are counted as waiting objects. The waiting objects make up a waiting queue M. As soon as an inspection area (not shown) becomes available, object P1 located at the head of waiting queue M leaves the queue, and objects P2 to Pn proceed to the previous area in waiting queue M.

[0049] In Fig. 4, objects Q1 and Q2 are objects passing through the first area at a normal walking speed. Since objects Q1 and Q2 are moving at a speed equal to or higher than the second threshold, they are not counted as waiting objects.

[0050] 4, object Q3 is an object that is completely stationary within the first region. For example, object Q3 is stationary in the location for a certain period of time or more to check a guide display, to wait for a meeting, etc. Object Q3 is not counted as a waiting object because its speed is equal to or less than the first threshold.

[0051] When the information processing device 110 completes counting the waiting objects, the process proceeds to step SP15.

[0052] (Step SP15) This step is a step for calculating the time it takes for the waiting object to pass through a predetermined second area S2 contained within the first area S1.

[0053] The information processing device 110 sets a predetermined second area in the first area in advance according to an operation by an operator. In this embodiment, the second area is set to a size at least equal to that of one person and a rectangular shape, but is not limited thereto. The second area S2 may be a circle, a line, or a dot. The position of the second area may be anywhere in the first area, but it is preferable to set it at a position that must be passed through regardless of the length of the waiting line, for example, near the front of the waiting line.

[0054] The information processing device 110 calculates the passing time from the difference between the time when the first waiting object P1 moves from the first area S1 to the second area S2 and the time when the second waiting object P2 moves from the first area S1 to the second area S2. The information processing device 110 may also calculate the passing time of the second area from the difference between the time when the first waiting object P1 enters the second area S2 from the first area S1 and the time when the first waiting object P2 exits the second area S2. In this way, the passing time is synonymous with the time interval during which the waiting queue M moves, and is calculated by focusing on a part of the waiting queue M. This passing time is stored in the memory 111.

[0055] When the information processing device 110 has completed the calculation of the transit time, the process proceeds to step SP16.

[0056] (Step SP16) This step is a step for multiplying the total number of waiting objects by the passing time to calculate the waiting time of the waiting queue.

[0057] The information processing device 110 calculates the waiting time from the number of waiting objects calculated in step SP14 and the passing time calculated in step SP15. This calculation of the waiting time is executed when the number of waiting objects changes or when the passing time is updated, and may be skipped at other times. The calculated waiting time is stored in the memory 111 as a predicted waiting time. Also, when the passing time becomes 0, such as when the system is started, the calculation of this waiting time may be skipped, or the passing time at the previous system start-up may be set as the initial value, or the user may set the initial value in advance. There are.

[0058] When the information processing device 110 has completed calculation of the waiting time, the process proceeds to step SP17.

[0059] (Step SP17) In this step, the information processing device 110 outputs the predicted waiting time to the monitor device 130 and causes the monitor device 130 to display the predicted waiting time. Note that the monitor device 130 may display data such as the past predicted waiting time, the total number of waiting objects, and the passing time in addition to the current predicted waiting time.

[0060] After displaying the predicted waiting time on the monitor device 130, the information processing device 110 returns to step SP11. Note that the information processing device 110 may return to step SP11 after a predetermined time has elapsed since completing step SP17.

[0061] The LiDAR system 1 does not need to include the monitor device 130. In this case, the information processing device 110 may output the calculated predicted waiting time to an individual's smartphone. The information processing device 110 may also output the predicted waiting time to an airport website.

[0062] Furthermore, the information processing device 110 may set the determination period when calculating the moving speed of the object based on the passing time. For example, the determination period may be set to the same time as the passing time, or may be set to a period obtained by adding a predetermined time to the passing time. As described above, the passing time is an index indicating the frequency of exiting from the waiting queue, in other words, it indicates the time from when the waiting object in the waiting queue moves once to when it moves again. Therefore, by setting the determination period for calculating the moving speed based on the passing time, it is possible to reliably include both a state in which the waiting object is stationary and a state in which it is moving in the determination period, thereby improving the accuracy of counting the number of waiting objects.

[0063] Furthermore, the information processing device 110 may use a statistical passing time calculated based on the passing times of a predetermined number of objects instead of the passing time. The statistical passing time is, for example, the average value, median, mode, maximum value, minimum value, or the like of the multiple passing times.

[0064] Furthermore, the information processing device 110 may obtain the speed of an object from a measuring device that measures the speed of a moving object using the Doppler effect or the like.

[0065] The LiDAR system 1 may also be applied to waiting lines for taxis, waiting lines for attractions at amusement parks, waiting lines at restaurants, and the like.

[0066] In addition, the object to be detected is not limited to a human being, but may be a car. In this case, the LiDAR system 1 can be applied to car congestion, such as calculating the waiting time for a parking lot.

[0067] Moreover, the waiting time may be calculated using the length of the waiting queue or the area of ​​the waiting queue instead of the number of waiting objects.

[0068] Furthermore, when the LiDAR system 1 according to the present embodiment calculates the passing time, if the total number of waiting objects is constant and the speed of the object passing through the second region S2 increases, the passing time becomes shorter, and the predicted waiting time output by the information processing device 110 also becomes shorter. Conversely, if the total number of waiting objects is constant and the speed of the object passing through the second region S2 decreases, the passing time becomes longer, and the predicted waiting time output by the information processing device 110 also becomes longer. Therefore, it can be understood that the LiDAR system 1 according to the present embodiment is configured as follows.

[0069] When the number of objects constituting the matrix does not change, the information processing device 110 outputs a short waiting time when the speed of an object passing through the second region S2 among the objects constituting the matrix is ​​fast, and outputs a long waiting time when the speed of an object passing through the second region S2 among the objects constituting the matrix is ​​slow.

[0070] Also, assume that there is an object moving at a predetermined speed within the first area and outside the waiting line while the LiDAR system 1 according to this embodiment is counting the waiting objects. In this case, the waiting time output by the information processing device 110 changes depending on whether the moving speed of the object is within a certain range. Therefore, it can be understood that the LiDAR system 1 according to this embodiment is configured as follows.

[0071] The information processing device 110 outputs a short waiting time when an object outside the waiting queue and present within the first area S1 is moving at a speed equal to or less than the first threshold or equal to or more than the second threshold, and outputs a long waiting time when the object is moving at a speed faster than the first threshold and less than the second threshold.

[0072] The LiDAR system 1 having the above configuration calculates the waiting time at the rear of the waiting line from the number of waiting objects constituting the waiting line in a predetermined first area and the passing time which is the frequency at which the waiting objects pass through a predetermined second area. Therefore, the LiDAR system 1 can be realized with a simple configuration without the need to constantly track all the waiting objects constituting the waiting line. [Explanation of symbols]

[0073] 1. LiDAR system 110... Information processing device 111...Memory 112 Sensor Interface 113 Monitor Interface 120...LiDAR device 130...Display device

Claims

1. A LiDAR device that supplies a signal related to point cloud data obtained by measuring a distance to an object in a predetermined measurement area; An information processing device; Equipped with The information processing device includes: Detecting the number of objects waiting in a queue among the objects present in a predetermined first area based on the point cloud data; calculating a passing time, which is a time interval from when a first waiting object among the plurality of waiting objects moves from the first area to a predetermined second area to when a second waiting object among the plurality of waiting objects moves from the first area to the second area, based on the point cloud data; A waiting time in the waiting queue is calculated based on a value based on an integrated value of the number of waiting objects and the passing time. LiDAR system.

2. the information processing device stores a predetermined number of the passing times, and calculates a statistical passing time which is a statistical value of the stored plurality of the passing times; A waiting time in the waiting queue is calculated based on a value based on an integrated value of the number of waiting objects and the statistical passing time. The LiDAR system of claim 1 .

3. The information processing device counts, among the objects in the first area, an object whose moving speed within a predetermined determination time is equal to or less than a first threshold and equal to or more than a second threshold as the waiting object. The LiDAR system of claim 2.

4. The information processing device sets the determination time based on the passing time. The LiDAR system of claim 3.

5. A sensor interface is connected to a LiDAR device that supplies a signal related to point cloud data obtained by measuring a distance to an object in a predetermined measurement area, Detecting the number of objects waiting in a waiting queue among the objects present in a predetermined first area; calculating a passing time which is a time interval from when a first waiting object among the plurality of waiting objects moves from the first area to a predetermined second area to when a second waiting object among the plurality of waiting objects moves from the first area to the second area; An information processing device that calculates a waiting time within the first area from a value based on an integrated value of the number of waiting objects and the passing time.

6. The signal is stored in a memory of an information processing device connected to a LiDAR device that supplies a signal related to point cloud data obtained by measuring a distance to an object in a predetermined measurement area, Detecting the number of objects waiting in a waiting queue among the objects present in a predetermined first area; calculating a passing time which is a time interval from when a first waiting object among the plurality of waiting objects moves from the first area to a predetermined second area to when a second waiting object among the plurality of waiting objects moves from the first area to the second area; a program for calculating a waiting time in the first area based on a value based on an integrated value of the number of waiting objects and the passing time;

7. A LiDAR system including a LiDAR device that detects an object and a speed of the object in a predetermined first area, and an information processing device that outputs a waiting time of a queue by inputting information from the LiDAR, The information processing device includes: In the case where the number of objects constituting the matrix does not change, When the speed of the objects that compose the matrix and exist around a predetermined area is fast The standby time is shortened, When the speed of the objects that compose the matrix and exist around the predetermined area is slow The standby time is extended. LiDAR system

8. A LiDAR system including a LiDAR device that detects an object and a speed of the object in a predetermined first area, and an information processing device that outputs a waiting time of a queue by inputting information from the LiDAR, The information processing device includes: An object that is outside the matrix and within the first region is When moving at a speed equal to or less than the first threshold or equal to or greater than the second threshold The standby time is shortened, When the vehicle is moving at a speed faster than the first threshold and less than the second threshold The standby time is extended. LiDAR system

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