Loading determination device, program, and loading determination method

Abstract

To provide a loading determination device, a program, and a loading determination method that can determine the presence or absence of the loading on a vehicle with simple calculation.SOLUTION: A loading determination device (10) comprises: an acquisition unit (131) that acquires tire internal pressure data and vehicle speed data detected by a detector mounted on a vehicle; and a determination unit (132) that determines the presence or absence of the loading on the vehicle on the basis of the amplitude of the internal pressure data and the speed data. The determination unit (132) may determine the presence or absence of the loading on the vehicle by using a threshold determined in advance on the basis of the relationship between the amplitude and the speed of the vehicle.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present disclosure relates to a load determination device, a program, and a load determination method. [Background technology]

[0002] Conventionally, methods for estimating the load of a moving vehicle have been proposed. For example, Patent Document 1 discloses a method for calculating the change in load from the difference between the measured pressure and a reference pressure, and a tire model that has been devised in advance and relates the change in load to the change in pressure. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Special Publication No. 2013-536109 Summary of the Invention [Problem to be solved by the invention]

[0004] Here, in the method of Patent Document 1, processing is performed by focusing on the increase in tire internal pressure (the difference between the measured pressure and the reference pressure), but there is a risk that it may not be possible to appropriately respond to, for example, tire internal pressure adjustment before driving, and it is also susceptible to the influence of noise in the sensor measurement. Therefore, if it is attempted to accurately estimate the vehicle load taking these influences into account, the judgment logic becomes complicated.

[0005] In particular, when it comes to loading goods (minerals) in mining vehicles equipped with OR (Off the Road) tires, operational efficiency is emphasized, so the vehicles are often in two states: almost the maximum load (fully loaded) or almost zero load (empty). For such vehicles, there is a demand for a method to quickly determine whether the vehicle is loaded (fully loaded or empty) with sufficient accuracy by simple calculation using less data. Here, the mining vehicle is a dump truck or the like used in mining work, has a body that is significantly larger than that of a general truck, and travels on rough unpaved roads.

[0006] In view of the above circumstances, an object of the present disclosure is to provide a load determination device, a program, and a load determination method that can determine whether a vehicle is loaded or not by simple calculation. [Means for solving the problem]

[0007] (1) A load determination device according to an embodiment of the present disclosure includes: an acquisition unit that acquires tire internal pressure data and vehicle speed data detected by a detection device mounted on a vehicle; and a determination unit that determines whether the vehicle is loaded or not based on the amplitude of the internal pressure data and the speed data. With this configuration, it is possible to determine whether the vehicle is loaded or not through simple calculation.

[0008] (2) As an embodiment of the present disclosure, in (1), The determination unit determines whether the vehicle is loaded by using a predetermined threshold value based on a relationship between the amplitude and a speed of the vehicle. This configuration allows for rapid determination with sufficient accuracy.

[0009] (3) As an embodiment of the present disclosure, in (2), The judgment unit uses the threshold value determined using a model generated by machine learning using learning data in which the internal pressure data and the speed data, which are actual data, are explanatory variables and the presence or absence of the vehicle being loaded corresponding to the explanatory variables is the objective variable. With this configuration, a threshold value that enables more accurate judgment can be determined by a machine learning model using performance data.

[0010] (4) As an embodiment of the present disclosure, in any one of (1) to (3), The internal pressure data is acquired at predetermined intervals, The determination unit uses an average value of the speed data for the predetermined period as the speed of the vehicle. With this configuration, by appropriately setting the predetermined period, it is possible to achieve both accurate determination and reduced power consumption on the detection device side.

[0011] (5) As an embodiment of the present disclosure, in any one of (1) to (4), The determination unit outputs a signal indicating that it is not possible to determine whether the vehicle is loaded or not when the speed of the vehicle falls below a lower limit determined based on the detection performance of the detection device. This configuration makes it possible to avoid notifying an erroneous determination result and to increase the reliability of the determination.

[0012] (6) A program according to an embodiment of the present disclosure, The loading determination device, Obtaining tire internal pressure data and vehicle speed data detected by a detection device mounted on a vehicle; and determining whether the vehicle is loaded or not based on the amplitude of the internal pressure data and the speed data. With this configuration, it is possible to determine whether the vehicle is loaded or not through simple calculation.

[0013] (7) A method for determining loading according to an embodiment of the present disclosure includes: A loading determination method executed by a loading determination device, comprising: The loading determination device, Obtaining tire internal pressure data and vehicle speed data detected by a detection device mounted on a vehicle; and determining whether the vehicle is loaded or not based on the amplitude of the internal pressure data and the speed data. With this configuration, it is possible to determine whether the vehicle is loaded or not through simple calculation. Effect of the Invention

[0014] According to the present disclosure, it is possible to provide a loading determination device, a program, and a loading determination method that can determine whether a vehicle is loaded or not by simple calculation. [Brief description of the drawings]

[0015] [Figure 1] FIG. 1 is a diagram illustrating a configuration example of a load determination system including a load determination device according to an embodiment of the present disclosure. [Diagram 2] FIG. 2 is another diagram showing an example of the configuration of the load determination system of FIG. [Diagram 3] FIG. 3 is a diagram illustrating an example of a time series change in tire internal pressure data. [Figure 4] FIG. 4 is a diagram for explaining the determination of whether or not a vehicle is loaded. [Diagram 5] FIG. 5 is an example of a flowchart illustrating a process of a loading determination method according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] Hereinafter, a loading determination device 10 (see FIG. 1), a program, and a loading determination method according to an embodiment of the present disclosure will be described with reference to the drawings. In each drawing, the same or corresponding parts are given the same reference numerals. In the description of this embodiment, the description of the same or corresponding parts will be omitted or simplified as appropriate.

[0017] Figures 1 and 2 are diagrams showing a configuration example of a load determination system. The load determination system includes a load determination device 10. Figure 1 is a block diagram including an internal configuration example of the load determination device 10 and a configuration example of a device mounted on a vehicle 20. Figure 2 shows the overall configuration of the load determination system.

[0018] The load determination device 10 according to the present embodiment determines whether the vehicle 20 is loaded. The load determination device 10 may determine whether the vehicle 20 is loaded or not, i.e., whether the vehicle 20 is loaded with almost the maximum load (full load) or almost zero load (empty). The load determination device 10 is not limited to simply indicating whether the vehicle 20 is loaded or not, but may also indicate a numerical value related to the state of the tire 30 based on the determination result so that the manager of the vehicle 20 can determine, for example, whether the tire 30 needs to be replaced, repaired, or rotated to change the mounting position. Repair of the tire 30 may include retreading, which involves scraping the surface of the tread rubber of the tire 30 and attaching new rubber to reuse the tire 30. The numerical value related to the state of the tire 30 may be, for example, the cumulative time of full load or the operating rate. For example, the manager of the vehicle 20 may determine to replace some or all of the tires 30 when the cumulative time of full load of the vehicle 20 exceeds a reference time. Here, the vehicle 20 may be, for example, a passenger car, a truck, a bus, or a construction vehicle, and is not limited to a specific type of moving body. In this embodiment, the vehicle 20 is described as a mining vehicle equipped with OR tires and transporting minerals. In addition, in order to avoid redundancy in the illustrations in Figs. 1 and 2, only one vehicle 20 is shown, but the loading determination system may be configured to include multiple vehicles 20.

[0019] The loading determination device 10 includes a communication unit 11, a storage unit 12, and a control unit 13. The control unit 13 includes an acquisition unit 131, a determination unit 132, and an output unit 133. The loading determination device 10 may be, for example, a computer as a hardware configuration. The computer may be a server computer or a portable computer such as a laptop or a tablet. Details of the components of the loading determination device 10 will be described later. In this embodiment, the loading determination device 10 is a computer located away from the work site of the mining vehicle. Here, the loading determination device 10 may not be a single device, but may be configured of multiple devices that are arranged in multiple locations and can transmit and receive data to each other via a network 40. In other words, multiple devices connected by the network 40 may function as the loading determination device 10 shown in FIG. 1 as a whole. Therefore, for example, the loading determination device 10 may be configured of one computer as a hardware configuration, or may be configured of multiple computers connected by the network 40. When the system is configured with multiple computers, the storage unit 12 may be a shared memory that can be accessed by each computer.

[0020] The load determination device 10 may configure a load determination system together with devices (detection device 70 and on-board communication device 80) mounted on the vehicle 20 connected by a network 40. The network 40 is, for example, the Internet. The network 40 may also be configured to include, for example, a local area network (LAN) in part. Here, the load determination system may further include a terminal device 50 used by an administrator who manages the vehicle 20. The terminal device 50 is, for example, a general-purpose mobile terminal such as a smartphone or a tablet terminal, but is not limited to these. The terminal device 50 may function as a display unit that displays the determination result output from the load determination device 10. The load determination system may also include a storage device 90 (storage device 90 on the cloud) on the network 40 as viewed from the load determination device 10 and the devices mounted on the vehicle 20. In this embodiment, the storage device 90 includes a database that stores information on the state of the tire 30 detected by the detection device 70 mounted on the vehicle 20 as time-series data in association with the vehicle 20 to be detected. In the case where the vehicle-mounted communication device 80 also outputs the position information of the vehicle 20, the database also stores the position information as time-series data. In the present embodiment, the load determination device 10 obtains necessary information from the database via the network 40.

[0021] In this embodiment, the vehicle 20 includes a detection device 70 and an on-board communication device 80. The detection device 70 is a device or on-board system including sensors that generates information about the state of the tires 30. In this embodiment, the detection device 70 includes a tire pressure monitoring system (TPMS).

[0022] The tire pressure monitoring system monitors the pressure (internal pressure) of a tire 30 attached to a vehicle 20. The tire pressure monitoring system may also monitor the temperature (internal tire temperature) of the tire 30. The tire pressure monitoring system may be configured to include, for example, a sensor installed inside the tire 30, a processor that calculates and outputs the pressure of the tire 30 based on a detection value of the sensor, and a memory that stores the detection value of the sensor, etc. The sensor may include a pressure sensor and a temperature sensor.

[0023] The in-vehicle communication device 80 is a device that outputs information on the state of the tire 30 detected by the detection device 70 so that the information is stored in a database. In this embodiment, the in-vehicle communication device 80 is realized by a communication function of a digital tachograph, but is not limited thereto, and may be, for example, a dedicated communication device. The in-vehicle communication device 80 may output information on the current position of the vehicle 20 to the storage device 90 or the loading determination device 10. In this embodiment, the in-vehicle communication device 80 has a GPS (Global Positioning System) function and outputs GPS information including coordinates as position information of the vehicle 20. That is, in this embodiment, the in-vehicle communication device 80 outputs information on the internal pressure of the tire 30 and the position of the vehicle 20, and these pieces of information are stored in the database of the storage device 90 on the cloud. Here, the in-vehicle communication device 80 may also output information on the temperature of the tire 30, and the temperature information may also be stored in the database of the storage device 90 on the cloud. In addition, in this embodiment, the in-vehicle communication device 80 calculates the speed of the vehicle 20 based on the position information of the vehicle 20, and the information on the speed of the vehicle 20 is also stored in the database of the storage device 90 on the cloud.

[0024] Here, in the case where the load determination system does not include the storage device 90, the storage unit 12 of the load determination device 10 may have a database.

[0025] The components of the loading determination device 10 will be described in detail below. The communication unit 11 includes one or more communication modules that connect to the network 40. The communication unit 11 may include a communication module that supports mobile communication standards such as 4G (4th Generation) and 5G (5th Generation). The communication unit 11 may include a communication module that supports a wired or wireless LAN standard.

[0026] The storage unit 12 is one or more memories. The memory may be, for example, a semiconductor memory, a magnetic memory, an optical memory, or the like, but is not limited to these and may be any memory. The storage unit 12 is, for example, built into the load determination device 10, but may also be configured to be accessed from the outside by the load determination device 10 via any interface.

[0027] The storage unit 12 stores various data used in various calculations performed by the control unit 13. The storage unit 12 may also store results and intermediate data of various calculations performed by the control unit 13.

[0028] In this embodiment, the storage unit 12 may temporarily store various information from the database of the storage device 90 on the cloud acquired via the communication unit 11. In addition, for example, when the loading determination system is configured to include multiple types of vehicles 20, the storage unit 12 may store vehicle information that is information about each type of vehicle 20.

[0029] The control unit 13 is one or more processors. The processor may be, for example, a general-purpose processor or a dedicated processor specialized for a specific process, but is not limited to these and may be any processor. The control unit 13 controls the overall operation of the load determination device 10.

[0030] Here, the loading determination device 10 may have the following software configuration. One or more programs used to control the operation of the loading determination device 10 are stored in the storage unit 12. When the program stored in the storage unit 12 is read by the processor of the control unit 13, it causes the control unit 13 to function as an acquisition unit 131, a determination unit 132, and an output unit 133.

[0031] The acquisition unit 131 acquires input data including internal pressure data of the tire 30 detected by a detection device 70 mounted on the vehicle 20 and speed data of the vehicle 20. In this embodiment, the internal pressure data of the tire 30 is time series data of the internal pressure of the tire 30 detected by a tire pressure monitoring system. Also, in this embodiment, the speed data of the vehicle 20 is time series data of the speed of the vehicle 20 calculated based on position information.

[0032] The determination unit 132 determines whether the vehicle 20 is loaded based on the input data. Here, FIG. 3 is a diagram illustrating a time series change in the internal pressure data of the tire 30. In FIG. 3, the horizontal axis indicates time, and the vertical axis indicates the internal pressure of the tire 30. "Empty" and "Fully loaded" in FIG. 3 indicate the loading state of the vehicle 20. "Empty" indicates a loading state with almost zero (no loading), and "Fully loaded" indicates a loading state with almost the maximum loading amount (loaded). The vehicle 20 loads luggage and transports it to a destination, unloads the luggage at the destination, moves again in an empty state, and repeats the work of loading luggage again at the destination. As shown in FIG. 3, the amplitude of the internal pressure of the tire 30 when fully loaded with luggage and traveling with a load on the tire 30 is larger than the amplitude of the internal pressure of the tire 30 when it is empty. In FIG. 3, A0 indicates a value twice the amplitude of the amplitude when it is empty, and A1 indicates a value twice the amplitude when it is fully loaded. Here, the amplitude of the internal pressure means the range of change in the internal pressure. In particular, since mining vehicles run on rough unpaved roads loaded with minerals several times the weight of the vehicle body, the amplitude of the internal pressure of the tire 30 when fully loaded is larger than the amplitude of the internal pressure of the tire 30 when the vehicle is empty. In particular, since operational efficiency is emphasized in mining vehicles, the vehicle is often either fully loaded or empty, and it is sufficient to determine which of the two states (whether or not the vehicle is loaded). It is possible to determine whether or not the vehicle 20 is loaded by using the difference in the amplitude of the internal pressure of the tire 30 as shown in FIG. 3.

[0033] In the above conventional technique, the load is calculated by focusing on the difference between the measured pressure and the reference pressure, but it is significantly affected by noise in the adjustment and measurement of the internal pressure of the tire 30, making it difficult to accurately calculate the load, i.e., to accurately determine whether the tire is loaded or not. In contrast, the amplitude of the internal pressure of the tire 30 is calculated regardless of the adjustment of the internal pressure (changes in the level of the internal pressure) and is less affected by noise. Therefore, it is possible to determine whether the tire is loaded or not more accurately than with the conventional technique.

[0034] The determination unit 132 may calculate the amplitude of the internal pressure, for example, using the root mean square (RMS), but is not limited to a specific calculation method.

[0035] Here, the amplitude of the internal pressure of the tire 30 changes depending on the speed of the vehicle 20. For example, if the vehicle 20 is moving at high speed, the amplitude of the internal pressure of the tire 30 becomes larger than when the vehicle 20 is moving at low speed. Therefore, the determination unit 132 determines whether the vehicle 20 is loaded or not based on the amplitude of the internal pressure data and the speed data. FIG. 4 is a diagram for explaining the determination of whether the vehicle 20 is loaded or not, in which the horizontal axis shows the speed of the vehicle 20 and the vertical axis shows the amplitude of the internal pressure of the tire 30. As shown in FIG. 4, the boundary between loaded and unloaded changes depending on the speed.

[0036] As shown in FIG. 4, the speed of the vehicle 20 may be an average speed for a predetermined period. Also, the amplitude of the internal pressure of the tire 30 may be an amplitude of the internal pressure for a predetermined period. That is, the internal pressure data may be acquired every predetermined period, and the determination unit 132 may use the average value of the speed data for the predetermined period as the speed of the vehicle 20. The predetermined period may be shorter than the loading cycle of the vehicle 20 (the period from loading luggage, unloading at the destination, and loading luggage again). The loading cycle is the time interval from time t1 to time t3 or the time interval from time t2 to time t4 in the example of FIG. 3. For example, the detection device 70 of a tire pressure monitoring system or the like is often battery-powered. Therefore, in order to reduce power consumption on the side of the detection device 70, the detection value (pressure of the tire 30) is transmitted at regular intervals, not continuously. The determination unit 132 may set the above-mentioned predetermined period so that the transmission interval from the detection device 70 is not too short, and a large number of data is obtained to be able to accurately calculate the amplitude of the internal pressure of the tire 30. By appropriately setting the predetermined period, it is possible to achieve both accurate determination and suppression of power consumption on the side of the detection device 70. As an example, when the loading cycle is 20 minutes or more and the transmission interval is 1 minute, the determination unit 132 may set the predetermined period to 15 minutes.

[0037] The determination unit 132 determines whether the vehicle 20 is loaded using a threshold value that is determined in advance based on the relationship between the amplitude of the internal pressure of the tire 30 and the speed of the vehicle 20. By using the threshold value, the determination can be made quickly and with sufficient accuracy. The determination unit 132 calculates the amplitude of the internal pressure data for a predetermined period. When calculating the amplitude of the internal pressure data using the root mean square, the determination unit 132 may calculate the average value of the internal pressure data for the predetermined period as the expected value. The determination unit 132 also obtains the average speed of the speed data for the predetermined period. Then, by comparing with the threshold value, that is, depending on which region divided by the threshold value the plot position of the calculated amplitude and average speed belongs to, the determination of whether the vehicle 20 is loaded is made.

[0038] Here, the threshold value used by the determination unit 132 is not limited to a specific method, and may be determined, for example, using a model generated by machine learning. In machine learning, learning data may be used in which internal pressure data and speed data, which are actual data (past measured values ​​and calculated values ​​accumulated in a database), are used as explanatory variables, and whether or not the vehicle 20 corresponding to the explanatory variables is loaded is used as a target variable. As a method for dividing the learning data into a loaded group and an unloaded group and specifying a threshold value given as a boundary between these groups, for example, logistic regression, support vector machine, k-nearest neighbor method, etc. may be used. A machine learning model using actual data can determine a threshold value that enables more accurate determination. As another method, an operator of the loading determination device 10 may determine a threshold value using a graph plotting the internal pressure data and speed data, which are actual data, and the presence or absence of the vehicle 20, which is actual data corresponding to these. In this case, the threshold value can be determined by reflecting the experience of the operator of the loading determination device 10. The determined threshold value is stored in the storage unit 12 and is read out when the determination unit 132 executes the load presence / absence determination. In addition, in FIG. 4, the threshold is a straight line passing through the origin, but is not limited to this and may be a straight line or a curve not passing through the origin.

[0039] In addition, in this embodiment, when the speed of the vehicle 20 falls below a lower limit determined based on the detection performance of the detection device 70, the determination unit 132 outputs that it is not possible to determine whether the vehicle 20 is loaded or not. As described above, the determination unit 132 performs the determination using the amplitude of the internal pressure of the tire 30, and is therefore less susceptible to noise than the conventional technology. However, when the vehicle 20 moves at a low speed, the detection value of the tire pressure monitoring system itself becomes small and may be buried in noise. In such a case, the internal pressure data of the tire 30 that is received is already affected by noise, and the determination unit 132 cannot accurately calculate the amplitude of the internal pressure of the tire 30. Therefore, the determination unit 132 may determine the lower limit based on the signal-to-noise ratio (SN ratio) of the tire pressure monitoring system, and set the region where the speed of the vehicle 20 falls below the lower limit as the determination impossible region, as shown in FIG. 4. When the plot position of the amplitude of the internal pressure of the tire 30 and the average speed of the vehicle 20 belongs to an undeterminable region, the determination unit 132 may output as a determination result that it is impossible to determine whether the vehicle 20 is loaded or not. By outputting the result that it is impossible to determine, it is possible to avoid notifying an erroneous determination result (for example, determining that the vehicle is loaded when the vehicle is actually not loaded), and to increase the reliability of the determination.

[0040] The output unit 133 may output the judgment result of the judgment unit 132 (e.g., whether the vehicle 20 is loaded or not) to a terminal device 50 or the like used by an administrator who manages the vehicle 20. The output unit 133 may process the judgment result of the judgment unit 132 into, for example, a cumulative time of full loading or an operating rate so that it is easy for the viewer to understand, and output the processed data to the terminal device 50 or the like. The administrator may plan or execute repairs, etc. of the tire 30 that is the subject of the judgment, based on the displayed judgment result. In addition, the administrator may plan or execute rotations, etc., that change the mounting positions of the tires 30 that are the subject of the judgment, based on the displayed judgment result.

[0041] Fig. 5 is an example of a flowchart showing the process of the load determination method executed by the load determination device 10 according to this embodiment. The load determination device 10 can determine whether the vehicle 20 is loaded or not by a simple calculation by executing the determination process as shown in Fig. 5.

[0042] The acquisition unit 131 acquires internal pressure data of the tire 30 detected by the detection device 70 mounted on the vehicle 20 and speed data of the vehicle 20 (step S1). The acquisition unit 131 acquires the internal pressure data and the speed data at the above-mentioned predetermined period.

[0043] The determination unit 132 calculates the amplitude of the internal pressure data for a predetermined period (step S2). The determination unit 132 also obtains an average speed of the speed data for the predetermined period. The determination unit 132 also reads out a threshold value from the storage unit 12.

[0044] The determination unit 132 uses a threshold value to determine whether the vehicle 20 is loaded during a predetermined period (step S3). As described above, the determination unit 132 may make the determination based on whether the plot position of the calculated amplitude and average speed belongs to a loaded region, an unloaded region, or an undeterminable region (see FIG. 4).

[0045] As described above, the loading determination device 10, the program, and the loading determination method according to the present embodiment can determine whether the vehicle 20 is loaded or not by a simple calculation due to the above-mentioned configuration. In particular, it becomes possible to quickly determine whether a mining vehicle equipped with OR tires is loaded or not (fully loaded or empty) with sufficient accuracy.

[0046] Although the embodiments of the present disclosure have been described based on the drawings and examples, it should be noted that a person skilled in the art would easily be able to make various modifications or alterations based on the present disclosure. Therefore, it should be noted that these modifications or alterations are included in the scope of the present disclosure. For example, the functions included in each component or step can be rearranged so as not to cause logical inconsistencies, and multiple components or steps can be combined into one or divided. The embodiments of the present disclosure can also be realized as a storage medium having a program executed by a processor provided in an apparatus recorded thereon. It should be understood that these are also included in the scope of the present disclosure. Contributing to the United Nations-led Sustainable Development Goals (SDGs)

[0047] The SDGs have been proposed to realize a sustainable society. One embodiment of the present disclosure is considered to be a technology that can contribute to "No. 9 Build infrastructure for industry and technological innovation." [Explanation of symbols]

[0048] 10 Loading determination device 11 Communications Department 12 Storage section 13 Control section 20 Vehicles 30 Tires 40 Network 50 Terminal Equipment 70 Detection Device 80 Vehicle-mounted communication device 90 Storage device 131 Acquisition Department 132 Judgment section 133 Output section

Claims

1. an acquisition unit that acquires tire internal pressure data and vehicle speed data detected by a detection device mounted on a vehicle; a determination unit that determines whether the vehicle is loaded or not based on the amplitude of the internal pressure data and the speed data.

2. The loading determination device according to claim 1 , wherein the determination unit determines whether the vehicle is loaded by using a threshold value that is set in advance based on a relationship between the amplitude and a speed of the vehicle.

3. The loading determination device according to claim 2, wherein the determination unit uses the threshold value determined using a model generated by machine learning using learning data in which the internal pressure data and the speed data, which are actual data, are explanatory variables and the presence or absence of the vehicle being loaded corresponding to the explanatory variables is a target variable.

4. The internal pressure data is acquired at predetermined intervals, The load determination device according to claim 1 , wherein the determination unit uses an average value of the speed data for the predetermined period as the speed of the vehicle.

5. The loading determination device according to claim 1 , wherein the determination unit outputs a signal indicating that it is not possible to determine whether the vehicle is loaded or not when the speed of the vehicle falls below a lower limit value determined based on the detection performance of the detection device.

6. The loading determination device, Obtaining tire internal pressure data and vehicle speed data detected by a detection device mounted on a vehicle; and determining whether the vehicle is loaded or not based on the amplitude of the internal pressure data and the speed data.

7. A loading determination method executed by a loading determination device, comprising: The loading determination device, Obtaining tire internal pressure data and vehicle speed data detected by a detection device mounted on a vehicle; determining whether the vehicle is loaded or not based on the amplitude of the internal pressure data and the speed data.

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