Information processing device, information processing method, and information processing program

Abstract

This information processing device comprises a processor. The processor acquires tire-related information including internal pressure values of a plurality of tires on a vehicle, and estimates that the vehicle has ridden over an obstacle on the basis of fluctuations in the internal pressure values of one tire and another tire among the internal pressure values of the plurality of tires included in the tire-related information.

Description

Information Processing Apparatus, Information Processing Method, and Information Processing Program

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

[0002] Tire damage is affected by the condition of the road surface on which a vehicle equipped with the tire is traveling. In view of this, a technique for acquiring road surface conditions while a vehicle is traveling is known (for example, Japanese Unexamined Patent Application Publication No. 2022-007616).

[0003] The technique disclosed in Japanese Unexamined Patent Application Publication No. 2022-007616 can detect and notify the presence or absence of obstacles on a road surface.

[0004] However, the technique disclosed in Japanese Unexamined Patent Application Publication No. 2022-007616 still has room for improvement in the detection accuracy of the presence or absence of obstacles.

[0005] An object of the present disclosure is to provide an information processing apparatus, an information processing method, and an information processing program that can improve detection accuracy for the presence or absence of obstacles, compared to a case of determining whether a vehicle has driven over an obstacle based on a change in the internal pressure value of a single tire.

[0006] A first aspect of the present disclosure includes a processor, wherein the processor acquires tire-related information including internal pressure values of a plurality of tires of a vehicle, and estimates that the vehicle has driven over an obstacle based on changes in the internal pressure values of one tire and another tire among the internal pressure values of the plurality of tires included in the tire-related information.

[0007] According to the information processing apparatus of the first aspect, detection accuracy for the presence or absence of obstacles can be improved compared to a case of determining whether a vehicle has driven over an obstacle based on a change in the internal pressure value of a single tire.

[0008] A second aspect of the present disclosure is the information processing apparatus according to the first aspect, wherein the processor estimates that the vehicle has driven over the obstacle based on changes in the internal pressure values of one front tire, which is the one tire, and one rear tire, which is the other tire.

[0009] According to the information processing device of the second embodiment, it becomes possible to detect load transfer in the longitudinal direction of the vehicle and the pitching motion of the vehicle body, and the accuracy of detecting the presence or absence of obstacles can be further improved compared to simply comparing the internal pressure fluctuations of the left and right tires.

[0010] A third aspect of the present disclosure is an information processing apparatus of the second aspect, wherein the one front tire and the one rear tire are located at different positions in the longitudinal direction of the vehicle and on opposite sides in the lateral direction of the vehicle.

[0011] According to the information processing device of the third embodiment, load transfer associated with vehicle roll and pitching when driving over an obstacle can be considered more appropriately, and the accuracy of detecting the presence or absence of an obstacle can be further improved while reducing the influence of local road surface fluctuations.

[0012] A fourth aspect of the present disclosure is an information processing device of any one of the first to third aspects, wherein the processor acquires a reference internal pressure value and a threshold value indicating the amount of variation from the reference internal pressure value, set for each of the plurality of tires, and estimates that the vehicle has driven over an obstacle when the internal pressure values ​​of one tire and the other tires fall outside the range of the threshold values ​​set for each.

[0013] According to the information processing device of the fourth embodiment, the internal pressure fluctuations are evaluated while considering the pressure characteristics of each tire, and if the pressure falls outside the threshold range based on criteria suitable for each tire, it is possible to estimate whether an obstacle has been driven over, thereby further improving the accuracy of obstacle detection.

[0014] A fifth aspect of this disclosure is an information processing device according to the fourth aspect, wherein the processor acquires load information indicating the load of the vehicle's cargo, and updates the threshold value of each of the plurality of tires based on the acquired load information.

[0015] According to the information processing device of the fifth embodiment, the effect of tire pressure due to fluctuations in load can be appropriately corrected, and the optimal threshold setting according to load conditions can be made possible, thereby improving the accuracy of obstacle detection adapted to driving conditions.

[0016] A sixth aspect of this disclosure is an information processing device according to the fourth or fifth aspect, wherein the processor acquires tire condition information indicating the condition of tire damage according to a user performing work at a work site using a plurality of vehicles, and updates the threshold value for each of the plurality of tires in the plurality of vehicles used by the user based on the acquired tire condition information.

[0017] According to the sixth embodiment of the information processing device, it becomes possible to set optimal thresholds according to the characteristics of the usage environment and each vehicle, thereby improving the accuracy of overrun detection and optimizing tire maintenance management.

[0018] A seventh aspect of this disclosure is an information processing device of any one of the fourth to sixth aspects, wherein the reference internal pressure value is an internal pressure value corresponding to a reference temperature, which is the temperature of the gas inside the tire in the vehicle before driving, and the processor converts the internal pressure values ​​of one tire and the other tire acquired while the vehicle is driving into internal pressure values ​​corresponding to the reference temperature, and estimates that the vehicle has driven over an obstacle when the converted internal pressure values ​​fall outside the range of thresholds set for each.

[0019] According to the information processing device of the seventh embodiment, the effects of internal pressure fluctuations due to changes in tire temperature during driving can be corrected, enabling appropriate threshold determination, thereby further reducing false detections and improving the accuracy of detecting the presence or absence of obstacles.

[0020] An eighth aspect of the present disclosure is an information processing device of any one of the first to seventh aspects, wherein the processor estimates the size of the obstacle based on the magnitude of fluctuations in the internal pressure of the vehicle's tires.

[0021] According to the information processing device of the eighth embodiment, it is possible to improve safety and operational efficiency by contributing to vehicle operation management and optimization of travel routes that take into account the degree of influence of obstacles.

[0022] A ninth aspect of the present disclosure is an information processing device of any one of the first to eighth aspects, wherein the processor identifies the tire that has driven over the obstacle based on fluctuations in the internal pressure values ​​of the first tire and the other tire, and stores the tire that has driven over in a tire inspection list of candidates for tire inspection.

[0023] According to the information processing device of the ninth embodiment, it is possible to appropriately identify tires affected by obstacles and prioritize their inspection, thereby improving vehicle safety and the efficiency of tire maintenance management.

[0024] A tenth aspect of this disclosure is an information processing device of any one of the first to ninth aspects, wherein the processor outputs the position indicated by the position information when the tire that has driven over the obstacle drives over the obstacle as the position of the obstacle.

[0025] According to the information processing device of the tenth embodiment, the location of obstacles can be identified and used to prioritize road surface maintenance and optimize the route, thereby improving the safety and efficiency of vehicle operation.

[0026] An eleventh aspect of this disclosure is an information processing device according to the eighth aspect, wherein the processor outputs a priority order for road surface maintenance based on the estimated size of the obstacle.

[0027] According to the information processing device of the 11th embodiment, it becomes possible to formulate an efficient road surface maintenance plan that takes into account the degree of impact of obstacles on vehicle operation, thereby improving vehicle driving safety and optimizing maintenance costs.

[0028] A twelfth aspect of this disclosure is an information processing device according to the tenth aspect, wherein the processor outputs a priority order for road surface maintenance based on the estimated location of the obstacle.

[0029] According to the information processing device of the 12th embodiment, it becomes possible to formulate an efficient road surface maintenance plan that takes into account the degree of impact of obstacles on vehicle operation, thereby improving vehicle driving safety and optimizing maintenance costs.

[0030] A thirteenth aspect of this disclosure is an information processing method, wherein a computer performs a process to acquire tire-related information including the internal pressure values ​​of a plurality of tires in a vehicle, and to estimate that the vehicle has run over an obstacle based on fluctuations in the internal pressure values ​​of one tire and the other tires among the plurality of internal pressure values ​​of the tires included in the tire-related information.

[0031] According to the information processing method of the 13th embodiment, the accuracy of detecting the presence or absence of an obstacle can be improved compared to the case in which it is determined whether or not a vehicle has driven over an obstacle based on fluctuations in the internal pressure value of a single tire.

[0032] A fourteenth aspect of this disclosure is an information processing program which causes a computer to perform a process that acquires tire-related information including the internal pressure values ​​of multiple tires in a vehicle, and estimates that the vehicle has run over an obstacle based on fluctuations in the internal pressure values ​​of one tire and the other tires among the multiple tire internal pressure values ​​included in the tire-related information.

[0033] According to the information processing program of the 14th embodiment, the accuracy of detecting the presence or absence of an obstacle can be improved compared to the case where it is determined whether or not a vehicle has driven over an obstacle based on fluctuations in the internal pressure value of a single tire.

[0034] According to the disclosed technology, the accuracy of detecting the presence or absence of an obstacle can be improved compared to determining whether a vehicle has run over an obstacle based on fluctuations in the internal pressure of a single tire.

[0035] This is a diagram showing the overall configuration including the information processing device and the vehicle. This is a first block diagram showing the hardware configuration of the information processing device. This is a block diagram showing the storage configuration of the information processing device. This is a first flowchart showing the flow of the estimation process. This is a second block diagram showing the hardware configuration of the information processing device. This is a second flowchart showing the flow of the estimation process. This is a first flowchart showing the flow of the threshold update process. This is a second flowchart showing the flow of the threshold update process.

[0036] An example of an embodiment of the disclosed technology will be described below with reference to the drawings. In each drawing, identical or equivalent components and parts are given the same reference numerals. Furthermore, the dimensional ratios in the drawings are exaggerated for illustrative purposes and may differ from actual ratios.

[0037] (First Embodiment) First, a first embodiment of the information processing system 1 according to this embodiment will be described.

[0038] Figure 1 is a diagram showing the overall configuration including the information processing device 10 and vehicles 50 according to this embodiment. As shown in Figure 1, the information processing system 1 of this embodiment is configured to include the information processing device 10 and a plurality of vehicles 50.

[0039] The information processing device 10 is a computer that performs various processes related to the information processing system 1.

[0040] Vehicle 50 is a mining vehicle used for work in mines. Vehicle 50 is equipped with multiple tires. For example, vehicle 50 has two front wheels positioned on the left and right sides at the front, and four rear wheels, two on each side at the rear, for a total of six tires.

[0041] Each vehicle 50 is equipped with a communication device 25 and a plurality of TPMS (Tire Pressure Monitoring Systems) 20. The information processing device 10 according to this embodiment is wirelessly connected to the communication device 25 of each vehicle 50. The communication device 25 is also wirelessly connected to each of the plurality of TPMS 20. In this way, the information processing device 10 receives tire-related information regarding the tires of the vehicle 50 while it is in motion and while it is stopped. The information processing device 10 is an example of the “information processing device” and “computer” of this disclosure, the vehicle 50 is an example of the “vehicle” of this disclosure, and the mine is an example of the “work site” of this disclosure.

[0042] Figure 2 is a first block diagram showing the hardware configuration of the information processing device 10 according to this embodiment. As shown in Figure 2, the information processing device 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, a RAM (Random Access Memory) 13, storage 14, an input / output I / F (Interface) 15, and a communication I / F 16. Each component is connected to the others via a bus 17 so as to be able to communicate with each other.

[0043] The CPU 11 is a central processing unit that executes various programs and controls each component. That is, the CPU 11 reads a program from the ROM 12 or the storage 14, and executes the program using the RAM 13 as a work area. The CPU 11 performs control of each of the above components and various arithmetic processes in accordance with programs stored in the ROM 12 or the storage 14. The CPU 11 is an example of the "processor" in the present disclosure.

[0044] A storage device configured by the ROM 12 stores various programs including an operating system and various data.

[0045] A memory configured by the RAM 13 temporarily stores programs and data as a work area.

[0046] The storage 14 is configured of an HDD (Hard Disk Drive), an SSD (Solid State Drive), or the like, and stores various data. Note that the storage 14 is not necessarily built into the information processing apparatus 10, and may be, for example, a portable storage device detachable from the information processing apparatus 10, or a cloud server external to the information processing apparatus 10 may be used as the storage device.

[0047] The input / output I / F 15 is an interface for communicating with input devices and output devices external to the information processing apparatus 10. The input device includes a pointing device such as a mouse and a keyboard, and is used for performing various inputs. The output device includes, for example, a liquid crystal display or an organic EL (Electro Luminescence) display, and is a device for outputting various information. The output device may adopt a touch panel system and function as an input device. Further, the output device may be provided with a speaker or the like as an audio output unit. For example, when the information processing apparatus 10 is installed in a vehicle 50, the output device is used as an in-vehicle monitor. Further, when the information processing apparatus 10 is installed in an operation management room, the output device is used as a monitor in the operation management room.

[0048] The communication I / F 16 is an interface for communicating with other devices external to the information processing apparatus 10. For example, wireless communication standards such as 4G, 5G, or Wi-Fi (registered trademark) are used for the communication. When the information processing apparatus 10 is installed in an operation control room, the information processing apparatus 10 performs data communication with each vehicle 50 via a wireless line, which is an example of a communication line connected to the communication I / F 16. Further, when the information processing apparatus 10 is installed in the vehicle 50, the information processing apparatus 10 performs data communication with a server (not shown) installed in the operation control room via a wireless line connected to the communication I / F 16, and may cause a monitor installed in the operation control room to display the status of the internal pressure and temperature of each tire as tire-related information.

[0049] Further, the communication I / F 16 performs wireless communication with a communication device 25 of the vehicle 50. The communication device 25 is provided in the vehicle 50 and communicates with a TPMS 20 of each tire of the vehicle 50.

[0050] The TPMS 20 includes, for example, a transmitter 23, a temperature sensor 21, a pressure sensor 22, and a GPS (Global Positioning System) sensor 26.

[0051] The temperature sensor 21 is a sensor that measures the temperature of gas inside a tire as the internal temperature of each tire. The pressure sensor 22 is a sensor that measures the internal pressure value of each tire. The GPS sensor 26 is a sensor that acquires position information of each tire. Further, measurement by the temperature sensor 21, the pressure sensor 22, and the GPS sensor 26 is performed constantly or at preset sampling intervals. Accordingly, for example, data of the time at which the internal pressure value of each tire is measured (time stamp of the internal pressure value) is recorded as associated data.

[0052] The transmitter 23 communicates with the communication device 25. Specifically, the transmitter 23 transmits tire-related information including the internal temperature, internal pressure value, and position information of each tire of the vehicle 50 transmitted from each of the above sensors to the communication device 25. The communication device 25 transmits the acquired tire-related information to the information processing apparatus 10.

[0053] Next, the configuration of the storage 14 of the information processing device 10 will be described. Figure 3 is a block diagram showing the configuration of the storage 14 of the information processing device 10.

[0054] As shown in Figure 3, the storage 14 stores the information processing program 14A and the database 14B.

[0055] The information processing program 14A is a program that causes the CPU 11 to execute various processes described later. When executing the information processing program 14A, the information processing device 10 uses the hardware resources shown in Figure 2 to execute the processes based on the information processing program 14A. The information processing program 14A is an example of an "information processing program" in this disclosure.

[0056] Database 14B is a database that stores various information related to the information processing system 1. This information includes, for example, tire-related information, a standard internal pressure value set for each tire, and a threshold value indicating the amount of variation from the standard internal pressure value.

[0057] The standard internal pressure value is set for each tire and used as a reference for estimating obstacle clearance. For example, the standard internal pressure value for one front tire is set to "900 kPa," which is based on the air pressure at ambient temperature. Hereafter, this standard internal pressure value at ambient temperature (reference temperature), such as "900 kPa," may be referred to as the "internal pressure value according to the reference temperature." In other words, the standard internal pressure value can be said to be the "internal pressure value according to the reference temperature." Furthermore, the standard internal pressure value for one rear tire, which is located in a different position from the front tire in the longitudinal direction of the vehicle 50 and on the opposite side in the lateral direction of the vehicle 50, is set to "950 kPa," taking into consideration that it is subjected to a higher load than the front tire.

[0058] The threshold is an internal pressure value that indicates the amount of variation from the standard internal pressure value, which is set according to each tire. For example, the threshold for one front tire is set to "plus or minus 50 kPa" to take into account pressure fluctuations when driving over obstacles, and the threshold for one rear tire is set to "plus or minus 40 kPa" to allow for a stricter judgment by taking into account the load distribution ratio of the rear wheels.

[0059] Figure 4 is a first flowchart showing the flow of the estimation process performed by the information processing device 10. The estimation process is performed when the CPU 11 reads the information processing program 14A from the storage 14, loads it into the RAM 13, and executes it. The estimation process is performed repeatedly and automatically, for example, at regular intervals.

[0060] In step S10 shown in Figure 4, the CPU 11 obtains the standard internal pressure value and threshold value set according to each tire of the vehicle 50 from the database 14B. Then, the CPU 11 proceeds to step S11.

[0061] In step S11, the CPU 11 obtains tire-related information for each tire of the vehicle 50, specifically the internal temperature, internal pressure, and position information of each tire, from the database 14B. Then, the CPU 11 proceeds to step S12.

[0062] In step S12, the CPU 11 converts the internal pressure values ​​of one front tire and one rear tire of the vehicle 50, which are the targets for obstacle mounting estimation, to internal pressure values ​​corresponding to a reference temperature. Boyle's Law (PV = NRT) is used for the conversion to correct for the effect of the internal temperature of the tire during driving and to obtain an internal pressure value that can be compared with the reference internal pressure value. For example, an internal pressure value of 1050 kPa (80°C = 353 K) measured during driving is converted to an internal pressure value of 886 kPa corresponding to a reference temperature of 25°C (298 K). This conversion method is publicly known, as shown in Japanese Patent Publication No. 2023-151602 and Japanese Patent Publication No. 2022-110942, etc., so a detailed explanation is omitted. The CPU 11 then proceeds to step S13, where it performs threshold determination using the converted internal pressure value.

[0063] In step S13, the CPU 11 determines whether the internal pressure values ​​of one front tire and one rear tire, converted to internal pressure values ​​corresponding to the reference temperature, have fallen outside the range of the respective thresholds. If the CPU 11 determines that each internal pressure value has fallen outside the range of the respective thresholds (step S13: YES), it proceeds to step S14. On the other hand, if the CPU 11 determines that each internal pressure value is not outside the range of the respective thresholds (step S13: NO), it returns to step S11. Furthermore, being outside the threshold range means exceeding the upper or lower limit of the threshold set based on the reference internal pressure value. For example, if the reference internal pressure value is 900 kPa and the threshold is set to plus or minus 50 kPa, then if the internal pressure value exceeds 950 kPa or falls below 850 kPa, it is determined to be outside the threshold range.

[0064] In step S14, the CPU 11 estimates that the vehicle 50 has driven over an obstacle. The CPU 11 also identifies the tire that drove over the obstacle based on the changes in the internal pressure values ​​of one front tire and one rear tire. For example, it compares the amount of internal pressure change at the time of driving over the obstacle with the timing of its occurrence and identifies the tire showing the most rapid change in internal pressure as the tire that drove over the obstacle. Then the CPU 11 proceeds to step S15.

[0065] In step S15, the CPU 11 estimates the size of the obstacle based on the magnitude of the fluctuations in the internal pressure values ​​of one front tire and one rear tire. For example, if the internal pressure of the tires fluctuates significantly, the CPU estimates the size of the obstacle based on the proportional relationship with the amount of fluctuation. In addition, the CPU considers the internal pressure fluctuations of not only the tire on top of the obstacle but also diagonally opposite and adjacent tires, and improves the estimation accuracy by reflecting the tilt and load fluctuations of the vehicle 50. Furthermore, it analyzes suspension fluctuations and changes in pitch and roll angles to evaluate the shape and height of the obstacle in detail. Note that changes in pitch and roll angles can be used not only for estimating the size of the obstacle but also as auxiliary information for determining whether the vehicle is running over the obstacle. Then, the CPU 11 proceeds to step S16.

[0066] In step S16, the CPU 11 performs post-processing after estimating whether the vehicle will run over an obstacle. As part of this post-processing, the CPU 11 performs at least one of the following. Then, the CPU 11 terminates the estimation process. The post-processing performed in step S16 will now be described.

[0067] Post-processing 1: Registration and handling of the tire on the road The CPU 11 registers the tire on the road as a candidate for inspection in the tire inspection list and stores it in the database 14B. During periodic inspections, the CPU 11 outputs an instruction to prioritize the inspection of the tire on the road. After the person in charge performs the inspection, the results are input via the input / output I / F 15 of the information processing device 10, and the CPU 11 instructs additional actions as necessary.

[0068] Post-processing 2: Recording and sharing of obstacle location information The CPU 11 outputs the location indicated by the position information when the tire that has driven over the obstacle is output as the location of the obstacle. The CPU 11 obtains the position information of the tire that has driven over when the internal pressure fluctuation of the tire has gone outside the threshold range from the database 14B and identifies the location of the obstacle. The location information of the obstacle is displayed on the map of the navigation system which is shared among multiple vehicles 50. This allows drivers of other vehicles 50 to recognize the presence of obstacles in advance and select a safe route. In addition, the location information of the obstacle is linked with the road surface maintenance list described later and is used to determine the priority of road surface maintenance.

[0069] Post-processing 3: Determining the priority of road surface maintenance based on the size of obstacles The CPU 11 determines the priority of road surface maintenance based on the estimated size of obstacles and outputs instructions. The CPU 11 registers the position information of the vehicle 50 when it hits an obstacle in the road surface maintenance list and stores it in the database 14B. The road surface maintenance list links the size and position information of obstacles and records the maintenance priority.

[0070] The CPU 11 outputs maintenance instructions to the maintenance vehicle based on the road surface maintenance list. Here, the larger the obstacle, the higher the priority assigned. For example, if the obstacle is 15 cm or larger, it is displayed in red on the map, and if it is less than 15 cm, it is displayed in yellow, visually indicating the priority. In this way, the icon color is changed according to the priority, providing intuitive information to drivers and maintenance personnel.

[0071] In mining operations, the road surface of the vehicle 50 is often littered with rocks that act as obstacles, and the tires of the vehicle 50 frequently run over these rocks. When tires run over rocks, the impact causes damage to the tire surface, and as this damage progresses, it leads to premature tire failure.

[0072] Premature tire failures lead to increased tire costs in mining operations and longer vehicle downtime due to breakdowns, thus requiring appropriate countermeasures. Therefore, by accurately detecting obstacles, the risk of tire damage can be reduced, leading to lower tire costs and reduced downtime.

[0073] However, mines contain a wide variety of rocks with different sizes, shapes, and hardnesses, and the magnitude of tire pressure fluctuations differs for each type of rock. In addition to rocks, road surface undulations also contribute to tire pressure fluctuations. Conventionally, obstacle detection was based only on the pressure fluctuations of a single tire, but this method made it difficult to properly distinguish between rocks that could cause significant tire damage and those that could not. Therefore, there is a need for more accurate detection that considers the behavior of the entire vehicle, not just the pressure fluctuations of a single tire. Against this backdrop, there is a strong demand for improved accuracy in obstacle detection.

[0074] Therefore, in the information processing device 10, the CPU 11 acquires tire-related information, including the internal pressure values ​​of multiple tires in the vehicle 50 while it is moving and while it is stopped. The CPU 11 then estimates that the vehicle 50 has run over an obstacle based on the fluctuations in the internal pressure values ​​of one tire and the other tires among the multiple tire internal pressure values ​​included in the tire-related information. As a result, the information processing device 10 can more accurately determine whether a fluctuation in a particular tire is due to an obstacle by comparing the internal pressure fluctuations of multiple tires. Therefore, the information processing device 10 can improve the accuracy of detecting the presence or absence of an obstacle compared to determining whether the vehicle 50 has run over an obstacle based on the fluctuation in the internal pressure value of a single tire.

[0075] Furthermore, in the information processing device 10, the CPU 11 acquires a reference internal pressure value and a threshold value indicating the amount of variation from the reference internal pressure value, which are set for each of the multiple tires. The CPU 11 then estimates that the vehicle 50 has run over an obstacle when the internal pressure values ​​of one tire and the other tires fall outside the range of the threshold values ​​set for each. As a result, the information processing device 10 can evaluate internal pressure fluctuations while considering the pressure characteristics of each tire and estimate running over an obstacle when the pressure falls outside the range of the threshold value based on a standard appropriate for each tire, thereby further improving the accuracy of obstacle detection.

[0076] Furthermore, in the information processing device 10, the reference internal pressure value is the internal pressure value corresponding to the reference temperature, which is the temperature of the gas inside the tire of the vehicle 50 before driving. The CPU 11 then converts the internal pressure values ​​of one tire and other tires acquired while the vehicle 50 is driving into internal pressure values ​​corresponding to the reference temperature, and if the converted internal pressure values ​​fall outside the range of the threshold set for each, it is estimated that the vehicle 50 has run over an obstacle. As a result, the information processing device 10 can correct for the effects of internal pressure fluctuations due to changes in tire temperature during driving and make appropriate threshold determination possible, thereby further reducing false detections and improving the accuracy of detecting the presence or absence of obstacles.

[0077] Furthermore, in the information processing device 10, the CPU 11 estimates the size of the obstacle based on the magnitude of fluctuations in the internal pressure of the vehicle's tires. As a result, the information processing device 10 contributes to the operational management of the vehicle 50 and the optimization of the travel route, taking into account the impact of obstacles, thereby improving safety and operational efficiency.

[0078] Furthermore, in the information processing device 10, the CPU 11 identifies the tire that has driven over an obstacle based on fluctuations in the internal pressure values ​​of one tire and other tires. The CPU 11 then stores the tire that has driven over an obstacle in a tire inspection list of candidates for tire inspection. As a result, the information processing device 10 can appropriately identify tires affected by obstacles and prioritize their inspection, thereby improving the safety of the vehicle 50 and the efficiency of tire maintenance management.

[0079] Furthermore, in the information processing device 10, the CPU 11 outputs the position indicated by the position information when the tire drives over an obstacle as the position of the obstacle. As a result, the information processing device 10 can identify the location of obstacles and use this information to prioritize road surface maintenance and optimize the operating route, thereby improving the safety and efficiency of the operation of the vehicle 50.

[0080] Furthermore, the CPU 11 in the information processing device 10 outputs a priority order for road surface maintenance based on the estimated size and location of obstacles. As a result, the information processing device 10 makes it possible to formulate an efficient road surface maintenance plan that takes into account the degree of impact of obstacles on the operation of vehicles 50, thereby improving the driving safety of vehicles 50 and optimizing maintenance costs.

[0081] Furthermore, in the information processing device 10, the CPU 11 estimates that the vehicle 50 has run over an obstacle based on fluctuations in the internal pressure values ​​of one front tire and the other rear tire. Moreover, the CPU 11 determines that the vehicle 50 has run over an obstacle if internal pressure fluctuations occur in both the front tire and the rear tire within a short period of time (a predetermined time), thereby enabling more accurate detection. As a result, the information processing device 10 enables detection that takes into account the load transfer in the longitudinal direction of the vehicle 50 and the pitching motion of the vehicle body, further improving the accuracy of obstacle detection compared to simply comparing internal pressure fluctuations of the left and right tires.

[0082] Furthermore, in the information processing device 10, one front tire and one rear tire are located in different positions in the longitudinal direction of the vehicle 50, and on opposite sides in the lateral direction of the vehicle 50. As a result, the information processing device 10 can more appropriately consider the load transfer associated with the rolling and pitching of the vehicle 50 when it drives over an obstacle, and can further improve the accuracy of detecting the presence or absence of an obstacle while reducing the influence of local road surface fluctuations.

[0083] For example, one front tire is the front wheel located to the front right, and one rear tire is the rear wheel located to the rear left. In this case, the CPU 11 estimates that the rear tire has driven over an obstacle only when the internal pressure value of the rear tire falls outside the threshold range set for the rear tire, and the internal pressure value of the front tire also falls outside the threshold range set for the front tire.

[0084] As described above, the information processing device 10, with the above configuration, improves detection accuracy compared to the conventional method of determining whether or not the vehicle 50 has driven over an obstacle based on fluctuations in the internal pressure value of a single tire. As a result, the accuracy and efficiency of tire inspection are improved, enabling proper tire maintenance. Furthermore, the quality of road surface maintenance is improved, leading to an improved driving environment and enhanced vehicle handling stability. The number of tires used for obstacle detection in the information processing device 10 is not particularly limited. Specifically, the information processing device 10 may be configured to perform obstacle detection based on fluctuations in the internal pressure values ​​of a minimum of two to a maximum of six tires.

[0085] Furthermore, the information processing device 10 allows for setting thresholds according to the size of the rock to be detected, making it possible to apply optimal detection criteria for each user and area. This is expected to improve user operational efficiency by detecting only necessary overruns and suppressing unnecessary detections.

[0086] (Second Embodiment) Next, a second embodiment of the information processing system 1 according to this embodiment will be described, omitting or simplifying parts that overlap with the above embodiment.

[0087] Figure 5 is a second block diagram showing the hardware configuration of the information processing device 10 according to this embodiment.

[0088] Similar to the above embodiment, the communication I / F 16 of the information processing device 10 communicates wirelessly with the communication device 25 of the vehicle 50. The communication device 25 is installed in the vehicle 50 and communicates with the TPMS 20 and transmitter 28 of each tire of the vehicle 50. The transmitter 28 communicates with the load sensor 27 mounted on the vehicle 50. The load sensor 27 is a sensor that acquires load information indicating the load of the cargo on the vehicle 50. The load sensor 27 is mounted on multiple axles and measures the load on each axle in real time, making it possible to accurately grasp the loading state of the entire vehicle 50 as load information. The transmitter 28 then transmits the load information acquired by the load sensor 27 to the communication device 25. The communication device 25 transmits the acquired load information to the information processing device 10. The information processing device 10 stores the acquired load information in the database 14B. The measurement by the load sensor 27 is performed continuously or at a preset sampling interval.

[0089] Figure 6 is a second flowchart showing the flow of estimation processing performed by the information processing device 10. In the second embodiment, the information processing device 10 executes a subroutine based on the following step S20 between step S10 and step S11.

[0090] In step S20 shown in Figure 6, the CPU 11 executes a threshold update process to update the threshold obtained in step S10.

[0091] Figure 7 is a first flowchart showing the flow of the threshold update process executed by the information processing device 10.

[0092] In step S30 shown in Figure 7, the CPU 11 obtains load information indicating the load of the vehicle 50 from the database 14B. Then, the CPU 11 proceeds to step S31.

[0093] In step S31, the CPU 11 updates the threshold for each of the multiple tires based on the load information acquired in step S30. For example, if the load is 10 tons (10,000 kg) or more, the load on the tires increases, so the threshold is raised by 20 kPa. On the other hand, if the load is less than 5 tons (5,000 kg), the load on the tires is reduced, so the threshold is lowered by 10 kPa. After that, the CPU 11 returns to the main routine and proceeds to step S11 shown in Figure 6.

[0094] As explained above, in the information processing device 10, the CPU 11 acquires load information indicating the load of the cargo on the vehicle 50. Then, the CPU 11 updates the threshold values ​​for each of the multiple tires based on the acquired load information. As a result, the information processing device 10 can appropriately correct the effect of tire pressure due to fluctuations in load and set optimal threshold values ​​according to load conditions, thereby improving the accuracy of obstacle detection adapted to driving conditions.

[0095] (Third Embodiment) Next, a third embodiment of the information processing system 1 according to this embodiment will be described, omitting or simplifying parts that overlap with the above embodiments.

[0096] In the third embodiment, a user working in a mine using multiple vehicles 50 inputs tire condition information indicating the extent of tire damage into a predetermined terminal and transmits it to the information processing device 10. The information processing device 10 stores the acquired tire condition information in the database 14B.

[0097] Tire condition information, for example, shows the cut occurrence rate per unit period. The cut occurrence rate is calculated as follows: Let N be the total number of tires inspected by the user in the past month, and M be the number of tires recorded as having a cut. Then, the cut occurrence rate (%) is calculated using the following formula: Cut occurrence rate (%) = (M / N) × 100

[0098] For example, if a user inspects 20 tires in the past month and one of them has a cut, the cut rate would be (1 / 20) x 100 = 5%.

[0099] Figure 8 is a second flowchart showing the flow of the threshold update process executed by the information processing device 10.

[0100] In step S40 shown in Figure 8, the CPU 11 obtains tire condition information from the database 14B. Then, the CPU 11 proceeds to step S41.

[0101] In step S41, the CPU 11 updates the threshold values ​​for each of the multiple tires in the multiple vehicles 50 used by the user, based on the tire condition information acquired in step S40. For example, if the tire condition information indicates that "the cut occurrence rate corresponding to the user in the inspection data for the past month is 5% or less," the threshold is increased by 10 kPa, and the sensitivity of the overrun detection is reduced. On the other hand, if the tire condition information indicates that "the cut occurrence rate corresponding to the user in the inspection data for the past month is 20% or more," the threshold is reduced by 15 kPa, and the sensitivity of the overrun detection is increased. After that, the CPU 11 returns to the main routine and proceeds to step S11 shown in Figure 6.

[0102] In mining operations, the mining site where each user works can differ, resulting in significant variations in the working environment. Specifically, the properties of the ground and the hardness of the rocks that act as obstacles vary from site to site, and furthermore, the type of tires used on the vehicles differs from user to user, leading to fluctuations in tire durability and failure risk.

[0103] For example, in User A's mine, the ground is soft and the rocks are prone to crumbling, resulting in low rock hardness and relatively low tire wear. On the other hand, in User B's mine, the ground is hard and there are many sharp rocks, resulting in high rock hardness and frequent tire wear failures. Furthermore, even within the same user's mine, the road surface conditions differ depending on the work area, and the rate of tire wear changes. For example, area X in User A's mine is flat with few sharp rocks and relatively stable pavement, resulting in a low rate of tire wear. On the other hand, area Y has been newly excavated and has many sharp rocks, creating an environment where tire wear occurs frequently.

[0104] Thus, differences in mining environments, geological conditions, and the characteristics of the vehicles used result in variations in tire damage risk and durability, requiring appropriate tire management and adjustment of detection criteria for each user.

[0105] Therefore, in the information processing device 10, the CPU 11 acquires tire condition information indicating the damage status of tires according to the user who is working in the mine using multiple vehicles 50. Then, based on the acquired tire condition information, the CPU 11 updates the threshold values ​​for each of the multiple tires in the multiple vehicles 50 used by the user. As a result, the information processing device 10 makes it possible to set optimal threshold values ​​according to the characteristics of the usage environment and each vehicle 50, thereby improving the accuracy of overrun detection and optimizing tire maintenance management.

[0106] (Other) Although embodiments of the present disclosure have been described in detail above with reference to the attached drawings, the technical scope of the present disclosure is not limited to these examples. It is clear that a person with ordinary skill in the art of the present disclosure may conceive of various modifications or alterations within the scope of the technical idea set forth in the claims, and it is understood that these modifications or alterations also fall within the technical scope of the present disclosure.

[0107] Furthermore, the effects described in the above embodiments are descriptive or illustrative, and are not limited to those described in the above embodiments. In other words, the technology relating to this disclosure may produce other effects that would be obvious to a person of ordinary skill in the art of this disclosure from the descriptions in the above embodiments, in addition to or in lieu of the effects described in the above embodiments.

[0108] The processing described in the above embodiment can also be implemented using dedicated hardware circuits. In this case, it may be executed on one piece of hardware or on multiple pieces of hardware.

[0109] In the above embodiment, the information processing program 14A was stored in the storage 14. However, the invention is not limited to this, and the information processing program 14A may also be stored in the ROM 12.

[0110] In the above embodiment, the system may use only the internal pressure value corresponding to the reference temperature to estimate that the vehicle 50 has run over an obstacle. Specifically, the temperature sensor 21 measures the temperature of the gas inside the tire, and when it is confirmed that it has cooled to a set reference temperature (e.g., 25°C), the internal pressure value at that time is recorded as the internal pressure value corresponding to the reference temperature. Based on this trigger, the internal temperature of the tire and the internal pressure value at that time are transmitted to the information processing device 10. The CPU 11 of the information processing device 10 performs a threshold determination based on the acquired internal pressure value corresponding to the reference temperature. For example, if the internal pressure value corresponding to the reference temperature before driving was 850 kPa, and the internal pressure value corresponding to the reference temperature after driving was 790 kPa, the fluctuation range (60 kPa) exceeds the set threshold (plus or minus 50 kPa), so the CPU 11 determines that there is an abnormality and estimates that there is a high possibility that the vehicle 50 has run over an obstacle.

[0111] In the above embodiment, the detection accuracy may be improved by dynamically adjusting the threshold for detecting overruns according to the operating environment of the vehicle 50. Specifically, the CPU 11 acquires past driving data of the vehicle 50, load capacity, tire wear, and external environmental information (e.g., temperature, humidity, rainfall), and optimizes the threshold based on a machine learning algorithm. For example, since slippage is more likely to occur in rainy weather, the threshold for internal pressure fluctuations is set lower to prevent false detections. Also, if false detections occur frequently in a particular mining area, a threshold correction coefficient can be applied to achieve environmentally adaptive operation. Furthermore, this process may be configured to enable more accurate adjustments by utilizing past detection data stored in the database 14B of the information processing device 10.

[0112] In the above embodiment, the configuration may be modified to improve the accuracy of detecting overruns due to internal pressure fluctuations by considering changes in tire stiffness. Specifically, the CPU 11 acquires the internal tire temperature, wear degree, and driving load during driving using the temperature sensor 21 and the pressure sensor 22, and applies a tire stiffness change model based on this data. For example, since internal pressure fluctuations become larger in worn tires, a correction coefficient is introduced according to the tire condition to suppress false detections. Furthermore, by combining this with vibration frequency analysis and detecting abnormal stiffness changes, detection that takes into account the progression of damage becomes possible. The data for this stiffness correction may be stored in the database 14B and continuously updated.

[0113] In the above embodiment, the configuration may be modified to improve the accuracy of obstacle detection by utilizing suspension operation data. Specifically, the CPU 11 uses a suspension pressure sensor to acquire the amount of extension and contraction of the suspension and compares it with internal pressure fluctuations to distinguish between simple load fluctuations and obstacle encounters. For example, when the suspension compresses rapidly, it can be determined that there is a high probability of encountering a large obstacle, thus distinguishing it from fluctuations caused by simple road surface irregularities. Furthermore, the roll and pitching data of the vehicle 50 may also be analyzed simultaneously, and the configuration may be modified to correct obstacle detection when an abnormal tilt angle occurs.

[0114] In the above embodiment, the system may be configured to take into account the tire slip rate to prevent misjudgments in obstacle detection. Specifically, the CPU 11 integrates the tire rotation speed from the wheel speed sensor and the internal pressure fluctuation from the pressure sensor 22 to more accurately determine the occurrence of obstacle overrun. For example, if the tire internal pressure hardly changes despite slippage, it is determined that there is a high probability that the obstacle is slippery (e.g., a wet rock). Furthermore, the system may be configured to allow for more detailed classification of obstacles by comparing the slip rate of the drive wheels with the behavior of the non-drive wheels and detecting imbalances in the driving force.

[0115] In the above embodiment, the system may be configured to analyze vibration data when the tire drives over an obstacle and determine the material of the rock. Specifically, the CPU 11 applies vibration data acquired by the vibration sensor to a frequency analysis algorithm to estimate the hardness of the obstacle. For example, sharp rocks contain many high-frequency components, so by performing high-frequency analysis, it becomes possible to identify rocks with high hardness. Alternatively, the system may be configured to store past obstacle data in the database 14B and learn the characteristics of the vibration patterns, thereby enabling more accurate identification of the type of obstacle driven over.

[0116] In the above embodiment, the acceleration data and internal pressure fluctuation data of the vehicle 50 may be integrated to improve the accuracy of obstacle detection. Specifically, the CPU 11 analyzes the acceleration data of the vehicle 50 acquired by the IMU (Inertial Measurement Unit) and, when an abnormal impact occurs, determines that an obstacle has been encountered by combining it with the internal pressure fluctuation data. For example, an obstacle is detected only when the internal pressure rises sharply after a sudden change in acceleration. Alternatively, the system may be configured to apply corrections based on the overall behavior of the vehicle 50, taking into account changes in pitching and roll angles.

[0117] In the above embodiment, the system may be configured to perform appropriate corrections considering the relationship between the vehicle's speed and internal pressure fluctuations. Specifically, the CPU 11 combines the speed data from the speed sensor and the internal pressure data from the pressure sensor 22, and applies different threshold corrections for each speed. For example, when driving at low speeds, the effect of internal pressure fluctuations is large, so the threshold is lowered to detect sensitively, and when driving at high speeds, the threshold is raised to prevent false detections. In addition, the system may be configured to perform corrections for overshoot detection when the speed change is rapid, taking into account internal pressure fluctuations during deceleration and acceleration.

[0118] In each of the above embodiments, the term "processor" refers to a processor in a broad sense, and includes general-purpose processors (e.g., CPU: Central Processing Unit, etc.) and dedicated processors (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, Programmable Logical Device, etc.).

[0119] Furthermore, the processor operations in each of the above embodiments may not be performed by a single processor, but may also be performed by multiple processors located in physically separate locations working together. Alternatively, some or all of the operations performed by specific multiple processors in each of the above embodiments may be integrated and performed by a single processor. In addition, the order of the processor operations is not limited to the order described in each of the above embodiments, and may be changed as appropriate.

[0120] Furthermore, although the above embodiment describes an embodiment in which the information processing program 14A is pre-stored (installed) in the storage 14, the invention is not limited to this. The information processing program 14A may be provided in a form recorded on a recording medium such as a CD-ROM (Compact Disk Read Only Memory), DVD-ROM (Digital Versatile Disk Read Only Memory), and USB (Universal Serial Bus) memory. Alternatively, the information processing program 14A may be provided in a form that is downloaded from an external device via a network. The technology disclosed herein can also be applied to programs and program products.

[0121] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0122] The disclosure of Japanese Patent Application No. 2025-048466 is incorporated herein by reference in its entirety.

Claims

1. An information processing device comprising a processor, the processor acquiring tire-related information including the internal pressure values ​​of multiple tires in a vehicle, and estimating that the vehicle has run over an obstacle based on fluctuations in the internal pressure values ​​of one tire and other tires among the multiple tire internal pressure values ​​included in the tire-related information.

2. The information processing apparatus according to claim 1, wherein the processor estimates that the vehicle has driven over an obstacle based on fluctuations in the internal pressure values ​​of one front tire, which is the first tire, and one rear tire, which is the other tire.

3. The information processing apparatus according to claim 2, wherein the one front tire and the one rear tire are located at different positions in the longitudinal direction of the vehicle and on opposite sides in the lateral direction of the vehicle.

4. The information processing apparatus according to claim 1, wherein the processor obtains a reference internal pressure value set for each of the plurality of tires and a threshold value indicating the amount of variation from the reference internal pressure value, and estimates that the vehicle has driven over an obstacle when the internal pressure values ​​of one tire and the other tires fall outside the range of the threshold values ​​set for each of them.

5. The information processing apparatus according to claim 4, wherein the processor acquires load information indicating the load of the vehicle's cargo, and updates the threshold value of each of the plurality of tires based on the acquired load information.

6. The information processing apparatus according to claim 4, wherein the processor acquires tire condition information indicating the damage status of the tires according to a user performing work at a work site using a plurality of vehicles, and updates the threshold value for each of the plurality of tires in the plurality of vehicles used by the user based on the acquired tire condition information.

7. The information processing device according to claim 4, wherein the reference internal pressure value is an internal pressure value corresponding to a reference temperature, which is the temperature of the gas inside the tire in the vehicle before driving, and the processor converts the internal pressure values ​​of one tire and the other tire obtained during the driving of the vehicle into internal pressure values ​​corresponding to the reference temperature, and estimates that the vehicle has run over an obstacle when the converted internal pressure values ​​fall outside the range of thresholds set for each.

8. The information processing apparatus according to claim 1, wherein the processor estimates the size of the obstacle based on the magnitude of fluctuations in the internal pressure of the vehicle's tires.

9. The information processing apparatus according to claim 1, wherein the processor identifies the tire that has driven over the obstacle based on fluctuations in the internal pressure values ​​of the first tire and the other tire, and stores the tire that has driven over in a tire inspection list of candidates for tire inspection.

10. The information processing apparatus according to claim 1, wherein the processor outputs the position indicated by the position information when the tire that has driven onto the obstacle has driven onto the obstacle as the position of the obstacle.

11. The information processing apparatus according to claim 8, wherein the processor outputs a priority order for road surface maintenance based on the estimated size of the obstacle.

12. The information processing apparatus according to claim 10, wherein the processor outputs a priority order for road surface maintenance based on the estimated location of the obstacle.

13. An information processing method in which a computer performs a process to acquire tire-related information including the internal pressure values ​​of multiple tires on a vehicle, and to estimate that the vehicle has run over an obstacle based on the fluctuations in the internal pressure values ​​of one tire and the other tires among the multiple tire internal pressure values ​​included in the tire-related information.

14. An information processing program that causes a computer to perform a process to acquire tire-related information, including the internal pressure values ​​of multiple tires on a vehicle, and to estimate that the vehicle has run over an obstacle based on fluctuations in the internal pressure values ​​of one tire and the other tires among the multiple tire internal pressure values ​​included in the tire-related information.

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