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

Abstract

To improve the controllability of a vehicle.SOLUTION: An information processing device 1 which can communicate with a vehicle 5 through a network includes a control part, and the control part executes operation including: acquiring tire related information; calculating an operation control parameter on the basis of the tire related information; and transmitting the operation control parameter to the vehicle 5.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present disclosure relates to an information processing device, an information processing method, a program, an operation control device, an operation control method, and a program. [Background technology]

[0002] BACKGROUND ART Conventionally, there is known a technique for restricting the autonomous driving of a vehicle when it is determined that the condition of the vehicle's tires is not suitable for the autonomous driving (for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Laid-Open No. 2018-167645 Summary of the Invention [Problem to be solved by the invention]

[0004] The above-mentioned background art does not take into consideration the fact that the state of the tires is reflected in the control of the vehicle.

[0005] In view of the above circumstances, an object of the present disclosure is to provide an information processing device, an information processing method, a program, a driving control device, a driving control method, and a program that can improve the controllability of a vehicle. [Means for solving the problem]

[0006] An information processing device according to an embodiment of the present disclosure includes: An information processing device capable of communicating with a vehicle via a network, the information processing device including a control unit, Obtaining tire-related information; Calculating a driving control parameter based on the tire-related information; transmitting the driving control parameters to the vehicle; Perform an action including:

[0007] An information processing method according to an embodiment of the present disclosure includes: An information processing method by an information processing device capable of communicating with a vehicle via a network, Obtaining tire-related information; Calculating a driving control parameter based on the tire-related information; transmitting the driving control parameters to the vehicle; Includes.

[0008] A program according to an embodiment of the present disclosure includes: It is a program for causing a computer to function as the information processing device.

[0009] An operation control device according to an embodiment of the present disclosure includes: An operation control device capable of communicating with an information processing device via a network, acquiring, from the information processing device, driving control parameters calculated based on tire-related information; Controlling the operation of the vehicle based on the operation control parameters; Perform an action including:

[0010] An operation control method according to an embodiment of the present disclosure includes: An operation control method using an operation control device capable of communicating with an information processing device via a network, acquiring, from the information processing device, driving control parameters calculated based on tire-related information; Controlling the operation of the vehicle based on the operation control parameters; Includes.

[0011] A program according to an embodiment of the present disclosure includes: This is a program for causing a computer to function as the operation control device. [Effects of the Invention]

[0012] According to an embodiment of the present disclosure, the information processing device, the information processing method, the program, the driving control device, the driving control method, and the program can improve the controllability of a vehicle. [Brief explanation of the drawings]

[0013] [Figure 1] 1 is a schematic diagram of an information processing system according to an embodiment of the present invention. [Figure 2] FIG. 1 is a block diagram showing a configuration of an information processing device. [Figure 3] FIG. 2 is a block diagram showing the configuration of a first vehicle. [Figure 4] FIG. 10 is a block diagram showing the configuration of a second vehicle. [Figure 5] FIG. 2 is a diagram showing the data structure of a tire-related information DB (database). [Figure 6] 10 is a graph showing a change in gain depending on a wear rate and a load. [Figure 7] 10 is a graph showing a change in gain depending on the wear rate and road surface condition. [Figure 8] FIG. 10 is a diagram showing the turning of a first vehicle. [Figure 9] 10 is a flowchart showing the operation of the information processing device and the second vehicle. DETAILED DESCRIPTION OF THE INVENTION

[0014] 1 is a schematic diagram of an information processing system S according to this embodiment. The information processing system S includes an information processing device 1, an external information processing device 2, a first vehicle 3, a tire 4 mounted on the first vehicle 3, and a second vehicle 5. The information processing device 1, the external information processing device 2, the first vehicle 3, the tire 4, and the second vehicle 5 can communicate with each other via a network NW. The network NW includes, for example, a mobile communication network or the Internet.

[0015] 1 illustrates one information processing device 1 for ease of explanation. However, the number of information processing devices 1 is not limited to this. For example, the processing executed by the information processing device 1 may be executed by multiple information processing devices 1 that are distributed.

[0016] The information processing device 1 is installed in a facility dedicated to the business operator or a facility such as a data center. The information processing device 1 is a computer such as a server belonging to a cloud computing system or other computing system. The information processing device 1 may be a server that supports the business operator in providing services. As an alternative example, the information processing device 1 may be mounted on the first vehicle 3 or the second vehicle 5. Another cloud computing system may be interposed between the information processing device 1 and the first vehicle 3 or the second vehicle 5.

[0017] The internal configuration of the information processing device 1 will be described in detail with reference to FIG.

[0018] The information processing device 1 includes a control unit 11, a communication unit 12, and a storage unit 13. The components of the information processing device 1 are connected to each other via, for example, a dedicated line so that they can communicate with each other.

[0019] The control unit 11 includes, for example, one or more general-purpose processors including a CPU (Central Processing Unit) or an MPU (Micro Processing Unit). The control unit 11 may include one or more dedicated processors specialized for specific processing. Instead of including a processor, the control unit 11 may include one or more dedicated circuits. The dedicated circuits may be, for example, a FPGA (Field-Programmable Gate Array) or an ASIC (Application Specific Integrated Circuit).

[0020] The communication unit 12 includes a communication module compatible with one or more wired or wireless LAN (Local Area Network) standards for connecting to a network. The communication unit 12 may include a module compatible with one or more mobile communication standards including LTE (Long Term Evolution), 4G (4th Generation), or 5G (5th Generation). The communication unit 12 may include a communication module compatible with one or more short-range communication standards or specifications including Bluetooth (registered trademark), AirDrop (registered trademark), IrDA, ZigBee (registered trademark), FeliCa (registered trademark), or RFID. The communication unit 12 transmits and receives any information via the network.

[0021] The memory unit 13 is, for example, a semiconductor memory, a magnetic memory, an optical memory, or at least one of these, a RAM or a ROM. The RAM is, for example, an SRAM or a DRAM. The ROM is, for example, an EEPROM. The memory unit 13 may function as, for example, a main memory device, an auxiliary memory device, or a cache memory. The memory unit 13 may store information resulting from analysis or processing by the control unit 11. The memory unit 13 may store various information related to the operation or control of the information processing device 1. The memory unit 13 may store system programs, application programs, embedded software, etc.

[0022] The external information processing device 2 is provided outside the information processing device 1. The hardware configuration of the external information processing device 2 is the same as that of the information processing device 1, and will not be described here.

[0023] The external information processing device 2 may be, for example, a device that remotely monitors tires by periodically measuring tire-related information from a device attached to the wheel of any tire. The tire-related information here may include at least one of the following: Wear condition Load (wheel load) Internal pressure / temperature Tire type

[0024] As an alternative example, the external information processing device 2 may be a device that provides a map platform. In this case, the external information processing device 2 collects the following information as tire-related information: The condition of the road surface under another vehicle traveling in front of the first vehicle 3 - Temperature of the area where the first vehicle 3 will be traveling

[0025] The first vehicle 3 may be any type of automobile, such as a gasoline vehicle, a diesel vehicle, an HEV, a PHEV, a BEV, or an FCEV. "HEV" is an abbreviation for hybrid electric vehicle. "PHEV" is an abbreviation for plug-in hybrid electric vehicle. "BEV" is an abbreviation for battery electric vehicle. "FCEV" is an abbreviation for fuel cell electric vehicle. The operation of the first vehicle 3 may be automated at any level. The level of automation may be, for example, any of levels 1 to 5 in the SAE classification. "SAE" is an abbreviation for Society of Automotive Engineers. Alternatively, the first vehicle 3 may be driven by a driver.

[0026] With reference to FIG. 3, the internal configuration of the first vehicle 3 will be described in detail.

[0027] The first vehicle 3 includes a driving control device 31, an ECU (Electronic Control Unit) 32, and a CAN bus 33. The driving control device 31 may be operated by a user device 34, a Robocar PC 35, or the like.

[0028] The driving control device 31 is, for example, an ADS (Autonomous Driving Controller). The driving control device 31 acquires vehicle driving data (for example, G, steering angle, vehicle speed, etc.) related to the steering, accelerator, shift, brake, vehicle speed, distance, etc. of the first vehicle 3 from the ECU 32 via the CAN bus 33.

[0029] The driving control device 31 acquires tire-related information about the tire 4 and transmits it to the information processing device 1. The tire-related information may include at least one of the following, for example. Wear condition (determined from vehicle height or camera) Load (wheel load) Tire type (determined from a camera or RFID) (the tire type ID may be transmitted to the information processing device 1) Internal pressure / temperature (determined by TPMS) Road surface conditions (determined from camera, G-sensor or CAN data) -Vehicle driving data above

[0030] The vehicle driving data may be raw data when transmitted to the information processing device 1. The vehicle driving data may be used by sensor fusion together with other tire-related information to calculate driving control parameters.

[0031] The tire 4 is one or more tires mounted on the first vehicle 3. The tire 4 acquires tire-related information by itself and transmits it to the information processing device 1. The tire-related information may include at least one of the following: Wear condition (determined from G sensors in the tire or driving noise) Load / wheel load (determined by G sensors inside the tires, etc.) Internal pressure / temperature (determined by TPMS) Road surface conditions (determined by G sensors and strain sensors in the tires)

[0032] A method for determining road surface conditions from a G sensor disposed within a tire 4 is described in WO 2006 / 135090. A method for estimating road surface friction conditions from a strain sensor disposed within a tire 4 is described in JP 2005-345238. As an alternative method for estimating road surface conditions, one or more strain sensors may be disposed on the wheel or side of the tire 4 rather than within the tire 4.

[0033] The second vehicle 5 may be any type of automobile, such as a diesel vehicle, HEV, PHEV, BEV, or FCEV. The second vehicle 5 may be automated at any level. The level of automation may be, for example, any of levels 1 to 5 in the SAE classification. "SAE" is an abbreviation for Society of Automotive Engineers. Alternatively, the second vehicle 5 may be driven by a driver.

[0034] With reference to FIG. 4, the internal configuration of the second vehicle 5 will be described in detail.

[0035] The second vehicle 5 includes a driving control device 51, an accelerator 54A, a brake 55A, a steering wheel 56A, a shifter 57A, sensors 54B to 57B, and ECUs 54C to 57C. The driving control device 51 may be operated by a user device 52, a Robocar PC 53, or the like.

[0036] The driving control device 51 is, for example, an ADS. When the driving control device 51 acquires driving control parameters from the information processing device 1, the driving control device 51 electrically intervenes in signals sent from the sensors 54B to 57B to the ECUs 54C to 57C, respectively. In this manner, the driving control device 51 controls the driving of the second vehicle 5.

[0037] For ease of explanation, the first vehicle 3 and the second vehicle 5 are depicted as separate vehicles. Alternatively, the first vehicle 3 and the second vehicle 5 may be the same vehicle. That is, the control unit 11 may acquire tire-related information from the first vehicle 3, calculate driving control parameters, and transmit the calculated driving control parameters to the first vehicle 3.

[0038] The processing executed by the information processing system S of this embodiment will be described in detail below.

[0039] [Getting tire-related information] The control unit 11 of the information processing device 1 acquires tire-related information. The tire-related information is acquired from at least one of the external information processing device 2, the first vehicle 3, and the tire 4.

[0040] The timing of acquisition may be one of the following: When the first vehicle 3 requests it (for example, when the OS (Operating System) starts up) - When a specified period of time has passed since the timestamp of each tire-related information When an environmental change (e.g., a rise in tire rubber temperature) is detected

[0041] Immediately after the first vehicle 3 starts running, the control unit 11 may request transmission of temperature information of the tire 4 until the temperature of the tire 4 reaches a steady value. The temperature of the tire 4 may be detected from the TPMS, the outside air temperature, the solar radiation condition, or the like.

[0042] [Calculation of operation control parameters] The control unit 11 calculates driving control parameters based on the tire-related information. When the tire-related information is acquired from a vehicle (for example, the first vehicle 3), the control unit 11 acquires the tire-related information and vehicle identification information from the vehicle. As shown in Fig. 5, the control unit 11 stores the tire-related information and the calculated driving control parameters in the storage unit 13 in association with the vehicle identification information.

[0043] The driving control parameters may be calculated from a correlation map between the tire-related information and the driving control parameters, or may be calculated based on a function. The control unit 11 may update the correlation map or function using vehicle driving data (described later) such as CAN data. The correlation map or function may be stored in the storage unit 13 for each piece of tire-related information. The correlation map or function may be calculated from actual measurement data of the tire-related information and the vehicle driving data, or may be calculated from a tire model.

[0044] When the control unit 11 is unable to acquire at least some of the tire-related information, the control unit 11 may calculate driving control parameters corresponding to the tire condition with the greatest risk. For example, the control unit 11 may calculate driving control parameters with a small gain for the longitudinal direction of the vehicle. The control unit 11 may calculate different driving control parameters for the longitudinal direction and the lateral direction of the vehicle.

[0045] The control unit 11 may calculate or correct the driving control parameters based on the tire-related information as well as vehicle factors (such as the vehicle model) of the second vehicle 5 to which the driving control parameters are sent. The vehicle factors may be used by inversely estimating the equivalent CP based on vehicle driving data (such as CAN data).

[0046] The control unit 11 may estimate each piece of tire-related information from vehicle driving data. For example, the control unit 11 may estimate the wear state of the tire 4 from the driving distance.

[0047] The tire-related information may differ for each tire 4 mounted on the first vehicle 3. The control unit 11 may calculate the driving control parameters based on a representative value of each tire (such as an average of the left and right wheels or an average of all four wheels). As an alternative example, the control unit 11 may transmit to the second vehicle 5 a representative value of the driving control parameters (such as an average of all four wheels) calculated based on the wear state or internal pressure of each tire.

[0048] When using information on road surface conditions as tire-related information, the control unit 11 may acquire the tire-related information from a plurality of vehicles. In this case, the tire-related information may be acquired through inter-vehicle communication.

[0049] If the tire gain is fixed in driving control, the controllability of the vehicle gradually changes with changes in tire-related information. Therefore, the control unit 11 detects gain changes from the tire-related information and calculates driving control parameters to deal with the gain changes. For example, the control unit 11 may calculate driving control parameters so that the gain changes return to the state before the change, or may calculate driving control parameters so that the gain increases or decreases. Here, gain is a value that indicates responsiveness to driving operations. For example, the smaller the gain, the more difficult it is for the vehicle to turn when steering the vehicle. The smaller the gain, the more difficult it is for the vehicle to stop when braking.

[0050] A specific example in which driving control parameters are calculated from tire-related information including vehicle driving data will be described below.

[0051] <Example of calculating driving control parameters from tire-related information> As a first example, the control unit 11 acquires the load and the wear state as tire-related information. As shown in Fig. 6, the higher the load, the higher the gain. The higher the wear rate, the higher the gain.

[0052] As a second example, the control unit 11 acquires road surface conditions and wear conditions as tire-related information. As the tire 4 wears, the tread becomes thinner and the grooves become shallower. Shallower grooves increase the rigidity of the tread, so the gain increases when the road surface is dry (corresponding to "Dry") as shown in FIG. 7. Conversely, when the road surface is wet (corresponding to "Wet"), drainage is poor, so the more worn the tire 4 is, the more slippery it becomes. As a result, the gain decreases.

[0053] <Example of calculating driving control parameters from vehicle driving data> As a first example, as shown in Fig. 8, when the turning radius R of the first vehicle 3 is known from position information such as a GPS (Global Positioning System), the control unit 11 can calculate the lateral G from the turning radius R and the vehicle speed V. The control unit 11 can estimate the gain change of the tire 4 from the relationship between the lateral G, the steering wheel operation amount, and the turning radius R. In this case, the control unit 11 estimates the gain change from the characteristic that the steering wheel operation amount that establishes the equation of motion changes depending on the wear state. For example, the control unit 11 can also estimate the mass point system μ in conjunction with load estimation such as CAIS (analysis of in-tire acceleration sensor data).

[0054] For example, the control unit 11 can determine that the gain of the tire 4 has increased due to a decrease in the required steering amount of the steering wheel. If it is raining, the control unit 11 can detect a decrease in drainage and a decrease in gain due to wear due to an increase in the steering amount of the steering wheel.

[0055] 8, a two-wheel model is used as the vehicle model of the first vehicle 3. As an alternative example, a two-degree-of-freedom mass system model may be used as the vehicle model of the first vehicle 3.

[0056] As a second example, the control unit 11 can estimate that the gain of the tires relative to the longitudinal G has changed from the amount of braking applied to the first vehicle 3 and the braking distance calculated from the position information. In this case, the control unit 11 can estimate the mass system μ in combination with load estimation such as CAIS.

[0057] For example, the control unit 11 determines that the gain of the tire has increased due to a decrease in the amount of braking required in fine weather. The control unit 11 can detect a decrease in drainage and gain due to wear due to an increase in the amount of braking required in rainy weather.

[0058] The control unit 11 may use an estimator called a state observer to calculate the driving control parameters. As a backup in the system, the estimator can pass vehicle driving data through an optimized filter to estimate the unmeasurable gain and μ.

[0059] <Another example of calculating driving control parameters from vehicle driving data> As a first example, the control unit 11 may calculate the control parameters from the time change of the Lissajous waveform of the vehicle travel data "vehicle side input vs. vehicle response." The relationship between the vehicle side input and the vehicle response is as follows. [Table 1]

[0060] As a second example, the control unit 11 may estimate an MF (Magic Formula) tire model based on "vehicle input vs. vehicle response" of the vehicle driving data, and calculate the control parameters using the estimated tire model. Since the vehicle response can be predicted based on the vehicle input and a simulation model of the vehicle and tires, the control unit 11 can estimate the tire model from the vehicle input and the vehicle response if the vehicle model is provided.

[0061] The control unit 11 may remove the influence of the tires (longitudinal / lateral springs, rotational springs, etc.) in the vehicle model (simulation) based on tire-related information (wear state, etc.).

[0062] <Example of calculating tire-related information from vehicle driving data> As a first example, the control unit 11 may calculate the dynamic loaded radius from the vehicle speed and the tire rotation speed, and calculate the wear state of the tire 4 from the difference between the calculated dynamic loaded radius and the dynamic loaded radius of a new tire.

[0063] As a second example, the control unit 11 may determine the tire wear state of the tire 4 from sprung vibration (acceleration), which is one of the vehicle driving data. The wear state may be determined from vibration information acquired in advance for each wear state, or may be determined from a vibration simulation.

[0064] As a third example, the control unit 11 may inversely estimate the road surface μ (tire μ) from the current behavior of the first vehicle 3 and the wear state of the tires 4.

[0065] [Send operation control parameters] The control unit 11 transmits the calculated driving control parameters to the second vehicle 5 via the communication unit 12. The transmission may be performed in response to a request when the OS of the second vehicle 5 is started. Alternatively, when the tire-related information is acquired from the first vehicle 3, the driving control parameters may be transmitted to the first vehicle 3 identified by the vehicle identification information.

[0066] In this embodiment, the control unit 11 may charge a fee to the destination for providing the driving control parameters. When determining the fee to be charged for providing the driving control parameters, the control unit 11 may calculate the fee based on the number of requests from the second vehicle 5.

[0067] [Operation control] The second vehicle 5 acquires the driving control parameters from the information processing device 1. The driving control parameters are parameters corresponding to tire-related information.

[0068] The driving control device 51 of the second vehicle 5 controls driving based on the driving control parameters. The driving control parameters may be applied to at least one gain of the acceleration or deceleration (longitudinal G) and steering (lateral G) of the second vehicle 5.

[0069] The driving control device 51 may set different gains for acceleration and deceleration for the same driving control parameters. The driving control device 51 may change the gains depending on the load on each wheel.

[0070] [Sequence diagram] With reference to FIG. 9, an information processing method and a driving control method performed by the control unit 11 of the information processing device 1 and the driving control device 51 of the second vehicle 5 will be described.

[0071] In step S1, the control unit 11 acquires tire-related information via a network.

[0072] In step S2, the control unit 11 calculates driving control parameters based on the tire-related information.

[0073] In step S3, the control unit 11 transmits the driving control parameters to the second vehicle 5.

[0074] In step S4, the second vehicle 5 acquires the driving control parameters from the information processing device 1.

[0075] In step S5, the second vehicle 5 executes driving control of the second vehicle 5 based on the acquired driving control parameters.

[0076] As described above, according to this embodiment, the control unit 11 executes operations including acquiring tire-related information, calculating driving control parameters based on the tire-related information, and transmitting the driving control parameters to the second vehicle 5. Since the information processing device 1 calculates the driving control parameters in this manner, it is possible to improve the controllability of the vehicle.

[0077] Furthermore, according to this embodiment, the operation of the control unit 11 includes acquiring tire-related information and vehicle identification information from the first vehicle 3, and transmitting driving control parameters to the vehicle identified by the vehicle identification information. The operation also includes acquiring tire-related information from tires 4 of the first vehicle 3. The operation further includes acquiring tire-related information from an external information processing device. With this configuration, the information processing device 1 can acquire a variety of tire-related information, thereby enabling it to calculate optimal driving control parameters.

[0078] Furthermore, according to this embodiment, the operation includes calculating a driving control parameter corresponding to the tire condition that poses the greatest risk when at least a portion of the tire-related information cannot be acquired. With this configuration, the information processing device 1 can reduce the risk of an accident, etc.

[0079] Furthermore, according to this embodiment, the operation includes calculating the driving control parameters based on the vehicle factors of the second vehicle 5 to which the driving control parameters are sent. With this configuration, the information processing device 1 can calculate driving control parameters that are suitable for the individual circumstances of the second vehicle 5.

[0080] Furthermore, according to this embodiment, the operation includes transmitting the driving control parameters to the second vehicle 5 in response to a request made when the OS is started in the second vehicle 5. This configuration enables the information processing device 1 to transmit the driving control parameters early before the second vehicle 5 starts traveling.

[0081] Although the present disclosure will be described based on various drawings and examples, it should be noted that those skilled in the art may make various modifications and alterations based on the present disclosure. Other modifications are possible within the scope of the present disclosure. For example, the functions included in each means or step may be rearranged so as not to cause logical inconsistencies, and multiple means or steps may be combined or divided into one.

[0082] For example, in the above-described embodiment, a program for executing all or part of the functions or processes of the information processing device 1 can be recorded on a computer-readable recording medium. Computer-readable recording media include non-transitory computer-readable media, such as magnetic recording devices, optical discs, magneto-optical recording media, or semiconductor memories. The program can be distributed, for example, by selling, transferring, or lending a portable recording medium, such as a DVD (Digital Versatile Disc) or CD-ROM (Compact Disc Read Only Memory), on which the program is recorded. The program can also be distributed by storing the program in the storage of a server and transmitting the program from the server to another computer. The program can also be provided as a program product. The present disclosure can also be realized as a program executable by a processor.

[0083] A computer temporarily stores a program recorded on a portable recording medium or transferred from a server in its main storage device. The computer then reads the program stored in the main storage device using a processor and executes processing in accordance with the read program. The computer may also read the program directly from a portable recording medium and execute processing in accordance with the program. The computer may also execute processing in accordance with the received program each time a program is transferred from a server to the computer. Processing may also be executed through a so-called ASP-type service that achieves its functions simply by issuing execution instructions and obtaining results, without transferring the program from the server to the computer. "ASP" is an abbreviation for application service provider. Programs include information used for processing by a computer that is equivalent to a program. For example, data that does not directly instruct a computer but has properties that define computer processing falls under the category of "equivalent to a program." [Explanation of symbols]

[0084] S Information Processing System NW Network 1. Information processing equipment 11 Control section 12 Communications Department 13 Storage section 2. External information processing device 3 First car 31 Operation control device 32 ECU 33 CAN bus 34 User device 34 35 Robocar PC 4 tires 5 Second vehicle 51 Operation control device 52 User Device 53 Robocar PC 54A Accelerator 55A Brake 56A Steering 57A Shift 54B to 57B Sensors 54C to 57C ECU

Claims

1. An information processing device capable of communicating with a vehicle via a network, the information processing device including a control unit, Obtaining tire-related information; Calculating driving control parameters for controlling acceleration, deceleration, and steering of the vehicle performing automatic driving based on the tire-related information, the driving control parameters being calculated using a correlation map or function calculated in advance from actual measurement data of the tire-related information and vehicle driving data; transmitting the driving control parameters to the vehicle; calculating a driving control parameter corresponding to a tire condition with the highest risk when at least a part of the tire-related information cannot be acquired; An information processing device that performs operations including:

2. 2. The information processing apparatus according to claim 1, wherein the operation is: acquiring the tire-related information and vehicle identification information from the vehicle; transmitting the driving control parameters to a vehicle identified by the vehicle identification information; An information processing device comprising:

3. 3. The information processing device according to claim 1, wherein the operation is: and acquiring tire-related information from tires of the vehicle.

4. 4. The information processing device according to claim 1, wherein the operation is: and acquiring the tire-related information from an external information processing device.

5. 5. The information processing device according to claim 1, wherein the operation is: An information processing device that calculates the driving control parameters based on vehicle factors of the vehicle that is a destination of the driving control parameters.

6. 6. The information processing device according to claim 1, wherein the operation is: and transmitting the driving control parameters to the vehicle in response to a request at the time of booting an OS (Operating System) in the vehicle.

7. 7. The information processing device according to claim 1, An information processing device in which the driving control parameter is calculated so as to increase or decrease a gain, which is a value indicating responsiveness to driving operation.

8. An information processing method by an information processing device capable of communicating with a vehicle via a network, Obtaining tire-related information; Calculating driving control parameters for controlling acceleration, deceleration, and steering of the vehicle performing automatic driving based on the tire-related information, the driving control parameters being calculated using a correlation map or function calculated in advance from actual measurement data of the tire-related information and vehicle driving data; transmitting the driving control parameters to the vehicle; calculating a driving control parameter corresponding to a tire condition with the highest risk when at least a part of the tire-related information cannot be acquired; An information processing method, including:

9. A program for causing a computer to function as the information processing device according to any one of claims 1 to 7.

10. An operation control device capable of communicating with the information processing device according to any one of claims 1 to 7 via a network, acquiring, from the information processing device, driving control parameters calculated based on tire-related information; Controlling the operation of the vehicle based on the operation control parameters; An operation control device that performs an operation including the steps of:

11. An operation control method using an operation control device capable of communicating with the information processing device according to any one of claims 1 to 7 via a network, comprising: acquiring, from the information processing device, driving control parameters calculated based on tire-related information; Controlling the operation of the vehicle based on the operation control parameters; An operation control method including:

12. A program for causing a computer to function as the operation control device according to claim 10.

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