Straddled vehicle-related css

The straddle-type vehicle CSS uses an LLM to generate and output CHL information, addressing the challenges of high-level interaction in saddle-type vehicles by enhancing cooperation and reducing hardware resource load.

WO2025248779A1PCT designated stage Publication Date: 2025-12-04YAMAHA MOTOR CO LTD
View PDF 2 Cites 0 Cited by

Patent Information

Application Number
PCT/JP2024/020100
Authority / Receiving Office
WO · WO
Patent Type
Applications
Current Assignee / Owner
Filing Date
2024-05-31
Publication Date
2025-12-04

AI Technical Summary

Technical Problem

Saddle-type vehicles that can turn in a lean position face challenges in achieving high-level interaction with riders due to increased factors to consider, available information, and requirements for timely and appropriate information output, leading to higher hardware resource demands and lengthy data collection needs.

Method used

A straddle-type vehicle-related character simulating system (CSS) utilizing a Large Scale Language Model (LLM) to generate and output Communicative Human Language (CHL) information, with reduced data volume, to enhance rider cooperation and reduce hardware resource load.

Benefits of technology

The system effectively enhances the sense of cooperation between the saddle-type vehicle and the rider, improving well-being while reducing hardware resource demands, enabling advanced interaction with reduced data volume and timely information output.

✦ Generated by Eureka AI based on patent content.

Smart Images

  • Figure JP2024020100_04122025_PF_FP_ABST
    Figure JP2024020100_04122025_PF_FP_ABST
Patent Text Reader

Abstract

The objective of the present invention is to construct a system capable of enhancing a rider's wellbeing by effectively and efficiently strengthening a sense of collaboration between a straddled vehicle and the rider, and to reduce the load on the hardware resources that constitute the system. In a system according to the present invention, prompt data for character simulation are generated using data acquired by means of data acquisition processing and character simulation data. The prompt data are supplied to an LLM, and character-simulated linguistic interpretation data are obtained from the LLM. Using the linguistic interpretation data, character-simulated CHL information indicating a linguistic interpretation result is output from an output device. When data for setting the character simulation are input, the character simulation data are updated on the basis of the data.
Need to check novelty before this filing date? Find Prior Art

Description

Straddled vehicle related CSS

[0001] The present invention relates to a CSS (character simulating system) for a straddle-type vehicle.

[0002] Patent Literature 1 discloses a conversation information output device for a vehicle. The conversation information output device outputs conversation information corresponding to a generated pseudo-emotion, and includes an acquisition unit that acquires operation information related to at least one driving operation performed by the driver, a determination unit that determines an operation level corresponding to the difficulty of the at least one driving operation performed by the driver based on the operation information acquired by the acquisition unit, a generation unit that generates a pseudo-emotion based on the operation level determined by the determination unit, a creation unit that creates conversation information to be output to the driver based on the pseudo-emotion generated by the creation unit, and an output unit that outputs the conversation information created by the creation unit. By outputting conversation information based on the pseudo-emotion, the device in Patent Literature 1 can make a saddle-type vehicle appear to have emotions.

[0003] Patent Document 2 discloses a vehicle conversation information output device. This vehicle conversation information output system outputs conversation information corresponding to a preset personality to a driver of the vehicle. The device includes an acquisition unit that acquires usage information regarding the driver's use of the vehicle; a change unit that changes the set personality based on the usage information acquired by the acquisition unit; a creation unit that creates conversation information to be output to the driver based on the personality changed by the change unit; and an output unit that outputs the conversation information created by the creation unit to the driver. In the device of Patent Document 2, the conversation information includes at least one of the conversation content and the conversation frequency, and the usage information includes experience change information that changes as the driver's vehicle driving experience increases. The change unit changes the selected personality in accordance with the experience change information. The device of Patent Document 2 can give the impression of sharing memories of experiences gained while driving. This can increase the driver's attachment to the saddle-type vehicle.

[0004] International Publication No. 2018 / 189841 Japanese Patent No. 6906046

[0005] An object of the present invention is to effectively and efficiently enhance the sense of cooperation between the saddle-type vehicle and the rider, thereby improving the rider's well-being and reducing the load on hardware resources.

[0006] In view of the above problems, the present inventors have conducted extensive research and have obtained the following findings.

[0007] The saddle-type vehicle referred to in the present invention is configured to be able to turn in a lean position. That is, the saddle-type vehicle is equipped with handlebars, and is configured so that the rider leans the vehicle body and turns by shifting his or her weight while gripping the handlebars with both hands. As a result, when the saddle-type vehicle turns, the rider leans together with the vehicle body toward the inside of the curve. In this way, when turning, the rider uses his or her entire body to move the saddle-type vehicle, and the saddle-type vehicle is configured to lean together with the rider in response to the rider's movement. Turning such a saddle-type vehicle can feel to the rider like a collaborative effort between the rider and the saddle-type vehicle. Therefore, compared to vehicles other than saddle-type vehicles that can turn in a lean position, such as ordinary four-wheeled automobiles (hereinafter also referred to as non-lean vehicles), the saddle-type vehicle is a vehicle that is more likely to create a sense of unity with the rider. The stronger the sense of unity the rider feels with the saddle-type vehicle, the more enjoyable the rider's experience of driving the saddle-type vehicle.

[0008] As such, compared to non-lean vehicles, saddle-ride vehicles are vehicles that tend to make the act of driving itself more enjoyable, and by enhancing the sense of collaboration between the saddle-ride vehicle and the rider, the rider's well-being can be improved. The sense of collaboration between the saddle-ride vehicle and the rider can be enhanced not only by the response of the saddle-ride vehicle (vehicle body) to the rider's operations, but also by the provision of information from the saddle-ride vehicle to the rider. However, while providing information from the saddle-ride vehicle to the rider can dramatically enhance the sense of collaboration if done well, there is a risk that the sense of collaboration may be significantly impaired if done poorly. Even if the saddle-ride vehicle responds well to the rider's operations, if the saddle-ride vehicle provides information to the rider poorly, the rider's impression of the saddle-ride vehicle will be negatively affected. Therefore, it is important to consider how information is provided from the saddle-ride vehicle to the rider.

[0009] In order to successfully provide information from a saddle-type vehicle to a rider, the rider's preferences, emotions, personality, and situation must be acquired in greater detail, increasing the number of factors that must be considered as input information. In addition, the output information, such as the content, transmission method, and transmission timing of the information, must also be set in greater detail, increasing the number of factors that must be considered. In other words, in order to achieve a higher level of interaction between the saddle-type vehicle and the rider, the number of factors that must be considered increases.

[0010] Furthermore, as described above, the saddle-type vehicle referred to in the present invention is configured to be able to turn in a lean position. Therefore, in addition to operating the accelerator, brakes, and steering, the rider must also shift his or her own weight to perform a turning operation in conjunction with steering. This weight shift and the resulting vehicle lean are not present in a non-lean vehicle, so compared to a non-lean vehicle, more information can be obtained from a saddle-type vehicle that can turn in a lean position. This can also be said to mean that there is more information available to achieve a higher level of interaction between the saddle-type vehicle and the rider. A notable example is a manual saddle-type vehicle in which different operations are performed with both hands and feet, as follows: Left hand: operates the clutch lever Right hand: operates the throttle (accelerator) and front brake lever Left foot: operates the gear shift pedal (however, gear shifting may also be performed using a manual lever) Right foot: operates the rear brake As the rider shifts his or her own weight, the operating parts corresponding to each of the hands and feet can be operated at different times for different vehicle operations, further increasing the amount of information that can be obtained. Saddle-type vehicles that can turn in a lean position are not limited to this example, but regardless of the type of vehicle, saddle-type vehicles that can turn in a lean position tend to have a greater variety of information that can be obtained compared to non-lean vehicles.

[0011] Furthermore, in a saddle-type vehicle that can turn in a lean position, it is difficult to obtain much information actively input from the rider other than driving operations while driving. Information actively input other than driving operations is likely to reflect the rider's emotions, which is important from the perspective of interaction with the saddle-type vehicle. However, in a saddle-type vehicle that can turn in a lean position, many parts of the body (both hands, both legs, and weight shift) are required for driving operations, and many working areas of the brain are used for driving, leaving little working area available for operations other than driving, making it difficult for sudden changes in emotions to occur. In addition, the installation space for operating parts other than driving operations (such as plywood panels) is smaller than in a non-lean vehicle. Therefore, it is difficult for the rider to actively input a large amount and variety of information other than driving operations while driving. As a result, while the variety and amount of information that can be obtained is large, the variety and amount of information actively input from the rider other than driving operations is limited.

[0012] As described above, in a saddle-type vehicle that can turn in a lean position, there are many factors that must be considered and a large amount of information that can be used to achieve a high level of interaction between the saddle-type vehicle and the rider. To achieve this high level of interaction between the saddle-type vehicle and the rider, it is necessary to take these factors and information into account and provide outputs that are more easily accepted by the rider in a more timely manner. This presents a particular challenge for high-level interaction between the saddle-type vehicle that can turn in a lean position and the rider.

[0013] As the above-mentioned trends of "increasing factors to be considered," "increasing amount of available information," and "higher demands for timeliness and appropriateness of output" become stronger, the load on the hardware resources required for the information output system increases, and more hardware resources are required. In addition, since a large amount of learning data needs to be collected, preparation takes a long time. The devices disclosed in Patent Documents 1 and 2 also have a similar problem. That is, the devices disclosed in Patent Documents 1 and 2 have the problem of requiring enormous hardware resources and learning data in order to achieve high-level interaction between the saddle-riding vehicle and the rider to a degree that can enhance the sense of cooperation between the saddle-riding vehicle and the rider.

[0014] The present invention has been completed based on the above findings, and can provide the following straddle-type vehicle-related character simulating system.

[0015] (1) A CSS related to a saddle-riding vehicle, the CSS related to a saddle-riding vehicle including: at least one memory; at least one processor capable of communicating with an LLM (Large Scale Language Model), connected to the memory, and configured to execute at least one program stored in the memory; at least one first input device provided on the saddle-riding vehicle or an accessory or a carried item of a rider of the saddle-riding vehicle; and at least one output device provided on the saddle-riding vehicle or an accessory or a carried item of a rider of the saddle-riding vehicle, and configured to output CHL (Communicative Human Language) information, the at least one program including a data acquisition process for acquiring at least one type of data related to the saddle-riding vehicle or its rider from the at least one input device, and / or acquiring CHL information input from the rider to the at least one first input device as data from the at least one first input device; a prompt generation process that generates character simulating prompt data that can be linguistically interpreted by the LLM and has a reduced amount of data, using the data acquired by the data acquisition process and character simulating data that is stored in the memory and is used to generate prompts customized to express a pseudo-character of the saddle riding type vehicle; a linguistic interpretation process that supplies the character simulating prompt data to the LLM and acquires character-simulated linguistic interpretation data that is generated through linguistic interpretation by the LLM; an output process that uses the character-simulated linguistic interpretation data to output character-simulated CHL information that indicates the linguistic interpretation result from the at least one output device; and a character setting process that receives input of data for setting the character simulating from the at least one first input device or at least one second input device different from the at least one first input device, and updates the character simulating data based on the input data.a CSS system for a straddle-type vehicle, the CSS system being programmed to cause the at least one processor to execute the following:

[0016] In the system (1), an LLM is used to provide information from the saddle-ride type vehicle to the rider in order to effectively and efficiently enhance the sense of cooperation between the saddle-ride type vehicle and the rider. Additionally, the system (1) has a configuration suitable for using an LLM to provide information from the saddle-ride type vehicle to the rider. That is, in the system (1), character simulating prompt data is generated using data acquired from at least one first input device by a data acquisition process and character simulating data. The character simulating data is stored in a memory and is used to generate customized prompts to express a pseudo-character of the saddle-ride type vehicle. The character simulating prompt data is data with a reduced data volume that can be linguistically interpreted by the LLM. The character simulating prompt data is supplied to the LLM, and character-simulated linguistic interpretation data is obtained from the LLM. Furthermore, in the system (1), character-simulated CHL information indicating the linguistic interpretation result is output from an output device using the character-simulated linguistic interpretation data. Additionally, in the system (1), when data for setting the character simulating is input, the character simulating data is updated based on the input data. This allows for effective and efficient realization of high-level interaction between the saddle-type vehicle and the rider. As a result, the system (1) effectively and efficiently enhances the sense of cooperation between the saddle-type vehicle and the rider, thereby improving the rider's well-being and reducing the load on hardware resources. In other words, assuming the same hardware resources are used, more advanced processing is possible, thereby realizing higher-level interaction. The system (1) can respond at a high level to all of the "increase in factors to be considered," "increase in available information," and "increased requirements for timeliness and appropriateness of output" while reducing the load on hardware resources, thereby resolving the challenges (described above) specific to high-level interaction between a saddle-type vehicle capable of turning in a lean position and the rider.From the perspective of achieving the above-mentioned effects (achieving both "reduced load on hardware resources" and "high-level interaction"), a prompt generation process is performed using data acquired from the saddle-type vehicle or the rider, and / or data input by the rider, and character simulating data to generate prompt data (character simulating prompt data) that is linguistically interpretable, has a reduced amount of data, and is customized to express a pseudo-character of the saddle-type vehicle, and the generated prompt data is then supplied to the LLM. In this context, updating the character simulating data through a character setting process in relation to the prompt generation process has important technical significance.

[0017] The saddle-riding vehicle-related CSS includes at least one memory, at least one processor, at least one first input device, and at least one output device. These devices are communicatively connected to each other. These devices may be provided in a single device to form a centralized processing system, or may be provided in multiple devices communicatively connected to each other to form a distributed processing system. The saddle-riding vehicle-related CSS may further include at least one second input device. The at least one second input device is communicatively connected to the at least one processor. The at least one first input device is provided in the saddle-riding vehicle or an accessory equipped or carried by the rider thereof. The at least one memory may be provided in the saddle-riding vehicle, an accessory equipped or carried by the rider, a user terminal, or a server. The at least one processor may be provided in the saddle-riding vehicle, an accessory equipped or carried by the rider, a user terminal, or a server. The at least one output device is provided in the saddle-riding vehicle or an accessory equipped or carried by the rider thereof. The at least one output device may be provided in a user terminal, in addition to the saddle-riding vehicle or the rider's equipment or carried items. The at least one second input device may be provided, for example, in a device separate from the saddle-riding vehicle and the rider's equipment or carried items. The saddle-riding vehicle-related CSS according to the present invention may employ, for example, any of the system configurations (a) to (p) shown in FIGS. 2 and 3 . FIG. 2 illustrates a device in which a first input device (I), a processor (P), a memory (M), and an output device (O) are provided in the system configuration. FIG. 3 illustrates a device in which the first input device, the processor, and the output device are provided. For ease of understanding, FIGS. 2 and 3 use the same reference numerals as those used in the embodiments described below, but these reference numerals are not intended to limit the present invention. In FIG. 2 , the memory is provided in the device in which the processor is provided. In FIG. 3 , the memory is also provided in the device in which the processor is provided, although not shown. However, the present invention is not limited to this example.The memory may be provided in a device different from the device in which the processor is provided (e.g., a device in which the first input device and / or output device is provided). Although a device in which the second input device is provided is not shown in FIGS. 2 and 3 , the second input device may be provided in a device different from the device in which the first input device is provided. In FIGS. 2 and 3 , the output device may be provided in a device other than the saddle-type vehicle or the rider's equipment or personal belongings. For example, the output device may also be provided in a user terminal. Furthermore, there may be multiple first input devices, output devices, memories, and processors. Therefore, if a single system has multiple devices, the single system may satisfy the requirements of multiple system configurations among (a) to (p) shown in FIGS. 2 and 3 . There may also be multiple second input devices. An example of a system configuration will now be described. As a specific example, a smartwatch corresponding to a rider's personal item may comprise the system, since it includes at least one memory, at least one processor, at least one first input device, and at least one output device (see FIGS. 2(n) and 3(n)). As another specific example, the smartwatch may comprise the at least one first input device, a meter of the saddle-riding vehicle may comprise the at least one output device, and a server capable of communicating with the saddle-riding vehicle may comprise at least one memory and at least one processor (see FIGS. 2(l) and 3(l)). As yet another specific example, a sensor provided on the saddle-riding vehicle may comprise the at least one first input device, a meter of the saddle-riding vehicle may comprise the at least one output device, and a server capable of communicating with the saddle-riding vehicle may comprise at least one memory and at least one processor (see FIGS. 2(d) and 3(d)). In one example, the smartwatch is a saddle-ride vehicle-related IPG (Interactive Prompt Generator) that generates character-simulating prompt data to be provided to the LLM and retrieves character-simulated linguistic interpretation data from the LLM. In the second and third examples, the server is a saddle-ride vehicle-related IPG.In the saddle-riding-type vehicle-related CSS, all processes may be executed by a single processor, or each process may be executed by a different processor. The system may include: at least one first input device and at least one output device, each provided on the saddle-riding-type vehicle or on equipment or carried by the rider; and at least one processor and at least one memory, each provided on the saddle-riding-type vehicle, on equipment or carried by the rider, on a server, or on a user terminal (see (a) to (p) of FIGS. 2 and 3). In this case, since the output device is provided on the saddle-riding-type vehicle or on equipment or carried by the rider, output can be performed at appropriate times while the saddle-riding-type vehicle is traveling. The hardware configuration of the saddle-riding-type vehicle-related CSS is not particularly limited.

[0018] The output device is configured to output the CHL information. The output is performed visually or audibly. As shown in FIGS. 2 and 3 , the output device is provided on the saddle-riding type vehicle or on equipment or a carried item of the rider. For example, if the output device is on equipment or a carried item of the rider, the equipment or a carried item of the rider may be detachably attached in a position that is easily visible to the rider riding the saddle-riding type vehicle (for example, near the meter of the saddle-riding type vehicle). The output device may be provided on the saddle-riding type vehicle or on equipment or a carried item of the rider, or on, for example, a user terminal. The output device itself may have a function for communicating with the outside via a network. The output device may be connected to a control device included in an apparatus (saddle-riding type vehicle, equipment or a carried item of the rider, or a user terminal) in which the output device is provided, and may be controlled by the control device. In this case, the control device may have a function for communicating with the outside via a network. The output device outputs the CHL information visually or audibly. The output device is not particularly limited, and examples thereof include the following devices.・Meter (instrument panel) (presents visual output information) ・HMD (Head-Mounted Display) (presents visual output information) ・Speaker (presents auditory output information) ・Intercom (headset) (presents auditory output information) ・Mirror (presents visual output information using lights, etc.) ・Road surface illumination lights (presents visual output information) ・Roadside displays (presents visual output information) ・HUD (Head-Up Display) combiner (presents visual output information) ・HUD screen (presents visual output information) ・Smartphone (presents visual or auditory output information) ・Smartwatch (presents visual or auditory output information) ・Smartglasses (presents visual or auditory output information) ・Earphones (presents auditory output information) ・Bone conduction earphones (presents auditory output information)

[0019] As shown in FIGS. 2 and 3 , the first input device may be provided on the saddle-type vehicle, or on equipment or a portable item of the rider. The first input device is configured, for example, to acquire or generate at least one type of data related to the saddle-type vehicle or its rider over time while the saddle-type vehicle is traveling, and supply the at least one type of data to at least one processor. The at least one type of data related to the saddle-type vehicle or its rider may be, for example, saddle-type vehicle-related data or rider biometric data. The saddle-type vehicle-related data is, for example, data indicating saddle-type vehicle-related parameters that are related to the traveling state of the saddle-type vehicle and change as the saddle-type vehicle travels, detected by the first input device. The saddle-type vehicle-related data may be, for example, parameters that are not related to the traveling state of the saddle-type vehicle or that do not change as the saddle-type vehicle travels. Examples of such saddle-type vehicle-related data include the cumulative on / off period of a switch provided on the saddle-type vehicle, the continuous on / off period of the switch, etc. The lidar biometric data is, for example, data indicating lidar biometric parameters detected by the first input device. The first input device may function as an independent device and have a communication function so as to output data acquired or generated independently. The first input device functioning independently is not particularly limited, and examples thereof include a GPS (Global Positioning System) receiver, a GNSS (Global Navigation Satellite System) receiver, a chest strap equipped with a heart rate sensor, or a smart watch. The GPS receiver or GNSS receiver is provided, for example, in a saddle-type vehicle or in equipment or portable items of the rider. The chest strap or smart watch corresponds to the rider's equipment. The first input device may be configured by a combination of a detection device and a control device. In this case, examples of the detection device include a GPS module, a GNSS module, an IMU (Inertial Measurement Unit), and a heart rate sensor module provided on the handle grip of a saddle-type vehicle.Since riders typically wear gloves as protectors, when acquiring heart rates using a heart rate sensor module attached to a handlebar grip, it may be necessary to devise a method for acquiring heart rates. For example, an optical heart rate sensor module may be employed that can ensure light transmittance even through gloves. By using gloves with a light-transmitting portion, heart rates may be measured using the optical heart rate sensor module through the portion. For example, a pressure-type heart rate sensor configured to detect the pulse of a rider's finger even when the rider is wearing gloves may be employed. A pressure-type heart rate sensor may be employed on the assumption that the rider will wear gloves suitable for detecting finger pulses using the pressure-type heart rate sensor. An example of a control device is an electronic control unit (ECU). In this case, the ECU itself is not a first input device, but in combination with various modules, it functions as a first input device and outputs at least one type of data related to the saddle-type vehicle or its rider. In this way, the first input device, either as an independent device or in combination with the control device, realizes the function of outputting at least one type of data related to the saddle-riding type vehicle or its rider. Note that, hereinafter, unless otherwise specified, the term "first input device" is used to encompass both a method of communicating with the outside world independently and a method of communicating with the outside world via the control device. The first input device may be configured, for example, to generate data related to CHL information input by the rider while the saddle-riding type vehicle is traveling and supply the data to at least one processor. The first input device may be provided, for example, in an apparatus provided with a first input device that acquires or generates at least one type of data related to the saddle-riding type vehicle or its rider. The CHL information input by the rider may be, for example, audio information or text information.The CHL information input by the rider may be, for example, CHL information input by the rider to the first input device in response to CHL information visually or audibly output by the output device (e.g., CHL information corresponding to character-simulated linguistic interpretation data), CHL information actively input by the rider to the first input device, or CHL information input by the rider to the first input device independently of the CHL information visually or audibly output by the output device. Examples of such first input devices include a microphone, a touch panel, a combination of a microphone module with an ECU or a CPU, and the like. Examples of devices that may include such first input devices include smartphones, smartwatches, smart glasses, and intercoms (headsets). The first input device may be configured to receive input data for character simulating settings and supply the data to at least one processor. The first input device may be provided in, for example, a device that includes a first input device that acquires or generates at least one type of data related to the saddle-type vehicle or its rider, or in a device that generates data related to the CHL information input by the rider. The data input by the first input device is performed using, for example, CHL information. The CHL information may be, for example, voice information or text information. Examples of such a first input device include a microphone, a touch panel, and a combination of a microphone module with an ECU or a CPU. Examples of devices equipped with such a first input device include a smartphone, a smart watch, smart glasses, an intercom (headset), and a personal digital assistant (PDA).

[0020] Examples of the first input device and the saddle-riding type vehicle-related data acquired or generated by the first input device are not particularly limited, but include the following: GPS receiver: traveling position information GNSS receiver: traveling position information IMU (6-axis sensor): acceleration in three axes (front / rear, left / right, and up / down) of the saddle-riding type vehicle while traveling, and angular velocity in three axes (pitch, roll, and yaw) Throttle opening sensor: throttle opening Brake position sensor: brake operation ON / OFF or operation amount (operation pressure) Clutch sensor: clutch operation ON / OFF or operation amount Gear position sensor: gear position Steering angle sensor: steering angle Steering torque sensor: steering torque Vehicle speed sensor: vehicle speed Wheel speed sensor: rotation speed of front or rear wheels Engine rotation speed sensor: engine rotation speed

[0021] Examples of the first input device and the lidar biometric data (i.e., lidar biometric parameters) acquired or generated by the first input device include, but are not limited to, the following: The lidar biometric data can be acquired over time while the saddle-riding vehicle is traveling. The lidar biometric data is used to estimate the rider's emotions while the saddle-riding vehicle is traveling, and prompt data for character simulating is generated based on the results. The following are examples of the first input device and the lidar biometric data, but are not limited to these: Heart rate sensor: heart rate Brain wave sensor: brain wave Sweat rate sensor: sweat rate Respiration rate sensor: breathing pattern (rhythm / frequency) Body temperature sensor: body temperature Blood pressure sensor: blood pressure Facial expression camera: recognition of the rider's facial expressions Eye camera: eye movement tracking Oxygen saturation sensor: blood oxygen level Grip pressure sensor: grip pressure Microphone: voice (tone, pitch, speed, volume)

[0022] The at least one second input device is provided, for example, on a device owned by an entity that provides services related to saddle-riding vehicles. The device is, for example, a device different from the device on which the first input device is provided. The device may be, for example, a tablet, a laptop PC, a desktop PC, etc. Examples of services provided related to saddle-riding vehicles include manufacturing saddle-riding vehicles, selling saddle-riding vehicles, and maintaining saddle-riding vehicles. The entity may be, for example, a manufacturer of saddle-riding vehicles. The phrase "the second input device is provided on the device" includes cases where the second input device is provided integrally with the device main body and cases where the second input device is provided separably from the device main body. The second input device is configured, for example, to receive input of data for setting character simulating. Data input via the second input device is performed, for example, using CHL information. The CHL information may be, for example, audio information or text information. Examples of the second input device include a microphone, a touch panel, a keyboard, etc. The second input device may function as an independent device and have a communication function so as to output input data (data for setting up character simulating) independently. The second input device that functions independently is not particularly limited and may be, for example, a tablet. The second input device may be configured by combining an input module and a control device. In this case, an example of the input module is a keyboard. An example of the control device is a CPU provided in a PC. In this case, the CPU itself is not the second input device, but in combination with the input module, it functions as the second input device and outputs input data (data for setting up character simulating). In this way, the second input device realizes the function of outputting input data (data for setting up character simulating) either as an independent device or in combination with a control device. In the following, unless otherwise specified, the term "second input device" is used to encompass both a method of communicating with the outside world independently and a method of communicating with the outside world via a control device.

[0023] The memory includes, but is not limited to, RAM, ROM, non-volatile RAM, PROM, EPROM, EEPROM, flash memory, magnetic data storage, optical data storage, registers, or a combination thereof. There may be one or more memories.

[0024] Processors include central processing units (CPUs), microprocessors, general-purpose processors, digital signal processors (DSPs), graphics processing units (GPUs), controllers, microcontrollers, programmable logic devices (PLDs), field programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), etc. Multiple processors can be configured using any combination of these. Execution of a program by at least one processor is not limited to execution of the entire program by a single processor, but may also include execution of the program by parallel processing in a multiprocessor constructed by multiple processors. In a multiprocessor, either symmetric or asymmetric multiprocessing may be performed. A multiprocessor may be tightly coupled or loosely coupled. A processor may be a multi-core processor.

[0025] A large-scale language model (LLM) refers to a language model with a large number of parameters. The large-scale language model is capable of performing natural language processing tasks. The large-scale language model may be a natural language generation model. The natural language generation model is based on the large-scale language model and is capable of creating a sentence consisting of new CHL information from input CHL information. Note that creating a sentence consisting of new CHL information from input CHL information is an example of a natural language processing task. The number of parameters in the large-scale language model may be, for example, 1 billion or more, 10 billion or more, or 100 billion or more. A language model refers to a model of communicative human language using word occurrence probabilities. In one embodiment, the large-scale language model is a language model capable of performing inference using techniques such as zero-shot learning (ZSL), one-shot learning (OSL), or few-shot learning (FSL) without fine-tuning. In one embodiment, the large-scale language model is configured to perform a task and provide output in response to an input prompt. The prompt includes CHL information. The large-scale language model is not particularly limited, and examples thereof include GPT-3, GPT-4, GShad, Switch Transformer, Gopher, HyperCLOVA, etc. The large-scale language model is not included in the saddle-riding type vehicle-related CSS, but can communicate with the saddle-riding type vehicle-related CSS.

[0026] Communicative human language (CHL) information is linguistic information that can be understood, recognized, and memorized by humans. CHL information is based on the linguistic system used by humans in everyday conversation. CHL information is transmitted visually or audibly as text information or audio information.

[0027] A saddle-type vehicle is a vehicle equipped with a saddle-type seat. A saddle-type vehicle is a vehicle configured so that a rider rides the vehicle while straddling a saddle. In the present invention, a saddle-type vehicle is equipped with handlebars and configured so as to be able to turn in a lean position. Saddle-type vehicles include motorcycles, three-wheeled motor vehicles each having a pair of left and right front or rear wheels, and four-wheeled motor vehicles each having a pair of left and right front and rear wheels. Motorcycles are not particularly limited, and examples include scooters, mopeds, off-road vehicles, and on-road vehicles. Saddle-type vehicles that can turn in a lean position have the property of making the rider feel a sense of unity and cooperation with the saddle-type vehicle, so the saddle-type vehicle-related CSS according to the present invention is suitable for saddle-type vehicles that can turn in a lean position.

[0028] Rider equipment or personal items refer to devices that are worn or carried by the rider while riding a saddle-type vehicle and are capable of communication. The equipment or personal items are moved along with the rider by the saddle-type vehicle while the saddle-type vehicle is traveling. The rider here refers to a person riding in the saddle-type vehicle. Therefore, the rider includes not only the person driving the saddle-type vehicle but also a passenger. An example of a passenger is a tandem rider. Equipment is not particularly limited, and examples include HMDs, smart glasses, intercoms (headsets), shoes, boots, gloves, helmets, clothing, earphones, and bone conduction earphones. Personal items are not particularly limited, and examples include smartphones, electronic keys, personal digital assistants (PDAs), and smart watches. It is not necessary to strictly distinguish between equipment and personal items; items that fall under either or both are considered "equipment or personal items."

[0029] A user terminal refers to a device that is not a rider's equipment or personal belongings and is used by a person (hereinafter also referred to as a user) who is not a rider. However, a person may be a rider when riding a saddle-type vehicle and a user when using the user terminal without riding a saddle-type vehicle. The user terminal may, for example, be a device used by a rider after riding the saddle-type vehicle. The user terminal may constitute a saddle-type vehicle-related CSS according to the present invention. The user is not particularly limited, and may be, for example, a rider after riding the saddle-type vehicle. The user terminal is not particularly limited, and may be, for example, a terminal owned by the rider (e.g., a tablet, laptop PC, or desktop PC). When the saddle-type vehicle-related CSS according to the present invention includes a user terminal, the rider can obtain character-simulated linguistic interpretation data via the user terminal, thereby understanding the rider's emotions during riding, the riding state of the saddle-type vehicle, and the CHL information output in response to these, i.e., character-simulated CHL information, after riding.

[0030] The server is not a rider's equipment or a carried item, nor is it a user terminal. The server is not intended to be operated by either the rider or the user. However, the server may be operated by a person for purposes other than processing related to the CSS related to the saddle-riding vehicle (e.g., maintenance).

[0031] The "at least one program" does not necessarily have to be stored in a single memory, but may be stored separately in different memories in devices that can communicate with each other. Execution of the "at least one program" performs data acquisition processing, prompt generation processing, linguistic interpretation processing, output processing, and character setting processing.

[0032] The data acquisition process is a process in which at least one processor acquires at least one type of data related to the saddle-riding vehicle or its rider from a first input device provided on the saddle-riding vehicle or on an accessory or carried by the rider, or a process in which at least one processor acquires CHL information input by the rider to the first input device as data from the first input device. The process in which at least one processor acquires at least one type of data related to the saddle-riding vehicle or its rider from a first input device provided on the saddle-riding vehicle or on an accessory or carried by the rider may be, for example, a process in which at least one processor acquires at least one type of data related to the saddle-riding vehicle or its rider from a first input device provided on the saddle-riding vehicle or on an accessory or carried by the rider over time while the saddle-riding vehicle is traveling. The first input device and the at least one type of data related to the saddle-riding vehicle or its rider are as described above. Acquisition over time refers to repeated acquisition of data over time. The specific manner of time-dependent acquisition is not particularly limited, and may be, for example, periodic or non-periodic acquisition. Multiple types of data may be acquired over time. In this case, the acquisition timing of each data may be the same or different. The data acquisition process may be performed based on an instruction input by a user, or may be performed without input from a user. The timing and trigger for performing the data acquisition process are not particularly limited.

[0033] The prompt generation process is a process in which at least one processor generates character simulating prompt data using at least one type of data related to the saddle-type vehicle or its rider and character simulating data. In addition to the at least one type of data related to the saddle-type vehicle or its rider and the character simulating data, other data may also be used. The other data may include, for example, data obtainable via a network or data stored in a memory. The network is not particularly limited and may be constructed using various wireless networks. The communication method and communication protocol are not particularly limited. Examples of networks include the Internet, an in-vehicle network (e.g., CAN), an OBD-II network, and a mobile network such as LTE / 5G. The other data may include, for example, data used as a template when generating a prompt, history data indicating past interactions, etc. When the at least one type of data related to the saddle-type vehicle or its rider is saddle-type vehicle-related data, the other data may include, for example, rider biometric data. When the at least one type of data related to a saddle-type vehicle or its rider is rider biometric data, for example, saddle-type vehicle-related data may be used as the other data. The character simulating prompt data can be linguistically interpreted by the LLM. The character simulating prompt data has a smaller data volume than the at least one type of data related to a saddle-type vehicle or its rider. This means that the data volume of the generated character simulating prompt data is smaller than the data volume of the at least one type of data related to a saddle-type vehicle or its rider used to generate the character simulating prompt data. Examples of character simulating prompt data include the following (i) to (vi).

[0034] (i) CHL information relating to the amount of change over time of a saddle-riding type vehicle-related parameter indicated by the saddle-riding type vehicle-related data and the method of evaluating that parameter. Because this character simulating prompt data is CHL information, it can be directly interpreted linguistically by the LLM. Furthermore, since it also includes data on the evaluation method, evaluation can be performed. Examples of the amount of change over time of the parameter are not particularly limited, and include, for example: - Amount of change over time of bank angle when turning - Amount of change over time of brake operation amount (operation pressure) when turning - Amount of change over time of running position when turning - Amount of change over time of vehicle speed

[0035] (ii) Visual data visually showing the amount of change over time in the saddle-riding-type vehicle-related parameters indicated by the saddle-riding-type vehicle-related data, and CHL information related to the evaluation method for the parameters. The visual data is, for example, data in the form of a graph showing the amount of change over time in the saddle-riding-type vehicle-related parameters. If the LLM is multimodal, the multimodal LLM can also interpret the visual data linguistically. Furthermore, since the evaluation method data is also included, evaluation can be performed. Specific examples are not particularly limited, and include, for example, the same examples as those in (i) above.

[0036] (iii) CHL information relating to a reading method for reading saddle-riding-type vehicle-related data as the amount of change over time of a saddle-riding-type vehicle-related parameter and a method for evaluating the parameter. The saddle-riding-type vehicle-related data is numerical data. Therefore, the LLM cannot directly interpret the saddle-riding-type vehicle-related data linguistically. However, since the character simulating prompt data also includes data on the reading method, the LLM can read the saddle-riding-type vehicle-related data based on the reading method. Furthermore, since the character simulating prompt data also includes data on the evaluation method, evaluation can be performed. Specific examples are not particularly limited, and include the same examples as in (i) above.

[0037] (iv) CHL information relating to the amount of change over time in the rider biometric parameters indicated by the rider biometric data and the method of evaluating those parameters. Because this character simulating prompt data is CHL information, it can be directly interpreted linguistically by the LLM. Furthermore, since it also includes data on the evaluation method, evaluation can be performed. Examples of the amount of change over time in the parameters are not particularly limited and include, for example: - Change in heart rate over time - Change in brain waves over time - Change in sweat rate over time - Change in respiratory rate over time - Change in body temperature over time - Change in blood pressure over time - Change in the rider's facial expression over time - Change in eye movement over time - Change in blood oxygen level over time - Change in grip pressure over time - Change in voice over time

[0038] (v) Visual data visually showing the amount of change over time in the LIDAR biometric parameter indicated by the LIDAR biometric data, and CHL information related to the evaluation method for that parameter. The visual data is, for example, data that graphically shows the amount of change over time in the LIDAR biometric parameter. If the LLM is multimodal, the multimodal LLM can also interpret the visual data linguistically. Furthermore, since the evaluation method data is also included, evaluation can be performed. Specific examples are not particularly limited, and include, for example, the same examples as those in (iv) above.

[0039] (vi) CHL information relating to a reading method for reading LIDAR biometric data as a time-dependent change in LIDAR biometric parameters and a method for evaluating the parameters. LIDAR biometric data is numerical data. Therefore, the LLM cannot directly interpret the LIDAR biometric data linguistically. However, since the character simulating prompt data also includes data on the reading method, the LLM can read the LIDAR biometric data based on the reading method. Furthermore, since the character simulating prompt data also includes data on the evaluation method, evaluation can be performed. Specific examples are not particularly limited, and include, for example, the same examples as those in (iv) above.

[0040] The character simulating prompt data is data for linguistically interpreting at least one type of data related to a saddle-type vehicle or its rider, and as shown in (i) to (vi) above, includes, for example, two elements: (I) how to read at least one type of data related to a saddle-type vehicle or its rider, and (II) how to evaluate the read data. Element (I) is, for example, how to obtain characteristics or trends of at least one type of data related to a saddle-type vehicle or its rider. Element (II) is how to communicate these characteristics or trends to the rider. When character simulating prompt data is generated using at least one type of data related to a saddle-type vehicle or its rider and character simulating data, elements (I) and (II) are included in the character simulating prompt data, for example. Furthermore, another element (III) may also be included. Element (III) may include, but is not limited to, specifying the tone of voice of the output (utterance), specifying the creativity or accuracy used when generating the output (utterance), specifying continuity or consistency with previous outputs (utterances), or a combination of at least two of these.

[0041] Character simulating data is used when generating the character simulating prompt data. The character simulating data is used to generate a prompt customized to represent a pseudo-character of the saddle-riding type vehicle. In other words, the character simulating prompt data is customized to represent the pseudo-character of the saddle-riding type vehicle. The pseudo-character of the saddle-riding type vehicle, for example, serves as the basis for acquiring character-simulated linguistic interpretation data and for displaying the linguistic interpretation results and outputting character-simulated CHL information. For example, the personality of the personified saddle-riding type vehicle corresponds to this. Displaying the linguistic interpretation results and outputting character-simulated CHL information means, for example, that the personified saddle-riding type vehicle makes a statement based on its personality about the state of the saddle-riding type vehicle while it is traveling or the rider's emotions estimated while the saddle-riding type vehicle is traveling. The pseudo-character of the saddle-riding type vehicle may be generated by, for example, the rider, or may be generated by the manufacturer of the saddle-riding type vehicle. Alternatively, the rider may customize a character (default character) previously generated by the manufacturer of the saddle-riding type vehicle. One or more characters may be generated. If multiple characters are generated, the rider may select one character from among these multiple characters. A new character may be generated separately while an existing character exists. Examples of default characters include kind, cool, and angry. Customizing a default character means, for example, strengthening or weakening the characteristics of the default character. There may be one or more default characters. If there are multiple default characters, the rider may select one character from among these multiple characters. A new default character may be added in addition to existing characters. If there are multiple characters, the rider can select a character depending on his or her mood.The pseudo-character of the saddle-riding vehicle does not change, for example, as the rider gains more experience driving the saddle-riding vehicle. The pseudo-character of the saddle-riding vehicle does not change, for example, as the rider drives the saddle-riding vehicle. The character simulating data may be, for example, data that serves as a template when generating a prompt, at least a portion of the data that serves as the template, or data used to customize at least a portion of the data that serves as the template to represent the pseudo-character of the saddle-riding vehicle. The character simulating data may be, for example, data related to the reading of at least one type of data related to the saddle-riding vehicle or its rider, and / or data related to the evaluation of the read data. An example of the character simulating data related to the reading of data is, for example, a data reading method. An example of the data reading method is, for example, a reading method for reading data as the amount of change in a parameter over time. An example of the character simulating data related to the evaluation of the read data is, for example, an evaluation criterion for the read data. The evaluation may include, for example, advice or impressions based on the evaluation. For example, the method of reading data and the evaluation criteria of the read data may be set differently depending on the pseudo-character of the saddle riding type vehicle. As is clear from the above description, at least a portion of the character simulating prompt data may include at least a portion of the character simulating data.

[0042] The linguistic interpretation process is a process in which at least one processor supplies character-simulating prompt data to the LLM and acquires character-simulated linguistic interpretation data from the LLM. The character-simulated linguistic interpretation data is data generated by linguistic interpretation by the LLM. The character-simulated linguistic interpretation data may be, for example, linguistic interpretation data about the state of the saddle-ride type vehicle while it is traveling, or linguistic interpretation data about the rider's emotions estimated while the saddle-ride type vehicle is traveling.

[0043] The output process is a process of outputting character-simulated CHL information indicating a linguistic interpretation result from at least one output device using character-simulated linguistic interpretation data acquired from the LLM. The output process is performed, for example, while the saddle-riding type vehicle is traveling. The output process may be performed, for example, before or after the saddle-riding type vehicle is traveling. The output process may be performed such that the character-simulated linguistic interpretation data acquired from the LLM is output directly from the output device. The character-simulated linguistic interpretation data acquired from the LLM may be modified, and the output process may be performed using the modified character-simulated linguistic interpretation data. This output is performed visually and / or audibly. The character-simulated CHL information indicating a linguistic interpretation result is, for example, CHL information indicating a linguistic interpretation result in which a pseudo-character of the saddle-riding type vehicle is reflected. The character-simulated CHL information indicating a linguistic interpretation result is, for example, CHL information indicating a linguistic interpretation result in which a pseudo-character of the saddle-riding type vehicle is reflected regarding the traveling state of the saddle-riding type vehicle and / or the rider's emotions. When outputting the CHL information that indicates the linguistic interpretation result and that has undergone character simulation, an avatar associated with the pseudo-character of the saddle-riding type vehicle may also be output. The avatar may be generated by the rider, the manufacturer of the saddle-riding type vehicle, or the rider may customize an avatar (default avatar) that has been generated in advance by the manufacturer of the saddle-riding type vehicle.

[0044] The character setting process receives input of data for setting character simulating from at least one first input device or at least one second input device different from the at least one first input device, and updates the character simulating data based on the input data. Examples of cases in which data for setting character simulating is input from the first input device include when a rider inputs data. Examples of cases in which data for setting character simulating is input from the second input device include when a manufacturer of a saddle-riding type vehicle inputs data based on a request from a rider, or when a manufacturer of a saddle-riding type vehicle adds a new character. The character simulating data is as described above. The character setting process is not particularly limited. The data for setting character simulating includes, for example, data used to update the character simulating data. The data is used, for example, to change at least a portion of the character simulating data. The data for setting character simulating is, for example, data related to various parameters that contribute to the formation of a pseudo-character of the saddle-riding type vehicle. The parameters may be quantified, for example. Updating the character simulating data may involve, for example, changing at least a portion of the data that serves as a template when generating a prompt. If character simulating data is data used to customize at least a portion of the template data to represent a pseudo-character of a saddle-riding vehicle, updating the character simulating data may involve changing at least a portion of the character simulating data. Updating the character simulating data may involve, for example, changing at least a portion of the method for reading at least one type of data related to the saddle-riding vehicle or its rider, and / or changing at least a portion of the evaluation criteria for the read data.The character simulating data is updated, for example, when the pseudo-character of the saddle-riding type vehicle is changed. Changing the pseudo-character of the saddle-riding type vehicle may involve, for example, changing at least some of the parameters that contribute to the formation of the character, or selecting a character different from the current character from among a plurality of types of characters. Receiving input of data for setting the character simulating includes, for example, adding a new pseudo-character of the saddle-riding type vehicle.

[0045] The present invention can further employ the following configuration.

[0046] (2) The CSS related to a saddle-riding type vehicle of (1), wherein the at least one program is further programmed to cause the at least one processor to execute the following in the output process: visually or audibly output CHL information corresponding to the character-simulated linguistic interpretation data by the at least one output device, and output visual information consisting of an image and / or video so as to overlap at least partially in time with the CHL information.

[0047] According to the system of (2), CHL information is output visually or audibly. CHL information and visual information are output so as to overlap in time. By using visual information in combination, the efficiency of information transmission to the rider can be improved. It is possible to increase the information transmitted to the rider and improve the impression given to the rider while suppressing the increase in output information. It is possible to achieve a higher level of interaction while suppressing the increase in load on hardware resources. The system of (2) can more effectively solve the above-mentioned unique problems.

[0048] The CHL information corresponding to the character-simulated linguistic interpretation data is, for example, CHL information that indicates the linguistic interpretation result and is character-simulated. The CHL information that indicates the linguistic interpretation result and is character-simulated is as described above.

[0049] The visual information may be stored in at least one memory in advance. The visual information may be received from outside the saddle-type vehicle-related CSS via a communication line such as the Internet. The visual information may be generated within the saddle-type vehicle-related CSS. The visual information may be generated by at least one processor. The visual information may be generated by the LLM. Images are static visual information. Video is dynamic visual information. Images may consist of or include visualizations, or may include non-visualizations such as photo images. Videos may be animations or simulations, or may be live-action captures.

[0050] (3) The CSS related to a straddle-type vehicle according to (2), wherein the at least one program is further programmed to cause the at least one processor to execute a visual information generation process that generates the visual information using the data acquired by the data acquisition process.

[0051] According to the system of (3), both the CHL information and the visual information are generated based on at least one type of data related to the saddle-type vehicle or its rider, and are output so as to overlap in time with each other. By increasing the correlation between the visual information and the CHL information, the efficiency of information transmission to the rider can be further improved. It is possible to increase the information transmitted to the rider and improve the impression given to the rider while suppressing an increase in the amount of output information. It is possible to achieve a higher level of interaction while suppressing an increase in the load on hardware resources. The system of (3) can more effectively solve the above-mentioned unique problems.

[0052] (4) The CSS related to a saddle-riding type vehicle according to (3), wherein the at least one program is further programmed to cause the at least one processor to execute the following in the visual information generation process: generating the visual information by the LLM using the data acquired by the data acquisition process.

[0053] According to the system of (4), both the CHL information and the visual information are generated by the LLM based on at least one type of data related to the saddle-type vehicle or its rider, and are output so as to overlap in time with each other. This makes it possible to improve the correlation between the visual information and the CHL information while reducing the load on hardware resources. The system of (4) can more effectively solve the above-mentioned unique problems.

[0054] (5) The CSS related to a saddle-riding type vehicle according to any one of (2) to (4), wherein in the output process, the CHL information output by the at least one output device includes a description of or related to the visual information output so as to overlap in time with the CHL information.

[0055] According to the system of (5), the correlation between CHL information and visual information can be further enhanced. It is possible to have the rider recognize multiple types of highly relevant information in a timely manner. The efficiency of information transmission to the rider can be improved. It is possible to increase the information transmitted to the rider and improve the impression given to the rider while suppressing the increase in output information. It is possible to achieve a higher level of interaction while suppressing the increase in load on hardware resources. The system of (5) can more effectively solve the above-mentioned unique problems.

[0056] A description of or relating to visual information may be a description or explanation of the visual content contained in the visual information itself, or may be a description of how to view the visual content rather than the visual content contained in the visual information itself.

[0057] The present invention can further employ the following configuration: (6) The CSS related to a saddle-riding type vehicle according to any one of (1) to (5), including the at least one first input device, the at least one output device, and an IPG related to a saddle-riding type vehicle, capable of communicating with each of the at least one first input device, the at least one output device, and the LLM via a network, and having the at least one memory and the at least one processor.

[0058] The system (6) includes a saddle-type vehicle-related IPG, so customization by entities such as saddle-type vehicle manufacturers can be easily realized.

[0059] The present invention can further employ the following configurations: (7) A straddle-type vehicle-related IPG included in the straddle-type vehicle-related CSS of (6).

[0060] The saddle-type vehicle-related IPG (7) can be easily customized by entities such as saddle-type vehicle manufacturers.

[0061] According to the present invention, by effectively and efficiently enhancing the sense of cooperation between the saddle-type vehicle and the rider, it is possible to build a system that can improve the rider's well-being and reduce the load on the hardware resources that make up the system.

[0062] FIG. 1(a) is a system overview diagram illustrating a saddle-riding-vehicle-related CSS according to an embodiment of the present invention, and FIG. 1(b) is a flowchart illustrating processing performed by the system. FIGS. 2(a) to 2(p) are diagrams illustrating devices in which an input device (I), a processor (P), a memory (M), and an output device (O) are provided in the saddle-riding-vehicle-related CSS according to an embodiment of the present invention. FIGS. 3(a) to 3(p) are tables illustrating devices in which an input device, a processor, and an output device are provided in the saddle-riding-vehicle-related CSS according to the present invention. FIG. 4 is a flowchart illustrating processing performed by the saddle-riding-vehicle-related CSS according to a first modified embodiment of the present invention.

[0063] FIG. 1A is a system overview diagram for explaining a straddle-type vehicle-related CSS 11 according to an embodiment of the present invention.

[0064] The saddle-riding-type vehicle-related CSS 11 (hereinafter simply referred to as the system 11) includes at least one first input device 13, at least one output device 14, and a saddle-riding-type vehicle-related IPG 1. The system 11 further includes at least one second input device 15. The at least one first input device 13 is provided in at least one of the saddle-riding-type vehicle 16 and the rider's equipment 17 and / or portable equipment 17. The at least one processor 2 acquires at least one type of data related to the saddle-riding-type vehicle or its rider from the at least one first input device 13. Examples of the first input device 13 illustrated in the figure include a GPS module, a smartwatch, a grip sensor, and an ECU. The GPS module is configured to acquire location information of the saddle-riding-type vehicle 16. The smartwatch may be configured to acquire, for example, heart rate and sweat rate. The grip sensor is configured to acquire, for example, heart rate and grip pressure. Since riders typically wear gloves as protectors, obtaining heart rates using a grip sensor may require some ingenuity depending on the heart rate obtaining method, as described above. As described above, the ECU does not function as a first input device alone, but functions as a first input device in combination with a GPS module or a grip sensor. At least one processor 2 obtains at least one type of data related to the saddle-riding vehicle or its rider (saddle-riding vehicle-related data or rider biometric data) from the GPS module or grip sensor via the ECU. The second input device 15 is, for example, a desktop PC owned by the manufacturer of the saddle-riding vehicle 16. The desktop PC is configured to receive input data for setting character simulating, which will be described later. Examples of cases in which data for setting character simulating is input from the second input device 15 include when the manufacturer of the saddle-riding vehicle 16 inputs data based on a rider's request or when the manufacturer of the saddle-riding vehicle 16 adds a new character. Of course, the first input device 13 and the second input device 15 are not limited to these examples.

[0065] The saddle-ride type vehicle-related IPG 1 includes at least one processor 2, at least one memory 3, and at least one communication module 4. The memory 3 stores programs for executing (A) data acquisition processing, (B) prompt generation processing, (C) linguistic interpretation processing, (D) output processing, and (E) character setting processing. The at least one processor 2 executes the programs. The number of processors 2, memories 3, and communication modules 4 is not particularly limited, and each may be one or more.

[0066] The hardware configuration of the system 11 is not particularly limited. The output device 14 may also have the functions of the saddle-riding-type vehicle-related IPG 1. If the saddle-riding-type vehicle-related IPG 1 is separate from the output device 14, the saddle-riding-type vehicle-related IPG 1 may be configured by a single server 19 or multiple servers 19 connected to each other so that they can communicate with each other. In this case, the multiple servers 19 may be configured to provide cloud computing services. The communication module 4 enables communication between the processor 2 and each of the LLM (Large Scale Language Model) 6, the first input device 13, the output device 14, and the second input device 15.

[0067] Each of the multiple output devices 14 can communicate with the saddle-riding vehicle-related IPG 1 via the network 12. The number of output devices 14 is not particularly limited. At least one output device 14 is required. The output device 14 may be provided in the saddle-riding vehicle 16, or in the rider's equipment 17 or portable equipment 17. The output device 14 may also be provided in, for example, a user terminal 18. Examples of the output device 14 shown in the figure include a meter on the saddle-riding vehicle 16, a helmet HUD, and a smartphone. Of course, the output device 14 is not limited to these examples.

[0068] The network 12 enables communication between the first and second input devices 13, 15, the plurality of output devices 14, the saddle-type vehicle-related IPG 1, and the LLM 6. The network 12 is not particularly limited and can be constructed using various wireless networks. There are also no particular limitations on the communication method or communication protocol.

[0069] The LLM 6 is stored in one server or in multiple servers that are communicatively connected to each other. The LLM 6 can communicate with the system 11. This is the same as the LLM 6 being able to communicate with the saddle-ride type vehicle-related IPG 1 in this embodiment. The LLM 6 outputs to the system 11 in response to input from the system 11. Communication between the LLM 6 and the system 11 is performed using at least CHL information.

[0070] 1B is a flowchart illustrating the processing performed by the saddle-riding-type vehicle-related output system 11. In this embodiment, data related to the rider's heart rate (rider biometric data) generated by a smartwatch and a grip sensor is used as at least one type of data related to the saddle-riding-type vehicle or its rider. The processing shown in FIG. 1B can be implemented in any of the system configurations shown in FIGS. 2 and 3A to 3P.

[0071] [Data Acquisition Process (A)] At least one processor 2 acquires at least one type of data (rider biological data) over time from a first input device 13 provided on the saddle-riding vehicle 16 or on the rider's equipment 17 or portable item 17 while the saddle-riding vehicle 16 is traveling (step S11). Specifically, the at least one processor 2 acquires data related to the rider's heart rate over time from a smartwatch and a grip sensor.

[0072] [Prompt Generation Process (B)] At least one processor 2 generates character simulating prompt data using at least one type of data (rider biological data) acquired in step S11 and character simulating data (step S12). In this embodiment, the character simulating data is used to generate a customized prompt to represent a cool character. In this embodiment, the character simulating prompt data is data indicating the following CHL information. Note that the method for evaluating the heart rate includes, for example, giving advice to the rider based on the heart rate and expressing impressions about the heart rate to the rider. - Transition of the rider's heart rate over time, and - A method for evaluating the heart rate that changes over time.

[0073] [Linguistic Interpretation Process (C)] At least one processor 2 supplies the character simulating prompt data generated in step S12 to the LLM 6 (step S13).

[0074] The LLM 6 linguistically interprets the character simulating prompt data provided in step S13 (step S21). In this embodiment, the LLM 6 uses the provided character simulating prompt data to evaluate the rider's heart rate based on the evaluation method. For example, if an increase in the rider's fatigue level is detected based on the rider's heart rate, the LLM 6 generates character-simulated linguistic interpretation data (linguistic interpretation data about the rider's emotions estimated while the saddle-type vehicle is traveling) such as, "You seem tired. I recommend you take a break." As another example, if an increase in the rider's anxiety is detected based on the rider's heart rate, the LLM 6 may generate character-simulated linguistic interpretation data (linguistic interpretation data about the rider's emotions estimated while the saddle-type vehicle is traveling) such as, "You seem mentally unstable. Is something wrong?"

[0075] Next, the at least one processor 2 obtains the character-simulated linguistic interpretation data generated in step S21 from the LLM 6 (step S14).

[0076] [Output Process (D)] At least one processor 2 supplies the character-simulated linguistic interpretation data acquired from the LLM 6 in step S14 to the output device 14 (step S15).

[0077] The output device 14 outputs character-simulated CHL information that indicates the linguistic interpretation result of the rider's emotion estimated during riding based on the character-simulated linguistic interpretation data supplied from at least one processor 2 (step S31). In this embodiment, the CHL information, for example, "You seem tired. We recommend you take a break," is displayed on the meter of the saddle-ride type vehicle. The CHL information may be output as audio information from a headset serving as an output device, for example.

[0078] [Character Setting Process (E)] At least one processor 2 receives input of data for setting character simulating from at least one second input device 15 (step S41). At least one processor 2 acquires the data input in step S41 (step S42). At least one processor 2 updates the character simulating data based on the data acquired in step S42 (step S43). This makes it possible, for example, to change a cool character into a gentle character. For example, the CHL information to be output changes. The CHL information to be output can be adapted to the rider's preferences. This makes it easier for the rider to become attached to the saddle-ride type vehicle 16.

[0079] (Variation 1) A saddle-riding-type vehicle-related CSS according to Variation 1 of the embodiment of the present invention will be described with reference to FIG. 4 . In Variation 1, the memory 3 stores programs for executing (A) data acquisition processing, (B) prompt generation processing, (C) linguistic interpretation processing, (D1) output processing, (E) character setting processing, and (F) visual information generation processing. At least one processor 2 executes these programs. In Variation 1, the (A) data acquisition processing, (B) prompt generation processing, (C) linguistic interpretation processing, and (E) character setting processing are the same as those in the above embodiment. Therefore, their description will be omitted. The (D1) output processing and (F) visual information generation processing will be described below. In Variation 1, the at least one type of data acquired in step S11 includes data related to the rider's heart rate (rider biometric data) as well as data related to the position information of the saddle-riding-type vehicle 16 (saddle-riding-type vehicle-related data). The data related to the position information of the saddle-riding-type vehicle 16 is acquired, for example, by a GPS module.

[0080] [Visual Information Generation Process (F)] At least one processor 2 generates visual information using at least one type of data acquired in step S11. In Variation 1, at least one processor 2 generates visual information using the at least one type of data acquired in step S11 via the LLM 6 (step S22). More specifically, the process is as follows: At least one processor 2 supplies the at least one type of data acquired in step S11 to the LLM 6 (step S16). The LLM 6 generates visual information using the at least one type of data provided in step S16 (step S22). At least one processor 2 acquires the visual information generated in step S22 from the LLM 6 (step S17). Note that in the example shown in FIG. 4, the visual information generation process (F) is performed after the linguistic interpretation process (C), but the visual information generation process (F) may be performed before the linguistic interpretation process (C) or before the prompt generation process (B).

[0081] The visual information may be an image or a video. In the example shown in Fig. 4, the LLM 6 generates the visual information, but the visual information may be stored in advance in at least one memory 3, or may be received from outside the system 11 via a communication line such as the Internet. The visual information may be generated based on, for example, data relating to the position information of the saddle riding type vehicle 16. The visual information may be, for example, data indicating the positional relationship between the current position of the saddle riding type vehicle 16 and the nearest rest area, together with a map image.

[0082] [Output Process (D1)] At least one processor 2 supplies the character-simulated linguistic interpretation data acquired from the LLM 6 in step S14 and the visual information acquired from the LLM 6 in step S17 to the output device 14 (step S15A). At least one processor 2 outputs the visual information in step S31A so that the visual information and the character-simulated CHL information overlap at least partially in time. In the example shown in FIG. 4 , the output of the character-simulated CHL information and the visual information start at the same time. However, for example, the output of the character-simulated CHL information may start before the visual information, or the output of the character-simulated CHL information may start after the visual information. The same applies to the end of the output of the character-simulated CHL information and the visual information. In Variation 1, the character-simulated CHL information may include an explanation about or related to the visual information that is output so as to overlap in time with the CHL information. In Modification 1, for example, audio information such as "You seem tired. We recommend you take a rest" is output from a headset, which is an accessory of the rider, while a positional relationship between the current position of the saddle riding type vehicle 16 and the nearest rest area is displayed together with a map image on a meter provided on the saddle riding type vehicle 16. In other words, in Modification 1, the CHL information and visual information are output so as to overlap in time. Note that in Modification 1, if the rider accepts the suggestion to take a rest, audio information (CHL information) regarding the nearest rest area may be output from the headset while the positional relationship between the current position of the saddle riding type vehicle 16 and the nearest rest area is displayed together with a map image on the meter of the saddle riding type vehicle 16.

[0083] In this embodiment, a case has been described in which data related to the rider's heart rate is used to output a message corresponding to the rider's emotions from an output device. However, the present invention is not limited to the above embodiment. The present invention can be implemented in other embodiments, and various modifications can be added. For example, an interaction may occur between the rider and the saddle-riding vehicle 16 via a headset worn by the rider. The interaction may be initiated by the rider or the saddle-riding vehicle 16. The timing of starting the interaction is not particularly limited, and may be before the saddle-riding vehicle 16 starts moving, while the saddle-riding vehicle 16 is moving, or after the saddle-riding vehicle 16 has started moving. For example, the rider's driving technique may be evaluated using changes over time in the bank angle or riding position during a turn. For example, the output of a device provided in the saddle-riding vehicle may be controlled while character-simulated CHL information is output. For example, music corresponding to the rider's emotions may be output from an audio system while interacting with the rider. For example, data for setting the character simulating may be input from the first input device 14 instead of the second input device 15. For example, when the rider changes the pseudo character of the saddle-ride type vehicle, the rider inputs data for setting the character simulating from the first input device 14.

[0084] 1: Saddle-ride type vehicle-related IPG (saddle-ride type vehicle-related interactive prompt generator) 2: Processor 3: Memory 4: Communication module 6: LLM 11: Saddle-ride type vehicle-related CSS (system) 12: Network 13: Input device 14: First output device 15: Second input device

Claims

1. A CSS (character simulating system) related to a straddle-type vehicle, the CSS including: at least one memory; at least one processor capable of communicating with an LLM (large-scale language model), connected to the memory, and configured to execute at least one program stored in the memory; at least one first input device provided on the straddle-type vehicle or an accessory or carried by a rider of the straddle-type vehicle; and at least one output device provided on the straddle-type vehicle or an accessory or carried by a rider of the straddle-type vehicle, and configured to output CHL (communicative human language) information, the at least one program comprising: a data acquisition process for acquiring at least one type of data related to the straddle-type vehicle or its rider from the at least one input device, and / or acquiring CHL information input by the rider to the at least one first input device as data from the at least one first input device; a prompt generation process that generates character simulating prompt data that can be linguistically interpreted by the LLM and has a reduced amount of data, using the data acquired by the data acquisition process and character simulating data that is stored in the memory and is used to generate prompts customized to express a pseudo-character of the saddle riding type vehicle; a linguistic interpretation process that supplies the character simulating prompt data to the LLM and acquires character-simulated linguistic interpretation data that is generated through linguistic interpretation by the LLM; an output process that uses the character-simulated linguistic interpretation data to output character-simulated CHL information that indicates the linguistic interpretation result from the at least one output device; and a character setting process that receives input of data for setting the character simulating from the at least one first input device or at least one second input device different from the at least one first input device, and updates the character simulating data based on the input data.a CSS system for a straddle-type vehicle, the CSS system being programmed to cause the at least one processor to execute the following:

2. A CSS related to a saddle-riding type vehicle as set forth in claim 1, wherein said at least one program is further programmed to cause said at least one processor to execute the following in said output processing: visually or audibly output CHL information corresponding to said character-simulated linguistic interpretation data by said at least one output device, and output visual information consisting of an image and / or video so as to overlap at least partially in time with said CHL information.

3. A CSS related to a straddle-type vehicle as set forth in claim 2, wherein said at least one program is further programmed to cause said at least one processor to execute a visual information generation process that generates said visual information using said data acquired by said data acquisition process.

4. A CSS related to a straddle-type vehicle as set forth in claim 3, wherein said at least one program is further programmed to cause said at least one processor to execute the following in said visual information generation process: generate said visual information by said LLM using said data acquired by said data acquisition process.

5. A CSS related to a straddle-type vehicle as set forth in any one of claims 2 to 4, wherein, in the output process, the CHL information output by the at least one output device includes an explanation about or related to the visual information that is output so as to overlap in time with the CHL information.

6. A CSS related to a saddle-riding vehicle according to any one of claims 1 to 5, comprising: the at least one first input device; the at least one output device; and the CSS related to a saddle-riding vehicle (IPG) capable of communicating with the at least one first input device, the at least one output device and the LLM via a network, the IPG having the at least one memory and the at least one processor.

7. A straddle-type vehicle-related IPG included in the straddle-type vehicle-related CSS according to claim 6.

Citation Information

Patent Citations

  • Agent device

    JP2000020888A

  • Communication device for vehicle

    JP2001219795A