WO2020204111A1 - Procédé d'analyse de données de déplacement de véhicule à inclinaison, dispositif d'analyse de données de déplacement de véhicule à inclinaison, procédé de traitement d'informations utilisant des données d'analyse et dispositif de traitement d'informations utilisant des données d'analyse - Google Patents

Procédé d'analyse de données de déplacement de véhicule à inclinaison, dispositif d'analyse de données de déplacement de véhicule à inclinaison, procédé de traitement d'informations utilisant des données d'analyse et dispositif de traitement d'informations utilisant des données d'analyse Download PDF

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WO2020204111A1
WO2020204111A1 PCT/JP2020/015118 JP2020015118W WO2020204111A1 WO 2020204111 A1 WO2020204111 A1 WO 2020204111A1 JP 2020015118 W JP2020015118 W JP 2020015118W WO 2020204111 A1 WO2020204111 A1 WO 2020204111A1
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data
lean vehicle
analysis
lean
driving
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PCT/JP2020/015118
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English (en)
Japanese (ja)
Inventor
圭祐 森島
謙作 磯部
中尾　浩
佑輔 梅澤
裕章 木邨
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ヤマハ発動機株式会社
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Priority to JP2021512195A priority Critical patent/JP7210704B2/ja
Publication of WO2020204111A1 publication Critical patent/WO2020204111A1/fr

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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
    • B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
    • B60W40/08—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to drivers or passengers
    • B60W40/09—Driving style or behaviour

Definitions

  • the present invention relates to a lean vehicle driving data analysis method, a lean vehicle driving data analyzer, an information processing method using the analysis data, and an information processing device using the analysis data.
  • a device for determining the driving skill of a driver is known.
  • a device for determining a driver's driving skill for example, a configuration disclosed in Patent Document 1 is known.
  • Patent Document 1 discloses an evaluation device capable of evaluating the driving skill of a vehicle. This Patent Document 1 analyzes the riding skill of a driver (rider) using the driving data of a lean vehicle.
  • Lean vehicles are used in various scenes because of their high mobility and convenience. There is a need for a lean vehicle-specific analysis that takes into account various usage scenarios.
  • the amount of data processed by the information processing device becomes enormous, and the hardware load of the device becomes large. Will be higher. Therefore, the hardware resources required by the information processing apparatus increase, which imposes restrictions on the design of the hardware resources. Therefore, the degree of freedom in designing the hardware resources of the information processing device is reduced.
  • An object of the present invention is to provide a lean vehicle driving data analysis method capable of outputting analysis data peculiar to a lean vehicle based on the driving data of a lean vehicle while increasing the degree of freedom in designing hardware resources.
  • a lean vehicle is a vehicle that tilts to the right when turning right and tilts to the left when turning left.
  • Lean vehicles are smaller in size than non-lean vehicles. That is, the lean vehicle is smaller in the front-rear direction and / or the left-right direction of the vehicle body than the non-lean vehicle. Further, since the amount of steering rotation of the lean vehicle is smaller than 360 degrees, the amount of steering rotation of the lean vehicle is smaller than that of the non-lean vehicle. Further, a lean vehicle is a rider-active vehicle that can be actively operated by the driver, unlike a non-lean vehicle. Therefore, driving a lean vehicle is different from driving a non-lean vehicle. The driving data of a lean vehicle whose driving is different from that of a non-lean vehicle is significantly different from the driving data of a non-lean vehicle, that is, for example, a four-wheeled vehicle.
  • the present inventors examined the driving situation of the lean vehicle in more detail, they noticed that the lean vehicle had a much higher degree of freedom of driving by the driver's intention than the non-lean vehicle.
  • the driver when driving a lean vehicle, the driver is more likely to be exposed to external stress than when driving a non-lean vehicle. Moreover, the external stress exerted on the driver driving the lean vehicle is very diverse.
  • the driving data of the lean vehicle has more variations than the driving data of the non-lean vehicle due to the difference in the driver who operates the lean vehicle, the difference in the lean vehicle, the difference in the driving environment, and the like.
  • lean vehicles are lighter than non-lean vehicles. For this reason, lean vehicles are more manoeuvrable and convenient than non-lean vehicles. Lean vehicles are used for a variety of purposes and tend to be used more frequently. Therefore, the lean vehicle is used in various scenes.
  • the weight and the position of the center of gravity of the lean vehicle are at least one of the state where the passenger is placed on the rear seat and the state where the luggage is loaded on the luggage storage portion (hereinafter, simply, the state where at least one of the passenger and the luggage is placed). ) And the state where the passenger is not placed on the rear seat and the luggage is not loaded on the luggage storage portion (hereinafter, simply referred to as the state where neither the passenger nor the luggage is loaded). ,to differ greatly. Therefore, the behavior of the lean vehicle is also different.
  • the behavior of a lean vehicle such as cornering and braking is different between a state in which at least one of a passenger and luggage is carried and a state in which neither a passenger or luggage is carried.
  • lean vehicles have a higher ratio of passenger or luggage weight to vehicle weight than non-lean vehicles.
  • the present inventors have run data of the lean vehicle in the state where at least one of the passenger and the luggage is carried on the lean vehicle and the state where neither the passenger nor the luggage is carried on the lean vehicle. I noticed that was different.
  • the present inventors noticed the following points while analyzing the running data of a lean vehicle carrying at least one of a passenger and luggage.
  • the present inventors have the driving skill of the driver who drives the lean vehicle when the driver is alone. Not only skill), but also, for example, the skill and driving ability of the driver who drives a lean vehicle with at least one of the passenger and luggage, and at least one of the passenger and luggage. It was found that it is possible to output analysis data peculiar to lean vehicles, which was difficult to output until now, such as the tendency of the behavior of lean vehicles in a state of being in a state of being.
  • the driver or the like can send the lean vehicle in the state in which at least one of the passenger and the luggage is carried. It is possible to grasp not only the driving skill of a preferable driver but also the driving skill of the driver. That is, it is possible to provide more preferable analysis data to the driver who operates the lean vehicle for business use.
  • the driver of the lean vehicle and the passenger have different feelings about the input received from the lean vehicle. Therefore, when a lean vehicle is used as a business vehicle for carrying a customer, the driver who drives the lean vehicle is required to have a driving skill different from the driving skill when riding the lean vehicle alone.
  • the present inventors have noticed that by performing the above-mentioned analysis, it is possible to provide analysis data such as more preferable driving skill and driving skill to a driver who drives a lean vehicle for such a business use.
  • the running data of the lean vehicle with at least one of the passenger and the luggage carried is analyzed, the data to be processed can be limited. It was found that this can reduce the load on the hardware resources of the system and increase the degree of freedom in designing the hardware resources.
  • the present inventors examined in detail the relationship between the driving data of the lean vehicle and the evaluation data of the customer, and found that the evaluation data of the customer is related to the comfort felt by the customer with respect to the driving of the lean vehicle. Do you get it. From this, if data on the driving skill and / or driving skill required for driving the lean vehicle that the customer feels comfortable can be output, the driver refers to the data and drives the lean vehicle desired by the customer. Is thought to be possible.
  • the present inventors analyze the lean vehicle driving data by using the lean vehicle driving data in a state where at least one of the passenger and the luggage is carried so that the driver can drive comfortably. I came up with a method to do it.
  • the present inventors can acquire analysis data peculiar to a lean vehicle based on the running data of the lean vehicle with at least one of a passenger and luggage on it while increasing the degree of freedom in designing hardware resources. Created a driving data analysis method.
  • the lean vehicle running data analysis method acquires lean vehicle running reference data which is running reference data of a lean vehicle that leans to the right when turning right and leans to the left when turning left. Based on the lean vehicle driving standard data acquisition process, the lean vehicle driving data acquisition process for analysis that acquires the lean vehicle driving data for analysis, which is the driving data of the lean vehicle to be analyzed, and the lean vehicle driving standard data acquired above.
  • the lean vehicle travel reference data is more than the lean vehicle travel data of a lean vehicle in a state where no passenger is placed on the rear seat of the lean vehicle and no luggage is loaded on the luggage storage portion, and the passenger is on the rear seat.
  • the lean vehicle travel data for analysis includes lean vehicle travel data in a state where at least one of the passenger and the luggage is carried.
  • the lean vehicle travel data analysis method analyzes the analysis lean vehicle travel data of the analysis target lean vehicle.
  • the present embodiment uses a lean vehicle driving standard generated based on lean vehicle driving data including lean vehicle driving data with at least one of a passenger and luggage on it, and uses at least one of the passenger and luggage.
  • the present embodiment uses unevenly distributed data of the running state of the lean vehicle in which at least one of the passenger and the luggage is carried. Therefore, in this embodiment, the number of data to be processed can be limited. Thereby, in this embodiment, the load on the hardware resource of the device for analyzing the lean vehicle traveling data can be reduced, and the degree of freedom in designing the hardware resource can be increased.
  • the lean vehicle running data includes more lean vehicle running data in a state where at least one of the passenger and the luggage is carried than the lean vehicle running data in the state where neither the passenger nor the luggage is loaded.
  • Lean vehicle driving data including lean vehicle driving data with at least one of a passenger and luggage on board, is analyzed using the lean vehicle driving criteria generated based on the basis. As described above, in this embodiment, the analysis can be performed by the lean vehicle traveling data in a state where the weight and the position of the center of gravity of the lean vehicle are similar. In particular, the lean vehicle behaves differently when the weight and the position of the center of gravity of the lean vehicle are different.
  • the analysis data obtained is that the weight and center of gravity of the lean vehicle are in the same state, that is, the analysis data is on board.
  • the present embodiment can output not only the driving skill for driving the lean vehicle but also the analysis data of the driver's skill and the driving skill for driving the lean vehicle with at least one of the passenger and the luggage on it, for example. ..
  • the driver can grasp the driving skill and driving skill suitable for the lean vehicle in which at least one of the passenger and the luggage is carried.
  • the driver can obtain analytical data for driving in which the passenger in the rear seat feels comfortable.
  • he / she can obtain analysis data for driving while avoiding the influence of vibration or inclination of a lean vehicle on the loaded luggage as much as possible. it can.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle running data includes classification-related data for classifying at least one of the driver and the lean vehicle, and includes lean vehicle running data of a plurality of lean vehicles having different classifications, and is lean for analysis.
  • the vehicle travel data includes analysis classification-related data for classifying at least one of the analysis target person and the analysis target lean vehicle, and is generated in the analysis data acquisition step based on the reference generation lean vehicle travel data.
  • the lean vehicle driving data is configured to include classification-related data for classifying at least one of the driver and the vehicle, so that the device for analyzing the lean vehicle driving data is a lean vehicle driving standard. Based on the data, the lean vehicle traveling data for analysis can be analyzed, and the analysis data of at least one of the driver and the vehicle classified using the classification-related data can be obtained. In this way, by classifying at least one of the driver and the vehicle by the classification-related data, it is possible to process the data corresponding to at least one of the driver and the vehicle when acquiring the analysis data. .. This makes it possible to limit the amount of data processed by the device that analyzes the lean vehicle travel data.
  • analysis data corresponding to the classification can be obtained.
  • analysis data corresponding to the vehicle type analysis data corresponding to the driver's gender, age group, and the like can be easily obtained.
  • the load on the hardware resource of the device for analyzing the lean vehicle running data is further reduced to increase the design freedom of the hardware resource of the device, and the lean vehicle based on the running data of the lean vehicle. It is possible to provide a lean vehicle driving data analysis method capable of outputting specific analysis data.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle running data includes reference generation lean vehicle driving input data related to operation input to the lean vehicle, reference generation lean vehicle behavior data related to the behavior of the lean vehicle, and the position of the lean vehicle.
  • the lean vehicle driving data for analysis includes at least one of the lean vehicle position data for reference generation related to the above, and the lean vehicle driving data for analysis is the lean vehicle driving input data for analysis related to the operation input to the lean vehicle to be analyzed, the analysis. It includes at least one of the analysis lean vehicle behavior data related to the behavior of the target lean vehicle and the analysis lean vehicle position data related to the position of the analysis target lean vehicle.
  • the lean vehicle driving data used when analyzing the lean vehicle driving data for analysis more reflects the driving skill and driving skill of the driver's lean vehicle in the state where at least one of the passenger and the luggage is carried. Includes data to be used.
  • the lean vehicle driving input data is data related to the operation input by the driver, it more reflects the result of the driver's judgment.
  • the result of the driving input is strongly reflected in the lean vehicle behavior data and the lean vehicle position data.
  • the lean vehicle driving data more strongly reflects the change in driving with respect to the lean vehicle after the driver judges.
  • the analysis lean vehicle position data regarding the traveling position of the analysis target lean vehicle is reflected in the operation input of the analysis target person, for example, and is based on the analysis target lean vehicle behavior of the analysis target lean vehicle driven by the analysis target person. It is used to detect driving skills.
  • the lean vehicle driving data for analysis it is possible to analyze the lean vehicle driving data for analysis with higher accuracy based on the lean vehicle driving standard data. Further, by using the lean vehicle driving data for analysis that specifies the type of data, the type of data processed by the device that analyzes the lean vehicle driving data can be reduced, and the hardware load of the device can be further reduced. Can be done. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle traveling data includes reference generation lean vehicle traveling environment data related to the traveling environment in which the lean vehicle travels, and the analysis lean vehicle traveling data includes traveling in which the analysis target lean vehicle travels. Includes lean vehicle driving environment data for analysis related to the environment.
  • Lean vehicle driving environment data includes, for example, map data.
  • This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel.
  • the lean vehicle driving environment data can be used for analyzing the lean vehicle driving data together with the lean vehicle driving input data, the lean vehicle behavior data, and the lean vehicle position data.
  • the lean vehicle traveling data in which the data type is specified the type of data processed by the apparatus for analyzing the lean vehicle traveling data can be reduced, and the hardware load of the apparatus can be further reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle travel data further includes more travel data when the lean vehicle travels on a public road than data when the lean vehicle travels on a road other than a public road, and the analysis lean vehicle travel data ,
  • the travel data when the lean vehicle to be analyzed travels on a public road is included more than the travel data when the lean vehicle to be analyzed travels on a road other than a public road.
  • lean vehicle driving data including a large amount of data when driving on a public road, it becomes easier to analyze the driving skill and / or driving skill of the driver from the driving data of the lean vehicle.
  • lean vehicle driving data it is possible to acquire more accurate analysis data while ensuring the degree of freedom in designing the hardware resources of the information processing device.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle driving data includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle, but a plurality of them are left, and the analysis lean vehicle driving data includes. It includes data in a state where a plurality of judgment options of the analysis target person are limited by vehicles around the analysis target lean vehicle, but a plurality of them are left.
  • lean vehicle driving data By using lean vehicle driving data in a state where the driver's judgment options are limited but multiple are left, it becomes easier to analyze the driver's driving skill and / or motor skill from the driving data of the lean vehicle. .. By using such lean vehicle driving data, it is possible to acquire more accurate analysis data while ensuring the degree of freedom in designing the hardware resources of the information processing device.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the lean vehicle running reference data includes evaluation data related to riding by a passenger of the lean vehicle for reference generation or evaluation data related to transportation by a requester for carrying luggage, and lean vehicle running data for reference generation. Generated based on.
  • the lean vehicle driving reference data is added with evaluation data related to boarding by a passenger on the rear seat or evaluation data related to transportation by a requester for carrying luggage to be placed on the luggage storage section. Is generated. From this, the lean vehicle traveling standard data can reflect the evaluation related to boarding by the passenger or the evaluation related to the transportation by the requester of the transportation of the luggage.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations. According to the lean vehicle running data of the lean vehicle in at least one of the state where the passenger is placed on the rear seat and the state where the luggage is loaded on the luggage loading portion, the passenger is not placed on the rear seat and the passenger is described. Acquires the non-loaded lean vehicle driving standard data generated based on the lean vehicle driving data for generating the non-loaded state standard, which includes a lot of lean vehicle driving data of the lean vehicle in the state where no luggage is loaded in the luggage storage part.
  • a lean vehicle for non-loading state analysis including the analysis lean vehicle running data of the analysis target lean vehicle in a state where no passenger is placed on the rear seat and no luggage is loaded on the luggage storage portion.
  • the lean vehicle running data is a lean vehicle running state based on driving with at least one of the passenger and the luggage loaded, and a lean vehicle running state related to the lean vehicle with neither the passenger nor the luggage loaded.
  • the lean vehicle in the state where neither the passenger nor the luggage is loaded can be analyzed based on.
  • the driver sees changes in driving skills, etc. by comparing the analysis data in the non-mounted state with the analysis data analyzed in the lean vehicle driving data in the state where at least one of the passenger and the luggage is loaded. be able to. Further, using the analysis data in the state where at least one of the passenger and the luggage is loaded and the analysis data in the non-loading state in which neither the passenger nor the luggage is loaded, the lean vehicle has a different weight and center of gravity position. It is also possible to obtain more accurate analysis data such as the characteristics of the driver when driving a vehicle.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the acquired analysis data is stored, and the output data of at least one of the analysis target person and the analysis target vehicle is generated by using the stored analysis data.
  • the output data is generated as information processing analysis data used for further information processing.
  • the analysis data obtained by the lean vehicle driving data analysis method using the analysis lean vehicle traveling data of the analysis target lean vehicle driven by the analysis target person can be used in a further information processing device.
  • the lean vehicle travel data analyzer is used when a plurality of drivers drive a reference generation lean vehicle that tilts to the right when turning right and tilts to the left when turning left.
  • the lean vehicle driving standard data acquisition unit that acquires lean vehicle driving standard data based on the standard generation lean vehicle driving data related to each obtained driving data, and the driver of the analysis target tilts to the right when turning right.
  • the analysis lean vehicle driving data acquisition unit for acquiring the analysis lean vehicle driving data related to the driving data obtained when driving the analysis target lean vehicle traveling to the left when turning left, and the above-mentioned acquired
  • An analysis data acquisition unit that acquires analysis data obtained by analyzing the acquired lean vehicle travel data for analysis based on the lean vehicle travel reference data, and an output analysis data for output using the acquired analysis data. It has an output analysis data generation unit to be generated and an analysis data output unit to output the generated analysis data for output.
  • the rear seat is more than the lean vehicle travel data of the lean vehicle in a state where no passenger is placed on the rear seat of the lean vehicle and no luggage is loaded on the luggage storage unit.
  • the lean vehicle generated based on the reference generation lean vehicle running data including a large amount of lean vehicle running data of the lean vehicle in at least one state of carrying a passenger and carrying luggage on the luggage loading portion.
  • Acquire driving standard data The analysis lean vehicle travel data acquisition unit includes the analysis lean vehicle travel data including lean vehicle travel data in at least one of a state in which a passenger is placed on the rear seat and a state in which luggage is loaded on the luggage storage unit. Get the data.
  • the analysis data acquisition unit acquires the analysis data of the analysis target person by analyzing the acquired lean vehicle travel data for analysis based on the acquired lean vehicle travel reference data.
  • the lean vehicle driving data analyzer analyzes the analysis lean vehicle driving data of the analysis target person who drives the lean vehicle for analysis.
  • the lean vehicle driving data analyzer of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle running data includes classification-related data for classifying at least one of the driver and the vehicle, and includes lean vehicle running data of a plurality of lean vehicles having different classifications.
  • the driving data includes analysis classification-related data for classifying at least one of the analysis target person and the analysis target lean vehicle.
  • the analysis data acquisition unit analyzes the analysis lean vehicle travel data based on the lean vehicle travel reference data generated based on the reference generation lean vehicle travel data, thereby performing the analysis classification-related data.
  • the analysis data of at least one of the analysis target person and the analysis target lean vehicle classified by using the above is acquired.
  • the lean vehicle driving data analyzer of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle running data includes reference generation lean vehicle driving input data related to operation input to the lean vehicle, reference generation lean vehicle behavior data related to the behavior of the lean vehicle, and the position of the lean vehicle.
  • the lean vehicle driving data for analysis includes at least one of the lean vehicle position data for reference generation related to the above, and the lean vehicle driving data for analysis is the lean vehicle driving input data for analysis related to the operation input to the lean vehicle to be analyzed, the analysis. It includes at least one of the analysis target lean vehicle behavior data related to the behavior of the target lean vehicle and the analysis target lean vehicle position data related to the position of the analysis target lean vehicle.
  • the lean vehicle driving data analyzer of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle running data includes reference generation lean vehicle running environment data related to the running environment in which the lean vehicle runs, and the analysis lean vehicle running data further runs the analysis target lean vehicle. Includes analytical lean vehicle driving environment data related to the driving environment.
  • the lean vehicle driving data analyzer of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle travel data includes more data when the lean vehicle travels on a public road than data when the lean vehicle travels on a road other than a public road
  • the analysis lean vehicle travel data includes the data when the lean vehicle travels on a public road. It includes more data when the lean vehicle to be analyzed travels on a public road than data when the lean vehicle to be analyzed travels on a road other than a public road.
  • the lean vehicle driving data analyzer of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle driving data includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle, but a plurality of them are left, and the analysis lean vehicle driving data includes. It includes data in a state where a plurality of judgment options of the analysis target person are limited by vehicles around the analysis target lean vehicle, but a plurality of them are left.
  • the lean vehicle driving data analyzer of the present invention preferably includes the following configurations.
  • the analysis data corresponding to at least one category of the analysis target person and the vehicle is generated as information processing analysis data used for further information processing.
  • the information processing method using the analysis data according to the embodiment of the present invention is an information processing method using the output data generated as the information processing analysis data by the above-mentioned lean vehicle traveling data analysis method.
  • the output data is acquired, the first data different from the output data is acquired, and the output data and the first data are used to obtain the output data and the second data different from the first data.
  • Data is generated and the second data is output.
  • the information processing method using the analysis data may be any information processing method as long as it is an information processing method using the analysis data obtained by analyzing the lean vehicle driving data.
  • the first and second data relate to markets, goods, services, environments or customers used in business such as lean vehicle sharing, lean vehicle rental, lean vehicle leasing, lean vehicle insurance, etc. It may be data.
  • the output data output using the analysis data of at least one of the analysis target person and the analysis target lean vehicle obtained and classified by analyzing the analysis lean vehicle running data, and the output output data described above.
  • the acquired output data and the second data different from the first data are generated and output. Therefore, it is possible to generate and output the second data with higher accuracy.
  • the information processing device using the analysis data is the information processing device using the output data generated as the information processing analysis data by the lean vehicle traveling data analysis device described above.
  • This information processing apparatus uses the output data acquisition unit for acquiring the output data, the first data acquisition unit for acquiring the first data different from the output data, the output data, and the first data. It includes a second data generation unit that generates output data and second data different from the first data, and a second data output unit that outputs the second data.
  • This specification describes an embodiment of a lean vehicle traveling data analysis method, a lean vehicle traveling data analyzer, an information processing method using analysis data, and an information processing apparatus using analysis data according to the present invention.
  • the lean vehicle is a vehicle that turns in an inclined posture.
  • a lean vehicle is a vehicle that tilts to the left when turning to the left and to the right when turning to the right in the left-right direction of the vehicle.
  • the lean vehicle may be a single-seater vehicle or a vehicle that can accommodate a plurality of people.
  • the lean vehicle includes not only a two-wheeled vehicle but also all vehicles that turn in an inclined posture, such as a three-wheeled vehicle or a four-wheeled vehicle.
  • the analysis data is data obtained by analyzing the driving of the driver.
  • it is data obtained by analyzing a driver's driving skill and / or driving skill according to a lean vehicle driving standard.
  • the evaluation data is evaluation data related to the evaluation regarding the boarding by the passenger or the evaluation regarding the transportation by the requester of the transportation of the luggage.
  • the evaluation data is, for example, an evaluation of the driver and / or the vehicle when the customer gets on the vehicle, and the comprehensive evaluation felt by the customer is given, for example, on a five-point scale.
  • the customer's evaluation of boarding is a subjective and qualitative evaluation of the customer when the customer boarded.
  • the evaluation data is, for example, an evaluation of the requested transportation by a customer who has requested the transportation of the package, and a comprehensive evaluation felt by the customer is given, for example, on a five-point scale. The highest evaluation is 5, and the smaller the number, the lower the evaluation.
  • the evaluation data may include the degree of reliability, comfort, economic efficiency including quickness (short time to reach the destination), and the like.
  • the evaluation axis in the evaluation data is not limited to one.
  • the evaluation axis in the evaluation data may have a plurality of items.
  • the vehicle traveling data is data related to the traveling of a lean vehicle.
  • the vehicle traveling data relates to lean vehicle driving input data related to driving input to the lean vehicle by the driver, lean vehicle behavior data related to the behavior of the lean vehicle, and a position where the lean vehicle is traveling. It includes lean vehicle position data, lean vehicle driving environment data related to the driving environment in which the lean vehicle travels, and the like.
  • the vehicle traveling data may include processed data obtained by processing lean vehicle driving input data, lean vehicle behavior data, lean vehicle position data, lean vehicle traveling environment data, and the like.
  • the vehicle traveling data may include processing data processed using other data such as lean vehicle driving input data, lean vehicle behavior data, lean vehicle position data, and lean vehicle traveling environment data.
  • the classification-related data includes data for classifying the individual driver, data for classifying the gender of the driver, data for classifying the age group of the driver, data for classifying the manufacturer of the vehicle, and classifying the vehicle type. Includes data, data that classifies vehicle performance (eg, drive source output, drive source type, suspension, etc.). This classification-related data is used to limit the range of use of lean vehicle driving standard data and analytical lean vehicle driving data in response to classifications such as driver attributes, manufacturers, and vehicle types when generating analysis data. Used.
  • the lean vehicle driving input data is data related to the driver's operation input performed when the driver drives the lean vehicle. Specifically, it may include data related to accelerator operation, brake operation, steering, or change in the position of the center of gravity due to a change in the driver's posture. Specifically, the lean vehicle driving input data may include operations of various switches such as a horn switch, a blinker switch, and a lighting switch. Since the lean vehicle driving input data is data related to the driving input by the driver, the result of the driver's judgment is more reflected. Lean vehicles tend to have many variations because there are many types of driving by the driver and the degree of freedom of the driver's choice during driving is high. Further, the lean vehicle driving input data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle driving input data may include data acquired from a sensor or the like and processing data processed using other data.
  • the lean vehicle behavior data is data related to the behavior of the lean vehicle generated by the operation input of the driver when the driver drives the lean vehicle.
  • the data related to the behavior of the lean vehicle includes, for example, the acceleration, speed, and angle of the lean vehicle that change when the driver who is the analysis target drives. That is, the data on the behavior of the lean vehicle shows the posture change including the steering of the lean vehicle and the change of the position of the center of gravity when the driver who is the analysis target operates the accelerator or the brake to accelerate or decelerate the lean vehicle X. It is the data showing the behavior of the lean vehicle that occurs when the above is performed.
  • the lean vehicle behavior data relating to the behavior of the lean vehicle includes not only the data relating to the acceleration, speed, and angle of the lean vehicle, but also the switch operation performed on the lean vehicle by the driver who is the analysis target. May include movements that occur in lean vehicles. That is, the data relating to the behavior of the lean vehicle includes data related to the operation generated in the lean vehicle by operating various switches such as a horn switch, a blinker switch, and a lighting switch.
  • the lean vehicle behavior data strongly reflects the result of the driver's driving input.
  • the lean vehicle behavior data may include processing data obtained by processing data acquired from a sensor or the like.
  • the lean vehicle behavior data may include data acquired from a sensor or the like and processing data processed using other data.
  • the traveling position data of the lean vehicle is the data related to the position of the lean vehicle. For example, it can be detected based on GPS or information of a communication base station of a communication mobile terminal.
  • the traveling position data of the lean vehicle can be calculated by various positioning techniques, SLAM, or the like.
  • the lean vehicle position data affects the driving of the driver and is reflected in the behavior of the vehicle. Therefore, the lean vehicle position data also tends to strongly reflect the driving skill and / or driving skill of the driver.
  • the lean vehicle position data may include processing data obtained by processing data acquired from a sensor or the like.
  • the lean vehicle position data may include data acquired from a sensor or the like and processing data processed using other data.
  • the lean vehicle driving environment data includes, for example, map data.
  • the map data may be associated with information on road conditions, signals, information on road traffic environment such as equipment, regulatory information on road travel, and the like. It may also be associated with environmental data such as weather, temperature or humidity.
  • the driving environment in which a lean vehicle travels is considered to be an example of external stress that the driver receives.
  • Lean vehicle driving environment data influences the driver's judgment and influences the driver's driving. Therefore, the driver's driving skill and / or driving skill is likely to appear in the lean vehicle driving environment data.
  • Lean vehicle driving environment data can be obtained from various means. It is not limited to a certain means. For example, it is an external environment recognition device mounted on a lean vehicle. More specifically, there are cameras, drivers, radars, and the like. Also, for example, a communication device. More specifically, it is an inter-vehicle communication device and a road-to-vehicle communication device. For example, it can be obtained via the Internet.
  • the luggage storage portion means a portion for loading or holding luggage in a lean vehicle.
  • the luggage storage unit may have any structure as long as it can load or hold the luggage.
  • the luggage storage section includes at least one of a loading platform, a storage section which is a space provided under the seat, a side back, and a front car.
  • the luggage storage unit includes an area or member capable of loading or holding luggage legally permitted on a lean vehicle.
  • the reference generation lean vehicle running data including a large amount of lean vehicle running data of the lean vehicle in at least one state in which the luggage is loaded on the luggage loading portion is the reference generation lean vehicle running data in which the passenger is not placed on the rear seat and the luggage is placed.
  • the reference generation lean vehicle running data including a large amount of lean vehicle running data of the lean vehicle in at least one state in which the luggage is loaded on the luggage loading portion is the reference generation lean vehicle running data in which the passenger is not placed on the rear seat and the luggage is placed. It may include a part of lean vehicle running data of a lean vehicle in a state where no luggage is loaded in the unit.
  • the travel data when the lean vehicle travels on a non-public road is included. It does not have to be included at all.
  • the lean vehicle includes more travel data when the lean vehicle travels on a public road than when the lean vehicle travels on a non-public road, the travel data when the lean vehicle travels on a non-public road is included. It may be partially included.
  • the analysis target lean vehicle includes more travel data when the analysis target lean vehicle travels on a public road than the travel data when the analysis target lean vehicle travels on a non-public road
  • the analysis target lean vehicle travels on a non-public road. It is not necessary to include the driving data at the time of the operation.
  • the fact that the analysis target lean vehicle includes more travel data when the analysis target lean vehicle travels on a public road than the travel data when the analysis target lean vehicle travels on a non-public road means that the analysis target lean vehicle travels on a non-public road. It may include a part of driving data.
  • the lean vehicle travel reference data is more than the lean vehicle travel data of the lean vehicle in at least one of a state in which a passenger is placed on the rear seat and a state in which luggage is loaded on the luggage storage portion.
  • a large amount of lean vehicle travel data of a lean vehicle in a state where no passenger is placed on the rear seat and no luggage is loaded on the luggage storage portion means that the passenger is placed on the rear seat and the luggage is loaded. It is not necessary to include any lean vehicle running data of the lean vehicle in at least one state in which the luggage is loaded on the mounting portion.
  • the lean vehicle travel reference data is more than the lean vehicle travel data of the lean vehicle in at least one of a state in which a passenger is placed on the rear seat and a state in which luggage is loaded on the luggage storage portion, the rear seat of the lean vehicle.
  • a state in which a passenger is not carried on the rear seat and no luggage is loaded on the luggage storage portion A large amount of lean vehicle travel data of a lean vehicle means that a passenger is placed on the rear seat and the luggage storage portion It may include a part of lean vehicle travel data of a lean vehicle in at least one state with luggage loaded.
  • lean vehicle running data analysis method capable of outputting analysis data peculiar to the lean vehicle based on the running data of the lean vehicle while increasing the degree of freedom in designing hardware resources.
  • An analysis method can be provided.
  • FIG. 1 is a diagram showing a schematic configuration of a lean vehicle traveling data analyzer according to the first embodiment of the present invention.
  • FIG. 2 is a flowchart showing a lean vehicle traveling data analysis method according to the first embodiment of the present invention.
  • FIG. 3 is a diagram showing a schematic configuration of a lean vehicle traveling data analysis processing system according to a second embodiment of the present invention.
  • FIG. 4 is a flowchart showing an information processing method using the analysis data.
  • FIG. 1 shows a schematic configuration of a lean vehicle traveling data analyzer 1 according to an embodiment of the present invention.
  • the lean vehicle travel data analyzer 1 is a lean vehicle travel when the analysis target drives a lean vehicle X (lean vehicle to be analyzed) that tilts to the right when turning right and tilts to the left when turning left. Analyze the data and output the analysis result.
  • the lean vehicle running data in this embodiment is data related to the running of the lean vehicle.
  • the lean vehicle driving data is data related to the driving skill and driving skill of the driver among the data related to the driving of the lean vehicle obtained when the driver on the front seat FS drives the lean vehicle. It means the data used when obtaining the analysis data to be included.
  • the lean vehicle driving data is related to the lean vehicle driving input data related to the driving input to the lean vehicle by the driver, the lean vehicle behavior data related to the behavior of the lean vehicle, and the running position of the lean vehicle. It includes lean vehicle position data, lean vehicle driving environment data related to the driving environment in which the lean vehicle travels, and the like.
  • the lean vehicle traveling data may include data other than the lean vehicle driving input data, the lean vehicle behavior data, the lean vehicle position data, and the lean vehicle traveling environment data. Further, the lean vehicle traveling data may include only one or a plurality of data among the lean vehicle driving input data, the lean vehicle behavior data, the lean vehicle position data, and the lean vehicle traveling environment data.
  • the lean vehicle running data is the lean vehicle running data for analysis.
  • the lean vehicle driving input data is lean vehicle driving input data for analysis.
  • the lean vehicle behavior data is lean vehicle behavior data for analysis.
  • the lean vehicle position data is lean vehicle position data for analysis.
  • the lean vehicle running environment data is lean vehicle running environment data for analysis.
  • the lean vehicle driving data may include processed data obtained by processing lean vehicle driving input data, lean vehicle behavior data, lean vehicle position data, lean vehicle driving environment data, and the like.
  • the vehicle traveling data may include processing data processed by using lean vehicle driving input data, lean vehicle behavior data, lean vehicle position data, lean vehicle traveling environment data, and other data.
  • the lean vehicle driving input data is data related to the driver's operation input performed when the driver drives the lean vehicle.
  • the lean vehicle driving input data may include data related to accelerator operation, braking operation, steering, or change in the position of the center of gravity due to a change in the driver's posture.
  • the lean vehicle driving input data may include operations of various switches such as a horn switch, a blinker switch, and a lighting switch. Since the lean vehicle driving input data is data related to driving input by the driver, it more reflects the driving skill and / or driving skill of the driver.
  • the lean vehicle driving input data may include processing data obtained by processing data acquired from a sensor or the like.
  • the lean vehicle driving input data may include processing data processed using data acquired from a sensor or the like and other data.
  • the lean vehicle behavior data is data related to the behavior of the lean vehicle generated by the operation input of the driver when the lean vehicle is driven by the driver.
  • the lean vehicle behavior data includes, for example, the acceleration, speed, and angle of the lean vehicle that changes when the driver drives. That is, the lean vehicle behavior data is generated when the driver accelerates or decelerates the lean vehicle by operating the accelerator or the brake, or changes the posture including steering of the lean vehicle or changing the position of the center of gravity. This is data showing the behavior of a lean vehicle.
  • the lean vehicle behavior data may include not only data on the acceleration, speed, and angle of the lean vehicle, but also movements that occur in the lean vehicle due to a switch operation or the like performed by the driver on the lean vehicle. That is, the lean vehicle behavior data includes data related to the operation generated in the lean vehicle by operating various switches such as a horn switch, a blinker switch, and a lighting switch. The lean vehicle behavior data strongly reflects the driving skill and / or driving skill of the driver. Further, the lean vehicle behavior data may include processing data obtained by processing data acquired from a sensor or the like. The lean vehicle behavior data may include processing data processed using data acquired from a sensor or the like and other data.
  • the lean vehicle position data is data related to the running position of the lean vehicle.
  • the lean vehicle position data can be detected based on GPS or information of a communication base station of a communication mobile terminal.
  • the lean vehicle position data can be calculated by various positioning techniques, SLAM, or the like.
  • the lean vehicle position data strongly reflects the driving skill and / or driving skill of the driver.
  • the lean vehicle position data may include processed data obtained by processing data acquired from a sensor or the like.
  • the lean vehicle position data may include processing data processed using data acquired from a sensor or the like and other data.
  • the lean vehicle driving environment data includes, for example, map data.
  • This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel.
  • the map data may be associated with environmental data such as weather, temperature or humidity.
  • the lean vehicle driving environment data can be used for analysis of lean vehicle driving data together with the lean vehicle driving input data, the lean vehicle behavior data, and the lean vehicle position data.
  • the information on the road conditions includes information on roads (regions) in a congested environment such as frequent traffic jams and many vehicles parked on the street. By combining this information with the time zone, the accuracy of the information is further improved.
  • the information on the road condition includes information on a road that is easily flooded when there is a squall.
  • the lean vehicle driving environment data is considered to be an example of external stress received by the driver.
  • the lean vehicle driving environment data affects the driving of the driver. Therefore, by using the lean vehicle driving environment data, the driving skill and / or driving skill of the driver is more likely to appear in the driving data of the lean vehicle. Further, since the purpose and frequency of use of the lean vehicle are affected by using the lean vehicle running environment data, the running data of the lean vehicle is more likely to include data peculiar to the lean vehicle.
  • the lean vehicle driving data analysis device 1 includes a lean vehicle driving reference data acquisition unit 10, a lean vehicle driving data acquisition unit 20 for analysis, an analysis data acquisition unit 30, an output data generation unit 40, and a data output unit 50.
  • a data storage unit 60 is provided.
  • the lean vehicle traveling data analyzer 1 is, for example, a mobile terminal owned by the person to be analyzed.
  • the lean vehicle travel data analysis device 1 may be an arithmetic processing unit that acquires data via communication and performs arithmetic processing.
  • the lean vehicle driving standard data acquisition unit 10 acquires the lean vehicle driving standard data used when analyzing the lean vehicle driving data for analysis. This lean vehicle travel reference data is generated based on the reference generation lean vehicle travel data.
  • the reference generation lean vehicle travel data is the lean vehicle travel data of a lean vehicle in a state where no passenger is placed on the rear seat RS of the lean vehicle and no luggage is loaded on the luggage storage portion RC. Rather, it includes a large amount of lean vehicle travel data of a lean vehicle in at least one of a state in which a passenger is placed on the rear seat RS and a state in which luggage is loaded on the luggage loading portion RC.
  • the reference generation lean vehicle driving data may include classification-related data for classifying at least one of the driver on the front seat FS and the lean vehicle. Further, the reference generation lean vehicle travel data may include lean vehicle travel data of a plurality of lean vehicles having different categories.
  • the reference generation lean vehicle driving data is the reference lean vehicle driving input data related to the driving input to the lean vehicle by different drivers, and the reference generation related to the traveling position of the lean vehicle driven and driven by different drivers.
  • Lean vehicle position data for use, lean vehicle behavior data for generating standards related to the behavior of lean vehicles driven and driven by different drivers, and lean vehicle driving environment data for standards related to the driving environment in which lean vehicles run, etc. including.
  • the reference generation lean vehicle driving data is other than the reference generation lean vehicle driving input data, the reference generation lean vehicle behavior data, the reference generation lean vehicle position data, and the reference generation lean vehicle driving environment data. It may contain data.
  • the reference generation lean vehicle driving data includes the reference generation lean vehicle driving input data, the reference generation lean vehicle behavior data, the reference generation lean vehicle position data, and the reference generation lean vehicle driving environment data. , May contain only one or more data.
  • the lean vehicle running data described above is the reference generation lean vehicle running data.
  • the lean vehicle driving input data described above is lean vehicle driving input data for reference generation.
  • the lean vehicle behavior data described above is lean vehicle behavior data for reference generation.
  • the lean vehicle position data described above is lean vehicle position data for reference generation.
  • the lean vehicle driving environment data described above is lean vehicle driving environment data for reference generation.
  • the reference generation lean vehicle running data may include reference generation classification-related data.
  • the reference classification-related data is used to generate analysis data corresponding to classifications such as driver attributes (gender, age, etc.), manufacturer, and vehicle type when analyzing lean vehicle driving data for analysis. ..
  • classifications such as driver attributes (gender, age, etc.), manufacturer, and vehicle type when analyzing lean vehicle driving data for analysis. ..
  • the lean vehicle travel reference data is generated based on the reference generation lean vehicle travel data including the lean vehicle travel data of a plurality of lean vehicles.
  • the lean vehicle travel reference data is used when analyzing the analysis lean vehicle travel data.
  • the lean vehicle travel reference data may be generated based on the reference generation lean vehicle travel data including the lean vehicle travel data of a plurality of lean vehicles having different categories.
  • the lean vehicle travel reference data is used when analyzing the analysis lean vehicle travel data.
  • the lean vehicle driving standard data is used, for example, as a standard for classifying the lean vehicle driving skill and driving skill of the driver who is the analysis target.
  • the lean vehicle reference travel data is generated based on, for example, the reference generation lean vehicle travel data, and is stored in the data storage unit 60.
  • the lean vehicle running reference data may be data generated in advance, or may be data generated by the lean vehicle running reference data acquisition unit 10.
  • the analysis lean vehicle driving data acquisition unit 20 of the present embodiment acquires the analysis lean vehicle driving data including the driving data when the driver who is the analysis target on the front seat FS drives the lean vehicle X.
  • the analysis lean vehicle travel data acquisition unit 20 is at least one of a state in which the analysis target person has a passenger on the rear seat RS of the lean vehicle Y and a state in which the luggage is loaded on the luggage storage unit RC.
  • the data included in the lean vehicle running data of the lean vehicle X that is, the lean vehicle driving input data to be analyzed, the lean vehicle behavior data for analysis, the lean vehicle position data for analysis and the analysis Obtain lean vehicle driving environment data for use.
  • Lean vehicle running data in a state where no passenger is placed on the rear seat RS of the lean vehicle and no luggage is loaded on the luggage storage portion RC is also acquired, but in the present embodiment, the rear seat RS of the lean vehicle Y is used.
  • the analysis lean vehicle driving data acquisition unit 20 may acquire the analysis lean vehicle driving input data by, for example, acquiring the driving of the analysis target person with respect to the lean vehicle X as an operation signal. Specifically, the analysis lean vehicle driving data acquisition unit 20 changes the position of the center of gravity due to data related to the driver's operation input in the lean vehicle X, that is, accelerator operation, brake operation, steering, or change in the driver's posture. Data related to the above, data related to the operation of various switches such as a horn switch, a blinker switch, and a lighting switch may be acquired. These data are transmitted from the lean vehicle X.
  • the analysis lean vehicle driving data acquisition unit 20 obtains data including the acceleration, speed, and angle of the lean vehicle X that changes when the driver who is the analysis target drives the lean vehicle X, for example, the analysis lean vehicle behavior. It may be acquired as data.
  • the analysis lean vehicle travel data acquisition unit 20 acquires the analysis lean vehicle behavior data by, for example, a gyro sensor.
  • the lean vehicle behavior data for analysis is a posture change including steering of the lean vehicle X or a change in the position of the center of gravity when the driver who is the analysis target operates the accelerator or the brake to accelerate or decelerate the lean vehicle X. This is data showing the behavior of the lean vehicle X that occurs when the above is performed.
  • the analysis lean vehicle travel data acquisition unit 20 may acquire the analysis lean vehicle position data related to the travel position of the lean vehicle X based on, for example, GPS or the information of the communication base station of the communication mobile terminal. ..
  • the lean vehicle position data for analysis can be calculated by various positioning techniques, SLAM, or the like.
  • the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data from, for example, map data.
  • This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel.
  • the map data may be associated with environmental data such as weather, temperature or humidity.
  • the map data may include information in which road information and information on the road traffic environment (information incidental to the road such as a signal) are associated with rule information related to road travel.
  • the analysis lean vehicle driving data acquisition unit 20 may acquire the analysis lean vehicle driving environment data by, for example, an external environment recognition device mounted on the lean vehicle X. More specifically, the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data from a camera, radar, or the like. Further, the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data by, for example, a communication device. More specifically, the analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data by the vehicle-to-vehicle communication device and the road-to-vehicle communication device. The analysis lean vehicle traveling data acquisition unit 20 may acquire the analysis lean vehicle traveling environment data via the Internet, for example. As described above, the lean vehicle traveling environment data for analysis can be obtained from various means. The means for acquiring the analysis lean vehicle driving environment data is not limited to a certain means.
  • the analysis lean vehicle travel data acquisition unit 20 may also acquire information (for example, classification-related data) related to the analysis target person and the lean vehicle X, for example.
  • the lean vehicle travel data acquisition unit 20 for analysis may acquire the data from the data storage unit 60 in which the input data is stored, or acquire the data directly input to the lean vehicle travel data analyzer 1. You may.
  • the analysis lean vehicle travel data acquisition unit 20 may acquire information from the lean vehicle X.
  • the analysis lean vehicle travel data acquisition unit 20 may receive and acquire detection signals from a gyro sensor, GPS, a detection unit that detects operation signals of various switches, etc. provided in the lean vehicle X. ..
  • the analysis lean vehicle travel data acquisition unit 20 may acquire, for example, analysis classification-related data of the analysis target person and the lean vehicle X.
  • the analysis classification-related data is data for classifying at least one of the driver and the lean vehicle, which are the analysis target persons.
  • the classification-related data includes data for classifying the individual driver, data for classifying the gender of the driver, data for classifying the age group of the driver, data for classifying the manufacturer of the vehicle, data for classifying the vehicle type, and vehicle performance. Includes data that classifies (for example, drive source type and output, suspension performance, etc.).
  • the reference generation lean vehicle driving input data related to the operation input to the lean vehicle the lean vehicle behavior data related to the behavior of the lean vehicle
  • the lean vehicle position data related to the position of the lean vehicle is the lean vehicle travel data for analysis.
  • the analysis classification-related data When analyzing the analysis lean vehicle driving data and generating the analysis data, the analysis classification-related data includes the attributes (gender, age, etc.) of the analysis target person and the manufacturer from the lean vehicle driving reference data described later. And when limiting to the data corresponding to the classification such as vehicle type. By using this analysis classification-related data, it is possible to limit the data to be processed when analyzing the analysis lean vehicle driving data and generating the analysis data, and it is possible to reduce the load on the hardware resources.
  • the analysis data acquisition unit 30 analyzes the analysis lean vehicle travel data obtained by the analysis lean vehicle travel data acquisition unit 20 based on the lean vehicle reference travel data obtained by the lean vehicle travel reference data acquisition unit 10. Acquire the analysis data obtained by this.
  • This analysis data is analysis data of at least one of the analysis target person and the lean vehicle X.
  • the analysis data includes, for example, data related to the driving skill and driving skill of the classified lean vehicle to be analyzed.
  • the driving skill means a driving skill of a driver who drives a lean vehicle.
  • the driving skill means a skill related to the driver's driving when driving a lean vehicle.
  • the analysis data includes, for example, data related to the traveling of the classified lean vehicle X. This data is, for example, data related to the driving skill and driving skill of the analysis target person who is the driver.
  • the output data generation unit 40 generates output data for output from the analysis data. For example, the output data generation unit 40 generates output data using a plurality of analysis data stored in the data storage unit 60. As a result, it is possible to generate highly accurate output data.
  • the output data generation unit 40 may generate the analysis data as it is as output data.
  • the data output unit 50 outputs the output data generated by the output data generation unit 40 from the lean vehicle traveling data analyzer 1.
  • the weight of the lean vehicle differs greatly between the loaded state in which at least one of the passenger and the luggage is loaded and the non-loaded state in which neither the passenger or the luggage is loaded, and the behavior of the lean vehicle is large. Is also different. Then, by using the driving data of the lean vehicle with at least one of the passenger and the luggage carried, not only the driving skill of driving the lean vehicle but also, for example, the lean with at least one of the passenger and the luggage carried. It is possible to output analysis data peculiar to a lean vehicle, such as the driving skill of the driver who operates the vehicle and the tendency of the behavior of the lean vehicle with at least one of the passenger and the luggage on it.
  • the analysis data can output the analysis data of at least one of the driver and the vehicle classified using the classification-related data.
  • analysis data corresponding to the classification can be obtained. For example, analysis data corresponding to a vehicle type, driver's gender, and analysis data corresponding to an age group can be easily obtained.
  • FIG. 2 is a flow showing a lean vehicle driving data analysis method.
  • the lean vehicle driving standard data acquisition unit 10 acquires the lean vehicle driving standard data generated based on the standard generation lean vehicle driving data (step SA1).
  • the lean vehicle travel reference data is generated based on the reference generation lean vehicle travel data and is stored in advance in the data storage unit 60.
  • the reference generation lean vehicle running data is the lean vehicle running data of the lean vehicle with at least one of the passenger and the luggage loaded from the lean vehicle running data of the lean vehicle with neither the passenger nor the luggage loaded. Including many. Further, the reference generation lean vehicle driving data may include classification-related data for classifying at least one of the driver and the lean vehicle. Further, the reference generation lean vehicle travel data may include lean vehicle travel data of a plurality of lean vehicles having different categories.
  • the analysis lean vehicle driving data acquisition unit 20 acquires the analysis lean vehicle driving data which is the driving data of the lean vehicle X traveling by the driver who is the analysis target (step SA2).
  • the analysis lean vehicle running data includes the analysis lean vehicle running data in a state where at least one of a passenger riding on the rear seat RS and an object to be put on the luggage loading unit RC when traveling on the lean vehicle X is placed. Further, the analysis lean vehicle travel data may include analysis classification-related data for classifying at least one of the analysis target person and the lean vehicle X.
  • the analysis lean vehicle driving data includes analysis lean vehicle driving input data related to driving input to the lean vehicle by the analysis target person and analysis lean vehicle position data related to the traveling position of the traveling lean vehicle X. And the analysis lean vehicle behavior data related to the behavior of the traveling lean vehicle X, and the analysis lean vehicle traveling environment data related to the traveling environment of the traveling lean vehicle X.
  • the analysis lean vehicle travel data acquisition unit 20 includes, for example, an information acquisition unit that acquires information about the analysis target person and the lean vehicle X, and a detection sensor including a gyro sensor, GPS, and the like.
  • the analysis lean vehicle travel data acquisition unit 20 acquires, for example, the analysis lean vehicle position data and the analysis lean vehicle behavior data from the output of the detection sensor.
  • the analysis lean vehicle travel data acquisition unit 20 acquires, for example, analysis classification-related data from the data acquired by the information acquisition unit.
  • the analytical travel degree-of-freedom-related data is acquired using, for example, the analytical lean vehicle position data obtained from the output of the detection sensor.
  • the analysis data acquisition unit 30 acquires the analysis data of at least one of the analysis target person and the lean vehicle X by analyzing the analysis lean vehicle travel data based on the lean vehicle travel reference data (step SA3). ).
  • the classification-related data it is also possible to acquire the analysis data of at least one of the classified analysis target person and the lean vehicle X.
  • the analysis data includes, for example, data related to the driving skill and driving skill of a lean vehicle of a driver who is an analysis target traveling on a public road.
  • the output data generation unit 40 generates output data for output from the analysis data (step SA4). After that, the data output unit 50 outputs the output data (step SA5). End this flow (end).
  • the lean vehicle driving data of the lean vehicle in which at least one of the passenger and the luggage is carried is obtained rather than the lean vehicle driving data of the lean vehicle in which neither the passenger nor the luggage is carried.
  • analysis data peculiar to lean vehicles such as driving skills and driving skills for driving lean vehicles in consideration of various usage scenarios, which was difficult to output until now. it can.
  • the driving skill and driving skill with at least one of the passenger and luggage are analyzed in detail. be able to.
  • the lean vehicle running data of the lean vehicle with at least one of the passenger and the luggage carried is analyzed. Distinguish between the case of analyzing the driving data of a lean vehicle with at least one of the passenger and luggage on it and the state of carrying at least one of the passenger and luggage with neither passenger nor luggage on board. Comparing with the case of analyzing the traveling data of the lean vehicle, the amount of data is smaller only in the traveling data of the lean vehicle in the state of at least one of the passenger and the luggage. That is, unevenly distributed data of the running state of the lean vehicle in which at least one of the passenger and the luggage is carried is used. Therefore, in this embodiment, the number of data to be processed can be limited. As a result, the load on the hardware resource of the device that analyzes the lean vehicle driving data can be reduced, and the degree of freedom in designing the hardware resource can be increased.
  • the types of data processed by the lean vehicle traveling data analyzer 1 can be reduced, and the hardware load of the device can be reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be increased.
  • This embodiment is an example of a lean vehicle driving data analysis method for analyzing lean vehicle driving data.
  • the lean vehicle driving data analysis method of the present embodiment includes the following steps.
  • the lean vehicle running reference data generated based on the lean vehicle running data for reference generation is acquired.
  • This reference generation lean vehicle travel data is more lean vehicle travel of a lean vehicle with at least one of the passenger and luggage on it than lean vehicle travel data of a lean vehicle with neither passenger nor luggage on it.
  • the reference generation lean vehicle driving data may include classification-related data for classifying at least one of the driver and the lean vehicle, and may include lean vehicle driving data of a plurality of lean vehicles having different classifications. May be good.
  • the reference generation lean vehicle driving data means lean vehicle driving data by a plurality of drivers.
  • the reference generation lean vehicle running data may be acquired by various sensors provided in the lean vehicle.
  • the lean vehicle travel data for generating the reference may be acquired by various sensors provided on the lean vehicle so as to be easily detachable.
  • the lean vehicle travel data for reference generation may be acquired by various sensors temporarily provided in the lean vehicle for data collection.
  • the lean vehicle driving data for analysis related to the driving data of the lean vehicle X obtained when the analysis target person drives the lean vehicle X which is the analysis target lean vehicle is acquired.
  • the analysis lean vehicle running data means the lean vehicle running data of the lean vehicle X driven by the analysis target person.
  • the analysis target lean vehicle means a lean vehicle X driven by the analysis target person, which is a target for acquiring analysis lean vehicle travel data.
  • the analysis target person may be included in the plurality of drivers.
  • the person to be analyzed may not be included in the plurality of drivers.
  • the lean vehicle to be analyzed may be included in the lean vehicle that acquires the reference generation lean vehicle travel data.
  • the lean vehicle to be analyzed may not be included in the lean vehicle that acquires the reference generation lean vehicle travel data.
  • the analysis target lean vehicle data may be included in the reference generation lean vehicle travel data.
  • the lean vehicle travel data for analysis may not be included in the lean vehicle travel data for reference generation.
  • the analysis lean vehicle running data may be acquired by various sensors provided in the analysis target lean vehicle.
  • the analysis lean vehicle travel data may be acquired by various sensors provided so as to be easily detachable from the analysis target lean vehicle.
  • the analysis lean vehicle travel data may be acquired by various sensors temporarily provided in the analysis target lean vehicle for data collection.
  • the various sensors for collecting the lean vehicle running data for analysis may have lower detection accuracy than the various sensors for collecting the lean vehicle running data for reference generation.
  • the various sensors for collecting the lean vehicle running data for analysis may be the same as the various sensors for collecting the lean vehicle running data for reference generation.
  • the type of data included in the analysis lean vehicle travel data may be less than the type of data included in the reference generation lean vehicle travel data.
  • the type of data included in the analysis lean vehicle travel data may be the same as the type of data included in the reference generation lean vehicle travel data.
  • the lean vehicle travel data analyzer 1 analyzes the acquired lean vehicle travel data for analysis based on the acquired lean vehicle travel reference data, and thereby at least one of the analysis target person and the analysis target lean vehicle. Get analytical data.
  • the lean vehicle driving data analyzer 1 uses the analysis data to generate output data for output.
  • the lean vehicle driving data analyzer 1 outputs the output data.
  • This embodiment is an example of a lean vehicle driving data analysis method for analyzing lean vehicle driving data.
  • the lean vehicle driving data analysis method of the present embodiment includes the following steps.
  • the reference generation lean vehicle travel data is the reference generation lean vehicle driving input data related to the operation input to the lean vehicle, and the reference related to the behavior of the lean vehicle.
  • the lean vehicle behavior data for generation and the reference lean vehicle position data for generation related to the position of the lean vehicle are included, and the lean vehicle travel data for analysis is used as an operation input to the lean vehicle to be analyzed.
  • the reference generation lean vehicle driving data means lean vehicle driving data by a plurality of drivers.
  • the lean vehicle is a vehicle that tilts to the right when turning right and tilts to the left when turning left.
  • the reference generation lean vehicle travel data may be acquired by various sensors provided in the lean vehicle.
  • the lean vehicle travel data for generating the reference may be acquired by various sensors provided so as to be easily removable from the lean vehicle.
  • the lean vehicle travel data for reference generation may be acquired by various sensors temporarily provided in the lean vehicle for data collection.
  • the lean vehicle driving data for analysis related to the driving data of the lean vehicle X obtained when the analysis target person drives the lean vehicle X which is the analysis target lean vehicle is acquired.
  • the analysis lean vehicle running data means the lean vehicle running data of the lean vehicle X driven by the analysis target person.
  • the analysis target lean vehicle means a lean vehicle X driven by the analysis target person, which is a target for acquiring analysis lean vehicle travel data.
  • the analysis target person may be included in the plurality of drivers.
  • the person to be analyzed may not be included in the plurality of drivers.
  • the lean vehicle to be analyzed may be included in the lean vehicle that acquires the reference generation lean vehicle travel data.
  • the lean vehicle to be analyzed may not be included in the lean vehicle that acquires the reference generation lean vehicle travel data.
  • the analysis target lean vehicle data may be included in the reference generation lean vehicle travel data.
  • the lean vehicle travel data for analysis may not be included in the lean vehicle travel data for reference generation.
  • the analysis lean vehicle running data may be acquired by various sensors provided in the analysis target lean vehicle.
  • the analysis lean vehicle travel data may be acquired by various sensors provided so as to be easily detachable from the analysis target lean vehicle.
  • the analysis lean vehicle travel data may be acquired by various sensors temporarily provided in the analysis target lean vehicle for data collection.
  • the various sensors for collecting the lean vehicle running data for analysis may have lower detection accuracy than the various sensors for collecting the lean vehicle running data for reference generation.
  • the various sensors for collecting the lean vehicle running data for analysis may be the same as the various sensors for collecting the lean vehicle running data for reference generation.
  • the type of data included in the analysis lean vehicle travel data may be less than the type of data included in the reference generation lean vehicle travel data.
  • the type of data included in the analysis lean vehicle travel data may be the same as the type of data included in the reference generation lean vehicle travel data.
  • the lean vehicle driving data used when analyzing the lean vehicle driving data for analysis includes data that more reflects the driving skill and driving skill of the driver's lean vehicle.
  • the analysis lean vehicle position data regarding the traveling position of the analysis target lean vehicle is, for example, the position with another lean vehicle when the analysis target lean vehicle driven by the analysis target person is traveling with a predetermined degree of freedom. Used to identify relationships.
  • the analysis lean vehicle behavior data related to the behavior of the analysis target lean vehicle is, for example, driven by the analysis target person when the analysis target lean vehicle driven by the analysis target person is traveling with a predetermined degree of freedom. It is used to detect the driving skill and driving skill of the analysis target person from the analysis lean vehicle behavior of the analysis target lean vehicle.
  • the lean vehicle driving data for analysis for analysis with higher accuracy based on the lean vehicle driving standard data. Further, by using the analysis lean vehicle traveling data in which the data type is specified, the type of data processed by the apparatus for analyzing the lean vehicle traveling data can be reduced, and the hardware load of the apparatus can be further reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle running data includes reference generation lean vehicle running environment data related to the running environment in which the lean vehicle runs, and the analysis lean vehicle running data further runs the analysis target lean vehicle. Includes analytical lean vehicle driving environment data related to the driving environment.
  • Lean vehicle driving environment data includes, for example, map data.
  • This map data may be associated with, for example, information on road conditions, information on road traffic environments such as traffic lights and equipment, and regulatory information on road travel.
  • the lean vehicle driving environment data can be used for analyzing the lean vehicle driving data together with the lean vehicle behavior data and the lean vehicle position data.
  • the lean vehicle traveling data in which the data type is specified the type of data processed by the apparatus for analyzing the lean vehicle traveling data can be reduced, and the hardware load of the apparatus can be further reduced. Further, since the hardware resources required by the device can be reduced, the degree of freedom in designing the hardware resources of the device can be further increased.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle travel data further includes more travel data when the lean vehicle travels on a public road than data when the lean vehicle travels on a road other than a public road, and the analysis lean vehicle travel data ,
  • the travel data when the lean vehicle to be analyzed travels on a public road is included more than the travel data when the lean vehicle to be analyzed travels on a road other than a public road.
  • lean vehicle driving data including a large amount of data when driving on a public road, it becomes easier to analyze the driving skill and driving skill of the driver from the driving data of the lean vehicle.
  • lean vehicle driving data it is possible to acquire more accurate analysis data while ensuring the degree of freedom in designing the hardware resources of the information processing device.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle driving data includes data in a state where a plurality of judgment options of the driver are limited by vehicles around the lean vehicle, but a plurality of them are left, and the analysis lean vehicle driving data includes. It includes data in a state where a plurality of judgment options of the analysis target person are limited by vehicles around the analysis target lean vehicle, but a plurality of them are left.
  • lean vehicle driving data By using lean vehicle driving data in a state where the driver's judgment options are limited but multiple are left, it becomes easier to analyze the driver's driving skill and driving skill from the driving data of the lean vehicle. By using such lean vehicle driving data, it is possible to acquire more accurate analysis data while ensuring the degree of freedom in designing the hardware resources of the information processing device.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the lean vehicle running reference data includes evaluation data related to evaluation related to boarding by a passenger of the lean vehicle for reference generation or evaluation related to transportation by a requester of transportation of goods, and lean vehicle running data for reference generation. Is generated based on.
  • the lean vehicle driving reference data is generated by adding the evaluation data related to the evaluation related to boarding by the passenger or the evaluation related to the transportation by the requester of the transportation of the object.
  • the lean vehicle running standard data can reflect the evaluation related to the riding by the passenger or the evaluation related to the transportation by the requester of the transportation of the object.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations. According to the lean vehicle running data of the lean vehicle in at least one of the state where the passenger is placed on the rear seat and the state where the luggage is loaded on the luggage loading portion, the passenger is not placed on the rear seat and the passenger is described. Acquires the non-loaded lean vehicle driving standard data generated based on the lean vehicle driving data for generating the non-loaded state standard, which includes a lot of lean vehicle driving data of the lean vehicle in the state where no luggage is loaded in the luggage storage part.
  • a lean vehicle for non-loading state analysis including the analysis lean vehicle running data of the analysis target lean vehicle in a state where no passenger is placed on the rear seat and no luggage is loaded on the luggage storage portion.
  • the lean vehicle driving data includes the lean vehicle driving data based on driving with a passenger and at least one of the luggage loaded states, and the lean vehicle driving data without the passenger and loaded with luggage. Includes lean vehicle driving data based on state driving.
  • Lean vehicle running of a lean vehicle with no passengers and no luggage than the lean vehicle running data of a lean vehicle with passengers on board and at least one with luggage Based on the data containing a lot of data, the lean vehicle running reference data in the non-mounted state is acquired. Then, the lean vehicle running data of the lean vehicle in the state where the passenger is not carried and the luggage is not loaded is acquired as the lean vehicle running data in the non-mounted state.
  • the lean vehicle in the state where neither the passenger nor the luggage is loaded Can perform based analysis.
  • the driver can change the driving skill and the like. Can be seen. Further, using the analysis data of the state in which at least one of the passenger and the luggage is loaded and the analysis data of the non-loading state in which neither the passenger or the luggage is loaded, the weight and the position of the center of gravity of the lean vehicle are used. If the difference is different, more accurate analysis data such as the characteristics of the driver when driving a lean vehicle can be obtained.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the acquired analysis data is stored, and the output data of at least one of the analysis target person and the analysis target vehicle is generated by using the stored analysis data.
  • the memory includes not only the memory for storage but also the temporary memory of the result.
  • the analysis data stored in the storage and the analysis data stored in the temporary memory may be used for the plurality of analysis data. These may be used to update the analysis data stored in the storage. These may be used to generate new analytical data. Statistical processing may be performed using these.
  • the old analysis data and the new analysis data can be used to more accurately analyze the lean vehicle running data of the lean vehicle X driven by the analysis target person.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the output data is generated as information processing analysis data used for further information processing.
  • the analysis data obtained by the lean vehicle driving data analysis method using the analysis lean vehicle traveling data of the analysis target lean vehicle driven by the analysis target person can be used in a further information processing device.
  • the lean vehicle travel data analyzer 1 drives a reference generation lean vehicle in which a plurality of drivers tilt to the right when turning right and tilt to the left when turning left.
  • the lean vehicle driving standard data acquisition unit 10 that acquires lean vehicle driving standard data based on the standard generation lean vehicle driving data related to the driving data obtained at each time, and the driver of the analysis target turn right when turning right.
  • Lean vehicle travel data acquisition unit 20 for analysis that acquires lean vehicle travel data for analysis related to travel data obtained when driving a lean vehicle for analysis that tilts to the left when turning left.
  • An analysis data acquisition unit 30 that acquires analysis data obtained by analyzing the acquired lean vehicle travel data for analysis based on the acquired lean vehicle travel reference data, and an output for output using the acquired analysis data. It includes an output analysis data generation unit 40 that generates the analysis data for output, and a data output unit 50 that outputs the analysis data for the generated output.
  • the lean vehicle travel reference data acquisition unit 10 rides on the rear seat from the lean vehicle travel data of the lean vehicle in a state where no passenger is placed on the rear seat of the lean vehicle and no luggage is loaded on the luggage storage portion.
  • the lean generated based on the reference generation lean vehicle running data including a large amount of lean vehicle running data of the lean vehicle in at least one state of carrying a person and carrying luggage on the luggage loading portion. Acquire vehicle driving standard data.
  • the analysis lean vehicle travel data acquisition unit 20 acquires the analysis lean vehicle travel data including the lean vehicle travel data in a state where at least one of the passenger and the luggage is carried.
  • the analysis data acquisition unit 30 acquires the analysis data of the analysis target person by analyzing the acquired lean vehicle travel data for analysis based on the acquired lean vehicle travel reference data.
  • the lean vehicle driving data analyzer 1 analyzes the analysis lean vehicle driving data of the analysis target person who drives the lean vehicle for analysis.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle driving data includes classification-related data for classifying at least one of the driver and the lean vehicle, and includes lean vehicle running data of a plurality of lean vehicles having different classifications.
  • the lean vehicle travel data for analysis includes analysis classification-related data for classifying at least one of the analysis target person and the analysis target lean vehicle.
  • the analysis data acquisition unit 30 analyzes the analysis lean vehicle travel data based on the lean vehicle travel reference data generated based on the reference generation lean vehicle travel data, thereby relating to the analysis classification.
  • the analysis data of at least one of the analysis target person and the analysis target lean vehicle classified by using the data is acquired.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle running data includes reference generation lean vehicle driving input data related to operation input to the lean vehicle, reference generation lean vehicle behavior data related to the behavior of the lean vehicle, and the position of the lean vehicle.
  • the lean vehicle driving data for analysis includes at least one of the lean vehicle position data for reference generation related to the above, and the lean vehicle driving data for analysis is the lean vehicle driving input data for analysis related to the operation input to the lean vehicle to be analyzed, the analysis. It includes at least one of the analysis target lean vehicle behavior data related to the behavior of the target lean vehicle and the analysis target lean vehicle position data related to the position of the analysis target lean vehicle.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle traveling data includes reference generation lean vehicle traveling environment data related to the traveling environment in which the lean vehicle travels
  • the analysis lean vehicle traveling data includes traveling in which the analysis target lean vehicle travels.
  • lean vehicle driving environment data for analysis related to the environment includes the following configurations.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations.
  • the reference generation lean vehicle travel data includes data in a state where a plurality of driver's judgment options are limited by vehicles around the lean vehicle, but a plurality of data are left, and the analysis lean vehicle travel data includes the data. Includes data in which the analysis target's judgment options are limited by the vehicles around the analysis target lean vehicle, but a plurality of data are left.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations.
  • the analysis data corresponding to at least one category of the analysis target person and the vehicle is generated as information processing analysis data used for further information processing.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations.
  • the lean vehicle running reference data includes evaluation data related to evaluation related to boarding by a passenger of the lean vehicle for reference generation or evaluation related to transportation by a requester of transportation of goods, and lean vehicle running data for reference generation. Is generated based on.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations. According to the lean vehicle running data of the lean vehicle in at least one of the state where the passenger is placed on the rear seat and the state where the luggage is loaded on the luggage loading portion, the passenger is not placed on the rear seat and the passenger is described. Acquires the non-loaded lean vehicle driving standard data generated based on the lean vehicle driving data for generating the non-loaded state standard, which includes a lot of lean vehicle driving data of the lean vehicle in the state where no luggage is loaded in the luggage storage part.
  • a lean vehicle for non-loading state analysis including the analysis lean vehicle running data of the analysis target lean vehicle in a state where no passenger is placed on the rear seat and no luggage is loaded on the luggage storage portion.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations. At least one of the acquired analysis data and the non-mounted state analysis data is stored, and at least one of the stored plurality of analysis data and the non-mounted state analysis data is used to at least one of the analysis target person and the analysis target vehicle. Generate one output data.
  • the lean vehicle traveling data analyzer 1 of the present invention preferably includes the following configurations.
  • the output data is generated as information processing analysis data used for further information processing.
  • FIG. 3 shows an example of the lean vehicle driving data analysis system 100 including the lean vehicle traveling data analysis device 1 of the first embodiment.
  • the same components as those of the first embodiment are designated by the same reference numerals and the description thereof will be omitted, and only the configurations different from the first embodiment will be described.
  • the lean vehicle driving data analysis system 100 includes a lean vehicle driving data analysis device 1 and a lean vehicle driving standard data generation device 101 that generates lean vehicle driving reference data.
  • the lean vehicle travel reference data generation device 101 is, for example, an information processing arithmetic unit capable of communicating with the lean vehicle travel data analysis device 1 and having a processor.
  • the lean vehicle travel data analysis device 1 is an information processing arithmetic unit having a processor
  • the lean vehicle travel reference data generation device 101 may be the same information processing arithmetic unit as the lean vehicle travel data analysis device 1.
  • the lean vehicle driving standard data generation device 101 acquires the lean vehicle driving data and generates the lean vehicle driving standard data based on the standard generation lean vehicle driving data including these data.
  • the lean vehicle travel reference data generation device 101 has a data storage unit 111 and a lean vehicle travel reference data generation unit 112. Although not particularly shown, the lean vehicle travel reference data generation device 101 has an acquisition unit for acquiring lean vehicle travel data and classification-related data. Further, although not particularly shown, the lean vehicle travel reference data generation device 101 has an output unit that outputs the generated lean vehicle travel reference data.
  • the data storage unit 111 stores lean vehicle running data for reference generation, lean vehicle running reference data, evaluation data, and analysis data. Specifically, the data storage unit 111 stores lean vehicle travel data for reference generation, including lean vehicle travel data obtained when a plurality of drivers each drive the lean vehicle Y. Further, the data storage unit 111 stores the lean vehicle travel reference data generated by the lean vehicle travel reference data generation unit 112, which will be described later. The data storage unit 111 stores evaluation data of a plurality of customers for the boarding at that time. Further, the data storage unit 111 stores the analysis data analyzed by the lean vehicle traveling data analyzer 1 described later.
  • the lean vehicle running data includes, for example, lean vehicle driving input data of lean vehicle Y, lean vehicle behavior data of lean vehicle Y, lean vehicle position data of lean vehicle Y, lean vehicle running environment data of lean vehicle Y, and the like.
  • the lean vehicle travel reference data generation unit 112 generates lean vehicle travel reference data based on the reference generation lean vehicle travel data stored in the data storage unit 111.
  • the lean vehicle travel reference data generated by the lean vehicle travel reference data generation unit 112 is stored in the data storage unit 111.
  • the lean vehicle travel reference data stored in the data storage unit 111 analyzes the lean vehicle travel data (lean vehicle travel data for analysis) of the lean vehicle X (lean vehicle for analysis) by the lean vehicle travel data analyzer 1. Used when. Since the method of analyzing the lean vehicle running data in the lean vehicle running data analyzer 1 is the same as that of the first embodiment, detailed description thereof will be omitted.
  • the lean vehicle travel data analyzer 1 acquires the analysis data of at least one of the analysis target person and the lean vehicle X by analyzing the lean vehicle travel data of the lean vehicle X based on the lean vehicle travel reference data. , Output the output data generated from the analysis data. Since the configuration of the lean vehicle travel data analyzer 1 is the same as that of the first embodiment, detailed description of the lean vehicle travel data analyzer 1 will be omitted.
  • the output data output from the lean vehicle traveling data analyzer 1 may be input to, for example, the information processing device 102.
  • the output data is generated in the lean vehicle traveling data analysis device 1 as information processing data used for information processing in the information processing device 102.
  • the information processing device 102 provides data related to insurance, markets, goods, services, environment or customers used in business such as sharing of lean vehicles, rental of lean vehicles, leasing of lean vehicles, and vehicle insurance of lean vehicles. It may be an apparatus that performs the processing of.
  • the lean vehicle travel data analysis device 1 is an information processing calculation device
  • the information processing device 102 may be the same device as the lean vehicle travel data analysis device 1.
  • the information processing device 102 may be the same information processing calculation device as the lean vehicle travel reference data generation device 101.
  • the information processing device 102 includes, for example, an output data acquisition unit 121, a first data acquisition unit 122, a second data generation unit 123, a second data output unit 124, and a data storage unit 125.
  • the output data acquisition unit 121 acquires the output data output from the lean vehicle travel data analyzer 1.
  • the first data acquisition unit 122 acquires the first data different from the output data.
  • This first data is data to be processed by the information processing apparatus 102.
  • the second data is data related to insurance, markets, products, services, environment or customers used in business such as sharing of lean vehicles, rental of lean vehicles, leasing of lean vehicles, vehicle insurance of lean vehicles, etc. Is.
  • the first data is stored in the data storage unit 125.
  • the second data generation unit 123 uses the output data and the first data to generate second data different from the output data and the first data. Similar to the first data, this second data also includes insurance, markets, products, services, etc. used in business such as sharing of lean vehicles, rental of lean vehicles, leasing of lean vehicles, and vehicle insurance of lean vehicles. Data related to the environment or customers.
  • the second data output unit 124 outputs the second data generated by the second data generation unit 123.
  • FIG. 4 is a flowchart showing the operation of information processing by the information processing device 102.
  • the output data acquisition unit 121 of the information processing device 102 acquires the output data output from the lean vehicle travel data analysis device 1 (step SB1).
  • the first data acquisition unit 122 of the information processing device 102 acquires the first data stored in the data storage unit 125 (step SB2). This first data is different from the output data.
  • the second data generation unit 123 of the information processing apparatus 102 generates the second data by using the acquired output data and the acquired first data (step SB3). This second data is different from the output data and the first data.
  • the second data output unit 124 of the information processing device 102 outputs the generated second data (step SB4).
  • the output data output from the lean vehicle driving data analyzer 1 in this way can be used as an information processing device in fields such as lean vehicle sharing, lean vehicle rental, lean vehicle leasing, and lean vehicle vehicle insurance. It can be used when processing credit risk or credit score. That is, the analysis data obtained by analyzing the lean vehicle driving data is used for arithmetic processing of the information processing device in fields such as lean vehicle sharing, lean vehicle rental, lean vehicle leasing, and lean vehicle insurance. can do.
  • the information processing device acquires the output output data and the acquired output. Using the data, credit risk or credit score can be output by arithmetic processing.
  • information processing methods include a process of acquiring output data output from the lean vehicle driving data analyzer 1 and a process of acquiring output data. It may include a step of outputting credit risk data related to credit risk or credit score data related to credit score using the acquired output data.
  • the information processing device acquires output data output from the lean vehicle driving data analyzer 1.
  • a unit and a credit risk output unit that outputs credit risk data related to credit risk or a credit score output unit that outputs credit score data related to credit score may be included by using the acquired output data.
  • the analysis target person when the output credit risk is low or the credit score is high, for example, the analysis target person can easily rent a lean vehicle, or the analysis target person rents a lean vehicle.
  • the fee may be given preferential treatment, or the person to be analyzed may receive preferential treatment of insurance premiums.
  • the lean vehicle running data analysis method in each of the above-described embodiments is an example of the lean vehicle running data analysis method for analyzing the lean vehicle running data to be analyzed.
  • the lean vehicle driving data analysis method of the present invention preferably includes the following configurations.
  • the output data is generated as information processing data used for further information processing.
  • the further information processing is related to business insurance, markets, goods, services, environment or customers such as lean vehicle sharing, lean vehicle rental, lean vehicle leasing, lean vehicle vehicle insurance, etc. It may be the processing of the data to be processed.
  • the output data output by the lean vehicle driving data analysis method of the present invention is used in the information processing method using the following analysis data.
  • the output data is acquired.
  • first data different from the output data is acquired.
  • the output data and the acquired first data are used to generate second data different from the output data and the acquired first data.
  • the generated second data is output.
  • the information processing method may be any information processing method as long as it is an information processing method using analysis data obtained by analyzing lean vehicle driving data.
  • the first data and the second data are insurance, markets, goods, services, environments or environments used in business such as lean vehicle sharing, lean vehicle rental, lean vehicle leasing, lean vehicle vehicle insurance, etc. It may be data related to the customer.
  • the analysis data available in the information processing device 102 can be acquired by the lean vehicle driving data analysis device 1 and the lean vehicle driving data analysis method. Further, as described in the first embodiment, by analyzing the lean vehicle travel data and obtaining the analysis data, the types of data processed by the system can be reduced, and the load on the hardware of the lean vehicle travel data analyzer 1 can be reduced. Can be reduced.
  • the lean vehicle travel reference data is generated using the lean vehicle travel data, but the lean vehicle travel is performed using not only the lean vehicle travel data but also data other than the lean vehicle travel data. Reference data may be generated.
  • the lean vehicle travel data is acquired as the lean vehicle travel data for analysis
  • the analysis data is acquired by analyzing the lean vehicle travel data for analysis based on the lean vehicle travel reference data.
  • the analysis data may be acquired by acquiring data other than the lean vehicle travel data for analysis and analyzing the data and the lean vehicle travel data.
  • the output data may be used in combination with data other than the lean vehicle driving data.
  • each data described in each of the above embodiments may be combined with data other than the lean vehicle traveling data.
  • the present invention can be used for a lean vehicle driving data analysis method, a lean vehicle driving data analysis processing device, an information processing method using analysis data, and an information processing device using analysis data.
  • Lean vehicle driving data analyzer 10 Lean vehicle driving reference data acquisition unit 20: Lean vehicle driving data acquisition unit 30 for analysis: Analysis data acquisition unit 40: Output data generation unit 50: Data output unit 60, 111: Data storage Part 100: Lean vehicle driving data analysis system 101: Lean vehicle driving reference data generation device 102: Information processing device

Abstract

L'invention concerne un procédé d'analyse de données de déplacement de véhicule à inclinaison pour délivrer en sortie des données d'analyse sur un véhicule à inclinaison tout en augmentant un degré de liberté dans la conception de ressources matérielles. Le procédé d'analyse de données de déplacement de véhicule à inclinaison selon l'invention consiste à : acquérir des données de référence de déplacement de véhicule à inclinaison générées sur la base de données de déplacement de véhicule à inclinaison à des fins de génération de référence qui comprennent des données de déplacement de véhicule à inclinaison sur un véhicule à inclinaison tandis qu'un passager et/ou un bagage sont embarqués ; acquérir des données de déplacement de véhicule à inclinaison à des fins d'analyse qui comprennent les données de déplacement de véhicule à inclinaison tandis que le passager et/ou le bagage sont embarqués ; et acquérir des données d'analyse d'une personne à analyser par analyse des données de déplacement de véhicule à inclinaison à des fins d'analyse acquises sur la base des données de référence de déplacement de véhicule à inclinaison acquises.
PCT/JP2020/015118 2019-04-01 2020-04-01 Procédé d'analyse de données de déplacement de véhicule à inclinaison, dispositif d'analyse de données de déplacement de véhicule à inclinaison, procédé de traitement d'informations utilisant des données d'analyse et dispositif de traitement d'informations utilisant des données d'analyse WO2020204111A1 (fr)

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JP2015203726A (ja) * 2014-04-11 2015-11-16 ヤマハ発動機株式会社 教習支援装置、教習支援プログラムおよび教習支援方法

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WO2013128919A1 (fr) * 2012-02-27 2013-09-06 ヤマハ発動機株式会社 Ordinateur hôte, système de détermination de compétence de fonctionnement, procédé de détermination de compétence de fonctionnement et programme de détermination de compétence de fonctionnement
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