WO2010084580A1 - Dispositif d'évaluation d'un mécanisme d'entraînement et procédé de commande, programme de commande et support de stockage pour dispositif d'évaluation d'un mécanisme d'entraînement - Google Patents

Dispositif d'évaluation d'un mécanisme d'entraînement et procédé de commande, programme de commande et support de stockage pour dispositif d'évaluation d'un mécanisme d'entraînement Download PDF

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WO2010084580A1
WO2010084580A1 PCT/JP2009/050804 JP2009050804W WO2010084580A1 WO 2010084580 A1 WO2010084580 A1 WO 2010084580A1 JP 2009050804 W JP2009050804 W JP 2009050804W WO 2010084580 A1 WO2010084580 A1 WO 2010084580A1
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Prior art keywords
evaluation
driving
driving evaluation
emotion
value
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PCT/JP2009/050804
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English (en)
Japanese (ja)
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宏平 伊藤
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パイオニア株式会社
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Priority to PCT/JP2009/050804 priority Critical patent/WO2010084580A1/fr
Priority to JP2010547340A priority patent/JPWO2010084580A1/ja
Publication of WO2010084580A1 publication Critical patent/WO2010084580A1/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 driving evaluation of a moving body and a technique for calculating emotion based on driving evaluation.
  • Patent Document 1 proposes a method of determining a driving tendency of a driver by comparing data indicating the operation of the vehicle resulting from the driving operation of the driver during traveling with a predetermined threshold.
  • Patent Document 2 the handling of a vehicle by a user is expressed by virtual emotions assuming that the vehicle has a personality, and the virtual emotions are expressed on the display unit of the in-vehicle device by a predetermined character expression.
  • a display method has been proposed.
  • technologies related to the present invention are described in Patent Literature 3 and Patent Literature 4, respectively.
  • JP 2000-47569 A Japanese Patent Laid-Open No. 2003-72488 International Publication WO2007 / 0778767 JP 11-78729 A
  • the driving evaluation when the driving evaluation is performed based only on the behavior of the vehicle, the driving evaluation may be biased for each driver. Similarly, driving evaluation may be biased depending on the characteristics of the vehicle such as whether it is a vehicle model that emphasizes operability or a vehicle model that emphasizes safety. However, providing excessively biased driving evaluation to the driver may not provide useful information for the driver. In particular, when the emotional expression is executed based on the driving evaluation, the same emotional expression is lost due to the biased driving evaluation, and there is a possibility of giving a passenger a feeling of fatigue. Patent Documents 1 to 4 do not describe any of the above problems.
  • An object of the present invention is to provide a driving evaluation device that performs driving evaluation with appropriate fluctuation while preventing excessively biased driving evaluation and reflecting the behavior of the vehicle, and repeats relative evaluation. This aims to bring about improved driving as a result.
  • the invention according to claim 1 is a driving evaluation device mounted on a moving body, wherein the driving data acquisition unit acquires driving data of the moving body, the driving data, and parameters for determining driving evaluation. And a parameter adjusting unit that sequentially adjusts the parameters based on driving evaluations determined in the past.
  • the invention according to claim 10 is a method for controlling a driving evaluation apparatus mounted on a moving body, wherein the driving data acquiring step for acquiring driving data of the moving body, the driving data, and driving evaluation are determined. And a parameter adjustment step of sequentially adjusting the parameters based on the previously determined operation evaluations.
  • the invention according to claim 11 is a control program executed by a driving evaluation device mounted on a moving body, the driving data acquiring unit acquiring driving data of the moving body, the driving data, and driving evaluation.
  • a driving evaluation determination unit that determines the driving evaluation based on the parameter for determining the parameter, and a parameter adjustment unit that sequentially adjusts the parameter based on the driving evaluation determined in the past.
  • the invention according to claim 12 is a storage medium characterized by storing the control program according to claim 11.
  • FIG. 1 It is an example of the figure which shows the structure of a driving
  • a driving evaluation device is mounted on a moving body, based on an driving data acquisition unit that acquires driving data of the moving body, the driving data, and a parameter for determining driving evaluation.
  • a driving evaluation determination unit that determines driving evaluation; and a parameter adjustment unit that sequentially adjusts the parameters based on driving evaluations determined in the past.
  • the above-mentioned driving evaluation device corresponds to, for example, a vehicle-mounted multi-purpose device that operates for the purpose of communication with a driver, or a vehicle-mounted navigation device mounted on a moving body such as an automobile.
  • the driving evaluation device includes an driving data acquisition unit, a driving evaluation determination unit, and a parameter adjustment unit.
  • the driving data acquisition unit acquires driving data such as speed or acceleration of the moving body.
  • the driving evaluation determination unit determines driving evaluation based on driving data and parameters for determining driving evaluation.
  • the above-described parameter is, for example, a threshold value for determining driving evaluation.
  • the parameter adjustment unit sequentially adjusts the parameters based on the operation evaluation determined in the past.
  • driving evaluation determined in the past refers to one or a plurality of arbitrary driving evaluations determined by the driving evaluation determination unit by the time of parameter adjustment, for example, the latest (most recent) predetermined number of driving evaluations.
  • driving evaluation refers to driving evaluation.
  • Sequential adjustment refers to adjusting a parameter according to a predetermined cycle or other predetermined rule.
  • the parameter adjustment unit after accumulating the driving evaluation over a predetermined number or a predetermined time width, belongs to a relatively high evaluation based on a predetermined value of the driving evaluation.
  • the parameter is changed based on the number and the number belonging to the low rating.
  • the driving evaluation device can prevent the driving evaluation from being biased excessively by changing the parameters by comparing the number belonging to the high evaluation and the number belonging to the low evaluation among the past driving evaluations. .
  • the driving evaluation device further includes a preprocessing unit that calculates a behavior value indicating the magnitude of the behavior of the moving body based on the driving data, and the driving evaluation determination unit includes the behavior value and
  • the driving evaluation belongs to a low evaluation or a high evaluation by comparing with a first threshold, and the parameter adjustment unit is greater than the number belonging to the high evaluation If the number belonging to the low evaluation is less than or equal to the number belonging to the high evaluation, the first threshold is decreased.
  • the driving evaluation apparatus further includes a preprocessing unit that calculates a behavior value based on the driving data.
  • the behavior value is, for example, an absolute value of acceleration in the front-rear direction of the moving body, or a value calculated based on the absolute value.
  • the first threshold value adjusted by the parameter adjustment unit is a parameter for determining whether the driving evaluation belongs to a low evaluation or a high evaluation. Therefore, the driving evaluation device can prevent the driving evaluation from being excessively biased to high evaluation or low evaluation by changing the first threshold as described above.
  • the driving data is an acceleration of the moving body.
  • the preprocessing unit sets, as the behavior value, a difference between the absolute value of the acceleration and an average absolute value of the acceleration acquired in the past.
  • acceleration acquired in the past refers to any one or more accelerations acquired in the past, for example, a predetermined number of accelerations acquired most recently.
  • the driving evaluation device can calculate the behavior value P without being affected by the road gradient, for example. Also, by calculating the absolute value average of past accelerations as a value to be subtracted from the acceleration, it is possible to prevent the behavior values from fluctuating unnecessarily due to fluctuations in the past acceleration.
  • the driving evaluation determination unit does not determine the driving evaluation while the moving body is stopped.
  • the driving evaluation apparatus determines that the driving evaluation is high because the moving body has no behavior. Therefore, in this aspect, the driving evaluation device prevents an unnecessarily biased driving evaluation while the moving body is stopped.
  • the driving evaluation apparatus further includes an emotion calculation unit that calculates an emotion based on the driving evaluation and fluctuation characteristics, and the parameter adjustment unit includes a predetermined number or a predetermined time width. After accumulating the emotion over the range, the fluctuation characteristic is changed based on the change width of the emotion.
  • the fluctuation characteristic is a parameter for determining the magnitude of the emotion fluctuation, that is, the degree of change of the emotion with respect to the driving evaluation.
  • the driving evaluation apparatus when the change width is larger than a predetermined width, the fluctuation characteristic is changed so that the fluctuation of the emotion is reduced, and when the change width is equal to or smaller than the predetermined width, the fluctuation is The characteristic is changed so that the fluctuation becomes large.
  • the predetermined width is determined in advance as an appropriate emotion change width based on experiments or the like. In this way, the driving evaluation device can appropriately change the emotion fluctuation characteristics.
  • an emotion expression unit that expresses an emotion based on the emotion is further provided.
  • an emotion expression part can perform emotion expression with moderate fluctuation, without being overly biased.
  • a method for controlling the driving evaluation device mounted on the moving body the driving data acquiring step for acquiring driving data of the moving body, the driving data, and the driving evaluation.
  • the driving evaluation device can prevent the driving evaluation from being excessively biased by performing the driving evaluation based on the above-described control method.
  • the driving program is a control program executed by the driving evaluation apparatus mounted on the moving body, the driving data acquiring unit acquiring driving data of the moving body, and the driving data.
  • a driving evaluation determining unit that determines driving evaluation based on parameters for determining driving evaluation, and a parameter adjusting unit that sequentially adjusts the parameters based on driving evaluation determined in the past.
  • the driving evaluation device can prevent the driving evaluation from being excessively biased by executing this control program.
  • FIG. 1 shows a conceptual diagram of a driving evaluation system in the present embodiment.
  • the driving evaluation system includes a driving evaluation device 100 and an emotion expression device 200.
  • the driving evaluation device 100 and the emotion expression device 200 are connected by an electrical method regardless of wired connection or wireless connection, and can exchange data according to a predetermined communication protocol.
  • the driving evaluation device 100 is mounted on a vehicle and performs an evaluation (referred to as “driving evaluation”) regarding driving performed by a driver of the vehicle.
  • the driving evaluation apparatus 100 includes a driving data acquisition unit 100a, a preprocessing unit 100b, a driving evaluation determination unit 100c, an emotion calculation unit 100d, and a parameter adjustment unit 100e.
  • the driving data acquisition unit 100a acquires the acceleration Pa of the vehicle.
  • the acceleration Pa is an example of driving data in the present invention.
  • the preprocessing unit 100b performs predetermined preprocessing on the acquired acceleration Pa, and converts the acquired acceleration Pa into a value more accurately reflecting the behavior of the vehicle.
  • the value of the acceleration Pa after the above pre-processing is referred to as “behavior value P”.
  • the driving evaluation determination unit 100c determines the driving evaluation “Va” based on whether or not the behavior value P is larger than a predetermined threshold “T1”.
  • the first threshold value T1 is an example of the driving evaluation parameter in the present invention.
  • the emotion calculation unit 100d calculates the emotion “Ve” expressed by the emotion expression device 200 based on the driving evaluation Va. At that time, the emotion calculation unit 100d determines the influence of the driving evaluation Va on the emotion Ve based on the influence “R”.
  • the influence degree R is an example of a fluctuation characteristic in the present invention.
  • the parameter adjusting unit 100e adjusts the first threshold T1 based on the driving evaluation Va transmitted from the driving evaluation determining unit 100c. In addition to this, the parameter adjustment unit 100e adjusts the influence level R based on the emotion Ve transmitted from the emotion calculation unit 100d.
  • the emotion expression device 200 is a device capable of expressing emotion based on the emotion Ve input from the driving evaluation device 100.
  • the emotion expression device 200 is, for example, a machine or device that autonomously performs actions such as communication with a user and photographing a scenery outside a vehicle.
  • the emotion expression device 200 may be realized as one function of the navigation device, and may perform a predetermined display on a display included in the navigation device.
  • the emotion calculation unit 100d may be realized by a device separate from the driving evaluation device 100.
  • the device including the emotion calculation unit 100d is electrically connected to the driving evaluation device 100 and the emotion expression device 200, and exchanges signals regarding the driving evaluation Va, the emotion Ve, the influence degree R, and the like.
  • the emotion calculation unit 100d may be realized by the emotion expression device 200.
  • the driving evaluation device 100 and the emotion expression device 200 exchange signals such as driving evaluation Va, emotion Ve, and influence level R.
  • the driving evaluation device 100 and the emotion expression device 200 may be realized as an integrated multipurpose device.
  • the “multipurpose device” refers to a machine or device that autonomously performs actions such as communication with a user and photographing a scenery outside a vehicle.
  • the multipurpose device may be configured to have a function of interlocking with the navigation device and music or video content reproduction as necessary.
  • FIG. 2 is an example of a schematic configuration of the driving evaluation apparatus 100.
  • the driving evaluation device 100 includes an acceleration sensor 11, a system controller 20, a data storage unit 36, a communication interface 37, and a communication device 38.
  • the acceleration sensor 11 is made of, for example, a piezoelectric element, detects vehicle acceleration, and outputs acceleration data.
  • the acceleration sensor 11 detects an acceleration Pa with the forward direction of the vehicle as positive.
  • the system controller 20 includes an interface 21, a CPU (Central Processing Unit) 22, a ROM (Read Only Memory) 23, and a RAM (Random Access Memory) 24, and controls the entire operation evaluation apparatus 100.
  • a CPU Central Processing Unit
  • ROM Read Only Memory
  • RAM Random Access Memory
  • the interface 21 performs an interface operation between the acceleration sensor 11 and the system controller 20.
  • the interface 21 inputs the acceleration Pa to the system controller 20.
  • the CPU 22 controls the entire system controller 20.
  • the CPU 22 functions as the driving data acquisition unit 100a, the preprocessing unit 100b, the driving evaluation determination unit 100c, the emotion calculation unit 100d, and the parameter adjustment unit 100e by executing a program prepared in advance.
  • the ROM 23 has a nonvolatile memory (not shown) in which a control program for controlling the system controller 20 is stored.
  • the RAM 24 stores various data such as route data preset by the user via the input device 60 so as to be readable, and provides a working area to the CPU 22.
  • the system controller 20, the data storage unit 36, and the communication interface 37 are connected to each other via the bus line 30.
  • the data storage unit 36 is configured by, for example, an HDD and stores various data.
  • the data storage unit 36 stores, for example, each parameter necessary for calculating the emotion Ve.
  • the communication device 38 is a device that can communicate with the emotion expression device 200.
  • the communication device 38 is a communication adapter that is electrically connected to the emotion expression device 200 via various AV cables, coaxial cables, or the like, or wirelessly, for example.
  • the communication device 38 transmits the emotion Ve to the emotion expression device 200 at every predetermined cycle or upon request from the emotion expression device 200.
  • the interface 37 performs an interface operation between the communication device 38 and the system controller 20.
  • the CPU 22 functions as the driving data acquisition unit 100a, the preprocessing unit 100b, the driving evaluation determination unit 100c, the emotion calculation unit 100d, and the parameter adjustment unit 100e.
  • the preprocessing unit 100b calculates the behavior value P by relatively evaluating the acceleration Pa. Specifically, the preprocessing unit 100b sets the difference between the absolute value of the acceleration Pa and the average absolute value of the acceleration acquired in the past as the behavior value P. Thus, by calculating the behavior value P based on the acceleration Pa, the pre-processing unit 100b appropriately calculates the behavior value P.
  • the driving data acquisition unit 100a acquires the acceleration Pa from the acceleration sensor 11. Then, the preprocessing unit 100b converts the acceleration Pa into an absolute value.
  • the preprocessing unit 100b subtracts the average of the absolute values of the most recently acquired accelerations (for example, 10) from the absolute value of the currently acquired acceleration Pa and sets the absolute value as the behavior value P. . That is, if the absolute value average of accelerations for a predetermined number (hereinafter referred to as “acceleration absolute value average”) is “Pam”, the preprocessing unit 100b uses the following equation (1) to calculate the behavior value P. Is calculated.
  • the predetermined number is set to an appropriate value by, for example, experiments.
  • the preprocessing unit 100b can set the behavior value P to a value that accurately reflects the behavior of the vehicle. it can. Furthermore, the preprocessing unit 100b can calculate the behavior value P without being affected by the road gradient.
  • the acceleration sensor 11 detects an acceleration Pa whose absolute value in the forward direction of the vehicle is 0 or more due to the influence of gravity due to the vehicle being tilted back and forth. To do.
  • the preprocessing unit 100b calculates the behavior value P according to the equation (1), thereby preventing the behavior value P from fluctuating due to the slope of the stopped road surface.
  • the preprocessing unit 100b calculates the behavior value P using Equation (1), thereby preventing the behavior value P from fluctuating due to the gradient of the road surface during traveling.
  • the pre-processing unit 100b calculates the absolute value average Pam of the past acceleration as a value to be subtracted from the acceleration Pa, so that the behavior value C fluctuates unnecessarily due to the fluctuation of the acceleration Pa acquired in the past. prevent.
  • FIG. 3A is an example of a graph of a change in acceleration Pa over time.
  • FIG. 3B is an example of a graph of the time change of the behavior value P calculated according to the equation (1).
  • the behavior value P is always 0 or more.
  • the behavior value P increases in a time zone in which the change in the acceleration Pa is large, that is, a time zone in which the behavior of the vehicle is intense.
  • the pre-processing unit 100b can set the behavior value P to a value that appropriately reflects the behavior of the vehicle.
  • the preprocessing unit 100b may use the acquired acceleration Pa as the attachment angle when there is a deviation between the front direction of the vehicle and the detection direction of the acceleration Pa, that is, when the attachment angle has occurred. You may correct
  • the preprocessing unit 100b may simplify the preprocessing using the absolute value of the acceleration Pa as the behavior value P instead of the above-described processing.
  • the driving evaluation determination unit 100c determines the driving evaluation Va by comparing the behavior value P with the first threshold value T1.
  • the parameter adjustment unit 100e sequentially changes the first threshold value T1 based on the determined operation evaluation Va. Specifically, the parameter adjustment unit 100e accumulates the driving evaluation Va, raises the first threshold T1 when there are many high evaluations among the accumulated driving evaluation Va, and sets the first threshold when there are many low evaluations. Lower the threshold T1. This prevents the driving evaluation Va from being excessively biased.
  • the driving evaluation Va takes two values: a high evaluation “VaH” indicating that the driving state is good, and a low evaluation “VaL” indicating that the driving state is other than that. To do.
  • the driving evaluation determination unit 100c After calculating the behavior value P, the driving evaluation determination unit 100c acquires the first threshold value T1 held in the data storage unit 36 or the like, and determines whether or not the behavior value P is larger than the first threshold value T1.
  • the initial value of the first threshold T1 is set to an appropriate value in advance through experiments or the like, for example, and stored in the data storage unit 36 or the like.
  • the driving evaluation determination unit 100c determines that the driving state is good and sets the driving evaluation Va to the high evaluation VaH.
  • the driving evaluation determination unit 100c determines that the driving state is not good and sets the driving evaluation Va to the low evaluation VaL.
  • FIG. 4 shows an example of a graph showing the behavior value P over time and the range of each driving evaluation Va.
  • the high evaluation VaH and the low evaluation VaL are divided with the first threshold T1 as a boundary.
  • a threshold T2 (hereinafter referred to as “stop”) is determined. "Referred to as” second threshold value T2 ") is set.
  • the driving evaluation determination unit 100c considers that the vehicle is stopped and invalidates the driving evaluation Va.
  • the parameter adjustment unit 100e After calculating the driving evaluation Va, the parameter adjustment unit 100e holds the result in the data storage unit 36 or the like. When the predetermined number of driving evaluations Va (hereinafter referred to as “number N1”) are accumulated, the parameter adjustment unit 100e changes the first threshold T1 based on the number N1 of driving evaluations Va. .
  • the number N1 is determined in advance to an appropriate value through experiments or the like.
  • the parameter adjustment unit 100e decreases the first threshold T1 when the number of high evaluation VaH is larger than the number of low evaluation VaL among a predetermined number of operation evaluation Va.
  • the value to be subtracted from the first threshold value T1 is set to an appropriate value through experiments or the like.
  • the first threshold value T1 after the change is set to the average value or the median value of the behavior values P corresponding to the number N1 of driving evaluation Va.
  • the driving evaluation apparatus 100 can prevent the driving evaluation Va from being excessively biased to the high evaluation VaH. In other words, the driving evaluation apparatus 100 can relatively determine the current driving evaluation Va based on the past driving evaluation Va.
  • the parameter adjustment unit 100e increases the first threshold T1 when the number of high evaluation VaH is equal to or less than the number of low evaluation VaL among the predetermined number of operation evaluation Va.
  • the value to be added to the first threshold T1 is set to an appropriate value by experiment or the like.
  • the first threshold value T1 after the change is set to an average value or a median value of the behavior values P corresponding to the number N1 of driving evaluation Va.
  • the driving evaluation apparatus 100 can prevent the driving evaluation Va from being excessively biased to the low evaluation VaL. In other words, the driving evaluation apparatus 100 can relatively determine the current driving evaluation Va based on the past driving evaluation Va.
  • FIG. 5A shows a graph of the temporal change of the emotion Ve when the first threshold value T1 is fixed
  • FIG. 5B shows a case where the first threshold value T1 is sequentially adjusted by the method shown in the embodiment.
  • the graph of the time change of the emotion Ve is shown.
  • the emotion Ve has a minimum value “Vemin” and a maximum value “Vemax”, and the higher the value, the better the mood. A specific method for calculating the emotion Ve will be described later.
  • the emotion Ve when the first threshold value T1 is fixed, the emotion Ve is biased to a value indicating that the mood is good.
  • the emotion Ve when the first threshold value T1 is sequentially adjusted, the emotion Ve has an appropriate fluctuation.
  • the behavior value P tends to be biased for each driver.
  • the behavior value P is biased depending on whether the operability-oriented vehicle type or the safety-oriented vehicle type is used.
  • the first threshold value T1 is sequentially adjusted, and the threshold value T1 is reset in consideration of the past driving evaluation Va. It is possible to prevent the emotion Ve from being biased. As a result, the driving evaluation apparatus 100 can more closely approximate the change in the emotion Ve to the human emotional change.
  • the parameter adjustment unit 100e decreases the first threshold T1, and the number of high evaluation VaH is equal to or less than the number of low evaluation VaL. In this case, the first threshold T1 is increased.
  • the method to which the present invention is applicable is not limited to this. For example, instead of this, when the number of high evaluation VaH and the number of low evaluation VaL are the same or a difference within a predetermined range, the parameter adjustment unit 100e determines that the first threshold T1 is appropriately set. It is not necessary to determine and change the first threshold value.
  • the parameter adjustment unit 100e changes the threshold value T1 when the operation evaluation Va is accumulated by the number N1, but instead, the operation is performed over a predetermined time width (hereinafter referred to as “time width Tw1”). After accumulating the evaluation Va, the threshold value T1 may be changed based on the operation evaluation Va. Even in this case, the parameter adjustment unit 100e changes the first threshold T1 based on the number of high evaluation VaH and the number of low evaluation VaL among the operation evaluation Va acquired in the time width Tw1.
  • the emotion calculation unit 100d calculates the emotion Ve based on the driving evaluation Va and the influence R. Further, the parameter adjusting unit 100e accumulates the emotion Ve over a predetermined number (hereinafter referred to as “number N2”) or a predetermined time width (hereinafter referred to as “time width Tw2”). The influence degree R is changed based on whether or not a predetermined fluctuation range is exceeded.
  • the number N2 is set to be the same as the number N1, for example.
  • the time width Tw2 is set to be the same as the time width Tw1, for example.
  • the number N2 and the time width T2 are set in advance to appropriate values based on experiments or the like. By doing in this way, emotion calculation part 100d calculates emotion Ve which has moderate fluctuation width.
  • the emotion calculation unit 100d calculates the “behavior change value C” based on the driving evaluation Va. Furthermore, the emotion calculation unit 100d calculates the “behavior score Vr” from the behavior change value C. Then, the emotion calculation unit 100d calculates the emotion Ve based on the behavior score Vr and the influence level R. These processes are executed each time the behavior value P is calculated as one process (loop). Hereinafter, these processes will be described in order.
  • the emotion calculation unit 100d adds a predetermined value “A” to the behavior change value C when the driving evaluation Va is the high evaluation VaH, and subtracts the behavior value P from the behavior change value C when the driving evaluation Va is the low evaluation VaL. To do.
  • the initial value of the behavior change value C is set to zero.
  • the predetermined value A is, for example, a constant determined in advance by experiments or the like, or a variable having a negative correlation with the behavior value P.
  • the behavior change value C is a cumulative value and is not initialized for each process. Therefore, when the ratio of the high evaluation VaH is large in the calculated driving evaluation Va, the behavior change value C gradually increases. On the other hand, when the ratio of the low evaluation VaL is large in the calculated driving evaluation Va, the behavior change value C gradually decreases.
  • the emotion calculation unit 100d adds the behavior change value C to the behavior score Vr.
  • the behavior score Vr is a cumulative value, and an initial value is set to 0, for example.
  • the emotion calculation unit 100d adds a value obtained by multiplying the behavior score Vr by the influence level R to the standard value of the emotion Ve (hereinafter referred to as “base emotion Vb”), that is, the offset value of the emotion Ve. Is emotion Ve.
  • the base emotion Vb is set to an intermediate value between the maximum value Vemax and the minimum value Vemin of the emotion Ve, for example. That is, the emotion calculation unit 100d calculates the emotion Ve by the following equation (2).
  • the greater the influence level R the greater the change in emotion Ve.
  • the initial value of the degree of influence R is set to a relatively small value, and specifically, an appropriate value is set in advance through experiments or the like. Further, the influence degree R is updated, for example, every time width Tw2 or every time the number Ve of emotions Ve is acquired.
  • the parameter adjusting unit 100e accumulates the emotion Ve over the number N2 or the time width Tw2, and then the predetermined change area (hereinafter referred to as “change width Vew”) of the accumulated emotion Ve is stored. , Called “setting region Kw”).
  • the setting area Kw is a width or a value range for determining whether or not the change width Vew, that is, the difference between the maximum value and the minimum value of the accumulated emotion Ve is appropriate.
  • the setting area Kw is set to an appropriate value by an experiment or the like, for example.
  • the parameter adjustment unit 100e determines that the change width Vew is larger than the appropriate change width, and lowers the influence level R.
  • the amount of decrease in the degree of influence R is, for example, a predetermined constant or a variable having a positive correlation with the change width Vew.
  • the parameter adjustment unit 100e determines that the change width Vew is smaller than the appropriate change width, and increases the influence level R.
  • the increase amount of the influence degree R is, for example, a predetermined constant or a variable having a negative correlation with the change width Vew.
  • FIG. 6A shows a graph of the temporal change of the emotion Ve before the adjustment of the influence level R.
  • FIG. 6B shows a graph of the temporal change of the emotion Ve after the influence degree R is adjusted.
  • the change width Vew is larger than the setting area Kw before the influence R is adjusted. Therefore, in this case, the parameter adjustment unit 100e decreases the influence level R.
  • the change width Vew is substantially within the set region Kw.
  • the driving evaluation device 100 can give the emotion Ve appropriate fluctuations by changing the influence level R based on the change width Vew and the setting region Kw.
  • the parameter adjustment unit 100e changes the influence level R by comparing the change width Vew and the setting region Kw.
  • the method to which the present invention is applicable is not limited to this.
  • the parameter adjustment unit 100e defines the setting area Kw as a predetermined value range, and changes the influence R based on whether the emotion Ve does not exceed the maximum value or the minimum value of the setting area Kw. May be.
  • the parameter adjustment unit 100e may change the influence degree R every time the influence degree R exceeds the maximum value or the minimum value.
  • the parameter adjustment unit 100e always changes the influence level R after accumulating the emotion Ve by the number N2 or after accumulating the emotion Ve over the time width Tw2.
  • the method to which the present invention is applicable is not limited to this.
  • the parameter adjustment unit 100e may not change the influence level R when the change width Vew is the same as the setting region Kw or a difference within a predetermined range.
  • the emotion calculation unit 100d may initialize the behavior change value C and the behavior score Vr periodically. In this case, for example, the emotion calculation unit 100d initializes the behavior change value C and the behavior score Vr at the same time as adjusting the degree of influence R.
  • FIG. 7 is an example of a flowchart showing the procedure of processing executed by the CPU 22 in this embodiment.
  • the CPU 22 repeatedly executes the processing of the flowchart shown in FIG. 7 according to a predetermined cycle.
  • the CPU 22 acquires operation data (step S101). That is, the CPU 22 acquires the acceleration Pa with the forward direction of the vehicle as positive from the acceleration sensor 11.
  • the CPU 22 performs preprocessing (step S102). That is, the CPU 22 calculates the behavior value P using Equation (2) based on the acceleration Pa. Further, when the absolute value average Pam of acceleration cannot be calculated immediately after the start of the process, the CPU 22 calculates the behavior value P from the equation (2) with the absolute value average Pam of acceleration set to 0, for example.
  • the CPU 22 determines whether or not the behavior value P is greater than the first threshold value T1 (step S103). Thereby, CPU22 determines driving
  • the CPU 22 determines that the behavior of the vehicle is larger than the reference, and determines the driving evaluation Va as the low evaluation VaL (step S104).
  • step S103 when the behavior value P is equal to or less than the first threshold value T1 (step S103; No), the CPU 22 determines that the behavior of the vehicle is within the reference, and determines the driving evaluation Va as the high evaluation VaH (step S105). .
  • the CPU 22 calculates the emotion Ve (step S106). Specifically, as described above, the CPU 22 calculates the behavior change value C based on the driving evaluation Va. Further, the CPU 22 calculates a behavior score Vr from the behavior change value C. Then, the CPU 22 calculates the emotion Ve from the expression (2) based on the behavior score Vr and the influence degree R.
  • step S107 determines whether or not sufficient data has been accumulated. Specifically, the CPU 22 determines whether or not the sampling number of the emotion Ve has reached the number N1. When it is determined that sufficient data has been accumulated (step S107; Yes), the CPU 22 executes the process of step S108. On the other hand, when determining that sufficient data is not accumulated (step S107; No), the CPU 22 returns the process to step S101.
  • step S107 when it is determined that sufficient data has been accumulated (step S107; Yes), the CPU 22 determines whether or not the number of low evaluation VaL is larger than the number of high evaluation VaH (step S108). That is, the CPU 22 determines which of the accumulated driving evaluation Va is larger, the proportion occupied by the low evaluation VaL and the proportion occupied by the high evaluation VaH.
  • step S108 when the number of low evaluation VaL is larger than the number of high evaluation VaH (step S108; Yes), CPU22 raises threshold value T1 (step S109). Thereby, in the range of the behavior value P, the value range determined as the low evaluation VaL is narrowed, and the value range determined as the high evaluation VaH is widened.
  • step S108 when the number of the low evaluation VaL is equal to or less than the number of the high evaluation VaH (step S108; No), the CPU 22 decreases the threshold T1 (step S110). Thereby, in the range of the behavior value P, the range of values determined as the low evaluation VaL is widened, and the range of values determined as the high evaluation VaH is narrowed.
  • the CPU 22 determines whether or not the change width Vew of the accumulated emotion Ve is larger than the setting area Kw (step S111). That is, the CPU 22 calculates the change width Vew from the difference between the maximum value and the minimum value of the number N1 of emotion Ve, and compares it with a predetermined setting area Kw, so that the change width Vew of the emotion Ve is appropriate. Judge whether or not.
  • step S111 If the emotion change width Vew is larger than the setting area Kw (step S111; Yes), the CPU 22 decreases the influence R (step S112). Thereby, CPU22 suppresses the excessive fluctuation
  • step S111 when the change width Vew is equal to or smaller than the set area Kw (step S111; No), the CPU 22 increases the influence level R (step S113). Thereby, the CPU 22 gives an appropriate fluctuation to the emotion Ve to be calculated thereafter, and increases the change width Vew.
  • step S114 determines whether or not an end signal has been issued. For example, the CPU 22 determines whether or not the occupant has pressed a power button or the like provided in the driving evaluation device 100. If it is determined that an end signal has been issued (step S114; Yes), the CPU 22 ends the process of the flowchart. On the other hand, when the end signal has not been issued (step S114; No), the CPU 22 returns the process to step S101 again.
  • the driving evaluation apparatus includes the driving data acquisition unit, the driving evaluation determination unit, and the parameter adjustment unit.
  • the driving data acquisition unit acquires acceleration.
  • the driving evaluation determination unit determines driving evaluation based on the acceleration and a first threshold that is a threshold for determining driving evaluation.
  • the parameter adjustment unit sequentially adjusts the parameters based on the operation evaluation determined in the past.
  • the driving evaluation device can prevent the driving evaluation from being excessively biased by changing the parameter in consideration of the past driving evaluation.
  • the CPU 22 determines the emotion Ve based on the driving evaluation Va.
  • the method for determining the emotion Ve to which the present invention is applicable is not limited to this.
  • the CPU 22 may determine the emotion Ve based on whether or not the road is congested. As a result, the CPU 22 calculates an emotion Ve that more closely matches the human emotion.
  • the CPU 22 determines that the vehicle has behaved to repeat stopping and starting a predetermined number of times within a predetermined time width, It is considered that there is traffic and lowers the emotion Ve.
  • the predetermined time, the predetermined number of times, and the amount of emotion reduction are determined in advance to appropriate values based on experiments and the like.
  • the CPU 22 determines whether or not the vehicle has been repeatedly stopped and started, for example, whether or not the behavior value P has increased or decreased the second threshold value T2, or whether the absolute value of the acceleration Pa is experimental or the like. Judgment is made based on whether or not a predetermined threshold value is raised or lowered.
  • the CPU 22 may determine whether or not the road is congested based on road information from a navigation device (not shown) provided in the vehicle. . Specifically, the CPU 22 acquires information (hereinafter referred to as “VICS information”) distributed from a VICS (Vehicle Information Communication System) center or the like from the navigation device. Then, the CPU 22 determines whether or not the road on which the vehicle is traveling or the road to be traveled is jammed based on this information, and reflects it in the emotion Ve.
  • VICS information Vehicle Information Communication System
  • the driving evaluation device 100 and the navigation device are configured to be electrically connected and to be able to exchange signals with each other.
  • the present invention can be used for navigation devices and other multipurpose devices installed in vehicles.

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  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Automation & Control Theory (AREA)
  • Mathematical Physics (AREA)
  • Transportation (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)
  • Measurement Of The Respiration, Hearing Ability, Form, And Blood Characteristics Of Living Organisms (AREA)

Abstract

L'invention concerne un dispositif d'évaluation d'un mécanisme d'entraînement comprenant une section d'acquisition de données de mécanisme d'entraînement, une section de détermination de l'évaluation du mécanisme d'entraînement et une section de réglage des paramètres. La section d'acquisition de données de mécanisme d'entraînement acquiert des données de mécanisme d'entraînement telles que la vitesse et l'accélération d'un objet en mouvement. La section de détermination de l'évaluation du mécanisme d'entraînement détermine l'évaluation du mécanisme d'entraînement en se basant sur les données et les paramètres du mécanisme d'entraînement. La section de réglage des paramètres effectue un réglage séquentiel des paramètres en se basant sur l'évaluation du mécanisme d'entraînement déterminée précédemment.
PCT/JP2009/050804 2009-01-21 2009-01-21 Dispositif d'évaluation d'un mécanisme d'entraînement et procédé de commande, programme de commande et support de stockage pour dispositif d'évaluation d'un mécanisme d'entraînement WO2010084580A1 (fr)

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PCT/JP2009/050804 WO2010084580A1 (fr) 2009-01-21 2009-01-21 Dispositif d'évaluation d'un mécanisme d'entraînement et procédé de commande, programme de commande et support de stockage pour dispositif d'évaluation d'un mécanisme d'entraînement
JP2010547340A JPWO2010084580A1 (ja) 2009-01-21 2009-01-21 運転評価装置、運転評価装置の制御方法、制御プログラム及び記憶媒体

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JP2014139777A (ja) * 2012-12-21 2014-07-31 Denso Corp 車両用情報提供装置
JP2017502639A (ja) * 2013-12-24 2017-01-19 アムステッド、レイル、カンパニー、インコーポレイテッドＡｍｓｔｅｄ Ｒａｉｌ Ｃｏｍｐａｎｙ， Ｉｎｃ． 列車編成と鉄道車両とにおける稼働異常を検出するためのシステムと方法
WO2018190178A1 (fr) * 2017-04-12 2018-10-18 川崎重工業株式会社 Système de génération d'émotions artificielles et procédé de sortie d'informations de conversation pour véhicule
CN109906461A (zh) * 2016-11-16 2019-06-18 本田技研工业株式会社 情感估计装置和情感估计***
WO2022196660A1 (fr) * 2021-03-19 2022-09-22 株式会社デンソー Dispositif d'aide à la conduite, procédé d'aide à la conduite, enregistreur de conduite et programme de commande d'aide à la conduite

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JPH06255519A (ja) * 1993-03-09 1994-09-13 Mazda Motor Corp 車両の制御装置
JP2004306770A (ja) * 2003-04-07 2004-11-04 Daihatsu Motor Co Ltd 車両の運転状況評価装置及び運転状況評価方法
JP2006347296A (ja) * 2005-06-14 2006-12-28 Toyota Motor Corp 運転評価装置

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JPH06255519A (ja) * 1993-03-09 1994-09-13 Mazda Motor Corp 車両の制御装置
JP2004306770A (ja) * 2003-04-07 2004-11-04 Daihatsu Motor Co Ltd 車両の運転状況評価装置及び運転状況評価方法
JP2006347296A (ja) * 2005-06-14 2006-12-28 Toyota Motor Corp 運転評価装置

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2014139777A (ja) * 2012-12-21 2014-07-31 Denso Corp 車両用情報提供装置
US9381848B2 (en) 2012-12-21 2016-07-05 Denso Corporation Information provision device for vehicle
JP2017502639A (ja) * 2013-12-24 2017-01-19 アムステッド、レイル、カンパニー、インコーポレイテッドＡｍｓｔｅｄ Ｒａｉｌ Ｃｏｍｐａｎｙ， Ｉｎｃ． 列車編成と鉄道車両とにおける稼働異常を検出するためのシステムと方法
CN109906461A (zh) * 2016-11-16 2019-06-18 本田技研工业株式会社 情感估计装置和情感估计***
CN109906461B (zh) * 2016-11-16 2022-10-14 本田技研工业株式会社 情感估计装置和情感估计***
WO2018190178A1 (fr) * 2017-04-12 2018-10-18 川崎重工業株式会社 Système de génération d'émotions artificielles et procédé de sortie d'informations de conversation pour véhicule
JPWO2018190178A1 (ja) * 2017-04-12 2020-02-20 川崎重工業株式会社 乗物の疑似感情生成システムおよび会話情報出力方法
US11046384B2 (en) 2017-04-12 2021-06-29 Kawasaki Jukogyo Kabushiki Kaisha Vehicle pseudo-emotion generating system and conversation information output method
WO2022196660A1 (fr) * 2021-03-19 2022-09-22 株式会社デンソー Dispositif d'aide à la conduite, procédé d'aide à la conduite, enregistreur de conduite et programme de commande d'aide à la conduite

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