Driving evaluation device, driving evaluation method, and driving evaluation program

Abstract

The present invention relates to a driving evaluation device, a driving evaluation method, and a driving evaluation program. A driving evaluation device includes: an acquisition unit that acquires at least one of vehicle information related to a vehicle state and driving information related to a driver's driving state; a determination unit that determines whether a predetermined failed operation related to driving has been performed based on at least one of the vehicle information and the driving information acquired by the acquisition unit; and a calculation unit that calculates a failed operation possibility as a possibility that the failed operation is performed based on the failed operation determined by the determination unit, and calculates an evaluation value related to the driver's driving using a Z-score of the failed operation possibility calculated based on the failed operation possibility.

Description

Technical Field

[0001] The present invention relates to a driving evaluation device, a driving evaluation method, and a driving evaluation program. Background Art

[0002] Japanese Unexamined Patent Application Publication No. 2019-79151 (JP 2019-79151 A) discloses a technique for evaluating a driver's driving skill by comparing reference data indicating a standard for whether a driver is performing an appropriate action with the driver's actions. Specifically, in the technique of JP 2019-79151 A, when the driver's action exceeds the corresponding reference data, the evaluation is marked as good, and when the action is below the corresponding reference data, the evaluation is marked as bad. Summary of the Invention

[0003] However, in the technique of JP 2019-79151 A, when the per-unit-time action of a driver who should have a low evaluation is exactly appropriate, the evaluation is high, and when the per-unit-time action of a driver who should have a high evaluation is exactly inappropriate, the evaluation is low. Therefore, the technique of JP 2019-79151 A is vulnerable to external factors such as the vehicle driving environment at the time of evaluation and differences between vehicles, and there is room for improvement from the perspective of evaluating a driver's driving.

[0004] Therefore, an object of the present invention is to provide a driving evaluation device, a driving evaluation method, and a driving evaluation program that can reduce the influence of external factors such as the vehicle driving environment and differences between vehicles when evaluating a driver's driving.

[0005] A driving evaluation device according to a first aspect of the present disclosure includes: an acquisition unit that acquires at least one of vehicle information related to a vehicle state and driving information related to a driver's driving state; a determination unit that determines whether a predetermined failure operation related to driving has been performed based on at least one of the vehicle information and the driving information acquired by the acquisition unit; and a calculation unit that calculates a failure operation possibility as a possibility that the failure operation is performed based on the failure operation determined by the determination unit, and calculates an evaluation value related to the driver's driving using a Z-score of the failure operation possibility calculated based on the failure operation possibility.

[0006] In the driving evaluation device according to the above solution, the acquisition unit acquires at least one of vehicle information and driving information. Further, the determination unit determines whether a failure operation has been performed based on at least one of the vehicle information and the driving information acquired by the acquisition unit. Further, the calculation unit calculates the failure operation probability based on the failure operation determined by the determination unit, and calculates the evaluation value of the driver using the Z-score. Here, the Z-score is a score converted so that the average is zero and the standard deviation is one. As a result, in the driving evaluation device, the evaluation value of the driver is calculated using the Z-score, thereby realizing the evaluation of the driver's driving using an index such as a deviation value. Therefore, according to the driving evaluation device, when evaluating the driver's driving, it is possible to reduce the influence of external factors such as the vehicle driving environment and the differences between vehicles.

[0007] In the above solution of the driving evaluation device, when calculating the nth evaluation value of driver i who is a member of the driver, the following assumptions are made: Among them, the assumed failure operation probability of the failure operation probability of driver i is The average value of the assumed failure operation probabilities of all drivers including driver i is The standard deviation of the assumed failure operation probabilities of all drivers including driver i is If the failure operation probability from the start of driving the vehicle by driver i to the current time is T, the calculation unit can calculate the Z-score of driver i using the following expression (1) And calculate the Score of the evaluation value of driver i using the following expression (2) i , where Zmin indicates the lower limit of the Z-score, Zmax indicates the upper limit of the Z-score, Smin indicates the lower limit of the evaluation value, and Smax indicates the upper limit of the evaluation value:

[0008] Expression 1

[0009]

[0010] Expression 2

[0011]

[0012] According to the above aspect, the calculation unit calculates using the above expression (1) and calculates Score i using the above expression (2). As a result, in the driving evaluation device, even if the failure operation probability of the driver per unit time is exactly high or exactly low, the influence of the failure operation probability on the evaluation value can be reduced using the assumed failure operation probability in which the failure operation probability is assumed.

[0013] In the above solution of the driving evaluation device, it is assumed that the desired sampling time is and an expected cut-off frequency is Then, the calculation unit can calculate the variable r using the following expression (3) and calculate the assumed failure operation possibility of driver i using the following expression (4)

[0014] Expression 3

[0015]

[0016] Expression 4

[0017]

[0018] According to the above aspect, the calculation unit calculates the variable r using the above expression (3) and calculates As a result, in the driving evaluation device, by adjusting the value of the variable r, the variable component below the expected number of days can be cut off.

[0019] The driving evaluation method according to the second aspect of the present disclosure includes: obtaining at least one of vehicle information related to the vehicle state and driving information related to the driving state of the driver; determining whether a predetermined failure operation related to driving has been performed based on at least one of the obtained vehicle information and driving information; and calculating the failure operation possibility as the possibility of performing the failure operation based on the determined failure operation, and calculating an evaluation value related to the driving of the driver using the Z-score of the failure operation possibility calculated based on the failure operation possibility.

[0020] The driving evaluation program according to the third aspect of the present disclosure causes a computer to execute: obtaining at least one of vehicle information related to the vehicle state and driving information related to the driving state of the driver; determining whether a predetermined failure operation related to driving has been performed based on at least one of the obtained vehicle information and driving information; and calculating the failure operation possibility as the possibility of performing the failure operation based on the determined failure operation, and calculating an evaluation value related to the driving of the driver using the Z-score of the failure operation possibility calculated based on the failure operation possibility.

[0021] As described above, the driving evaluation device, driving evaluation method, and driving evaluation program according to the present invention can reduce the influence of external factors such as the vehicle driving environment and differences between vehicles when evaluating the driving of a driver. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The features, advantages, technology, and industrial significance of the exemplary embodiments of the present invention will be described below with reference to the accompanying drawings, in which the same reference numerals represent the same elements, and in which:

[0023] Figure 1 is a schematic diagram showing a schematic configuration of a driving evaluation system according to the present embodiment;

[0024] Figure 2 is a block diagram showing a hardware configuration of a driving evaluation device according to the present embodiment;

[0025] Figure 3 is a block diagram showing an example of a functional configuration of a driving evaluation device according to the present embodiment;

[0026] Figure 4 is a block diagram showing a hardware configuration of a vehicle according to the present embodiment; and

[0027] Figure 5 is a flowchart showing a flow of calculation processing executed by a driving evaluation device according to the present embodiment. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0028] The driving evaluation system 10 according to the present embodiment will be described below. The driving evaluation system 10 according to the present embodiment is a system in which business operators of operating vehicles such as taxi companies and transportation companies evaluate the driving operations of their drivers. Figure 1 is a schematic diagram showing a schematic configuration of the driving evaluation system 10.

[0029] As Figure 1 shown, the driving evaluation system 10 includes a driving evaluation device 20 and a vehicle 40. The driving evaluation device 20 and the vehicle 40 are connected to each other via a network N so as to be able to communicate with each other. The vehicle 40 connected to the network N is, for example, a vehicle that is traveling while carrying a user.

[0030] The driving evaluation device 20 is a server computer owned by a business operator who manages the vehicle 40. The vehicle 40 may be a gasoline vehicle, a hybrid vehicle, or an electric vehicle, but in the present embodiment, the vehicle 40 is taken as an example of a gasoline vehicle.

[0031] The hardware configuration of the driving evaluation device 20 will be described below. Figure 2 is a block diagram showing a hardware configuration of the driving evaluation device 20.

[0032] As Figure 2 shown, the driving evaluation device 20 includes a central processing unit (CPU) 21, a read-only memory (ROM) 22, a random access memory (RAM) 23, a storage unit 24, an input unit 25, a display unit 26, and a communication unit 27. Each configuration is communicably connected to each other via a bus 28.

[0033] The CPU 21 is a central processing unit that executes various programs and controls various units. That is, the CPU 21 reads programs from the ROM 22 or the storage unit 24 and uses the RAM 23 as a work area to execute the programs. The CPU 21 controls each configuration in the above configuration and performs various arithmetic processes according to the programs recorded in the ROM 22 or the storage unit 24.

[0034] The ROM 22 stores various programs and various data. As a work area, the RAM 23 temporarily stores programs or data.

[0035] The storage unit 24 is composed of a storage device such as a hard disk drive (HDD), a solid state drive (SSD), or a flash memory, and stores various programs and various data. In the present embodiment, the storage unit 24 stores at least a driving evaluation program 24A for executing the following calculation process.

[0036] The input unit 25 includes a clicking device such as a mouse, a keyboard, a microphone, and a camera, and is used to perform various inputs.

[0037] The display unit 26 is, for example, a liquid crystal display, and displays various types of information. A touch panel may be adopted as the display unit 26, and the touch panel may serve as the input unit 25.

[0038] The communication unit 27 is an interface for communicating with other devices. For communication, for example, a wired communication standard such as Ethernet (registered trademark) or Fiber Distributed Data Interface (FDDI) is used, or a wireless communication standard such as the fourth generation (4G), the fifth generation (5G), or Wi-Fi (registered trademark) is used.

[0039] When executing the above driving evaluation program 24A, the driving evaluation device 20 executes the process based on the above driving evaluation program 24A by using the above hardware resources.

[0040] The functional configuration of the driving evaluation device 20 will be described below. Figure 3 is a block diagram showing an example of the functional configuration of the driving evaluation device 20 according to the present embodiment.

[0041] As Figure 3 shown, the CPU 21 of the driving evaluation device 20 has an acquisition unit 21A, a determination unit 21B, and a calculation unit 21C as functional configurations. When the CPU 21 reads and executes the driving evaluation program 24A stored in the storage unit 24, each functional configuration is realized.

[0042] The acquisition unit 21A acquires at least one of vehicle information related to the vehicle state and driving information related to the driver's driving state. In the present embodiment, as an example, the acquisition unit 21A acquires both vehicle information and driving information. Specifically, the acquisition unit 21A acquires the steering angle, acceleration, and speed of the vehicle 40 detected by a steering angle sensor 51, an acceleration sensor 52, and a vehicle speed sensor 53 included in the vehicle 40 described below, respectively, as the vehicle information. In addition, the acquisition unit 21A acquires an image captured by a camera 55 included in the vehicle 40 described below, as the driving information.

[0043] The determination unit 21B determines whether a predetermined failed operation related to driving has been performed based on at least one of the vehicle information and the driving information acquired by the acquisition unit 21A. As an example, in the present embodiment, a sudden steering operation, a sudden acceleration operation, a sudden braking operation, and a lane departure operation are provided as the failed operations.

[0044] The sudden steering operation is determined based on the information detected by the steering angle sensor 51. As an example, when the amount of change in the steering angle within a predetermined time is equal to or greater than a predetermined value, the determination unit 21B determines that the sudden steering operation has been performed.

[0045] The sudden acceleration operation and the sudden braking operation are determined based on the information detected by the acceleration sensor 52. As an example, when the acceleration detected by the acceleration sensor 52 in a predetermined direction is equal to or greater than a predetermined value, the determination unit 21B determines that the sudden acceleration operation or the sudden braking operation has been performed.

[0046] The lane departure operation is determined based on the image in front of the vehicle captured by the camera 55 described above. As an example, when the position of the vehicle 40 deviates from the image in front of the vehicle captured by the camera 55 by a predetermined amount or more, the determination unit 21B determines that the lane departure operation has been performed.

[0047] The calculation unit 21C calculates a failure operation probability, which is the probability that the failed operation is performed, based on the failed operation determined by the determination unit 21B, and calculates an evaluation value related to the driver's driving using the Z-score of the failure operation probability calculated based on the failure operation probability. The calculation methods of the failure operation probability, the Z-score of the failure operation probability, and the evaluation value performed by the calculation unit 21C will be described later.

[0048] The hardware configuration of the vehicle 40 is described below. Figure 4 It is a block diagram showing the hardware configuration of the vehicle 40.

[0049] As Figure 4As shown, vehicle 40 is configured to include in-vehicle device 15, a plurality of electronic control units (ECUs) 50, steering angle sensor 51, acceleration sensor 52, vehicle speed sensor 53, microphone 54, camera 55, input switch 56, monitor 57, speaker 58, and global positioning system (GPS) device 59.

[0050] In-vehicle device 15 is configured to include CPU 41, ROM 42, RAM 43, storage unit 44, in-vehicle communication interface (I / F) 45, input and output I / F 46, and wireless communication I / F 47. CPU 41, ROM 42, RAM 43, storage unit 44, in-vehicle communication I / F 45, input and output I / F 46, and wireless communication I / F 47 are interconnected via internal bus 48 so as to be able to communicate with each other.

[0051] CPU 41 is a central processing unit that executes various programs and controls various units. That is, CPU 41 reads programs from ROM42 or storage unit 44 and uses RAM 43 as a work area to execute the programs. CPU 41 controls each configuration in the above configuration and performs various arithmetic processes according to the programs recorded in ROM 42 or storage unit 44.

[0052] ROM 42 stores various programs and various data. RAM 43 temporarily stores programs or data as a work area.

[0053] Storage unit 44 is composed of a storage device such as an HDD, SSD, or flash memory, and stores various programs and various data.

[0054] In-vehicle communication I / F 45 is an interface for connecting to ECU 50. For this interface, a communication standard based on the controller area network (CAN) protocol is used. In-vehicle communication I / F 45 is connected to external bus 60.

[0055] ECU 50 is provided for each function of vehicle 40, and in this embodiment, ECU 50A and ECU50B are provided. ECU 50A takes the electric power steering ECU as an example, and steering angle sensor 51 is connected to ECU 50A. In addition, as ECU50B, an ECU for vehicle stability control (VSC) is taken as an example, and acceleration sensor 52 and vehicle speed sensor 53 are connected to ECU 50B. In addition to acceleration sensor 52 and vehicle speed sensor 53, a yaw rate sensor can be connected to ECU 50B.

[0056] Steering angle sensor 51 is a sensor for detecting the steering angle of the steering wheel. The steering angle detected by steering angle sensor 51 is stored in storage unit 44 and transmitted to driving evaluation device 20 as vehicle information.

[0057] The acceleration sensor 52 is a sensor for detecting the acceleration acting on the vehicle 40. The acceleration sensor 52 is, for example, a triaxial acceleration sensor that detects the acceleration applied to the vehicle in the longitudinal direction of the vehicle as the X-axis direction, the vehicle width direction as the Y-axis direction, and the vehicle height direction as the Z-axis direction. The acceleration detected by the acceleration sensor 52 is stored in the storage unit 44 and transmitted to the driving evaluation device 20 as vehicle information.

[0058] The vehicle speed sensor 53 is a sensor for detecting the speed of the vehicle 40. The vehicle speed sensor 53 is, for example, a sensor provided on the wheel. The speed detected by the vehicle speed sensor 53 is stored in the storage unit 44 and transmitted to the driving evaluation device 20 as vehicle information.

[0059] The input and output I / F 46 is an interface for communicating with a microphone 54, a camera 55, an input switch 56, a monitor 57, a speaker 58, and a GPS device 59 mounted on the vehicle 40.

[0060] The microphone 54 is a device provided on the front pillar, dashboard, etc. of the vehicle 40 and collects the voice of the driver of the vehicle 40. The microphone 54 can be provided in the camera 55 described later.

[0061] As an example, the camera 55 is configured to include a charge-coupled device (CCD) image sensor. For example, the camera 55 is provided at the front of the vehicle 40 and captures an image in front of the vehicle. The image captured by the camera 55 is used, for example, to identify the inter-vehicle distance, lane, traffic light, etc. of the vehicle traveling in front. The image captured by the camera 55 is stored in the storage unit 44 and transmitted to the driving evaluation device 20 as driving information. The camera 55 can be configured as an imaging device for other purposes, such as a dash cam. In addition, the camera 55 can be connected to the in-vehicle device 15 via the ECU 50 (for example, the camera ECU).

[0062] The input switch 56 is provided on the dashboard, center console, steering wheel, etc., and is a switch that is operated by the driver's finger input. As the input switch 56, for example, a button-type numeric keypad, a touchpad, etc. can be adopted.

[0063] The monitor 57 is a liquid crystal monitor provided on the dashboard, instrument panel, etc., and is used to display images of operation suggestions and function descriptions related to the functions of the vehicle 40. The monitor 57 can be set to also serve as a touchpad for the input switch 56.

[0064] The speaker 58 is a device provided on the instrument panel, center console, front pillar, dashboard, etc., and is used to output voices of operation suggestions and function descriptions related to the functions of the vehicle 40. The speaker 58 can be provided on the monitor 57.

[0065] The GPS device 59 is a device that measures the current position of the vehicle 40. The GPS device 59 includes an antenna (not shown) that receives signals from GPS satellites. The GPS device 59 can be connected to the in-vehicle device 15 via an automotive navigation system connected to the ECU 50 (for example, a multimedia ECU).

[0066] The wireless communication I / F 47 is a wireless communication module for communicating with the driving evaluation device 20. For the wireless communication module, communication standards such as 5G, Long-Term Evolution (LTE), and Wi-Fi (registered trademark) are used, for example. The wireless communication I / F 47 is connected to the network N.

[0067] Figure 5 is a flowchart showing the flow of a calculation process for calculating an evaluation value related to a driver's driving by the driving evaluation device 20. The calculation process is executed when the CPU 21 reads the driving evaluation program 24A from the storage unit 24, and the calculation process expands the driving evaluation program 24A into the RAM 23 and executes the program. As an example, the case of calculating the evaluation value of the driver i who is the driver of the vehicle 40 will be described below.

[0068] In Figure 5 In the step S10 shown, the CPU 21 acquires vehicle information and driving information from the vehicle 40. Then, the process proceeds to step S11. In the present embodiment, the vehicle information and the driving information are transmitted from the vehicle 40 to the driving evaluation device 20 every 10 minutes.

[0069] In step S11, the CPU 21 determines whether a failure operation has been performed within the past 10 minutes based on at least one of the vehicle information and the driving information acquired in step S10. Then, the process proceeds to step S12.

[0070] In step S12, the CPU 21 calculates a failure operation probability based on the failure operation determined in step S1. The failure operation probability is the probability that a failure operation has been performed from the time when the driver i starts driving the vehicle 40 to the current time. Then, the process proceeds to step S13. As an example, the failure operation probability is a value obtained by dividing the number of failure operations from the time when the vehicle 40 starts being driven to the current time by the time from the time when the vehicle 40 starts being driven to the current time, and multiplying this value by 100 (%).

[0071] In step S13, the CPU 21 calculates the Z-score of the failure operation probability based on the failure operation probability calculated in step S12. Then, the process proceeds to step S14. The Z-score is a score that is transformed so that the average is zero and the standard deviation is one.

[0072] Here, when calculating the nth evaluation value of driver i, the following assumptions are made: It is assumed that the assumed failure operation probability of the failure operation probability of driver i is The average value of the assumed failure operation probabilities of all drivers including driver i is The standard deviation of the assumed failure operation probabilities of all drivers including driver i is If the failure operation probability from when driver i starts driving the vehicle 40 to the current time is T, then the CPU 21 calculates, as the Z-score of driver i, using the following expression (5)

[0073] The assumed failure operation probability is the assumed failure operation probability considering driving environment, human factors, vehicle environment, seasonal fluctuation factors, etc. The driving environment includes, for example, whether the road is a familiar road or a road driven for the first time, the number of vehicles traveling, etc.

[0074] Human factors include, for example, age, number of years of work experience, etc. Vehicle environment includes, for example, whether the driver is familiar with the driving vehicle or is driving the vehicle for the first time. Seasonal fluctuation factors include, for example, climate factors, busy factors, etc.

[0075] Expression 5

[0076]

[0077] In addition, it is assumed that the expected sampling time is The expected cut-off frequency is Then the CPU 21 calculates the variable r using the following expression (6) and calculates, as the assumed failure operation probability of driver i, using the following expression (4) Here, The unit of is seconds.

[0078] Expression 6

[0079]

[0080] Expression 7

[0081]

[0082] In step S14, the CPU 21 calculates the evaluation value of driver i using the Z-score of the failure operation probability calculated in step S13. Then, the process ends.

[0083] Here, the CPU 21 calculates the Score, which is the evaluation value of driver i, using the following expression (8): i , where Zmin indicates the lower limit of the Z-score, Zmax indicates the upper limit of the Z-score, Smin indicates the lower limit of the evaluation value, and Smax indicates the upper limit of the evaluation value. In this embodiment, as an example, Zmin is set to "-3", Zmax is set to "3", Smin is set to "30", and Smax is set to "100".

[0084] Expression 8

[0085]

[0086] Through the above processing, the CPU 21 of the driving evaluation device 20 calculates the evaluation value of each driver every 10 minutes. Then, the CPU 21 stores the calculated evaluation value in the storage unit 24 in a case where the evaluation value for each driver is associated with the date and time at the time of calculating the evaluation value. By performing a predetermined operation on the input unit 25, the evaluation value for each driver stored in the storage unit 24 is displayed on the display unit 26 and can be confirmed by the manager (operation manager) of the business operator.

[0087] Here, when a business operator who operates vehicles, such as a taxi company or a transportation company, calculates the evaluation value of each of multiple drivers, the calculation method must be designed such that the value of a good driver with the number of accidents and the number of near misses less than a predetermined number within a predetermined time is higher than the value of a dangerous driver with the number of accidents and the number of near misses equal to or greater than a predetermined number within a predetermined time. A near miss refers to a dangerous situation close to an accident. Although no accident has occurred, it may directly lead to an accident. "Dangerous situation" is, for example, a situation where the change amount of the steering angle is equal to or greater than a predetermined value within a predetermined time, and a situation where the acceleration is equal to or greater than a predetermined value, that is, a situation where a collision is detected.

[0088] Since both good drivers and dangerous drivers have the possibility of performing failed operations, the following calculation method is not desirable: where the evaluation value is low when the possibility of a driver's failed operation per unit time is exactly high, and the evaluation value is high when the possibility of a driver's failed operation per unit time is exactly low.

[0089] Therefore, in the present embodiment, the CPU 21 acquires at least one of vehicle information and driving information. In addition, the CPU 21 determines whether a failure operation has been performed based on at least one of the acquired vehicle information and driving information. Then, the CPU 21 calculates the failure operation probability based on the determined failure operation and calculates the evaluation value of the driver using the Z-score. As a result, in the driving evaluation device 20 according to the present embodiment, the evaluation value of the driver is calculated using the Z-score, thereby enabling the evaluation of the driver's driving using an index such as a deviation value. Therefore, according to the driving evaluation device 20, when evaluating the driver's driving, the influence of external factors such as the vehicle driving environment and differences between vehicles can be reduced.

[0090] The failure operation probability depends on driving environment, human factors, vehicle environment, seasonal fluctuation factors, etc. As an example, the failure operation probability fluctuates depending on whether the road as the driving environment is a familiar road or a road being driven for the first time, and on the climate factor as the seasonal fluctuation factor, whether the weather is sunny or rainy.

[0091] Therefore, in the present embodiment, the CPU 21 calculates the Z-score of the driver's failure operation probability using the above expression (5) and calculates the evaluation value of the driver using the above expression (8). As a result, with the driving evaluation device 20 according to the present embodiment, even if the failure operation probability of the driver is exactly high or exactly low per unit time, the influence of the failure operation probability on the evaluation value can be reduced by using the assumed failure operation probability in which the failure operation probability is assumed.

[0092] In addition, in the present embodiment, the CPU 21 calculates the variable r using the above expression (6) and calculates the assumed failure operation probability of the driver using the above expression (7). As a result, with the driving evaluation device 20 according to the present embodiment, by adjusting the value of the variable r, the variable component below the desired number of days can be cut off. According to the driving evaluation device 20, a low-pass filter with a cut-off frequency of can be obtained. As an example, according to the driving evaluation device 20, assuming the cut-off frequency is 0.0000116 (Hz), the variable component below one day (86,400 seconds) can be cut off.

[0093] Here, assuming the desired sampling time is 600 (seconds) and the cut-off frequency is 0.0000116 (Hz), the value of the variable r calculated using the above expression (6) is "0.04278". Therefore, assuming the variable r is 0.04278, the above expression (7) is represented by the following expression (9).

[0094] Expression 9:

[0095]

[0096] Other

[0097] In the above embodiment, the failure operation possibility is calculated by using the number of failure operations from the start of driving the vehicle 40 to the current time. However, the calculation method of the failure operation possibility is not limited to this. As an example, weighting can be performed for each type of failure operation, the failure operation score of the failure operations from the start of driving the vehicle 40 to the current time can be calculated, and the calculated failure operation score can be used to calculate the failure operation possibility. In this case, the CPU 21 calculates the failure operation possibility (%) by dividing the failure operation score from the start of driving the vehicle 40 to the current time by the time from the start of driving the vehicle 40 to the current time and multiplying the value by 100. It should be noted that as an alternative to or in addition to performing weighting for each type of failure operation, the above weighting can be performed by using the degree of deviation from a reference value, the driving position where the failure operation is performed, whether the user is in the vehicle, the number of years of work experience of the driver, etc.

[0098] In the above embodiment, sudden steering operations, sudden acceleration operations, sudden braking operations, and lane protrusion operations are assumed to be failure operations. However, the types of failure operations can be more or less. In addition, the number of driving operations determined to be failure operations can vary depending on the age of the driver. As an example, the older the driver, the more driving operations may be determined to be failure operations. Specifically, compared with drivers under 60 years old, drivers over 60 years old may have a larger number of driving operations determined to be failure operations.

[0099] In the above embodiment, the evaluation value for each driver is stored in the storage unit 24 of the driving evaluation device 20, displayed on the display unit 26 by performing a predetermined operation on the input unit 25, and can be confirmed by the operation manager. However, the evaluation value of the driver is not limited to being only confirmable by the operation manager, and can also be confirmed by the driver himself / herself. As an example, when the calculated evaluation value is lower than a predetermined value, the CPU 21 can transmit the evaluation value to a mobile terminal such as a smartphone held by the driver corresponding to the evaluation value and the vehicle driven by the driver.

[0100] When the evaluation value can be confirmed by the driver, in addition to the evaluation value, it is also desirable to transmit advice information that helps improve the evaluation value. A variety of types of advice information are provided and stored in advance in the storage unit 24 of the driving evaluation device 20. The CPU 21 extracts the advice information corresponding to the driver from the storage unit 24 and transmits the advice information together with the evaluation value to the mobile terminal held by the driver and the vehicle driven by the driver.

[0101] In addition, when the evaluation value can be confirmed by the driver, it is desirable for the operation manager to confirm whether the driver has confirmed the advice information. As an example, the following configuration can be adopted: when the driver displays the advice information transmitted from the driving evaluation device 20 on the mobile terminal or the vehicle, a confirmation notice indicating that the advice information has been confirmed is transmitted from the mobile terminal or the vehicle to the driving evaluation device 20.

[0102] In addition, when the driving evaluation device 20 does not receive the above confirmation notice for a predetermined time or longer, the driving evaluation device 20 can transmit a reminder notice urging the confirmation of the advice information to the mobile terminal held by the driver and the vehicle driven by the driver.

[0103] It should be noted that various processors other than the CPU can also execute the calculation processing performed when the CPU 21 reads software (program) in the above embodiments. Examples of such processors include programmable logic devices (PLDs), such as field programmable gate arrays (FPGAs) whose circuit configuration can be changed after production; and dedicated circuits such as application specific integrated circuits (ASICs), which are processors having a circuit configuration specifically designed to execute specific processing. The calculation processing can be executed by one of these different processors, or by a combination of two or more processors of the same type or different types (for example, a combination of FPGAs, a combination of a CPU and an FPGA, etc.). Furthermore, more specifically, the hardware structure of these different processors is a circuit in which circuit elements such as semiconductor elements are combined.

[0104] In addition, in the above embodiments, the mode of pre-storing (installing) the driving evaluation program 24A in the storage unit 24 has been described, but the present invention is not limited thereto. The driving evaluation program 24A can be recorded on a record medium to be provided, such as a compact disc read only memory (CD-ROM), a digital versatile disc read only memory (DVD-ROM), and a universal serial bus (USB) memory. In addition, the driving evaluation program 24A can be downloaded from an external device via the network N.

Claims

1. A driving assessment device, comprising: An acquisition unit that acquires at least one of vehicle information related to a vehicle state and driving information related to a driver's driving state; A determination unit that determines whether a predetermined failed operation related to driving has been performed based on at least one of the vehicle information and the driving information acquired by the acquisition unit; And A calculation unit that calculates a failure operation probability as a probability that the failed operation has been performed based on the failed operation determined by the determination unit, and calculates an evaluation value related to the driver's driving using a Z-score of the failure operation probability calculated based on the failure operation probability, When calculating the nth evaluation value of driver i, who is a member of the driver, the following assumptions are made: It is assumed that the assumed failure operation probability of driver i is The average value of the assumed failure operation probabilities of all drivers including driver i is The standard deviation of the assumed failure operation probabilities of all drivers including driver i is If the failure operation probability from the start of driving the vehicle by driver i to the current time is T, then the calculation unit Calculate, using the following expression (1), the and Calculate Score, which is the evaluation value of the driver i, using the following expression (2): i , where Zmin indicates the lower limit of the Z-score, Zmax indicates the upper limit of the Z-score, Smin indicates the lower limit of the evaluation value, and Smax indicates the upper limit of the evaluation value: Expression 1 Expression 2 wherein, it is assumed that the desired sampling time is and the desired cut-off frequency is then the calculation unit calculates a variable r using the following expression (3) and calculates the likelihood of the hypothesized failure operation of the driver i using the following expression (4) Expression 3 Expression 4 2. A driving assessment method, comprising: Acquire at least one of vehicle information related to a vehicle state and driving information related to a driver's driving state; Determine whether a predetermined failed operation related to driving has been performed based on at least one of the acquired vehicle information and the driving information; And Calculate a failure operation probability as a probability that the failed operation has been performed based on the determined failed operation, and calculate an evaluation value related to the driver's driving using a Z-score of the failure operation probability calculated based on the failure operation probability, When calculating the nth evaluation value of driver i, who is a member of the driver, the following assumptions are made: The assumed failure operation probability of driver i's failure operation probability is The average value of the assumed failure operation probabilities of all drivers including driver i is The standard deviation of the assumed failure operation probabilities of all drivers including driver i is If the failure operation probability from when driver i starts driving the vehicle to the current time is T, then Calculate, using the following expression (1), the and Calculate Score, which is the evaluation value of the driver i, using the following expression (2). i , where Zmin indicates the lower limit of the Z-score, Zmax indicates the upper limit of the Z-score, Smin indicates the lower limit of the evaluation value, and Smax indicates the upper limit of the evaluation value: Expression 1 Expression 2 wherein, it is assumed that the desired sampling time is and the desired cut-off frequency is then the variable r is calculated using the following expression (3), and the likelihood of the hypothesized failure operation of the driver i is calculated using the following expression (4) Expression 3 Expression 4

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