Driving evaluation apparatus and driving evaluation method

Abstract

To provide a driving evaluation apparatus for appropriately evaluating the driving skill of a driver.SOLUTION: A driving evaluation apparatus includes: an error information generation section 12 that generates steering error information, which is information on an error of an actual measured value with respect to a predicted value of steering for each of a target vehicle and other vehicles on an evaluation target road, on the basis of traveling information of a plurality of vehicles acquired by an information acquisition section 11; and a driving evaluation section 13 that evaluates a driving skill of a driver of the target vehicle in a drying period according to a first criterion on the basis of the steering error information of the other vehicles and the target vehicle in the drying period, and evaluates the driving skill of the driver of the target vehicle in an ice and snow period according to a second criterion looser than the first criterion on the basis of the steering error information of the other vehicles in the drying period and the steering error information of the target vehicle in the ice and snow period.SELECTED DRAWING: Figure 4

Description

Technical Field

[0001] The present invention relates to a driving evaluation device and a driving evaluation method for evaluating a driver's driving skill.

Background Art

[0002] Conventionally, as this type of device, there is known a device that determines the excellence of a driver based on information from a G-sensor mounted on a vehicle and generates insurance information regarding the driver's insurance contents according to the excellence (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the configuration of the device described in Patent Document 1 above, the excellence of a driver who frequently drives on a road surface that has an adverse effect on driving operations is likely to be low. If such excellence is used, it is difficult to appropriately evaluate the driver's driving skill.

Means for Solving the Problems

[0005] An operation evaluation device according to an aspect of the present invention includes travel information of an evaluation target vehicle and a comparison target vehicle associated with time information, the travel information including position information of the evaluation target vehicle and the comparison target vehicle and steering information which is operation information of the steering, and road map information; an information acquisition unit that acquires the travel information and the road map information; an error information generation unit that generates steering error information which is information on an error between an actual measurement value and a predicted value of steering for each of the evaluation target vehicle and the comparison target vehicle on an evaluation target road specified by the road map information based on the travel information acquired by the information acquisition unit; a driving skill evaluation unit that evaluates the driving skill of the driver of the evaluation target vehicle in a first period according to a first criterion based on the steering error information of the comparison target vehicle in the first period generated by the error information generation unit and the steering error information of the evaluation target vehicle in the first period, and evaluates the driving skill of the driver of the evaluation target vehicle in a second period according to a second criterion based on the steering error information of the comparison target vehicle in the first period generated by the error information generation unit and the steering error information of the evaluation target vehicle in a second period different from the first period. The degree of error in the second period is greater than the degree of error in the first period. When defining the steering error determined by the steering error information of the comparison target vehicle in the first period as a reference value and the steering error determined by the steering error information of the evaluation target vehicle as an evaluation target value, the second criterion is determined so as to increase a threshold for reducing the driving skill of the driver as compared with the difference between the reference value and the evaluation target value, or to correct the difference between the reference value and the evaluation target value to be smaller than that of the first criterion.

[0006] Another aspect of the present invention, the driving evaluation method, includes steps of: acquiring driving information of an evaluation target vehicle and a comparison target vehicle associated with time information, the driving information including position information of the evaluation target vehicle and the comparison target vehicle and steering information which is operation information of steering; acquiring road map information; generating steering error information which is information of an error between an actual measurement value and a predicted value of steering for each of the evaluation target vehicle and the comparison target vehicle on an evaluation target road specified by the road map information based on the acquired driving information; evaluating the driving skill of the driver of the evaluation target vehicle in a first period according to a first criterion based on the steering error information of the comparison target vehicle in the first period and the steering error information of the evaluation target vehicle in the first period, and evaluating the driving skill of the driver of the evaluation target vehicle in a second period according to a second criterion based on the steering error information of the comparison target vehicle in the first period and the steering error information of the evaluation target vehicle in a second period different from the first period; and executing the steps by a computer. The degree of error in the second period is larger than the degree of error in the first period. When defining the steering error determined by the steering error information of the comparison target vehicle in the first period as a reference value and the steering error determined by the steering error information of the evaluation target vehicle as an evaluation target value, the second criterion is determined such that the threshold for reducing the driving skill of the driver is larger when comparing the difference between the reference value and the evaluation target value than the first criterion, or such that the difference between the reference value and the evaluation target value is corrected to be smaller.

Advantages of the Invention

[0007] According to the present invention, it is possible to appropriately evaluate the driving skill even for a driver who frequently drives on a road surface that has an adverse effect on driving operations.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2A

Figure 2B

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9A

Figure 9B

Mode for Carrying Out the Invention

[0009] Hereinafter, embodiments of the present invention will be described with reference to FIGS. 1 to 9B. The driving evaluation device according to the embodiment of the present invention is configured to evaluate the driving skill of a driver (referred to as a target driver) of a target vehicle (evaluation target vehicle) based on steering information, which is operation information of the steering. When evaluating the driving skill, when the target vehicle travels on a road with a predetermined road surface condition such as an icy or snowy road, the steering of the target driver tends to become unstable, which may adversely affect the evaluation of the driving skill of the target driver. In the present embodiment, paying attention to this point, the driving evaluation device is configured so that the driving skill of the target driver can be appropriately evaluated in such a situation.

[0010] FIG. 1 is a diagram schematically showing the overall configuration of a driving evaluation system 1 including a driving evaluation device according to an embodiment of the present invention. As shown in FIG. 1, the driving evaluation system 1 includes a server device 10 that functions as a driving evaluation device and a plurality of in-vehicle devices 30 mounted on a plurality of vehicles 20. The server device 10 and the plurality of in-vehicle devices 30 can communicate with each other via a network 2.

[0011] The network 2 includes not only a public wireless communication network typified by the Internet or a mobile phone network but also a closed communication network provided for each predetermined management area, such as a wireless LAN, Wi-Fi (registered trademark), Bluetooth (registered trademark), etc. The server device 10 is configured, for example, as a single server or as a distributed server composed of separate servers for each function. The server device 10 can also be configured as a distributed virtual server created in a cloud environment called a cloud server.

[0012] The plurality of vehicles 20 include a target vehicle 20A driven by a target driver who is the subject of driving evaluation and other vehicles 20B and 20C driven by other drivers. The other vehicles 20B and 20C are vehicles (comparison target vehicles) that are comparison targets for the target vehicle 20A. The number of comparison target vehicles is not limited to two, and may be one or three or more.

[0013] Each vehicle 20 is assigned a unique identification ID (vehicle ID), and the vehicle type and vehicle class can be specified using the vehicle ID. The target vehicle 20A and the other vehicles 20B and 20C may have the same or different vehicle types and vehicle classes. A unique identification ID (user ID) of the driver is associated with the vehicle ID, and the driver of the vehicle 20 can be specified using the user ID.

[0014] Figure 2A is a diagram showing the relationship between the target vehicle 20A and other vehicles 20B and 20C. As shown in Figure 2A, when the horizontal axis is the time axis, the target vehicle 20A travels on a specific road within a predetermined area AR1, that is, the road RD1 (referred to as the evaluation target road) that is the target of driving skill evaluation, at time ta within a predetermined period ΔTa. The other vehicles 20B and 20C travel on the same evaluation target road RD1 at times tb and tc within a predetermined period ΔTb that is earlier than the predetermined period ΔTa. Hereinafter, for convenience, the predetermined period ΔTa may be referred to as the target period, and the predetermined period ΔTb may be referred to as the comparison period.

[0015] The target period ΔTa is the period from time t1 to time t2, and the comparison period ΔTb is the period from time t3 to time t4. In Figure 2A, time t4 is earlier than time t1, and there is another period between the target period ΔTa and the comparison period ΔTb. The relationship between time t1 and time t4 is not limited to this, and time t1 may be the same as time t4. That is, the target period ΔTa and the comparison period ΔTb may be continuous. The target period ΔTa may be longer or shorter than the comparison period ΔTb. The target period ΔTa and the comparison period ΔTb may be of the same length.

[0016] The target period ΔTa and the comparison period ΔTb are determined according to the road surface condition of the evaluation target road RD1 within the predetermined area AR1. The target period ΔTa is the period during which the predetermined road surface condition of the evaluation target road RD1 is maintained. For example, the target period ΔTa is the period during which snow accumulation or freezing occurs on the evaluation target road RD1 and the evaluation target road RD1 becomes an icy and snowy road (snowy road, frozen road), that is, the icy and snowy period. The icy and snowy road is a type of non-dry road, and compared with a dry road, the friction coefficient of the road surface is small. In addition, since snow accumulates on the road surface, the degree of unevenness of the road surface is large. Therefore, the driver's steering operation (steering) is likely to become unstable. Thus, the period during which the steering is likely to become unstable due to the influence of the road surface can be set as the target period ΔTa.

[0017] The length of such a target period ΔTa varies by region. That is, when a predetermined area AR1 is included in a region with a short snow accumulation period, the target period ΔTa is short, for example, about 1 to 2 months. On the other hand, when a predetermined area AR1 is included in a region with a long snow accumulation period, the target period ΔTa is long, for example, about 4 to 6 months.

[0018] The comparison period ΔTb is a period during which a stable steering can be achieved. For example, if the remaining period of a year excluding the ice and snow period is a period when there is no ice and snow and the road surface is dry, this dry period can be set as the comparison period ΔTb. Among the remaining period of a year excluding the ice and snow period, a specific period when the road surface is further dry may also be set as the comparison period ΔTb.

[0019] The target period ΔTa is a period for evaluating the driving skills of the target driver and may be outside the ice and snow period. For example, as shown in FIG. 2B, the target period ΔTa may be included in the comparison period ΔTb. That is, the target period ΔTa may be a dry period. The target period ΔTa and the comparison period ΔTb may be the same. The target period ΔTa and the comparison period ΔTb in FIGS. 2A and 2B may be set in units of months, weeks, days, or hours.

[0020] The predetermined area AR1 is an area including points where the target periods ΔTa and the comparison periods ΔTb for each other are the same. Specifically, the predetermined area AR1 is an area including points where the weather for each other is the same, and for example, it is an area divided as an administrative district such as a municipality or a prefecture. The predetermined area AR1 may be wider or narrower than the administrative district. For example, when the evaluation target road RD1 extends from town A adjacent to each other to town B, the two administrative districts (town A and town B) may be included in the predetermined area AR1.

[0021] The road to be evaluated RD1 is a road with the same road name, such as Route 〇〇 of the national highway or Route 〇〇 of the prefectural road. The area including this road to be evaluated RD1 may be set as a predetermined area AR1. It may be configured such that from the starting point to the ending point of the road with the same road name is included within the same predetermined area AR1. A part of the road with the same road name may be included in the predetermined area AR1. That is, the predetermined area AR1 may be set in units of roads.

[0022] The configurations of the in-vehicle device 30 of the target vehicle 20A in FIG. 1 and the in-vehicle devices 30 of other vehicles 20B and 20C are the same as each other. FIG. 3 is a block diagram showing the schematic configuration of the in-vehicle device 30. As shown in FIG. 3, the in-vehicle device 30 includes a positioning sensor 31, a sensor group 32, a communication unit 33, and a controller 35. The positioning sensor 31, the sensor group 32, and the communication unit 33 are each communicably connected to the controller 35.

[0023] The positioning sensor 31 receives a positioning signal transmitted from a positioning satellite. The positioning satellite is an artificial satellite such as a GPS satellite or a quasi-zenith satellite, and the current position (latitude, longitude, altitude) of the vehicle 20 can be detected using the positioning information from the positioning satellite received by the positioning sensor 31. Therefore, the positioning sensor 31 functions as a position detection unit that detects the position of the vehicle 20.

[0024] The sensor group 32 is a general term for a plurality of sensors that detect the driving state of the vehicle 20. The sensor group 32 includes a steering angle sensor 321 that detects the steering angle of the steering wheel. Although not shown, a vehicle speed sensor, an acceleration sensor, a wheel speed sensor, etc. are also included in the sensor group 32.

[0025] The controller 35 is an electronic control unit configured to include a computer having a CUP, a ROM, a RAM, and other peripheral circuits. The controller 35 reads signals from the positioning sensor 31 and the sensor group 32 at a predetermined period. The controller 35 associates time information with the position data of the vehicle 20 detected by the positioning sensor 31 to generate position information of the vehicle 20. The controller 35 associates time information with the data of the steering angle detected by the steering angle sensor 321 to generate steering angle information. The position information and the steering angle information can be stored in the storage unit of the controller 35.

[0026] The communication unit 33 communicates with the server device 10 via the network 200 according to a command from the controller 35. Thereby, the time-series position information and steering angle information of the vehicle 20 can be transmitted to the server device 10 with a vehicle ID attached. The communication unit 33 transmits driving information including the position information and steering angle information of the vehicle 20 at a predetermined period during the driving of the vehicle 20. The communication unit 33 may transmit driving information including the position information and steering angle information of the vehicle 20 at a predetermined timing according to a request from the server device 10.

[0027] FIG. 4 is a block diagram showing the configuration of the server device 10. As shown in FIG. 4, the server device 10 includes an ECU having an arithmetic unit 10A such as a CPU, a storage unit 10B such as a ROM and a RAM, and other peripheral circuits (not shown) such as an I / O interface, and a communication unit 15. The communication unit 15 communicates with the in-vehicle device 30 via the network 2. The in-vehicle devices 30 with which the communication unit 15 communicates include not only the in-vehicle devices 30 of the vehicles 20 (target vehicle 20A, other vehicles 20B, 20C) within the predetermined area AR1 but also the in-vehicle devices 30 of the vehicles 20 outside the predetermined area AR1. The communication unit 15 can also communicate with the server device of an insurance company operating a vehicle insurance business via the network 2.

[0028] Running information is transmitted from in - vehicle devices 30 of a plurality of vehicles 20 inside and outside a predetermined area AR1 to the server device 10 via the network 2. This running information is stored in the storage unit 10B together with the vehicle ID. Further, the storage unit 10B stores road map information, user information, various programs executed by the arithmetic unit 10A, threshold values used in the arithmetic operations of the arithmetic unit 10A, etc. The storage unit 10B can also store a target period ΔTa for evaluating driving skills. This target period ΔTa can be changed by an external command.

[0029] The road map information includes information on the evaluation target road RD1 (information such as the position, name, road width, traffic volume of the road) and information on a predetermined area AR1 (Figs. 2A, 2B) to which the evaluation target road RD1 belongs. The user information is information on the driver including the user ID associated with the vehicle ID. The user information includes the user's address, name, and in addition, contract information of the automobile insurance the user subscribes to.

[0030] Instead of storing all the above - mentioned information in the storage unit 10B of the server device 10, some of the information may be stored in the storage unit of another device provided to be communicable with the server device 10. For example, at least one of the running information of the plurality of vehicles 20 and the road map information may be stored in a device different from the server device 10.

[0031] By executing the program stored in the storage unit 10B, the arithmetic unit 10A functions as an information acquisition unit 11, an error information generation unit 12, a driving evaluation unit 13, and an information output unit 14.

[0032] The information acquisition unit 11 acquires predetermined driving information necessary for calculating the driving skill of the target driver from among the driving information of a plurality of vehicles 20 stored in the storage unit 10B. Specifically, the information acquisition unit 11 first acquires driving information including the time-series position information and steering information of the target vehicle 20A. The acquired driving information includes the driving information within the target period ΔTa in FIGS. 2A and 2B. Further, the information acquisition unit 11 acquires road map information, and based on the road map information and the position information of the target vehicle 20A, identifies the road (evaluation target road RD1) on which the target vehicle 20A traveled during the target period ΔTa.

[0033] Then, the information acquisition unit 11 acquires the driving information of other vehicles 20B and 20C that traveled on the evaluation target road RD1 during the comparison period ΔTb from among the driving information of a plurality of vehicles 20 stored in the storage unit 10B. The comparison period ΔTb is, for example, a dry period when the road surface is a dry road (non-ice and snow road). On the other hand, the target period ΔTa is an ice and snow period or a dry period when the road surface is an ice and snow road.

[0034] The error information generation unit 12 generates steering error information on the evaluation target road RD1 based on the driving information (steering information) of the vehicle 20 acquired by the information acquisition unit 11. The steering error information is information on the error between the measured value of the steering angle of the vehicle 20 and the predicted value of the steering angle of the vehicle 20 on the evaluation target road RD1. Such an error may be referred to as a prediction error of the steering angle.

[0035] FIG. 5 is a diagram for explaining the prediction error of the steering angle. In the figure, θ(n) is the steering angle (measured steering angle) included in the steering angle information acquired at a predetermined time interval by the information acquisition unit 11 at time point n (for example, time point ta in FIG. 2A). On the other hand, θp(n) is the steering angle (predicted steering angle) calculated based on the steering angle information at reference time points n-1, n-2, and n-3 before time point n. The predicted steering angle θp(n) can be calculated, for example, by a second-order Taylor expansion centered on time point n-1 using the steering angles of the past three points. The difference between the measured steering angle θ(n) and the predicted steering angle θp(n) is the prediction error e(n). The prediction error e(n) is a physical quantity representing the complexity of the steering operation.

[0036] FIG. 6 is a diagram showing an example of a histogram indicating the distribution of the magnitudes of prediction errors e(n) obtained from a plurality of vehicles 20 traveling on the same evaluation target road RD1. In FIG. 6, the prediction errors e(n) obtained from the steering angle information of the plurality of vehicles 20 during a period when the road surface is in a dry state (dry period) and the prediction errors e(n) obtained from the steering angle information of the plurality of vehicles 20 during a period when the road surface is in an ice and snow state (ice and snow period) are shown in different patterns from each other.

[0037] The coefficient of friction of the road surface of an ice and snow road is smaller and the degree of unevenness of the road surface is larger than that of a dry road. Therefore, steering tends to become unstable on an ice and snow road. Accordingly, when the prediction error corresponding to the peak frequency is defined as the mode value, as shown in FIG. 6, the mode value es of the prediction error during the ice and snow period is larger than the mode value ed of the prediction error during the dry period. Also, when the value obtained by dividing the total sum of the prediction error data by the number of data is defined as the average value, the average value of the prediction error during the ice and snow period is larger than the average value of the prediction error during the dry period. Further, when the middle value when the entire data is arranged in order is defined as the median value, the median value of the prediction error during the ice and snow period is larger than the median value of the prediction error during the dry period. Such mode values es, ed, average value, and median value are representative values representing the data of the prediction error e(n).

[0038] The error information generation unit 12 sets the dry period as the comparison period ΔTb. Then, based on a histogram indicating the distribution of the magnitudes of the prediction errors e(n) obtained from the driving information of a plurality of vehicles 20 (for example, a plurality of vehicles 20 excluding the target vehicle 20A) that have traveled on the same evaluation target road RD1 within the comparison period ΔTb, a reference error value α0 representing the prediction error data of the comparison period ΔTb is calculated. For the reference error value α0, for example, the mode value ed in FIG. 6 corresponding to the peak frequency of the histogram is used. Other representative values (average value, median value) of the histogram may be used for the reference error value α0.

[0039] Furthermore, the error information generation unit 12 calculates a target error value α1 representing the data of the prediction error e(n) for the target period ΔTa based on a histogram showing the distribution of the magnitudes of the prediction errors e(n) obtained from the driving information of the target vehicle 20A that traveled on the road to be evaluated RD1 within the target period ΔTa (during the drying period or the ice and snow period). As the target error value α1, a representative value of the same type as the reference error value α0 obtained from the histogram (for example, the mode corresponding to the peak frequency) is used.

[0040] The driving evaluation unit 13 calculates a prediction difference Δα (=α1 - α0), which is the difference between the reference error value α0 within the comparison period ΔTb calculated by the error information generation unit 12 and the target error value α1 within the target period ΔTa, and evaluates the driving skill of the target driver based on the prediction difference Δα. More specifically, the driving evaluation unit 13 first sets a threshold β used for evaluating the driving skill according to the target period ΔTa. Specifically, when the target period ΔTa is the ice and snow period, a threshold βs is set, and when the target period ΔTa is the drying period, a threshold βd is set. The threshold βs is set to a value larger than the threshold βd.

[0041] Next, the driving evaluation unit 13 determines whether the prediction difference Δα is greater than the threshold β using the threshold β corresponding to the target period ΔTa. That is, when the target period ΔTa is the ice and snow period, it is determined whether the prediction difference Δα is greater than the threshold βs, and when the target period ΔTa is the drying period, it is determined whether the prediction difference Δα is greater than the threshold βd. When the prediction difference Δα is greater than the threshold β, the driving evaluation unit 13 lowers the evaluation value of the driving skill of the target driver. For example, when the evaluation value of the driving skill is set in three levels: A, B, and C, when the prediction difference Δα is greater than the threshold β, the evaluation value of the driving skill of the target driver is lowered by one level from A to B. When the prediction difference Δα is greater than the threshold β by a predetermined value or more, the evaluation value of the driving skill may be lowered by two levels from A to C.

[0042] On the one hand, when the prediction difference Δα is less than or equal to the threshold value β, the driving evaluation unit 13 maintains the evaluation value of the driving skill of the target driver. When the target error value α1 is smaller than the reference error value α0 and the prediction difference Δα is a negative value, the driving evaluation unit 13 may increase the evaluation value of the driving skill of the target driver (for example, increase it by one or two levels).

[0043] The information output unit 14 outputs the evaluation value of the driving skill of the target driver obtained by the driving evaluation unit 13. The output evaluation value is transmitted to the server device of the insurance company that operates the vehicle insurance business via the communication unit 15. The insurance company determines the insurance premium of the target driver based on the transmitted evaluation value.

[0044] FIG. 7 is a flowchart showing an example of the processing executed by the arithmetic unit 10A of the server device 10 according to the program stored in the storage unit 10B in advance. The processing shown in this flowchart is executed every time the target period ΔTa (ice and snow period or dry period) ends in order to evaluate the driving skill of the target driver in the most recent target period ΔTa, for example.

[0045] First, in step S1, information stored in the storage unit 10B, that is, the driving information of a plurality of vehicles 20 including the target vehicle 20A associated with time information and the road map information are acquired. Next, in step S2, based on the driving information of the evaluation target road RD1 within the predetermined area AR1 among the acquired driving information, the steering error information for the target vehicle 20A and the steering error information for a plurality of vehicles 20 excluding the target vehicle 20A are generated. The steering error information for the target vehicle 20A is information on the prediction error e(n) of the steering angle obtained from the steering angle information of the target vehicle 20A when the target vehicle 20A travels on the evaluation target road RD1 within the target period ΔTa (information on the histogram of the prediction error). The steering error information for a plurality of vehicles 20 excluding the target vehicle 20A is information on the prediction error e(n) of the steering angle obtained from the steering angle information of other vehicles 20B, 20C when other vehicles 20B, 20C travel on the same evaluation target road RD1 within the comparison period ΔTb (information on the histogram of the prediction error as shown in FIG. 6).

[0046] Next, in step S3, based on the steering error information for the plurality of vehicles 20 generated in step S2, a reference error value α0, which is a representative value of the data of the prediction error e(n) of the plurality of vehicles 20 in the comparison period ΔTb, is calculated. For example, the mode value ed in FIG. 6 is calculated as the reference error value α0. Next, in step S4, based on the steering error information for the target vehicle 20A generated in step S2, a target error value α1, which is a representative value (a representative value of the same type as the reference error value α0) of the data of the prediction error e(n) of the target vehicle 20A in the target period ΔTa, is calculated. Next, in step S5, the reference error value α0 is subtracted from the target error value α1 to calculate a prediction difference Δα.

[0047] Next, in step S6, based on the time information included in the driving information of the target vehicle 20A, it is determined whether the most recent target period ΔTa is a snow and ice period. If it is affirmed in step S6, the process proceeds to step S7, and it is determined whether the prediction difference Δα is greater than a threshold value βs corresponding to the pre-stored snow and ice period. On the other hand, if the target period ΔTa is a dry period, it is negated in step S6. In this case, the process proceeds to step S8, and it is determined whether the prediction difference Δα is greater than a threshold value βd corresponding to the pre-stored dry period.

[0048] If it is affirmed in step S7 or affirmed in step S8, the process proceeds to step S9. In step S9, the evaluation value of the driving skill of the target driver is decreased. For example, the evaluation value is uniformly decreased by one level. Note that instead of uniformly decreasing the evaluation value by one level, it may be determined how much to decrease according to the difference between the prediction difference Δα and the threshold values βs, βd. If it is negated in step S7 or negated in step S8, step S9 is skipped and the process proceeds to step S10. In this case, the evaluation value of the driving skill of the target driver is maintained. Depending on the magnitude of the prediction difference Δα (for example, when the prediction difference Δα is a negative value), the evaluation value may be increased.

[0049] In step S10, the evaluation value of the driving skill of the target driver calculated is output to the outside. Specifically, the evaluation value is transmitted to the server device of the insurance company via the communication unit 15. The server device of the insurance company as the transmission destination can be specified based on the user information of the target driver stored in the storage unit 10B. The insurance company determines the insurance premium of the target driver using the transmitted evaluation value.

[0050] Summarizing the operation of the driving evaluation device according to this embodiment, it is as follows. When the target vehicle 20A travels on the evaluation target road RD1 during the dry period, the driving skill of the target driver is evaluated based on the steering information included in the driving information of other vehicles 20B and 20C that have traveled on the evaluation target road RD1 during the dry period. More specifically, based on the histogram of the prediction error e(n) (Fig. 6) obtained from the steering information of other vehicles 20B and 20C during the dry period, a reference error value α0 (for example, the mode value ed), which is a representative value of the prediction error e(n), is calculated (step S3). Furthermore, based on the histogram of the prediction error e(n) obtained from the steering information of the target vehicle 20A during the dry period, a target error value α1 is calculated (step S4).

[0051] In this case, as shown in Fig. 7, the reference error value α0 (= ed) is small, but since the target vehicle 20A travels on a dry road, the target error value α1 also tends to be small. At this time, as shown in Example 1 of Fig. 8, if the prediction difference Δα1 during the dry period is equal to or less than the threshold value βd, the evaluation value is maintained (step S8 → step S10). On the other hand, as shown in Example 2 of Fig. 8, if the prediction difference Δα2 is greater than the threshold value βd, the evaluation value is decreased (step S8 → step S9 → step S10). For example, the evaluation value is decreased by one level. The greater the difference Δα10 between the prediction difference Δα2 and the threshold value βd, the more the evaluation value may be decreased significantly.

[0052] Even when the target vehicle 20A travels on the evaluation target road RD1 during the ice and snow period, the driving skill of the target driver is evaluated based on the steering information included in the driving information of other vehicles 20B and 20C that have traveled on the evaluation target road RD1 during the dry period. More specifically, based on the histogram of the prediction error e(n) (Figure 6) obtained from the steering information of other vehicles 20B and 20C during the dry period, a reference error value α0 (for example, the mode value ed) that is a representative value of the prediction error e(n) is calculated (step S3). Further, based on the histogram of the prediction error e(n) obtained from the steering information of the target vehicle 20A during the ice and snow period, a target error value α1 is calculated (step S4).

[0053] In this case, since the target vehicle 20A travels on an ice and snow road, the target error value α1 is likely to be large, and thus the prediction difference Δα is also likely to be large. At this time, as shown in Example 3 of Figure 8, if the prediction difference Δα2 during the ice and snow period is equal to or less than the threshold value βs, the evaluation value is maintained (step S7 → step S10). On the other hand, as shown in Example 4 of Figure 8, if the prediction difference Δα4 is greater than the threshold value βs, the evaluation value is decreased (step S7 → step S9 → step S10). For example, the evaluation value is decreased by one level. The greater the difference Δα20 between the prediction difference Δα4 and the threshold value βs, the more the evaluation value may be decreased significantly.

[0054] On an ice and snow road, the driver's steering becomes unstable, so the prediction difference Δα is likely to be large. If, without considering this point, a common threshold value β (for example, βd) is used for both the case where the target period ΔTa is the dry period and the case where it is the ice and snow period (first criterion), in Example 3 of Figure 8, the prediction difference Δα will be greater than the threshold value β. As a result, the evaluation value of the driver's driving skill will be decreased, which is harsh on the driver. In this regard, as in this embodiment, when the target period ΔTa is the ice and snow period, if a threshold value βs greater than the threshold value βd is used (second criterion), the prediction difference Δα3 does not exceed the threshold value β, and the driving skill of the target driver can be appropriately evaluated.

[0055] According to this embodiment, the following operational effects can be achieved. (1) The driving evaluation device is driving information of vehicles 20 including a target vehicle 20A associated with time information and other vehicles 20B and 20C, the driving information including position information of the target vehicle 20A and the other vehicles 20B and 20C and steering information which is operation information of the steering, and road map information. An information acquisition unit 11 acquires the driving information and the road map information. Based on the driving information acquired by the information acquisition unit 11, an error information generation unit 12 generates steering error information which is information on an error (prediction error e(n)) between an actual measurement value and a predicted value of steering for each of the target vehicle 20A and the other vehicles 20B and 20C on an evaluation target road RD1 specified by the road map information. Based on the steering error information of the other vehicles 20B and 20C in a comparison period ΔTb (dry period) generated by the error information generation unit 12 and the steering error information of the target vehicle 20A in a target period ΔTa (dry period) the same as the comparison period ΔTb, a driving evaluation unit 13 evaluates the driving skill of the driver of the target vehicle 20A in the target period ΔTa according to a first criterion. On the other hand, based on the steering error information of the other vehicles 20B and 20C in a comparison period ΔTb (dry period) generated by the error information generation unit 12 and the steering error information of the target vehicle 20A in a target period ΔTa (icy and snowy period) different from the comparison period ΔTb, the driving evaluation unit 13 evaluates the driving skill of the driver of the target vehicle 20A in the target period ΔTa according to a second criterion (Figs. 2A, 2B, 4). A representative value (for example, the mode value es) of a histogram representing the degree of the prediction error e(n) of steering in the icy and snowy period is larger than a representative value (mode value ed) of a histogram representing the degree of the prediction error e(n) in the dry period (Fig. 6). The second criterion is determined so as to suppress a decrease in the driving skill of the driver more than the first criterion. Specifically, when a steering error determined by the steering error information of the other vehicles 20B and 20C in the comparison period ΔTb (dry period) is defined as a reference error value α0 and a steering error determined by the steering error information of the target vehicle 20A is defined as a target error value α1, the second criterion is determined so as to increase a threshold value β for reducing the driving skill of the driver as compared with a difference (prediction difference Δα) between the reference error value α0 and the target error value α1 more than the first criterion (βs > βd) (Fig. 8).

[0056] As a result, it is possible to appropriately evaluate the driving skills even for a target driver who frequently drives on a road surface that has an adverse effect on driving operations, that is, a road surface such as an icy or snowy road surface. That is, since steering is likely to become unstable during the ice and snow period, the target error value α1 of the target driver during the ice and snow period is likely to increase. If the driving skills of the target driver are evaluated without considering this point, the driving skills of the target driver who drives during the ice and snow period will be evaluated as low, which is harsh on the target driver. In this regard, in the present embodiment, when evaluating the driving skills of the target driver during the ice and snow period, a looser criterion (second criterion) is used to suppress a decrease in the driving skills of the target driver compared to when evaluating the driving skills of the target driver during the dry period. Therefore, it is possible to appropriately evaluate the driving skills of the target driver during the ice and snow period.

[0057] (2) When the target error value α1 determined by the steering error information of the target vehicle 20A in the target period ΔTa when the target period ΔTa is a dry period is larger than the reference error value α0 determined by the steering error information of the other vehicles 20B and 20C in the comparison period ΔTb (dry period), and the difference (predicted difference Δα) between the target error value α1 and the reference error value α0 is larger than the threshold value βd, and when the target error value α1 determined by the steering error information of the target vehicle 20A in the target period ΔTa when the target period ΔTa is an ice and snow period is larger than the reference error value α0, and the difference (predicted difference Δα) between the target error value α1 and the reference error value α0 is larger than the threshold value βs (>βd), the degree of the driving skills of the driver of the target vehicle 20A is reduced (FIGS. 7 and 8). For example, when the driving skills are evaluated in three levels of A, B, and C, it is reduced from A to B or from A to C. By setting the threshold value βs used in the second criterion to a value larger than the threshold value βd used in the first criterion in this way, the second criterion is determined to suppress a decrease in the driving skills of the driver more than the first criterion. As a result, it is possible to appropriately evaluate the driving skills of the target driver during the ice and snow period.

[0058] (3) The vehicles for which steering error information is generated during the comparison period ΔTb (drying period) are a plurality of vehicles 20 (other vehicles 20B, 20C) different from the target vehicle 20A (Fig. 1). The reference error value α0 is a representative value (for example, the mode value ed) of the prediction error e(n) included in the steering error information of the plurality of vehicles 20 during the comparison period ΔTb (Fig. 6). Thus, the reference error value α0 can be set to a good value using a large amount of steering information, and the driving skill of the target driver can be appropriately evaluated using the reference error value α0.

[0059] (4) The target period ΔTa is a period when ice and snow occur on the road surface, and the comparison period ΔTb is a period when ice and snow do not occur on the road surface (Fig. 2A). In this case, steering becomes unstable during the target period ΔTa compared to the comparison period ΔTb, but by using the method according to this embodiment, the driving skill of the driver during the target period ΔTa can be appropriately evaluated.

[0060] (5) The driving evaluation device further includes an information output unit 14 that outputs information on driving skill so that the information on driving skill evaluated by the driving evaluation unit 13 is used for calculating the driver's vehicle insurance (Fig. 4). Thus, an appropriate insurance premium can be calculated according to the driving skill of the target driver.

[0061] (6) The above-described driving evaluation device can also be configured as a driving evaluation method. In this case, the driving evaluation method includes: a step of acquiring running information of vehicles 20 including a target vehicle 20A associated with time information and other vehicles 20B and 20C, the running information including position information of the target vehicle 20A and the other vehicles 20B and 20C and steering information which is operation information of the steering wheel (step S1); a step of generating steering error information which is information on an error (prediction error e(n)) between an actual measurement value and a predicted value of steering for each of the target vehicle 20A and the other vehicles 20B and 20C on an evaluation target road RD1 specified by road map information based on the acquired running information (step S2); a step of evaluating the driving skill of the driver of the target vehicle 20A in the target period ΔTa according to a first criterion based on the steering error information of the other vehicles 20B and 20C in the comparison period ΔTb (dry period) and the steering error information of the target vehicle 20A in the same target period ΔTa (dry period) as the comparison period ΔTb, and evaluating the driving skill of the driver of the target vehicle 20A in the target period ΔTa according to a second criterion based on the steering error information of the other vehicles 20B and 20C in the comparison period Tb (dry period) and the steering error information of the target vehicle 20A in a target period ΔTa (snow and ice period) different from the comparison period ΔTb (steps S3 to S10), which is executed by a computer (FIG. 7). A representative value (for example, the mode value es) of a histogram representing the degree of prediction error in the target period ΔTa (snow and ice period) is larger than a representative value (mode value ed) of a histogram representing the degree of prediction error e(n) in the comparison period ΔTb (dry period) (FIG. 6). The second criterion is determined so as to suppress a decrease in the driving skill of the driver more than the first criterion. Specifically, when a steering error determined by the steering error information of the other vehicles 20B and 20C in the comparison period ΔTb (dry period) is defined as a reference error value α0 and a steering error determined by the steering error information of the target vehicle 20A is defined as a target error value α1, the second criterion is determined to increase a threshold value β for reducing the driving skill of the driver as compared with a difference (prediction difference Δα) between the reference error value α0 and the target error value α1 more than the first criterion (βs > βd) (FIG. 8). Thereby, it is possible to appropriately evaluate the driving skill even for a driver who frequently drives on a road surface that has an adverse effect on driving operations.

[0062] The above-described embodiment can be modified into various forms. Hereinafter, some modification examples will be described. In the above-described embodiment, the threshold value βs (second threshold value) used in the second criterion is set to be larger than the threshold value βd (first threshold value) used in the first criterion. However, as long as the second criterion is set to suppress a decrease in the driving skill of the driver more than the first criterion, the first and second criteria used in the driving evaluation unit 13 are not limited to those described above. For example, the second criterion may be defined to correct the difference (prediction difference Δα) between the reference error value α0 and the target error value α1 to be smaller than that of the first criterion. More specifically, when the target period ΔTa is a dry period, the target error value α1 determined by the steering error information of the target vehicle 20A in the target period ΔTa is larger than the reference error value α0 determined by the steering error information of other vehicles 20B and 20C in the comparison period ΔTb (dry period), and the difference (prediction difference Δα) between the target error value α1 and the reference error value α0 is larger than the threshold value βd, and when the target period ΔTa is a snow and ice period, the target error value α1 determined by the steering error information of the target vehicle 20A in the target period ΔTa is larger than the reference error value α0, and the corrected value (γ×Δα) obtained by multiplying the difference (prediction difference Δα) by a predetermined correction coefficient γ greater than 0 and less than 1 is larger than the threshold value βd, the degree of the driving skill of the driver of the target vehicle 20A may be decreased. In this case, what determines the magnitude relationship between the prediction difference Δα and the threshold value βd is the first criterion, and what determines the magnitude relationship between the corrected value obtained by multiplying the prediction difference Δα by the correction coefficient and the threshold value βd is the second criterion. Even when the first criterion and the second criterion are defined in this way, the second criterion is defined to suppress a decrease in the driving skill of the driver more than the first criterion, and thereby the driving skill of the target driver in the snow and ice period can be appropriately evaluated.

[0063] In the above embodiment, the vehicle (comparison target vehicle) for which steering error information is generated during the comparison period ΔTb (drying period) is a plurality of vehicles 20 (other vehicles 20B, 20C) different from the target vehicle (evaluation target vehicle) 20A. However, the comparison target vehicle may be the same vehicle as the target vehicle 20A. In this case, the reference error value α0 may be a representative value (for example, the mode value) of the prediction error e(n) included in the steering error information of the target vehicle 20A during the comparison period ΔTb. Thereby, using the steering information of the same vehicle 20A that has traveled on the evaluation target road RD1 during different periods (drying period, ice and snow period), the driving skill of the driver during the target period ΔTa (ice and snow period) can be evaluated. When the same driver travels on the same evaluation target road RD1, the variation in the prediction error e(n) should be small. When the variation in the prediction error e(n) becomes large, it is considered that the influence due to the change in the road surface condition is large. Therefore, by using the driving information of the same driver, not only can the driving skill of the driver be accurately evaluated, but also the change in the road surface condition can be estimated.

[0064] In the above embodiment, the administrative district is set as the predetermined area AR1, and the driving skill of the target driver is evaluated using the driving information of the vehicle 20 traveling on the evaluation target road RD1 within the same administrative district. However, the predetermined area AR1 is not limited to the administrative district. For example, as shown in FIG. 9A, a predetermined map mesh obtained by dividing the road map may be set as the predetermined area AR2, and the driving skill of the target driver may be evaluated using the driving information of the vehicle 20 traveling on the evaluation target road RD1 within the predetermined map mesh.

[0065] In the above-described embodiment, the steering error information is generated using the driving information of other vehicles 20B and 20C that travel at the same location (the same evaluation target road RD1) as the target vehicle 20A. However, even if the evaluation target roads are different, as long as they are within the same predetermined area AR1, it is assumed that the road surface conditions are the same. Considering this point, the steering error information may be generated using the driving information of other vehicles different from those described above. For example, as shown in FIG. 9B, the steering error information may be generated using the driving information of the vehicle 20 traveling on the evaluation target road RD1 within the predetermined area AR1 and the vehicle 20 traveling on another evaluation target road RD2. That is, the other vehicles 20B and 20C in FIG. 1 are not limited to vehicles that travel on the same evaluation target road RD1 as the target vehicle 20A.

[0066] When including the vehicle 20 traveling on the evaluation target road RD2 different from the evaluation target road RD1 in the other vehicles in FIG. 1, it is preferable to include the vehicle 20 traveling on the evaluation target road RD2 with a traffic volume level similar to that of the evaluation target road RD1 in the other vehicles. This is because if the traffic volume levels are similar, it is assumed that the road surface conditions are similar. Note that the traffic volume information is included in the road map information acquired by the information acquisition unit 11.

[0067] In the above-described embodiment, regarding the other vehicles 20B and 20C in FIG. 1, it is not necessary for the vehicle type and class to be the same as those of the target vehicle 20A. However, if the vehicle type and class are the same, the behaviors of the vehicles 20 when traveling on roads with the same road surface conditions are likely to be equal to each other. Considering this point, other vehicles with the same vehicle type and class as the target vehicle 20A may be used as the other vehicles 20B and 20C in FIG. 1. The vehicle type and class can be specified by the vehicle ID acquired by the information acquisition unit 11. In the above-described embodiment, the steering error information for the plurality of vehicles 20 in the comparison period ΔTb is generated using the steering information of the plurality of vehicles 20 excluding the target vehicle 20A. However, the steering information for the plurality of vehicles 20 in the comparison period ΔTb may be generated using the steering information of the plurality of vehicles 20 including the target vehicle 20A.

[0068] In the above-described embodiment, the information on driving skills output from the information output unit 14 is transmitted to the server of the insurance company. However, the information on driving skills may be used not only for calculating insurance premiums but also for other purposes (for example, evaluation of cognitive functions). Therefore, the information output unit 14 may transmit the information on driving skills to other devices. In the above-described embodiment, the arithmetic unit 10A of the server device 10 executes the process of FIG. 7 every time the target period ΔTa ends. However, the process of FIG. 7 may be executed after a predetermined period has elapsed since the end of the target period ΔTa. In this case, not only the comparison period ΔTb (second period) may be determined before the target period ΔTa (first period), but also the comparison period ΔTb may be determined after the target period ΔTa. That is, if the first period and the second period are different, the second period may be after rather than before the first period.

[0069] In the above-described embodiment, the reference error value α0 (reference value) representing the steering error information is calculated based on the steering error information of the other vehicles 20B and 20C in the comparison period ΔTb. However, the reference value may be other than the representative value described above. In the above-described embodiment, the target error value α1 (evaluation target value) representing the steering error information is calculated based on the steering error information of the target vehicle 20A in the target period ΔTa. However, the evaluation target value may be other than the representative value described above.

[0070] In the above embodiment, when the target period ΔTa is included in the comparison period ΔTb (FIG. 2B), that is, when the target period ΔTa is a dry period, the target error value α1 (the first evaluation target value) is calculated based on the steering error information of the target vehicle 20A. When the target period ΔTa is not included in the comparison period (FIG. 2A), that is, when the target period ΔTa is a snow and ice period, the target error value α1 (the second evaluation target value) is calculated based on the steering error information of the target vehicle 20A. Instead of setting the target period ΔTa to either the dry period or the snow and ice period in this way, the target period ΔTa may be set for each of the snow and ice period and the dry period. That is, a plurality of target periods ΔTa may be set throughout the year. The target period ΔTa in which the second evaluation target value is calculated may be a period with a road surface condition that makes steering more unstable than the target period ΔTa in which the first evaluation target value is calculated, and may be other than the snow and ice period.

[0071] In the above embodiment, when the prediction difference Δα is greater than the threshold value β, the driving skill of the target driver is decreased from A (the first level) to B (the second level) or from A (the first level) to C (the second level). However, the degree of decrease is not limited to that described above. In the above embodiment, the error information generation unit 12 generates information on the prediction error e(n), which is information on the error between the measured value and the predicted value of steering on the evaluation target road RD1 specified by the road map information, based on the driving information of the plurality of vehicles 20 acquired by the information acquisition unit 11. However, the generated steering error information is not limited to the information on the prediction error e(n). For example, information on the steering entropy value, which is a value obtained by quantifying the smoothness of steering, may be generated as the steering error information.

[0072] In the above embodiment, the server device 10 constitutes the driving evaluation device. However, the driving evaluation device may also be constituted by other than the server device 10. The driving evaluation device may be constituted by a plurality of devices (for example, the server device 10 and the in-vehicle device 30).

[0073] The above description is merely an example, and the present invention is not limited to the above-described embodiments and modified examples as long as the features of the present invention are not impaired. It is also possible to arbitrarily combine one or more of the above embodiments and modified examples, and it is also possible to combine modified examples with each other.

Explanation of Signs

[0074] 10 Server device, 11 Information acquisition unit, 12 Error information generation unit, 13 Driving evaluation unit, 14 Information output unit, 20 Vehicle, 20A Target vehicle, 20B, 20C Other vehicles, ΔTa Target period, ΔTb Comparison period, RD1 Evaluation target road, α0 Reference error value, α1 Target error value, Δα Prediction difference, β, βs, βd Threshold value

Claims

1. Driving information of an evaluation target vehicle and a comparison target vehicle associated with time information, the driving information including position information of the evaluation target vehicle and the comparison target vehicle and steering information which is operation information of steering, and road map information, an information acquisition unit configured to acquire the driving information and the road map information; Based on the driving information acquired by the information acquisition unit, an error information generation unit configured to generate steering error information which is information on an error between an actual measurement value and a predicted value of steering for each of the evaluation target vehicle and the comparison target vehicle on an evaluation target road specified by the road map information; Based on the steering error information of the comparison target vehicle in a first period and the steering error information of the evaluation target vehicle in the first period generated by the error information generation unit, a driving evaluation unit configured to evaluate a driving skill of a driver of the evaluation target vehicle in the first period according to a first criterion, and based on the steering error information of the comparison target vehicle in the first period and the steering error information of the evaluation target vehicle in a second period different from the first period generated by the error information generation unit, evaluate a driving skill of a driver of the evaluation target vehicle in the second period according to a second criterion; A degree of the error in the second period is larger than a degree of the error in the first period; When defining a steering error determined by the steering error information of the comparison target vehicle in the first period as a reference value and a steering error determined by the steering error information of the evaluation target vehicle as an evaluation target value, the second criterion is determined such that a threshold value for reducing a driving skill of a driver is larger as compared with a difference between the reference value and the evaluation target value than the first criterion, or the difference between the reference value and the evaluation target value is corrected to be smaller. A driving evaluation device characterized by this.

2. In the driving evaluation device according to claim 1, When defining a steering error determined by the steering error information of the evaluation target vehicle in the first period as a first evaluation target value and a steering error determined by the steering error information of the evaluation target vehicle in the second period as a second evaluation target value, When the first evaluation target value is greater than the reference value and the difference between the first evaluation target value and the reference value is greater than the first threshold value, and when the second evaluation target value is greater than the reference value and the difference between the second evaluation target value and the reference value is greater than the second threshold value which is greater than the first threshold value, the driving evaluation unit reduces the degree of the driving skill of the driver of the vehicle to be evaluated from a first level to a second level. A driving evaluation device characterized by this.

3. In the driving evaluation device according to claim 1, When defining the steering error determined by the steering error information of the vehicle to be evaluated in the first period as the first evaluation target value and the steering error determined by the steering error information of the vehicle to be evaluated in the second period as the second evaluation target value, When the first evaluation target value is greater than the reference value and the difference between the first evaluation target value and the reference value is greater than the threshold value, and when the second evaluation target value is greater than the reference value and the corrected value obtained by multiplying the difference between the second evaluation target value and the reference value by a predetermined correction coefficient is greater than the threshold value, the driving evaluation unit reduces the degree of the driving skill of the driver of the vehicle to be evaluated from a first level to a second level. A driving evaluation device characterized by this.

4. In the driving evaluation device according to any one of claims 1 to 3, The comparison target vehicle is the same vehicle as the vehicle to be evaluated, The reference value is a representative value of the steering error determined by the steering error information of the comparison target vehicle in the first period, The evaluation target value is a representative value of the steering error determined by the steering error information of the vehicle to be evaluated. A driving evaluation device characterized by this.

5. In the driving evaluation device according to any one of claims 1 to 3, The comparison target vehicle is a plurality of vehicles different from the vehicle to be evaluated, The reference value is a representative value of the steering error determined by the steering error information of the comparison target vehicle in the first period, The driving evaluation device is characterized in that the evaluation target value is a representative value of the steering error determined by the steering error information of the vehicle to be evaluated.

6. In the driving evaluation device according to any one of claims 1 to 3, The driving evaluation device is characterized in that the second period is a period in which ice and snow occur on the road surface, and the first period is a period in which ice and snow do not occur on the road surface.

7. In the driving evaluation device according to any one of claims 1 to 3, The driving evaluation device further comprises an information output unit that outputs the information on the driving skill so that the information on the driving skill evaluated by the driving evaluation unit is used for calculating the vehicle insurance of the driver.

8. A step of acquiring running information of a vehicle to be evaluated and a comparison target vehicle associated with time information, the running information including position information of the vehicle to be evaluated and the comparison target vehicle and steering information which is operation information of the steering, and road map information; A step of generating steering error information which is information on an error between an actual measurement value and a predicted value of steering for each of the vehicle to be evaluated and the comparison target vehicle on an evaluation target road specified by the road map information based on the acquired running information; A step of evaluating the driving skill of the driver of the vehicle to be evaluated in the first period according to a first criterion based on the steering error information of the comparison target vehicle in the first period and the steering error information of the vehicle to be evaluated in the first period, and evaluating the driving skill of the driver of the vehicle to be evaluated in the second period according to a second criterion based on the steering error information of the comparison target vehicle in the first period and the steering error information of the vehicle to be evaluated in a second period different from the first period, the steps being executed by a computer, The degree of the error in the second period is greater than the degree of the error in the first period. When defining the steering error determined by the steering error information of the comparison target vehicle in the first period as a reference value and the steering error determined by the steering error information of the evaluation target vehicle as an evaluation target value, the second criterion is set to increase the threshold for reducing the driver's driving skill as compared with the difference between the reference value and the evaluation target value more than the first criterion, or to define so as to correct the difference between the reference value and the evaluation target value to be smaller. A driving evaluation method characterized by this is provided.

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