Driving ability assessment system and driving ability assessment method

Abstract

To determine operation ability without causing an operational issue.SOLUTION: An operation ability determination system 10 comprises: an information acquisition section 13 which acquires steering angle data indicating a time series change in a steering angle of a vehicle on the basis of information indicating whether an operation support function supporting at least either acceleration and deceleration or brake in operation by a driver of the vehicle is in execution; and an evaluation value calculation section 15 which calculates an evaluation value indicating a steering characteristic of the driver on the basis of the steering angle data acquired with the information acquisition section 13. The evaluation value calculation section 15 calculates the evaluation value by making weight of first steering angle data, among the steering angle data acquired with the information acquisition section 13, during a period when the operation support function is in execution larger than weight of second steering angle data during a period when the operation support function is not in execution.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a driving ability determination system and a driving ability determination method for determining the driving ability of a vehicle driver. [Background technology]

[0002] As this type of device, a device that measures a driver's safe driving ability is known (see, for example, Patent Document 1). The device described in Patent Document 1 intermittently applies a load to the driver by audio output to distribute attention, calculates steering entropy values ​​that represent steering deviations under load and no load conditions, and evaluates the driver's safe driving ability based on the difference between the deviation evaluation values ​​calculated under load and no load conditions.

[0003] By assessing the driving ability of elderly drivers and providing them with an opportunity to consider returning their driver's license or introducing driving assistance functions as necessary, we can improve road safety and contribute to the development of sustainable transportation systems. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2014-174848 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the device described in Patent Document 1 requires imposing a load on the driver in order to evaluate the driver's safe driving ability, which impedes driving. [Means for solving the problem]

[0006] A driving ability assessment system according to one aspect of the present invention includes an information acquisition unit that acquires steering angle data indicating changes in the steering angle of the vehicle over time, along with information on whether a driving assistance function that assists at least one of acceleration / deceleration and braking among driving operations by a driver of the vehicle is activated, and an evaluation value calculation unit that calculates an evaluation value representing the steering characteristics of the driver based on the steering angle data acquired by the information acquisition unit. The evaluation value calculation unit calculates the evaluation value by assigning a greater weight to first steering angle data during a period when the driving assistance function is activated than to second steering angle data during a period when the driving assistance function is not activated, among the steering angle data acquired by the information acquisition unit.

[0007] A driving ability assessment method according to another aspect of the present invention includes an information acquisition step of acquiring steering angle data indicating a change in the steering angle of the vehicle over time, together with information on whether a driving assistance function that assists at least one of acceleration / deceleration and braking among driving operations by a driver of the vehicle is activated, and an evaluation value calculation step of calculating an evaluation value representing the steering characteristics of the driver based on the steering angle data acquired in the information acquisition step. In the evaluation value calculation step, the evaluation value is calculated by weighting, among the steering angle data acquired in the information acquisition step, first steering angle data during a period when the driving assistance function is activated more heavily than second steering angle data during a period when the driving assistance function is not activated. [Effects of the Invention]

[0008] According to the present invention, driving ability can be determined without interfering with driving. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a diagram for explaining a driving section and a driving load. [Figure 2] 1 is a block diagram showing an example of a configuration of a main part of a driving ability determination system according to an embodiment of the present invention; [Figure 3] FIG. 3 is a diagram for explaining fluctuations in the steering angle of a vehicle. [Figure 4]FIG. 10 is a diagram illustrating an example of a degree display of the degree of steering shake. [Figure 5] 3 is a time chart for explaining the state of the driving assistance function taken into account by the evaluation value calculation unit of FIG. 2; [Figure 6] 3 is a flowchart showing an example of evaluation processing executed by the calculation unit of FIG. 2; [Figure 7] 3 is a flowchart showing an example of weighting processing executed by the calculation unit of FIG. 2; [Figure 8] 10 is a flowchart showing another example of the weighting process executed by the calculation unit of FIG. 2. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an embodiment of the present invention will be described with reference to FIGS. 1 to 8. A driving ability determination system according to an embodiment of the present invention determines the driving ability of a vehicle driver. Generally, a driver's driving behavior is composed of three elements: cognition, judgment, and operation. Of these elements, abilities related to "cognitive function," which is a person's intellectual function related to cognition and judgment, are known to gradually decline with age. Declining cognitive function makes it difficult to drive a vehicle safely. The driving ability related to cognitive function is determined based on driving data when the driver drives a vehicle, and safe driving can be supported by the driver and their family members by understanding the tendency of cognitive function decline.

[0011] Figure 1 is a diagram explaining the relationship between driving sections and driving load. As shown in Figure 1, the driving load imposed on a driver due to driving behavior varies depending on the driving section, such as road shape. For example, driving on S-curves or winding roads, or parking in a parking space, increases the driving load. In other words, driving load increases on driving sections where the driver is required to make many steering maneuvers per unit of vehicle movement and the vehicle's driving trajectory has a complex shape. In this case, high driving skills are required, as steering is required in coordination with accelerator and brake operations, and vehicle sense is also required. In such driving sections (high-load sections), the driver's driving skills have a significant impact on driving stability.

[0012] On the other hand, there is almost no driving load when driving on a straight road. In other words, there is almost no steering required from the driver per unit of vehicle movement, and the vehicle's driving trajectory is extremely simple, so there is almost no driving load. In such driving sections (no-load sections), the driver's driving skill has almost no effect on driving stability.

[0013] Driving loads fall somewhere in between these two levels when driving on curved roads, changing lanes on multi-lane roads, turning right or left at intersections, etc. Even in these driving sections (low load sections), the driver's driving skill does not have much of an impact on driving stability.

[0014] However, even in no-load or low-load sections, for example, when driving on a single-lane highway (two-way traffic section) with no central divider, the driver needs to recognize the conditions of the vehicle's own lane and the oncoming lane. In this case, the driver's mental activity increases as the driver's gaze shifts between the vehicle's own lane and the oncoming lane, increasing the cognitive load (hereinafter referred to as "cognitive load"). The cognitive load also increases because gaze shifts are required in sections with multiple lanes with heavy traffic, sections with many signs and traffic signals, sections with many pedestrians such as in busy areas, sections with many blind spots such as curved roads with poor visibility or intersections, and sections where multiple roads intersect.

[0015] Furthermore, when making a turn at an intersection to change the direction of travel of the vehicle by crossing the oncoming lane (a right turn in countries and regions where vehicles drive on the left side of the road, and a left turn in countries and regions where vehicles drive on the right side of the road; hereinafter simply referred to as a "right turn"), the driver needs to grasp the situation of the oncoming lane ahead while also grasping the situation of the lane ahead after the right turn in order to recognize the target trajectory of the vehicle. In this case too, the driver's line of sight shifts between the oncoming lane ahead and the lane ahead after the right turn, increasing the cognitive load.

[0016] In a driving section where cognitive load is high (hereinafter referred to as a "specific section"), the state of the driver's cognitive function affects the driving stability. By acquiring driving data for the specific section in a manner that allows it to be distinguished from other sections and evaluating the driving stability based on the driving data, it is possible to determine the driving ability related to the driver's cognitive function. For example, time-series location information of the vehicle can be acquired, and based on the acquired location information, it is possible to identify the driving data for the specific section that is preset in the map information.

[0017] However, even when driving the same section, the driving load and cognitive load change depending on whether the driver is receiving assistance from the vehicle's driving assistance function. Therefore, in this embodiment, the driving ability determination system is configured as follows so that the driving ability related to cognitive function can be appropriately determined by changing the way driving data is handled depending on the state of the vehicle's driving assistance function.

[0018] FIG. 2 is a block diagram showing an example of the configuration of the main parts of a driving ability determination system (hereinafter referred to as the system) 10. As shown in FIG. 2, the system 10 includes a computer having a calculation unit 11 such as a CPU, a storage unit 12 such as a ROM and a RAM, and peripheral circuits thereof. The calculation unit 11 functions as an information acquisition unit 13, a load determination unit 14, an evaluation value calculation unit 15, a cognitive function evaluation unit 16, and an information output unit 17. The storage unit 12 stores information such as programs executed by the calculation unit 11 and setting values. The system 10 may be configured as an on-board device mounted on a vehicle, as a server device or the like provided outside the vehicle, or as a combination of an on-board device and an external server device or the like.

[0019] The information acquisition unit 13 acquires time-series vehicle driving data for each pre-registered driver. For example, it acquires driving data measured in a pre-registered vehicle that each driver drives daily. The driving data includes at least time-series information on the state of the vehicle's driving assistance functions and time-series steering angle data that indicates changes in the steering angle of the steering wheel (steering wheel, handle) by the driver. The driving data also includes time-series position information of the vehicle.

[0020] The driving data is transmitted from the vehicle to the system 10 at a predetermined interval via, for example, a TCU (telematics control unit) mounted on the vehicle. The information acquisition unit 13 acquires the driving data transmitted from pre-registered vehicles as time-series driving data for each pre-registered driver. The time-series driving data for each driver acquired by the information acquisition unit 13 is stored in the storage unit 12.

[0021] The load determination unit 14 determines whether a predetermined cognitive load is acting on the driver for each unit time based on the driving data stored in the memory unit 12. More specifically, the load determination unit 14 determines whether the driving section for each unit time is a no-load section or a low-load section (no-load / low-load section) or a high-load section in FIG. 1 based on time-series position information of the vehicle. Furthermore, the load determination unit 14 determines whether the driving section for each unit time is a specific section among the no-load / low-load sections that is preset in the map information.

[0022] The evaluation value calculation unit 15 calculates an α value representing the average steering characteristics of an individual driver and an Hp value representing the steering characteristics of the driver when the cognitive load is increased, based on the steering angle data stored in the storage unit 12. More specifically, the evaluation value calculation unit 15 calculates the α value based on the steering angle data for a period determined by the load determination unit 14 to be traveling in a no-load / low-load section. The evaluation value calculation unit 15 also calculates the Hp value based on the calculated α value and the steering angle data for a period determined by the load determination unit 14 to be traveling in a specific section.

[0023] 3 is a diagram for explaining fluctuations in the steering angle θ of a vehicle. When the vehicle is being driven stably, the steering is smooth and stable, resulting in small fluctuations in the steering angle θ. On the other hand, when the vehicle is being driven unstable, the steering becomes unstable and the fluctuations in the steering angle θ become large.

[0024] More specifically, as shown in FIG. 3, a predicted steering angle θp(n) at time point n is calculated by second-order Taylor expansion centered on time point (n-1) based on the actual steering angles θ(n-3), θ(n-2), and θ(n-1) at time points n-3, n-2, and n-1 immediately preceding the specific time point n. Since the predicted steering angle θp(n) is an estimated value assuming smooth steering, if the actual steering is smooth, it will match the actual steering angle θ(n), but if the actual steering is unstable, it will deviate from the actual steering angle θ(n) depending on the degree of the unstable steering. The degree of such unstable steering can be expressed as a prediction error e(n) calculated by the following equation (i): e(n)=θ(n)-θp(n) (i)

[0025] FIG. 4 is a diagram illustrating an example of a frequency display of the degree of steering error, showing an example of the frequency display of the prediction error e(n). The evaluation value calculation unit 15 calculates the predicted steering angle θp(n) and prediction error e(n) at each time point n based on the steering angle data in the no-load and low-load sections, and calculates the 90th percentile value (α value) of the frequency distribution of the prediction error e(n) as shown by the solid line. The smoother the steering and the less the steering error, the sharper the frequency distribution of the prediction error e(n) will be centered around "0°," where there is no steering error, and the smaller the α value will be. On the other hand, the more the steering error is, the broader the frequency distribution of the prediction error e(n) will be and the larger the α value will be.

[0026] By using steering angle data from no-load and low-load sections, excluding high-load sections where there is a lot of steering and driving skill has a large effect on steering error, it is possible to properly calculate the α value, which represents the driver's average steering error.

[0027] Furthermore, the evaluation value calculation unit 15 calculates the Hp value based on the calculated α value and the steering angle data for the specific section. More specifically, the evaluation value calculation unit 15 calculates the predicted steering angle θp(n) and prediction error e(n) for each time point n based on the steering angle data for the specific section, and divides the frequency distribution of the prediction error e(n) as indicated by the dashed line into nine ranges P1 to P9 based on the α value. That is, based on eight reference values ​​-5α, -2.5α, -α, -0.5α, 0.5α, α, 2.5α, and 5α, the nine ranges are divided into P1 (to -5α), P2 (-5α to -2.5α), P3 (-2.5α to -α), P4 (-α to -0.5α), P5 (-0.5α to 0.5α), P6 (0.5α to α), P7 (α to 2.5α), P8 (2.5α to 5α), and P9 (5α or higher). Then, based on the proportions p1 to p9 of the ranges P1 to P9, the steering entropy value (Hp value) is calculated by the following formula (ii). Hp=-Σpi·log9pi ···(ii)

[0028] The Hp value represents the smoothness of steering, and the smaller the steering error and the sharper the frequency distribution of the prediction error e(n), the smaller the value, and the larger the steering error and the broader the frequency distribution of the prediction error e(n).By using steering angle data from specific sections where there is a lot of eye movement and the cognitive function is greatly affected by steering error, it is possible to appropriately calculate the Hp value, which represents the driver's steering error when the cognitive load is higher than usual.

[0029] 5 is a time chart for explaining the states of the driving assistance functions considered by the evaluation value calculation unit 15. The first driving assistance function is a driving assistance function that assists the driver of the vehicle in at least one of acceleration / deceleration and braking among driving operations, and the second driving assistance function is a driving assistance function that assists the driver in steering.

[0030] The first driving assistance function includes a function that assists in accelerating and decelerating so that the vehicle travels at a set speed, a function that detects a preceding vehicle using a camera or other device and assists in accelerating and decelerating so that the vehicle follows the preceding vehicle while maintaining a set distance. It also includes a function that assists in braking so that the vehicle stops when the preceding vehicle stops. The second driving assistance function includes a function that detects the driving lane using a camera or other device and issues a warning with steering vibration if the vehicle is in danger of deviating from the driving lane, and a function that assists in steering (applies steering force) so that the vehicle travels near the center of the driving lane. Even if these driving assistance functions are activated, they may not operate normally if the camera or other device cannot recognize the preceding vehicle or the driving lane due to weather conditions, etc.

[0031] The time series information regarding the status of the vehicle's driving assistance functions acquired by the information acquisition unit 13 includes information on whether the first driving assistance function is activated, information on whether the first driving assistance function is operating normally after activation, and information on whether the second driving assistance function is operating.

[0032] As shown in Fig. 5, among the steering angle data acquired by the information acquisition unit 13 and stored in the storage unit 12, steering angle data during the period (t1 to t2, t3 onward) during which the first driving assistance function is activated, more specifically during the period after activation during which the function is operating normally, will be referred to as "first steering angle data" hereinafter. Steering angle data other than the first steering angle data will be referred to as "second steering angle data" hereinafter. Note that, among the first steering angle data, steering angle data during the period (t4 to t5) during which the second driving assistance function is activated is excluded from the first steering angle data and treated as the second steering angle data.

[0033] (Evaluation value weighting) The evaluation value calculation unit 15 performs weighting so that the weight of the first steering angle data is greater than the weight of the second steering angle data, and then calculates the Hp value, or the α value and the Hp value. More specifically, the evaluation value calculation unit 15 calculates the α value without weighting, and calculates the Hp value after weighting. Alternatively, the evaluation value calculation unit 15 performs weighting and then calculates the α value, and then calculates the Hp value after weighting.

[0034] (Weighting of α value - Weighting to frequency -) When the evaluation value calculation unit 15 calculates the α value after performing weighting, first, based on the first steering angle data for the period determined by the load determination unit 14 to be in the no-load / low-load section, the predicted steering angle θp1(n) and the prediction error e1(n) are calculated. Also, based on the second steering angle data for the same period, the predicted steering angle θp2(n) and the prediction error e2(n) are calculated. Next, the frequency of the prediction error e1(n) (the frequency distribution shown by the solid line in FIG. 4) is multiplied by the weight coefficient W1 (0 < W1, for example, W1 = 1), and the frequency of the prediction error e2(n) is multiplied by the weight coefficient W2 (0 ≤ W2 < W1, for example, W2 = 0), and these are added together. The evaluation value calculation unit 15 calculates the 90th percentile value in the frequency distribution of the weighted and added prediction error (W1e1(n) + W2e2(n)) as the α value.

[0035] (Weighting of Hp value - Weighting to frequency -) When the evaluation value calculation unit 15 calculates the Hp value after performing weighting, first, based on the first steering angle data for the period determined by the load determination unit 14 to be in the specific section, the predicted steering angle θp1(n) and the prediction error e1(n) are calculated. Also, based on the second steering angle data for the same period, the predicted steering angle θp2(n) and the prediction error e2(n) are calculated. Next, the frequency of the prediction error e1(n) (the frequency distribution shown by the dashed line in FIG. 4) is multiplied by the weight coefficient W1 (0 < W1, for example, W1 = 1), and the frequency of the prediction error e2(n) is multiplied by the weight coefficient W2 (0 ≤ W2 < W1, for example, W2 = 0), and these are added together. The evaluation value calculation unit 15 divides the frequency distribution of the weighted and added prediction error (W1e1(n) + W2e2(n)) into ranges P1 to P9 based on the α value, and calculates the Hp value according to formula (ii) based on the ratios p1 to p9 of each range P1 to P9.

[0036] (Weighting of Hp value - Direct weighting -) When calculating the Hp value after weighting, the evaluation value calculation unit 15 may calculate the Hp1 value based on the first steering angle data and the Hp2 value based on the second steering angle data, and multiply the calculated Hp1 value and Hp2 value by the weighting coefficients W1 and W2, respectively. More specifically, the evaluation value calculation unit 15 calculates the predicted steering angle θp1(n), the prediction error e1(n), and the Hp1 value based on the first steering angle data during the period determined by the load determination unit 14 to be traveling in the specific section. Also, based on the second steering angle data for the same period, the predicted steering angle θp2(n), the prediction error e2(n), and the Hp2 value are calculated. The evaluation value calculation unit 15 multiplies the Hp1 value by the weighting coefficient W1(0 < W1, for example, W1 = 1), multiplies the Hp2 value by the weighting coefficient W2(0 ≤ W2 < W1, for example, W2 = 0), and calculates the sum of these values (W1Hp1 + W2Hp2) as the Hp value.

[0037] The cognitive function evaluation unit 16 evaluates the driver's cognitive function based on the Hp value calculated by the evaluation value calculation unit 15. That is, by continuously monitoring the Hp value representing the deviation of steering when the cognitive load increases, the tendency of the driver's cognitive function to decline can be evaluated. For example, if the Hp value calculated regularly (e.g., monthly) based on the driving data of daily driving shows an increasing trend, it is evaluated that the cognitive function has a tendency to decline.

[0038] The information output unit 17 transmits the evaluation result by the cognitive function evaluation unit 16 to a user terminal such as the driver himself or his family. For example, a notification can be sent to a pre-registered email address. In this case, triggered by the notification, the driver himself or his family can consider returning the driver's license or replacing the vehicle with a vehicle equipped with a more advanced driving support function. Since objective information based on driving data is provided, it is easier for the driver himself to accept the current status of his cognitive function and can consider appropriate countermeasures at an early stage.

[0039] FIG. 6 is a flowchart showing an example of an evaluation process executed by the calculation unit 11 of the system 10. The process shown in this flowchart is executed, for example, periodically. First, in step S1, the driving data stored in the memory unit 12 is read. Next, in step S2, based on the driving data read in step S1, it is determined whether the driving section per unit time is a no-load / low-load section or a high-load section. Furthermore, based on the driving data of the no-load / low-load section, it is determined whether the driving section per unit time is a specific section.

[0040] Next, in step S3, an α value is calculated based on steering angle data during the period determined in step S2 to be traveling in a no-load / low-load section. Next, in step S4, an Hp value is calculated based on the α value calculated in step S3 and steering angle data during the period determined in step S2 to be traveling in a specific section. The latest Hp value calculated in step S4 is stored and accumulated in memory unit 12. Next, in step S5, the latest Hp value stored in memory unit 12 is compared with past Hp values ​​to determine the driver's driving ability related to cognitive function. Next, in step S6, the evaluation result of step S5 is sent to a pre-registered email address, and the process ends.

[0041] In this way, the α value and Hp value, which are indices for determining the driver's driving ability, can be calculated based only on daily driving data, so that driving ability can be determined without interfering with driving (steps S1 to S4). In addition, the cognitive function of the driver is automatically evaluated based only on daily driving data, and the evaluation results are notified to the driver and his / her family, so the burden on family members living far away from the elderly driver can be reduced (steps S1 to S6).

[0042] 7 is a flowchart showing an example of weighting processing executed by the calculation unit 11 of the system 10, in which the frequency of prediction error is multiplied by a weighting coefficient in the process of calculating the evaluation values ​​(α value, Hp value). The processing shown in this flowchart is executed in steps S3 and / or S4 of FIG.

[0043] (Weighting of alpha value - weighting of frequency) When the frequency of the prediction error is multiplied by a weighting factor in the process of calculating the α value, the process shown in this flowchart is executed in step S3 of FIG. 6. As shown in FIG. 7, first, in step S10, a predicted steering angle θp1(n) is calculated based on first steering angle data for the period determined in step S2 to be traveling in a no-load / low-load zone, and a prediction error e1(n) is calculated. Also, a predicted steering angle θp2(n) is calculated based on second steering angle data for the same period, and a prediction error e2(n) is calculated. Next, in step S11, the frequency of the prediction error e1(n) calculated in step S10 is multiplied by a weighting factor W1, and the frequency of the prediction error e2(n) calculated in step S10 is multiplied by a weighting factor W2. Next, in step S12, the weighted frequencies W1e1(n) and W2e2(n) calculated in step S11 are added together. In this case, in step S3 of FIG. 6, the 90th percentile value in the frequency distribution of the weighted and summed prediction errors (W1e1(n)+W2e2(n)) calculated in step S12 is calculated as the α value.

[0044] (Weighting of Hp values ​​- Weighting of frequencies) When the frequency of the prediction error is multiplied by a weighting factor in the process of calculating the Hp value, the process shown in this flowchart is executed in step S4 of FIG. 6. As shown in FIG. 7, first, in step S10, a predicted steering angle θp1(n) is calculated based on first steering angle data for the period determined in step S2 to be traveling through a specific section, and a prediction error e1(n) is calculated. Also, a predicted steering angle θp2(n) is calculated based on second steering angle data for the same period, and a prediction error e2(n) is calculated. Next, in step S11, the frequency of the prediction error e1(n) calculated in step S10 is multiplied by a weighting factor W1, and the frequency of the prediction error e2(n) calculated in step S10 is multiplied by a weighting factor W2. Next, in step S12, the weighted frequencies W1e1(n) and W2e2(n) calculated in step S11 are added together. In this case, in step S4 of FIG. 6, the Hp value is calculated based on the frequency distribution of the weighted and summed prediction errors (W1e1(n)+W2e2(n)) summed in step S12 and the α value calculated in step S3 of FIG. 6.

[0045] (Hp value weighting - direct weighting) FIG. 8 is a flowchart showing another example of the weighting process executed by the calculation unit 11 of the system 10. This is a variation of the flowchart in FIG. 6 in which the evaluation value (Hp value) is directly multiplied by a weighting coefficient. Steps S1 to S3, S5, and S6 in FIG. 8 are similar to steps S1 to S3, S5, and S6 in FIG. 6, and therefore will not be described here. As shown in FIG. 8, in step S4A, a predicted steering angle θp1(n), a prediction error e1(n), and an Hp1 value are calculated based on the α value calculated in step S3 and the first steering angle data for the period determined in step S2 to be traveling through the specific section. Furthermore, a predicted steering angle θp2(n), a prediction error e2(n), and an Hp2 value are calculated based on the second steering angle data for the same period. Next, in step S4B, the Hp1 value calculated in step S4A is multiplied by a weighting coefficient W1, and the Hp2 value calculated in step S4A is multiplied by a weighting coefficient W2. Next, in step S4C, the weighted Hp1 and Hp2 values ​​calculated in step S4B are added together to calculate the Hp value (W1Hp1+W2Hp2).

[0046] It is considered that the driver can concentrate on steering while the first driving assistance function, which assists the vehicle in constant speed driving and following a preceding vehicle, is activated. In the evaluation, the first steering angle data during such a period is actively used, that is, the weight of the first steering angle data is made greater than the weight of the second steering angle data to calculate the evaluation value, thereby enabling the driving ability to be determined with high accuracy (steps S11, S4B).

[0047] For example, when the first steering angle data is actively used to calculate the Hp value, it is possible to evaluate the steering characteristics of the driver when the driver is receiving driving assistance and the cognitive load is high while concentrating on steering. In this case, the accuracy of the Hp value, which is periodically calculated and accumulated, is improved, so the driver's cognitive function can be evaluated with high accuracy. Furthermore, when the first steering angle data is also actively used to calculate the α value, it is possible to evaluate the steering characteristics of the driver when the driver is receiving driving assistance and the cognitive load is high while concentrating on steering. This improves the accuracy of the α value, so the driver's cognitive function can be evaluated with even higher accuracy.

[0048] According to this embodiment, the following effects can be achieved. (1) System 10 includes information acquisition unit 13 that acquires steering angle data indicating changes in the steering angle of the vehicle over time, along with information on whether a first driving assistance function that assists in at least one of acceleration / deceleration and braking among driving operations performed by the driver of the vehicle is activated, and evaluation value calculation unit 15 that calculates an evaluation value representing the steering characteristics of the driver based on the steering angle data acquired by information acquisition unit 13 (FIG. 2). Evaluation value calculation unit 15 calculates the evaluation value by weighting, among the steering angle data acquired by information acquisition unit 13, first steering angle data during a period when the first driving assistance function is activated more heavily than second steering angle data during a period when the first driving assistance function is not activated.

[0049] In this way, by calculating an evaluation value that serves as an index for determining the driver's driving ability based on daily driving data, the driver's driving ability can be determined without interfering with driving. Furthermore, while the first driving assistance function that assists the vehicle in constant speed driving and following a preceding vehicle is activated, the driver can concentrate on steering, and by actively using the steering angle data during such periods, the driving ability can be determined with high accuracy.

[0050] (2) The first steering angle data is steering angle data during a period when the first driving assistance function is operating normally after activation. The second steering angle data further includes steering angle data during a period when the first driving assistance function is not operating normally after activation. For example, even if the first driving assistance function is activated, if the vehicle ahead cannot be recognized due to weather conditions or the like, the steering angle data during a period when the first driving assistance function is not actually operating is treated as the second steering angle data. This allows for more accurate assessment of the driver's driving ability.

[0051] (3) The information acquisition unit 13 further includes information on whether a second driving assistance function that assists the driver in steering is operating. The first steering angle data is steering angle data for a period when the first driving assistance function is activated and the second driving assistance function is not activated. The second steering angle data further includes steering angle data for a period when the first driving assistance function is activated and the second driving assistance function is activated. By reducing the weight of the steering angle data for a period when steering is assisted, which is the subject of the evaluation of driving ability, the driver's driving ability can be determined more accurately.

[0052] (4) The system 10 further includes a load determination unit 14 that determines whether or not a predetermined cognitive load is acting on the driver based on the steering angle data acquired by the information acquisition unit 13 (FIG. 2). The evaluation value calculation unit 15 calculates an α value that represents the average steering characteristics of the driver based on the steering angle data acquired by the information acquisition unit 13, and calculates an Hp value that represents the steering characteristics of the driver when the predetermined cognitive load is acting based on the calculated α value and the steering angle data acquired by the information acquisition unit 13, the steering angle data for a period during which the load determination unit 14 determines that the predetermined cognitive load is acting.

[0053] The evaluation value calculation unit 15 calculates the α value without weighting either the first steering angle data or the second steering angle data, while calculating the Hp value by weighting the first steering angle data more heavily than the second steering angle data. In this way, by actively using the first steering angle data obtained when the driver is receiving driving assistance and concentrating on steering, resulting in increased cognitive load, the Hp value can be accurately calculated, enabling the driver's cognitive function to be accurately evaluated. Furthermore, because the steering angle data used to calculate the α value is used regardless of the state of the driving assistance function, ensuring a sufficient amount of data allows the α value, which represents the driver's average steering characteristics, to be appropriately calculated.

[0054] (5) The evaluation value calculation unit 15 calculates the α value by weighting the first steering angle data more heavily than the second steering angle data, and calculates the Hp value by weighting the first steering angle data more heavily than the second steering angle data. For example, when a sufficient amount of data is available, the α value can be accurately calculated and the driver's cognitive function can be accurately evaluated by actively using the first steering angle data obtained when the driver is receiving driving assistance and concentrating on steering and the cognitive load increases.

[0055] In the above embodiment, an example has been described in which the α value is calculated based on the steering angle data when the vehicle is traveling in a no-load / low-load section, and the Hp value is calculated based on the steering angle data when the vehicle is traveling in a specific section, but the evaluation value calculation unit is not limited to this.The evaluation value calculation unit may be any unit that calculates an evaluation value that represents the steering characteristics of each driver based on the steering angle data for each driver.

[0056] While the present invention has been described above as a driving ability assessment system, it can also be used as a driving ability assessment method. That is, the driving ability assessment method includes an information acquisition step S1, each executed by a computer, for acquiring steering angle data indicating changes in the steering angle of the vehicle over time, along with information on whether a first driving assistance function that assists the driver of the vehicle in at least one of acceleration / deceleration and braking is active, and evaluation value calculation steps S3, S4, S10-S12, and S4A-A4C for calculating an evaluation value representing the driver's steering characteristics based on the steering angle data acquired in the information acquisition step S1 (FIGS. 6-8). In the evaluation value calculation steps S3, S4, S10-S12, and S4A-A4C, the evaluation value is calculated by weighting the first steering angle data acquired in the information acquisition step S1 during a period when the first driving assistance function is active more heavily than the second steering angle data acquired during a period when the first driving assistance function is not active.

[0057] The above description is merely an example, and the present invention is not limited to the above-described embodiment and modifications as long as the features of the present invention are not impaired. One or more of the above-described embodiment and modifications can be arbitrarily combined, and modifications can also be combined with each other. [Explanation of symbols]

[0058] 10 driving ability assessment system (system), 11 calculation unit, 12 memory unit, 13 information acquisition unit, 14 load assessment unit, 15 evaluation value calculation unit, 16 cognitive function assessment unit, 17 information output unit

Claims

1. an information acquisition unit that acquires steering angle data indicating a change in the steering angle of the vehicle over time, together with information on whether a driving assistance function that assists at least one of acceleration / deceleration and braking among driving operations performed by a driver of the vehicle is activated; an evaluation value calculation unit that calculates an evaluation value representing a steering characteristic of a driver based on the steering angle data acquired by the information acquisition unit, A driving ability assessment system characterized in that the evaluation value calculation unit calculates the evaluation value by giving a greater weight to first steering angle data during a period in which the driving assistance function is activated, among the steering angle data acquired by the information acquisition unit, than to second steering angle data during a period in which the driving assistance function is not activated.

2. 2. The driving ability determination system according to claim 1, the first steering angle data is steering angle data during a period in which the driving assistance function is operating normally after activation, The driving ability determination system, wherein the second steering angle data further includes steering angle data for a period during which the driving assistance function is not operating normally after activation.

3. 2. The driving ability determination system according to claim 1, the driving assistance function is a first driving assistance function, The information acquisition unit further includes information on whether a second driving assistance function that assists the driver in steering is operating, the first steering angle data is steering angle data during a period when the first driving assistance function is activated and the second driving assistance function is not activated, A driving ability determination system characterized in that the second steering angle data further includes steering angle data for a period during which the first driving assistance function is activated and the second driving assistance function is in operation.

4. 2. The driving ability determination system according to claim 1, a load determination unit that determines whether a predetermined load is acting on the driver based on the steering angle data acquired by the information acquisition unit, the evaluation value calculation unit calculates a first evaluation value representing an average steering characteristic of the driver based on the steering angle data acquired by the information acquisition unit, and calculates a second evaluation value representing the steering characteristic of the driver when the predetermined load is applied based on the calculated first evaluation value and steering angle data acquired by the information acquisition unit for a period during which the load determination unit determines that the predetermined load is applied; A driving ability assessment system characterized in that the evaluation value calculation unit calculates the first evaluation value without weighting either the first steering angle data or the second steering angle data, while calculating the second evaluation value by weighting the first steering angle data more than the weighting of the second steering angle data.

5. 2. The driving ability determination system according to claim 1, a load determination unit that determines whether a predetermined load is acting on the driver based on the steering angle data acquired by the information acquisition unit, the evaluation value calculation unit calculates a first evaluation value representing an average steering characteristic of the driver based on the steering angle data acquired by the information acquisition unit, and calculates a second evaluation value representing the steering characteristic of the driver when the predetermined load is applied based on the calculated first evaluation value and steering angle data acquired by the information acquisition unit for a period during which the load determination unit determines that the predetermined load is applied; The driving ability assessment system is characterized in that the evaluation value calculation unit calculates the first evaluation value by making the weight of the first steering angle data greater than the weight of the second steering angle data, and calculates the second evaluation value by making the weight of the first steering angle data greater than the weight of the second steering angle data.

6. Each of the methods is executed by a computer. an information acquisition step of acquiring steering angle data indicating a time-series change in the steering angle of the vehicle together with information on whether a driving assistance function that assists at least one of acceleration / deceleration and braking among driving operations performed by a driver of the vehicle is activated; an evaluation value calculation step of calculating an evaluation value representing a steering characteristic of a driver based on the steering angle data acquired in the information acquisition step, A driving ability assessment method characterized in that in the evaluation value calculation step, the evaluation value is calculated by increasing the weight of first steering angle data during a period in which the driving assistance function is activated, among the steering angle data acquired in the information acquisition step, compared to the weight of second steering angle data during a period in which the driving assistance function is not activated.

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