JP7727607B2 - Driving ability assessment system and driving ability assessment method - Google Patents

Description

The present invention relates to a driving ability assessment system and a driving ability assessment method for assessing the driving ability of a vehicle driver.

A known example of this type of device is one that measures a driver's safe driving ability (see, for example, Patent Document 1). This device intermittently applies a load to the driver through audio output to distract them, calculates steering entropy values that represent steering error under both a loaded and unloaded condition, and evaluates the driver's safe driving ability based on the difference between the error evaluation values calculated under the loaded and unloaded conditions.

By assessing the driving ability of elderly drivers and providing them with an opportunity to consider surrendering their driver's license or adopting driving assistance features as necessary, we can improve road safety and contribute to the development of sustainable transportation systems.

JP 2014-174848 A

However, the device described in Patent Document 1 above requires imposing a load on the driver in order to evaluate their safe driving ability, which interferes with driving.

One aspect of the present invention, a driving ability assessment system, includes an information acquisition unit that acquires steering angle data indicating changes in the vehicle's steering angle over time, along with information on whether steering assistance is being provided by a steering assistance function that assists the vehicle driver in steering, and an evaluation value calculation unit that calculates an evaluation value representing the driver's steering characteristics based on the steering angle data acquired by the information acquisition unit. The evaluation value calculation unit calculates the evaluation value by weighting, among the steering angle data acquired by the information acquisition unit, first steering angle data during periods when steering assistance is not being provided by the steering assistance function more heavily than second steering angle data during periods when steering assistance is being provided by the steering assistance function.

A driving ability assessment method according to another aspect of the present invention includes an information acquisition step executed by a computer to acquire steering angle data indicating changes in the steering angle of the vehicle over time, along with information on whether steering assistance is being provided by a steering assistance function that assists the driver in steering the vehicle, and an evaluation value calculation step to calculate an evaluation value representing the driver's steering characteristics 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 steering assistance is not being provided by the steering assistance function more heavily than second steering angle data during a period when steering assistance is being provided by the steering assistance function.

This invention makes it possible to assess driving ability without interfering with driving.

FIG. 1 is a diagram for explaining a driving section and a driving load. 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; FIG. 3 is a diagram for explaining fluctuations in the steering angle of a vehicle. FIG. 10 is a diagram illustrating an example of a degree display of the degree of steering shake. 3 is a time chart for explaining the state of the steering assist function taken into account by the evaluation value calculation unit of FIG. 2 ; 3 is a flowchart showing an example of an evaluation process executed by the calculation unit of FIG. 2 . 3 is a flowchart showing an example of a weighting process executed by the calculation unit of FIG. 2 . 10 is a flowchart showing another example of weighting processing executed by the calculation unit of FIG. 2 .

Embodiments of the present invention will now be described with reference to Figures 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 can be determined based on driving data when the driver drives a vehicle, allowing the driver and their family to understand trends in cognitive function decline and support safe driving.

Figure 1 is a diagram explaining driving sections and driving load. As shown in Figure 1, the driving load imposed on a driver due to driving behavior changes depending on the driving section, such as road shape. For example, driving load increases when driving on S-curves or winding roads, or when parking in a parking space. That is, 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 conjunction 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.

On the other hand, there is almost no driving load when driving on straight roads. 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.

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

However, even in no-load or low-load sections, for example, when driving on a single-lane highway (two-way traffic section) with no median strip, the driver needs to be aware of the conditions in their own lane and the oncoming lane. In this case, shifting their gaze between their own lane and the oncoming lane increases the driver's mental activity and increases the cognitive load (hereinafter referred to as "cognitive load"). Gaze shifts are also 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, thereby increasing the cognitive load.

Furthermore, when making a turn at an intersection to change the vehicle's direction of travel and cross the oncoming lane (a right turn in countries and regions where vehicles drive on the left, or a left turn in countries and regions where vehicles drive on the right; hereafter referred to simply as a "right turn"), the driver must 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 vehicle's target trajectory. In this case, too, the driver's gaze must shift between the oncoming lane ahead and the lane ahead, increasing the cognitive load.

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

However, when a driver is receiving assistance from the vehicle's driving assistance functions, particularly steering assistance, it becomes difficult to evaluate the driver's own driving stability based on driving data and determine the driver's driving ability related to cognitive function. Therefore, in this embodiment, the driving ability assessment system is configured as follows to appropriately assess driving ability related to cognitive function by changing the way driving data is handled depending on the state of the vehicle's steering assistance functions.

Figure 2 is a block diagram showing an example of the main components of a driving ability assessment system (hereinafter referred to as the system) 10. As shown in Figure 2, the system 10 includes a computer having a calculation unit 11 such as a CPU, a storage unit 12 such as ROM and RAM, and peripheral circuits. The calculation unit 11 functions as an information acquisition unit 13, a load determination unit 14, an evaluation value calculation unit 15, a reliability determination unit 16, a cognitive function assessment unit 17, and an information output unit 18. 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 installed in a vehicle, as a server device or the like provided external to the vehicle, or as a combination of an on-board device and an external server device or the like.

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 on a daily basis. The driving data includes at least time-series information on the status of the vehicle's steering assist function 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.

Driving data is transmitted from the vehicle to the system 10 at a predetermined interval, for example, via a TCU (telematics control unit) installed in 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 memory unit 12.

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

The evaluation value calculation unit 15 calculates an α value, which represents the average steering characteristics of an individual driver, and an Hp value, which represents the steering characteristics of the driver when cognitive load increases, based on the steering angle data stored in the memory unit 12. More specifically, the evaluation value calculation unit 15 calculates the α value based on 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 steering angle data for a period determined by the load determination unit 14 to be traveling in a specific section.

Figure 3 is a diagram explaining fluctuations in the steering angle θ of a vehicle. When the vehicle is being driven stably, steering is smooth and the fluctuations in the steering angle θ are small. On the other hand, when the vehicle is being driven unstable, steering becomes shaky and the fluctuations in the steering angle θ become large.

More specifically, as shown in Figure 3, a predicted steering angle θp(n) at time n is calculated by second-order Taylor expansion centered on time (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 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)

Figure 4 is a diagram illustrating an example of a frequency display of the degree of steering error, showing an example of a 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 for 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 steering error there is, the sharper the frequency distribution of the prediction error e(n) will be centered at "0°," where there is no steering error, and the smaller the α value will be. On the other hand, the more steering error there is, the broader the frequency distribution of the prediction error e(n) will be and the larger the α value will be.

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 impact on steering error, it is possible to appropriately calculate the α value, which represents the driver's average steering error.

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 shown by the dashed line into nine ranges P1 to P9 based on the α value. That is, based on the eight reference values -5α, -2.5α, -α, -0.5α, 0.5α, α, 2.5α, and 5α, the steering entropy value (Hp value) is divided into nine ranges: 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 each range P1 to P9, the steering entropy value (Hp value) is calculated using the following formula (ii):
Hp=-Σpi・log ₉ pi...(ii)

The Hp value represents the smoothness of steering, and decreases as steering variance decreases and the frequency distribution of prediction error e(n) becomes sharper. It also increases as steering variance increases and the frequency distribution of prediction error e(n) becomes broader. By using steering angle data from specific sections where there is a lot of eye movement and cognitive function is significantly affected by steering variance, it is possible to appropriately calculate the Hp value, which represents the driver's steering variance when cognitive load is higher than normal.

Figure 5 is a time chart illustrating the state of the steering assist function considered by the evaluation value calculation unit 15. The steering assist function is a driving assistance function that assists the driver in steering. The steering assist function includes a function that detects the driving lane using a camera or the like and issues a warning with steering vibration if there is a risk that the vehicle will deviate from the driving lane, and a function that assists steering operation so that the vehicle stays near the center of the driving lane. Even if the steering assist function is activated, it may not operate normally if the camera or the like cannot recognize the preceding vehicle or the driving lane due to blurred lane markings, weather conditions, etc.

The time-series information regarding the status of the vehicle's steering assist function acquired by the information acquisition unit 13 includes information on whether the steering assist function is activated, information on whether steering assist is actually being performed, and information on whether the driving lane is recognized by a camera or the like.

As shown in FIG. 5, of the steering angle data acquired by the information acquisition unit 13 and stored in the memory unit 12, steering angle data acquired during a period when steering assistance is not being provided by the steering assistance function will be referred to as "first steering angle data" below. More specifically, steering angle data acquired during a period when the steering assistance function is activated and when steering assistance is not being provided (t1 to t4, t5 onward) will be referred to as "first steering angle data." Furthermore, steering angle data acquired during a period when steering assistance is being provided by the steering assistance function will be referred to as "second steering angle data." More specifically, steering angle data acquired during a period when the steering assistance function is activated and when steering assistance is being provided (t4 to t5) will be referred to as "second steering angle data." However, steering angle data acquired during a period when the driving lane is not recognized by a camera or the like and when steering assistance is not being provided (t2 to t3) will be excluded from the first steering angle data and treated as the second steering angle data.

(Weighting of evaluation values)
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.

(Weighting of alpha value - weighting of frequency)
When calculating the α value after weighting, the evaluation value calculation unit 15 first calculates a predicted steering angle θp1(n) and a prediction error e1(n) based on the first steering angle data for the period in which the load determination unit 14 determines that the vehicle is traveling in a no-load/low-load zone. The evaluation value calculation unit 15 also calculates a predicted steering angle θp2(n) and a prediction error e2(n) based on the second steering angle data for the same period. Next, the evaluation value calculation unit 15 multiplies the frequency of the prediction error e1(n) (frequency distribution shown by the solid line in FIG. 4 ) by a weighting coefficient W1 (0<W1, e.g., W1=1), multiplies the frequency of the prediction error e2(n) by a weighting coefficient W2 (0≦W2<W1, e.g., W2=0), and sums these. The evaluation value calculation unit 15 calculates the α value as the 90th percentile value in the frequency distribution of the weighted and summed prediction errors (W1e1(n) + W2e2(n)).

(Weighting of Hp values - weighting of frequency)
When calculating the Hp value after weighting, the evaluation value calculation unit 15 first calculates a predicted steering angle θp1(n) and a prediction error e1(n) based on the first steering angle data for the period during which the load determination unit 14 determines that the vehicle is traveling through a specific section. The evaluation value calculation unit 15 also calculates a predicted steering angle θp2(n) and a prediction error e2(n) based on the second steering angle data for the same period. Next, the evaluation value calculation unit 15 multiplies the frequency of the prediction error e1(n) (frequency distribution indicated by the dashed line in FIG. 4 ) by a weighting coefficient W1 (0<W1, for example, W1=1), multiplies the frequency of the prediction error e2(n) by a weighting coefficient W2 (0≦W2<W1, for example, W2=0), and adds these results together. The evaluation value calculation unit 15 divides the frequency distribution of the weighted and summed prediction errors (W1e1(n) + W2e2(n)) into ranges P1 to P9 based on the α value, and calculates the Hp value using formula (ii) based on the proportions p1 to p9 of each range P1 to P9.

(Weighting of Hp values - direct weighting)
When calculating the Hp value after weighting, the evaluation value calculation unit 15 may calculate an Hp1 value based on the first steering angle data and an Hp2 value based on the second steering angle data, and multiply the calculated Hp1 value and Hp2 value by weighting coefficients W1 and W2. 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 for a period during which the load determination unit 14 determines that the vehicle is traveling in a specific section. In addition, the evaluation value calculation unit 15 calculates the predicted steering angle θp2(n), the prediction error e2(n), and the Hp2 value based on the second steering angle data for the same period. The evaluation value calculation unit 15 multiplies the Hp1 value by a weighting coefficient W1 (0<W1, for example, W1=1) and multiplies the Hp2 value by a weighting coefficient W2 (0≦W2<W1, for example, W2=0), and calculates the sum of these (W1Hp1+W2Hp2) as the Hp value.

The reliability determination unit 16 determines whether the evaluation value (Hp value) is reliable based on the frequency at which steering assistance is performed. More specifically, the reliability determination unit 16 calculates the frequency of steering assistance based on the driving data acquired by the information acquisition unit 13 and compares the calculated frequency with a predetermined threshold to determine whether the Hp value is reliable. In other words, if the frequency of steering assistance is higher than the threshold, the driver's steering is unstable, making it difficult to properly calculate the Hp value, which represents the driver's steering deviation. Therefore, the Hp value calculated during such a period is determined to be unreliable. The frequency of steering assistance is calculated, for example, as the number of times the steering assistance function is activated while the steering assistance function is active and the driving lane is recognized by a camera or the like. The frequency of steering assistance may be calculated as the number of times the steering assistance function is activated per unit driving time (times/h) or the number of times it is activated per unit driving distance (times/km).

When the reliability determination unit 16 determines that the Hp value is reliable, the cognitive function evaluation unit 17 evaluates the driver's cognitive function based on the Hp value calculated by the evaluation value calculation unit 15. In other words, by continuously monitoring the Hp value, which represents steering fluctuations when cognitive load increases, it is possible to evaluate a trend toward a decline in the driver's cognitive function. For example, if the Hp value, calculated periodically (e.g., monthly) based on driving data from daily driving, is on the rise, it is evaluated that the driver's cognitive function is on the decline.

When the reliability determination unit 16 determines that the Hp value is unreliable, the cognitive function evaluation unit 17 evaluates the driver's cognitive function based on the frequency of steering assistance calculated by the reliability determination unit 16. For example, if the frequency of steering assistance per predetermined period (e.g., one month) is on an increasing trend, the cognitive function evaluation unit 17 evaluates that the cognitive function is on a declining trend. When the reliability determination unit 16 determines that the Hp value is unreliable, the cognitive function evaluation unit 17 may evaluate the driver's cognitive function using other parameters included in the driving data instead of or in addition to the frequency of steering assistance. For example, if the driving data includes time-series acceleration data indicating changes in vehicle acceleration, the cognitive function evaluation unit 17 may calculate the frequency of sudden braking where acceleration (deceleration) exceeds a predetermined threshold, and evaluate the driver's cognitive function based on the calculated frequency of sudden braking.

The information output unit 18 transmits the evaluation results from the cognitive function evaluation unit 17 to a user device such as the driver or a family member. For example, a notification can be sent to a pre-registered email address. In this case, the notification can prompt the driver or a family member to consider returning their driver's license or switching to a vehicle with enhanced driving assistance functions. Because objective information based on driving data is provided, it is easier for the driver to accept the current state of their cognitive function and consider appropriate measures early on.

Figure 6 is a flowchart showing an example of the 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 for the no-load/low-load section, it is determined whether the driving section per unit time is a specific section.

Next, in step S3, the α value is calculated based on the steering angle data for the period determined in step S2 to be traveling in a no-load/low-load section. Next, in step S4, the Hp value is calculated based on the α value calculated in step S3 and the steering angle data for 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 the memory unit 12.

Next, in step S5, the frequency at which steering assistance was performed is calculated based on the driving data read in step S1. The latest frequency calculated in step S5 is stored and accumulated in the memory unit 12. Next, in step S6, it is determined whether the Hp value calculated in step S4 is reliable based on the frequency calculated in step S5. If the result in step S6 is positive, the process proceeds to step S7, where the latest Hp value stored in the memory unit 12 is compared with previous Hp values to determine the driver's driving ability related to cognitive function. On the other hand, if the result in step S6 is negative, the process proceeds to step S8, where the latest frequency stored in the memory unit 12 is compared with previous frequencies to determine the driver's driving ability related to cognitive function. Next, in step S9, the evaluation results of steps S7 and S8 are sent to a pre-registered email address, and the process ends.

In this way, the α value and Hp value, which are indicators for assessing a driver's driving ability, can be calculated based solely on daily driving data, making it possible to assess driving ability without interfering with driving (steps S1-S4). Furthermore, the driver's cognitive function is automatically assessed based solely on daily driving data, and the assessment results are notified to the driver and their family, reducing the burden on family members living far away from the elderly driver (steps S1-S9).

Figure 7 is a flowchart showing an example of weighting processing executed by the calculation unit 11 of the system 10, and shows an example of weighting processing in which the frequency of prediction error is multiplied by a weighting coefficient in the process of calculating evaluation values (α value, Hp value). The processing shown in this flowchart is executed in steps S3 and/or S4 of Figure 6.

(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.

(Weighting of Hp values - weighting of frequency)
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.

(Weighting of Hp values - 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 of FIG. 6 in which the evaluation value (Hp value) is directly multiplied by a weighting factor. Steps S1 to S3 and S5 to S9 in FIG. 8 are similar to steps S1 to S3 and S5 to S9 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 predicted 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 predicted 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 factor W1, and the Hp2 value calculated in step S4A is multiplied by a weighting factor 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).

When the steering assist function is activated, the driver receives a warning accompanied by steering vibration and steering assistance (steering force is applied), making it difficult to evaluate the driver's own driving stability based on steering angle data and determine the driver's cognitive function-related driving ability. On the other hand, when steering assistance is not provided in a normal state where the lane is recognized by a camera or other device, the driver's own steering is stable, and the vehicle is traveling near the center of the lane due to the driver's own steering. By actively utilizing the first steering angle data during periods when the driver's steering is stable, i.e., by weighting the first steering angle data more heavily than the second steering angle data to calculate the evaluation value, driving ability can be accurately determined (steps S11, S4B).

For example, if the first steering angle data is actively used to calculate the Hp value, it is possible to evaluate the driver's steering characteristics when the cognitive load increases while steering is stable. In this case, the accuracy of the Hp value, which is calculated and accumulated periodically, is improved, allowing for a more accurate evaluation of the driver's cognitive function. Furthermore, if the first steering angle data is also actively used to calculate the α value, it is possible to evaluate the driver's steering characteristics while steering is stable, and the accuracy of the α value is improved, allowing for an even more accurate evaluation of the driver's cognitive function.

According to this embodiment, the following effects can be achieved.
(1) The system 10 includes an 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 steering assistance is being provided by a steering assistance function that assists the driver of the vehicle in steering, and an evaluation value calculation unit 15 that calculates an evaluation value that represents the steering characteristics of the driver based on the steering angle data acquired by the information acquisition unit 13 ( FIG. 2 ). The evaluation value calculation unit 15 calculates the evaluation value by assigning a greater weight to first steering angle data, of the steering angle data acquired by the information acquisition unit 13, during a period when steering assistance is not being provided by the steering assistance function, than to second steering angle data during a period when steering assistance is being provided by the steering assistance function.

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 steering assist function is activated and steering assistance is being provided by the steering assist function, an alert is issued with steering vibration, and steering operation is assisted (steering force is applied). By actively utilizing the first steering angle data from periods when steering assistance is not being provided by the steering assist function, the driver's own driving stability can be evaluated based on the steering angle data, and the driver's driving ability related to their cognitive function can be determined.

(2) The information acquisition unit 13 further acquires information on whether the steering assist function is activated. The first steering angle data is steering angle data for a period when the steering assist function is activated and steering assist is not being performed. The second steering angle data is steering angle data for a period when the steering assist function is activated and steering assist is being performed. When steering assist is not being performed in a normal state where the driving lane is recognized by a camera or the like, the driver's own steering is stable, and by actively using the first steering angle data for such a period, driving ability can be accurately determined.

(3) The steering assist function provides steering assist based on the results of lane recognition by a camera or the like mounted on the vehicle. The information acquisition unit 13 further acquires information on whether the lane is recognized by a camera or the like. The first steering angle data is steering angle data from a period when the lane is recognized by a camera or the like and steering assist is not being performed. The second steering angle data further includes steering angle data from a period when the lane is not recognized by a camera or the like and steering assist is not being performed. For example, even during a period when steering assist is not being performed, steering angle data from a period when the steering assist function is simply not operating normally, such as when the lane cannot be recognized due to blurred lane markings or weather conditions, is treated as second steering angle data. This enables the driver's driving ability to be determined more accurately.

(4) The system 10 further includes a load determination unit 14 that determines whether a predetermined cognitive load is acting on the driver based on the steering angle data acquired by the information acquisition unit 13 (Figure 2). The evaluation value calculation unit 15 calculates an α value that represents the driver's average steering characteristics based on the steering angle data acquired by the information acquisition unit 13, and calculates an Hp value that represents the driver's steering characteristics when a predetermined cognitive load is acting based on the calculated α value and the steering angle data acquired by the information acquisition unit 13 for a period during which the load determination unit 14 determines that a predetermined cognitive load is acting.

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 when steering assistance is not being provided, the driver's own steering is stable, and cognitive load is high, the Hp value can be accurately calculated, and the driver's cognitive function can be accurately evaluated. Furthermore, because the steering angle data used to calculate the α value is used regardless of the state of the steering assistance function, ensuring a sufficient amount of data makes it possible to appropriately calculate the α value, which represents the driver's average steering characteristics.

(5) The evaluation value calculation unit 15 calculates the α value by weighting the first steering angle data greater than the weighting of the second steering angle data, and calculates the Hp value by weighting the first steering angle data greater than the weighting of the second steering angle data. For example, if 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 first steering angle data when the driver's own steering is stable and cognitive load is high.

(6) The system 10 further includes a reliability determination unit 16 that determines whether the evaluation value is reliable based on the frequency with which steering assistance is provided (Figure 2). That is, if the frequency of steering assistance is higher than a predetermined frequency, the driver's steering is unstable, making it difficult to properly calculate an evaluation value that represents the driver's steering deviation. In this case, evaluation using other methods may be performed. For example, if the frequency of steering assistance per predetermined period (e.g., one month) is on the rise, it can be evaluated that cognitive function is on the decline.

In the above embodiment, an example was described in which the α value was calculated based on steering angle data when traveling through a no-load/low-load section, and the Hp value was calculated based on steering angle data when traveling through 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 steering angle data for each driver.

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, executed by a computer, for acquiring steering angle data indicating changes in the vehicle's steering angle over time, along with information on whether steering assistance is being provided by a steering assistance function that assists the vehicle driver in steering, 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 (see FIGS. 6-8). In the evaluation value calculation steps S3, S4, S10-S12, and S4A-A4C, the evaluation value is calculated by weighting, among the steering angle data acquired in the information acquisition step S1, first steering angle data during periods when steering assistance is not being provided by the steering assistance function more heavily than second steering angle data during periods when steering assistance is being provided by the steering assistance function.

The above description is merely an example, and the present invention is not limited to the above-described embodiments and variations, as long as the features of the present invention are not impaired. It is also possible to combine one or more of the above embodiments and variations in any desired manner, and it is also possible to combine variations together.

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. Reliability assessment unit, 17. Cognitive function assessment unit, 18. Information output unit

Claims (8)

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 steering assistance is being performed by a steering assistance function that assists the driver of the vehicle in steering;
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 increasing the weight of first steering angle data during a period in which steering assistance is not being provided by the steering assistance function, among the steering angle data acquired by the information acquisition unit, compared to the weight of second steering angle data during a period in which steering assistance is being provided by the steering assistance function. 2. The driving ability determination system according to claim 1,
The information acquisition unit further acquires information on whether the steering assist function is activated,
the first steering angle data is steering angle data during a period when the steering assist function is activated and the steering assist is not being performed,
A driving ability determination system, characterized in that the second steering angle data is steering angle data during a period when the steering assist function is activated and the steering assist is being performed. 3. The driving ability determination system according to claim 1,
the steering assist function performs the steering assist based on a result of recognition of a driving lane by a sensor mounted on the vehicle,
The information acquisition unit further acquires information on whether the driving lane is recognized by the sensor,
the first steering angle data is steering angle data during a period in which the driving lane is recognized by the sensor and the steering assist is not being performed,
A driving ability determination system, characterized in that the second steering angle data further includes steering angle data for a period when the driving lane is not recognized by the sensor and the steering assistance is not being performed. 3. 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. 3. 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. 3. The driving ability determination system according to claim 1,
A driving ability determination system further comprising a reliability determination unit that determines whether the evaluation value is reliable or not based on the frequency with which the steering assistance is performed. Each of the methods is executed by a computer.
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 steering assistance is being performed by a steering assistance function that assists the driver of the vehicle in steering;
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 steering assistance is not being provided by the steering assistance function, 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 steering assistance is being provided by the steering assistance function. 8. The driving ability determination method according to claim 7,
In the information acquisition step, information on whether the steering assist function is activated is further acquired,
the first steering angle data is steering angle data during a period when the steering assist function is activated and the steering assist is not being performed,
A driving ability determination method, characterized in that the second steering angle data is steering angle data during a period when the steering assist function is activated and the steering assist is being performed.