DRIVER DISTRACTED STATE DETERMINATION APPARATUS, CIRCUIT AND COMPUTER PROGRAM THEREFOR

A controller acquires a driving load score based on the travel environment information, acquires a distracted state occurrence score based on the driving load score and an elapsed time with the driving load score, acquires a search behavior score based on the travel environment information and the driver's sightline when the distracted state occurrence score is equal to or higher than a specified value, acquires a distracted state level of the driver based on the search behavior score and an elapsed time with the search behavior score, and determines that the driver is in the distracted state when the distracted state level is equal to or higher than a threshold and the search behavior score is increased in response to an increase in the driving load score.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority to Japanese Patent Application No. 2022-151226 filed in the Japanese Patent Office on Sep. 22, 2022, the entire contents of which being incorporated herein by reference.

TECHNICAL FIELD

The present disclosure relates to a driver state determination apparatus that determines a state of a driver who drives a vehicle.

BACKGROUND ART

One of main causes of traffic accidents is a state where a driver lacks concentration on driving, i.e., a so-called distracted state. Conventionally, as techniques for detecting the distracted state, the following techniques have been proposed: a technique of focusing on change amounts of the driver's face direction and sightline direction (for example, see Patent document 1), a technique of focusing on the number of times of visual recognition behavior (for example, see Patent document 2), a technique of focusing on the driver's degree of concentration and degree of comfort on driving (for example, see Patent document 3), and the like.

PRIOR ART DOCUMENTS

Patent Documents

SUMMARY

Problems to be Solved

However, in the related art as described above, even in the case where, due to a mild disease, aging, or the like, the change amounts of the driver's face direction and sightline direction or the number of times of the visual recognition behavior is reduced, or the driver's degree of concentration on driving is reduced, the driver may be determined to be in the distracted state. In other words, in the related art, the driver's distracted state cannot be distinguished from another abnormal state of the driver, such as the disease, and accurately determine the driver's distracted state.

Embodiments are directed solving this and other problems and therefore has a purpose of providing a driver state determination apparatus capable of distinguishing a driver's distracted state from another abnormal state of the driver, such as a disease, and promptly and accurately determining the driver's distracted state.

Means for Solving the Problems

In order to solve the above-described and other problems, a driver state determination apparatus that determines a state of a driver who drives a vehicle, may include: a travel environment information acquisition device that acquires travel environment information of the vehicle; a sightline detector that detects the driver's sightline; and a controller configured to determine the driver's state based on the travel environment information and the driver's sightline. The controller is configured to: acquire a driving load score based on the travel environment information, the driving load score representing a magnitude of a load on the driver during driving of the vehicle; acquire a distracted state occurrence score based on the driving load score and an elapsed time with the driving load score, the distracted state occurrence score representing a degree of likelihood that the driver is brought into a distracted state; acquire a search behavior score based on the travel environment information and the driver's sightline in the case where the distracted state occurrence score is equal to or higher than a specified value, the search behavior score representing a degree of normality of search behavior by the driver's visual perception; acquire a distracted state level of the driver based on the search behavior score and an elapsed time with the search behavior score; and determine that the driver is in the distracted state in the case where the distracted state level is equal to or higher than a threshold and where the search behavior score is increased in response to an increase in the driving load score.

Accordingly, the controller acquires the distracted state occurrence score, which represents the degree of likelihood that the driver is brought into the distracted state, based on the driving load score and the elapsed time with the driving load score. Thus, in a situation where the driver is likely to be in the distracted state according to the driving load, whether the driver is in the distracted state may be promptly determined. In addition, in the case where the distracted state occurrence score is equal to or higher than the specified value, the controller acquires the search behavior score, which represents the degree of normality of the search behavior by the driver's visual perception, based the travel environment information and the driver's sightline. Then, the controller acquires the distracted state level of the driver based the search behavior score and the elapsed time with the search behavior score. Thus, the distracted state may be promptly determined based on the degree of normality of the search behavior, which is easily affected by the distracted state. Furthermore, in the case where the distracted state level is equal to or higher than the threshold, and the search behavior score is increased in response to the increase in the driving load score, the controller determines that the driver is in the distracted state. Thus, the distracted state may be accurately determined by focusing on a change that appears characteristically at the time when the driver is in the distracted state but not in an abnormal state (that the search behavior becomes normal when the driving load is increased and thus a behavior request for the driver is enhanced) and distinguishing such a change from a change in the abnormal state. In this way, the driver's distracted state may be distinguished from another abnormal state, such as a disease, and promptly and accurately determine the driver's distracted state.

The controller may be configured to: acquire a cognitive load score, which represents a magnitude of a load on the driver to recognize an object in travel environment of the vehicle, and an operation load score, which represents a magnitude of a load to operate the vehicle in the travel environment, based on the travel environment information; and acquire the driving load score on the basis of the cognitive load score and the operation load score.

Accordingly, the controller acquires the driving load score based on the cognitive load score and the operation load score. Thus, a magnitude of the driving load may be evaluated in consideration of a cognitive load and an operation load, which affect likelihood of occurrence of the distracted state. Thus, a more accurate distracted state occurrence score may be determined.

The controller may be configured to: acquire a surprise value, which represents a distance between a predicted position and an actual position of the object that attracts the driver's attention, based on the travel environment information; and calculate the search behavior score such that the search behavior score is increased as a tendency of the driver's sightline to be directed to the object with the relatively high surprise value is increased.

Accordingly, the controller calculates the driver's search behavior score based on a behavioral principle of a person that the driver in a normal state directs his/her sightline to the object with the relatively high surprise value. Thus, the search behavior score, to which the driver's state is further accurately reflected, may be acquired.

Advantages

According to the driver state determination apparatus described herein, the driver's distracted state may be distinguished from the other abnormal state, such as the disease, and promptly and accurately determine the driver's distracted state.

DETAILED DESCRIPTION

A description will hereinafter be made on a driver state determination apparatus according to an embodiment with reference to the accompanying drawings.

First, a description will be made on a configuration of the driver state determination apparatus according to this embodiment with reference toFIG.1andFIG.2.FIG.1is an explanatory view of a vehicle on which the driver state determination apparatus is mounted, andFIG.2is a block diagram of the driver state determination apparatus.

A vehicle1according to this embodiment includes: drive power sources2such as an engine and an electric motor that output drive power; a transmission3that transmits the drive power output from the drive power source2to drive wheels; a brake4that applies a braking force to the vehicle1; and a steering device5for steering the vehicle1.

A driver state determination apparatus100is configured to determine a state of a driver of the vehicle1and to execute control of the vehicle1and driving assistance control when necessary. As illustrated inFIG.2, the driver state determination apparatus100has a controller10, plural sensors, plural control systems, and plural information output devices.

More specifically, the plural sensors include an outside camera21and a radar22for acquiring travel environment information of the vehicle1as well as a navigation system23and a positioning system24for detecting a position of the vehicle1. The plural sensors also include a vehicle speed sensor25, an acceleration sensor26, a yaw rate sensor27, a steering angle sensor28, a steering torque sensor29, an accelerator sensor30, and a brake sensor31for detecting behavior of the vehicle1and the driver's driving operation. The plural sensors further include an in-vehicle camera32for detecting the driver's sightline. The plural control systems include: a powertrain control module (PCM)33that controls the drive power source2and the transmission3; a dynamic stability control system (DSC)34that controls the drive power source2and the brake4; and an electric power steering system (EPS)35that controls the steering device5. The plural information output devices include a display36that outputs image information and a speaker37that outputs voice information.

In addition, as other sensors, a peripheral sonar system that measures a distance and a position of a peripheral structure relative to the vehicle1, a corner radar that measures approach of the peripheral structure at each of four corner sections of the vehicle1, and various sensors (for example, a heart rate sensor, an electrocardiogram sensor, a steering wheel grip force sensor, and the like) that detect the driver's state may be included.

The controller10executes various arithmetic operations based on signals received from the plural sensors, transmits, to the PCM33, the DSC34, and the EPS35, a control signal for appropriately actuating the drive power source2, the transmission3, the brake4, and the steering device5, and transmits, to the display36and the speaker37, a control signal for outputting desired information. The controller10is a computer that includes one or more processors10a(typically, a CPU), memory10b(ROM, RAM, and the like, e.g., a non-transitory storage device) that stores various programs and data, an input/output device, and the like. As used herein ‘computer’ refers to circuitry that may be configured via the execution of computer readable instructions, and the circuitry may include one or more local processors10a(e.g., CPU's), and/or one or more remote processors, such as a cloud computing resource, or any combination thereof.

The outside camera21captures an image, e.g., a visible image, an infrared image, or the like, around the vehicle1and outputs image data. The controller10identifies an object (for example, a preceding vehicle, a parked vehicle, a pedestrian, a travel road, a lane marking (a lane divider, a white line, or a yellow line), a traffic signal, a traffic sign, a stop line, an intersection, an obstacle, or the like) based on the image data received from the outside camera21. The outside camera21corresponds to an example of the “travel environment information acquisition device” in the disclosure.

The radar22measures a position and a speed of the object (particularly, the preceding vehicle, the parked vehicle, the pedestrian, a dropped object on the travel road, or the like). For example, a millimeter-wave radar can be used as the radar22. The radar22transmits a radio wave in an advancing direction of the vehicle1, and receives a reflected wave generated when the object reflects the transmitted wave. Then, based on the transmitted wave and the received wave, the radar22measures a distance between the vehicle1and the object (for example, an inter-vehicular distance) and a relative speed of the object to the vehicle1. In this embodiment, instead of the radar22, a laser radar, an ultrasonic sensor, or the like may be used to measure the distance from and the relative speed of the object. Alternatively, the plural sensors may be used to constitute a position and speed measuring device. The radar22corresponds to an example of the “travel environment information acquisition device” in the disclosure.

The navigation system23stores map information therein and can provide the map information to the controller10. Based on the map information and current vehicle position information, the controller10identifies a road, the intersection, the traffic signal, a building, or the like that exists around (particularly, in the advancing direction of) the vehicle1. The map information may be stored in the controller10. The positioning system24is a GPS system and/or a gyroscopic system, and detects the position of the vehicle1(the current vehicle position information). Each of the navigation system23and the positioning system24also corresponds to an example of the “travel environment information acquisition device” in the disclosure.

The vehicle speed sensor25detects a speed of the vehicle1based on a rotational speed of the wheel or a driveshaft, for example. The acceleration sensor26detects acceleration of the vehicle1. This acceleration includes acceleration in a front-rear direction of the vehicle1and acceleration in a lateral direction (that is, lateral acceleration) thereof. In the present specification, the acceleration includes not only a change rate of the speed in a speed increasing direction but also a change rate of the speed in a speed reducing direction (that is, deceleration).

The yaw rate sensor27detects a yaw rate of the vehicle1. The steering angle sensor28detects a rotation angle (a steering angle) of the steering wheel of the steering device5. The steering torque sensor29detects torque (steering torque) applied to a steering shaft via the steering wheel. The accelerator sensor30detects a depression amount of an accelerator pedal. The brake sensor31detects a depression amount of a brake pedal.

The in-vehicle camera32captures an image of the driver and outputs image data. The controller10detects the driver's sightline direction based on the image data received from the in-vehicle camera32. The in-vehicle camera32corresponds to an example of the “sightline detector” in the disclosure.

The PCM33controls the drive power source2of the vehicle1to adjust the drive power of the vehicle1. For example, the PCM33controls an ignition plug of the engine, a fuel injection valve, a throttle valve, a variable valve mechanism, the transmission3, an inverter that supplies electric power to the electric motor, and the like. When the vehicle1has to be accelerated or decelerated, the controller10transmits the control signal to the PCM33so as to adjust the drive power.

The DSC34controls the drive power source2and the brakes4of the vehicle1and thereby executes deceleration control and posture control of the vehicle1. For example, the DSC34controls a hydraulic pump, a valve unit, and the like of the brake4, and controls the drive power source2via the PCM33. When it is necessary to execute the deceleration control or the posture control of the vehicle1, the controller10transmits the control signal to the DSC34so as to adjust the drive power or generate the braking force.

The EPS35controls the steering device5of the vehicle1. For example, the EPS35controls the electric motor, which applies the torque to the steering shaft of the steering device5, and the like. When the advancing direction of the vehicle1has to be changed, the controller10transmits the control signal to the EPS35so as to change a steering direction.

The display36is provided in front of the driver in a cabin and displays the image information to the driver. As the display36, for example, a liquid-crystal display or a head-up display is used. The speaker37is installed in the cabin and outputs various types of the voice information.

Next, a description will be made on a flow of driver state determination processing by the driver state determination apparatus100in this embodiment with reference toFIG.3.FIG.3is a flowchart of the driver state determination processing.

The driver state determination processing is initiated when a power supply of the vehicle1is turned on. Then, the driver state determination processing is repeatedly executed by the controller10in a specified cycle (for example, every 0.05 to 0.2 second).

When the driver state determination processing is initiated, first, the controller10acquires various types of information including the travel environment information and the driver's sightline based on the signals that are received from the sensors including the outside camera21, the radar22, the navigation system23, the positioning system24, and the in-vehicle camera32(step S1).

Next, based on the travel environment information acquired in step S1, the controller10acquires a cognitive load score that represents a magnitude of a load for the driver to recognize the object in the travel environment of the vehicle1(step S2). More specifically, a cognitive load score table is stored in the memory10bin advance. In the cognitive load score table, factors, each of which affects the driver's cognitive load, are each associated with scores, each of which represents a magnitude of the cognitive load corresponding to each of the factors, in advance.FIG.4is an example of a cognitive load score table. In the example illustrated inFIG.4, the number of the objects to be seen by the driver during driving, an angle between the objects, prominence (a degree of saliency) of the object, and a moving speed of the object are set as the factors (cognitive load factors), each affect the cognitive load. As can be seen inFIG.4, the cognitive load score increases as (1) the number of the objects to be seen increases, (2) the angle between the objects increases, (3) the degree of saliency of the object increases, and/or (4) the moving speed of the object increases. The controller10acquires a value of each of the cognitive load factors based on the travel environment information acquired from the outside camera21and the radar22. Then, the controller10calculates an average value of the cognitive load scores, each of which corresponds to the value of the respective cognitive load factor, as the cognitive load score in the current travel environment.

Next, based on the travel environment information acquired in step S1, the controller10acquires an operation load score that represents a magnitude of a load for the driver to operate the vehicle1in the travel environment of the vehicle1(step S3). More specifically, an operation load score table is stored in the memory10bin advance. In the operation load score table, factors, each of which affects the driver's operation load, are each associated with scores, each of which represents a magnitude of the operation load corresponding to each of the factors, in advance.FIG.5is an example of the operation load score table. In the example illustrated inFIG.5, a radius of curvature of a road curve, presence or absence of loss of an own lane, a signal color, and deceleration of the preceding vehicle are set as the factors (operation load factors), each of which affects the operation load. In addition, as may be seen inFIG.5, the operation load score increases (1) as the radius of curvature decreases, (2) when the loss of the own lane is present is compared to a situation in which the loss of the own lane is absent, (3) based on a traffic signal color, in an order of green (go), yellow (caution), and red (stop), and/or (4) as the deceleration of the preceding vehicle increases. The controller10acquires a value of each of the operation load factors based on the travel environment information acquired from the outside camera21, the radar22, the navigation system23, and the positioning system24. Then, the controller10calculates an average value of the operation load scores, each of which corresponds to the value of the respective operation load factor, as the operation load score in the current travel environment.

Next, the controller10calculates a driving load score based on the cognitive load score acquired in step S2and the operation load score acquired in step S3(step S4). More specifically, a driving load score map in which a driving load score is set is stored in the memory10bin advance. The driving load score corresponds to the cognitive load score and the operation load score.FIG.6is an example of the driving load score map. As may be seen in the example illustrated inFIG.6, the driving load score increases as the cognitive load score increases and/or as the operation load score increases. For example, in the case where the cognitive load score is 2 and the operation load score is 1, the driving load score is 4. In the case where the cognitive load score is 4 and the operation load score is 3, the driving load score is 10. The controller10refers to this driving load score map and acquires the driving load score that corresponds to the cognitive load score acquired in step S2and the operation load score acquired in step S3.

Next, based on the driving load score acquired in step S4and an elapsed time with the driving load score, the controller10acquires a distracted state occurrence score representing a degree of likelihood that the driver is brought into the distracted state (step S5). More specifically, a distracted state occurrence score map in which a distracted state occurrence score is set is stored in the memory10bin advance. The distracted state occurrence score corresponds to the driving load score and the elapsed time with the driving load score.FIG.7is an example of a distracted state occurrence score map. As may be seen inFIG.7, the distracted state occurrence score increases as the driving load score decreases and/or as the elapsed time increases. This is because, in the case where the low driving load continues for a long time, the driver is more likely to be brought into the distracted state. Every time the controller10acquires the driving load score in the driver state determination processing, which is executed repeatedly, the controller10stores the driving load score and time of acquisition. Then, after acquiring the driving load score in step S4, the controller10refers to the distracted state occurrence score map and acquires the distracted state occurrence score that corresponds to the driving load score acquired in step S4and a time in which the driving load score remains the same (the elapsed time).

Next, the controller10determines whether the distracted state occurrence score acquired in step S5is equal to or higher than a specified threshold (step S6). For example, in the case where the distracted state occurrence score map illustrated inFIG.7is used, the threshold is set to 1. As a result, if the distracted state occurrence score is not equal to or higher than the threshold (is lower than the threshold) (step S6: NO), the controller10determines that the driver is unlikely to be in the distracted state, and terminates the driver state determination processing.

On the other hand, if the distracted state occurrence score is equal to or higher than the threshold (step S6: YES), the controller10calculates a search behavior score based on the travel environment information and the driver's sightline that are acquired in step S1(step S7). The search behavior score represents a degree of normality of search behavior by the driver's visual perception.

More specifically, based on the signals received from the outside camera21and the radar22, the controller10identifies a position of a visual recognition required object that should be recognized visually by the driver (the object that attracts top-down attention of the driver). The controller10also identifies distribution of the saliency (ease of attracting bottom-up attention of the driver) in front of the vehicle1based on the signal received from the outside camera21. Then, the controller10calculates a predicted position (probability distribution) after a specified time of each of the identified position of the visual recognition required object and the identified saliency distribution by a known method.

Next, the controller10acquires the actual position of the visual recognition required object and the actual saliency distribution after a specified time, and calculates a distance (for example, expressed by the Kullback-Leibler divergence) from the predicted position (the probability distribution) of each of the position of the visual recognition required object and the saliency distribution, which have been calculated earlier. The distance calculated herein is set as a surprise value for respective one of the visual recognition required object and the saliency distribution. In other words, as the distance between the predicted position and the actual position of each of the position of the visual recognition required object and the saliency distribution is increased, the surprise to the driver is increased. Thus, the driver in the normal state is highly likely to direct his/her sightline.

Then, the controller10calculates the search behavior score from the calculated surprise value such that the search behavior score is increased as a tendency of the driver's sightline to be directed at the object with the relatively high surprise value is increased. For example, the controller10generates a receiver operating characteristic (ROC) curve by plotting a probability that the surprise value in the driver's sightline direction exceeds the specified threshold and a probability that the surprise value at a random point in front of the vehicle1exceeds the specified threshold while changing the specified threshold. Then, the controller10sets the search behavior score by multiplying an area under the curve (AUC) of the ROC curve by a specified coefficient. In this case, as the tendency of the driver's sightline to be directed to the object with the high surprise value is increased, the AUC is increased, and the search behavior score is increased.

Next, the controller10calculates the driver's distracted state level based on the search behavior score and an elapsed time with the search behavior score (step S8). More specifically, a distracted state level map in which a distracted state level is set is stored in the memory10bin advance. The distracted state level corresponds to the search behavior score and the elapsed time with the search behavior score.FIG.8is an example of the distracted state level map. As can be seen inFIG.8, the distracted state level increases as the search behavior score decreases and/or as the elapsed time is increases. This is because, when a low state of the search behavior score, that is, a low state of the tendency of the driver's sightline to be directed to the object with the high surprise value continues for a long time, the driver is highly likely to be in the distracted state. Every time the controller10calculates the search behavior score in the driver state determination processing, which is executed repeatedly, the controller10stores the search behavior score and time of calculation. Then, after calculating the search behavior score in step S7, the controller10refers to the distracted state level map and acquires the distracted state level that corresponds to the search behavior score calculated in step S7and a time in which the search behavior score remains the same (the elapsed time).

Next, the controller10determines whether the distracted state level calculated in step S8is equal to or higher than a specified threshold (step S9). For example, in the case where the distracted state level map illustrated inFIG.8is used, the threshold is set to 1. As a result, if the distracted state level is not equal to or higher than the threshold (is lower than the threshold) (step S9: NO), the controller10determines that the driver is in the normal state (step S10), and terminates the driver state determination processing.

On the other hand, if the distracted state level is equal to or higher than the threshold (step S9: YES), the controller10determines whether the search behavior score has been increased in response to the increase in the driving load score (step S11). More specifically, every time the controller10acquires the driving load score and the search behavior score in the driver state determination processing, which is executed repeatedly, the controller10stores the driving load score, the search behavior score, and the time of acquisition of each thereof. Then, the controller10identifies, in time-series data, a change in the search behavior score in a period in which the increased state of the driving load score is maintained.FIG.9is a graph illustrating the change in the search behavior score at the time with the high driving load according to this embodiment. As indicated by a one-dot chain line inFIG.9, in the case where the search behavior score increases while the increased state of the driving load score is maintained, the controller10determines that the search behavior score has been increased in response to the increase in the driving load score.

That the search behavior score is increased in response to the increase in the driving load score means that, when the driving load is increased and a behavior request for the driver is enhanced, the driver can take the normal search behavior in response thereto. That is, a reason why the search behavior score is low and the distracted state level is high prior the increase in the driving load is not because the driver suffers from abnormality, such as disease, but because the driver is in the distracted state. Thus, if the search behavior score is increased in response to the increase in the driving load score (step S11: YES), the controller10determines that the driver is in the distracted state (step S12).

Next, the controller10transmits the control signal to the display36and the speaker37, and causes one or both of the display36and the speaker37to output a warning for notifying the driver that the driver is in the distracted state (step S13). At this time, the controller10may cause the display36and the speaker37to respectively output the image information and the voice information (sightline guidance information) for guiding the driver's sightline to the visual recognition required object not visually recognized by the driver. After step S13, the controller10terminates the driver state determination processing.

Meanwhile, as indicated by a dotted line in the example illustrated inFIG.9, if the search behavior score has not been increased in response to the increase in the driving load score (step S11: NO), it means that, even when the behavior request for the driver is enhanced due to the increased driving load, the driver cannot take the normal search behavior in response thereto. That is, it is considered that the reason why the search behavior score is low and the distracted state level is high prior the increase in the driving load is because the driver suffers from the abnormality, such as disease. Thus, the controller10determines that the driver is in an abnormal state (step S14).

In this case, the controller10transmits, to the PCM33, the DSC34, and the EPS35, the control signal for appropriately actuating the drive power source2, the transmission3, the brake4, and the steering device5, and executes driving assistance control of the vehicle1such that the vehicle1is safely stopped on a road shoulder, for example (step S15). In addition, the controller10may transmit the control signal at least one of to the display36and the speaker37to cause the display36and the speaker37to output the warning. After step S15, the controller10terminates the driver state determination processing.

Next, a description will be made on operational effects of the driver state determination apparatus100in the above-described embodiment.

The controller10acquires the distracted state occurrence score, which represents the degree of likelihood that the driver is brought into the distracted state, based on the driving load score and the elapsed time with the driving load score. Thus, in a situation where the driver is likely to be in the distracted state according to the driving load, whether the driver is in the distracted state may be promptly determined. In addition, in the case where the distracted state occurrence score is equal to or higher than the specified value, the controller10acquires the search behavior score, which represents the degree of normality of the search behavior by the driver's visual perception, based on the travel environment information and the driver's sightline. Then, the controller10acquires the distracted state level of the driver based on the search behavior score and the elapsed time with the search behavior score. Thus, the distracted state may be promptly determined based on the degree of normality of the search behavior, which is easily affected by the distracted state.

Furthermore, in the case where the distracted state level is equal to or higher than the threshold, and the search behavior score is increased in response to the increase in the driving load score, the controller10determines that the driver is in the distracted state. Thus, the distracted state may be accurately determined by focusing on the change that appears characteristically at the time when the driver is in the distracted state but not in the abnormal state (that the search behavior becomes normal when the driving load is increased and thus the behavior request for the driver is enhanced) and distinguishing such a change from the change in the abnormal state. In this way, the driver's distracted state may be distinguished from another abnormal state, such as the disease, and promptly and accurately determine the driver's distracted state.

The controller10acquires the driving load score based on the cognitive load score and the operation load score. Thus, a magnitude of the driving load may be evaluated in consideration of the cognitive load and the operation load, which affect likelihood of the occurrence of the distracted state. Thus, the further accurate distracted state occurrence score may be acquired.

The controller10acquires the surprise value based on the travel environment information. Then, the controller10calculates the search behavior score such that the search behavior score is increased as the tendency of the driver's sightline to be directed to the object with the relatively high surprise value is increased. In this way, the driver's search behavior score is calculated based on a behavioral principle of a person that the driver in the normal state directs his/her sightline to the object with the relatively high surprise value. Thus, the search behavior score, to which the driver's state is further accurately reflected, may be acquired.

No claim element herein is to be construed under the provisions of 35 U.S.C. 112(f) unless the element is expressly recited using the phrase “means for.” As used herein, the terms “comprises,” “comprising,” or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.

The present disclosure is not limited to only the above-described embodiments, which are merely exemplary. It will be appreciated by those skilled in the art that the disclosed systems and/or methods can be embodied in other specific forms without departing from the spirit of the disclosure or essential characteristics thereof. The presently disclosed embodiments are therefore considered to be illustrative and not restrictive. The disclosure is not exhaustive and should not be interpreted as limiting the claimed invention to the specific disclosed embodiments. In view of the present disclosure, one of skill in the art will understand that modifications and variations are possible in light of the above teachings or may be acquired from practicing of the disclosure. The scope of the invention is indicated by the appended claims, rather than the foregoing description.

DESCRIPTION OF REFERENCE SIGNS AND NUMERALS