JP2017174093A - Driver state determination device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide a driver state determination device capable of accurately determining whether or not the driver state is abnormal.SOLUTION: A driver state determination device 100 includes: a recognition part 21 for recognizing a driving posture of a driver 1; a storage part 22 for storing a normal driving posture of the driver 1; a deviation amount calculation part 23a for calculating an amount of deviation between the normal driving posture and the driving posture recognized by the recognition part 21 for each of a plurality of normal driving postures stored in the storage part 22 ; a lowest deviation amount selection part 23b for selecting the amount of deviation of the lowest value from among the calculated amount of deviation as the lowest deviation amount; an accumulated value calculation part 23c for accumulating the selected lowest deviation amount and calculating a deviation amount accumulated value; and a determination part 23 for determining a state of the driver 1 as being abnormal when the deviation amount accumulated value exceeds a predetermined threshold value.SELECTED DRAWING: Figure 1

Description

  One aspect of the present invention relates to a driver state determination device.

  As a technique related to a conventional driver state determination device, for example, a technique described in Patent Document 1 is known. In the technique described in Patent Literature 1, the driver's face position is captured by the camera using a camera provided in front of the driver's seat, and the driver's face does not exist or the eyes are closed from the captured image. Is continuously detected for a predetermined period, it is determined that the driver's condition is abnormal.

JP 2007-331652 A

  In recent years, a system has been introduced that reduces the damage caused by contact with obstacles by, for example, automatically controlling the driving of the vehicle when the state of the driver in the vehicle is determined and the driver's state is abnormal. It is desired. In order to realize such a system, in the driver state determination device as described above, it is important to accurately determine whether or not the driver's state is abnormal.

  An aspect of the present invention has been made in view of the above circumstances, and an object of the present invention is to provide a driver state determination device that can accurately determine whether or not a driver's state is abnormal.

  A driver state determination device according to an aspect of the present invention recognizes a driving posture including a relative positional relationship among a plurality of skeleton parts in a driver of a vehicle based on a detection result by a detection unit including at least a distance sensor. A recognition unit, a storage unit that stores a plurality of normal driving postures that are the driving postures of the driver in a normal driving state, and the normal driving postures for each of the plurality of normal driving postures stored in the storage unit And a deviation amount calculation unit for calculating a deviation amount between the recognition posture and the driving posture recognized by the recognition unit, and a deviation value with the smallest value among the deviation amounts calculated for each of the plurality of normal driving postures stored in the storage unit. Calculated by the minimum deviation amount selection unit that selects the amount as the minimum deviation amount, the integrated value calculation unit that calculates the deviation amount integrated value by integrating the minimum deviation amount selected by the minimum deviation amount selection unit, and the integrated value calculation unit Amount of misalignment Calculated value, and a determination unit the state of the driver to be abnormal when exceeding a predetermined threshold.

  In this driver state determination device, the deviation amount calculation unit calculates a deviation amount from the driving posture recognized by the recognition unit for each of the plurality of normal driving postures. The minimum deviation amount selection unit selects a deviation amount having the smallest value among the deviation amounts calculated for each of the plurality of normal driving postures as the minimum deviation amount. Here, the normal driving posture having the smallest deviation amount among the plurality of normal driving postures stored in the storage unit is a posture closest to the driving posture of the driver. That is, the minimum deviation amount selection unit sets the deviation amount between the normal driving posture closest to the driving posture of the driver and the driving posture of the driver among the plurality of normal driving postures stored in the storage unit as the minimum deviation amount. select. The integrated value calculation unit integrates the deviation amount (minimum deviation amount) from the normal driving posture closest to the driver's driving posture to calculate a deviation amount integrated value. The determination unit determines that the driver's condition is abnormal when the deviation amount integrated value exceeds a predetermined threshold. By making a determination by integrating the minimum deviation amount in this way, for example, when the driver's posture becomes abnormal for a moment due to the vehicle overcoming a step, etc., or for a moment due to noise of the detection unit, etc. Even when the driver's abnormal driving posture is recognized by the recognition unit, the driver state determination device can suppress erroneous determination of the driver's state as abnormal. Therefore, according to the driver state determination device, it is possible to accurately determine whether or not the driver's state is abnormal.

  The integrated value calculation unit may integrate the minimum deviation amount selected by the minimum deviation amount selection unit and subtract a predetermined amount from the deviation amount integrated value every time a predetermined time elapses. In this case, the driver state determination device can automatically subtract the deviation amount integrated value that increases by integrating the deviation amount as time elapses.

  The driver state determination device may include a learning unit that stores the driving posture of the driver recognized by the recognition unit in the storage unit as a normal driving posture at times other than the determination by the determination unit. According to this configuration, it is possible to cause the storage unit to learn the driving posture of the driver at a time other than the determination time by the determination unit as the normal driving posture.

  According to one aspect of the present invention, it is possible to provide a driver state determination device that can accurately determine whether or not a driver's state is abnormal.

It is a block diagram which shows the structure of the driver | operator state determination apparatus which concerns on embodiment. It is a figure explaining a some frame part. It is a figure which shows an example of the driving posture recognized by the recognition part. It is a flowchart explaining the process of the determination mode performed in driver | operator state determination ECU. It is a flowchart explaining the process of the learning mode performed in driver | operator state determination ECU.

  DESCRIPTION OF EMBODIMENTS Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the drawings. In the following description, the same or equivalent elements will be denoted by the same reference numerals, and redundant description will be omitted.

  FIG. 1 is a block diagram illustrating a configuration of a driver state determination device 100 according to the embodiment. FIG. 2 is a diagram illustrating a plurality of skeleton parts 2 of the driver 1. As shown in FIG. 1, the driver state determination device 100 is a device that determines whether or not the state of the driver 1 riding in a vehicle such as an automobile is abnormal. The vehicle is not particularly limited, and may be, for example, a commercial vehicle such as a truck or a bus, a normal passenger vehicle, a large vehicle, a medium vehicle, a small vehicle, or a light vehicle.

  The driver state determination device 100 includes a depth sensor (detection unit) 10, a driver state determination ECU 20, and an output unit 30. The depth sensor 10 is a distance sensor that acquires depth information. The depth sensor 10 is configured by an infrared sensor that is a sensor that acquires depth information (distance image) up to an object. The depth sensor 10 is disposed between the window on the passenger seat side of the vehicle and the windshield. The depth sensor 10 can be photographed in a direction from above the driver 1 toward the driver 1 side. The depth sensor 10 may be configured by a distance sensor other than the infrared sensor. The depth sensor 10 may further include an RGB sensor that acquires a color image of the object in addition to the distance sensor that acquires depth information.

  As shown in FIGS. 1 and 2, the depth sensor 10 acquires depth information of the upper body of the driver 1, and from the acquired depth information, the three-dimensional coordinates (X-axis coordinates, Y-axis coordinates and Z-axis coordinates) are acquired. The depth sensor 10 outputs information regarding the three-dimensional coordinates to the driver state determination ECU 20 as sensor information. As the depth sensor 10, for example, the depth obtainable range is 0.5 to 8.0 [m], the driver 1 detectable range is 0.5 to 4.5 [m], and the skeleton part 2 is Those having a detectable number of 20 or 25 [location / person] are used. In addition, it does not specifically limit as a method of acquiring the three-dimensional coordinate of the some frame | skeleton part 2, A well-known method is employable.

  The skeletal part 2 is a structural part composed of one or more bones and cartilage. The skeleton part 2 is a part having one or a plurality of functions and / or structures that are united on the skeleton. The skeleton part 2 is also called a skeleton point. As the skeleton part 2 of the present embodiment, the skeleton part of the upper body of the driver 1, for example, “head”, “left shoulder”, “left elbow”, “left arm”, “left hand”, “right shoulder”, Examples include “right elbow”, “right arm”, “right hand”, “spinal cord”, “center of spine”, and “waist”. The upper body is the part of the body from the head to the waist.

  The driver state determination ECU 20 is an electronic control unit having a CPU [Central Processing Unit], a ROM [Read Only Memory], a RAM [Random Access Memory], and the like. The driver state determination ECU 20 executes various controls by loading a program stored in the ROM into the RAM and executing it by the CPU. The driver state determination ECU 20 may be composed of a plurality of electronic control units. The driver state determination ECU 20 includes a recognition unit 21, a storage unit 22, a determination processing unit 23, and a learning unit 24.

  The recognition unit 21 recognizes a driving posture including a relative three-dimensional positional relationship in the plurality of skeleton parts 2 of the driver 1 based on the sensor information of the depth sensor 10. Specifically, first, for each item composed of two combinations of the plurality of skeleton parts 2, the magnitude relationship of the three-dimensional coordinates of the other skeleton part 2 with respect to the coordinates of one skeleton part 2 is calculated. For example, the magnitude relationship is bit-patterned depending on whether the coordinate of one skeleton part 2 is larger, smaller, or equal to the coordinate of one skeleton part 2 in each of the X, Y, and Z axes. Expressed. The magnitude relationship is set as relative position information (also referred to as a relative checkpoint). A group of information having such relative position information for each of a plurality of items is recognized as a driving posture (also referred to as a posture model).

  FIG. 3 is a diagram illustrating an example of a driving posture recognized by the recognition unit 21. In the example illustrated in FIG. 3, the driving posture has 66 combinations (items) of the skeleton parts 2, for example, where the number of the skeleton parts 2 is twelve. Each item has relative position information regarding the magnitude relationship of the three-dimensional coordinates of the other skeleton part 2 with respect to one skeleton part 2 in the XYZ coordinate system. As shown in the drawing, for example, when the item is “head-left shoulder”, the X-axis coordinate of the head is smaller than the X-axis coordinate of the left shoulder, and the Y-axis coordinate of the head is equal to the Y-axis coordinate of the left shoulder “=”. The Z-axis coordinate of the head is larger than the Z-axis coordinate of the left shoulder and is “>”. In other words, one driving posture is described as a vector formed by comparing the relative magnitude relations of coordinates for a combination of a plurality of skeleton parts 2 with three axes.

  As shown in FIG. 1, the storage unit 22 stores and accumulates a plurality of normal driving postures. The normal driving posture is a driving posture of the driver 1 in a normal driving state. As will be described later, the storage unit 22 stores the driving posture recognized by the learning unit 24 during normal driving (during normal driving) as a normal driving posture. The plurality of normal driving postures stored in the storage unit 22 construct a “dictionary”, that is, an aggregate that collects a number of normal driving postures. The plurality of normal driving postures stored in the storage unit 22 are used as teacher data. The plurality of normal driving postures are configured in the form of a list of relative position information. Hereinafter, the plurality of normal driving postures stored in the storage unit 22 are also simply referred to as “dictionaries”.

  Based on the plurality of normal driving postures stored in the storage unit 22 and the current driving posture recognized by the recognition unit 21 (hereinafter referred to as “current driving posture”), the determination processing unit 23 performs the following determination modes. And determine whether or not the state of the driver 1 is abnormal.

  Specifically, the determination processing unit 23 includes a deviation amount calculation unit 23a, a minimum deviation amount selection unit 23b, an integrated value calculation unit 23c, and a determination unit 23d. The deviation amount calculation unit 23 a calculates, for each of a plurality of normal driving postures stored in the storage unit 22, a deviation amount between the normal driving posture and the current driving posture recognized by the recognition unit 21. Here, the amount of deviation represents how much the current driving posture is deviated (separated) from the normal driving posture. The larger the deviation amount is, the more the current driving posture is shifted from the normal driving posture. The case where the amount of deviation is zero is a case where the normal driving posture as a comparison target matches the current driving posture recognized by the recognition unit 21. When the amount of deviation is very small (when it is equal to or less than a predetermined value), the amount of deviation calculation unit 23a may calculate the amount of deviation as zero.

  More specifically, the deviation amount calculation unit 23a compares the relative position information of the plurality of items with the relative position information of the plurality of items of the current driving posture for one normal driving posture, and compares the relative position information. Calculate the number of items with different information. At this time, when the magnitude relation of the X-axis coordinates, the magnitude relation of the Y-axis coordinates, and the magnitude relation of the Z-axis coordinates included in the relative position information are all the same, the deviation amount calculation unit 23a matches the relative position information. And

  Next, the deviation amount calculation unit 23a calculates the deviation amount based on the number of items having different relative position information. For example, the deviation amount calculation unit 23a may use the number of items having different relative position information as the deviation amount. Alternatively, the shift amount calculation unit 23a may calculate the shift amount by weighting each item when using the number of items having different relative position information as the shift amount.

  Subsequently, the deviation amount calculation unit 23a performs such a deviation amount calculation on all of the plurality of normal driving postures stored in the storage unit 22. Thus, every time the current driving posture is recognized by the recognizing unit 21, the deviation amount calculating unit 23 a calculates the normal driving posture and the current driving posture with respect to all of the plurality of normal driving postures stored in the storage unit 22. The amount of deviation is calculated.

  The minimum deviation amount selection unit 23b sets the smallest deviation amount as the minimum deviation amount among the deviation amounts calculated by the deviation amount calculation unit 23a for each of the plurality of normal driving postures stored in the storage unit 22. select. The selection of the minimum deviation amount is performed every time the deviation amount is calculated for all of the plurality of normal driving postures stored in the storage unit 22.

  The integrated value calculation unit 23c calculates a deviation amount integrated value by integrating the minimum deviation amount every time the determination unit 23 selects the minimum deviation amount. That is, the integrated value calculation unit 23c adds the minimum deviation amount selected this time to the integrated value of the minimum deviation amounts selected in the past (deviation amount integrated value).

  Further, the integrated value calculation unit 23c subtracts a predetermined amount from the deviation amount integrated value every time a predetermined time elapses. The integrated value calculation unit 23c subtracts the deviation amount integrated value every time the deviation amount integrated value is integrated. When the timing at which the minimum deviation amount is selected is a fixed timing, the integrated value calculation unit 23c subtracts the deviation amount integrated value by a predetermined amount each time the minimum deviation amount is integrated. In addition, when the timing at which the minimum deviation amount is selected varies, the minimum deviation amount is set in consideration of the selection timing (time interval) of the minimum deviation amount so that the predetermined amount is subtracted every predetermined time. Every time integration is performed, the integrated deviation amount is subtracted. Note that the variation in timing at which the minimum deviation amount is selected may occur due to, for example, the load (calculation amount) of the CPU. Further, the integrated value calculation unit 23c may perform the integration of the deviation amount integrated value and the subtraction of the deviation amount integrated value at different timings or at different periods.

  The determination unit 23d determines that the state of the driver 1 is abnormal when the deviation amount integrated value calculated by the integrated value calculation unit 23c exceeds a predetermined threshold. The determination unit 23d determines that the state of the driver 1 is normal when the deviation amount integrated value calculated by the integrated value calculation unit 23c is equal to or less than a predetermined threshold. This threshold value is a predetermined value stored in order to appropriately determine whether or not the state of the driver 1 is abnormal. The threshold value can be determined based on experiments, past results and experiences, simulations, and the like. The threshold value may be a fixed value or a variable value.

  The learning unit 24 executes a learning mode (also referred to as a dictionary registration mode or a dictionary strengthening mode) in which the current driving posture recognized by the recognition unit 21 is learned as a normal driving posture at a time other than the determination by the determination processing unit 23. Specifically, the learning unit 24 stores and accumulates the current driving posture of the driver 1 recognized by the recognition unit 21 in the storage unit 22 as a normal driving posture during normal driving other than when mode determination is performed, for example. Note that the learning unit 24 has a small amount of deviation between the current driving posture of the driver 1 during normal driving recognized by the recognition unit 21 and the normal driving posture stored in the storage unit 22 (less than a predetermined value). ), The learning unit 24 may not perform the process of accumulating the recognized current driving posture in the storage unit 22. Thereby, increase of the dictionary memorize | stored in the memory | storage part 22 can be suppressed.

  The output unit 30 notifies the driver 1 of information corresponding to the determination result by the determination processing unit 23. The output unit 30 includes, for example, at least one of a display for displaying image information and a speaker for audio output. When the determination processing unit 23 determines that the state of the driver 1 is abnormal, the output unit 30 displays a warning display on the display panel, for example, and / or outputs a warning sound such as a warning message from the speaker. On the other hand, when the determination processing unit 23 determines that the state of the driver 1 is normal, the output unit 30 displays, for example, on the display panel that the current driving posture corresponds to the normal driving posture, and / or A sound indicating that the current driving posture corresponds to the normal driving posture is output from the speaker.

  In the present embodiment, the driver state determination device 100 may be applied to a travel support device (not shown) and the vehicle travel may be automatically controlled based on the determination result of the determination unit 23d. For example, when the determination unit 23d determines that the state of the driver 1 is abnormal, the vehicle control ECU (not shown) may control the steering actuator and the brake actuator so that the vehicle is brought close to the road shoulder and stopped. The driver state determination device 100 can be employed in various travel support devices, drive support devices, travel safety devices, and the like.

  In the present embodiment, execution of the determination mode by the determination processing unit 23 and execution of the learning mode by the learning unit 24 may be switched as desired in accordance with, for example, an operation of a mode switching unit (not shown) by the driver 1. Good. In the present embodiment, the acquisition of the three-dimensional coordinates of the skeleton part 2, the conversion to the expression (driving posture) as a relative positional relationship, and the calculation of the shift amount for all the dictionaries are the number of processing frames per second. Real-time processing is performed with tens of frames.

  Next, the process of the driver state determination device 100 will be described with reference to the flowchart shown in FIG.

  FIG. 4 is a flowchart illustrating processing in a determination mode that is executed by the driver state determination ECU 20. As shown in FIG. 4, the driver state determination ECU 20 repeatedly executes the following processing relating to the determination mode at a predetermined cycle.

  First, the driver state determination ECU 20 acquires sensor information from the depth sensor 10 (S1). The recognition unit 21 recognizes the current driving posture of the driver 1 based on the sensor information of the depth sensor 10 (S2). The deviation amount calculation unit 23a calculates the deviation amount from the current driving posture for each of the plurality of normal driving postures (S3). And the minimum deviation | shift amount selection part 23b selects the deviation | shift amount with the smallest value among the deviation | shift amounts calculated with respect to each of several normal driving | running | working attitude | positions as a minimum deviation amount (S4). When the minimum deviation amount is selected, the integrated value calculation unit 23c integrates the selected minimum deviation amount to calculate the deviation amount integrated value, and subtracts the deviation amount integrated value as time passes ( S5).

  Subsequently, the determination unit 23d determines whether or not the calculated deviation amount integrated value exceeds a predetermined threshold (S6). When the deviation amount integrated value exceeds the threshold (S6: YES), the determination unit 23d determines that the state of the driver 1 is abnormal. Thereafter, the driver state determination ECU 20 causes the output unit 30 to output a warning sound and / or a warning display, and shifts to a process in the next cycle. Instead of or in addition to this, the vehicle control ECU automatically controls the travel of the vehicle, for example, brings the vehicle to the road shoulder and stops.

  On the other hand, when the deviation amount integrated value does not exceed the threshold (S6: NO), the determination unit 23d determines that the state of the driver 1 is normal. Thereafter, the driver state determination ECU 20 outputs from the output unit 30 that the current driving posture corresponds to the normal driving posture, and shifts to the processing of the next cycle.

  FIG. 5 is a flowchart illustrating the learning mode process executed by the driver state determination ECU 20. As shown in FIG. 5, the driver state determination ECU 20 repeatedly executes the following processing relating to the determination mode at a predetermined period, for example, during normal driving other than during mode determination execution.

  First, the driver state determination ECU 20 acquires sensor information from the depth sensor 10 (S11). The recognition unit 21 recognizes the current driving posture of the driver 1 based on the sensor information of the depth sensor 10 (S12). The learning unit 24 stores the current driving posture in the storage unit 22 as a normal driving posture (S13). Thereafter, the driver state determination ECU 20 proceeds to the process of the next cycle.

  As described above, in the driver state determination device 100, the deviation amount calculation unit 23 a calculates the deviation amount from the current driving posture recognized by the recognition unit 21 for each of the plurality of normal driving postures stored in the storage unit 22. calculate. The minimum deviation amount selection unit 23b selects, as the minimum deviation amount, the smallest deviation amount among the deviation amounts calculated for each of the plurality of normal driving postures. Here, the normal driving posture having the smallest deviation amount among the plurality of normal driving postures stored in the storage unit 22 is a posture closest to the current driving posture of the driver 1. That is, the minimum deviation amount selection unit 23b sets the deviation amount between the normal driving posture closest to the current driving posture of the driver 1 and the current driving posture among the plurality of normal driving postures stored in the storage unit 22. Select as quantity. The integrated value calculation unit 23c integrates the deviation amount (minimum deviation amount) from the normal driving posture closest to the current driving posture of the driver 1 to calculate a deviation amount integrated value.

  The determination unit 23d determines that the state of the driver 1 is abnormal when the deviation amount integrated value exceeds a predetermined threshold value. Thus, by determining by integrating the minimum deviation amount, for example, when the posture of the driver 1 becomes an abnormal posture for a moment due to the vehicle overcoming a step or the like, due to noise of the depth sensor 10 or the like Even if the abnormal driving posture of the driver 1 is recognized by the recognition unit 21 for a moment, the driver state determination device 100 can suppress erroneous determination of the state of the driver 1 as abnormal. Therefore, according to the driver state determination device 100, it is possible to accurately determine whether or not the state of the driver 1 is abnormal.

  Further, the deviation amount calculation unit 23 a calculates a deviation amount between the normal driving posture stored in the storage unit 22 and the current driving posture recognized by the recognition unit 21. That is, it is not necessary for the storage unit 22 to store the abnormal driving posture pattern of the driver 1, and only the normal driving posture needs to be stored. For this reason, increase of the dictionary which the memory | storage part 22 memorize | stores can be suppressed. In addition, the deviation amount calculation unit 23a is configured to calculate the deviation amount by comparing the normal driving posture and the current driving posture without using the abnormal driving posture pattern of the driver 1, and thus the abnormal driving posture is calculated. The amount of calculation for calculating the amount of deviation can be suppressed as compared with the case where the posture pattern is also the object of comparison.

  The integrated value calculation unit 23c integrates the minimum deviation amount selected by the minimum deviation amount selection unit 23b, and subtracts a predetermined amount from the deviation amount integrated value every time a predetermined time elapses. For this reason, the driver state determination apparatus 100 can automatically subtract the deviation amount integrated value that increases by integrating the deviation amount as time elapses.

  The learning unit 24 causes the storage unit 22 to store the driving posture of the driver 1 recognized by the recognition unit 21 as a normal driving posture when the determination processing unit 23 does not perform the determination. According to this configuration, it is possible to cause the storage unit 22 to learn the driving posture of the driver 1 at a time other than the determination time by the determination processing unit 23 as a normal driving posture.

  The preferred embodiments of the present invention have been described above. However, the present invention is not limited to the above-described embodiments. The present invention can be modified without departing from the scope described in the claims or applied to other embodiments. May be.

  For example, in the above embodiment, the depth sensor 10 is used as the detection unit, but other sensors including a distance sensor may be used. In short, it is only necessary to recognize the driving posture including the relative positional relationship of the plurality of skeleton parts 2 of the driver 1 based on the detection result of the detection unit.

  In addition, it is not essential for the integrated value calculation unit 23c to perform a process of subtracting a predetermined amount every time a predetermined amount of time has elapsed. Further, the subtraction of the deviation amount integrated value can be performed by various methods other than the subtraction every time a predetermined time elapses. For example, after the notification that the state of the driver 1 is abnormal is performed by the output unit 30, and the response operation (such as pressing a button) for the notification is performed by the driver 1, the integrated value calculation unit 23c may subtract the deviation amount integrated value.

  It is not essential for the driver state determination device 100 to learn the normal driving posture using the learning unit 24.

  DESCRIPTION OF SYMBOLS 1 ... Driver, 2 ... Skeletal part, 10 ... Depth sensor (detection part), 21 ... Recognition part, 22 ... Memory | storage part, 23a ... Deviation amount calculation part, 23b ... Minimum deviation amount selection part, 23c ... Integrated value calculation part , 23d ... determination unit, 24 ... learning unit, 100 ... driver state determination device.

Claims (3)

A recognition unit for recognizing a driving posture including a relative positional relationship of a plurality of skeleton parts in a driver of the vehicle based on a detection result by at least a detection unit including a distance sensor;
A storage unit that stores a plurality of normal driving postures that are the driving postures of the driver in a normal driving state;
For each of the plurality of normal driving postures stored in the storage unit, a deviation amount calculating unit that calculates a deviation amount between the normal driving posture and the driving posture recognized by the recognition unit;
A minimum shift amount selection unit that selects the shift amount having the smallest value as the minimum shift amount among the shift amounts calculated for each of the plurality of normal driving postures stored in the storage unit;
An integrated value calculation unit that calculates the deviation amount integrated value by integrating the minimum deviation amount selected by the minimum deviation amount selection unit;
A driver state determination apparatus comprising: a determination unit that determines that the driver's state is abnormal when the deviation amount integrated value calculated by the integrated value calculation unit exceeds a predetermined threshold.   2. The integrated value calculation unit according to claim 1, wherein the integrated value calculation unit integrates the minimum deviation amount selected by the minimum deviation amount selection unit, and subtracts a predetermined amount from the deviation amount integrated value every time a predetermined time elapses. Driver state determination device.   The driving according to claim 1, further comprising: a learning unit that stores the driving posture of the driver recognized by the recognition unit in the storage unit as the normal driving posture at a time other than the determination by the determination unit. Person state determination device.

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