Driver monitoring device, driver monitoring method, and program

Abstract

To calculate an index for predicting the future change of the risk of a driving situation that a driver is in.SOLUTION: And a predictive danger score calculation unit 14 that calculates a predictive danger score indicating a degree of danger of movement of the moving body 100 by driving of the driver D after a predetermined time point based on the driving behavior of the driver D recognized by the driving behavior recognition unit at the predetermined time point while the driver D is driving the moving body 100 and the biological information during driving which is the biological information of the driver D recognized by the biological information recognition unit 11 at the predetermined time point.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to a driver monitoring device, a driver monitoring method, and a program. [Background technology]

[0002] In recent years, efforts to provide access to sustainable transport systems that take into consideration vulnerable transport participants have become more active. To achieve this, we are focusing on research and development into preventive safety technologies to further improve road safety and convenience. For example, Patent Document 1 discloses a technology that calculates the driver's drowsiness risk based on information obtained from the vehicle driver, calculates the monotonous driving risk based on information on the route the vehicle is traveling, and estimates the time at which the driver's future drowsiness level will exceed a predetermined threshold based on the drowsiness risk and monotonous driving risk. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-61480 Summary of the Invention [Problem to be solved by the invention]

[0004] In preventive safety technology, predicting changes in the degree of risk of the driving situation in which a driver of a mobile vehicle is in is effective in preventing accidents involving the mobile vehicle. Therefore, an object of the present application is to calculate an index that predicts future changes in the risk of the driving situation in which a driver is in. To solve the above problems, the present application aims to calculate an index that predicts future changes in the risk of a driver's driving situation, thereby further improving traffic safety and contributing to the development of a sustainable transportation system. [Means for solving the problem]

[0005] A first aspect for achieving the above object is a driver monitoring device comprising: a biometric information recognition unit that recognizes the biometric information of a driver of a mobile body; a driving behavior recognition unit that recognizes the driving behavior of the driver while driving the mobile body; and a predicted risk score calculation unit that calculates a predicted risk score indicating the degree of risk for the movement of the mobile body due to driving by the driver from the predetermined point in time onwards, based on the driving behavior of the driver recognized by the driving behavior recognition unit at a predetermined point in time while the driver is driving the mobile body and the driving biometric information of the driver recognized by the biometric information recognition unit at the predetermined point in time.

[0006] The above-mentioned driver monitoring device may be provided with a health level recognition unit that recognizes the driver's health level based on pre-driving biometric information, which is the driver's biometric information recognized by the biometric information recognition unit before the driver starts driving the mobile vehicle, and the predicted risk score calculation unit may be configured to calculate the predicted risk score based on the driver's driving behavior recognized by the driving biometric information at the specified time point, the driving biometric information recognized by the biometric information recognition unit at the specified time point, and the driver's health level recognized by the health level recognition unit.

[0007] In the driver monitoring device, the biological information recognition unit may be configured to recognize a heart rate of the driver as the biological information of the driver.

[0008] The above-mentioned driver monitoring device may be equipped with a mobile body position recognition unit that recognizes the position of the mobile body, and a mobile environment recognition unit that recognizes the mobile body's mobile environment from the specified time onwards based on the position of the mobile body at the specified time recognized by the mobile body position recognition unit, and the predicted risk score calculation unit may be configured to correct the predicted risk score based on the mobile environment estimated by the mobile environment estimation unit.

[0009] The driver monitoring device may be configured to include a travel route guidance unit that, when the predicted risk score calculation unit calculates a predicted risk score that is greater than or equal to a predetermined value, guides the driver to a travel route that will result in a travel environment that is recognized by the travel environment recognition unit as reducing the driver's driving load.

[0010] As a second aspect for achieving the above object, in a driver monitoring device, there is provided a driver monitoring method executed by a computer, the driver monitoring method including: a biometric information recognition step for recognizing biometric information of a driver of a mobile body; a driving behavior recognition step for recognizing the driving behavior of the driver while driving the mobile body; and a predicted risk score calculation step for calculating a predicted risk score indicating the degree of risk for the movement of the mobile body due to driving by the driver from the predetermined point in time onwards, based on the driving behavior of the driver recognized by the driving behavior recognition step at a predetermined point in time while the driver is driving the mobile body, and the driving biometric information of the driver recognized by the biometric information recognition step at the predetermined point in time.

[0011] A third aspect for achieving the above object is a program that causes a computer to function as a biometric information recognition unit that recognizes the biometric information of a driver of a mobile body, a driving behavior recognition unit that recognizes the driving behavior of the driver while driving the mobile body, and a predicted risk score calculation unit that calculates a predicted risk score that indicates the degree of risk for the movement of the mobile body due to driving by the driver from the predetermined point in time onwards, based on the driving behavior of the driver recognized by the driving behavior recognition unit at a predetermined point in time while the driver is driving the mobile body and the driving biometric information, which is the driver's biometric information recognized by the biometric information recognition unit at the predetermined point in time. [Effects of the Invention]

[0012] According to the driver monitoring device, the driver monitoring method, and the program, it is possible to calculate an index that predicts future changes in the risk of the driving situation in which the driver is placed. [Brief explanation of the drawings]

[0013] [Figure 1] FIG. 1 is an explanatory diagram of a manner in which a driver monitoring device is used. [Figure 2] FIG. 2 is a configuration diagram of the driver monitoring device. [Figure 3] FIG. 3 is an explanatory diagram of the correspondence between lifestyle habit data, driving-related abilities, and driving diagnostic indices for coaching. [Figure 4] FIG. 4 is a flowchart of the process for calculating the predicted risk score. [Figure 5] FIG. 5 is an explanatory diagram of the concept of predicted risk scores. DETAILED DESCRIPTION OF THE INVENTION

[0014] [1. How to use the driver monitoring device] With reference to Fig. 1, a description will be given of how the driver monitoring device 2 of this embodiment is used. The driver monitoring device 2 is configured as a function of a communication terminal 1 used by a driver D of a vehicle 100. The communication terminal 1 is a smartphone, a mobile phone, a tablet terminal, or the like. The communication terminal 1 is attached to a terminal holder 150 provided in the vehicle 100. The vehicle 100 corresponds to the moving body of the present disclosure. The moving body of the present disclosure may be an aircraft, a ship, or the like other than a vehicle.

[0015] The vehicle 100 is equipped with an ECU (Electronic Control Unit) 110 that controls the operation of the vehicle 100, a communication unit 120, a navigation device 121, a front camera 130 that takes images in front of the vehicle 100, a driver monitor camera 131 that takes images of the driver D, a display 132, speakers 133a and 133b, an acceleration sensor 134, etc. The ECU 110 communicates with the communication terminal 1 via the communication unit 120. The vehicle 100 is equipped with a steering wheel 140, an accelerator pedal 141, a brake pedal 142, etc. as driving operation units.

[0016] The driver monitoring device 2 recognizes the operation (driving behavior) of the steering wheel 140, accelerator pedal 141, and brake pedal 142 by the driver D by receiving operation information through communication with the ECU 110 or by detection information from an acceleration sensor built into the communication terminal 1. The driver monitoring device 2 also acquires biometric information (heart rate, etc.) of the driver D measured by a wearable device worn by the driver D through communication with the wearable device.

[0017] Then, based on the driving behavior and biological information of the driver D, the driver monitoring device 2 calculates a predicted risk score indicating the degree of risk for the movement of the vehicle 100 driven by the driver D from a predetermined point in time when the driving behavior and biological information are recognized. The value of the predicted risk score becomes larger as the degree of risk increases. Furthermore, the driver monitoring device 2 supports the movement of the vehicle 100 driven by the driver D by notifying the driver D according to the level of the predicted risk score.

[0018] [2. Configuration of driver monitoring device] The configuration of the driver monitoring device 2 will be described with reference to Fig. 2. The communication terminal 1 having the functions of the driver monitoring device 2 includes a control unit 3 having a processor 10 and a memory 20, a communication unit 30, a camera 31, an acceleration sensor 32, a GNSS (Global Navigation Satellite System) sensor 33, a display 34, a speaker 35, and a microphone 36.

[0019] The communication unit 30 performs short-range wireless communication using specifications such as Bluetooth (registered trademark) and UWB (Ultra Wide Band) between the vehicle 100 (more specifically, the ECU 110 mounted on the vehicle 100) and a wearable device 160 (such as a smart watch, wearable smart underwear, or a sensing device attached to the body or skin) worn by the driver D. The communication unit 30 also communicates with a traffic information server 210, a vehicle management server 211, and the like via the communication network 200.

[0020] The camera 31 captures an image of the driver D with the communication terminal 1 attached to the terminal holder 150 (see FIG. 1). The acceleration sensor 32 detects, for example, six axes (acceleration in each of the longitudinal, lateral, and vertical directions, and angular velocity about each axis). The GNSS sensor 33 detects the position of the communication terminal 1. With the communication terminal 1 attached to the terminal holder 150, the position detected by the GNSS sensor 33 becomes the current position of the vehicle 100. The display 34 is a touch panel, and the driver D instructs the use and stopping of functions of the driver monitoring device 2 by touching the display 34.

[0021] The memory 20 stores an application program 21 for the driver monitoring device 2. By reading and executing the program 21, the processor 10 functions as a biometric information recognition unit 11, a health level recognition unit 12, a driving behavior recognition unit 13, a predicted risk score calculation unit 14, a moving object position recognition unit 15, a moving environment recognition unit 16, and a moving route guidance unit 17.

[0022] The processing executed by the biometric information recognition unit 11 corresponds to the biometric information recognition step in the driver monitoring method of the present disclosure, the processing executed by the driving behavior recognition unit 13 corresponds to the driving behavior recognition step in the driver monitoring method of the present disclosure, and the processing executed by the predicted risk score calculation unit 14 corresponds to the predicted risk score calculation step in the present disclosure.

[0023] The biological information recognition unit 11 recognizes the biological information of the driver D by communicating with the wearable device 160 and acquiring measurement information Bid relating to the physical activity of the driver D measured by the wearable device 160. The biological information includes heart rate, sleep time, sleep quality (REM sleep, non-REM sleep, sleep depth), exercise status (number of steps, exercise time, etc.), etc.

[0024] The health level recognition unit 12 recognizes the health level of the driver D before the driver D starts driving the vehicle 100, based on pre-driving biometric information, which is biometric information recognized by the biometric information recognition unit 11 before the driver D starts driving the vehicle 100. As shown in FIG. 3 , the health level recognition unit 12 acquires the driver D's daily lifestyle habit data (sleep, exercise, stress) shown in A1 from the driver D's biometric information as factors that affect the driving-related abilities (planning, perception, attention, judgment, operation) shown in A2, and recognizes the driver D's health level based on the lifestyle habit data. Furthermore, the health level recognition unit 12 may use the driver D's voice data acquired by a dialogue app executed by the wearable device 160 or the communication terminal 1 as a voice marker as the lifestyle habit data, and recognize the driver D's health level from the results of analyzing the voice.

[0025] Regarding A2's driving abilities, for example, planning is evaluated by questionnaire analysis values, perception is evaluated by the error from the standard, attention is evaluated by reaction speed, judgment is evaluated by the accuracy rate, and operation is evaluated by the time it takes to complete a task. Regarding A1's daily lifestyle data, sleep includes sleep duration and sleep quality (REM sleep, non-REM sleep), exercise includes the number of steps and exercise duration, and stress includes heart rate variability. The evaluation of driving abilities is used as a driving diagnostic index for coaching to be notified to driver D, as shown in A3.

[0026] The health level recognition unit 12 recognizes that the health level of the driver D has declined in the following cases, for example. Pre-driving state 1: When it is estimated that driver D's stress level is high based on fluctuations in his / her heart rate. Pre-driving condition 2: When driver D's sleep time is shorter than the past average. Pre-driving state 3: Driver D's exercise time is shorter than the past average.

[0027] The driving behavior recognition unit 13 recognizes the driving behavior of the driver D by acquiring measurement information Dri related to the driving behavior of the driver D measured in the vehicle 100 through communication with the vehicle 100. The measurement information Dri includes the operation speed of the accelerator pedal 141 detected by the accelerator pedal sensor, the operation speed of the brake pedal 142 detected by the brake pedal sensor, the operation speed of the steering wheel detected by the steering sensor, and left / right wobble of the vehicle 100 detected by the yaw rate sensor. The driving behavior recognition unit 13 recognizes driving behavior such as sudden acceleration, sudden deceleration, and abrupt steering based on the measurement information Dri.

[0028] The predicted risk score calculation unit 14 calculates a predicted risk score for the movement of the vehicle 100 driven by the driver D, based on the health level of the driver D before starting to drive recognized by the health level recognition unit 12, the heart rate of the driver D while driving recognized by the biometric information recognition unit 11, and the driving behavior of the driver D recognized by the driving behavior recognition unit 13. The processing by the predicted risk score calculation unit 14 will be described later.

[0029] The mobile object position recognition unit 15 recognizes the position (current position) of the vehicle 100 based on the position detection signal of the GNSS sensor 33. The movement environment recognition unit 16 recognizes the future driving environment (movement environment) of the vehicle 100 based on the position of the vehicle 100 recognized by the mobile object position recognition unit 15 and traffic information Trd (including map information, congestion information, weather information, etc.) transmitted from the traffic information server 210. The traffic information may be acquired through communication with a navigation device 121 provided in the vehicle 100. The movement route guidance unit 17 performs route guidance to notify the driver of a movement route that guides the driver along a driving route that reduces driving load when the predicted risk score calculated by the predicted risk score calculation unit 14 is equal to or greater than a predetermined value.

[0030] [3. Calculation process of predicted risk score] The procedure for calculating the predicted risk score executed by the driver monitoring device 2 will be described with reference to the flowchart shown in FIG.

[0031] 4, health degree recognition unit 12 repeatedly executes the process of recognizing the health degree of driver D before driver D starts driving vehicle 100 in step S1 based on the biometric information recognized by biometric information recognition unit 11 before driver D starts driving vehicle 100, as described above, until it recognizes in step S2 that driver D has started driving vehicle 100. Health degree recognition unit 12 recognizes that driver D has started driving vehicle 100 by communicating with vehicle 100.

[0032] In the following step S3, the biometric information recognition unit 11 recognizes the heart rate of the driver D by acquiring measurement information Bid of the driver D's heart rate through communication with the wearable device 160. In the next step S4, the driving behavior recognition unit 13 recognizes the driving behavior of the driver D by acquiring measurement information Dri of the driving behavior through communication with the vehicle 100.

[0033] In the following step S5, the moving environment recognition unit 16 recognizes the future driving environment of the vehicle 100 based on the position of the vehicle 100 recognized by the moving object position recognition unit 15 and the traffic information Mad acquired from the traffic information server 210. In the following step S5, the predicted risk score calculation unit 14 calculates a predicted risk score based on the driver D's health level before driving, heart rate, driving behavior, and the future driving environment of the vehicle 100.

[0034] 5, the vertical axis represents the risk score indicating the degree of risk when the vehicle 100 is driven by the driver D, and the horizontal axis represents time t, showing an example of the transition of the risk score. n indicates the time point at which the risk score is calculated. The risk score is calculated based on Driver D's driving behavior and heart rate, and heart rate fluctuations are an indicator of Driver D's stress, but the time constant of changes in the amount of hormones (such as cortisol) secreted in Driver D's body to deal with stress is low (the amount secreted does not change immediately).

[0035] Therefore, the predicted risk score calculation unit 14 uses the level of driving behavior as a reference value of the risk score, and calculates t n t after ΔT (for example, 15 minutes) from n A predicted risk score, which is a predicted value of the risk score at +ΔT, is calculated. PDT n +ΔT)=α·Da(t n )×β·Hb(t n )+HI ·····(1) However, Pd(t n +ΔT):t n Predicted risk score after ΔT, Da(t n ):t n Level of driving behavior in, α,β: adjustment coefficient, Hb(t n ):t n HI: Adjusted value according to the health level of driver D before driving.

[0036] In addition, the predicted risk score calculation unit 14 calculates the t of the vehicle 100 recognized by the moving environment recognition unit 16. n The predicted risk score is corrected to be higher as the driving load depending on the driving environment of the vehicle 100 at the time point +ΔT increases. For example, the driving load increases as the volume of traffic on the road increases, as the road becomes narrower, and as the weather worsens (rain, strong winds, etc.).

[0037] Here, the calculation of the predicted risk score by the predicted risk score calculation unit 14 may be performed by applying various commonly used statistical models. For example, the predicted risk score may be calculated by applying statistical processing using a multiple logistic model or the like.

[0038] In the next step S6, the predicted risk score calculation unit 14 determines whether the predicted risk score is equal to or greater than a predetermined value. If the predicted risk score is equal to or greater than the predetermined value, the predicted risk score calculation unit 14 proceeds to step S10, and if the predicted risk score is less than the predetermined value, the predicted risk score calculation unit 14 proceeds to step S7. In step S10, the predicted risk score calculation unit 14 communicates with the vehicle 100 to output driving advice to the driver D based on the predicted risk score by displaying it on the display 34 or outputting it as audio from the speaker 35, and the processing proceeds to step S7.

[0039] The driving advice includes route guidance that provides guidance on a driving route that reduces the driving load by the travel route guidance unit 17. The route guidance is performed by displaying the route on the display 34 and outputting a guidance voice from the speaker 35.

[0040] In step S7, the predicted risk score calculation unit 14 determines, through communication with the vehicle 100, whether the driver D has finished driving the vehicle 100. If the driver D has finished driving the vehicle 100, the predicted risk score calculation unit 14 proceeds to step S8, and if the driver D has not finished driving the vehicle 100, the predicted risk score calculation unit 14 proceeds to step S20. In step S20, when the predicted risk score recognition cycle has elapsed, the predicted risk score calculation unit 14 proceeds to step S3 and executes the processing from step S3 onwards again, and if the predicted risk score recognition cycle has not elapsed, the predicted risk score calculation unit 14 proceeds to step S7.

[0041] 4. Other Embodiments In the above embodiment, the biometric information recognition unit 11 recognized the heart rate as the biometric information of the driver D. In another embodiment, the biometric information of the driver D may be the blood pressure, body temperature, etc. of the driver D detected by a vital sensor provided in the wearable device 160. Note that the biometric information recognition unit 11 may recognize the biometric information of the driver D by acquiring detection information such as the heart rate, blood pressure, body temperature, etc. detected by a vital sensor provided in the communication terminal 1 or the vehicle 100.

[0042] In the above embodiment, the health level recognition unit 12 is provided, and the predicted risk score calculation unit 14 calculates the predicted risk score based on the pre-driving health level of the driver D recognized by the health level recognition unit 12. In another embodiment, the health level recognition unit 12 may be omitted.

[0043] In the above-described embodiment, the vehicle is equipped with a moving object position recognition unit 15 and a moving environment recognition unit 16, and the predicted risk score calculation unit 14 corrects the predicted risk score based on the driving load due to the future driving environment of the vehicle 100. In another embodiment, the moving object position recognition unit 15 and the moving environment recognition unit 16 may be omitted, and the predicted risk score may not be corrected based on the driving load due to the future driving environment of the vehicle 100.

[0044] In the above embodiment, a travel route guidance unit 17 is provided to guide the driver D to a travel route that reduces the driving load on the driver D when a predicted risk score equal to or greater than a predetermined value is calculated, but the travel route guidance unit 17 may be omitted and the above guidance may not be provided.

[0045] In the above embodiment, the driver monitoring device 2 is configured as a function of the communication terminal 1. In another embodiment, the driver monitoring device of the present disclosure may be configured as a function of an in-vehicle device such as the ECU 110 provided in the vehicle 100, or as a dedicated in-vehicle device. In this case, the in-vehicle device receives measurement information Bid of biological information through communication with the wearable device 160 worn by the driver D, and recognizes the biological information.

[0046] The driver monitoring device of the present disclosure may also be configured as a function of a server such as the vehicle management server 211. In this case, the server receives measurement information Bid of biological information through communication with the wearable device 160 worn by the driver D (directly or via the communication terminal 1 or the vehicle 100), and recognizes the biological information.

[0047] 2 is a schematic diagram showing the configuration of the driver monitoring device 2 divided by main processing content to facilitate understanding of the present invention, but the configuration of the driver monitoring device 2 may be divided by other divisions. Furthermore, the processing of each component may be executed by one hardware unit or multiple hardware units. Furthermore, the processing of each component shown in FIG. 4 may be executed by one program or multiple programs.

[0048] 5. Configurations supported by the above embodiments The above embodiment is a specific example of the following configuration.

[0049] (Configuration 1) A driver monitoring device comprising: a biometric information recognition unit that recognizes the biometric information of a driver of a mobile body; a driving behavior recognition unit that recognizes the driving behavior of the driver while driving the mobile body; and a predicted risk score calculation unit that calculates a predicted risk score that indicates the degree of risk for the movement of the mobile body due to driving by the driver from the predetermined point in time onwards, based on the driving behavior of the driver recognized by the driving behavior recognition unit at a predetermined point in time while the driver is driving the mobile body and the driving biometric information of the driver recognized by the biometric information recognition unit at the predetermined point in time. According to the driver monitoring device of configuration 1, it is possible to calculate an index that predicts future changes in the risk of the driving situation in which the driver is placed.

[0050] (Configuration 2) A driver monitoring device as described in Configuration 1, which is provided with a health degree recognition unit that recognizes the health degree of the driver based on pre-driving biometric information, which is the biometric information of the driver recognized by the biometric information recognition unit before the driver starts driving the mobile body, and the predicted risk score calculation unit calculates the predicted risk score based on the driver's driving behavior recognized by the driving biometric information at the specified time point, the driving biometric information recognized by the biometric information recognition unit at the specified time point, and the driver's health degree recognized by the health degree recognition unit. According to the driver monitoring device of configuration 2, the accuracy of the predicted risk score can be improved by reflecting the driver's health condition before driving.

[0051] (Configuration 3) The driver monitoring device according to Configuration 1 or 2, wherein the biological information recognition unit recognizes the heart rate of the driver as the biological information of the driver. According to the driver monitoring device of configuration 3, the predicted risk score can be calculated based on the driver's heart rate, which varies depending on the driver's stress level.

[0052] (Configuration 4) A driver monitoring device described in any one of configurations 1 to 3, comprising a mobile body position recognition unit that recognizes the position of the mobile body, and a mobile environment recognition unit that recognizes the mobile body's mobile environment from the specified time onwards based on the position of the mobile body at the specified time recognized by the mobile body position recognition unit, wherein the predicted risk score calculation unit corrects the predicted risk score based on the mobile environment estimated by the mobile environment estimation unit. According to the driver monitoring device of configuration 4, the predicted risk score can be corrected taking into account the travel environment (such as the degree of road congestion, road narrowness, weather, etc. when the travel object is a vehicle) that affects the degree of risk when the driver drives the travel object.

[0053] (Configuration 5) A driver monitoring device as described in Configuration 4, which includes a travel route guidance unit that guides the driver to a travel route that results in a travel environment that is recognized by the travel environment recognition unit as reducing the driving load of the driver when the predicted risk score calculation unit calculates a predicted risk score that is greater than or equal to a predetermined value. According to the driver monitoring device of configuration 5, when the predicted risk score is equal to or greater than a predetermined value, the risk of traveling by a moving body can be reduced by guiding the driver to a travel route that reduces driving load and prompting the driver to change the travel route.

[0054] (Configuration 6) A driver monitoring method executed by a computer, comprising: a biometric information recognition step of recognizing biometric information of a driver of a mobile body; a driving behavior recognition step of recognizing the driving behavior of the driver while driving the mobile body; and a predicted risk score calculation step of calculating a predicted risk score indicating the degree of risk for the movement of the mobile body due to driving by the driver from the predetermined point in time onwards, based on the driving behavior of the driver recognized by the driving behavior recognition step at a predetermined point in time while the driver is driving the mobile body, and the driving biometric information of the driver recognized by the biometric information recognition step at the predetermined point in time. By executing the driver monitoring method of the sixth aspect by a computer, the same effects as those of the driver monitoring device of the first aspect can be obtained.

[0055] (Configuration 7) A program that causes a computer to function as a biometric information recognition unit that recognizes the biometric information of a driver of a mobile body, a driving behavior recognition unit that recognizes the driving behavior of the driver while driving the mobile body, and a predicted risk score calculation unit that calculates a predicted risk score that indicates the degree of risk for the movement of the mobile body due to driving by the driver from the predetermined time point onwards, based on the driving behavior of the driver recognized by the driving behavior recognition unit at a predetermined time point while the driver is driving the mobile body and the driving biometric information of the driver recognized by the biometric information recognition unit at the predetermined time point. The configuration of the driver monitoring device of configuration 1 can be realized by executing the program of configuration 7 by a computer. [Explanation of symbols]

[0056] 1...communication terminal, 2...driver monitoring device, 10...processor, 11...biometric information recognition unit, 12...health level recognition unit, 13...driving behavior recognition unit, 14...predicted risk score calculation unit, 15...mobile object position recognition unit, 16...movement environment recognition unit, 17...movement route guidance unit, 21...program, 30...communication unit, 31...camera, 32...acceleration sensor, 33...GNSS sensor, 34...display, 35...speaker, 36...microphone, 100...vehicle, 110...ECU, 120...communication unit, 121...navigation device, 130...front camera, 131...driver monitoring camera, 132...display, 133a, 133b...speakers, 150...terminal holder, 160...wearable device, 200...communication network, 210...traffic information server, 211...vehicle management server, D...driver

Claims

1. a biometric information recognition unit that recognizes biometric information of a driver of the mobile body; a driving behavior recognition unit that recognizes driving behavior of the driver while driving the moving object; a predicted risk score calculation unit that calculates a predicted risk score indicating a degree of risk regarding the movement of the moving body due to driving by the driver from a predetermined time point onwards, based on the driving behavior of the driver recognized by the driving behavior recognition unit at the predetermined time point while the driver is driving the moving body and the driving biometric information, which is the biometric information of the driver recognized by the biometric information recognition unit at the predetermined time point; A driver monitoring device comprising:

2. a health level recognition unit that recognizes a health level of the driver based on pre-driving biological information, which is biological information of the driver recognized by the biological information recognition unit, before the driver starts driving the moving body; The predicted risk score calculation unit calculates the predicted risk score based on the driving behavior of the driver recognized from the during-driving biological information at the predetermined time point, the during-driving biological information recognized by the biological information recognition unit at the predetermined time point, and the health level of the driver recognized by the health level recognition unit. The driver monitoring device according to claim 1 .

3. The biometric information recognition unit recognizes the heart rate of the driver as the biometric information of the driver.

3. A driver monitoring device according to claim 1 or 2.

4. a mobile object position recognition unit that recognizes the position of the mobile object; a moving environment recognition unit that recognizes a moving environment of the moving body after the predetermined time point based on the position of the moving body at the predetermined time point recognized by the moving body position recognition unit, The predicted risk score calculation unit corrects the predicted risk score based on the moving environment estimated by the moving environment estimation unit.

3. A driver monitoring device according to claim 1 or 2.

5. and a travel route guidance unit that, when the predicted risk score calculation unit calculates the predicted risk score to be equal to or greater than a predetermined value, guides the user to a travel route that provides a travel environment that is recognized by the travel environment recognition unit as reducing the driving load of the driver.

5. A driver monitoring device according to claim 4.

6. 1. A computer-implemented driver monitoring method, comprising: a biometric information recognition step of recognizing biometric information of a driver of the mobile body; a driving behavior recognition step of recognizing a driving behavior of the driver while driving the moving object; a predicted risk score calculation step of calculating a predicted risk score indicating a degree of risk regarding the movement of the moving body due to driving by the driver from a predetermined time point onwards, based on the driving behavior of the driver recognized in the driving behavior recognition step at the predetermined time point while the driver is driving the moving body, and the driving biometric information, which is the biometric information of the driver recognized in the biometric information recognition step at the predetermined time point; A driver monitoring method comprising:

7. Computer, a biometric information recognition unit that recognizes biometric information of a driver of the mobile body; a driving behavior recognition unit that recognizes driving behavior of the driver while driving the moving object; a predicted risk score calculation unit that calculates a predicted risk score indicating a degree of risk regarding the movement of the moving body due to driving by the driver from a predetermined time point onwards, based on the driving behavior of the driver recognized by the driving behavior recognition unit at the predetermined time point while the driver is driving the moving body and the driving biometric information, which is the biometric information of the driver recognized by the biometric information recognition unit at the predetermined time point; A program that makes it work.

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