JP7590976B2 - Driver drowsiness prevention system, computer, terminal, driver drowsiness prevention method and program - Google Patents

Description

The present invention relates to a driver doze prevention system, a computer, a terminal, a driver doze prevention method, and a program that select and execute a preventive measure to prevent a driver from dozing off while driving.

In recent years, the harsh working conditions of drivers have become a social issue, and there have been an increasing number of news reports of drivers falling asleep while driving and causing traffic accidents. As a result, technology to prevent drivers from falling asleep while driving has attracted attention.

One example of such technology is one that detects the driver's pulse while driving and determines whether the driver is drowsy (see Patent Document 1).

JP 2011-248850 A

However, in order to prevent traffic accidents caused by the driver falling asleep while driving, it is not enough to simply determine whether the driver is asleep. Furthermore, the configuration of Patent Document 1 merely determines whether the driver is asleep and is not intended to prevent the driver from falling asleep, making it difficult to prevent the driver from falling asleep.

The present invention aims to provide a driver drowsiness prevention system, computer, terminal, driver drowsiness prevention method, and program that can acquire biometric information of a driver while driving, determine the level at which the driver is likely to fall asleep while driving, and select and execute a preventive measure corresponding to this level from among a number of preventive measures for preventing drowsiness.

The present invention provides the following solutions:

The present invention provides a driver drowsiness prevention system that selects and executes a preventive measure to prevent a driver from falling asleep while driving, comprising:
An acquisition means for acquiring biometric information of the driver;
A determination means for determining a level at which the driver is likely to fall asleep while driving by analyzing the acquired biological information;
a selection means for identifying a plurality of preventive measures corresponding to the determined level among a plurality of preventive measures for preventing dozing at the wheel , randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level, determining whether the selected preventive measure has already been selected within a predetermined interval, and if so, selecting again one preventive measure from among the plurality of preventive measures corresponding to the level excluding the selected one preventive measure, and randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level if all of the plurality of preventive measures corresponding to the level have been selected , and rotating and selecting the preventive measures for preventing dozing at a predetermined interval;
an execution means for executing the selected one of the prevention measures;
The present invention provides a driver drowsiness prevention system comprising:

According to the present invention, a driver doze prevention system that selects and executes preventive measures to prevent a driver from dozing off while driving acquires biometric information of the driver, analyzes the acquired biometric information, determines a level at which the driver is likely to doze off while driving, identifies a plurality of preventive measures for preventing dozing off according to the determined level from among a plurality of preventive measures for preventing dozing off , randomly selects one preventive measure from among the plurality of preventive measures according to the level, determines whether the selected preventive measure has already been selected within a predetermined interval, and if so, selects again one preventive measure from among the plurality of preventive measures according to the level excluding the selected one preventive measure, and if all of the plurality of preventive measures according to the level have been selected , randomly selects one preventive measure from among the plurality of preventive measures according to the level, rotates the preventive measures for preventing dozing off at a predetermined interval, and executes the selected one preventive measure.

Although this invention is in the system category, it also exerts similar functions and effects in other categories such as methods and programs according to the category.

The present invention also provides a computer for selecting and executing a preventive measure for preventing a driver from falling asleep while driving, comprising:
An acquisition means for acquiring biometric information of the driver;
A determination means for determining a level at which the driver is likely to fall asleep while driving by analyzing the acquired biological information;
a selection means for identifying a plurality of preventive measures corresponding to the determined level among a plurality of preventive measures for preventing dozing at the wheel , randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level, determining whether the selected preventive measure has already been selected within a predetermined interval, and if so, selecting again one preventive measure from among the plurality of preventive measures corresponding to the level excluding the selected one preventive measure, and if all of the plurality of preventive measures corresponding to the level have been selected , randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level, and rotating and selecting the preventive measures for preventing dozing at a predetermined interval;
an execution means for executing the selected one of the prevention measures;
The present invention provides a computer comprising:

The present invention also provides a terminal for selecting and executing a preventive measure for preventing a driver from falling asleep while driving, comprising:
an execution means for analyzing the driver's biological information, and executing one of a plurality of preventive measures for preventing dozing off at the wheel, which is determined based on a result of determining a level at which the driver is likely to doze off while driving , randomly selecting one of the preventive measures from among the plurality of preventive measures for preventing dozing off at the wheel, and if it is determined that the one selected preventive measure has already been selected within a predetermined interval, executing one preventive measure again from the plurality of preventive measures for the level excluding the one selected preventive measure, and if all of the plurality of preventive measures for the level have been selected , randomly selecting one of the preventive measures from among the plurality of preventive measures for the level, and rotating and executing the preventive measures for preventing dozing off at a predetermined interval;
The present invention provides a terminal comprising:

According to the present invention, it is possible to provide a driver drowsiness prevention system, computer, terminal, driver drowsiness prevention method, and program that can acquire biometric information of a driver while driving, determine the level at which the driver is likely to fall asleep while driving, and select and execute a prevention measure corresponding to this level from among a number of prevention measures for preventing drowsiness.

FIG. 1 is a diagram showing an outline of a driver drowsiness prevention system 1. As shown in FIG. FIG. 2 is a diagram showing the overall configuration of the driver drowsiness prevention system 1. As shown in FIG. FIG. 3 is a flowchart showing a process for executing measures to prevent drowsiness, which is executed by the computer 10. As shown in FIG. FIG. 4 is a flowchart showing a process for executing measures to prevent drowsiness, which is executed by the computer 10. As shown in FIG. FIG. 5 is a diagram showing an example of a preventive measures database recorded by the computer 10. As shown in FIG.

The best mode for carrying out the present invention will be described below with reference to the drawings. Note that this is merely an example, and the technical scope of the present invention is not limited to this example.

[Outline of Driver Drowsiness Prevention System 1]
An overview of a preferred embodiment of the present invention will be described with reference to Fig. 1. Fig. 1 is a diagram for explaining an overview of a driver drowsiness prevention system 1 according to a preferred embodiment of the present invention. The driver drowsiness prevention system 1 is a computer system that is composed of a computer 10 and that selects and executes preventive measures to prevent the driver from falling asleep while driving.

The driver doze prevention system 1 may include a driver terminal carried or worn by the driver (e.g., a mobile terminal such as a smartphone or tablet terminal, or a wearable terminal such as a head-mounted display such as smart glasses), sensors that detect various information, a photographing device that takes images such as video and still images of the vehicle driven by the driver and the driver's face and body, a measuring device that measures the driver's biometric information (e.g., heart rate, body temperature, pulse rate), an output device that outputs messages and images on the vehicle's windshield, a stimulus generating device that gives the driver some kind of stimulus (e.g., vibration, odor, sound), and other terminals and devices. In this case, the driver doze prevention system 1 executes each process described below using one or more combinations of the computer 10 and the included terminals and devices.

In addition, the driver drowsiness prevention system 1 may be realized by a single computer, such as computer 10, or may be realized by multiple computers, such as a cloud computer.

The computer 10 is connected to the driver's terminal, sensors, vehicle, imaging device, measuring device, output device, stimulus generating device, and other terminals and devices via a public line network, etc., so as to be able to communicate data, and transmits and receives the necessary data and information.

The computer 10 acquires biometric information of the driver while driving. The biometric information includes, for example, heart rate, body temperature, and pulse rate.

For example, sensors installed in the vehicle (on the steering wheel or seat) or a driver terminal worn by the driver measure the driver's biometric information while driving. The sensors and driver terminal transmit the measured biometric information to computer 10. By receiving this biometric information, computer 10 acquires the driver's biometric information while driving.

In addition, for example, a camera installed inside the vehicle captures images of the driver's face and body while driving. The camera transmits these images to computer 10. Computer 10 receives these images and performs image analysis. Computer 10 estimates biometric information of the driver while driving based on the results of the image analysis. Computer 10 acquires the estimated biometric information as the driver's biometric information.

The computer 10 analyzes the acquired biometric information to determine the level at which the driver is likely to fall asleep while driving. The level at which the driver is likely to fall asleep is a numerical representation of the driver's degree of drowsiness, with the higher the numerical value, the higher the degree of drowsiness.

For example, computer 10 analyzes the values of heart rate, body temperature, and pulse rate in the biometric information. Computer 10 determines the level based on the values in the biometric information. Computer 10 determines the level that corresponds to the current analysis result by referring to a level determination database that previously records the content and values of the biometric information in association with the levels.

The computer 10 selects a preventive measure from among a number of preventive measures for preventing drowsiness, depending on the determined level. The preventive measures include, for example, measures that stimulate the driver's five senses or measures that control the vehicle itself.

For example, the computer 10 selects a prevention measure that corresponds to the level determined this time by referring to a prevention measure database in which levels and prevention measures are previously recorded in correspondence with each other.

In addition, the computer 10 can also be configured to select the prevention measures by rotating them at a predetermined interval.

For example, when the computer 10 selects a prevention measure the next time or later, if the period between this time and the next time is a specified interval, the computer 10 will select a prevention measure that is different from the prevention measure selected this time.

The computer 10 executes the selected prevention measures.

For example, computer 10 transmits a command to a terminal or device corresponding to the selected prevention measure to execute the prevention measure. The terminal or device receives this command and executes the prevention measure selected by computer 10 in accordance with the command. As a result, computer 10 executes the selected prevention measure, and driver drowsiness prevention system 1 executes the selected prevention measure.

In addition, the computer 10 can also be configured to learn which of the implemented prevention measures prevented the driver from falling asleep and which did cause the driver to fall asleep.

For example, based on whether or not the driver was prevented from falling asleep as a result of the prevention measures being executed, computer 10 learns whether or not the driver was prevented from falling asleep by associating this result with whether or not the driver was prevented from falling asleep. When selecting a prevention measure from the next time onwards, computer 10 selects a prevention measure according to the determined level and the result of this learning.

Next, we will provide an overview of the processing performed by the driver drowsiness prevention system 1.

The computer 10 acquires biometric information of the driver while driving (step S01). The biometric information is as described above.

Sensors installed in the vehicle and a driver terminal worn by the driver measure the driver's biometric information while driving. The sensors and driver terminal transmit the measured biometric information to computer 10. By receiving this biometric information, computer 10 acquires the biometric information of the driver while driving.

An imaging device installed inside the vehicle captures images of the driver's face and body while driving. The imaging device transmits these images to computer 10. Computer 10 receives these images and performs image analysis. As part of its image analysis, computer 10 extracts feature points (e.g., shape, contour, hue) and feature quantities (e.g., statistical values such as the average, variance, histogram, etc. of pixel values). Computer 10 estimates the driver's biometric information while driving based on the extracted feature points and feature quantities. Computer 10 acquires the estimated biometric information as the driver's biometric information.

The computer 10 analyzes the acquired biometric information (step S02). The computer 10 analyzes, for example, the values of heart rate, body temperature, and pulse rate in the biometric information.

Based on the analysis results of the biometric information, the computer 10 determines the level at which the driver is likely to fall asleep while driving (step S03). This level is as described above.

The computer 10 determines this level by referring to the level determination database described above. The computer 10 determines the level that corresponds to the value in the currently acquired biometric information.

The computer 10 selects a preventive measure from among a plurality of preventive measures for preventing drowsiness, depending on the determined level (step S04). The preventive measures are as described above.

The computer 10 refers to the above-mentioned prevention measures database and selects this prevention measure. The computer 10 selects the prevention measure according to the level determined this time.

The computer 10 executes the selected prevention measures (step S05).

The computer 10 creates a command for the terminal or device corresponding to the selected prevention measure to execute this prevention measure. The computer 10 transmits this created command to the terminal or device. The terminal or device receives this command. The terminal or device executes the prevention measure according to this command. As a result, the computer 10 executes the selected prevention measure, and the driver drowsiness prevention system 1 executes the selected prevention measure.

The above is an overview of the processing performed by the driver drowsiness prevention system 1.

[System Configuration of Driver Drowsiness Prevention System 1]
The system configuration of the driver drowsiness prevention system 1 according to a preferred embodiment of the present invention will be described with reference to Fig. 2. Fig. 2 is a diagram showing the system configuration of the driver drowsiness prevention system 1 according to a preferred embodiment of the present invention. In Fig. 2, the driver drowsiness prevention system 1 is a computer system that is composed of a computer 10 and selects and executes preventive measures to prevent the driver from falling asleep while driving.

The computer 10 is connected to the driver's terminal, sensors, vehicle, imaging device, measuring device, output device, stimulus generating device, and other terminals and devices, etc., via a public line network, etc., so as to be able to communicate data, and transmits and receives the necessary data and information.

The driver doze prevention system 1 may include a driver terminal, sensors, a vehicle, a photographing device, a measuring device, an output device, a stimulus generating device, and other terminals and devices, which are not shown. In this case, the driver doze prevention system 1 executes each process described below using the computer 10 and one or more combinations of the included terminals and devices.

In addition, the driver drowsiness prevention system 1 may be realized by a single computer, such as computer 10, or may be realized by multiple computers, such as a cloud computer.

In addition, the driver drowsiness prevention system 1 may be realized by a single computer, such as computer 10, or may be realized by multiple computers, such as a cloud computer.

The computer 10 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), etc., and includes, as a communication unit, a device for enabling communication with other terminals and devices, such as a Wi-Fi (Wireless-Fidelity) compatible device conforming to IEEE802.11. The computer 10 also includes, as a recording unit, a data storage unit such as a hard disk, semiconductor memory, recording medium, memory card, etc. The computer 10 also includes, as a processing unit, various devices that execute various processes.

In the computer 10, the control unit loads a specified program and cooperates with the communication unit to realize a biometric information acquisition module 20 and a prevention measure execution module 21. In the computer 10, the control unit loads a specified program and cooperates with the recording unit to realize a recording module 30. In the computer 10, the control unit loads a specified program and cooperates with the processing unit to realize an analysis module 40, a judgment module 41, a selection module 42, a command creation module 43, a prevention judgment module 44, and a learning module 45.

[Processing for Implementing Measures to Prevent Drowsiness]
The process of executing measures to prevent dozing at the wheel, which is executed by the driver dozing prevention system 1, will be described with reference to Figures 3 and 4. Figures 3 and 4 are flowcharts of the process of executing measures to prevent dozing at the wheel, which is executed by the computer 10. The processes executed by each of the above-mentioned modules will be described together with this process.

First, the biometric information acquisition module 20 acquires biometric information of the driver while driving (step S10). In step S10, the biometric information is the driver's heart rate, body temperature, pulse rate, etc., as described above. The biometric information acquisition module 20 acquires biometric information measured by a terminal or device, or acquires as biometric information the results of estimation based on an image captured by an imaging device. In the following explanation, the biometric information acquisition module 20 will be described as acquiring heart rate as biometric information. It goes without saying that the present invention can be applied to things other than heart rate.

This section describes the case where the biometric information acquisition module 20 acquires biometric information measured by a terminal or device.

Sensors installed on the steering wheel or seat, or a driver terminal or measuring device worn by the driver, measure the driver's heart rate while driving. These terminals and devices transmit the measured heart rate to computer 10 as biometric information. The biometric information acquisition module 20 receives this heart rate and acquires the biometric information.

We will explain the case where the biometric information acquisition module 20 acquires biometric information based on an image captured by the imaging device.

The imaging device captures an image of the driver's face and body while driving. The imaging device transmits the captured image to the computer 10 as image information. The biometric information acquisition module 20 receives the image information. Based on this image information, the biometric information acquisition module 20 performs image analysis of the image of the driver while driving and extracts feature points and features of the image. The biometric information acquisition module 20 identifies pulse wave information based on the extracted feature points and features. The biometric information acquisition module 20 estimates the driver's heart rate based on this identified pulse wave information. The biometric information acquisition module 20 acquires this estimated heart rate as biometric information.

In addition, the biometric information acquisition module 20 may acquire biometric information by methods other than the examples described above.

The analysis module 40 analyzes the acquired biometric information (step S11). In step S11, the analysis module 40 analyzes the heart rate, which is the acquired heart rate value. The analysis module 40 analyzes the heart rate per unit time.

In addition, the analysis module 40 may analyze biometric information using methods other than the examples described above.

Based on the analysis results of the acquired biometric information, the judgment module 41 judges the level at which the driver is likely to fall asleep while driving (step S12). In step S12, the level at which the driver is likely to fall asleep while driving is a numerical representation of the driver's degree of drowsiness, with a higher numerical value indicating a higher degree of drowsiness and a lower numerical value indicating a lower degree of drowsiness.

The judgment module 41 judges this level by referring to a level judgment database previously recorded by the recording module 30. The level judgment database registers the contents and values of biometric information in association with this level. The judgment module 41 compares the heart rate, which is the biometric information judged this time, with the heart rates registered in the level judgment database, and identifies those that match or are close. In this case, if there are multiple levels of closeness, the judgment module 41 identifies the higher level as the closeness. The judgment module 41 judges this identified level as the level at which the driver is likely to fall asleep while driving.

If the value of the analyzed biometric information does not match or approximate any of the values registered in the level determination database, the determination module 41 determines that the level is 0. If the determination module 41 determines that the level is 0, the computer 10 determines that the driver is not drowsy, and ends this process.

The selection module 42 selects a preventive measure from among a plurality of preventive measures for preventing drowsiness, according to the level determined this time (step S13). In step S13, the selection module 42 refers to the preventive measures database recorded in advance by the recording module 30 and selects this preventive measure. The preventive measures database is a database in which the level at which the driver is likely to fall asleep is associated with preventive measures for preventing the driver from falling asleep and registered. These preventive measures are measures that stimulate the driver's five senses or control the vehicle itself. The preventive measures include generating a sound similar to a heartbeat for the driver, providing some kind of stimulus to the driver (e.g., seat vibration, odor generation, explosion sound, unpleasant sound), projecting a message (e.g., support from family, warning of risks caused by falling asleep or traffic accidents, notification that the driver is about to fall asleep) on the windshield, projecting an image (e.g., family, the driver's state when he was about to fall asleep in the past, victims of traffic accidents and vehicles) on the windshield, and slowing or stopping the vehicle.

Note that the prevention measures are not limited to the examples mentioned above and can be modified as appropriate.

[Preventive Measures Database]
Based on FIG. 5, the prevention measures database recorded by the recording module 30 will be described. FIG. 5 is a diagram showing an example of the prevention measures database. In FIG. 5, the prevention measures database is registered with a level and a prevention measure associated with each other. In the prevention measures database, a plurality of prevention measures are registered with each level associated with each other. In level 1, "emitting a sound similar to a heart sound" is registered as the first prevention measure, and "vibrating the seat" is registered as the second prevention measure. In level 2, "projecting a message on the windshield" is registered as the first prevention measure, and "issuing an alert from a smartphone" is registered as the second prevention measure. In level 3, "projecting an image on the windshield" is registered as the first prevention measure, and "generating an unpleasant sound" is registered as the second prevention measure. In level 4, "generating an explosion sound" is registered as the first prevention measure, and "generating an odor" is registered as the second prevention measure. In level 5, "stopping the vehicle" is registered as the first prevention measure. In the preventive measures database, the higher the level, the more the preventive measures that are more effective in waking up the driver from drowsiness are associated with the higher the level. That is, the preventive measures database registers preventive measures according to the degree of drowsiness of the driver.

Although not shown, each prevention measure is linked to a terminal or device that executes the prevention measure. "Emitting a sound similar to a heartbeat" is linked to the driver's terminal or a speaker in the vehicle driven by the driver. "Vibrating the seat" is linked to a stimulus generating device provided in the seat of the vehicle driven by the driver. "Projecting a message on the windshield" is linked to the windshield of the vehicle driven by the driver and an output device that outputs a message to the windshield. "Giving an alert from a smartphone" is linked to the driver's terminal. "Projecting an image on the windshield" is linked to the windshield of the vehicle driven by the driver and an output device that outputs an image to the windshield. "Generating an unpleasant sound" is linked to the driver's terminal or a speaker in the vehicle driven by the driver. "Generating an explosion sound" is linked to the driver's terminal or a speaker in the vehicle driven by the driver. "Generating an odor" is linked to a stimulus generating device provided in the vehicle driven by the driver. "Stop vehicle" is linked to the vehicle that the driver is driving.

Note that the levels and the contents of the prevention measures registered in the prevention measures database are not limited to the above-mentioned examples and can be changed as appropriate. Also, the number of levels and prevention measures is not limited to the above-mentioned examples and can be changed as appropriate.

The selection module 42 compares the currently determined level with the levels registered in the prevention measures database and identifies a match. The selection module 42 identifies multiple prevention measures associated with the identified level. The selection module 42 selects one prevention measure from among the multiple prevention measures based on a predetermined condition (e.g., random, a preset order).

A specific example in which the selection module 42 selects one prevention measure is described below.

If the currently determined level is 2, the selection module 42 refers to the prevention measures database and identifies the prevention measures associated with the currently determined level, level 2. As a result, the selection module 42 identifies "projecting a message on the windshield" and "issuing an alert from a smartphone" as the prevention measures. The selection module 42 randomly selects one of these two prevention measures.

The selection module 42 judges whether the currently selected preventive measure has been selected within a predetermined interval (step S14). In step S14, the selection module 42 judges whether the currently selected preventive measure has already been selected within a predetermined interval, such as within one hour, within several hours, within one day, within several days, etc. If the selection module 42 judges that the currently selected preventive measure has been selected within a predetermined interval (step S14 YES), the selection module 42 reselects a preventive measure from among the multiple preventive measures for preventing dozing off, among the preventive measures corresponding to the level determined this time, excluding the preventive measure selected by the above-mentioned step S13 processing (step S15). The processing of step S15 is substantially similar to the processing of step S13 described above, but differs in that a preventive measure corresponding to the level is selected from among the preventive measures other than the preventive measure selected by the above-mentioned step S13 processing. That is, the processing of step S15 selects one preventive measure from among the preventive measures not selected by the selection module 42.

After executing the process of step S15, the computer 10 executes the process of step S14 described above again. Here, if the selection module 42 determines that the currently selected preventive measure has not been selected within a predetermined interval, it executes the process of step S16 described below.

On the other hand, if the selection module 42 determines that the preventive measures selected this time were selected within a predetermined interval, it executes the process of step S15 described above again. If the computer 10 determines, as a result of repeating these processes, that all preventive measures corresponding to the determined level have been selected within a predetermined interval, it selects one of the multiple preventive measures based on a predetermined condition (e.g., random, a preset order) and executes the process of step S16 described below in accordance with the selected one preventive measure. In other words, if all preventive measures corresponding to the determined level have been selected within a predetermined period, the computer 10 selects one preventive measure in accordance with the above-mentioned predetermined condition, regardless of whether it has been selected in the past.

As a result, the computer 10 will select the preventive measures to be selected by rotating them at predetermined intervals.

On the other hand, if it is determined in step S14 that the currently selected preventive measure has not been selected within a predetermined interval (step S14 NO), the command creation module 43 creates a command for causing the terminal, device, or vehicle to execute the selected preventive measure (step S16). In step S16, the command creation module 43 creates a command required for the terminal, device, or vehicle linked to the selected preventive measure to execute this preventive measure.

Based on the example above, the processing performed by the command creation module 43 will be explained.

When "emit a sound similar to a heart sound" is selected as a preventive measure, the command creation module 43 creates a command required for the driver terminal or the vehicle to output a sound similar to a heart sound that has been recorded in advance. When "vibrate the seat" is selected as a preventive measure, the command creation module 43 creates a command required for the stimulus generating device to generate vibrations. When "project a message on the windshield" is selected as a preventive measure, the command creation module 43 creates a command required for the output device or the vehicle to project a message that has been recorded in advance on the windshield. When "alert from smartphone" is selected as a preventive measure, the command creation module 43 creates a command required for the driver terminal to output a pre-recorded alert. When "project an image on the windshield" is selected as a preventive measure, the command creation module 43 creates a command required for the output device or the vehicle to project an image that has been recorded in advance on the windshield. When "generate an unpleasant sound" is selected as a preventive measure, the command creation module 43 creates a command required for the driver terminal or the vehicle to output a pre-recorded unpleasant sound. When "generate an explosion sound" is selected as a preventive measure, the command creation module 43 creates a command required for the driver terminal or the vehicle to output a pre-recorded explosion sound. The command creation module 43 creates a command required for the stimulus generator to generate an odor if "generate an odor" is selected as a preventive measure. The command creation module 43 creates a command required for the vehicle to stop if "stop the vehicle" is selected as a preventive measure.

The prevention measure execution module 21 transmits the created command to the corresponding terminal, device, or vehicle, and executes the selected prevention measure (step S17). In step S17, the terminal, device, or vehicle receives the created command. These execute the prevention measure according to this command. As a result, the computer 10 executes the selected prevention measure, and the driver drowsiness prevention system 1 executes the selected prevention measure.

Based on the examples above, we will explain the prevention measures implemented by terminals, devices, and vehicles.

When the driver terminal or vehicle receives the command "emit a sound similar to a heartbeat," it outputs a sound similar to a heartbeat that it has recorded in advance from the speaker. When the stimulus generating device receives the command "vibrate the seat," it vibrates the seat. When the output device or vehicle receives the command "project a message onto the windshield," it projects a message that it has recorded in advance onto the windshield. When the driver terminal receives the command "issue an alert from a smartphone," it outputs an alert that it has recorded in advance. When the output device or vehicle receives the command "project an image onto the windshield," it projects an image that it has recorded in advance onto the windshield. When the driver terminal or vehicle receives the command "generate an unpleasant sound," it outputs an unpleasant sound that it has recorded in advance from the speaker. When the driver terminal or vehicle receives the command "generate an explosion sound," it outputs an explosion sound that it has recorded in advance from the speaker. When the stimulus generating device receives the command "generate an odor," it generates an odor. When the vehicle receives the command "stop the vehicle," it stops the vehicle.

The biometric information acquisition module 20 again acquires the biometric information of the driver while driving after the preventive measures are implemented (step S18). The process of step S18 is the same as the process of step S10 described above.

The analysis module 40 analyzes the biometric information acquired again (step S19). The process of step S19 is the same as the process of step S11 described above.

Based on the analysis results of the reacquired biometric information, the determination module 41 determines the level to which the driver is likely to fall asleep while driving (step S20). The process of step S20 is the same as the process of step S12 described above.

The prevention judgment module 44 judges whether the currently executed prevention measure has prevented the driver from falling asleep while driving based on the analysis result of the bioinformation (step S21). In step S21, the prevention judgment module 44 judges whether the level based on the analysis result of the bioinformation is 0. This is because if the level is 0, it can be determined that the driver has woken up.

If the prevention judgment module 44 judges that the driver has been prevented from falling asleep (step S21 YES), i.e., if the judged level is 0, it judges that the driver has been prevented from falling asleep, and the recording module 30 records the currently executed prevention measure and the fact that the driver has been prevented from falling asleep (the driver has woken up) as associated information on awakening (step S22). After executing this process, the computer 10 executes the process of step S29 described below.

On the other hand, in step S21, when the prevention determination module 44 determines that the driver's dozing has not been prevented (step S21 NO), that is, when the determined level is 1 or more, it determines whether or not the level is equal to or higher than the level determined by the process of step S12 described above (step S23). In step S23, the prevention determination module 44 determines whether or not the degree of dozing has changed before and after the prevention measure is executed. If the prevention determination module 44 determines that the level is lower than the level determined last time (step S23 NO), it determines that the driver's dozing has not been prevented but has had a certain effect, and the recording module 30 records the currently executed prevention measure and the fact that it has had a certain effect as partial awakening information in association with each other (step S24). After executing this process, the computer 10 determines that the driver's dozing has not been prevented and executes the process of step S26 described later.

On the other hand, in step S23, if the prevention judgment module 44 judges that the level is equal to or higher than the level judged previously (step S23 YES), it judges that the driver's drowsiness has not been prevented, and the recording module 30 records the currently executed preventive measure and the fact that it was ineffective as non-awakening information (step S25).

The selection module 42 selects a prevention measure corresponding to a level higher than the level determined by the processing of step S12 described above (step S26). In step S26, the selection module 42 selects a prevention measure corresponding to a level higher than the level determined previously. The selection module 42 selects a prevention measure corresponding to a level that is one or more steps higher than the previous level.

When selecting a prevention measure corresponding to the determined level, the computer 10 executes the processing of steps S14 and S15 described above, and selects a prevention measure corresponding to the currently determined level.

In addition, when the level is higher than the level determined by the processing of step S12 described above by a predetermined range or more, the selection module 42 can select a prevention measure corresponding to the highest level in the prevention measure database or the next highest level. Specifically, when the level determined previously is 1 and the level determined this time is 3, the selection module 42 selects a prevention measure corresponding to the highest level 5 or the next highest level 4 among the levels registered in the prevention measure database in FIG. 5 described above.

The command creation module 43 creates a command for causing the terminal, device, or vehicle to execute the selected prevention measure (step S27). The process of step S27 is the same as the process of step S16 described above.

The prevention measure execution module 21 transmits the created command to the corresponding terminal, device, or vehicle to execute the selected prevention measure (step S28). The process of step S28 is the same as the process of step S17 described above.

After executing the selected prevention measure, the computer 10 will again execute the processing from step S18 onwards described above, and will continue to do so until the driver stops falling asleep while driving.

In addition, even if the computer 10 has executed a predetermined number of preventive measures or all of the preventive measures, if the driver does not stop falling asleep while driving, the computer 10 may be configured to execute a combination of multiple preventive measures registered in the preventive measures database or all of the preventive measures at once.

In this embodiment, for the sake of simplicity, it is described that the processing of step S29 described below is executed after the processing of step S28 described above.

The learning module 45 learns the awakening information, partial awakening information, and non-awakening information (step S29). In step S29, the learning module 45 learns the preventive measures taken and their results (woke up, did not wake up but had a certain effect, or did not wake up at all) in association with each other. In other words, the learning module 45 learns which preventive measures for the driver while driving woke up the driver from drowsiness and which did not wake up the driver from drowsiness. At this time, the learning module 45 also learns the identifier of the target driver, etc., and learns effective preventive measures for a specific driver.

In addition, the learning module 45 may be configured not to learn the identifiers of the target drivers, but to learn effective preventive measures against unspecified drivers.

The recording module 30 records the learning results (step S30).

From the next time onwards, when the computer 10 executes the processing of steps S13 and S26 described above, it will take the learning results into account and select a prevention measure.

Let us explain this example in detail.

In the above-mentioned processing of steps S13 and S26, the selection module 42 selects a prevention measure according to the determined level and the learning result. The selection module 42 selects a prevention measure from among the prevention measures registered in the prevention measure database that correspond to the determined level, excluding prevention measures corresponding to partial awakening information and/or non-awakening information. At this time, if all prevention measures associated with the determined level have been excluded, the selection module 42 selects a prevention measure associated with a level higher than the determined level. Furthermore, if all prevention measures associated with this higher level have been excluded, the selection module 42 can also select a prevention measure associated with a higher level or a combination of multiple prevention measures associated with the determined level or a higher level.

In addition, the selection module 42 may be configured to give a lower priority when selecting partial awakening information and/or non-awakening information.

The above is the process for implementing measures to prevent drowsiness.

The above-mentioned means and functions are realized by a computer (including a CPU, an information processing device, and various terminals) reading and executing a predetermined program. The program is provided, for example, in the form of software as a service (SaaS) provided from the computer via a network. The program is also provided in a form recorded on a computer-readable recording medium, such as a flexible disk, CD (CD-ROM, etc.), DVD (DVD-ROM, DVD-RAM, etc.). In this case, the computer reads the program from the recording medium, transfers it to an internal or external recording device, records it, and executes it. The program may also be recorded in advance on a recording device (recording medium), such as a magnetic disk, optical disk, or magneto-optical disk, and provided to the computer from the recording device via a communication line.

Although the embodiments of the present invention have been described above, the present invention is not limited to these embodiments described above. Furthermore, the effects described in the embodiments of the present invention are merely a list of the most favorable effects resulting from the present invention, and the effects of the present invention are not limited to those described in the embodiments of the present invention.

1 Driver drowsiness prevention system, 10 Computer

Claims (7)

A driver drowsiness prevention system that selects and executes a preventive measure to prevent a driver from falling asleep while driving, the preventive measure comprising:
An acquisition means for acquiring biometric information of the driver;
A determination means for determining a level at which the driver is likely to fall asleep while driving by analyzing the acquired biological information;
a selection means for identifying a plurality of preventive measures corresponding to the determined level among a plurality of preventive measures for preventing dozing at the wheel , randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level, determining whether the selected preventive measure has already been selected within a predetermined interval, and if so, selecting again one preventive measure from among the plurality of preventive measures corresponding to the level excluding the selected one preventive measure, and randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level if all of the plurality of preventive measures corresponding to the level have been selected , and rotating and selecting the preventive measures for preventing dozing at a predetermined interval;
an execution means for executing the selected one of the prevention measures;
A driver drowsiness prevention system comprising: A learning means for learning which of the implemented preventive measures did not cause the driver to fall asleep and which of the implemented preventive measures did cause the driver to fall asleep;
Further equipped with
the selection means selects the one of the prevention measures according to the determined level and a learning result.
2. The driver drowsiness prevention system according to claim 1. The selection means selects the preventive measures for preventing drowsiness at predetermined intervals in a rotating manner according to the determined level.
2. The driver drowsiness prevention system according to claim 1. A computer that selects and executes a preventive measure to prevent a driver from falling asleep while driving, the computer comprising:
An acquisition means for acquiring biometric information of the driver;
A determination means for determining a level at which the driver is likely to fall asleep while driving by analyzing the acquired biological information;
a selection means for identifying a plurality of preventive measures corresponding to the determined level among a plurality of preventive measures for preventing dozing at the wheel , randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level, determining whether the selected preventive measure has already been selected within a predetermined interval, and if so, selecting again one preventive measure from among the plurality of preventive measures corresponding to the level excluding the selected one preventive measure, and randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level if all of the plurality of preventive measures corresponding to the level have been selected , and rotating and selecting the preventive measures for preventing dozing at a predetermined interval;
an execution means for executing the selected one of the prevention measures;
A computer comprising: A terminal that selects and executes a preventive measure to prevent a driver from falling asleep while driving,
an execution means for analyzing the driver's biological information, and executing one of a plurality of preventive measures for preventing dozing off at the wheel, which is determined based on a result of determining a level at which the driver is likely to doze off while driving , randomly selecting one of the preventive measures from among the plurality of preventive measures for preventing dozing off at the wheel, and if it is determined that the one selected preventive measure has already been selected within a predetermined interval, executing one preventive measure again from the plurality of preventive measures for the level excluding the one selected preventive measure, and if all of the plurality of preventive measures for the level have been selected , randomly selecting one of the preventive measures from among the plurality of preventive measures for the level, and rotating and executing the preventive measures for preventing dozing off at a predetermined interval;
A terminal comprising: 1. A method for preventing a driver from falling asleep while driving, the method being executed by a computer to select and execute a preventive measure for preventing a driver from falling asleep while driving, the method comprising:
acquiring biometric information of the driver;
analyzing the acquired biological information to determine a level at which the driver is likely to fall asleep while driving;
a step of: identifying a plurality of preventive measures corresponding to the determined level among a plurality of preventive measures for preventing dozing at the wheel ; randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level ; determining whether the selected one preventive measure has already been selected within a predetermined interval; if the one preventive measure has already been selected, reselecting one preventive measure from among the plurality of preventive measures corresponding to the level excluding the selected one preventive measure; if all of the plurality of preventive measures corresponding to the level have been selected , randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level; and rotating and selecting the preventive measures for preventing dozing at a predetermined interval;
executing the selected one of the prevention measures;
1. A computer-implemented method for preventing driver drowsiness, comprising: A computer that selects and executes a preventive measure to prevent a driver from falling asleep while driving,
acquiring biometric information of the driver;
analyzing the acquired biological information to determine a level at which the driver is likely to fall asleep while driving;
a step of identifying a plurality of preventive measures corresponding to the determined level among a plurality of preventive measures for preventing dozing at the wheel, randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level, determining whether the selected one preventive measure has already been selected within a predetermined interval, and if so, selecting again one preventive measure from among the plurality of preventive measures corresponding to the level excluding the selected one preventive measure, and if all of the plurality of preventive measures corresponding to the level have been selected , randomly selecting one preventive measure from among the plurality of preventive measures corresponding to the level, and rotating and selecting the preventive measures for preventing dozing at a predetermined interval;
executing the selected one of the prevention measures;
A computer readable program for executing the program.

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