JP2010017403A - Apparatus and method for detecting driver abnormality and program for detection and treatment of driver abnormality - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To prevent an accident caused by psychological abnormality of a driver. <P>SOLUTION: When a physical abnormality is detected, a driver abnormality detection apparatus detects the psychological abnormality of the driver from the driver information input from each various in-vehicle sensor and the driver information acquired from each in-vehicle device. Next, the severity of the psychological abnormality of the driver is measured by monitoring the driver reaction with output of a message for calling on the driver. Subsequently, a coping treatment corresponding to the measured severity is aquired from the coping treatment table, and the acquired coping treatment is operated. <P>COPYRIGHT: (C)2010,JPO&INPIT

Description

  The present invention relates to a driver abnormality detection device, a driver abnormality detection method, and a driver abnormality detection processing program.

  Conventionally, in order to prevent accidents caused by changes in the driver's physical condition, driving based on sensor values from various sensors (such as microphones, cameras, body temperature sensors, pulse sensors, etc.) provided in the passenger compartment There has been proposed a technique for taking measures to alleviate the change in the physical condition of the driver when the change in the physical condition occurring in the driver is detected.

  In Patent Document 1, when the driver's fatigue is detected based on sensor values acquired by various sensors, for example, a comfortable music or a message prompting a break is output to the passenger compartment. Techniques for taking measures to alleviate physical changes are disclosed.

JP 2006-282111 A

  By the way, the technique disclosed in Patent Document 1 described above detects and copes with a driver's physical abnormality such as fatigue, but does not detect and cope with a driver's mental abnormality. There is a problem that it may not be possible to completely prevent an accident caused by a driver's mental change.

  Therefore, the present invention has been made to solve the above-described problems of the prior art, and a driver abnormality detection device and a driver abnormality that can prevent an accident caused by a mental change of the driver. It is an object to provide a detection method and a driver abnormality detection processing program.

  In order to solve the above-described problems and achieve the object, the present invention relates to mental abnormality detection information for detecting a mental abnormality occurring in a driver in association with various in-vehicle sensors and various in-vehicle devices. The mental abnormality detection information storage means for storing the information in advance, and the mental abnormality detection information that matches the driver information input from the various in-vehicle sensors and the various in-vehicle devices with reference to the mental abnormality detection information storage means An information search means for searching for information, and a measure for controlling the various on-vehicle devices to cope with a driver's mental change when the information search means searches for the mental change detection information. And coping processing execution means for executing processing.

  Further, the present invention stores in advance mental abnormality detection information for detecting a mental abnormality occurring in the driver in association with driver information acquired by various in-vehicle sensors and various in-vehicle devices. By referring to the mental abnormality detection information storage unit, an information retrieval step for retrieving the mental abnormality detection information that matches the driver information input from the various in-vehicle sensors and the various in-vehicle devices, and the information retrieval step A coping process execution step of controlling the various in-vehicle devices to execute coping process for coping with the driver's mental abnormality when the mental abnormality detection information is retrieved. It is characterized by.

  Further, the present invention stores in advance mental abnormality detection information for detecting a mental abnormality occurring in the driver in association with driver information acquired by various in-vehicle sensors and various in-vehicle devices. By referring to the mental change detection information storage unit, an information search procedure for searching for the mental change detection information that matches the driver information input from the various in-vehicle sensors and the various in-vehicle devices, and the information search procedure When the mental abnormality detection information is retrieved, a countermeasure processing execution procedure for controlling the various in-vehicle devices and executing a countermeasure processing for coping with the driver's mental abnormality is executed on the computer. It is characterized by making it.

  ADVANTAGE OF THE INVENTION According to this invention, there exists an effect that the accident resulting from a driver | operator's mental abnormality can be prevented.

  Exemplary embodiments of a driver abnormality detection device, a driver abnormality detection method, and a driver abnormality detection processing program according to the present invention will be described below in detail with reference to the accompanying drawings. In addition, below, after describing Example 1 as one embodiment of the driver abnormality detection device according to the present invention, other embodiments included in the present invention will be described.

  In the following first embodiment, the outline and features of the driver abnormality detection device according to the first embodiment, the configuration and processing of the driver abnormality detection device will be described in order, and finally the effects of the first embodiment will be described.

[Outline and Features of Driver Abnormality Detection Device (Example 1)]
First, the outline and characteristics of the driver assistance apparatus according to the first embodiment will be described with reference to FIG. FIG. 1 is a diagram for explaining the outline and features of the driver assistance apparatus according to the first embodiment.

  The driver abnormality detection device according to the first embodiment is mounted on a vehicle and is based on information acquired by various sensors (for example, a microphone, a camera, a body temperature sensor, a pulse sensor, and the like) provided in the vehicle interior. When an abnormality in the physical condition occurring in the vehicle is detected, the outline of the processing is to deal with the abnormality in the physical condition of the driver.

  And the driver abnormality detection apparatus which concerns on Example 1 has the main characteristics in the point which prevents the accident resulting from a driver | operator's mental abnormality.

  This main feature will be specifically described. As shown in FIG. 1, the driver abnormality detection device is connected to various in-vehicle sensors and various in-vehicle devices.

  Various in-vehicle sensors include a pulse sensor that detects the driver's pulse, a body temperature sensor that detects the driver's body temperature, an in-vehicle camera that captures the driver's facial expression, and the like. Output to the anomaly detector.

  Various vehicle-mounted devices include a navigation device that provides navigation information to the driver, a car stereo system that provides music and video, a mobile phone connected by the vehicle-mounted device, and the like, and acquires driver information related to the driver.

  Further, the driver abnormality detection device includes a physical abnormality detection table used for detecting a driver's physical abnormality, a mental abnormality detection table used for detecting a driver's mental abnormality, and a coping process for dealing with the driver's mental abnormality. Is stored in advance.

  And a driver | operator abnormality detection apparatus detects a physical abnormality in a driver | operator based on the driver | operator information input from various vehicle-mounted sensors (refer (1) of FIG. 1).

  For example, when an image of a driver frowning is input from an in-vehicle camera as driver information, the physical anomaly detection table is referred to the in-vehicle camera item and the physical anomaly detection information that “grinds face” Try searching for.

  As a result of the search, when physical anomaly detection information “grimacing” is retrieved from the physical anomaly detection table, the physical anomaly is detected on the assumption that the driver shows signs of physical anomaly.

  When a physical abnormality is detected, the driver abnormality detection device detects a psychological change in the driver based on driver information input from various in-vehicle sensors and driver information acquired from each in-vehicle device (FIG. 1). (See (2)).

  For example, the driver abnormality detection device acquires a call transmission history of a predetermined number of times or more to a specific partner (heterosexuality) from a mobile phone connected via a mobile connector. Then, the psychological change detection table is referred to with respect to the item of the mobile phone, and an attempt is made to search for mental change detection information of “call history of a predetermined number of calls to a specific partner (sex)”.

  As a result of the search, when mental change detection information “call history of a predetermined number of calls to a specific partner (heterosexuality)” is searched from the mental change detection table, the driver has experienced mental change. Detect as a thing.

  Next, the driver abnormality detection device measures the severity of the driver's mental abnormality by outputting a message calling the driver to detect the driver's reaction (see (3) in FIG. 1). .

  For example, the driver abnormality detection device reduces the severity of the mental change of the driver when a response within a predetermined time by the driver is detected in response to a message called to the driver.

  And a driver | operator abnormality detection apparatus acquires the countermeasure process matched with the measured severity from a countermeasure process table, and performs the acquired countermeasure process (refer (4) of FIG. 1).

  For example, when the measured severity is mild, the driver abnormality detection device operates the car stereo system and outputs the driver's favorite music and video.

  For this reason, the driver abnormality detection device according to the first embodiment can prevent an accident caused by a driver's mental change as in the main feature described above.

[Configuration of Driver Abnormality Detection Device (Example 1)]
Next, the configuration of the driver abnormality detection device according to the first embodiment will be described with reference to FIGS. FIG. 2 is a block diagram illustrating a configuration of the driver abnormality detection device according to the first embodiment. FIG. 3 is a diagram illustrating a configuration example of the body abnormality detection table according to the first embodiment. FIG. 4 is a diagram illustrating an example of the configuration of the mental disorder detection table according to the first embodiment. FIG. 5 is a diagram illustrating a configuration example of a countermeasure processing table according to the first embodiment.

  As shown in FIG. 2, the driver assistance apparatus 200 according to the first embodiment is mounted on a vehicle together with the in-vehicle sensor group and the in-vehicle apparatus group, and is connected to the in-vehicle sensor group and the in-vehicle apparatus group. The in-vehicle sensor group includes a biological information acquisition sensor group 110 and a vehicle state acquisition sensor group 120, and the in-vehicle device group includes a lamp / switch / illumination group 130 and an in-vehicle device group 140.

  The biological information acquisition sensor group 110 is a collection of sensors that acquire driver's biological information. For example, an in-vehicle camera that acquires information related to the driver's facial expression, a body temperature sensor that acquires information related to the driver's body temperature, and driving. A pulse sensor that acquires information related to the person's pulse, an in-vehicle microphone that acquires voice information of the rider, and the like are included.

  The biological information acquisition sensor group 110 outputs the acquired biological information of the driver to the driver abnormality detection device 200 as driver information.

  The vehicle state acquisition sensor group 120 is a collection of sensors that acquire information related to the state of the vehicle interior and the running state of the vehicle. For example, the vehicle state acquisition sensor group 120 is a seat sensor that detects seating on a seat installed in the vehicle interior, and measures vehicle speed. A vehicle speed sensor that detects a brake operation, a brake sensor that detects a brake operation, and the like.

  The vehicle state acquisition sensor group 120 outputs the acquired information on the state of the passenger compartment to the driver abnormality detection device 200 as driver information.

  The lamp / switch / illumination group 130 includes, for example, lamps such as hazard lamps and tail lamps, switches such as blinker switches and horn switches, and illuminations such as vehicle interior lighting and underfloor lighting.

  The in-vehicle device group 140 includes, for example, a navigation device, a car stereo system, an air conditioner, a mobile phone connected to a portable connector, a vehicle control system, and the like.

  The navigation device includes GPS information acquired from GPS (Global Positioning System) satellites, navigation information created using map data and the like (for example, current position, destination, moving direction, moving speed, etc.), etc. Remember.

  For example, the portable connector connects the cellular phone and the driver abnormality detection device 200 in a state where information stored in the cellular phone owned by the driver can be read.

  As shown in FIG. 2, the driver abnormality detection device 200 includes a physical abnormality detection table 210, a mental abnormality detection table 220, a coping process table 230, a driver information input reception unit 240, and a physical abnormality detection unit 250. , A psychological change detection unit 260, a severity measurement unit 270, and a coping process execution unit 280.

  For example, as shown in FIG. 3, the physical anomaly detection table 210 stores in advance physical anomaly detection information for detecting a driver's physical anomaly for each sensor type. This physical anomaly detection information is set in advance as an indication of a driver's physical anomaly.

  For example, when driver information (driver's facial expression) such as “moving in small steps”, “grimacing”, “shed tears” is acquired by an in-vehicle camera, Signs shall be seen.

  For example, as shown in FIG. 4, the psychological change detection table 220 is associated with mental change information for detecting a driver's mental change for each sensor / on-vehicle device type, and information on mental factors. Remember. This mental abnormality detection information is set in advance as an indication of a driver's mental abnormality.

  For example, when the driver information “mail transmission history or call transmission history more than a predetermined number of times to a specific partner (heterosexuality)” is acquired from a mobile phone, the driver shows signs of physical abnormality. It is assumed that the cause of the psychological change is “worries about romance”.

  In addition, when the driver information “received calls more than a predetermined number of times from a financial operator” is obtained from a mobile phone, the driver will show signs of physical change, and the psychological change factor is “ "Money trouble".

  In addition, when the driver information that “there is a driver (one person)” is acquired by the seat sensor and the driver information that “the destination setting is a suicide spot” is acquired from the navigation device, Symptom of abnormal change is seen, and the psychological change factor is "life trouble".

  For example, as shown in FIG. 5, the coping process table 230 stores psychological change coping processes for coping with the driver's mental changes in association with the severity levels composed of levels 1 to 3. To do.

  Severity level 1 corresponds to a case where the driver reacts to the message of the call within a predetermined time (for example, within 5 seconds), and is a mild symptom. Severity level 2 corresponds to a case where the driver reacts to a call message outside a predetermined time (for example, within 5 seconds), and is a moderate symptom. Severity level 3 corresponds to the case where the driver does not respond to the call message, and is a severe symptom.

  In the case of severity level 1 (slight symptom), for example, the coping process “operate the car stereo system to provide the driver's favorite music / video” is stored. In the case of severity level 2 (medium symptom), for example, a handling process of “operating the navigation device to provide route guidance to a place with good scenery” is stored.

  In the case of severity level 3 (severe), for example, a coping process such as “activate the vehicle control system and turn on the hazard lamp and stop” or “send the mobile phone to send to the family” is stored. To do. Note that these coping processes may be executed simultaneously or alternatively.

  The driver information input receiving unit 240 receives input of driver information acquired by the in-vehicle sensor group, and outputs the received driver information to the physical abnormality detection unit 250 and the mental abnormality detection unit 260.

  The physical abnormality detection unit 250 detects the physical abnormality of the driver based on the driver information (driver information acquired by the in-vehicle sensor group) input from the driver information input reception unit 240.

  Specifically, the physical anomaly detection unit 250 refers to the physical anomaly detection table 210 for the item of the in-vehicle camera, for example, when an image obtained by photographing the driver's face is input from the in-vehicle camera as the driver information. Then, it tries to search for physical anomaly detection information of “grimacing”.

  As a result of the search, when physical anomaly detection information “grimacing” is retrieved from the physical anomaly detection table 210, it is determined that the driver shows signs of physical anomaly, and the physical anomaly is detected. The fact that it has been detected is output to the psychological change detection unit 260.

  The psychological change detection unit 260 drives based on the driver information input from the driver information input reception unit 240 (driver information acquired by the in-vehicle sensor group) and the driver information acquired directly from the in-vehicle device group. Detect mental changes in the person.

  Specifically, when the physical anomaly detection unit 250 determines that a physical anomaly sign is seen by the physical anomaly detection unit 250, for example, from a mobile phone connected via a mobile connector, “ Driver information “call transmission history over a predetermined number of times to a specific partner (heterosexual)” is acquired.

  For example, the psychological change detection unit 260 determines the gender of the driver by analyzing the image of the driver input from the in-vehicle camera, and stores the call outgoing call history using the internal database of the opposite name provided in advance. By comparing a certain name, it is determined whether or not the other party of the call transmission history is of the opposite sex.

  Then, the psychological change detection unit 260 refers to the psychological change detection table 220 for the item of the mobile phone, and tries to search for the mental change detection information of “call transmission history more than a predetermined number of times to a specific partner (heterosexual)”. .

  As a result of the search, when mental change detection information “call history of a predetermined number of calls to a specific partner (heterosexuality) or more” is searched from the mental change detection table 220, the mental change detection unit 260 displays the driver. It is determined that there is a sign of a mental disorder, and the mental disorder is detected, and the fact that the mental disorder has been detected is output to the severity measuring unit 270.

  When the physical abnormality detection unit 250 determines that the physical abnormality detection unit 250 shows signs of physical abnormality, for example, from a mobile phone connected via a portable connector, “from a financial operator” The driver information “incoming history of a predetermined number of times or more” is acquired.

  The psychological change detection unit 260 determines whether or not the other party of the incoming call history is a financial operator by collating phone numbers in the incoming call history using a telephone directory database provided internally in advance.

  Then, the psychological change detection table 220 is referred to for the item of the mobile phone, and an attempt is made to search for mental change detection information “incoming history of a predetermined number of times or more from a financial operator”.

  As a result of the search, when the mental change detection information “incoming history of a predetermined number of times or more from a financial operator” is searched from the mental change detection table 220, the mental change detection unit 260 makes a mental change to the driver. It is determined that a sign of symptom is observed, and a mental disorder is detected, and the fact that the mental disorder has been detected is output to the severity measuring unit 270.

  In addition, when the physical abnormality detection unit 250 determines that there is a sign of physical abnormality, the psychological abnormality detection unit 260 acquires, for example, driver information “there is a driver (one person)” from the seat sensor. In addition, the driver information that the destination setting is a suicide spot is acquired from the navigation device.

  Then, the psychological change detection unit 260 refers to the mental change detection table 220 for the item “sheet sensor + navigation device” and tries to search for mental change detection information that “the destination setting is a suicide spot (one person)”. .

  As a result of the search, when the mental change detection information “Destination setting is a suicide spot (one person)” is searched from the mental change detection table 220, the mental change detection unit 260 makes a mental change to the driver. It is determined that a sign of symptom is observed, and a mental disorder is detected, and the fact that the mental disorder has been detected is output to the severity measuring unit 270.

  The psychological change detection unit 260 does not search the mental change detection table 220 for mental change detection information corresponding to the driver information input from the driver information input reception unit 240, and the mental change detection for the driver. If it is not determined that there is a sign, the fact is output to the countermeasure processing execution unit.

  When the psychological change detection unit 260 determines that the driver has signs of mental change, the severity measuring unit 270 measures the severity of the driver's mental change.

  Specifically, the severity measuring unit 270 outputs a message using a voice or image calling to the driver via a speaker or a display connected to the car stereo system, and is acquired by the in-vehicle camera. By analyzing the image and detecting the driver's reaction, the severity of the driver's mental abnormality is measured.

  For example, the severity measuring unit 270 measures as a mild symptom (severity level 1) when the driver responds to a call message within a predetermined time (for example, within 5 seconds). Further, when the driver reacts to the call message outside a predetermined time (for example, within 5 seconds), it is measured as a moderate symptom (severity level 2). If the driver does not respond to the call message, it is measured as a severe symptom (severity level 3).

  The coping processing execution unit 280 executes coping processing for coping with the driver's mental abnormality according to the severity measured by the severity measuring unit 270.

  Specifically, when the severity measured by the severity measuring unit 270 is severity level 1, the handling process execution unit 280 performs handling processing associated with the severity level 1, for example, “car “Provide music / video of the driver's preference by operating the stereo system” is acquired from the countermeasure processing table 230.

  Then, the handling process execution unit 280 controls the car stereo system to deal with the handling process acquired from the handling process table 230 (“operate the car stereo system to provide the driver's favorite music / video”). Execute.

  In addition, when the severity measured by the severity measuring unit 270 is severity level 2, the handling process execution unit 280 performs handling processing associated with the severity level 2, for example, “operate navigation device”. Then, the route guidance to a place with good scenery is acquired from the handling processing table 230.

  Then, the handling process execution unit 280 controls the navigation system to execute the handling process acquired from the handling process table 230 (“operate the navigation device to perform route guidance to a place with a good view”). .

  Further, when the severity measured by the severity measuring unit 270 is the severity level 3, the handling process execution unit 280 performs a handling process associated with the severity level 3, for example, “Vehicle control system. “Start, turn on hazard lamp and stop” is acquired from the countermeasure processing table 230.

  Then, the countermeasure processing execution unit 280 controls the vehicle control system to execute the countermeasure processing acquired from the countermeasure processing table 230 (“activate the vehicle control system to turn on the hazard lamp and stop”).

  When the handling process execution unit 280 receives from the mental change detection unit 260 that it has not been determined that the driver has a sign of mental change, the handling process execution unit 280 is configured to deal with the physical change. A coping process (for example, outputting a message prompting a break, adjusting the temperature of the air conditioner, etc.) is executed.

[Processing by Driver Abnormality Detection Device (Example 1)]
Subsequently, a process performed by the driver abnormality detection device according to the first embodiment will be described with reference to FIG. FIG. 6 is a diagram illustrating a flow of processing performed by the driver abnormality detection device according to the first embodiment.

  As shown in the figure, based on the driver information input from the driver information input receiving unit 240 (driver information acquired by the in-vehicle sensor group), whether or not a sign of the driver's physical anomaly is seen. A determination is made (step S1).

  Specifically, the physical anomaly detection unit 250 refers to the physical anomaly detection table 210 for the item of the in-vehicle camera, for example, when an image obtained by photographing the driver's face is input from the in-vehicle camera as the driver information. Then, it tries to search for physical anomaly detection information of “grimacing”.

  If the physical anomaly detection information “grind face” is retrieved from the physical anomaly detection table 210 as a result of the search, it is determined that the driver shows signs of physical anomaly.

  When it is determined by the physical anomaly detection unit 250 that a sign of physical anomaly is seen (Yes at Step S1), the psychological change detection unit 260 receives the driver information input from the driver information input reception unit 240. Based on (the driver information acquired by the in-vehicle sensor group and the driver information acquired from the in-vehicle device group), it is determined whether or not there is a sign of a driver's mental disorder (step S2).

  Specifically, when the physical anomaly detection unit 250 determines that a physical anomaly sign is seen by the physical anomaly detection unit 250, for example, from a mobile phone connected via a mobile connector, “ Driver information “call transmission history over a predetermined number of times to a specific partner (heterosexual)” is acquired.

  Then, the psychological change detection unit 260 refers to the psychological change detection table 220 for the item of the mobile phone, and tries to search for the mental change detection information of “call transmission history more than a predetermined number of times to a specific partner (heterosexual)”. .

  As a result of the search, when mental change detection information “call history of a predetermined number of calls to a specific partner (heterosexuality) or more” is searched from the mental change detection table 220, the mental change detection unit 260 displays the driver. It is determined that there is a sign of mental change.

  When the mentality detection unit 260 determines that the driver has signs of mental abnormality (Yes in step S2), the severity measuring unit 270, for example, a speaker connected to the car stereo system, Or, after outputting a message using voice or image calling to the driver via a display etc., analyzing the image acquired by the in-vehicle camera and detecting the driver's reaction, the driver's mental The severity of the abnormality is measured (step S3).

  Then, the coping process execution unit 280 executes coping process for coping with the driver's mental abnormality according to the severity measured by the severity measuring unit 270 (step S4).

  Here, returning to the description of step S2, if the mental abnormality detection unit 260 does not determine that the driver has a sign of mental abnormality (No in step S2), the countermeasure processing execution unit 280 Then, a coping process (for example, outputting a message for prompting a break, adjusting the temperature of the air conditioner, etc.) for coping with the physical abnormality is executed (step S5).

[Effects of Example 1]
As described above, according to the first embodiment, mental change detection information indicating a cause of a mental change occurring in the driver is associated with various on-vehicle sensors and various on-vehicle devices in advance. 220, when mental change detection information matching the driver information input from various in-vehicle sensors and various in-vehicle devices is retrieved from the psychological change detection table 220, the various in-vehicle devices are controlled. In addition, since the coping process for coping with the driver's mental abnormality is executed, an accident caused by the driver's mental abnormality can be prevented.

  Note that the processing (for example, see FIG. 6) of the driver abnormality detection device described in the first embodiment may be executed before the vehicle travels, or continues before the vehicle travels after being performed before the vehicle travels. May be executed.

  If the process of the driver abnormality detection device (see, for example, FIG. 6) is executed before the vehicle travels, an accident caused by the driver's mental change can be prevented in advance.

  Now, although Example 1 has been described as an embodiment of the driver abnormality detection device according to the present invention, the present invention may be implemented in various different forms other than the above-described example. is there. In the following, other embodiments included in the present invention will be described.

(1) Implementing only psychological change detection In the first embodiment described above, the case of detecting a psychological change when a physical change in the driver is detected has been described, but the present invention is not limited to this. Alternatively, it may be possible to directly detect mental changes.

  For example, as shown in FIG. 7, the driver abnormality detection device refers to a mental change detection table, and based on driver information input from various in-vehicle sensors and driver information acquired from each in-vehicle device, A mental disorder is detected (see (1) in FIG. 7).

  Next, the driver abnormality detection device measures the severity of the mental change of the driver by outputting a message calling the driver and monitoring the driver's reaction (see (2) in FIG. 7). .

  And a driver | operator abnormality detection apparatus acquires the countermeasure process matched with the measured severity from a countermeasure process table, and performs the acquired countermeasure process (refer (3) of FIG. 7).

  In this way, without detecting physical abnormalities, directly detecting mental abnormalities and executing coping processing, without requiring a processing load to detect physical abnormalities, Accidents caused by driver mental changes can be prevented.

  FIG. 7 is a diagram illustrating an overview of the driver abnormality detection device according to the second embodiment.

(2) Coping process for each severity and mental factor In the first embodiment, the coping process table 230 (see FIG. 5) is used to deal with the coping process in association with the severity of the driver's mental abnormality. The case where the contents are stored has been described. However, the present invention is not limited to this. For example, as shown in FIG. 8, the content of the countermeasure processing may be stored in association with the severity and the mental factor.

  By doing so, it is possible to execute the coping process corresponding to the severity and the mental factor, and it is possible to more reliably prevent the accident caused by the driver's mental abnormality.

  FIG. 8 is a diagram illustrating a configuration example of a countermeasure processing table according to the second embodiment.

(3) Device Configuration, etc. Each component of the driver abnormality detection device 200 shown in FIG. 2 is functionally conceptual and does not necessarily need to be physically configured as illustrated.

  That is, the specific form of the dispersion / integration of the driver abnormality detection device 200 is not limited to the one shown in the figure. For example, all or part of the integration of the psychological change detection unit 260 and the severity measurement unit 270, It can be configured to be functionally or physically distributed / integrated in arbitrary units according to various loads or usage conditions.

  Furthermore, each processing function (see FIG. 6 and the like) performed by the driver abnormality detection device 200 is realized by a CPU and a program that is analyzed and executed by the CPU, or It can be realized as hardware by wired logic.

(4) Driver Abnormality Detection Processing Program Various processes of the driver abnormality detection device 200 described in the first embodiment (for example, see FIG. 6 and the like) are executed by using a program prepared in advance as a personal computer or a workstation. It can implement | achieve by running with computer systems, such as.

  Therefore, in the following, an example of a computer that executes a driver abnormality detection processing program having the same function as in the first embodiment will be described with reference to FIG. FIG. 9 is a diagram illustrating a computer that executes a driver abnormality detection processing program.

  As shown in the figure, the computer 300 is configured by connecting an input unit 310, an output unit 320, an HDD 330, a RAM 340 and a CPU 350 via a bus 400.

  Here, the input unit 310 receives input of various data from the user. The output unit 320 displays various information. The HDD 330 stores information necessary for the CPU 350 to execute various processes. The RAM 340 temporarily stores various information. The CPU 350 executes various arithmetic processes.

  As shown in FIG. 9, the HDD 330 includes a driver abnormality detection processing program 331 that exhibits the same function as each processing unit of the driver abnormality detection device described in the first embodiment, and a driver abnormality detection. Processing data 232 is stored in advance.

  The driver abnormality detection processing program 331 may be appropriately distributed and stored in a storage unit of another computer that is communicably connected via a network.

  Then, the CPU 350 reads out the driver abnormality detection processing program 331 from the HDD 330 and develops it in the RAM 340, so that the driver abnormality detection processing program 331 functions as a driver abnormality detection processing process 341 as shown in FIG. It becomes like this.

  That is, the driver abnormality detection processing process 341 reads out the driver abnormality detection processing data 332 and the like from the HDD 330, expands it in an area allocated to itself in the RAM 340, and executes various processes based on the expanded data and the like. To do.

  The driver abnormality detection process 341 includes a driver information input receiving unit 240, a physical abnormality detection unit 250, a mental abnormality detection unit 260, a severity measuring unit 270, and the driver abnormality detection device 200 shown in FIG. This corresponds to the processing executed in the handling processing execution unit 280 or the like.

  Further, the above-described driver abnormality detection processing program 331 is not necessarily stored in the HDD 330 from the beginning. For example, a flexible disk (FD), a CD-ROM, a DVD disk, a magneto-optical disk inserted into the computer 300 is not necessary. Each program is stored in a “portable physical medium” such as a disk or an IC card, and “another computer (or server)” connected to the computer 300 via a public line, the Internet, a LAN, a WAN, or the like. In addition, the computer 300 may read and execute each program from these.

(5) Driver Abnormality Detection Method The following driver abnormality detection method is realized by the driver abnormality detection device described in the above embodiment.

  That is, mental anomaly detection that stores mental anomaly detection information for detecting mental anomalies occurring in the driver in association with driver information acquired by various in-vehicle sensors and in-vehicle devices. An information search step of searching for mental abnormality detection information that matches the driver information input from various in-vehicle sensors and various in-vehicle devices with reference to the information storage unit (see, for example, step S2 in FIG. 6), information search When mental abnormality detection information is retrieved by the step, a countermeasure processing execution step of controlling various vehicle-mounted devices to execute a countermeasure process for dealing with the driver's mental abnormality (for example, FIG. 6). The driver abnormality detection method including step S4) is realized.

  As described above, the driver abnormality detection device, the driver abnormality detection method, and the driver abnormality detection processing program according to the present invention detect an abnormality in the physical condition occurring in the driver and change the abnormality of the driver's physical condition. This is useful when executing the processing to deal with, and is particularly suitable for preventing accidents caused by mental changes in the driver.

BRIEF DESCRIPTION OF THE DRAWINGS It is a figure for demonstrating the outline | summary and the characteristic of the driver assistance apparatus which concern on Example 1. FIG. 1 is a block diagram illustrating a configuration of a driver abnormality detection device according to a first embodiment. It is a figure which shows the structural example of the physical abnormality detection table which concerns on Example 1. FIG. It is a figure which shows the structural example of the mental disorder detection table which concerns on Example 1. FIG. It is a figure which shows the structural example of the countermeasure process table which concerns on Example 1. FIG. It is a figure which shows the flow of a process by the driver | operator abnormality detection apparatus which concerns on Example 1. FIG. It is a figure which shows the outline | summary of the driver abnormality detection apparatus which concerns on Example 2. FIG. FIG. 10 is a diagram illustrating a configuration example of a countermeasure processing table according to the second embodiment. It is a figure which shows the computer which performs a driver | operator abnormality detection processing program.

Explanation of symbols

DESCRIPTION OF SYMBOLS 110 Biological information acquisition sensor group 120 Vehicle state acquisition sensor group 130 Lamp / switch / lighting group 140 In-vehicle device group 200 Driver abnormality detection device 210 Body abnormality detection table 220 Mental abnormality detection table 230 Handling process table 240 Driver information input reception part 250 Physical Change Detection Unit 260 Psychiatric Change Detection Unit 270 Severity Measurement Unit 280 Countermeasure Processing Execution Unit 300 Computer 310 Input Unit 320 Output Unit 330 HDD (Hard Disk Drive)
331 Driver abnormality detection processing program 332 Driver abnormality detection processing data 340 RAM (Random Access Memory)
341 Driver abnormality detection process 350 CPU (Central Processing Unit)
400 bus

Claims (6)

Mental change detection information storage means for storing in advance mental change detection information for detecting a mental change occurring in the driver in association with various on-vehicle sensors and various on-vehicle devices,
Referring to the mental abnormality detection information storage means, information retrieval means for retrieving the mental abnormality detection information that matches the driver information input from the various in-vehicle sensors and the various in-vehicle devices;
When the mental abnormality detection information is searched by the information search means, a countermeasure processing execution means for controlling the various in-vehicle devices and executing a countermeasure process for coping with the driver's mental abnormality; ,
A driver abnormality detection device comprising: Correspondence processing storage means for storing the countermeasure processing in advance in association with the severity of the mental abnormality and / or the factor of the mental abnormality,
Severity measurement means for detecting a response to a call to the driver and measuring the severity of the driver when the mental abnormality detection information is searched by the information search means,
Further comprising
The coping process executing means is the coping process stored by the coping process storage means, the severity measured by the severity measuring means, and / or the mental searched by the information search means. The driver abnormality detection device according to claim 1, wherein a countermeasure process associated with a cause of an abnormal change is acquired and the acquired countermeasure process is executed.   3. The driver abnormality detection device according to claim 1, wherein the information retrieval unit retrieves the mental abnormality detection information before the vehicle travels. Based on driver information acquired from various in-vehicle sensors and various in-vehicle devices, further comprising a physical abnormality detection means for detecting a physical abnormality of the driver,
The said information search means searches the said mental change detection information, when the driver's physical change is detected by the said physical change detection means, The mental change detection information is searched. The driver abnormality detection device described in 1. Psychological change detection information storage for preliminarily storing mental change detection information for detecting a mental change occurring in the driver in association with driver information acquired by various vehicle-mounted sensors and various vehicle-mounted devices. An information search step of searching for the mental abnormality detection information that matches the driver information input from the various in-vehicle sensors and the various in-vehicle devices,
A coping process execution step for controlling the various in-vehicle devices and executing coping process for coping with the driver's mental change when the mental change detection information is searched in the information search step; ,
A driver abnormality detection method comprising: Psychological change detection information storage for preliminarily storing mental change detection information for detecting a mental change occurring in the driver in association with driver information acquired by various vehicle-mounted sensors and various vehicle-mounted devices. An information search procedure for searching for the mental abnormality detection information that matches the driver information input from the various vehicle-mounted sensors and the various vehicle-mounted devices,
When the mental abnormality detection information is searched by the information search procedure, a coping process execution procedure for controlling the various in-vehicle devices and executing a coping process for coping with the driver's mental abnormality; ,
An abnormality detection program for a driver characterized by causing a computer to execute.

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