JP6301758B2 - Driver crisis management device, driver crisis management method, and driver crisis management program - Google Patents

Description

  The present invention relates to a driver crisis management device, a driver crisis management method, and a driver crisis management program for predicting a crisis of a moving body driven by a driver.

  2. Description of the Related Art Conventionally, a service for obtaining an individual's health state and managing it with a server to determine a daily health state has been performed. For example, there is a technique for transmitting measurement data from a sensor attached to the body to a server, analyzing past data, and detecting whether the received measurement data is normal or abnormal (see Patent Document 1).

JP 2003-150718 A Start position start position

  In the prior art, the collected health condition data is used to determine the state of the user, and is not used to predict a crisis in a moving body such as an automobile. In addition, the conventional mobile crisis prediction service analyzes the data of the mobile body itself and detects dangerous behavior such as sudden acceleration and sudden operation. The crisis prediction service considers the driver's own condition. Not something to do.

  The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a driver crisis management device, a driver crisis management method, and driver crisis management that prevent an accident caused by a driver's condition. To provide a program.

In order to solve the above-mentioned problem, the present invention is a driver crisis management device, which is an acquisition means for acquiring biological information of a driver who drives a mobile body and mobile body information, the biological information and the mobile body using the information and determination information set based on, a determination unit configured to determine whether the crisis of the movable body is predicted, if the crisis is predicted, presented for presenting risk to the mobile And the determination information used for predicting the crisis of the mobile body when a crisis event occurs in the mobile body when the crisis is not predicted and the presentation means does not present a crisis to the mobile body And analyzing means for correcting .

The present invention is a driver crisis management method performed by a computer, which is based on an acquisition step of acquiring biological information and moving body information of a driver who drives a moving body, the biological information and the moving body information. by using determination information set Te, a determination step of determining whether or not the crisis of the movable body is predicted, if the crisis is predicted, a presentation step of presenting a risk to the movable body, wherein An analysis for correcting the determination information used for predicting a crisis of the mobile object when a crisis event has occurred in the mobile object when a crisis is not predicted and the crisis is not presented to the mobile object in the presenting step And step .

The present invention is a driver crisis management program executed by a computer, the acquisition step of acquiring the biological information of the driver who drives the mobile body and the mobile body information from the computer, the biological information and the mobile body by using determination information set based on the information, the determining whether or not determination step crisis of the moving body is expected, if the crisis is predicted, presenting step of presenting a risk to the mobile And when the crisis is not predicted and the crisis is not presented to the mobile body in the presenting step, and the crisis event occurs in the mobile body, the determination information used for predicting the crisis of the mobile body An analysis step to correct the is executed.

  According to the present invention, it is possible to provide a driver crisis management device, a driver crisis management method, and a driver crisis management program that prevent an accident caused by a driver's condition.

1 is an overall configuration diagram of a driver management system according to an embodiment of the present invention. It is a functional block diagram of a mounting apparatus. It is a functional block diagram of a driver crisis management server. It is a flowchart of a data collection process. It is a graph which shows progress of the heart rate before crisis event occurrence. It is a flowchart of a crisis prediction process.

  Embodiments of the present invention will be described below.

  FIG. 1 is an overall configuration diagram showing a driver management system according to an embodiment of the present invention. The illustrated driving vehicle management system includes a mounting device 1 mounted on each mobile body, a driver crisis management server 2, a call center 3, and an insurance company system 4.

  The mounting device 1 is a device mounted on a moving body such as a car, a train, an airplane, or a bicycle. In this embodiment, an automobile is used as the moving body, but the moving body of the present invention is not limited to the automobile.

  FIG. 2 is a functional block diagram of the mounting apparatus 1 of the present embodiment. The illustrated mounting device 1 includes a biological information collection unit 11, a vehicle body information collection unit 12, a transmission unit 13, and an authentication unit 14.

  The biometric information collection unit 11 is always installed in an operation part (or in the vicinity of the operation part) that is a part that is touched by a finger or hand of a driving car, such as a handle or a lever, and a driver's biometric information (heart rate, respiration rate). Blood oxygen concentration, heart rate variability, etc.). For example, a pulse oximeter may be used as the biological information collection unit 11. In addition, by installing the biological information collection unit 11 at an operation part touched by a finger or hand such as a handle, it is possible to collect biological information while the driver is driving without any trouble in driving.

  The vehicle body information collection unit 12 collects vehicle body information such as steering wheel operation, brake operation, acceleration, ABS (Antilock Brake System) operation, and airbag operation. Moreover, the vehicle body information collection part 12 is good also as collecting position information using GPS. The transmission unit 13 transmits the biological information collected by the biological information collection unit 11 and the vehicle body information collected by the vehicle body information collection unit 12 in real time via a network such as a mobile network, an M2M (Machine to Machine), or a VoIP network. It transmits to the driver crisis management server 2.

  For example, a telematics module (http://www.docomo.biz/html/service/module/tm/) may be used for the vehicle body information collection unit 12 and the transmission unit 13. In this case, the biological information collection unit 11 such as a pulse oximeter is connected to the telematics module by USB connection or the like, and the telematics module transmits the biological information to the driver crisis management server 2 by wireless data communication together with the vehicle body information. The authentication unit 14 authenticates the driver by fingerprint authentication or the like.

  FIG. 3 is a functional block diagram of the driver crisis management server 2 of the present embodiment. The driver crisis management server 2 functions as a cloud, acquires the driver's biological information and vehicle body information from the mounting device 1 mounted on the moving body via the network, and combines these information. Use it as big data to predict the danger (danger prediction) of moving vehicles while driving.

  The driver crisis management server 2 shown in the figure includes an information acquisition unit 21, an analysis unit 22, a determination unit 23, a presentation unit 24, an information providing unit 27, a driver information storage unit 25, and a threshold storage unit 26. Is provided.

  The information acquisition unit 21 acquires the biological information and the moving body information of the driver who drives the moving body from the mounting device 1 in real time via the network. The analysis unit 22 sets determination conditions for performing crisis prediction using the biological information and vehicle body information of a plurality of drivers. In addition, the analysis unit 22 corrects the determination condition when a crisis event occurs in the moving body without the presentation unit 24 presenting the crisis to the moving body. The analysis unit 22 analyzes regional characteristics based on the vehicle body information and the biological information.

  The determination part 23 determines whether the crisis of a mobile body is predicted using the determination information set based on biometric information and mobile body information. When the crisis is predicted, the presenting unit 24 presents the crisis to the moving object. In addition, the presentation unit 24 identifies the position of the moving body where a crisis is predicted, and notifies the warning information to other moving bodies existing in the vicinity of the position. The information providing unit 27 provides the information stored in the driver information storage unit 25 to the insurance company 4 (or a driver's employment plan company, etc.).

  The driver information storage unit 25 stores biological information and vehicle body information of each driver. The threshold storage unit 26 stores a ratio of deviation set by the analysis unit 22 and common to all drivers.

  As the mounting device 1 and the driver crisis management server 2 described above, for example, a general-purpose computer system including a CPU, a memory, and an external storage device such as a hard disk can be used. In this computer system, each function of each device is realized by the CPU executing a predetermined program loaded on the memory. For example, the functions of the mounting device 1 and the driver crisis management server 2 are the CPU of the mounting device 1 in the case of the program for the mounting device 1, and the driver crisis in the case of the program for the driver crisis management server 2. This is realized by the CPU of the management server 2 executing it.

  Further, the program for the on-board device 1 and the program for the driver crisis management server 2 can be stored in a computer-readable recording medium such as a hard disk, a flexible disk, a CD-ROM, an MO, or a DVD-ROM. It can also be distributed via.

  Next, the processing of this embodiment will be described.

  FIG. 4 is a flowchart of data collection processing according to this embodiment. In this process, before the crisis prediction is performed, the biological information and the vehicle body information of each driver are collected in advance and the determination conditions for the crisis prediction are analyzed.

  When the driver starts driving, the authentication unit 14 of the mounting apparatus 1 mounted on the car performs biometric authentication such as fingerprint authentication and voice authentication to authenticate the driver (S11). If the authentication is successful, the authentication unit 14 transmits the user ID of the driver to the driver crisis management server 2 using the transmission unit 13, and connects the onboard device 1 and the driver crisis management server 2.

  Then, while the driver is driving for a predetermined time, the biological information collecting unit 11 installed at a portion where the driver's hand or finger touches the steering wheel or the like constantly collects the driver's biological information and collects vehicle information. The unit 12 always collects vehicle body information. And the transmission part 13 transmits the collected biometric information and vehicle body information to the driver | operator crisis management server 2 (cloud) in real time via a network (S12).

  The information acquisition unit 21 of the driver crisis management server 2 receives biological information and vehicle body information transmitted from the mounting device 1 in real time. And the analysis part 22 of the driver | operator crisis management server 2 calculates the average value of each item of the received biometric information (S13), matches with the user ID of the said driver | operator, and memorize | stores it in the driver | operator information storage part 25. (S14). Here, the heart rate, the respiratory rate, the blood oxygen concentration, the heart rate fluctuation, and the like are used as the biological information, and the average value during the driving period of S12 is stored in the driver information storage unit 25. Further, the information acquisition unit 21 stores the biological information and the vehicle body information collected during the driving period of S12 in the driver information storage unit 25 in association with the user ID together with the time information.

  And the analysis part 22 performs a crisis analysis whether the crisis event (dangerous operation, dangerous behavior) occurred during the driving | running | working period of S12 using the received vehicle body information (S15). In the present embodiment, steering wheel operation, brake operation, acceleration, ABS operation, airbag operation, and the like are collected as vehicle body information. From such vehicle body information, it is determined whether or not a crisis event such as ABS operation, air bag operation, sudden braking, sudden steering operation, sudden acceleration or deceleration has occurred.

  Then, biometric information of a predetermined time before or after the occurrence time of the crisis event (or a predetermined time before the occurrence time of the crisis event) is acquired from the driver information storage unit 25. And the analysis part 22 is a value of the biometric information before the occurrence of the crisis event, and a value (the lowest value or the highest value) far from the average value calculated in S13 leads to the dangerous behavior. The wax threshold is set (S16).

  FIG. 5 is a diagram for explaining the threshold setting in S16 when the heart rate is used as the biological information. Here, it is assumed that the crisis event detected in S15 has occurred at 52 between times 7-9. Further, it is assumed that the average value of the heart rate of the driver is “5”. For example, the average value of the heart rate is calculated as follows.

Average = {X1 (measured heart rate 1) + X2 (measured heart rate 2) + · + Xn (measured heart rate n)} / n
And just before the occurrence of the crisis event 51, the heart rate is decreased by a predetermined rate from the average value due to the driver being asleep. On the other hand, in the time zone 52 in which the crisis event occurs, the heart rate is higher than the average value due to awakening. That is, the example shown in FIG. 5 indicates that the driver is awake and is performing a sudden braking, a sudden steering operation, or the like.

  In the case of such biological information and body information, the analysis unit 22 is a value before the occurrence of a crisis event (here, a value before the value is inverted so as to approach the average value due to awakening), and the average value A value 53 (here, “3”) that is most distant is determined as a threshold value. When a crisis event occurs, the threshold is determined not only for the heart rate but also for other biological information.

  And the analysis part 22 calculates the ratio (decrease ratio or increase ratio) of the deviation from an average value to a threshold value about the threshold value of each biological information set in S16. Note that the ratio of deviation is calculated as follows, for example.

Deviation ratio (%) = {(average value-threshold) / average value} x 100
And the analysis part 22 calculates the average of the ratio of deviation of all the other drivers, and the ratio of deviation of the said driver, and makes it the ratio of deviation common to all the drivers. And the analysis part 22 determines the value which multiplied the ratio of the deviation common to all the drivers to the average value of the driver's biometric information as a threshold (determination condition) for the driver's crisis prediction, The crisis prediction threshold value is stored in the driver information storage unit 25. The analysis unit 22 stores a deviation ratio common to all the drivers in the threshold storage unit 26.

  In this way, by calculating the ratio of divergence common to all drivers, it is possible to predict the risk if only the average value of the driver's biometric information can be collected even for drivers who do not experience a crisis event. Thresholds can be set. In addition, it is good also as determining the threshold value for crisis prediction for every classification of crisis event.

  On the other hand, when no crisis event is detected from the vehicle body information in the crisis analysis of S15, or even when a crisis event is detected, there is no change in the biological information (from the average value to a predetermined value or ratio). If not lowered or increased), the process returns to S12, and the operation is started again. Alternatively, using the ratio of deviation common to all drivers calculated in S17 and the average value of the driver's biometric information, a threshold value for crisis prediction is calculated and stored in the driver information storage unit 25. Also good.

  By calculating the threshold for crisis prediction using the data collection process shown in FIG. 4 as described above, it is possible not only to detect the dangerous behavior of the vehicle immediately before the accident, but also to predict the accident in advance, although a prior data collection period is required. By preventing it in advance, it is possible to protect human lives including the driver.

  FIG. 6 is a flowchart of the crisis prediction process. In this process, the driver crisis management server 2 performs a crisis prediction using the crisis prediction threshold value calculated in FIG.

  When the driver starts driving, the authentication unit 14 of the mounting device 1 mounted on the car performs biometric authentication to authenticate the driver, and if the authentication is successful, the driver's user ID is transmitted. 13 is transmitted to the driver crisis management server 2 to connect the onboard device 1 and the driver crisis management server 2 (S21). As a result, the determination unit 23 of the driver crisis management server 2 reads the risk prediction threshold value of each biological information of the driver corresponding to the user ID from the driver information storage unit 25.

  While the driver is driving, in the mounting device 1, the biological information collection unit 11 always collects the driver's biological information, the vehicle body information collection unit 12 always collects the vehicle information, and the transmission unit 13 The collected biological information and vehicle body information are transmitted in real time to the driver crisis management server 2 (cloud) via the network (S22).

  The information acquisition unit 21 of the driver crisis management server 2 receives the biological information and the vehicle body information transmitted from the mounting device 1 in real time, and the determination unit 23 sequentially performs crisis prediction in real time based on the information. (S23). That is, the determination unit 23 determines whether or not each piece of biological information transmitted from the mounting device 1 has reached a crisis prediction threshold value for each corresponding piece of biological information. When at least one biological information reaches a corresponding crisis prediction threshold, the determination unit 23 refers to the driver information storage unit 25 and determines whether or not a flag is set for the driver. (S24).

  If the flag is not set in S24, the presentation unit 24 uses an automatic voice response to alert the driver (for example, “Driving measurement indicates attention. Please take a break. Is transmitted to the mounting apparatus 1 via the network (S25). As a result, an output device such as a speaker (not shown) of the mounting device 1 outputs a warning message to alert the driver. In addition, you may perform alerting using not only a voice message but other methods, such as an email. An accident can be prevented in advance by giving such attention.

  Then, the determination unit 23 sets a flag in the driver data in the driver information storage unit 25 (S26), returns to S23, and continues to perform risk prediction.

  On the other hand, when the flag is already set in S24, the presentation unit 24 uses an automatic voice response or the like to give a voice message to warn the driver (for example, “Driving measurement indicates a warning. Immediately drive. ”Is transmitted to the on-board device 1 via the network. As a result, an output device such as a speaker of the mounting device 1 outputs a warning voice message to warn the driver. Further, the presentation unit 24 may connect the mounting device 1 and the call center 3 and cause an operator to give a warning. As a result, the driver and the operator can communicate with each other, and the operator can support dangerous drivers such as falling asleep or drunk, and can prevent an accident.

  In this way, when a driver who has already been alerted and has a flag set again reaches the threshold for predicting a crisis, the operator can provide a call service as an emergency measure. In addition, accidents caused by physical conditions can be predicted and prevented in advance.

  Also, if an accident occurs while providing a call service by the operator, the operator is in a state where the operator can talk to the driver, so the driver's status such as the legs and arms being caught in the vehicle body cannot be confirmed immediately. This makes it possible to make an appropriate and prompt request for assistance, for example, by making an emergency team report a situation where a jack is necessary. That is, in an emergency case, the operator can arrange vehicle position information and an ambulance on behalf of the driver.

  The operator may set an evaluation for the driver in the driver information storage unit 25 for a malicious driver who ignores the warning by calling with the driver.

  Then, the determination unit 23 returns to S23 and continues to perform risk prediction until the driving is completed (S28).

  After the driving, the information acquisition unit 21 of the driver crisis management server 2 stores the biological information and the vehicle body information collected during the driving period in the driver information storage unit 25 in association with the user ID together with the time information. (S29).

  And the analysis part 22 performs the crisis analysis of whether the crisis event (dangerous operation, dangerous behavior) generate | occur | produced during the driving period using the vehicle body information collected during the driving period (S30). That is, it is determined from the vehicle body information whether or not a crisis event such as ABS operation, airbag operation, sudden braking, sudden steering operation, sudden acceleration / deceleration has occurred. If a crisis event has not occurred, the process is terminated.

  On the other hand, when a crisis event has occurred, the analysis unit 22 refers to the driver information storage unit 25 and determines whether or not a flag is set in the driver data (S31). If the flag is set, it means that a crisis event has occurred after S25, although the alert was issued before the crisis event occurred. For this reason, the analysis part 22 sets the information to the effect that it is a dangerous driver candidate to the data of the said driver | operator of the driver | operator information storage part 25 (S32).

  The information providing unit 27 of the driver crisis management server 2 designates the driver whose information indicating that the driver is a dangerous driver candidate in the driver information storage unit 25 as the insurance company 4 (or the driver's hiring schedule). Company). In other words, after obtaining permission from the driver to use his / her driving information, he / she can store driver information such as information indicating that he / she is a dangerous driver candidate and conversely information indicating that he / she is a good driver without a crisis event. The analysis result of the data stored in the unit 25 is provided / sold to the insurance company 4 or the like. However, in order not to be detrimental to the driver, such as health problems of the driver, etc., the driver's evaluation, such as a driver ignoring warning or an addict, will be added to classify and provide the characteristics of the driver Also good. In addition, for malicious drivers who do not accept operator warnings, flexible insurance sales are possible, such as proposals for insurance premium revisions in cooperation with insurance companies, and incentives for good drivers, etc. .

  If no flag is set in S31, the driver's threshold for crisis prediction is corrected. That is, since a crisis event has occurred without the biological information reaching the threshold value, the analysis unit 22 determines a threshold value that will lead to a dangerous behavior by the same process as S16 in FIG. 4 (S33). And the analysis part 22 calculates the ratio of the deviation from the average value of the said driver to the threshold value determined by S33 like S17 of FIG. 4, the ratio of the deviation of all the other drivers, and the said driving | operation An average with the driver's deviation rate is calculated as the deviation rate common to all drivers.

  Then, the analysis unit 22 re-determines a value obtained by multiplying the average value of the driver's biometric information by the ratio of deviation common to all drivers as a threshold for the driver's crisis prediction, and the crisis prediction. Is stored in the driver information storage unit 25. In addition, the analysis unit 22 stores in the threshold value storage unit 26 the ratio of divergence common to all drivers recalculated. As described above, the analysis unit 22 automatically corrects the threshold value, whereby an accident caused by the driver's condition can be brought close to 0 as much as possible.

  Next, the analysis unit 22 of the driver crisis management server 2 uses the biometric information and the vehicle body information of the driver information storage unit 25 collected by the processing of FIGS. (Processing) may be performed.

(1) Analysis as personnel evaluation When the moving body is an airplane, for each captain, the heart rate of each sub-captain who rides is totaled. Captains (superior) who have a high proportion of each sub-captain whose heart rate is higher than their average value are evaluated as having a problem with the person of the captain, and provided to the airline as personnel evaluations.

  In addition, evaluation in the case where there is a problem with the sub-captain in the reverse pattern can be performed by the same method. In addition, the same method is applied to buses, driving schools, railways, etc., and the relationship between the driver and passengers is extracted, such as when the guidance of a specific leader is too strict or there is a problem with a specific employee. be able to.

(2) Analysis as a region When the vehicle body information collection unit 12 of the mounting apparatus 1 also collects position information as vehicle body information and transmits it to the driver crisis management server 2, the analysis unit 22 is based on the vehicle body information and biological information. For example, regional characteristics may be analyzed as follows.

  If there are many drivers who perform sudden operations such as sudden braking and sudden steering wheel obtained from vehicle body information with the same position information (for example, about the size of Tokyo Dome), there is a problem with the road or structure at that position. Analyze and provide a list of locations that need construction to the local government.

  Also, if there are many drivers with the same position information and blood oxygen obtained from biological information lower than the average value, it is analyzed that there is a fire or gas leak near the position, and the fire Provide analysis result data to the agency.

  In addition, if the theft of tires obtained from vehicle body information occurs frequently with the same position information, the crime time can be predicted by analyzing the theft time, and the analysis result is sent to the National Police Agency. Provide data.

  In addition, if there are many drivers who are determined to be drunk based on biometric information with the same position information (drivers whose blood oxygen concentration has decreased and whose respiratory rate has increased), drive near that position. It analyzes that there is a restaurant that provides alcohol to the person, and provides analysis result data to the National Police Agency.

  In addition, the biometric information reaches a threshold value in S23 of FIG. 6, and it is dangerous for other vehicles (other drivers) existing in the vicinity of the problematic driver predicted to be in danger (for example, a driver in a dozing state). It is good also as notifying the warning information to the extent that a simple vehicle is nearby. Thereby, an accident can be prevented beforehand.

  In addition, if there are many taxi drivers who have the same position information and the heart rate obtained from the biometric information is lower than the average value, the taxi driver who has few passengers and is free (for example, a taxi driver who is asleep) Analyzing that there are a lot of hands), instructing the spare taxi driver to be dispatched to a place of work (place of the customer) with priority. Further, the above method is applied not only to the taxi driver but also to the driver of the moving trader and the driver of the transport trader to detect a spare driver and arrange the driver at an optimum position. Thereby, business profit can be improved.

(3) Analysis of disaster prediction Add the average value of the driver's biometric information existing in the same area information (for example, about one area of a prefecture), and divide by the total number of drivers, Calculate the overall average. The average for this whole area is a value that fluctuates daily as the parameter increases. Therefore, when the average of the same area information as a whole fluctuates more than a predetermined value, it can be analyzed that it is a sign that a disaster such as an earthquake will occur, and a disaster countermeasure warning may be provided to the area.

(4) Analysis of in-vehicle environment A driver who has a high outside air temperature acquired from the vehicle body information and whose heart rate acquired from the biometric information is higher than the average value. For a driver who is suddenly maneuvering, the vehicle interior environment is analyzed to be deteriorated, and the interior environment is adjusted to a comfortable state for the driver, such as automatically adjusting the interior cooling.

  In the present embodiment described above, not only the driver's biological information but also the vehicle body information can be combined to improve the accuracy of the crisis prediction (danger prediction) of the moving vehicle body. That is, the change before the crisis prediction can be obtained from both the biological surface and the vehicle surface, and the accuracy of the determination of the crisis prediction can be improved. For example, while acquiring a decrease in the heart rate of a driver such as during a nap from biological information, and also acquiring dangerous behavior such as sudden braking operation and unstable steering operation from vehicle body information, the risk prediction is performed with high accuracy. be able to.

  In addition, by sending biometric information and vehicle body information to the driver crisis management server 2 that is a cloud, it affects the driver who is moving and the area, place, time, climate, etc. where the accident has not yet occurred. It is possible to analyze and identify natural phenomena, and to implement prevention and countermeasures. For example, identify areas, places, times, climates, etc. that have a monotonous road that leads to a decrease in heart rate (biological information), a warm climate, and a driver's crisis event (vehicle information) such as a sharp handle, The driver can be notified of the crisis.

  Moreover, by transmitting biometric information and vehicle body information to the driver crisis management server 2 that is a cloud, it is possible to sequentially evaluate the characteristics of the driver and improve the productivity of the company. For example, it is possible to identify the effects caused by passengers in the business that cause an increase in heart rate (biological information) and a crisis event (vehicle information) such as sudden braking and steering, etc. can do.

  Also, by sending biometric information and vehicle body information to the driver crisis management server 2 that is a cloud, the driver's situation at the time of a measurable accident can be immediately analyzed before the rescue, and the time required for rescue can be reduced. Can do. For example, prior situation determination can be made with high accuracy when the heart rate decreases (biological information), the vehicle damage information, or the temperature of the vehicle body rises (where it burns).

  In the present embodiment, the biological information of the driver for a long time can be collected by providing a mechanism that can always collect the biological information by installing the biological information collecting unit 11 on a handle or the like.

  In the present embodiment, the threshold for crisis prediction is set using not only the information of each driver itself but also the information of other drivers. Thereby, the determination accuracy of crisis prediction can be improved.

  Further, in the present embodiment, it is possible to improve the determination system for crisis prediction by collecting the results (changes in biological information and vehicle body information) after notifying the driver of the crisis prediction and feeding back the results to the threshold value.

  Moreover, since this embodiment is a service provided by the driver crisis management server 2 that is a cloud, it can be applied to mobile units and call centers 3 around the world.

  Further, in the present embodiment, by obtaining the driver's biometric information in real time during driving, a crisis prediction is performed, and when it is determined that there is a danger, the driver and other vehicles existing in the vicinity The danger can be avoided by notifying the user of the alarm. In other words, before the driver causes an accident, it is possible to support the driver to drive appropriately by stopping the car or paying attention to falling asleep. The alarm may be notified by a nearby police or security company.

  Further, in the present embodiment, the driver can enjoy a service for receiving information (awareness and warning) from the driver crisis management server 2 by voice message or email for preventing danger during driving. In order to provide this service to drivers (customers) widely, the service provider company that operates the driver crisis management server 2, the insurance company 4 (or the driver's employment company), and the driver As a business model, the service can be provided to the driver at a low cost or free of charge in exchange for the driver's consent to use personal information. That is, the service provider provides the insurance company 4 with customer information (risk analysis results such as good driver, snooze driving, and drunk driving) and collects the selling price as consideration. The insurance company 4 can propose a premium for each driver characteristic.

  In addition, for the purpose of preventing accidents, service providers provide customer information to companies that plan to hire drivers (transportation companies, taxi industry, aviation industry, travel companies, etc., companies that employ drivers) The sales price can also be collected. By providing the driver characteristics, which are customer information, to the driver hiring company, the company can know the characteristics of dangerous drivers in advance and can choose not to adopt them in the first place. Further, in the present embodiment, since the biometric information and the vehicle body information are transmitted to the driver crisis management server 2 that is a cloud, the malicious company employs the driver while knowing that it is a dangerous driver and identifies a malicious company that has been operating for a long time. be able to.

  As a result, accidents of mobile objects (airplanes, cars, trains, bicycles, etc.) around the world can be reduced, and service providers can collect the reduced insurance money and accident costs. In addition, the identity of the driver can be identified from the driver information, and it can be applied to mobile security such as anti-theft (for example, theft detection, reporting to the police, etc.).

  Further, according to the present embodiment, accidents caused by the driver's condition are prevented in advance, so that (1) equipment damage or life loss caused by the driver's condition (physical condition, alcohol, etc.), (2) train Economic opportunity loss due to train driver's doze etc., (3) Social loss and corporate management damage due to aircraft accident, etc. (4) National compensation burden due to lifesaving, medical resource burden, It is possible to avoid the burden on the insurance company and (5) the burden on the accident party and related parties.

  In addition, this invention is not limited to said embodiment, Many deformation | transformation are possible within the range of the summary.

1: mounting device 11: biological information collection unit 12: body information collection unit 13: transmission unit 14: authentication unit 2: driver crisis management server 21: information acquisition unit 22: analysis unit 23: determination unit 24: presentation unit 25: Driver information storage unit 26: Threshold storage unit 27: Information providing unit 3: Call center 4: Insurance company

Claims (7)

A driver crisis management device,
An acquisition means for acquiring biological information of the driver driving the moving body and the moving body information;
Determination means for determining whether or not a crisis of the mobile object is predicted using determination information set based on the biological information and the mobile object information;
If the crisis is predicted, and presenting means for presenting a risk to the movable body,
When the crisis is not predicted and the presenting means does not present a crisis to the mobile object, the determination information used for predicting the crisis of the mobile object is corrected when a crisis event occurs in the mobile object Analyzing means
Driver crisis management device characterized by . The driver crisis management device according to claim 1,
The driver crisis management apparatus, wherein the acquisition unit acquires the biological information and the moving body information in real time when the moving body is driven. The driver crisis management device according to claim 1 or 2,
The analyzing means uses the biological information and the vehicle information of the driver and other drivers, the driver crisis management unit and sets the determination information. The driver crisis management device according to claim 3 ,
The vehicle body information includes position information of the moving body,
The driver crisis management apparatus characterized in that the presenting means identifies a position of a moving body where a crisis is predicted, and notifies warning information to other moving bodies existing in the vicinity of the position. The driver crisis management device according to claim 3 or 4 ,
The vehicle body information includes position information of the moving body,
The driver crisis management apparatus characterized in that the analysis means analyzes regional characteristics based on the vehicle body information and the biological information. A driver crisis management method performed by a computer,
An acquisition step of acquiring biological information of the driver driving the mobile body and the mobile body information;
A determination step of determining whether or not a crisis of the mobile object is predicted using determination information set based on the biological information and the mobile object information;
If the crisis is predicted, a presentation step of presenting a risk to the movable body,
When the crisis is not predicted and the crisis is not presented to the mobile body in the presenting step, the determination information used for predicting the crisis of the mobile body is corrected when a crisis event occurs in the mobile body A driver crisis management method characterized by performing an analysis step . A driver crisis management program run by a computer,
In the computer,
An acquisition step of acquiring biological information of the driver driving the mobile body and mobile body information;
A determination step of determining whether or not a crisis of the mobile object is predicted using determination information set based on the biological information and the mobile object information ;
If the crisis is predicted, presenting step presents the crisis to the mobile and,
When the crisis is not predicted and the crisis is not presented to the mobile body in the presenting step, the determination information used for predicting the crisis of the mobile body is corrected when a crisis event occurs in the mobile body A driver crisis management program characterized by executing an analysis step .

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