Information processing device, output control method, and output control program

Abstract

To improve the accuracy of information regarding fatigue. [Solution] The information processing device 1 includes an identification unit 11 that identifies situations in which the driver of a vehicle has a duty of care, an acquisition unit 12 that acquires vehicle driving information in the situations identified by the identification unit 11, an storage unit 13 that stores the vehicle driving information acquired by the acquisition unit 12, and an output control unit 17 that outputs information regarding the driver's fatigue based on the vehicle driving information stored by the storage unit 13.

Description

Technical Field

[0001] The present invention relates to an information processing apparatus, an output control method, and an output control program.

Background Art

[0002] For detecting driver abnormalities, information such as trips, sitting time, driving time, stress hormone indices, etc. is used. In addition, in the information providing apparatus described in Patent Document 1, an instability degree calculated from indices based on steering operations and pedal operations, indices based on the operation frequency of levers, and indices based on acceleration and deceleration rates is used (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art including the technology described in Patent Document 1, there is an aspect where it is impossible to distinguish whether the detected abnormality is stress or fatigue. Therefore, in the case of the above prior art, there arises a problem that the accuracy of information regarding fatigue decreases. An example of the problems to be solved by the present invention is the above-described problem.

[0005] The present invention has been made in view of the above, and an object thereof is to provide an information processing apparatus, an output control method, and an output control program that can, for example, improve the accuracy of information regarding fatigue.

Means for Solving the Problems

[0006] The information processing device according to claim 1 comprises: identification means for identifying situations in which a vehicle driver has a duty of care; acquisition means for acquiring driving information of the vehicle in the situations identified by the identification means; storage means for storing the driving information of the vehicle acquired by the acquisition means; and output control means for outputting information regarding the driver's fatigue based on the driving information of the vehicle stored by the storage means.

[0007] The output control method described in claim 10 is an output control method implemented by an information processing device, wherein the information processing device performs the following processes: identify a situation in which the driver of a vehicle has a duty of care; acquire driving information of the vehicle in the identified situation; store the acquired driving information of the vehicle; and output information regarding the driver's fatigue based on the stored driving information of the vehicle.

[0008] The output control program described in claim 11 causes a computer to perform the following processes: identify a situation in which the driver of a vehicle has a duty of care; acquire driving information of the vehicle in the identified situation; store the acquired driving information of the vehicle; and output information regarding the driver's fatigue based on the stored driving information of the vehicle. [Brief explanation of the drawing]

[0009] [Figure 1] Figure 1 is a block diagram showing an example of the functional configuration of an information processing device according to an embodiment. [Figure 2] Figure 2 shows an example of output related to fatigue. [Figure 3] Figure 3 is a schematic diagram showing an example of a temporary stop area. [Figure 4] Figure 4 is a schematic diagram illustrating an example of a method for acquiring driving information. [Figure 5] Figure 5 shows examples of the first and second approximate lines. [Figure 6] Figure 6 is a flowchart showing the procedure for output control processing according to the embodiment. [Figure 7]Figure 7 is a schematic diagram illustrating an example of the application of the duty of care area. [Figure 8] Figure 8 is a schematic diagram illustrating an example of the application of the duty of care area. [Figure 9] Figure 9 is a schematic diagram illustrating an example of the application of the duty of care area. [Figure 10] Figure 10 is a schematic diagram illustrating an example of the application of the duty of care area. [Figure 11] Figure 11 is a schematic diagram illustrating an example of the application of the duty of care area. [Figure 12] Figure 12 shows an example of the functional configuration of a client-server system related to an application example. [Figure 13] Figure 13 illustrates an example of a hardware configuration. [Modes for carrying out the invention]

[0010] The embodiments for carrying out the present invention (hereinafter referred to as "embodiments") will be described below with reference to the drawings. However, the present invention is not limited to the embodiments described below. Furthermore, in the drawings, the same parts are denoted by the same reference numerals.

[0011] <Example of usage scenario> Figure 1 is a block diagram showing an example of the functional configuration of an information processing device according to an embodiment. The information processing device 1 shown in Figure 1 is merely an example and may be implemented using any computer, including a drive recorder, navigation device, AV (Audio Visual) equipment, smartphone, tablet terminal, or wearable device.

[0012] One aspect of this is that the information processing device 1 can be used while it is brought into a vehicle. This is merely an example and does not mean that its use is limited to in-vehicle use, nor does it prevent the information processing device 1 from being used in a state other than in a vehicle. Hereafter, the state in which the information processing device 1 is brought into a vehicle may be referred to as "in-vehicle state".

[0013] <Examples of features provided> The information processing device 1 can provide an output control function for controlling the output of information related to fatigue. Hereinafter, as an example only, an example in which the above output control function is provided in a vehicle-entered state will be given, but the information processing device 1 is not prevented from providing the above output control function, other functions, services, etc. in the vehicle-entered state and other states.

[0014] FIG. 2 is a diagram showing an example of output of information related to fatigue. In FIG. 2, as an example of information output to the output unit 2 by the output control function provided by the information processing device 1 in a vehicle-entered state, notifications 2A to 2C are shown.

[0015] As shown in notification 2A of FIG. 2, when an event such as an increase in fatigue occurs, the output control function can cause the output unit 2 to display an alert including a message "Attention to fatigue! Don't you want to take a break once?" and an icon prompting a break.

[0016] Not limited to the occurrence of such an event, the output control function can also realize the constant output or periodic output of information related to fatigue, as exemplified by notification 2B and notification 2C in FIG. 2.

[0017] For example, as shown in notification 2B of FIG. 2, the output control function can cause the output unit 2 to display, as a message notifying the degree of increase in the driver's fatigue, "The fatigue level has increased by X points", etc.

[0018] Also, as shown in notification 2C of FIG. 2, the output control function can cause the output unit 2 to display a message such as "The average required time until your fatigue accumulates is 86 minutes. Take a break once before 20 minutes elapse". In this way, it is also possible to notify the statistical value of the required time from engine start until an alert for fatigue increase is output and the remaining time until the alert is output.

[0019] The following explanation will use, as an example, the processing and operation when Notification A, one of Notifications 2A to 2C, is executed by the output control function described above, but it is not limited to this example. In other words, it should be noted in advance that the output control function described above can execute at least one of Notifications 2A, 2B, 2C, other notifications, or any combination thereof.

[0020] <Example of a problem> As explained in the section on the problems above, the conventional technology described above has the drawback of being unable to distinguish whether the detected abnormality is stress or fatigue. Therefore, the conventional technology suffers from a problem of reduced accuracy in fatigue-related information. Thus, the output control function according to this embodiment aims to solve, and the above-mentioned problem is one example of this.

[0021] <An example of a problem-solving approach> Therefore, in the output control function according to this embodiment, a problem-solving approach may be adopted in which the driving information used to evaluate the degree of fatigue accumulation is narrowed down to driving information in situations where the driver has a duty of care. Hereinafter, situations in which the driver has a duty of care may be referred to as the "duty of care area."

[0022] The motivation to adopt this problem-solving approach can only be gained with the technical knowledge described below.

[0023] In the case of discontinuous driving behavior while stopped, the driver is at fault as described in (a) to (c) below. Here, "discontinuous driving behavior" refers, in one aspect, to driving that is not smooth. (i) If you can adequately anticipate hazards, you will drive at your own pace, and even if you have to stop, the driving should be relatively smooth. (b) Discontinuous operating behavior is thought to be caused by an unpredictable, sudden disturbance, or an error in the operator's risk assessment. (h) Stopping is a traffic rule (law) that must be followed when a vehicle on a non-priority road enters a priority road; therefore, if sudden braking occurs, you are more at fault than the other party.

[0024] If the area for evaluating the degree of fatigue accumulation is not limited to the area of ​​duty of care, the following disadvantages can be cited: (d) to (n). (ii) It is not possible to determine whether the fault lies with the driver or the other party. (e) When the other party is at fault, feelings of anger arise rather than fatigue. (H) If you are going straight, the faulty party will be constantly in front of and behind you. (T) This can easily lead to aggressive driving (excessive stress relief). (C) Also, simple signal stops are one of the factors that cause discontinuous driving behavior. (R) Just because something is discontinuous doesn't necessarily mean it will lead to stress or fatigue. (Nu) From the perspective of "physical fatigue + mental fatigue," evaluation should be based only on what is at fault on one's own part.

[0025] As described in (ii) to (nu) above, if the evaluation of the degree of fatigue accumulation is not narrowed down to the area of ​​duty of care, external disturbances, stress, and emotions that are not the driver's responsibility may be confused with fatigue and evaluated accordingly.

[0026] To reinforce the points (ii) to (nu) above, we will compare this with cases where discontinuous driving behavior occurs in situations outside the area of ​​the duty of care.

[0027] Firstly, let's consider the example of "Someone aggressively cut in front of me!" While this is stressful, it's unlikely to be the kind of stress that leads to fatigue. Rather, it's the kind of stress that leads to anger, and is highly likely to escalate into excessive stress relief such as road rage.

[0028] Secondly, let's consider the example of "driving on a one-way street when another vehicle suddenly drives in the wrong direction!" In this case, too, it may lead to discontinuous driving behavior such as sudden braking, but such discontinuous driving behavior does not necessarily lead to the accumulation of fatigue. In other words, you might feel a momentary shock or stress, but it doesn't necessarily lead to fatigue. Also, the discontinuous driving behavior doesn't necessarily mean that you were experiencing accumulated fatigue, which resulted in the sudden braking.

[0029] These two cases suggest that if the other party is at fault and has neglected their duty of care, even if the driver exhibits discontinuous driving behaviors such as sudden braking in order to avoid near misses or accidents, it does not necessarily mean that they are fatigued. In addition, it remains possible that the driver's level of alertness decreased due to fatigue, and as a result, they did not brake suddenly, but rather braked suddenly out of necessity to avoid danger.

[0030] From the above, the following technical insights can be obtained: (Wo) to (Ka). (Wo) Discontinuous driving behavior causes stress and fatigue to the driver, but the two are often confused. (W) Because this is a situation where the driver has a duty of care, fatigue (physical fatigue + mental fatigue) is likely to accumulate. (c) Focus on driving behavior in temporary stopping areas and level the degree of fatigue accumulation.

[0031] Based on the technical knowledge described in (Wo) to (Ka) above, when the evaluation of the degree of fatigue accumulation is limited to the area of ​​duty of care, the degree of fatigue accumulation can be evaluated separately from disturbances and stresses not attributable to the driver's responsibility, as described in (Yo) to (Re) below. (Yo) Discrete driving behavior occurring in areas where caution is required is not due to the driver's own intentions based on hazard prediction, but is highly likely to be caused by external disturbances or misinterpretations of hazard predictions. (T) Even if the other party was at fault, the driver himself was at fault for entering a priority road from a non-priority road. (R) Frequent encounters in areas requiring attention can lead to stress and the accumulation of fatigue.

[0032] Therefore, the output control function according to this embodiment can improve the accuracy of fatigue-related information.

[0033] <Configuration of Information Processing Device 1> Next, an example of the functional configuration of the information processing device 1 according to this embodiment will be described. Figure 1 schematically shows blocks corresponding to the functions of the information processing device 1. As shown in Figure 1, the information processing device 1 has an output unit 2, a gyro acceleration sensor 3, a storage unit 4, and a control unit 10. Note that Figure 1 only shows a selection of functional units related to the output control function described above, and the information processing device 1 may also be equipped with functional units other than those shown, for example, functional units that existing computers are equipped with by default or as options, such as a communication control unit.

[0034] Output unit 2 is a functional unit that outputs various types of information. As merely one example, output unit 2 may be implemented by various display devices, such as liquid crystal displays or organic EL (Electro-Luminescence) displays. Alternatively, output unit 2 may be implemented as a display input unit integrated with an input unit (not shown) by a touch panel or the like. Note that the display is not limited to being realized by light emission, but may also be realized by projection. As another example, output unit 2 may be implemented by various audio output devices, such as speakers.

[0035] The gyroaccelerometer 3 corresponds to an example of an acceleration detection unit and an angular velocity detection unit. As another example of an angular velocity detection unit, a geomagnetic sensor can also be used. For example, the gyroaccelerometer 3 can detect acceleration around three axes, such as the X, Y, and Z axes, and angular velocity around three axes, such as roll, pitch, and yaw. Although an example in which acceleration and angular velocity around three axes are detected is given here, the number of axes for which acceleration and angular velocity are detected is not limited to three. Also, although an example in which both acceleration and angular velocity are detected is given here, this does not prevent the detection of only one of the two.

[0036] The memory unit 4 is a functional unit that stores various types of data. As an example, the memory unit 4 can be realized by internal, external, or auxiliary storage or a portion of its storage area within the information processing device 1.

[0037] For example, in the memory unit 4, each time the driving information acquired by the acquisition unit 12 (described later) for each duty of care area is accumulated by the storage unit 13 (described later) up to a predetermined number of pieces, for example 50 pieces, the driving information is packaged into a single driving information group and then added to the memory unit 4 for storage. As this addition is repeated, the memory unit 4 stores a collection of driving information groups, each containing a predetermined number of pieces of driving information packaged together, as the driving information history 5.

[0038] In the following example, we will use the driving information history 5, which is accumulated from the time the vehicle's engine is started by the acquisition unit 12 described later until the engine is stopped, as an example. This is merely an example, and it goes without saying that driving information can continue to accumulate until it is reset by user settings or system settings.

[0039] The above driving information may include time-series data of acceleration in the direction of travel measured in the duty of care area, or the variance of acceleration obtained from the time-series data of acceleration in the direction of travel. Furthermore, the above driving information may include time-series data of velocity in the direction of travel measured in the duty of care area, or the average velocity obtained from the time-series data of velocity in the direction of travel.

[0040] The following explanation will continue using, as an example of the above driving information, driving behavior data represented by a pair of the variance value of the acceleration in the direction of travel and the average speed in the direction of travel acquired in the area of ​​duty of care. Accordingly, in the memory unit 4, whenever the driving behavior data acquired for each area of ​​duty of care has accumulated up to a predetermined number of pieces, for example 50 pieces, it is packaged into a single driving behavior data group and then added and stored. For this reason, the collection of driving behavior data groups in which a predetermined number of pieces of driving behavior data are packaged together can also be described as the driving information history 5.

[0041] Of this driving information history 5, the first group of driving information accumulated from the moment the vehicle's engine is started, i.e., the group of driving behavior data, can be considered to represent a relatively lower level of driver fatigue compared to the period after the vehicle has started driving. For this reason, the group of driving behavior data accumulated from the moment the vehicle's engine is started is distinguished from other groups of driving behavior data as the first distribution 5A of driving behavior data. This is because the first distribution 5A is used as a comparison target for the second distribution of driving behavior data, in order to evaluate the upward trend of the subsequently acquired group of driving behavior data as the second distribution of driving behavior data.

[0042] It should be noted that the information stored in the memory unit 4 is not limited to the driving information history 5 described above. Naturally, this does not prevent other data from being stored in the memory unit 4. For example, the memory unit 4 may store information used by the output control function described above, such as the degree of fatigue increase, the progression of the degree of fatigue increase, and statistical values ​​of the time required until fatigue increases. In addition, the memory unit 4 may also store map data used for vehicle navigation and image data captured for recording purposes.

[0043] The control unit 10 is a processing unit that performs overall control of the information processing device 1. As shown in Figure 1, the control unit 10 includes a specific unit 11, an acquisition unit 12, a storage unit 13, and an output control unit 17.

[0044] The identification unit 11 is a processing unit that identifies situations in which the vehicle driver has a duty of care. For example, the identification unit 11 is an example of an identification means. As just one example, the identification unit 11 performs map matching between the location information of the information processing device 1, measured by a location information measuring unit (not shown), and the duty of care area set on the map data stored in the storage unit 4. The location information measuring unit can be implemented by a GPS (Global Positioning System) receiver or the like.

[0045] For example, areas where drivers are required to pay attention can be defined using information about road signs included in the map data. Below is an example of how areas where drivers are required to stop can be defined. In this case, areas where drivers are required to pay attention can be defined based on nodes where stop signs exist, such as intersections, merging points, and intersections—points of change in road structure.

[0046] Figure 3 is a schematic diagram showing an example of a stop area. As an example, Figure 3 shows a stop area E1 set up at a T-junction where a stop road sign Rs1 is present. As shown in Figure 3, the stop area E1 is set up in an area within a predetermined distance, for example, 3m from the intersection (dark hatched area) and the boundary of the intersection (light hatched area). Although Figure 3 shows an example of a stop area set up at a T-junction, it goes without saying that stop areas can be set up similarly at intersections other than T-junctions.

[0047] Under these stop area settings, the identification unit 11 identifies the passage of a stop area by performing map matching between the location information of the information processing device 1 and the stop area. At this time, if the passage of a stop area is identified, the identification unit 11 further determines whether the direction of passage through the stop area corresponds to travel from a non-priority road to a priority road.

[0048] The acquisition unit 12 is a processing unit that acquires vehicle driving information in a stop area. For example, the acquisition unit 12 is an example of an acquisition means. As just one example, the acquisition unit 12 acquires driving information in a stop area when the direction of passage through the stop area corresponds to travel from a non-priority road to a priority road.

[0049] Figure 4 is a schematic diagram showing an example of a method for acquiring driving information. In Figure 4, as an example, the temporary stop area E1 shown in Figure 3 is indicated by dark and light hatching, and the trajectory of the vehicle's position information is indicated by arrows pointing in a direction corresponding to the passage of time. Furthermore, in Figure 4, the part of the arrow line that is included in the temporary stop area E1 is shown as a solid line, while the part that is not included in the temporary stop area E1 is shown as a dashed line. As shown in Figure 4, the acquisition unit 12 records the time t when entry into the temporary stop area E1 begins. s And the time when the departure from the temporary stop area E1 was completed t e It identifies the following. Subsequently, the acquisition unit 12 uses the log from the gyro acceleration sensor 3 to determine the time t s and time t eTime-series data of 3-axis acceleration corresponding to the interval is obtained.

[0050] After the acceleration is acquired in this manner, the acquisition unit 12 performs the following processing for each of the three-axis accelerations corresponding to the sampling frequency of the gyro acceleration sensor 3, or for each three-axis acceleration that has been resampled at a predetermined interval, for example, every 1 second.

[0051] In other words, the acquisition unit 12 analyzes the direction of travel from the three-axis accelerations: X-axis acceleration, Y-axis acceleration, and Z-axis acceleration. Specifically, the acquisition unit 12 removes the gravitational acceleration from the composite acceleration obtained by combining the three-axis accelerations. Then, the acquisition unit 12 projects the vector of the composite acceleration, from which the gravitational acceleration has been removed, onto the horizontal plane. For example, the horizontal plane can be calculated in advance by calibrating it using the three-axis acceleration when the information processing device 1 is stationary, for example, immediately after startup. The acquisition unit 12 can then analyze the direction of travel from the vector of the composite acceleration projected onto the horizontal plane.

[0052] This analysis of the direction of travel yields time-series data of acceleration in the direction of travel measured in the stopping area. Furthermore, by integrating the time-series data of acceleration in the direction of travel, time-series data of velocity in the direction of travel can be obtained. Here, an example of calculating velocity by integrating acceleration is given, but velocity can also be obtained by other methods. For example, velocity can be obtained by acquiring a vehicle speed pulse from the vehicle speed signal line, or by acquiring a vehicle speed signal via the ECU (Electronic Control Unit) installed in the vehicle using the functions of OBD (On-Board Diagnostics)2.

[0053] Furthermore, the acquisition unit 12 obtains the variance value of acceleration by calculating the variance from the time-series data of acceleration. In addition, the acquisition unit 12 obtains the average speed by calculating the average from the time-series data of speed. In this way, driving behavior data is obtained, which is represented by a pair of the variance value of acceleration in the direction of travel and the average speed in the direction of travel acquired in the area of ​​duty of care.

[0054] The storage unit 13 is a processing unit that stores vehicle driving information acquired by the acquisition unit 12. For example, the storage unit 13 is an example of a storage means. As just one example, the storage unit 13 repeats the following process from when the vehicle engine is started until it is stopped. For example, engine start and stop can be detected by determining whether or not power is supplied corresponding to plugging into or unplugging the vehicle's accessory socket or cigarette lighter socket, or by determining whether the vehicle is stopped for a long period of time, for example, more than one hour. After detecting engine start, the storage unit 13 stores the driving behavior data in a predetermined storage area in memory each time the acquisition unit 12 acquires driving behavior data in a temporary stop area. When the driving behavior data of temporary stop areas stored in memory in this way reaches a predetermined number of pieces, for example 50 pieces, a second distribution 15 of the driving behavior data is obtained. The second distribution 15 of the driving behavior data is then referenced by the output control unit 17 (described later) and added to the driving information history 5 stored in the storage unit 4.

[0055] The output control unit 17 is a processing unit that outputs information regarding the driver's fatigue based on the vehicle's driving information stored by the storage unit 13. For example, the output control unit 17 corresponds to an example of output control means.

[0056] As an example, the output control unit 17 controls whether or not to output information regarding driver fatigue based on the upward trend of the second approximation line, which approximates the second distribution 15 of driving behavior data stored by the storage unit 13, relative to the first approximation line, which approximates the first distribution 5A of driving behavior data stored in the memory unit 4.

[0057] For example, the first and second approximate lines can be calculated by performing regression analysis, such as multiple regression, on the first distribution 5A or the second distribution 15 of the driving behavior data. The partial regression coefficients of the first approximate line are calculated in the first round and then stored in memory or storage unit 4, allowing the calculation of multiple regression to be skipped in subsequent rounds.

[0058] Figure 5 shows an example of a first and second approximation line. Figure 5 shows a graph with the variance of acceleration on the vertical axis and the average velocity on the horizontal axis. Furthermore, in Figure 5, the group of driving behavior data corresponding to the first distribution 5A is plotted as circles, while the group of driving behavior data corresponding to the second distribution 15 is plotted as diamonds. In addition, in Figure 5, the first approximation line L1, which approximates the first distribution 5A of the driving behavior data, is shown as a dashed line, while the second approximation line L2, which approximates the second distribution 15 of the driving behavior data, is shown as a solid line.

[0059] As shown in Figure 5, the first approximation line L1 approximates an upward-sloping line because the degree of sudden braking and the variance increase as the speed increases. The second approximation line L2 also has the characteristic of being an upward-sloping graph. On the other hand, the range of acceleration variance values ​​that appears in the second approximation line L2 is narrower than the range of acceleration variance values ​​that appears in the first approximation line L1. Furthermore, when the average speed is in the low-speed range, the gap in acceleration variance values ​​observed between the first approximation line L1 and the second approximation line L2 becomes more pronounced. In other words, discontinuous driving behavior in the low-speed range is less likely to be observed in the first approximation line L1, while discontinuous driving behavior in the low-speed range is more likely to be observed in the second approximation line L2. This indicates that, when the average speed is high (when the intersection is large), traffic signals provide control, so even as fatigue accumulates, the variance of L2 will only be slightly higher than that of L1 in the region of high average speed. However, when the average speed is low (when the intersection is small), the risk of children or cyclists suddenly running out increases, so the degree of fatigue accumulation is more easily affected at lower speeds. From this, it is clear that comparing the intercept b1 of the first approximation line L1 and the intercept b2 of the second approximation line L2 is effective in determining the upward trend of the second approximation line L2 relative to the first approximation line L1, i.e., the degree of fatigue accumulation.

[0060] Therefore, the output control unit 17 determines whether the intercept b2 of the second approximation line L2 is greater than or equal to a threshold Th1 set based on the intercept b1 of the first approximation line L1. Such a threshold Th1 can be set to a value greater than the intercept b1, for example, intercept b1 + margin α. If the intercept b2 of the second approximation line L2 is greater than or equal to the threshold Th1, it can be estimated that the degree of fatigue accumulation is increasing. In this case, the output control unit 17 outputs information regarding the driver's fatigue. For example, as illustrated in notification 2A in Figure 2, the output control unit 17 can display an alert on the output unit 2 that includes the message "Beware of fatigue! Why not take a break?" and an icon prompting a break. Note that the alert may be implemented not only by display output but also by voice output. For example, a warning sound, such as a beep, can be sounded, or the text corresponding to the message can be read aloud by an automated voice.

[0061] In this way, the output control unit 17 determines the upward trend of the second approximation line relative to the first approximation line. Therefore, instead of evaluating the degree of fatigue accumulation by comparing driving behavior data with a statistically determined threshold, the degree of fatigue accumulation can be evaluated by the autocorrelation of driving behavior data. Consequently, even if there are individual differences in the degree of fatigue accumulation among drivers, it is possible to appropriately evaluate the degree of fatigue accumulation. As a result, it is possible to suppress the mental fatigue caused by making announcements to drivers who are not fatigued, and to suppress the failure to detect fatigued drivers.

[0062] In Figure 5, an example is shown where the vertical axis of the graph represents the variance of acceleration. However, instead of the variance of acceleration, the vertical axis can also represent something similar to the variance of acceleration, such as the degree of sudden braking or deceleration. Also, in Figure 5, an example is shown where the horizontal axis of the graph represents the average speed. However, instead of the average speed, the horizontal axis can also represent the median or mode of speeds similar to the average speed, or the size of the intersection. The "intersection size" mentioned here can be determined by classifying the size of the stop area node based on information such as the width and number of lanes associated with the links connected to the stop area node among the road network links included in the map data.

[0063] Furthermore, while an example of a threshold Th1 using intercept b1 + margin α is given here, the method is not limited to this. For example, the distribution of driving behavior data at the time of an accident can be obtained, and the threshold Th1 can be set based on this. Alternatively, the threshold Th1 can be set based on the transition of intercepts obtained by calculating the intercept of an approximate straight line for each group of driving behavior data from the set of driving behavior data included in the driving information history 5.

[0064] <Processing flow> Next, the processing flow of the information processing device 1 according to this embodiment will be described. Figure 6 is a flowchart showing the output control processing procedure according to this embodiment. This process can be repeated, as an example, from when the power supply of the information processing device 1 is turned ON until it is turned OFF, or from when the engine starts until the engine stops.

[0065] As shown in Figure 6, the identification unit 11 identifies the passage of a stop area by performing map matching between the location information of the information processing device 1 and the stop area (step S101).

[0066] Then, if it is determined that a stop area has been passed (step S101 Yes), the identification unit 11 further determines whether the direction of passing through the stop area corresponds to travel from a non-priority road to a priority road (step S102).

[0067] At this time, if the direction of passage through the stop area corresponds to travel from a non-priority road to a priority road (step S102 Yes), the acquisition unit 12 performs the following processing. That is, the acquisition unit 12 acquires driving behavior data represented by a pair of the variance value of the acceleration in the direction of travel acquired in the stop area and the average speed in the direction of travel acquired in the attention duty area (step S103). Subsequently, the storage unit 13 stores the driving behavior data of the stop area acquired in step S103 in a predetermined storage area on the memory (step S104).

[0068] At this time, if the driving behavior data of the pause area stored in memory reaches a predetermined number of pieces, for example 50 pieces (step S105 Yes), the output control unit 17 performs the following processing. That is, the output control unit 17 calculates a first approximate straight line that approximates the first distribution 5A of the driving behavior data stored in the memory unit 4 (step S106). Note that the distribution and approximate line in S106 may use fixed values ​​from past history or experimental data.

[0069] Furthermore, the output control unit 17 calculates a second approximate straight line that approximates the second distribution 15 of the driving behavior data accumulated by the storage unit 13 (step S107). Subsequently, the output control unit 17 compares the intercept b1 of the first approximate straight line L1 with the intercept b2 of the second approximate straight line L2 (step S108).

[0070] Here, if the intercept b2 of the second approximation line L2 is greater than or equal to the threshold Th1 set based on the intercept b1 of the first approximation line L1 (step S109 Yes), it can be estimated that the degree of fatigue accumulation is increasing. In this case, the output control unit 17 outputs information regarding the driver's fatigue (step S110) and proceeds to step S101.

[0071] If the program proceeds to branch S101No, S102No, S105No, or S109No, it will return to step S101.

[0072] <An example of the effects of the embodiment> As described above, the information processing device 1 according to this embodiment narrows down the driving information used to evaluate the degree of fatigue accumulation to driving information in situations where the driver has a duty of care. This makes it possible to evaluate the degree of fatigue accumulation separately from disturbances and stresses that are not the driver's responsibility. Therefore, the information processing device 1 according to this embodiment can improve the accuracy of information regarding fatigue.

[0073] Furthermore, the information processing device 1 of this embodiment controls whether or not to output information regarding driver fatigue based on the upward trend of a second approximation line, which approximates the second distribution of driving behavior data, relative to a first approximation line, which approximates the first distribution of driving behavior data. Therefore, instead of evaluating the degree of fatigue accumulation by comparing driving behavior data with a statistically determined threshold, the degree of fatigue accumulation can be evaluated by the autocorrelation of driving behavior data. Accordingly, according to the information processing device 1 of this embodiment, even if there are individual differences in the degree of fatigue accumulation among drivers, it is possible to prevent providing information to drivers who are not fatigued, thereby causing them mental fatigue, and to prevent omissions in providing information to drivers who are fatigued.

[0074] Furthermore, the information processing device 1 of this embodiment controls whether or not to output information regarding the driver's fatigue based on whether or not the intercept of the second approximation line is greater than or equal to a threshold determined by the intercept of the first approximation line. This makes it possible to determine the increase in the degree of fatigue accumulation by targeting the intercept where a significant gap in driving behavior appears between the first and second approximation lines. Therefore, according to the information processing device 1 of this embodiment, even if the target is a driver whose driving behavior gap between when fatigued and when not fatigued is smaller than that of other drivers, it is possible to provide information regarding fatigue while suppressing false detections and failures to detect an increase in the degree of fatigue accumulation.

[0075] Furthermore, the information processing device 1 of this embodiment selects the distribution of the first accumulated driving behavior data from the moment the vehicle engine is started as the first distribution. Therefore, the first approximate straight line is selected in which the driver's fatigue level is relatively low compared to after the vehicle starts running. Thus, according to the information processing device 1 of this embodiment, the increase in the degree of fatigue accumulation can be determined by comparing the first approximate straight line, which is more likely to show a gap in driving behavior compared to the second approximate straight line, with the second approximate straight line.

[0076] Furthermore, the information processing device 1 of this embodiment identifies a stop area, acquires driving information within the stop area, stores the acquired driving information within the stop area, and processes information regarding the driver's fatigue based on the stored driving information within the stop area. This makes it possible to evaluate the degree of fatigue accumulation when the driver is required to make a stop, which is one of the duties of care imposed on the driver and carries a higher proportion of negligence. Therefore, the information processing device 1 according to this embodiment can more effectively improve the accuracy of information regarding fatigue.

[0077] Furthermore, the information processing device 1 of this embodiment outputs information regarding the driver's fatigue, including the degree of increase in the driver's fatigue, the progression of the increase, an alert to the driver regarding fatigue, and statistical values ​​of the time elapsed from the time the vehicle engine is started until the alert is output. Therefore, according to the information processing device 1 of this embodiment, the increase in the degree of fatigue accumulation can be announced in a multifaceted manner.

[0078] <Application Examples> The above embodiment is merely an example, and various applications are possible.

[0079] (1) Examples of applications of methods for identifying areas of duty of care In the above embodiment, an example was given in which passage through a duty of care area is identified by map matching, but passage through a duty of care area may be identified by other methods. For example, instead of map matching, passage through a duty of care area may be identified by image recognition of an image captured by an imaging unit mounted on the information processing device 1, or a combination of map matching and image recognition may be used to identify passage through a duty of care area.

[0080] (2) Areas where caution is required other than stop areas In the above embodiment, a stop area was given as an example of an area where attention is required, but the output control function can be applied to other areas where attention is required besides stop areas, and the function is not limited to this.

[0081] Figure 7 is a schematic diagram illustrating an application example of the duty of care area. As an example, Figure 7 shows an example where a flashing signal area E2 is set at a four-way intersection where a flashing signal light Sg1 is installed. Furthermore, Figure 7 shows an excerpt of the yellow flashing signal light Sg1 installed at the four-way intersection, which is set on a non-priority road. As shown in Figure 7, the flashing signal area E2 is set within a predetermined distance, for example, within 3m (dark hatched area), from the intersection (dark hatched area) and the boundary of the intersection, similar to the case of the stop area E1 shown in Figure 3. It goes without saying that although Figure 7 shows an example where a flashing signal area is set at a four-way intersection, flashing signal areas can be set similarly at intersections other than four-way intersections.

[0082] Figure 8 is a schematic diagram illustrating an application example of the duty of care area. As an example, Figure 8 shows an overtaking caution area E3 that is set when vehicle C1 overtakes vehicle C2 on a one-lane road with a white center line. In this case, if the image recognizes that vehicle C1 is crossing the center line to overtake vehicle C2, the overtaking caution area E3 is set using the position information of vehicle C2. In the example shown in Figure 8, the overtaking caution area E3 is set to an area within a predetermined distance from the position information of vehicle C2, for example, within 5m, i.e., inside the dashed circle. When acquiring driving information in such an overtaking caution area E3, it is sufficient to acquire driving information for the section from when the image recognizes that vehicle C1 is crossing the center line to overtake vehicle C2 until the image recognizes that vehicle C1 is driving in front of vehicle C2. Alternatively, driving information may be acquired for the section from when the operation of the right turn signal is detected until the turn signal is returned to its original position. Although Figure 8 shows an example where the center line is white, it goes without saying that the same can be applied to dashed lines or yellow lines.

[0083] Figure 9 is a schematic diagram illustrating an application example of the duty of care area. As an example, Figure 9 shows a right-turn caution area E4 set when turning right at a four-way intersection where traffic lights Sg21 to Sg24, which display illuminated signals, are installed. As shown in Figure 9, the right-turn caution area E4 is set up in the same way as the stop area E1 shown in Figure 3, with the intersection (dark hatched area) and an area within a predetermined distance, for example, 3m, from the boundary of the intersection (dark hatched area). In such a right-turn caution area E4, when vehicle C3 turns right with traffic light Sg21 green, the driver of vehicle C3 is obligated to pay attention to vehicle B1 going straight with traffic light Sg22 green. Therefore, passage through the right-turn caution area E4 is specified only when the right-turn indicator is operated or when a right-turn route at the intersection is set in the navigation route. Although Figure 9 shows an example of setting a right-turn caution area at a four-way intersection, it goes without saying that right-turn caution areas can be set up similarly at intersections other than four-way intersections.

[0084] Figure 10 is a schematic diagram illustrating an example of the application of the duty of care area. As an example, Figure 10 shows a level crossing caution area E5 set up on a one-lane road in each direction where a level crossing R1, including barriers R11 and R12, is installed. As shown in Figure 10, the level crossing caution area E5 is set up to include the area of ​​barriers R11 and R12, and an area within a predetermined distance, for example, 3m, from barrier R11 located in front of the level crossing R1. Although Figure 10 shows an example of setting up a level crossing caution area on a one-lane road in each direction, it goes without saying that level crossing caution areas can be set up similarly on roads with two-way traffic where level crossings are installed.

[0085] Figure 11 is a schematic diagram illustrating an example of the application of the duty of care area. As an example, Figure 11 shows an example in which a pedestrian caution area E6 is set up on a road where a school zone road sign Rs2 exists. As shown in Figure 11, the pedestrian caution area E6 is set up with an area defined by the school zone road sign Rs2 and an area that extends further in front of the school zone road sign Rs2 at a predetermined distance, for example, within 5m.

[0086] As described above, the output control function can be applied to areas of caution other than those explained using Figures 7 to 11. For example, the output control function can be applied when the left has priority at an intersection without traffic lights, when crossing lanes to overtake a vehicle in front (a parked vehicle), when making a left turn and letting a motorcycle following on the left go first, and when crossing sidewalks such as those at gas stations and convenience stores.

[0087] In the above embodiment, an example was given in which the area requiring caution is identified by a sign-like road sign, but the area requiring caution may also be identified by a painted road sign.

[0088] (3) Examples of applications of driving information In the above embodiment, an example was given in which driving behavior data, represented by a pair of the variance of the acceleration in the direction of travel acquired in the area of ​​duty of care and the average speed in the direction of travel acquired in the area of ​​duty of care, is used as driving information. However, it is not necessary to include two items.

[0089] For example, the output control unit 17 can control whether or not to output information regarding the driver's fatigue based on the upward trend of a second distribution of acceleration variance values ​​accumulated by the storage unit 13 after the first distribution of acceleration variance values ​​accumulated by the storage unit 13, relative to a first distribution of acceleration variance values ​​accumulated by the storage unit 13.

[0090] More specifically, the output control unit 17 calculates a representative value of the first distribution by performing predetermined statistical processing, such as calculating the mean, median, and mode, on the variance of acceleration included in the first distribution. The output control unit 17 also calculates a representative value of the second distribution by performing the same statistical processing on the variance of acceleration included in the second distribution as applied to the first distribution. Then, the output control unit 17 determines whether the representative value of the second distribution is greater than or equal to a threshold Th2 set based on the representative value of the first distribution. This threshold Th2 can be set to a value greater than the representative value of the first distribution, for example, the representative value of the first distribution + a margin β. If the representative value of the second distribution is greater than or equal to the threshold Th2, it can be estimated that the degree of fatigue accumulation is increasing. In this case, the output control unit 17 outputs information regarding the driver's fatigue. This allows for providing information to drivers who are not fatigued, preventing them from experiencing mental fatigue, and also prevents information from being missed for fatigued drivers, even if there are individual differences in the degree of fatigue accumulation among drivers.

[0091] Furthermore, while the above embodiment provides an example of determining an upward trend using the distribution of acceleration variance, it is not necessary to use the distribution of acceleration variance. For example, the output control unit 17 can also output information regarding driver fatigue based on the change in acceleration variance accumulated by the accumulation unit 13 during driving in the attention duty area. As just one example, when acceleration variance in the attention duty area is newly accumulated by the accumulation unit 13, the output control unit 17 determines whether the frequency of observing acceleration variance values ​​that are above the threshold Th3 within a predetermined period retrospectively from that point is above the threshold Th4. If the frequency of observing acceleration variance values ​​that are above the threshold Th3 within the predetermined period is above the threshold Th4, it can be estimated that the degree of fatigue accumulation is increasing. In this case, the output control unit 17 outputs information regarding driver fatigue. This makes it possible to evaluate discontinuous driving behavior that leads to fatigue. Therefore, the accuracy of fatigue information can be effectively improved.

[0092] (4) Notification of fatigue recovery The above embodiment provides an example of determining the degree of fatigue accumulation, but it is also possible to determine the degree of fatigue recovery. As just one example, when the accumulation unit 13 newly accumulates the acceleration variance value in the duty of care area, the output control unit 17 can determine whether the frequency of observing acceleration variance values ​​below the threshold Th5 within a predetermined period retrospectively from that point is equal to or greater than the threshold Th6. If the frequency of observing acceleration variance values ​​below the threshold Th5 within the predetermined period is equal to or greater than the threshold Th6, it can be estimated that the degree of fatigue accumulation is decreasing, or in other words, that fatigue is recovering. As another example, the output control unit 17 determines whether the representative value of the second distribution is less than or equal to the representative value of the first distribution. If the representative value of the second distribution is less than or equal to the representative value of the first distribution, it can be estimated that the degree of fatigue accumulation is decreasing, or in other words, that fatigue is recovering. As a further example, the output control unit 17 can estimate that the degree of fatigue accumulation is decreasing, or in other words, that fatigue is recovering, if the intercept b2 of the second approximate line L2 is less than or equal to the intercept b1 of the first approximate line L1. In this case, the output control unit 17 outputs information regarding the driver's fatigue recovery, such as a message notifying the driver of fatigue recovery.

[0093] (5) Examples of applications of the first distribution In the above embodiment, an example was given in which the distribution of driving behavior data accumulated first from the time the vehicle engine was started is selected as the first distribution, but the system is not limited to this. For example, it is also possible to select as the first distribution the distribution of driving behavior data with the smallest intercept among a plurality of approximate lines that approximate each of the plurality of distributions of driving behavior data stored in the driving information history 5 of the storage unit 4. This makes it possible to determine the increase in the degree of fatigue accumulation by comparing the first approximate line, which is more likely to show a gap in driving behavior between it and the second approximate line, with the second approximate line.

[0094] Furthermore, in the above embodiment, the distribution of driving behavior data accumulated immediately before the accumulation of the second distribution of driving behavior data can also be referenced as the first distribution. This makes it possible to evaluate the degree of fatigue accumulation or the degree of fatigue recovery by reflecting recent changes in driving behavior in detail.

[0095] (6) Examples of applications of information notification For example, when performing notification 2B as shown in Figure 2, the gap between the intercept b1 of the first approximation line L1 and the intercept b2 of the second approximation line L2, for example, the absolute value or square of the difference, can be used to calculate the fatigue increase point, or the fatigue decrease point, in other words, the fatigue recovery point. As just one example, if the sign of the subtraction value obtained by subtracting intercept b1 from intercept b2 is positive, the output control unit 17 outputs a display or sound of the fatigue increase point, normalized to a predetermined numerical range, for example, 0 to 10. As another example, if the sign of the subtraction value obtained by subtracting intercept b1 from intercept b2 is negative, the output control unit 17 outputs a display or sound of the fatigue decrease point, normalized to a predetermined numerical range, for example, 0 to 10, in other words, the fatigue recovery point. As yet another example, the output control unit 17 can display or sound the changes in the fatigue increase points and / or fatigue decrease points calculated over time.

[0096] (7) Fatigue + Stress As mentioned above, stress does not necessarily lead to fatigue, but it can cause a certain degree of mental damage. Therefore, the information processing device 1 can also correct the variance of acceleration acquired as driving information according to the degree of stress. As just one example, the information processing device 1 can use at least one of the magnitude and frequency of near misses to correct the variance of acceleration.

[0097] Here, the magnitude of a near miss refers to the magnitude of gravitational acceleration that takes a negative value, that is, the acceleration acting vertically upward. For example, the larger the acceleration acting vertically upward, the larger the correction factor multiplied by the acceleration variance, while the smaller the acceleration acting vertically upward, the larger the correction factor multiplied by the acceleration variance. As just one example, if the acceleration acting vertically upward is 0 or greater, the acceleration variance is multiplied by a correction factor of 1 or greater, while if the acceleration acting vertically upward is less than 0, the acceleration variance is multiplied by a correction factor of 0 or greater but less than 1. Also, the higher the frequency of near misses, the larger the correction factor multiplied by the acceleration variance, while the lower the frequency of near misses, the larger the correction factor multiplied by the acceleration variance. As just one example, if the frequency of near misses is 7 or greater than the threshold Th7, the acceleration variance is multiplied by a correction factor of 1 or greater, while if the frequency of near misses is less than the threshold Th7, the acceleration variance is multiplied by a correction factor of 0 or greater but less than 1.

[0098] In addition, if the location information of the information processing device 1 corresponds to high-risk conditions such as nighttime, school commuting hours, or road width, the information processing device 1 can multiply the acceleration variance by a correction coefficient of 1 or more. On the other hand, if the location information of the information processing device 1 does not correspond to high-risk conditions such as nighttime, school commuting hours, or road width, the information processing device 1 can also multiply the acceleration variance by a correction coefficient of 0 or more but less than 1.

[0099] (8) Client-server system In the above embodiment, an example was given in which the information processing device 1 provides the above output control function, but the above output control function may also be provided as an output control service by the client-server system.

[0100] Figure 12 shows an example of the functional configuration of a client-server system related to an application example. In the client-server system 6 shown in Figure 12, one aspect is that the output control service described above is provided from the server device 8 to the client terminal 7. Note that in Figure 12, the same reference numerals are used for functional units that perform the same functions as those shown in Figure 1, and detailed explanations of functional units with the same reference numerals are omitted.

[0101] As shown in Figure 12, the client-server system 6 may include a client terminal 7 and a server device 8. The client terminal 7 and the server device 8 are connected to each other via a network NW. For example, the network NW may be any type of communication network, whether wired or wireless, such as the Internet or a LAN (Local Area Network).

[0102] Here, for the sake of explanation, Figure 12 shows an example where one client terminal 7 is connected to one server device 8, but naturally, one client terminal 7 may be connected to one server device 8.

[0103] Client terminal 7 is an example of a terminal device that receives the output control service described above. Client terminal 7 may be implemented by any computer, and as an example, it may be implemented by the information processing device 1 shown in Figure 1.

[0104] Here, since the output control service described above is provided by the server device 8, the client terminal 7 does not necessarily need to be equipped with the identification unit 11, acquisition unit 12, storage unit 13, and output control unit 17 shown in Figure 1. Instead, the client terminal 7 has an output unit 2 that performs the same functions as the information processing device 1 shown in Figure 1, in that it outputs information regarding the driver's fatigue. Furthermore, the client terminal 7 has a gyro acceleration sensor 3 that performs the same functions as the information processing device 1 shown in Figure 1, in that it uploads driving information to the server device 8.

[0105] When the server device 8 identifies the passage of the above-mentioned area of ​​duty of care, it may do so by any method; however, if map matching is used, it may have a location information measurement unit on the side of uploading location information. Also, if image recognition is used, it may have an image acquisition unit on the side of uploading images.

[0106] On the other hand, server device 8 is an example of a computer that provides the above output control service. As merely one example, server device 8 can be implemented as a server that provides the above output control service on-premises. Alternatively, server device 8 may be implemented as a SaaS (Software as a Service) application, thereby providing the above output control service as a cloud service.

[0107] The functional configuration of the server device 8 that provides the output control service described above will now be explained. Figure 12 schematically shows the blocks corresponding to the functions of the server device 8. As shown in Figure 8, the server device 8 has a communication interface unit 81, a storage unit 83, and a control unit 85. Note that Figure 1 only shows an excerpt of the functional units related to the output control service described above, and the server device 8 may also be equipped with functional units other than those shown, for example, functional units that existing computers are equipped with by default or as options.

[0108] The communication interface unit 81 corresponds to an example of a communication control unit that performs communication control with other devices, such as a client terminal 7. As an example, the communication interface unit 81 is implemented by a network interface card such as a LAN card. For example, the communication interface unit 81 may receive location information and images in addition to driving information from the client terminal 7. The communication interface unit 81 may also output information such as driver fatigue to the client terminal 7.

[0109] The memory unit 83 is a functional unit that stores various types of data. As an example, the memory unit 18 can be implemented by internal, external, or auxiliary storage of the server device 8. For example, the memory unit 83 stores a driving information history 5 that may match the driving information history 5 shown in Figure 1.

[0110] The control unit 85 is a processing unit that performs overall control of the server device 8. For example, the control unit 85 is implemented by a hardware processor. As shown in Figure 12, the control unit 85 has a specific unit 85A, an acquisition unit 85B, a storage unit 85C, and an output control unit 85D.

[0111] These identification unit 85A, acquisition unit 85B, storage unit 85C, and output control unit 85D may correspond to the identification unit 11, acquisition unit 12, storage unit 13, and output control unit 17 shown in Figure 1. For example, except for the following three points, the identification unit 85A, acquisition unit 85B, storage unit 85C, and output control unit 85D do not need to have any difference in the functions they perform compared to the identification unit 11, acquisition unit 12, storage unit 13, and output control unit 17. First, the identification unit 85A may acquire sensor information such as location information and images via the network NW. Second, the acquisition unit 85B may acquire driving information via the network NW. Third, the output control unit 85D may transmit information regarding driver fatigue via the network NW.

[0112] As described above, the client-server system 6 in this application example can improve the accuracy of fatigue-related information, similar to the information processing device 1 shown in Figure 1.

[0113] <System> Unless otherwise specified, the processing procedures, control procedures, specific names, and various data and parameters shown in the above documents and drawings may be changed at will.

[0114] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown. That is, all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0115] Furthermore, each processing function performed by each device may be implemented, in whole or in part, by a CPU (Central Processing Unit) and a program executed by that CPU, or by wired logic hardware.

[0116] <Hardware> Next, we will describe an example of a computer hardware configuration that executes an information processing program having similar functions to the information processing device described in this embodiment. Figure 13 is a diagram illustrating an example of a hardware configuration. As shown in Figure 13, the computer 100 has a communication device 100a, an HDD (Hard Disk Drive) 100b, memory 100c, and a processor 100d. Furthermore, each of the parts shown in Figure 13 is interconnected by a bus or the like.

[0117] The communication device 100a is a network interface card or the like, and communicates with other servers. The HDD 100b stores programs and DB (Database) that operate the functions shown in Figures 1 and 12.

[0118] The processor 100d operates processes that perform the functions described in Figures 1 and 12 by reading programs that perform the same processing as the processing units shown in Figures 1 and 12 from the HDD 100b and loading them into memory 100c. For example, a process performs the same functions as the processing units of computer 100. Specifically, the processor 100d reads programs that have the same functions as the identification unit 11, acquisition unit 12, storage unit 13, and output control unit 17 from the HDD 100b. Then, the processor 100d executes processes that perform the same processing as the identification unit 11, acquisition unit 12, storage unit 13, and output control unit 17.

[0119] Thus, the computer 100 operates as an information processing device that performs various processing methods by reading and executing a program. Furthermore, the computer 100 can also achieve the same functionality as in the above-described embodiment by reading the program from a recording medium using a media reader and executing the read program. It should be noted that the program referred to in this other embodiment is not limited to being executed by the computer 100. For example, the functions of the information processing device described in this embodiment can be similarly achieved when another computer or server executes the program, or when these computers or servers collaborate to execute the program.

[0120] This program can be distributed via networks such as the Internet. Furthermore, this program can be recorded on computer-readable storage media such as hard disks, flexible disks (FDs), CD-ROMs, MO (Magneto-Optical disks), and DVDs (Digital Versatile Discs), and executed by reading the program from these media using a computer. [Explanation of symbols]

[0121] 1. Information Processing Device 2 Output section 3. Gyro accelerometer 4 Storage section 5. Driving Information History 5A First distribution 10 Control Unit 11 Specific section 12 Acquisition Department 13 Storage section 15. Second distribution 17 Output Control Unit

Claims

1. A means of identifying situations in which a vehicle driver has a duty of care, An acquisition means for acquiring driving information of the vehicle in the scene identified by the aforementioned identification means, A storage means for storing the vehicle driving information acquired by the acquisition means, An output control means that outputs information regarding the driver's fatigue based on the vehicle's driving information stored by the storage means, Equipped with, The aforementioned identification means identifies the temporary stopping area, The acquisition means acquires the vehicle's driving information in the temporary stop area identified by the identification means, The storage means stores the driving information in the temporary stop area acquired by the acquisition means, The output control means executes information regarding the driver's fatigue based on the driving information of the temporary stop area accumulated by the storage means. Information processing device.

2. The storage means stores the variance value of the acceleration in the direction of travel, which is acquired by the acquisition means as driving information of the vehicle for each scene. The information processing apparatus according to claim 1, wherein the output control means outputs information regarding the driver's fatigue based on the change in the variance value of the acceleration accumulated by the accumulation means during driving in the scene.

3. The information processing apparatus according to claim 2, wherein the output control means controls whether or not to output information regarding the driver's fatigue based on the upward trend of a second distribution of acceleration variance values ​​accumulated by the storage means after the first distribution, with respect to a first distribution of acceleration variance values ​​accumulated by the storage means.

4. The storage means stores data represented by a pair of the variance value of the acceleration in the direction of travel and the average speed of the scene or the size of the intersection in the scene. The information processing apparatus according to claim 2 or 3, wherein the output control means controls whether or not to output information regarding the driver's fatigue based on the upward trend of a second approximation line, which approximates the second distribution of the data accumulated by the storage means, with respect to a first approximation line, which approximates the first distribution of the data accumulated by the storage means.

5. The information processing apparatus according to claim 4, wherein the output control means controls whether or not to output information regarding the driver's fatigue based on whether or not the intercept of the second approximate line is greater than or equal to a threshold determined by the intercept of the first approximate line.

6. The information processing apparatus according to claim 4 or 5, wherein the output control means selects as the first distribution the distribution of data first stored by the storage means from the time the vehicle's engine is started, or the distribution of data whose intercept is smallest among a plurality of approximate lines that approximate each of a plurality of distributions of the data stored by the storage means.

7. The storage means stores the variance value of the acceleration in the direction of travel, which is acquired by the acquisition means as driving information of the vehicle for each scene. The information processing apparatus according to any one of claims 1 to 6, wherein the output control means controls whether or not to output information regarding the driver's fatigue based on the frequency at which the variance value of the acceleration exceeds a threshold.

8. The information processing apparatus according to any one of claims 1 to 7, wherein the output control means outputs, as information relating to the driver's fatigue, the degree of increase in the driver's fatigue, the progression of the degree of increase, an alert to the driver regarding fatigue, or a statistical value of the time required from the time the vehicle's engine is started until the alert is output.

9. An output control method implemented by an information processing device, Identify situations in which the vehicle driver has a duty of care, The vehicle's driving information in the identified scene is acquired. The acquired vehicle driving information is stored, Based on the accumulated vehicle driving information, information regarding the driver's fatigue is output. The information processing device performs the processing, Identify the stop area, The vehicle's driving information in the identified temporary stop area is acquired. The acquired driving information in the temporary stop area is stored, Based on the accumulated driving information in the temporary stop area, the system performs the following actions regarding the driver's fatigue: An output control method in which the processing is performed by the information processing device.

10. Identify situations in which the vehicle driver has a duty of care, The vehicle's driving information in the identified scene is acquired. The acquired vehicle driving information is stored, Based on the accumulated vehicle driving information, information regarding the driver's fatigue is output. Let the computer perform the process, Identify the stop area, The vehicle's driving information in the identified temporary stop area is acquired. The acquired driving information in the temporary stop area is stored, Based on the accumulated driving information in the temporary stop area, the system performs the following actions regarding the driver's fatigue: An output control program that instructs a computer to perform a process.

Images