JP2019159360A - Output device, output method, and program - Google Patents

Abstract

To provide a method for reducing the possibility of and preventing a body condition of an occupant becoming worse.SOLUTION: An output device 10 includes: an acquisition section 11 for acquiring route information indicating a route of a mobile body and feature information indicating a feature of the route; and an output section 12 for outputting notification information on the basis of prediction of a change in a body condition of an occupant of a mobile body on a route to be obtained from route information and feature information.SELECTED DRAWING: Figure 2

Description

  The present invention relates to an output device, an output method, and a program.

  Patent Document 1 discloses an automatic driving vehicle that detects the physical condition of a passenger of a vehicle and performs automatic driving control in accordance with the physical condition of the passenger. Patent Document 2 discloses an automatic driving vehicle that detects a vehicle sickness state of a vehicle occupant and performs automatic driving control in accordance with the vehicle sickness state of the occupant.

JP 2008-120271 A JP 2012-59274 A

  The techniques described in Patent Documents 1 and 2 reduce or prevent the deterioration of the passenger's physical condition (car sickness) by controlling the automatic driving according to the physical condition of the passenger. However, there are cases where the deterioration of the physical condition of the passenger cannot be sufficiently reduced or prevented only by the control of the automatic driving. An object of the present invention is to provide a method for reducing or preventing deterioration of the physical condition of a passenger.

The present invention described in claim 1
An acquisition unit that acquires route information indicating a route of the moving object and feature information indicating a feature of the route;
An output unit that outputs notification information based on prediction of a physical condition change of a passenger of the moving body on the route obtained by the route information and the feature information;
An output device comprising:

The present invention according to claim 19 provides:
Computer
An acquisition step of acquiring route information indicating a route of the moving object and feature information indicating a feature of the route;
An output step of outputting notification information based on a prediction of a physical condition change of a passenger of the moving body on the route obtained by the route information and the feature information;
Is the output method to execute.

The present invention according to claim 20 provides:
Computer
Acquisition means for acquiring route information indicating a route of the moving object and feature information indicating a feature of the route;
An output means for outputting notification information based on a prediction of a physical condition change of a passenger of the moving object on the route obtained by the route information and the feature information;
It is a program that functions as

It is a figure which illustrates the hardware constitutions of an output device. It is an example of the functional block diagram of an output device. It is an example of the functional block diagram of an output device. It is a figure which shows an example of the information produced | generated by an output device typically. It is a figure which shows an example of the information produced | generated by an output device typically. It is a figure which shows an example of the information output by an output device typically. It is a figure which shows an example of the information output by an output device typically. It is a figure which shows an example of the information output by an output device typically. It is a flowchart which shows an example of the flow of a process of an output device. It is an example of the functional block diagram of an output device. It is a figure which shows an example of the information output by an output device typically. It is an example of the functional block diagram of an output device.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings. In all the drawings, the same reference numerals are given to the same components, and the description will be omitted as appropriate.

<First Embodiment>
First, an outline of the output device of this embodiment will be described. The output device acquires route information indicating the route of the moving body and feature information indicating the feature of the route. Then, the output device outputs the notification information based on the prediction of the physical condition change of the occupant of the moving body on the route obtained from the route information and the feature information.

  According to the output device of this embodiment, the user can manage his / her behavior in the vehicle based on the notification information output from the output device so that his / her physical condition does not deteriorate. As a result, the deterioration of the physical condition of the passenger is reduced or prevented.

  Next, the configuration of the output device of this embodiment will be described in detail. The output device may be a mobile body mounting device installed in a mobile body (eg, an automobile (which may or may not have an automatic driving function)) (for example, a car navigation system). ), A mobile device such as a smartphone, a tablet terminal, a mobile phone, a notebook PC (personal computer), or a stationary PC. The output device may be connected to and communicate with an ECU (electronic control unit) mounted on the moving body by wire and / or wirelessly. The ECU controls various systems mounted on the moving body.

  First, an example of the hardware configuration of the output device will be described. The functions of the output device include a CPU (Central Processing Unit) of an arbitrary computer, a memory, a program loaded into the memory, a storage unit such as a hard disk for storing the program (a program stored in advance from the stage of shipping the device) In addition, it is possible to store a program downloaded from a storage medium such as a CD (Compact Disc) or a server on the Internet, etc.), and an arbitrary combination of hardware and software centering on a network connection interface. It will be understood by those skilled in the art that there are various modifications to the implementation method and apparatus.

  FIG. 1 is a block diagram illustrating a hardware configuration of the output device. As shown in FIG. 1, the output device includes a processor 1A, a memory 2A, an input / output interface 3A, a peripheral circuit 4A, and a bus 5A. The peripheral circuit 4A includes various modules. The peripheral circuit 4A may not be provided.

  The bus 5A is a data transmission path through which the processor 1A, the memory 2A, the peripheral circuit 4A, and the input / output interface 3A transmit / receive data to / from each other. The processor 1A is an arithmetic processing device such as a CPU (Central Processing Unit) or a GPU (Graphics Processing Unit). The memory 2A is a memory such as a RAM (Random Access Memory) or a ROM (Read Only Memory). The input / output interface 3A includes an interface for acquiring information from an input device (eg, keyboard, mouse, microphone, etc.), external device, external server, external sensor, etc., and an information output device (eg, display, speaker, printer, An interface for outputting information to an external device, an external server, or the like. The processor 1A can issue a command to each module and perform a calculation based on the calculation result.

  Next, the functional configuration of the output device will be described. FIG. 2 shows an example of a functional block diagram of the output device 10 of the present embodiment. As illustrated, the output device 10 includes an acquisition unit 11 and an output unit 12. FIG. 3 shows another example of a functional block diagram of the output device 10 of the present embodiment. As illustrated, the output device 10 may include a prediction unit 13 in addition to the acquisition unit 11 and the output unit 12.

  The acquisition unit 11 acquires route information indicating the route of the moving body and feature information indicating the feature of the route.

  The route information indicates a “movement route from the departure point to the destination” calculated by the computer based on the departure point and the destination. The output device 10 may have a route search function for searching for the movement route. Then, the acquisition unit 11 may acquire route information indicating the movement route calculated by the output device 10. In addition, the acquisition unit 11 may acquire path information generated by an external device physically and / or logically separated from the output device 10 from the external device. In this case, the output device 10 and the external device are configured to be communicable by wire and / or wireless.

  The characteristic information indicates characteristics of a route that may cause the physical condition of the occupant to deteriorate, more specifically, car sickness.

  For example, the feature information may indicate prediction of acceleration (direction and magnitude of acceleration, etc.) applied to the moving moving body at each point on the path of the moving body. The acceleration applied to the moving body is caused by the acceleration in the moving direction of the moving body due to the acceleration of the moving body, the acceleration opposite to the moving direction of the moving body due to the deceleration of the moving body, the right turn of the moving body, etc. Acceleration in the right direction toward the traveling direction of the moving body, acceleration in the left direction in the traveling direction of the moving body due to left turn of the moving body, and the vertical direction of the moving body due to road irregularities There is acceleration. Irregular acceleration is repeatedly applied to the passenger, which may cause deterioration of the physical condition of the passenger (eg, car sickness).

  In addition, the feature information may indicate the curvature of a curve (eg, curve, right / left turn point) included in the route. The magnitude of the curvature has a causal relationship with the acceleration applied to the moving moving body.

  Next, a means for the acquisition unit 11 to acquire feature information of the route of the moving body will be described. For example, the output device 10 may hold map data indicating characteristics at each point on the road (eg, prediction of acceleration applied to a moving moving object, curvature, etc.). And the acquisition part 11 may acquire the characteristic (characteristic information) of the path | route of a moving body from the said map data. In addition, an external device that is physically and / or logically separated from the output device 10 may hold the map data. Then, the acquisition unit 11 may request feature information of the route of the moving body from the external device, and may acquire feature information of the route of the moving body from the external device. In this case, the output device 10 and the external device are configured to be communicable by wire and / or wireless.

  The prediction of acceleration at each point on the road may be obtained, for example, by statistically processing measured acceleration values at each point collected by an acceleration sensor installed in each of a plurality of moving objects. Good. Further, the curvature of each point on the road may be calculated based on the shape of the road.

  The prediction unit 13 predicts a change in the physical condition of the passenger based on the route information and the feature information. Specifically, the prediction unit 13 predicts whether or not there is a possibility that the passenger may get sick. Hereinafter, although an example of a prediction process is demonstrated, you may predict by another method.

"Prediction process 1"
For example, the prediction unit 13 may calculate a time schedule for predicting accelerations (acceleration direction and magnitude, etc.) applied to the moving body and the passenger while moving along the path of the moving body based on the route information and the feature information. Good. An example is shown in FIG. According to the time schedule of FIG. 4, acceleration in the right direction X ₁ G is applied 12 minutes and 19 seconds after departure, and acceleration in the left direction X ₂ G is applied 13 minutes and 01 seconds after departure. Further, an acceleration in the forward direction X ₄ G is applied after 14 minutes and 10 seconds from the departure, and an acceleration in the backward direction X ₅ G is applied after 14 minutes and 30 seconds from the departure. Thereafter, it can be seen that accelerations in various directions are irregularly and intermittently applied.

  After obtaining the acceleration prediction time schedule as described above, the prediction unit 13 determines whether there is a location that matches a predetermined “condition causing car sickness” in the acceleration prediction time schedule. You may search.

  The condition causing car sickness is a design matter, but can be defined using the magnitude of acceleration, the direction of acceleration, the time interval during which acceleration is applied, the duration, and the like. For example, “the time in which acceleration equal to or higher than the reference value continues for a reference time (eg, 10 minutes) at a time interval shorter than the first time (eg: 3 minutes)” or “first time ( For example, in a time interval shorter than 3 minutes), a time in which acceleration in a direction different from the acceleration that occurred at a reference value or earlier is continued for a reference time (eg, 10 minutes) " Others may also be used. In addition, data related to car sickness (such as sickness) for each subject was collected in advance from multiple subjects, including the magnitude of acceleration, the direction of acceleration, the time interval during which acceleration takes, and the duration, etc., and was generated based on this data. Conditions that cause car sickness may be used.

  Then, the prediction unit 13 predicts a time zone that matches the condition causing the car sickness as a time zone when the passenger may cause a car sickness, and the time zone that does not meet the condition that causes the car sickness is determined by the passenger. It may be predicted as a time zone in which there is no fear of causing car sickness.

"Prediction process 2"
For example, the prediction unit 13 may calculate a time schedule that passes through a location where the curvature is equal to or less than a reference value based on the route information and the feature information. An example is shown in FIG. According to the time schedule of FIG. 5, after passing 12 minutes 19 seconds from the departure, it passes through the curvature point of R = Y ₁ and after 13 minutes 01 seconds from the departure, it passes through the curvature point of R = Y ₂ to 14:00 it can be seen that pass through the curvature point of R = Y ₃ after seconds.

  After obtaining the time schedule for passing the curvature point as described above, the prediction unit 13 determines whether there is a point that matches a predetermined “condition causing car sickness” in the time schedule for passing the curvature point. You may search.

  The condition causing car sickness is a design matter, but can be defined by using a value of curvature, a time interval of passing through a curvature portion, a duration, and the like. For example, even if “the time during which the passage of the curvature portion equal to or less than the reference value continues at a time interval shorter than the first time (eg, 3 minutes) continues for more than the reference time (eg, 10 minutes)” It may be good or other. In addition, data related to car sickness (such as sickness) is collected in advance from a plurality of subjects, such as curvature values, time intervals between passing curvature points, durations, etc., and car sickness generated based on this data is caused. Conditions may be used.

  Then, the prediction unit 13 predicts a time zone that matches the condition causing the car sickness as a time zone when the passenger may cause a car sickness, and the time zone that does not meet the condition that causes the car sickness is determined by the passenger. It may be predicted as a time zone in which there is no fear of causing car sickness.

  The prediction unit 13 may also predict a time zone in which the passenger is not likely to get sick by using deep learning such as LSTM (Long Short-Term Memory) in consideration of the time direction.

  Moreover, although the said prediction was divided into the time slot | zone which may cause car sickness, and the time slot | zone which cannot raise | generate, it may divide into three or more time slots. That is, the time zone may be divided according to the degree of car sickness. For example, based on data related to car sickness, conditions that cause strong car sickness and conditions that cause weak car sickness are generated, and time periods that match the conditions that cause strong car sickness may cause strong car sickness, A time zone that matches the condition that causes weak car sickness may be predicted as a time zone that may cause weak car sickness, and a time zone that does not meet either condition may be predicted as a time zone that does not cause car sickness.

  In addition, using historical information of a time zone in which a passenger predicted in the past may cause car sickness and a time zone in which there is no risk of car sickness, three or more time zones, for example, time zones that cause car sickness A time zone in which car sickness is likely to occur, a time zone in which car sickness is unlikely to occur, and a time zone in which car sickness is not exceeded may be predicted.

  Returning to FIG. 2 and FIG. 3, the output unit 12 outputs the notification information based on the prediction of the physical condition change of the occupant of the moving body on the route obtained from the route information and the feature information. The output unit 12 may output the prediction result of the physical condition change of the passenger on the route as the notification information.

  For example, the output unit 12 may display the notification information on the display. FIG. 6 schematically shows an example of information output by the output unit 12. The illustrated information includes a map, and a route R from the departure point (eg, current point) A of the moving object to the destination B is shown on the map. In addition, a place P where the passenger is likely to deteriorate in physical condition (eg car sickness) is highlighted.

  FIG. 7 schematically shows another example of information output by the output unit 12. The information shown in the drawing is a guideline for the time to reach the entrance of the place P where the passenger may cause a physical condition deterioration (eg car sickness) and the time to reach the exit of the place P. Show.

  FIG. 8 schematically shows another example of information output by the output unit 12. The information shown in the figure indicates the time when the passenger reaches the entrance of the place P where the physical condition may deteriorate (e.g., getting sick) and the time when the passenger reaches the exit of the place P.

  In addition, the output unit 12 may output notification information via a speaker. For example, “There is a possibility of getting intoxicated from the crossing to the destination.

Moreover, the prediction unit 13 may predict a condition that causes car sickness from the past travel history. For example, probe data (travel information such as speed, triaxial acceleration, and triaxial angular velocity information) is acquired from an actual traveling vehicle (manually driven vehicle) on each route. The probe data is subjected to statistical processing (average processing, median processing, etc.) to predict conditions that cause car sickness in each route.
Moreover, you may predict the conditions which cause car sickness using the historical information when the passenger of the vehicle traveled the route in the past.

  Moreover, one or a plurality of information from the road feature information such as the road shape, the number of lanes and the number of pedestrians, the type information of the moving body such as the vehicle type, the weather information, the driving mode information of the autonomous driving vehicle, etc. Conditions that cause car sickness may be predicted.

  Next, an example of the processing flow of the output device 10 will be described using the flowchart of FIG.

  In S10, the acquisition unit 11 collects various information. Specifically, the acquisition unit 11 acquires route information indicating the route of the moving object and feature information indicating the feature of the route.

  In S11, the prediction unit 13 predicts a change in the physical condition of the passenger based on the route information and the feature information acquired in S10.

  In S12, the output part 12 produces | generates and outputs the alerting | reporting information notified to a passenger based on the prediction in S11.

  According to the output device 10 of the present embodiment described above, the user causes his / her physical condition to deteriorate while moving along the route to the destination based on the notification information output from the output device (eg, getting sick). Possible location and time zone can be grasped. For this reason, the user can take an appropriate response for preventing the deterioration of his / her physical condition based on the notification information. For example, a user performs a desired work such as reading in a place or time zone where there is no possibility of deteriorating physical condition, and a physical condition such as resting, taking a nap, looking at the scenery in a place or time period where there is a possibility of deteriorating physical condition Can take actions that are less likely to cause deterioration. As a result, it is possible to effectively reduce and prevent physical condition deterioration.

<Second Embodiment>
The output device 10 of this embodiment is different from that of the first embodiment in that it predicts a change in physical condition of a passenger of a moving object on the route of the moving object based on further additional information. According to this embodiment, it is possible to predict with higher accuracy.

  An example of the hardware configuration of the output device 10 is the same as that of the first embodiment.

  An example of a functional block diagram of the output device 10 is shown in FIG. As illustrated, the output device 10 includes an acquisition unit 11, an output unit 12, and a prediction unit 13.

  The acquisition unit 11 further acquires additional information for predicting a change in physical condition of the passenger of the moving object on the route of the moving object. Other configurations of the acquisition unit 11 are the same as those in the first embodiment.

  The additional information includes (1) information indicating the physical condition of the passenger on the day, (2) traffic congestion information on the route of the moving body, (3) the seat position of the passenger, and (4) the age of the passenger. Including at least one.

  The information indicating the physical condition of the passenger indicates a physical condition that may affect physical condition deterioration (eg, car sickness) that may occur to the passenger during the movement of the moving object. For example, whether it is lack of sleep, physical fatigue, mental depression, hungry or fullness, and the like may be included. For example, the acquisition unit 11 may receive an input indicating the physical condition of the passenger from the user.

  The traffic jam information of the route of the mobile body indicates whether or not there is a traffic jam location on the route of the mobile body. The acquisition unit 11 can acquire the traffic jam information through any technique.

  The seat position of the passenger indicates the seat position where the passenger is located in the moving body. For example, the acquisition unit 11 may receive an input indicating the seat position of the passenger from the user.

  Moreover, the acquisition part 11 may receive the input of a passenger's age from a user, for example.

  The prediction unit 13 predicts a change in the physical condition of the passenger based on the additional information in addition to the route information and the feature information. Specifically, the prediction unit 13 predicts whether or not there is a possibility that the passenger may get sick.

"Prediction process 3"
The prediction process 3 is a process obtained by improving the prediction processes 1 and 2 described in the first embodiment. For example, a plurality of “conditions causing car sickness” described in the prediction processes 1 and 2 may be prepared according to at least one of the physical condition, seat position, and age of the passenger. And the prediction part 13 may predict a passenger's physical condition change based on the "condition which causes car sickness" corresponding to a passenger's physical condition, a seat position, age, etc. FIG.

  For example, the condition that causes car sickness is “the time during which acceleration equal to or higher than a reference value continues for a reference time (eg, 10 minutes) at a time interval shorter than the first time (eg, 3 minutes)” In some cases, the physical condition that tends to cause physical condition deterioration (eg, lack of sleep, physical fatigue, mental depression, hunger or fullness), seat position, age, etc. May be long. Further, the acceleration reference value may be smaller as the physical condition, the seat position, and the age are more likely to cause physical deterioration. In addition, the reference time may be shorter as the physical condition, seat value, and age are likely to cause physical condition deterioration.

  In addition, the condition that causes car sickness is “the time during which the passage of the curvature portion below the reference value continues at a time interval shorter than the first time (eg, 3 minutes) continues for the reference time (eg, 10 minutes) or longer. In the case of “Yes”, the first time may be longer as the physical condition, the seat position, and the age are more likely to cause physical deterioration. Further, the curvature reference value may be larger as the physical condition, the seat position, and the age are more likely to cause physical deterioration. In addition, the reference time may be shorter as the physical condition, seat position, and age are likely to cause physical condition deterioration.

"Prediction process 4"
The prediction process 4 is a process obtained by improving the prediction process 1 described in the first embodiment. As described in the prediction process 1, “map data indicating characteristics at each point on the road (prediction of acceleration applied to a moving moving object)” indicates when traffic congestion occurs and when traffic congestion does not occur. Two patterns may be prepared. Then, the acquisition unit 11 predicts the acceleration (the direction and the magnitude of acceleration, etc.) applied to the moving mobile body at each point on the route of the mobile body when a traffic jam occurs, and You may acquire the characteristic information which shows both predictions (acceleration direction, magnitude | size, etc.) concerning the mobile body in driving | running | working in each point on a path | route.

  The prediction unit 13 uses the feature information at the time of occurrence of the traffic jam at the location where the traffic jam has occurred, and uses the feature information at the time when the traffic jam has not occurred at the location where the traffic jam has not occurred. Can be predicted.

"Prediction process 5"
The prediction process 5 is a process obtained by improving the prediction process 1 described in the first embodiment. More specifically, the prediction process 5 is a process in which the prediction processes 3 and 4 are combined. As described in the prediction process 1, “map data indicating characteristics at each point on the road (prediction of acceleration applied to a moving moving object)” indicates when traffic congestion occurs and when traffic congestion does not occur. Two patterns may be prepared. Then, the acquisition unit 11 predicts acceleration (direction and magnitude of acceleration, etc.) applied to the moving mobile body at each point on the path of the mobile body when a traffic jam occurs, and the mobile body when no traffic jam occurs. At each point on the route, characteristic information indicating both predictions of acceleration (direction and magnitude of acceleration, etc.) applied to the moving moving body may be acquired.

  The prediction unit 13 uses the feature information at the time of occurrence of the traffic jam at the location where the traffic jam occurs and uses the feature information at the time of no traffic jam at the location where the traffic jam has not occurred. Can be predicted. In other words, the prediction unit 13 predicts a change in the physical condition of the passenger based on the “condition causing car sickness” corresponding to the physical condition, seat position, age, and the like of the passenger.

  The configuration of the output unit 12 is the same as that of the first embodiment.

  According to the output device 10 of the present embodiment described above, the same function and effect as those of the first embodiment can be realized. Moreover, according to the output device 10 of the present embodiment, it is possible to predict the change in the physical condition of the passenger of the moving object on the route of the moving object with higher accuracy.

  A modification of this embodiment will be described. When there are a plurality of passengers, the acquisition unit 11 may acquire additional information for each passenger. And the prediction part 13 may predict a passenger's physical condition change for every passenger. And the prediction part 13 may output a prediction result for every passenger.

  Similar effects can be realized in the modified example. Moreover, according to a modification, alerting | reporting information can be output with respect to each of several passengers. Since the notification information can be adapted to each passenger, the notification information becomes useful information with higher accuracy.

  Another modification of the present embodiment will be described. The acquisition unit 11 may newly acquire at least one of the route information, the feature information, and the additional information while moving the route. For example, when the current location of the mobile object deviates from the route indicated by the route information and new route information is generated, the acquisition unit 11 may acquire new route information. And the acquisition part 11 may acquire the characteristic information regarding a new path | route according to this. Moreover, the acquisition part 11 may acquire the additional information which shows a new physical condition and a seat position, when there exists a change of a passenger's physical condition, a change of a seat position, etc.

  And the prediction part 13 repredicts a passenger's physical condition change at the timing (predetermined timing) when the acquisition part 11 newly acquired at least one of route information, characteristic information, and additional information. May be. And the output part 12 may output the alerting | reporting information based on a new prediction result newly.

  In addition, the prediction unit 13 may re-predict the passenger's physical condition change based on the passenger's sickness information. The acquisition of sickness information may be acquired based on a passenger's button input, past travel route and history information of passenger's sickness on the route, biosensor acquisition results, and the like.

  Also in this modification, the same effect can be realized. Moreover, according to the modified example, new notification information can be output according to a change in the situation. Therefore, the notification information is useful information with high accuracy.

<Third Embodiment>
The output device 10 of the present embodiment is different from the first and second embodiments in that a recommended schedule indicating the recommended behavior of the moving passenger is output based on the prediction of the physical condition change of the passenger. According to the present embodiment, the passenger can grasp an appropriate response for preventing the deterioration of his / her physical condition based on the notification information output from the output device 10.

  An example of the hardware configuration of the output device 10 is the same as in the first and second embodiments.

  An example of a functional block diagram of the output device 10 is shown in FIG. As illustrated, the output device 10 includes an acquisition unit 11, an output unit 12, a prediction unit 13, and a schedule generation unit 14.

  The acquisition unit 11 acquires information (task information) indicating a task performed while the passenger is moving. Other configurations of the acquisition unit 11 are the same as those in the first and second embodiments. Tasks can include tasks that are prone to motion sickness such as reading, watching movies, work, smartphone operations, research, etc., and tasks that are less likely to cause motion sickness such as sleeping, listening to music, enjoying scenery, etc. . Note that the plurality of tasks indicated as task information may be classified in advance into tasks that increase the possibility of physical condition deterioration and tasks that do not.

  Here, a method in which the acquisition unit 11 acquires task information will be exemplified.

  As a first example, there is an example in which task information is acquired by user input. For example, a task as exemplified above may be displayed on the display so as to be selectable, and a user input to be selected from among them may be accepted.

  As a second example, an example of acquiring a task set as a default in advance is given. For example, a task that is likely to be performed while the user is moving may be set in advance as a default. In addition, a task with the highest execution frequency among tasks input by the user in the past may be set as a default.

  In addition, based on the moving passengers detected in the past and the state in the vehicle, the task that the passengers were performing during the past movement is estimated, and the task with the highest frequency among them is set as the default. May be. For example, passenger information (posture information, the point of the passenger's line of sight, what the passenger has in his hand, etc.) based on images generated by a camera installed in the car or a TOF (time of flight) camera May be obtained. Further, information indicating the state (ON / OFF state) of the in-vehicle system may be acquired from the in-vehicle system (display, speaker, etc.). And based on such information, you may estimate the task which the passenger is performing.

  For example, correlation information indicating a correlation between a passenger or a state in the vehicle specified by the collected information and a task performed by the passenger in each state may be stored in the output device 10 in advance. Then, the output device 10 may estimate a task performed by the passenger based on the correlation information and the detected passenger or in-vehicle state.

  The correlation information may be unique to the passenger. For example, it is possible to collect passengers and in-vehicle states detected at the time of boarding in the past and a task selected by user input at that time, and generate correlation information based on the collected information. In addition, as the correlation information, a passenger's schedule information stored in a terminal device, a cloud, or the like owned by the passenger, future destination information, or the like may be used. The correlation information may be general-purpose information that applies to a general user. For example, the correlation information is collected from a plurality of output devices 10 used by a plurality of users, the passengers detected in the past and the state in the vehicle, and the task specified by the user input at that time, Correlation information can be generated based on the collected information.

  The prediction unit 13 predicts a change in the physical condition of the passenger based on the task information in addition to the route information and the feature information. Note that the prediction unit 13 may further predict the physical condition change of the passenger based on the additional information. Specifically, the prediction unit 13 predicts whether or not there is a possibility that the passenger may get sick.

"Prediction process 6"
The prediction process 6 is a process obtained by improving the prediction processes 1 and 2 described in the first embodiment and the prediction processes 3 to 5 described in the second embodiment. In the prediction process 6, a plurality of “conditions causing car sickness” may be prepared according to a task performed while the passenger is moving. And the prediction part 13 may predict a passenger's physical condition change based on the "condition which causes car sickness" corresponding to the task which a passenger performs during a movement.

  For example, the condition that causes car sickness is “the time during which acceleration equal to or higher than a reference value continues for a reference time (eg, 10 minutes) at a time interval shorter than the first time (eg, 3 minutes)” In some cases, the first time may be longer as the task corresponds to a task that is likely to cause physical deterioration. Moreover, the reference value of acceleration may be smaller as the task corresponds to a task that is likely to cause physical deterioration. In addition, the reference time may be shorter as the task corresponds to a task that is likely to cause physical deterioration.

  In addition, the condition that causes car sickness is “the time during which the passage of the curvature portion below the reference value continues at a time interval shorter than the first time (eg, 3 minutes) continues for the reference time (eg, 10 minutes) or longer. If “Yes”, the first time may be shorter as the task corresponds to a task that is less likely to cause physical deterioration. Further, the reference value of the curvature may be larger as the task corresponds to a task that is less likely to cause physical deterioration. The reference time may be longer as the task corresponds to a task that is likely to cause physical deterioration.

  The schedule generation unit 14 generates a recommended schedule based on the prediction of the passenger's physical condition predicted by the prediction unit 13 (predicted in the prediction process 6) and information indicating the task performed by the passenger while moving. Generate. For example, the schedule generation unit 14 indicates that the task is performed at a location or time zone where there is no possibility of causing physical condition deterioration (eg, car sickness), and resting is performed at a location or time zone where the physical condition may be deteriorated. A recommended schedule may be generated.

  Moreover, the schedule production | generation part 14 may produce | generate a recommendation schedule in the following flows.

  First, when the task indicated by the task information acquired by the acquisition unit 11 is a task that increases the possibility that the physical condition deteriorates, the prediction unit 13 predicts a change in physical condition when the task is performed by the above method. . And the schedule production | generation part 14 can ensure desired time in the time slot | zone estimated that there is no possibility that physical condition will deteriorate (example: car sickness) as a result of the prediction by the prediction part 13, and most An early time zone is determined as a recommended time zone for performing the task. In addition, when the desired time cannot be secured in the time zone predicted that the physical condition is not likely to deteriorate, all the time zones that are predicted not to cause car sickness and the possibility of car sickness A part of the predicted time zone may be determined as a recommended time zone for performing the task. In addition, if the desired time cannot be secured in the time zone that is predicted not to deteriorate, the recommended time to perform the task in all the time zones that are predicted not to cause car sickness You may decide as a belt.

  Thereafter, the schedule generation unit 14 determines a recommended action for the remaining time zone. For example, the schedule generation unit 14 may determine an action that is unlikely to cause car sickness, such as a break, as an action recommended in the remaining time zone. In addition, the schedule generation unit 14 may determine a task that is unlikely to cause car sickness, such as sleep, appreciation of music, or enjoying scenery, as an action recommended for the remaining time zone.

  In addition, the recommended behavior may be determined in the remaining time zone as follows. First, the prediction unit 13 executes a task indicated by the task information during a time period determined to perform the task indicated by the task information, and predicts a change in physical condition when another task is performed during the remaining time period. May be. The prediction unit 13 may repeat the prediction process while changing the task to be performed in the remaining time period until it is predicted that the physical condition is not likely to deteriorate in the remaining time period. Then, when the prediction unit 13 predicts that there is no possibility that the physical condition will deteriorate in the remaining time zone, the schedule generation unit 14 may determine the task as a task to be performed in the remaining time zone. .

  Note that the candidate for the task to be performed in the remaining time period may be a task performed by a passenger detected by a sensor or the like during the past movement. And the prediction part 13 may select in order from a task with high possibility of performing at that time in the candidate of a task, and may repeat the said prediction process. The possibility of performing each task at that time may be predicted based on, for example, environmental information such as the month, day of the week, time zone, weather, and temperature. That is, it is possible to collect environmental information when each task has been performed in the past, obtain a correlation between the value of the environmental information and the task to be performed, and make a prediction based on the correlation and the environmental information at that time.

  The output unit 12 outputs the recommended schedule generated by the schedule generation unit 14 as notification information. In the recommended schedule, a time zone in which the task indicated by the task information is recommended to be executed, a task recommended to be executed in the remaining time zone, and the like are indicated. In addition to the recommended schedule, the output unit 12 may further output the prediction of the passenger's physical condition change generated by the prediction unit 13.

  Note that after the output of the recommended schedule by the output unit 12, the output device 10 may accept editing of the recommended schedule by the user. The editing of the recommended schedule includes, for example, changing the content of the task or shifting the time. Further, based on this editing result, the prediction of changes in physical condition with respect to the edited schedule may be recalculated and output.

  FIG. 11 schematically shows an example of information output by the output unit 12. The illustrated information includes a map, and a route R from the departure point (eg, current point) A of the moving object to the destination B is shown on the map. In addition, a place P where the passenger is likely to deteriorate in physical condition (eg car sickness) is highlighted. Furthermore, it shows a guideline for the time to reach the entrance of the place P where the passenger is likely to deteriorate in physical condition (eg, get sick) and the time to reach the exit of the place P. .

  The recommended schedule is shown above the map. Specifically, it is shown that task X (eg, reading) is performed for the first 15 minutes, and rest is performed for the subsequent 13 minutes.

  According to the output device 10 of the present embodiment described above, it is possible to realize the same operational effects as those of the first and second embodiments. Further, according to the output device 10 of the present embodiment, the passenger can grasp an appropriate response for preventing deterioration of his / her physical condition based on the notification information output from the output device 10.

<Fourth Embodiment>
The output device 10 of the present embodiment is different from the first to third embodiments in that the system of the moving body is controlled based on the prediction of the physical condition change of the passenger. According to this embodiment, the moving body side can be controlled so that the passenger does not cause a target failure. The combination of the control on the moving body side and the control of the behavior of the passenger can more effectively reduce and prevent the deterioration of the physical condition of the passenger.

  An example of the hardware configuration of the output device 10 is the same as in the first to third embodiments.

  An example of a functional block diagram of the output device 10 is shown in FIG. As illustrated, the output device 10 includes an acquisition unit 11, an output unit 12, a prediction unit 13, a schedule generation unit 14, and a control unit 15.

  The configurations of the acquisition unit 11, the output unit 12, the prediction unit 13, and the schedule generation unit 14 are the same as those in the first to third embodiments.

  The control unit 15 controls the system of the moving body based on the prediction of the physical condition change of the passenger. The control unit 15 includes at least one of moving image control means, sound control means, temperature control means, and ventilation control means.

  The moving image control means controls the operation of the moving image display device based on the prediction of the physical condition change of the passenger. The moving image control means permits moving image display in places and time zones where the passenger is not likely to experience physical condition deterioration (eg, car sickness). That is, when there is an input for displaying a moving image during the time period, the moving image is displayed on the display according to the input. On the other hand, the moving image control means does not permit the moving image display in a place or time zone where the passenger may cause physical condition deterioration (eg, car sickness). That is, even if there is an input for displaying a moving image during the time period, the moving image is not displayed on the display.

  The voice control means controls the operation of the voice output device based on the prediction of the physical condition change of the passenger. The moving image control means may play music having a relaxing effect in a place or a time zone where the passenger may cause physical condition deterioration (eg, car sickness).

  The temperature control means controls at least one of the air conditioning equipment and the power window based on the prediction of the physical condition change of the passenger. The temperature control means controls at least one of the air conditioning equipment and the power window so that the temperature inside the vehicle is below a reference value in a place or time zone where the passenger may experience physical condition deterioration (eg car sickness). May be.

  The ventilation control means controls at least one of the ventilation facility and the power window based on the prediction of the physical condition change of the passenger. The ventilation control means may perform at least one of control for operating the ventilation facility and control for opening the window in a time zone or a place where the physical condition may be deteriorated.

  According to the output device 10 of the present embodiment described above, the same operational effects as those of the first to third embodiments can be realized. Moreover, according to the output device 10 of the present embodiment, the moving body side can be controlled so that the passenger does not deteriorate in physical condition. The combination of the control on the moving body side and the control of the behavior of the passenger can more effectively reduce and prevent the deterioration of the physical condition of the passenger.

  As mentioned above, although embodiment and the Example were described with reference to drawings, these are illustrations of this invention and can also employ | adopt various structures other than the above.

1A processor 2A memory 3A I / O I / F
4A Peripheral circuit 5A Bus 10 Output device 11 Acquisition unit 12 Output unit 13 Prediction unit 14 Schedule generation unit 15 Control unit

Claims (20)

An acquisition unit that acquires route information indicating a route of the moving object and feature information indicating a feature of the route;
An output unit that outputs notification information based on prediction of a physical condition change of a passenger of the moving body on the route obtained by the route information and the feature information;
An output device comprising: The output device according to claim 1,
The output unit outputs the prediction result as the notification information. The output device according to claim 1 or 2,
An output device further comprising prediction means for predicting a physical condition change of the occupant based on the route information and the feature information. The output device according to claim 3,
The output means further predicts a change in physical condition of the passenger based on information indicating the physical condition of the passenger on the day. The output device according to claim 3 or 4,
The prediction means is an output device that further predicts a physical condition change of the passenger based on traffic jam information of the route. The output device according to any one of claims 3 to 5,
The prediction means is an output device that further predicts a change in physical condition of the passenger based on the seat position of the passenger. The output device according to any one of claims 3 to 6,
The prediction means is an output device that further predicts a change in physical condition of the passenger based on the age of the passenger. The output device according to any one of claims 3 to 7,
The prediction means is an output device that predicts a change in physical condition of each of the plurality of passengers. The output device according to any one of claims 1 to 8,
The output unit is an output device that re-predicts a change in the physical condition of the occupant at a predetermined timing while moving along the route. The output device according to any one of claims 1 to 9,
The said output part is an output device which outputs the recommended schedule which shows the said passenger's recommended action produced | generated based on the said passenger's physical condition change prediction as said alerting | reporting information. The output device according to claim 10,
An output device further comprising schedule generation means for generating the recommended schedule based on prediction of the physical condition change of the passenger and information indicating a task performed while the passenger is moving. The output device according to claim 11.
In the recommended schedule, a time zone for performing the task and a time zone for resting, or a location for performing the task and a location for resting are defined. The output device according to any one of claims 1 to 12,
An output device further comprising moving image control means for controlling the operation of the moving image display device based on the prediction of the physical condition change of the passenger. The output device according to any one of claims 1 to 13,
An output device further comprising voice control means for controlling the operation of the voice output device based on the prediction of the physical condition change of the passenger. The output device according to any one of claims 1 to 14,
An output device further comprising temperature control means for controlling at least one of the air conditioning equipment and the power window based on the prediction of the physical condition change of the passenger. The output device according to claim 15,
The temperature control means is an output device that controls at least one of the air conditioning equipment and the power window so that the temperature inside the vehicle is equal to or lower than a reference value in a time zone or a place where there is a possibility of deterioration of physical condition. The output device according to any one of claims 1 to 15,
An output device further comprising ventilation control means for controlling at least one of a ventilation facility and a power window based on the prediction of the physical condition change of the passenger. The output device according to claim 17.
The said ventilation control means is an output device which performs at least one of the control which operates ventilation equipment, and the control which opens a window in the time slot | zone or location which may cause physical condition deterioration. Computer
An acquisition step of acquiring route information indicating a route of the moving object and feature information indicating a feature of the route;
An output step of outputting notification information based on a prediction of a physical condition change of a passenger of the moving body on the route obtained by the route information and the feature information;
Output method to execute. Computer
Acquisition means for acquiring route information indicating a route of the moving object and feature information indicating a feature of the route;
An output means for outputting notification information based on a prediction of a physical condition change of a passenger of the moving object on the route obtained by the route information and the feature information;
Program to function as.

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