Information processing equipment, vehicle, vehicle control procedure and program

Abstract

An information processing device (3) according to the present disclosure comprises a detection unit (31) which determines the sleep depth of a user riding in a vehicle (1) using sensor information acquired from a sensor (2) which acquires at least one of a state of the user or the environment around the user, and a control information generation unit (32) which generates control information to be used to control a journey of the vehicle (1) by means of automatic driving, using the sleep depth determined by the detection unit (31).

Description

Area

[0001] The present disclosure relates to an information processing device that controls a vehicle, a vehicle, a vehicle control procedure and a program. background

[0002] A passenger in a vehicle occasionally falls asleep during the ride. Patent 1 describes a technique that prevents the sleep of a passenger in a series hybrid vehicle from being disturbed. The vehicle described in Patent 1 can generate electrical energy using an electric motor and switches off the generation of electrical energy before and after the passenger falls asleep. Thus, the vehicle described in Patent 1 prevents the occurrence of vibration and noise disturbances caused by the generation of electrical energy before and after the passenger falls asleep, during which the sleep could be disturbed by these vibrations and noise. Reference list of patent literature

[0003] Patent literature 1: Japanese patent application, publication number 2019-131109 Summary of the technical problem

[0004] The technology described in patent literature 1 prevents the occurrence of vibration and noise disturbances due to the generation of electrical energy before and after an occupant falls asleep. However, sleep-disrupting events are not limited to vibration and noise disturbances caused by electrical energy generation. The vehicle's movement itself can affect a user who is an occupant. Therefore, it is desirable to conduct the journey in a manner appropriate to the user's sleep state.

[0005] The present disclosure was realized in light of the above considerations. One objective of the present disclosure is to provide an information processing device capable of controlling the driving of a vehicle based on a state related to the sleep of the user. Solution to the problem

[0006] To overcome the problem described above and to solve the task, an information processing device according to the present disclosure comprises: a detection unit for determining the sleep depth of a user riding in a vehicle using sensor information acquired from a sensor to detect at least one state of the user or of an environment around the user; and a control information generation unit for generating control information to be used to control a journey of the vehicle by means of automatic driving, using the sleep depth determined by the detection unit. Advantageous effects of the invention

[0007] The information processing device according to the present disclosure makes it possible to achieve an effect of being able to perform vehicle control according to a state relating to the sleep of the user. Brief description of the drawings Fig. Figure 1 is a representation illustrating an exemplary configuration of a vehicle according to a first embodiment. Fig. Figure 2 is a representation illustrating another exemplary configuration of the first embodiment. Fig. Figure 3 is a representation illustrating an exemplary configuration of the processing circuit implementing an information processing device of the first embodiment. Fig. Figure 4 is a flowchart illustrating an example of a processing flow in an information processing facility of a second embodiment. Fig. Figure 5 is a conceptual representation illustrating an example of a route determination in the second embodiment. Fig. Figure 6 is a representation illustrating an exemplary configuration for a vehicle of the second embodiment in the case where a user setting is received. Fig. Figure 7 is a flowchart illustrating an example of a processing flow in the information processing unit of the second embodiment in the case where a user setting is received. Fig. Figure 8 is a flowchart illustrating an example of a processing flow in an information processing facility of a third embodiment. Fig. Figure 9 is a representation illustrating an exemplary configuration for a vehicle of the third embodiment, which controls devices in the vehicle that influence the environment around a user. Fig. Figure 10 is a flowchart illustrating an example of a processing flow in an information processing facility of a fourth embodiment. Fig. Figure 11 is a representation illustrating an exemplary configuration of a vehicle of the fourth embodiment that determines a wake-up time using sleep information. Fig. Figure 12 is a flowchart illustrating an example of a processing flow in the information processing unit of the fourth embodiment, which predicts a wake-up time using sleep information. Fig. Figure 13 is a representation illustrating an exemplary configuration of a vehicle according to a fifth embodiment. Fig. Figure 14 is a representation illustrating an exemplary configuration for a detection unit of the fifth embodiment in a case where detection is carried out using machine learning. Fig. Figure 15 is a schematic representation illustrating an example of a neural network. Description of embodiments

[0008] The following section describes in detail an information processing device, a vehicle, a vehicle control procedure and a program according to the embodiments with reference to the drawings. First embodiment.

[0009] Fig. Figure 1 is a representation illustrating an exemplary configuration of a vehicle according to a first embodiment. A vehicle 1 of the present embodiment is a self-driving vehicle and comprises a sensor 2, an information processing unit 3, and a driving mechanism 4. An example is described here in which the vehicle 1 is a self-driving vehicle. However, the vehicle 1 may be capable of switching between automatic driving and manual driving, and it may be any vehicle capable of automatic driving.

[0010] Sensor 2 is a detection device that detects at least one aspect of the condition of a user traveling in vehicle 1 or of the environment surrounding the user, and transmits a detection result as sensor information to information processing unit 3. The sensor information is information that indicates at least one aspect of the condition of the user traveling in vehicle 1 or of the environment surrounding the user. Sensor 2 includes, but is not limited to, for example, at least one sensor that detects the user's vital signs, a camera that takes pictures of the user, a sensor that detects sound, an accelerometer attached to the user, an accelerometer that detects the acceleration of vehicle 1, or a sensor attached to vehicle 1.The vital data includes, among other things, at least one of the heart rate, temperature, blood pressure, or respiratory rate, but this is not a limitation. The sensor 2, which acquires the vital data, can be worn by the user, or it can be a non-contact sensor or the like, attached to the vehicle 1, or it can be something other than these. Although in . Fig. While a single sensor 2 is shown in Figure 1, multiple sensors 2 can also be provided. The number of sensors 2 is not limited to the one shown in Figure 1. Fig. The example shown is limited to one.

[0011] The information processing unit 3 comprises a sensor information acquisition unit 30, a detection unit 31, a control information generation unit 32, a driving control unit 33, and an information storage unit 34. The sensor information acquisition unit 30 receives sensor information from sensor 2 to acquire the sensor information and outputs the acquired sensor information to the detection unit 31. The detection unit 31 determines the user's sleep depth using the sensor information received by the sensor information acquisition unit 30, that is, the sensor information acquired from sensor 2. For example, the detection unit 31 uses the sensor information to determine whether the user is awake or asleep, and if the user is asleep, determines the user's sleep depth and communicates the determined sleep depth to the control information generation unit 32.

[0012] Sleep depth is an index that indicates the depth of sleep and can be specified, for example, in two stages: REM sleep, which is light sleep, and non-REM sleep, which is deeper sleep than REM sleep. Alternatively, it can be specified in a total of four or five stages by further subdividing non-REM sleep into three or four stages. Generally, REM and non-REM sleep alternate. Repeated cycles of REM and non-REM sleep are also called sleep cycles. A sleep cycle lasts approximately 90 to 120 minutes. REM sleep is a stage of sleep in which sleep is light and rapid eye movements occur. During REM sleep, breathing and heart rate are faster, and blood pressure and other vital signs are higher than in non-REM sleep. Non-REM sleep is deeper sleep than REM sleep.As described above, non-REM sleep is also classified into three or four stages, depending on sleep depth. For example, if non-REM sleep is classified into four stages, from the first stage, in which non-REM sleep is lightest, to the fourth stage, in which non-REM sleep is deepest, then the sleep of a person who has fallen asleep generally progresses through the sequence of first, second, third, and fourth stages of non-REM sleep, leading to deeper stages. REM sleep occurs after the fourth stage of non-REM sleep. Afterward, REM and non-REM sleep cycles repeat. However, in the second half of sleep, non-REM sleep increases in the lighter stages—that is, in the first and second stages—and REM sleep also increases.

[0013] Investigation Unit 31 can, for example, determine whether the sleep depth is REM sleep or one of the four or three stages of non-REM sleep using, for example, a sleep parameter that is at least one of the vital signs, an index indicating body movement, or the like. Examples of the index indicating body movement include, but are not limited to, the number of times the body rolls to the side, the number of times a specific point moves by a certain amount or more, and the like. The index indicating body movement is detected, for example, by a camera that takes images of the user, an accelerometer attached to the user, a sensor attached to the vehicle 1 (such as an accelerometer or a pressure sensor), or the like, but this is not a limitation.For example, the correlation between sleep depth and the numerical range of the sleep parameter is recorded in a tabular format as reference information. The detection unit 31 determines the sleep depth using the sensor information and the reference information. Alternatively, the relationship between the sleep parameter and sleep depth can also be learned through machine learning. The detection unit 31 can determine the sleep depth using the learning results and the acquired sleep parameter. Furthermore, the detection unit 31 can determine the sleep depth based on the characteristics of the changes between REM sleep and the four or three stages of non-REM sleep in a person's typical sleep pattern described above (for example, a standard pattern of repetitions of REM sleep and the four or three stages of non-REM sleep from sleep onset to wake-up).

[0014] The third and fourth stages of non-REM sleep are generally deep sleep. During deep sleep, sleep is insensitive to external stimuli such as noise, vibration, and light. Even if external stimuli occur, sleep is unlikely to be disturbed, and the sleep-wake cycle is less affected by these stimuli. In contrast, the first and second stages of non-REM sleep are light sleep, which is more sensitive to external stimuli than deep sleep. Events such as sleep disruption by external stimuli and disruption of the sleep-wake cycle are likely. Although REM sleep can be described as light sleep from which one can easily awaken, it is a state that is insensitive to external stimuli. Therefore, REM sleep can be adjusted or defined as light or deep sleep as needed, depending on the desired sleep depth.The definitions of deep sleep and light sleep are not limited to this example and can be determined as needed according to the use of sleep depth.

[0015] The sensor information displaying the environment around the user does not directly reveal the user's state, but it can be used to determine whether the immediate surroundings are suitable for sleeping. For example, the detection unit 31 can use the sensor information displaying the environment around the user to determine whether the environment is unsuitable for sleeping and can use this result to determine the depth of sleep. For example, assume that, as described below, sleep-related driving modes, such as a sleep-promoting mode and a mode in which the user is awake, are activated, and that acceleration is limited in the sleep-promoting mode.In this case, the detection unit 31 can determine that the sleep-promoting mode is set by using the sensor information acquired from sensor 2, which is an accelerometer, to detect the acceleration of vehicle 1, and can thus indirectly determine a state relating to the sleep of the user.

[0016] The information storage unit 34 stores map information and route information. The map information can be two-dimensional, three-dimensional, or a dynamic map that also contains dynamic information. For example, when the dynamic information of the dynamic map is received from a communication unit (not shown), the dynamic information stored in the information storage unit 34 is updated with the received dynamic information. The route information specifies a route or path of vehicle 1 and can include the time required to reach a destination (or an estimated time of arrival), an estimated time of arrival at an intermediate stop, and the like.

[0017] Using the sleep depth determined by the detection unit 31, the control information generation unit 32 generates control information for controlling the journey of vehicle 1 by means of automatic driving and outputs this control information to the journey control unit 33. The journey control of vehicle 1 is the control of the journey of vehicle 1 itself and includes, for example, setting a route, controlling the speed of vehicle 1, controlling the acceleration of vehicle 1, controlling driving behavior, controlling the stopping of vehicle 1, and the like. For example, the control information generation unit 32 can use the sleep depth determined by the detection unit 31 to determine whether the user is in deep sleep or not and generate control information to reduce external stimuli if the sleep is not deep.

[0018] One method for reducing external stimuli includes, but is not limited to, at least one of the following: selecting a route with fewer external stimuli, avoiding rapid acceleration and deceleration, limiting speed, driving gently, or the like. Furthermore, the detection unit 31 can, for example, determine the sleep depth for a given time period by utilizing the determined sleep depth, that is, by predicting the sleep depth for a given time period, and notify the control information generation unit 32 of the result of the sleep depth determination for the given time period. In this case, the control information generation unit 32 can define a route that allows the user to wake up as naturally as possible at the point where the user should wake up, by utilizing the sleep depth for the given time period.The given time span is a time span in the future, for example, a time span from the current time. The point at which the user is to wake up can be the user's destination or a place where the user is to make a stop along the way.

[0019] The control information generation unit 32 can switch between driving modes (hereinafter also referred to as driving modes) based on the depth of sleep for a given period of time. For example, the control information generation unit 32 can switch the driving mode to a normal driving mode without special restrictions if the user is awake and not asleep; to a restricted driving mode with limitations imposed to achieve a smoother ride if the user is light sleep; and to the normal driving mode if the user is deep sleep. A smooth ride is one in which external stimuli acting on the user are reduced. The definitions and method of switching driving modes are not limited to this example.In the case where the control information generation unit 32 generates control information about the route, the control information generation unit 32 can also use the map information stored in the information storage unit 34 to generate the control information.

[0020] In addition to the control information for driving, the control information generation unit 32 can generate control information for controlling equipment (not shown) in the vehicle 1. For example, the control information generation unit 32 can control equipment such as a seat, lighting adjustment devices, a sound or noise-generating device (such as music or ambient noise), and a massage device located on a seat in the vehicle 1, according to the depth of sleep. For example, in a case where sleep is light, the control information generation unit 32 can perform a control to gently tilt the seat to promote sleep, or it can perform a control to reduce the volume of the noise-generating device.In cases where the time required to reach the destination is long before the user falls asleep, the control information generation unit 32 can perform a control action to promote sleep. For example, the control information generation unit 32 can operate the massage device or play relaxing music to encourage sleep. To further promote sleep, the control information generation unit 32 can also set the driving mode described above to the restricted driving mode.

[0021] Whether or not sleep-inducing measures are implemented can be set by the user. Furthermore, the control information generation unit 32 can, for example, set a user-desired wake-up time, determine the time of sleep onset by calculating backwards from the set wake-up time so that the user is in REM sleep or non-REM sleep with light sleep at the wake-up time, and begin sleep-inducing measures before the specified time so that the user can easily fall asleep at or near the specified time. Alternatively, the control information generation unit 32 can set the wake-up time to an expected arrival time at the destination, determine the time of sleep onset so that the user can easily wake up near the destination, and implement measures to similarly promote sleep onset.

[0022] The driving control unit 33 controls the movement of the vehicle 1 by means of automatic driving. The driving control unit 33 performs driving control of the vehicle 1 by controlling the driving mechanism 4 based on information acquired from a sensor (not shown), such as a camera, a light detection and ranging (LiDAR) system, or a millimeter-wave sensor that detects obstacles, the map information stored in the information storage unit 34, and the vehicle's own position calculated by a self-positioning device (not shown). For example, if a destination is specified by the user or another operator, the driving control unit 33 uses the destination and map information to determine a route to the specified destination and controls the driving mechanism 4 to travel along the specified route.The driving control unit 33 stores route information, which specifies the determined route, in the information storage unit 34. The driving control unit 33 can also calculate the time required to reach the destination (or an estimated time of arrival) and an estimated time of arrival at an intermediate stop, and include this information in the route data. The driving control unit 33 can determine the route based on dynamic road and traffic information such as congestion and obstacle information. Driving control in automated driving can be performed using any method, and a typical method may be used, which is why it will not be described in detail here.

[0023] Upon receiving control information from the control information generation unit 32, the drive control unit 33 controls the drive mechanism 4 based on the received control information. An example is described here in which the drive control unit 33 defines a route. Alternatively, the control information generation unit 32 can define a route and communicate the defined route to the drive control unit 33 as control information, and the drive control unit 33 can then control the drive mechanism 4 according to the route based on the control information.

[0024] The driving mechanism 4 is a mechanism that causes the vehicle 1 to drive and includes, for example, a variety of mechanisms that cause the vehicle 1 to drive, including an acceleration operating device such as an accelerator pedal, a steering device and a brake.

[0025] In the present embodiment, the information processing unit 3 determines the user's sleep depth and, based on this determination, generates control information for controlling the vehicle 1's movement. This allows the vehicle 1 to perform drive control according to the user's sleep state. Consequently, the vehicle 1 can adapt the user's environment to the user's sleep depth based on acceleration, deceleration, and driving behavior, as well as the distance the vehicle 1 is to travel. Furthermore, the vehicle 1 can perform control such that the time at which the user is to wake up falls within REM sleep or light sleep / non-REM sleep, thus enabling a natural awakening.

[0026] In the example described above, the information processing unit 3 is housed in vehicle 1. However, an information processing unit can also be provided separately from a vehicle. Fig. Figure 2 is a representation illustrating a further exemplary configuration of the present embodiment. In the Fig. The example shown comprises a vehicle system 100, an information processing unit 3a, and a vehicle 1a. Components which perform the same functions as those in the example shown. Fig. The example shown in point 1 will be represented with the same reference symbols as in Fig. 1 is designated to avoid redundant descriptions. The information processing unit 3a is provided separately from the vehicle 1a. A communication unit 35, which can communicate with the vehicle 1a, is used instead of the one described in Fig. The sensor information acquisition unit 30 of the information processing unit 3 shown in Figure 1 is added. The communication unit 35 receives the sensor information and thus also functions as a sensor information acquisition unit, acquiring the sensor information. The drive control unit 33 in the Fig. The information processing unit 3 shown in Figure 1 is housed in vehicle 1a.

[0027] Vehicle 1a is obtained by removing the information processing unit 3 from the one in Fig. In Figure 1, the vehicle 1 shown is removed and a communication unit 36 ​​is added, which can communicate with the information processing unit 3a. A communication line between the vehicle 1a and the information processing unit 3a includes, for example, a wireless communication line, but can also be a combination of a wireless and a wired communication line. Communication between the vehicle 1a and the information processing unit 3a can take place via another device.

[0028] The communication unit 36 ​​of vehicle 1a receives the sensor information from sensor 2 and sends the received sensor information to the information processing unit 3a. The communication unit 35 of the information processing unit 3a receives the sensor information from vehicle 1a and outputs the received sensor information to the detection unit 31. The operating principles of the detection unit 31 and the control information generation unit 32 are the same as those in the Fig. In the example shown, the control information generation unit 32 outputs the generated control information to the communication unit 35. The communication unit 35 transmits the control information received from the control information generation unit 32 to the vehicle 1a. Upon receiving the control information from the information processing unit 3a, the communication unit 36 ​​of the vehicle 1a outputs the received control information to the driving control unit 33. The driving control unit 33, the information storage unit 34, and the driving mechanism 4 are the same as those in the example shown. Fig. 1 example shown.

[0029] In the case where the control information generation unit 32 generates control information about a route, the information processing unit 3a may also contain the information storage unit 34 and generate the control information using the map information stored in the information storage unit 34.

[0030] Next, the hardware configuration of the information processing device 3 of the present embodiment is described. In the information processing device 3 of the present embodiment, a program (computer program) describing the processing in the information processing device 3 is executed on a computer system, so that the computer system acts as the information processing device 3. The computer system includes, for example, a processing circuit. Fig. Figure 3 is a representation illustrating an exemplary configuration of the processing circuit implementing the information processing unit 3 of the present embodiment. As shown in Fig. As shown in Figure 3, the processing circuit comprises a processor 101, a main memory 102, and a communication unit 103. The processing circuit can be a single circuit or a plurality of circuits. These are connected via a system bus. The communication unit 103 can be provided separately from the processing circuit. The computer system implementing the information processing unit 3 can also include at least one input unit, such as keys or a keyboard for receiving input, or a display unit, such as a display or monitor.

[0031] In Fig. In the present embodiment, the processor 101 is, for example, a control unit, such as a central processing unit (CPU), that executes the program in which the processing in the information processing unit 3 is described. The main memory 102 comprises various memory types, such as random-access memory (RAM) and read-only memory (ROM), as well as a storage device, such as a hard disk, and stores the program to be executed by the processor 101, the necessary data obtained during processing, etc. The main memory 102 is also used as a temporary memory area for the program. The communication unit 103 is a receiver and a transmitter that perform communication processing.

[0032] An example of the operation of the computer system before the program of the present embodiment becomes executable is described here. In the computer system with the configuration described above, the program is installed in the main memory 102, for example, from a compact disc (CD)-ROM or a digital versatile disc (DVD)-ROM inserted into a CD-ROM drive or a DVD-ROM drive (not shown). At the time of program execution, the program read from the main memory 102 is stored in the main memory area of ​​the main memory 102. In this state, the processor 101 performs the processing as the information processing unit 3 of the present embodiment according to the program stored in the main memory 102.

[0033] In the description above, the program that describes the processing in the information processing unit 3 is provided using the CD-ROM or DVD-ROM as the recording medium, but this is not a limitation. For example, the program provided via a transmission medium, such as the Internet, can be used via the communication unit 103, depending on the configuration of the computer system, the size of the provided program, etc.

[0034] The program of the present embodiment, for example, causes a computer system controlling the vehicle 1 to perform a step of determining the sleep depth of a user using sensor information acquired by the sensor 2 and a step of generating control information that is used to control the driving of the vehicle 1 by automatic driving using the determined sleep depth.

[0035] The in Fig. The investigation unit 31 shown, the control information generation unit 32 and the driving control unit 33 are controlled by the unit shown in Figure 1. Fig. 3 shown processor 101 implements the in which in Fig. The program is executed in the 3 displayed memory locations, which contain 102 stored programs. Fig. 3. The 102 GB of RAM shown is also used to store the data in Fig. To implement the investigation unit 31 shown in Figure 1, the control information generation unit 32, and the driving control unit 33. The in Fig. The sensor information acquisition unit 30 shown in Figure 1 is replaced by the one shown in Figure 1. Fig. Communication unit 103, as shown in section 3, is implemented. The communication unit shown in Fig. The information storage unit 34 shown in Figure 1 is part of the system described in Figure 1. Fig. 3 of the displayed working memory 102.

[0036] The in Fig. 2. The information processing facility 3a shown is also a computer system including the one described in Fig. The processing circuit shown in section 3 is implemented. The computer system implementing the information processing device 3a can, in addition to the processing circuit, include at least one input unit or display unit. The information processing device 3a is implemented in section 3. Fig. The communication unit 35 shown in section 2 is formed by the one in Fig. The communication unit 103 shown in section 3 is implemented. The information processing unit 3a can be implemented by a variety of computer systems. The in Fig. The information processing facility 3a shown in Figure 2 can, for example, be implemented through a cloud system. Second embodiment.

[0037] A second embodiment describes an example of the vehicle control system of vehicle 1 with the information processing unit 3 described in the first embodiment. The configuration of vehicle 1 in the present embodiment is the same as that of the first embodiment. As an example, a configuration is described here in which the information processing unit 3 is provided in vehicle 1 as shown in Fig. 1 of the first embodiment is shown. However, the functionality of the present embodiment can also be applied to the one described in Fig. The exemplary configuration of the first embodiment shown in Figure 2 is used. Components that have the same functions as those in the first embodiment are designated with the same reference numerals as those of the first embodiment to avoid redundant descriptions.

[0038] In the present embodiment, the information processing device 3 determines a route to a destination, so that the vehicle 1 arrives in a parking zone, such as a service area (SA), and is parked during a period when a passenger in the vehicle 1 is in a light sleep, and then resumes its journey. Consequently, the information processing device 3 can prevent the occurrence of stimuli that affect the passenger due to the vehicle 1's movement during a light sleep period and promote the passenger's deep sleep.

[0039] Fig. Figure 4 is a flowchart illustrating an example of a processing flow in the information processing unit 3 of the present embodiment. As shown in Fig. As shown in Figure 4, the information processing unit 3 determines whether the user is asleep or not (step S1). In the present embodiment, the sensor information acquisition unit 30, for example, periodically acquires sensor information from sensor 2.

[0040] Specifically, in step S1, the investigation unit 31 uses the sensor information received from the sensor information acquisition unit 30 to determine whether the passenger in vehicle 1 is asleep or not. Sensor 2 is, for example, a camera, and the image data captured by the camera, which records pictures of the passenger, is used to determine whether the passenger is asleep or not. For example, investigation unit 31 can detect the passenger's movement based on the image data, which constitutes the sensor information, and determine whether the passenger is asleep or not based on this movement. Alternatively, it can determine whether the passenger's eyelids are closed or not based on the image data and determine whether the passenger is asleep or not based on this determination.Alternatively, a user-worn accelerometer can be used as Sensor 2, and the Investigation Unit 31 can determine whether the user is asleep or not based on the sensor information obtained from the accelerometer. Alternatively, a sensor that acquires vital data can be used as Sensor 2, and the Investigation Unit 31 can determine whether the user is asleep or not based on the sensor information, i.e., the vital data. Alternatively, the Investigation Unit 31 can determine whether the user is asleep or not using a combination of the image data and the vital data. A method for determining whether the user is asleep or not is not limited to these examples.

[0041] If the user is not asleep (No in step S1), step S1 is repeated. If the user is asleep (Yes in step S1), the information processing unit 3 determines the sleep depth until the destination is reached (step S2). Specifically, the determination unit 31 extracts the distance to the destination and the time required to reach the destination from the route information stored in the information storage unit 34, determines the sleep depth at each point in time from the current time until the time of arrival at the destination using the extracted information, and outputs the determined sleep depth to the control information generation unit 32. The distance to the destination and the time required to reach the destination are calculated, for example, by the driving control unit 33 and stored in the information storage unit 34 as route information, as described in the first embodiment.Alternatively, as described in the first embodiment, the control information generation unit 32 can define a route using the destination and map information and determine the required time. In this case, the control information generation unit 32 stores route information in the information storage unit 34. Here, an example is described in which the determination unit 31 determines the sleep depth until the destination is reached, although this is not a limitation. The determination unit 31 only needs to determine the sleep depth for a given upcoming time interval. As described above, the given time interval can be the time required to reach the destination, a time shorter than the time required to reach the destination (such as half the time required), or a predetermined time interval.

[0042] Next, the information processing unit 3 determines a route to reach a parking zone during a light sleep period (step S3). Specifically, the control information generation unit 32 determines a period during which the user's sleep is predicted to be light, using the sleep depth until reaching the destination determined by the detection unit 31. It then determines the route for vehicle 1 so that it arrives at a parking zone within the specified period and generates control information indicating the determined route. This control information can be output to the driving control unit 33 or stored as route information in the information storage unit 34.

[0043] For example, the tax information generation unit 32 first calculates the position of vehicle 1 during a light sleep period using the distance to the destination and the sleep depth obtained from the determination unit 31 until the destination is reached. If there is a parking zone near the calculated position, the tax information generation unit 32 determines a route so that vehicle 1 arrives at the parking zone and remains parked there for the duration of that period. The parking zone includes at least one parking area (PA) or a parking area (SA). The parking zone can be a rest area, such as a service station, or it can include a parking lot where parking is permitted. The parking lot can be the parking lot of a business, a park, or the like.If a parking zone exists on a previously defined route, the control information generation unit 32 can determine the driving speed so that vehicle 1 reaches the parking zone during the light sleep period and can also output the determined driving speed as control information to the driving control unit 33. If there is no parking zone on a previously defined route, the control information generation unit 32 selects a parking zone from among the parking zones around the route where vehicle 1 will arrive during the light sleep period and defines a route that passes through the parking zone. That is, the control information generation unit 32 updates the route information stored in the information storage unit 34 to route information (control information) that specifies the route that passes through the parking zone.Alternatively, the control information generation unit 32 can output the route information, which specifies the route passing through the parking zone, as control information to the drive control unit 33. The control information generation unit 32 generates control information for parking vehicle 1 in the parking zone and outputs this information to the drive control unit 33. An instruction to park vehicle 1 in the parking zone can be included in the route information. Consequently, the drive control unit 33 controls the movement of vehicle 1 based on the updated route information. When vehicle 1 arrives in the parking zone, the drive control unit 33 controls the drive mechanism 4 to park vehicle 1 in the parking zone.

[0044] In cases where a predetermined number or more periods of light sleep are expected to occur before arrival at the destination, and where driving is expected to resume after parking in a parking zone for a given period, the control information generation unit (CIG) 32 can determine parking zones that correspond one-to-one to two or more of the light sleep periods and define a route that passes through these two or more parking zones. For example, in a case where the time required to reach the destination is seven hours or more, four or five sleep cycles will occur. However, since the sleep cycles in the second half of the journey are for preparation for waking up, the CIG 32 can define a route that passes through two parking zones to promote deep sleep in the sleep cycles up to the second cycle in the first half of the journey.

[0045] Subsequently, the information processing unit 3 determines whether vehicle 1 has arrived in the parking zone or not (step S4). In particular, the control information generation unit 32 can determine that vehicle 1 has arrived in the parking zone if the control information generation unit 32 receives a notification from the driving control unit 33 that vehicle 1 has been parked in the parking zone, or it can determine that vehicle 1 has arrived in the parking zone if the control information generation unit 32 acquires the current position of vehicle 1 from the driving control unit 33 and the current position is within the parking zone.

[0046] If vehicle 1 has not arrived in the parking zone (No in step S4), step S4 is repeated. If vehicle 1 has arrived in the parking zone (Yes in step S4), the information processing unit 3 determines the sleep depth (step S5). Specifically, the control information generation unit 32 instructs the determination unit 31 to determine the sleep depth, and the determination unit 31 determines the user's current sleep depth based on the sensor information and outputs the determination result to the control information generation unit 32.

[0047] The information processing unit 3 determines whether the sleep is deep or not (step S6). In particular, the control information generation unit 32 determines, based on the investigation result received from the investigation unit 31, whether the user's sleep is deep or not.

[0048] If the sleep is not deep (No in step S6), processing is repeated from step S5. If the sleep is deep (Yes in step S6), the information processing unit 3 resumes the journey (step S7). Specifically, the control information generation unit 32 generates control information indicating the resumption of the journey and outputs this control information to the journey control unit 33. The journey control unit 33 controls the journey mechanism 4 to resume the journey of the vehicle 1 based on the control information received from the control information generation unit 32.As described above, the control information generation unit 32, which has determined that the user's sleep is deep after the vehicle 1 has arrived in the parking zone, uses the result of the sleep depth determination, which was determined by the determination unit 31 based on the sensor information, to generate control information indicating that the vehicle 1 is caused to leave the parking zone and resume its journey.

[0049] After the journey resumes, the information processing unit 3 determines whether parking is necessary or not (step S8). Specifically, if vehicle 1 has already been parked in all parking zones to be traversed along the route specified by the route information, the control information generation unit 32 determines that parking is unnecessary. Even if there is one parking zone among all the parking zones to be traversed along the route specified by the route information where vehicle 1 has not yet been parked, the control information generation unit 32 may, in step S8, determine that parking is unnecessary, even if there is a parking zone where vehicle 1 has not yet been parked, if the journey is expected to take longer than originally planned and the arrival at the destination will be delayed by a predetermined time or more.

[0050] If parking is not determined to be unnecessary (No in step S8), the processing is repeated from step S4. If parking is not necessary (Yes in step S8), the information processing unit 3 causes the vehicle 1 to travel to the destination (step S9). Specifically, in step S9, if the vehicle 1 has already parked in all the parking zones to be traversed, the driving mechanism 4 controls the vehicle 1 to travel to the destination based on the route information.In the event that there is a parking zone where vehicle 1 has not yet parked, but the information processing unit 3 determines in step S8 that parking is not necessary, the control information generation unit 32 in step S9 defines a route that does not pass through one or more of the remaining parking zones that vehicle 1 is scheduled to pass through (one or more parking zones that vehicle 1 has not yet arrived in). That is, the control information generation unit 32 updates the route information stored in the information storage unit 34 to reflect that the route does not pass through the remaining parking zone(s). Consequently, the journey control unit 33 controls vehicle 1's journey based on the updated route information control unit to cause vehicle 1 to travel to its destination.

[0051] In the Fig. In the example shown in Figure 4, the information processing unit 3 causes vehicle 1, which is parked in a parking zone, to resume its journey after the user has fallen into a deep sleep, although this is not a limitation. The information processing unit 3 can cause vehicle 1, which has been parked in a parking zone for a predetermined period of time, to resume its journey. Alternatively, the information processing unit 3 can cause vehicle 1 to resume its journey if at least one of the conditions—that the user falls into a deep sleep or that vehicle 1 has been parked in a parking zone for a predetermined period of time—is met.

[0052] Fig. Figure 5 is a conceptual representation illustrating an example of a route definition in the present embodiment. In the Fig. In example 5, a route 201 is defined from a departure point to a destination. It is assumed that the user fell asleep at a point 202 on route 201 after vehicle 1 left the departure point. In the example shown in Fig. In the example shown in Figure 5, the information processing unit 3 predicts the user's sleep depth, determines that the user's sleep will be light during a period (or duration) in which the vehicle 1 travels in section 203, and sets the route 201 so that it passes through SA 301 and SA 302. A section 204 is a section corresponding to a period in which the user is in deep sleep. Thus, the vehicle 1 is parked in parking zones, such as SAs 301 and 302, at times when the user is in light sleep, making it possible to avoid stimuli affecting the user due to the vehicle 1's movement, thereby promoting the user's deep sleep. It should be noted that Fig. 5 is an example and the specified route and number of parking zones do not apply to the one in Fig. The five examples shown are limited. The parking zones are not exclusively SAs, but also PAs, as described above, or parking spaces in shops, parks, and the like.

[0053] In the example described above, the user's deep sleep is promoted by parking vehicle 1 in the parking zones. However, it is conceivable that the user might want to get out of vehicle 1 in a parking zone to use the restroom or to shop. Therefore, it may be possible for the user to specify whether deep sleep should be promoted or whether the user should wake up in a parking zone.

[0054] Fig. Figure 6 is a representation illustrating an exemplary configuration for a vehicle of the present embodiment in the case where a user setting is received. The in Fig. Vehicle 1b, as depicted in section 6, is identical to the one shown in Fig. 1. Vehicle 1 as shown, except that a wake-up promotion device 5 has been added and an information processing device 3b has been provided instead of the information processing device 3. Components which have the same functions as those in the Fig. The example shown in point 1 will be represented with the same reference symbols as in Fig. 1 is used to avoid redundant descriptions.

[0055] As in Fig. As shown in Figure 6, the information processing unit 3b is the one described in Figure 6. Fig. Figure 1 shows an information processing unit 3 to which an input receiving unit 37 has been added. The input receiving unit 37 receives input from the user indicating whether or not the user intends to exit the vehicle 1 in a parking zone. The input receiving unit 37 outputs the received selection result to the control information generation unit 32. If the selection result indicates that the user will exit the vehicle 1 in the parking zone, the control information generation unit 32 sets the operating mode in the parking zone to "wake-up promotion." When the operating mode in the parking zone is set to "wake-up promotion," the control information generation unit 32 generates control information indicating the user's awakening upon the vehicle 1's arrival in the parking zone and outputs this control information to the wake-up promotion unit 5.Upon receiving control information from the control information generation unit 32, the wake-up promotion unit 5 performs an operation to promote the awakening of the user. This operation to promote the awakening of the user could, for example, be an operation that generates a sound, such as a voice, an alarm, or music, to announce arrival in the parking zone; an operation that vibrates the seat; or something else. In the case where the selection result indicates that the user will not exit vehicle 1 in the parking zone, the control information generation unit 32 sets the operating mode in the parking zone to sleep promotion and does not perform any control to awaken the user, even if vehicle 1 arrives in the parking zone, as in the example shown. Fig. 4 examples shown.

[0056] Fig. Figure 7 is a flowchart that provides an example of a processing flow in the information processing unit 3b of the present embodiment in the case where a user setting is received. Steps S1 to S4 are identical to those in the figure shown in Fig. 4. If yes, the information processing unit 3b determines in step S4 whether wake-up promotion is set or not (step S11). Specifically, the control information generation unit 32 determines whether the operating mode in the parking zone is wake-up promotion or not. If wake-up promotion is not set (no in step S11), steps S5 to S9 are carried out as in Fig. 4 executed.

[0057] If wake-up promotion is enabled (Yes in step S11), the information processing unit 3b promotes user wake-up (step S12). Specifically, the control information generation unit 32 generates control information indicating user wake-up and outputs the generated control information to the wake-up promotion unit 5. Upon receiving the control information from the control information generation unit 32, the wake-up promotion unit 5 executes the process to promote user wake-up.

[0058] Next, the information processing unit 3b determines whether a departure instruction exists, that is, an instruction to vehicle 1b to depart (step S13). If a departure instruction exists (Yes in step S13), the information processing unit 3b causes the process to continue with step S7. If no departure instruction exists (No in step S13), the information processing unit 3b repeats step S13. The instruction to vehicle 1b to depart is, for example, entered by the user. When an input of an instruction to vehicle 1b to depart is received from the user, the input receiving unit 37 outputs information indicating that an instruction to vehicle 1b to depart has been given to the control information generation unit 32.In step S13, the control information generation unit 32 determines whether a departure instruction exists or not, based on whether information indicating that a departure instruction has been given to vehicle 1b has been received by the input receiving unit 37 or not.

[0059] In the Fig. In example 7, if the operating mode is set to sleep promotion, the same processing will occur as in Fig. 4. If the operating mode is set to wake-up promotion, the user's awakening will be promoted when vehicle 1b arrives in the parking zone. Even if the user's awakening is promoted in the parking zone, the user will naturally awaken slightly, as the route is set so that vehicle 1b arrives in the parking zone during the light sleep period. In the Fig. In the example shown in Figure 7, the information processing unit 3b can operate according to the user's requirements, since the user can set the operating mode. The input receiving unit 37 and the wake-up promotion unit 5 can be used in the example shown in Figure 7. Fig. 2 of the first embodiment shown, vehicle 1a is added, and the information received by the input receiving unit 37 can be transmitted via the communication unit 36 ​​to the information processing unit 3a, so that the information processing unit 3a can perform the same process as in Fig. The process shown in section 7 is carried out.

[0060] In the Fig. 6 and Fig. In the example shown, vehicle 1b contains the wake-up aid 5, but the wake-up aid 5 may also be absent from vehicle 1b. If vehicle 1b arrives in a parking zone during the light sleep period, the user can sense the arrival and wake up naturally. Therefore, after arrival in a parking zone, the information processing unit 3b can wait for a given period of time until the user has exited vehicle 1b. If the user does not wake up even after the given period of time has elapsed, the information processing unit 3b can perform an operation if the operating mode is set to sleep promotion.

[0061] The in Fig. The information processing unit 3b shown in Figure 6 is, for example, provided by the unit shown in Figure 6. Fig. The 3 shown processing circuit and an input unit (not shown) are implemented. The input / receiver unit 37 is implemented by the input unit.

[0062] As described above, in the present embodiment, the route of vehicle 1 or 1b is set such that the vehicle 1 or 1b arrives at a parking zone during a light sleep period, and the vehicle 1 or 1b, having arrived at the parking zone, is stopped there. Consequently, the vehicle 1 or 1b can prevent sleep from being disturbed by stimuli due to the vehicle 1 or 1b moving during a light sleep period and promote the user's deep sleep. That is, it is possible to control the vehicle's movement according to the user's sleep state. Third embodiment.

[0063] Like the second embodiment, the third embodiment also describes an example of the vehicle control system for vehicle 1 with the information processing unit 3 described in the first embodiment. The configuration of vehicle 1 in the present embodiment is the same as that of the first embodiment. As an example, a configuration is described here in which the information processing unit 3 is provided in vehicle 1 as shown in Fig. 1 of the first embodiment is shown. However, the functionality of the present embodiment can also be applied to the one described in Fig. The exemplary configuration of the first embodiment shown in Figure 2 is used. Components that have the same functions as those in the first embodiment are designated with the same reference numerals as those of the first embodiment to avoid redundant descriptions.

[0064] Fig. Figure 8 is a flowchart illustrating an example of a processing flow in the information processing unit 3 of the present embodiment. As shown in Fig. As shown in Figure 8, the information processing unit 3 determines whether the user is asleep or not, as in step S1 of the second embodiment. In the present embodiment as well, the sensor information acquisition unit 30 acquires the sensor information, for example, periodically from the sensor 2.

[0065] If the user is not asleep (No in step S1), the information processing unit 3 decides to set the vehicle 1's driving mode to normal driving (step S21), and step S1 is repeated. For example, as described in the first embodiment, the user can set two types of driving modes for the vehicle 1: normal driving mode and restricted driving mode. The control information generation unit 32 sets the driving mode to normal driving mode. If the driving mode is already set to normal driving mode, it does not need to be changed. The control information generation unit 32 sets the driving mode to normal driving mode without any changes.

[0066] If the user is asleep (Yes in step S1), the information processing unit 3 determines the sleep depth (step S22). Specifically, the determination unit 31 determines the user's current sleep depth based on sensor information and outputs the result to the control information generation unit 32. Alternatively, the determination unit 31 can predict the sleep depth for a given upcoming time period using the current sleep depth and also output the prediction to the control information generation unit 32.

[0067] The information processing unit 3 determines whether the sleep is light or not (step S23). Specifically, the control information generation unit 32 determines, based on the determination result received from the detection unit 31, whether the user's sleep is light or not. If the sleep is light (yes in step S23), the information processing unit 3 decides to set the vehicle 1's driving mode to restricted driving (step S24) and repeats the processing from step S22. Specifically, in step S24, the control information generation unit 32 generates control information to make the vehicle 1's driving smoother than during normal, unrestricted driving. For example, the control information generation unit 32 sets the driving mode to restricted driving mode. If the driving mode is already set to restricted driving mode, it does not need to be changed.The control information generation unit 32 generates control information indicating that the driving mode has been set to the restricted driving mode without any changes and outputs the generated control information to the driving control unit 33. In restricted driving mode, as described in the first embodiment, driving control is performed to achieve a smoother ride.

[0068] Specifically, in restricted driving mode, a restriction can be imposed by setting at least one speed or acceleration value less than or equal to a threshold, or the route can be set to a route that allows for smoother driving. Examples of a route that allows for smoother driving include, but are not limited to, a route with fewer sharp curves, a route with fewer road surface irregularities, and a route with a gentler gradient. For example, it is assumed that numerical values ​​for curve curvature, road surface irregularities, and road gradients are included in the map information.The control information generation unit 32 can classify a curve whose curvature is greater than or equal to a threshold as a sharp curve, a section with a numerical value indicating the unevenness of the road surface that is less than or equal to a threshold as a section with low unevenness, and a section with a numerical value indicating the gradient of the road that is less than or equal to a threshold as a section with a low gradient. As described above, the control information generation unit 32 can obtain the predicted sleep depth value for the upcoming given time period from the determination unit 31. In this case, the control information generation unit 32 sets the driving mode to restricted driving mode during a period in which the sleep in the prediction result is light.

[0069] If sleep is not light (No in step S23), the information processing unit 3 decides to set the vehicle 1's driving mode to normal driving (step S25) and repeats the processing from step S22. Specifically, in step S25, the control information generation unit 32 sets the driving mode to normal driving mode. If the driving mode is already set to normal driving mode, it does not need to be changed. The control information generation unit 32 sets the driving mode to normal driving mode without any modification.

[0070] By carrying out the in Fig. In the process described in Figure 8, the information processing unit 3 can perform a control that enables a smoother ride during periods of light sleep for the user. That is, it is possible to control the ride according to the user's sleep state. In the example described above, vehicle 1 is instructed to ride smoothly during periods of light sleep to avoid disturbing the user's sleep. Furthermore, during these periods of light sleep, external stimuli acting on the user that are not related to the ride itself can be reduced. For example, adjusting at least one of the ambient brightness or noise levels in the user's immediate surroundings can reduce these external stimuli.In step S24 described above, the control information generation unit 32 can, for example, define a route that avoids well-lit areas or a route that avoids noisy areas. The route that avoids well-lit areas could, for example, be a route that avoids areas with many shops when vehicle 1 is traveling at night, but it is not limited to this. The route that avoids noisy areas could, for example, be a route that avoids areas around construction sites or a route with many people or cars, but this is not a restriction.

[0071] The control information generation unit 32 can control devices in the vehicle 1 that influence the user's immediate surroundings in order to reduce external stimuli acting on the user. Fig. Figure 9 is a representation illustrating an exemplary configuration for a vehicle of the present embodiment, which controls devices in a vehicle 1c that affect the user's immediate surroundings. The in Fig. 9 Vehicle 1c shown is vehicle 1 of the first embodiment, to which a loudspeaker 11, a noise reduction device 12 and a light reduction device 13 have been added.

[0072] The loudspeaker 11 outputs audio data from an audio output device (not shown) as a tone or noise. The audio output device is, for example, a device that plays music or the like in the vehicle 1c, a device that acquires transmitted or distributed audio data, or the like. The noise reduction device 12 is a device that reduces noise in the vehicle 1c and may be a combination of a noise-absorbing foil and a device that controls the extension and retraction of the noise-absorbing foil, or a device that performs noise suppression by detecting noise in the vehicle 1c and generating a noise with a phase opposite to that of the detected noise in order to suppress the noise through electrical processing, or it may be something other than these.The light reduction device 13 is a device that reduces light in the vehicle 1c and may, for example, consist of light control films which can adjust the light transmission and are attached to windows in the rear part of the vehicle 1c or the like, or of curtains or the like which block light while the vehicle 1c is parked, or may also be something other than these.

[0073] In the Fig. The example shown in section 9 generates the tax information generation unit 32 in the section shown. Fig. In step S24, as shown in Figure 8, the control information generation unit 32 further generates control information for the operation of the loudspeaker 11, the noise reduction device 12, and the light reduction device 13, and outputs the generated control information to the loudspeaker 11, the noise reduction device 12, and the light reduction device 13, thereby reducing noise and light in the vehicle 1. For example, the control information generation unit 32 generates control information to reduce the volume of the loudspeaker 11 or to turn off the loudspeaker 11, generates control information to cause the noise reduction device 12 to reduce noise in the vehicle 1, and generates control information to cause the light reduction device 13 to reduce light in the vehicle 1.In this way, the occurrence of stimuli not only attributable to the journey itself, but also of stimuli originating from the immediate environment and unrelated to the journey, which affect the user, can be prevented. In the [reference to]... Fig. The example shown in Figure 9 describes an example in which the vehicle 1c includes the loudspeaker 11, the noise reduction device 12, and the light reduction device 13, but this does not represent a limitation. The vehicle 1c can contain one or two loudspeakers 11, the noise reduction device 12, and the light reduction device 13.

[0074] The loudspeaker 11, the noise reduction device 12 and the light reduction device 13 can be added to the one described in Fig. 2 of the first embodiment shown, the vehicle 1a may be added. The information processing unit 3a can generate control information for controlling these devices and transmit the control information to the vehicle 1a via the communication unit 35. In this case as well, the vehicle 1a may contain one or two loudspeakers 11, the noise reduction device 12, and the light reduction device 13.

[0075] The information processing unit 3 can perform both the operation of the second embodiment and the operation described in the present embodiment. The vehicle 1a and the information processing unit 3a, shown in Fig. 2, can perform both the operation of the second embodiment and the operation described in the present embodiment.

[0076] This describes an example of the reduction of stimuli caused by both the journey and the environment surrounding the user. However, vehicle 1c can only reduce stimuli emanating from the environment around the user if the user is a light sleeper. Fourth embodiment.

[0077] Like the second and third embodiments, a fourth embodiment also describes an example of the vehicle control system of vehicle 1 with the information processing unit 3 described in the first embodiment. The configuration of vehicle 1 in the present embodiment is the same as that of the first embodiment. As an example, a configuration is described here in which the information processing unit 3 is provided in vehicle 1 as shown in Fig. 1 of the first embodiment is shown. However, the functionality of the present embodiment can also be applied to the one described in Fig. The exemplary configuration of the first embodiment shown in Figure 2 is used. Components that have the same functions as those in the first embodiment are designated with the same reference numerals as those of the first embodiment to avoid redundant descriptions.

[0078] Fig. Figure 10 is a flowchart illustrating an example of a processing flow in the information processing unit 3 of the present embodiment. Steps S1 and S2 are the same as steps S1 and S2 in the second embodiment. After step S2, the information processing unit 3 predicts a wake-up time (step S31). Specifically, the detection unit 31 predicts the user's wake-up time based on the determined sleep depth. For example, the detection unit 31 predicts the wake-up time by using the sleep depth determination result and a standard human sleep pattern, as described in the first embodiment, and outputs the prediction result to the control information generation unit 32.Specifically, the investigation unit 31 determines, for example, the sleep onset time and the sleep cycle, calculates, based on the sleep depth determination result, a time span in which REM sleep will occur within a given time span including an expected arrival time at the destination, and sets a time within the calculated time span as an expected awakening time. For example, the control information generation unit 32 can set the time in the middle of the time span during which REM sleep occurs as the expected awakening time.

[0079] Next, the information processing unit 3 determines a route to reach the destination within a given time interval from the predicted wake-up time (step S32). Specifically, the control information generation unit 32 determines a route to the destination of vehicle 1 such that vehicle 1 arrives at the destination within a given time interval from the wake-up time predicted in step S31, generates route information, which is control information specifying the determined route, and stores the route information in the information storage unit 34. Alternatively, the control information generation unit 32 can output the control information specifying the determined route to the driving control unit 33. By driving based on the route information, vehicle 1 can arrive at the destination within the given time interval from the predicted wake-up time.This can increase the likelihood that the user will wake up naturally near their destination. Thus, the present embodiment also enables driving control based on the user's sleep state.

[0080] In the example described above, the wake-up time is predicted based on sleep depth, but this is not a limitation. The wake-up time can be set by the user or determined based on sleep information, which includes at least one of the following: a user's sleep history, a user's wake-up time history, or a user's scheduled wake-up time, as described below.

[0081] Fig. Figure 11 is a representation illustrating an exemplary configuration of a vehicle of the present embodiment, which determines a wake-up time using sleep information. As shown in Fig. As shown in Figure 11, a vehicle 1d comprises an information processing unit 3d instead of the information processing unit 3. The information processing unit 3d is the information processing unit 3 to which a sleep information acquisition unit 38 has been added. The sleep information acquisition unit 38 receives sleep information from an information provisioning unit 6, which stores the user's sleep information in order to acquire the sleep information, and outputs the acquired sleep information to the investigation unit 31. Fig. Figure 11 shows an example where the information provisioning device 6 is a mobile device, such as a smartphone, tablet, or personal computer, carried by the user, and the information provisioning device 6 is located in the vehicle 1d. However, the information provisioning device 6 can also be located outside the vehicle 1d. The information provisioning device 6 is not limited to a mobile device carried by the user, but can also be a server or similar device that manages the sleep information of a large number of users.

[0082] Sleep information includes, for example, information managed by a sleep app (application software) that acquires and manages information about the user's sleep, but this is not a limitation. For instance, the Information Delivery Device 6 may have an alarm function, and a wake-up time set in the alarm function can be used as sleep information. Similarly, if the Information Delivery Device 6 has a schedule management function and the user has registered a wake-up time in a schedule, the registered wake-up time can be used as sleep information.

[0083] The sleep information managed by the sleep app includes, for example, the user's sleep onset time, wake-up time, and sleep cycle. For predicting wake-up time, the detection unit 31 can, for example, use the sleep information managed by the sleep app to calculate the mean wake-up time based on a history of the user's wake-up times and use this calculated mean as the predicted wake-up time. Alternatively, the detection unit 31 can calculate the mean sleep time based on a history of sleep onset and wake-up times, determine the user's sleep onset time using sensor information, and use the time elapsed since the determined sleep onset time as the predicted wake-up time.

[0084] If the sleep information is the wake-up time set in the alarm function, the investigation unit 31 can use the wake-up time specified by the sleep information as the predicted wake-up time. If the sleep information is the wake-up time registered in the schedule, the investigation unit 31 can use the wake-up time specified by the sleep information as the predicted wake-up time. If a schedule has been registered for a day on which the wake-up time is to be predicted, a wake-up time in the schedule for that day can be used as the predicted wake-up time.In the event that a schedule for a day on which the wake-up time is to be predicted has not been registered, a registered wake-up time on another day of the same day of the week can be used as the predicted value of the wake-up time, or the most frequently registered wake-up time among the registered wake-up times can be used as the predicted value of the wake-up time.

[0085] The in Fig. The 3D information processing unit shown in Figure 11 is, for example, the one in Fig. The processing circuit shown in Figure 3 is implemented. The sleep information acquisition unit 38 is implemented by the communication unit 103.

[0086] Fig. Figure 12 is a flowchart illustrating an example of a processing flow in the information processing unit 3d of the present embodiment, which predicts a wake-up time using the sleep information. Step S1 is the same as that in Figure 12. Fig. 10. If yes in step S1, the information processing unit 3d predicts the wake-up time based on the sleep information (step S41). Specifically, the determination unit 31 predicts the user's wake-up time using the sleep information received from the sleep information acquisition unit 38 and outputs the prediction result to the control information generation unit 32. Step S32 is the same as the one in the Fig. 10 examples shown.

[0087] The sleep information acquisition unit 38 can be attached to the vehicle 1a or the information processing unit 3a, as shown in Fig. 2 of the first embodiment. The information processing device 3a can, as in the present embodiment, predict the user's wake-up time based on the sleep information and determine a route to reach the destination within the given time span from the predicted wake-up time.

[0088] The information processing device 3d can perform at least one of the functions of the second embodiment or the third embodiment and the functions described in the present embodiment. The vehicle 1a and the in Fig. 2. The information processing device 3a shown can perform at least one of the functions of the second embodiment or the functions of the third embodiment.

[0089] As described above, in the present embodiment the wake-up time is predicted, and the route is determined such that the vehicle 1d arrives at the destination within the given time interval from the predicted wake-up time. This can increase the probability that the user wakes up naturally near their destination, thereby increasing user comfort. Fifth embodiment.

[0090] Fig. Figure 13 is a representation illustrating an exemplary configuration of a vehicle 1e according to a fifth embodiment. The vehicle 1e of the present embodiment is the same as the vehicle 1 of the first embodiment, except that it includes an information processing unit 3e instead of the information processing unit 3. Components having the same functions as those in the first embodiment are designated with the same reference numerals as those of the first embodiment to avoid redundant descriptions.

[0091] As in Fig. Figure 13 shows that the information processing unit 3e is the information processing unit 3 of the first embodiment, to which an identification unit 39 and a characteristic information storage unit 40 have been added. As an example, a configuration is described here in which the information processing unit 3e is provided in the vehicle 1e, as shown in Fig. Figure 1 of the first embodiment is shown. In the exemplary configuration shown in Fig. However, as shown in Figure 2 of the first embodiment, the identification unit 39 and the characteristic information storage unit 40 can be added to the information processing device 3a, and the operation of the present embodiment can be carried out.

[0092] In the present embodiment, the sensor 2 comprises, for example, a camera, and the sensor information includes image data acquired from the camera as it captures images of the user. The sensor information acquisition unit 30 outputs the image data to the identification unit 39. The identification unit 39 identifies the user based on the image data and outputs the identification result (user identification result) to the detection unit 31. User identification can involve the identification of an individual user or the identification of an attribute of the user. The attribute includes, for example, at least one such attribute, such as gender or age, but is not limited to these.

[0093] User identification is achieved, for example, through facial recognition technology. In the case where the identification unit 39 identifies the individual user, image data displaying a picture of the user's face has been pre-registered, and the identification unit 39 compares the registered image data with the captured image data to identify the individual user. The age need not be the age itself, but can be specified by a category such as infants, children, or adults, or by a category such as an age group like under 10, 10, or 20 years. The age categories are not limited to these examples. In the Fig. In the example shown in Figure 13, the identification unit 39 identifies the user based on the image data, but can also identify the user based on the vital data acquired as sensor information or identify the user based on a combination of the image data and the vital data.

[0094] The Characteristic Information Acquisition Unit 40 stores characteristic information that indicates a sleep-related characteristic of each user or attribute. The characteristic information includes at least one of the following: the user's sleep cycle, sleep duration, or wake-up time; vital signs characteristics at each sleep depth; body movement characteristics at each sleep depth; vital signs body movement characteristics during sleep and wake-up; and the like. This information is used in the investigation by the Investigation Unit 31.The characteristic information can be in tabular format, storing data for each element for each user, or it can be a learned model developed through machine learning, as described below. If the characteristic information is in tabular form, it is calculated, for example, through statistical processing of data pre-collected for each user or attribute. Alternatively, the characteristic information can be calculated based on sensor information acquired by sensor 2 when the user previously rode in vehicle 1e.

[0095] The investigation unit 31 determines a sleep-related index using the identification result obtained from the identification unit 39 and the characteristic information stored in the characteristic information storage unit 40. The sleep-related index can be sleep depth, wake-up time, the classification of whether the user is asleep or not, or two or more of these. That is to say, in the Fig. 4, Fig. 7, Fig. 8, Fig. 10 or Fig. As described in step S1, the determination unit 31 can use the identification result received from the identification unit 39 and the characteristic information stored in the characteristic information storage unit 40 to determine whether the user is asleep or not. In determining whether the user is asleep or not, at least one piece of information, such as the characteristics of vital data, body movement during sleep and wakefulness, or similar information, is used as the characteristic information.

[0096] When determining sleep depth in Fig. 4, Fig. 7, Fig. 8 or Fig. 10. The detection unit 31 can determine the sleep depth using the identification result received from the identification unit 39 and the characteristic information stored in the characteristic information storage unit 40. For example, when determining the user's sleep depth, at least one of the following is used as the characteristic information: information indicating the user's sleep cycle, vital signs characteristics at each sleep depth, user body movement characteristics at each sleep depth, or the like. In the determination of wake-up time described in the fourth embodiment, the detection unit 31 can determine the sleep depth using the identification result received from the identification unit 39 and the characteristic information stored in the characteristic information storage unit 40.When determining the user's wake-up time, at least one piece of information, such as sleep time, wake-up time, or similar, is used as the characteristic information. In this case, the characteristic information could be the current value of the user's wake-up time or sleep time.

[0097] As described above, the characteristic information may be a learned model. Fig. Figure 14 is a representation showing an exemplary configuration of the detection unit 31 of the present embodiment in the case where the detection is carried out using machine learning. In the Fig. In the example shown in Figure 14, the investigation unit 31 comprises a learning unit 311 and an inference unit 312. For example, the learning unit 311 generates a learned model through supervised learning, using a variety of datasets, each containing input data (the features) and the sleep-related index (the corresponding response data), and stores the generated learned model in the characteristic information storage unit 40 as the characteristic information. Features include, for example, information calculated from the sensor data.

[0098] In the case where the learned model is a model for inferring the classification of whether the user is asleep or not, the input data includes, for example, at least one piece of information specifying the characteristics of vital signs, body movement during sleep and wakefulness, and the like. In the case where the learned model is a model for inferring sleep depth, the input data includes, for example, at least one piece of information indicating the user's sleep cycle, the characteristics of vital signs at each sleep depth, the characteristics of the user's body movement at each sleep depth, and the like.The input data can be data calculated from data acquired by Sensor 2 in the past, data calculated from data acquired by a device other than Sensor 2, or a mixture of both. The input data can be data acquired from a sleep app or similar device. The response data can be acquired, for example, by separately acquiring and using brainwaves, or it can be determined based on the result of a stimulus applied to the user, or it can be determined by a different method.

[0099] Any algorithm can be used as the supervised learning algorithm employed to generate the learned model in Learning Unit 311. For example, a neural network model can be used. A neural network consists of an input layer made up of a large number of neurons, an intermediate layer (hidden layer) made up of a large number of neurons, and an output layer made up of a large number of neurons. The intermediate layer can consist of one, two, or more layers.

[0100] Fig. Figure 15 is a schematic representation illustrating an example of a neural network. For example, in a three-layer neural network, as in Fig. As shown in Figure 15, multiple inputs are fed into an input layer (X1 to X3), the values ​​are multiplied by weights W1 (w11 to w16) and fed into an intermediate layer (Y1 and Y2), and the results are further multiplied by weights W2 (w21 to w26) and output by an output layer (Z1 to Z3). The output results depend on the values ​​of weights W1 and weights W2.

[0101] In the present embodiment, the relationship between the features and the response data is learned by adjusting the weights W1 and W2 such that, upon input of the features, the output of the output layer approaches the sleep-related index representing the response data. It should be noted that the machine learning algorithm is not limited to the neural network but could also be another algorithm, such as a support vector machine. The machine learning used to generate the learned model in learning unit 311 is not limited to supervised learning but could also be reinforcement learning or the like.

[0102] The inference unit 312 calculates the features using the sensor information received by the sensor information acquisition unit 30 and inputs the features into the learned model, which is stored in the characteristic information storage unit 40, to infer the sleep-related index. Consequently, the sleep-related index is determined.

[0103] The learned model can be generated for each individual user or attribute. For example, the learned model can be generated for each age group. In the case where the identification result is the identification result of an individual user, the investigation unit 31 infers the sleep-related index by using the learned model corresponding to that individual user. In the case where the identification result is the identification result of a user attribute, the investigation unit 31 infers the sleep-related index by using the learned model corresponding to that attribute. Alternatively, instead of generating the learned model for each individual user or attribute, the learned model can also be generated by inputting the identification information or attributes of an individual user as features.At the time of inference, the identification information or attributes of the individual user can also be entered as features into the learned model.

[0104] Fig. Figure 14 shows an example where the investigation unit 31 contains the learning unit 311, but this does not represent a restriction. A learning device that generates a learned model can be provided separately from the vehicle 1e. The learning device can generate a learned model, and the learned model generated by the learning device can be stored in the characteristic information storage unit 40.

[0105] The in Fig. The information processing unit 3e shown in Figure 13 is, for example, the one described in Figure 13. Fig. The processing circuit shown in section 3 is implemented. Fig. The identification unit 39 shown in 13 is from the one in Fig. 3 shown processor 101 implements a processor located in the Fig. The program stored in memory 102 is executed in the 3 displayed memory locations. Fig. The 3 shown memory module 102 is also used to implement the functionality shown in Fig. The identification unit 39 shown in 13 is used. Fig. The characteristic information storage unit 40 shown in Figure 13 is part of the unit shown in Fig. 3 of the displayed working memory 102.

[0106] The functionality of the present embodiment is applicable for determining the sleep-related index in one of the first to fourth embodiments or a combination of two or more of the first to fourth embodiments.

[0107] As described above, in the present embodiment the individual user or user attribute is identified, and the sleep-related index, such as the classification of whether the user is asleep or not, sleep depth, or wake-up time, is determined based on the identification result. This can provide the same effects as in the first embodiment and increase the accuracy of the determination of the sleep-related index.

[0108] The configurations described in the above embodiments are an example and can be combined with other known techniques. The embodiments can be combined with one another. The configurations can be partially omitted or modified without deviating from the core concept. Reference symbol list

[0109] 1, 1a, 1b, 1c, 1d, 1e Vehicle; 2 Sensor; 3, 3a, 3b, 3d, 3e Information processing unit; 4 Driving mechanism; 5 Wake-up promotion unit; 6 Information provision unit; 11 Loudspeaker; 12 Noise reduction unit; 13 Light reduction unit; 30 Sensor information acquisition unit; 31 Detection unit; 32 Control information generation unit; 33 Driving control unit; 34 Information storage unit; 35, 36 Communication unit; 37 Input receiving unit; 38 Sleep information acquisition unit; 39 Identification unit; 40 Characteristic information storage unit; 100 Vehicle system; 311 Learning unit; 312 Inference unit. QUOTES INCLUDED IN THE DESCRIPTION

[0000] This list of documents cited by the applicant was automatically generated and is included solely for the reader's convenience. The list is not part of the German patent or utility model application. The DPMA accepts no liability for any errors or omissions. Cited patent literature

[0000] JP 2019-131109

[0003]

Claims

[1] Information processing facility, comprising: an investigative unit to determine the sleep depth of a user traveling in a vehicle using sensor information acquired from a sensor to capture at least one aspect of the user's condition or the environment surrounding the user; and a control information generation unit to generate control information to be used for controlling a vehicle's journey by automatic driving, using the sleep depth determined by the detection unit. [2] Information processing device according to claim 1, wherein the investigation unit determines the sleep depth for an upcoming given period of time, and The control information generation unit determines a period during which the user's sleep is predicted to be light, uses the sleep depth for the upcoming given time period determined by the detection unit, determines a route for the vehicle so that the vehicle arrives in a parking zone within the determined period, and generates the control information indicating the determined route. [3] Information processing device according to claim 2, wherein the control information generation unit generates the control information to park the vehicle in the parking zone and generates the control information indicating that the vehicle is caused to leave the parking zone and resume driving when, after the vehicle has arrived in the parking zone, the control information generation unit determines that the user's sleep is deep, using a result of the sleep depth determination determined by the determination unit based on sensor information. [4] Information processing device according to claim 2 or 3, wherein the parking zone comprises at least one of a service area or a parking area. [5] Information processing device according to any one of claims 1 to 4, wherein the control information generation unit generates the control information to make the journey of the vehicle a smoother journey than in a normal time without restrictions, when the control information generation unit determines that the sleep of the user is light, using the sleep depth determined by the detection unit. [6] Information processing device according to claim 5, wherein the smoother ride includes a ride on a route with less uneven road surfaces. [7] Information processing device according to claim 5 or 6, wherein the smoother ride includes a ride on a route with less sharp curves. [8] Information processing device according to any one of claims 5 to 7, wherein the smoother ride includes a ride in which at least one of the acceleration of the vehicle or the speed of the vehicle is less than or equal to a threshold value. [9] Information processing device according to any one of claims 1 to 8, wherein the control information generation unit actuates a noise reduction device to reduce noise in the vehicle when the control information generation unit determines that the user's sleep is light, using the sleep depth determined by the detection unit. [10] Information processing device according to any one of claims 1 to 9, wherein the control information generation unit actuates a light reduction device to reduce light in the vehicle when the control information generation unit determines that the user's sleep is light, using the sleep depth determined by the detection unit. [11] Information processing device according to any one of claims 1 to 10, wherein The investigation unit predicts the user's wake-up time using the determined sleep depth, and The control information generation unit determines a route for the vehicle so that the vehicle arrives at a destination within a given time period from the wake-up time predicted by the determination unit, and generates the control information that indicates the determined route. [12] Information processing device according to claim 11, comprising: an identification unit to identify the user; and a characteristic information acquisition unit to acquire characteristic information that indicates a sleep-related characteristic of each user, wherein The investigation unit predicts the wake-up time using a result of the identification by the identification unit and the characteristic information. [13] Information processing device according to claim 12, wherein the characteristic information includes a current value of at least one of the wake-up time or sleep time of the user. [14] Information processing device according to any one of claims 1 to 13, comprising: an identification unit to identify the user; and a characteristic information acquisition unit to acquire characteristic information that indicates a sleep-related characteristic of each user, wherein The investigation unit determines the sleep time using a result of the identification by the identification unit and the characteristic information. [15] Information processing device according to any one of claims 1 to 14, comprising: an identification unit to identify a user attribute; and a characteristic information acquisition unit to acquire characteristic information that indicates a sleep-related characteristic of each attribute, wherein The investigation unit determines the sleep depth using the attribute identified by the identification unit and the characteristic information. [16] Information processing device according to claim 14 or 15, wherein the characteristic information is a learned model generated by supervised learning using a plurality of data sets, each of which contains features calculated using the sensor information and sleep depth, which are corresponding response data. [17] Vehicle capable of driving by means of automatic driving, the vehicle comprising: an investigative unit to determine the sleep depth of a user traveling in a vehicle using sensor information acquired from a sensor to capture at least one aspect of the user's condition or the environment surrounding the user; a control information generation unit to generate control information to be used for controlling a journey of the vehicle, using the sleep depth determined by the detection unit; and a driving control unit to control the vehicle's journey through automatic driving using the control information. [18] Vehicle control procedure in an information processing device for controlling a vehicle capable of driving by automatic driving, the procedure comprising: a step of determining the sleep depth of a passenger in a vehicle using sensor information acquired from a sensor to capture at least one aspect of the passenger's condition or the environment surrounding the passenger; and a step of generating control information to be used to control the vehicle's journey by means of automatic driving, using the determined sleep depth. [19] Program that causes a computer system controlling a vehicle capable of driving automatically to perform: a step of determining the sleep depth of a passenger in a vehicle using sensor information acquired from a sensor to capture at least one aspect of the passenger's condition or the environment surrounding the passenger; and a step of generating control information to be used to control the vehicle's journey by means of automatic driving, using the determined sleep depth.

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