Driving assistance device, vehicle, driving assistance method, and recording medium

Abstract

This driving assistance device is a device that assists driving of a vehicle, and comprises one or more processors, and one or more memories communicably connected to the one or more processors. The one or more processors use the degrees of concentration of a driver of the vehicle during present and past driving to determine a trend in the degree of concentration, and determine details of information to be presented to the driver on the basis of the determined trend in the degree of concentration.

Description

Driving assistance device, vehicle, driving assistance method, and recording medium

[0001] The present disclosure relates to a driving assistance device, a vehicle, a driving assistance method, and a recording medium.

[0002] Techniques are known to encourage drowsy or distracted drivers to take a break.

[0003] For example, Patent Document 1 discloses a system that learns undesirable driving habits of a driver over time as the driver operates the vehicle, identifies one or more situational triggers associated with each learned undesirable driving habit, receives information from one or more vehicle sensors and one or more external sources, predicts when the driver will begin to engage in a particular undesirable driving habit, and implements one or more avoidance strategies to help the driver refrain from engaging in the particular undesirable driving habit, such as transmitting one or more speed recommendations to the driver, suggesting an alternative route to the driver, and presenting the driver with one or more coupons, offers, and discounts at businesses to encourage the driver to take a break by stopping at the business.

[0004] Patent document 2 also discloses an information provision system in which a mobile terminal or an information provision device determines whether the driver needs to rest based on information detected by a fatigue state detection means, and if it is determined that the driver needs to rest, the information provision device selects advertising information related to rest facilities that is associated with a location within a specified range from a point identified by the current location information of the mobile device.

[0005] JP2022-099334A JP11-065434A

[0006] A driver may temporarily lose concentration on driving due to poor physical condition or the like, or may chronically lose concentration on driving due to accumulated fatigue or the like. According to conventional technology, advertising information related to rest facilities is presented to a driver who needs to take a rest, etc. However, this technology does not take into consideration whether the loss of concentration on driving is temporary or chronic, and the information presented to the driver is not necessarily appropriate for improving the driver's concentration on driving.

[0007] In view of the above circumstances, an object of the present disclosure is to provide a technology that can appropriately improve a driver's concentration on driving depending on the driver's state.

[0008] A driving assistance device according to one embodiment of the present disclosure is a driving assistance device that assists in driving a vehicle, and includes one or more processors and one or more memories communicatively connected to the one or more processors, wherein the one or more processors determine a trend in the degree of concentration of the driver of the vehicle based on the current and past degree of concentration on driving, and determine the content of information to be presented to the driver based on the determined trend in the degree of concentration.

[0009] A vehicle according to an embodiment of the present disclosure is a vehicle equipped with the driving assistance device.

[0010] A driving assistance method according to one embodiment of the present disclosure is a driving assistance method that assists in driving a vehicle, and includes a computer determining a trend in the degree of concentration of the driver of the vehicle based on the current and past degree of concentration on driving, and determining content of information to be presented to the driver based on the determined trend in the degree of concentration.

[0011] A non-transitory tangible recording medium having a computer program recorded thereon according to one embodiment of the present disclosure is a non-transitory tangible recording medium having a computer program applied to a driving assistance device that assists in driving a vehicle, and causes a computer to perform the following: determining a trend in the degree of concentration of the driver of the vehicle based on the current and past degree of concentration on driving; and determining the content of information to be presented to the driver based on the determined trend in the degree of concentration.

[0012] According to an embodiment of the present disclosure, the driver's concentration on driving can be appropriately improved depending on the driver's state.

[0013] FIG. 1 is a schematic diagram showing a vehicle equipped with a driving assistance device according to an embodiment of the present disclosure. FIG. 2 is a block diagram showing a configuration example of a driving assistance device according to a first embodiment of the present disclosure. FIG. 3 is a flowchart illustrating a first operation example of the driving assistance device according to the first embodiment of the present disclosure. FIG. 4 is a graph illustrating an example of information representing a change in concentration level over time, generated in the first operation example of the driving assistance device according to the first embodiment of the present disclosure. FIG. 5 is a flowchart illustrating a second operation example of the driving assistance device according to the first embodiment of the present disclosure. FIG. 6 is a graph illustrating an example of information representing a change in concentration level over time, generated in the first operation example of the driving assistance device according to the second embodiment of the present disclosure. FIG. 7 is a flowchart illustrating a second operation example of the driving assistance device according to the second embodiment of the present disclosure.

[0014] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0015] 1. First Embodiment (1-1. Overall Configuration of Vehicle) With reference to FIG. 1, an example of a vehicle 1 equipped with a driving assistance device 20 according to an embodiment of the present disclosure will be described.

[0016] The vehicle 1 is configured as a front-wheel drive four-wheel vehicle in which a driving torque output from a driving force source 2 that generates driving torque for the vehicle 1 is transmitted to the left and right front wheels. The vehicle 1 may be a vehicle equipped with an internal combustion engine such as a gasoline engine or a diesel engine as the driving force source 2. The vehicle 1 may also be an electric vehicle equipped with a driving motor as the driving force source 2. The vehicle 1 may also be a hybrid electric vehicle equipped with both an internal combustion engine and a driving motor as the driving force source 2.

[0017] The combination of drive wheels and the drive method are not limited. For example, vehicle 1 may be a rear-wheel drive vehicle, a four-wheel drive vehicle, or an electric vehicle equipped with drive motors corresponding to each wheel. Furthermore, if vehicle 1 is an electric vehicle or a hybrid electric vehicle, vehicle 1 is equipped with a secondary battery that stores power supplied to the drive motor, and a motor or a generator such as a fuel cell that generates power to charge the battery.

[0018] Vehicle 1 is equipped with the above-mentioned driving force source 2, electric steering device 3, and brake devices 4LF, 4RF, 4LR, and 4RR (hereinafter collectively referred to as "brake device 4" unless a distinction is required) as equipment used to control the operation of vehicle 1.

[0019] The driving force source 2 outputs a driving torque that is transmitted to the front wheel drive shaft 6F via a transmission (not shown) and a differential mechanism 5. The driving of the driving force source 2 and the transmission is controlled by a vehicle control device 10 that includes one or more electronic control units (ECUs: Electronic Control Units).

[0020] The electric steering device 3 is provided on the front wheel drive shaft 6F. The electric steering device 3 includes an electric motor (not shown) and a gear mechanism (not shown), and is controlled by a vehicle control device 10 to adjust the steering angle of the front wheels. The vehicle control device 10 controls the electric steering device 3 based on the steering angle of the steering wheel 7 by the driver. If the vehicle 1 is a vehicle capable of executing automatic driving control, the vehicle control device 10 controls the electric steering device 3 based on the steering angle of the steering wheel 7 by the driver during manual driving. On the other hand, during automatic driving, the vehicle control device 10 controls the electric steering device 3 based on an appropriately set steering angle or steering angular velocity.

[0021] Brake devices 4LF, 4RF, 4LR, and 4RR apply braking force to the respective wheels. The brake devices 4 may be, for example, hydraulic brake devices. In this case, the vehicle control device 10 controls the drive of the hydraulic unit 8 to adjust the hydraulic pressure supplied to each brake device 4. If the vehicle 1 is an electric vehicle or a hybrid electric vehicle, the brake devices 4 are used in combination with regenerative braking using a drive motor.

[0022] The vehicle control device 10 mainly includes one or more electronic control units (ECUs: Electronic Control Units) that control the driving of the driving force source 2, the electric steering device 3, the brake device 4, and the like.

[0023] In addition, the vehicle 1 is equipped with an interior imaging camera 11 , an exterior imaging camera 12 , a vehicle state sensor 13 , a GNSS (Global Navigation Satellite System) sensor 14 , a communication device 15 , and a notification device 16 .

[0024] The in-vehicle image capturing camera 11 captures an image of the head of a driver driving the vehicle 1 from within the vehicle 1, and generates image data. The in-vehicle image capturing camera 11 includes an image capturing element such as a CCD (Charged Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor), and transmits the generated image data to the driving assistance device 20. Note that the in-vehicle image capturing camera 11 may be a camera included in a so-called DMS (Driver Monitor System).

[0025] The exterior image capturing camera 12 may include front image capturing cameras 12LF, 12RF and a rear image capturing camera 12R. The front image capturing cameras 12LF, 12RF capture images of the area in front of the vehicle 1 and generate image data. The rear image capturing camera 12R captures images of the area behind the vehicle 1 and generates image data. The exterior image capturing camera 12 includes an image capturing element such as a CCD (Charged Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor) and transmits the generated image data to the driving assistance device 20. In the vehicle 1 illustrated in FIG. 1 , the front image capturing cameras 12LF, 12RF are configured as stereo cameras including a pair of left and right cameras, but the front image capturing cameras 12LF, 12RF may also be monocular cameras. In addition to the exterior image capturing camera 12, the vehicle 1 may also include one or more ranging sensors selected from a radar sensor such as a LiDAR (Light Detection and Ranging) or a millimeter-wave radar, and an ultrasonic sensor.

[0026] The vehicle state sensor 13 includes at least one sensor that detects the state of the vehicle 1. The vehicle state sensor 13 may include, for example, a steering angle sensor, an accelerator position sensor, a brake stroke sensor, a brake pressure sensor, or an engine rotation speed sensor. The vehicle state sensor 13 may also include, for example, a vehicle speed sensor, an acceleration sensor, or an angular velocity sensor. The vehicle state sensor 13 transmits information indicating the detection result to the driving assistance device 20.

[0027] The GNSS sensor 14 receives satellite signals from positioning satellites such as GPS (Global Positioning System) satellites. The GNSS sensor 14 transmits position information of the vehicle 1 contained in the received satellite signals to the driving assistance device 20. Note that the GNSS sensor 14 may be provided with an antenna, in addition to the GPS sensor, that receives satellite signals from other satellite systems that identify the position of the vehicle 1.

[0028] The communication device 15 includes at least one communication interface. The communication interface may be, for example, an interface compatible with a mobile communication standard such as 4G (4th generation), 5G (5th generation), or LTE (Long Term Evolution), or a LAN (local area network) interface. The vehicle 1 can transmit and receive various information to and from an external server, etc., via the communication device 15.

[0029] The notification device 16 is driven by the driving assistance device 20 and notifies the driver of the vehicle 1 of various information by means of image display, sound output, audio output, or the like. The notification device 16 may include a display provided in the vehicle 1, or may include a speaker or the like provided in the vehicle 1. The notification device 16 may be integrated with a navigation system provided in the vehicle 1. The notification device 16 may also include a HUD (Head Up Display) that displays information on the front window of the vehicle 1.

[0030] (1-2. Driving Assistance Device) The driving assistance device 20 according to this embodiment will be described with reference to FIG.

[0031] (1-2-1. Configuration Example) The driving assistance device 20 functions as a device that assists the driver of the vehicle 1 in driving by executing a computer program by one or more processors such as CPUs (Central Processing Units). The computer program is a computer program that causes the processor to execute operations, described below, that should be performed by the driving assistance device 20. The computer program executed by the processor may be recorded on a recording medium that functions as a storage unit (memory) 22, described below, or may be recorded on a recording medium built into the driving assistance device 20 or any recording medium that can be externally attached to the driving assistance device 20.

[0032] The recording medium for recording a computer program may be a magnetic medium such as a hard disk, a floppy disk, or a magnetic tape; an optical recording medium such as a CD-ROM, a DVD, or a Blu-ray (registered trademark); a magneto-optical medium such as a floptical disk; a memory element such as a RAM or a ROM; a flash memory such as a USB memory or an SSD; or any other medium capable of storing a program.

[0033] The driving assistance device 20 is connected to the vehicle control device 10, the in-vehicle image capturing camera 11, the outside-vehicle image capturing camera 12, the vehicle state sensor 13, the GNSS (Global Navigation Satellite System) sensor 14, the communication device 15, and the notification device 16 via a dedicated line, a controller area network (CAN), a local internet (LIN), or other communication means. Note that an embodiment is also possible in which some or all of the components of the driving assistance device 20 are provided in the vehicle control device 10. Also, an embodiment is also possible in which some or all of the components of the driving assistance device 20 are provided in a server or the like belonging to a cloud computing system or other computing system, and are capable of communicating with the vehicle 1 via any network.

[0034] The driving assistance device 20 includes a processing unit 21 and a storage unit 22 .

[0035] (Processing Unit) The processing unit 21 includes one or more processors such as a CPU and various peripheral components. Part or all of the processing unit 21 may be configured with updatable components such as firmware, or may be a program module or the like that is executed by instructions from the CPU or the like.

[0036] (Storage Unit) The storage unit 22 is configured with one or more storage elements such as RAM or ROM connected to the processing unit 21 so as to be able to communicate with the processing unit 21. However, there is no particular limitation on the type and number of storage units 22. The storage unit 22 stores information such as computer programs executed by the processing unit 21, various parameters used in arithmetic processing, detection data, and arithmetic results.

[0037] (1-2-2. Functional Configuration of Processing Unit) The functional configuration of the processing unit 21 of the driving assistance device 20 will be described. The processing unit 21 includes an acquisition unit 23, a calculation unit 24, a determination unit 25, a storage processing unit 26, and a presentation unit 27. Each of these units is a function realized by execution of a computer program by one or more processors such as a CPU. However, some or all of the acquisition unit 23, the calculation unit 24, the determination unit 25, the storage processing unit 26, and the presentation unit 27 may be configured using analog circuits.

[0038] (Acquisition Unit) The acquisition unit 23 acquires image data including the driver of the vehicle 1 from the in-vehicle image capturing camera 11. The acquisition unit 23 may be configured to be able to acquire information on the current position of the vehicle 1 from the GNSS sensor 14. In addition, the acquisition unit 23 is configured to be able to appropriately acquire information necessary for processing, which will be described later, from the storage unit 22.

[0039] (Calculation unit) The calculation unit 24 calculates the driver's concentration level for current and past driving based on the state of the driver of the vehicle 1. Although details will be described later, the calculation unit 24 uses image data including the driver acquired by the acquisition unit 23 to calculate the driver's concentration level. In addition, the calculation unit 24 is configured to be able to execute calculation processes required for the processes described later.

[0040] (Determination Unit) The determination unit 25 determines the tendency of the driver's concentration level based on the current and past degrees of concentration of the driver of the vehicle 1 on driving calculated by the calculation unit 24. Specifically, the determination unit 25 determines the tendency of the driver's concentration level based on a comparison between the driver's current degree of concentration on driving and the driver's past degrees of concentration on driving. For example, if the frequency of occurrence of a state in which the concentration level is less than a predetermined value is equal to or greater than a predetermined frequency during the target period from the past to the present, the determination unit 25 determines that the tendency of the concentration level is a first tendency. On the other hand, if the frequency of occurrence of a state in which the concentration level is less than the predetermined value is less than the predetermined frequency during the target period from the past to the present, the determination unit 25 determines that the tendency of the concentration level is a second tendency. Note that the target period may include the current trip and one or more past trips, and may be, for example, the most recent week.

[0041] Furthermore, the determination unit 25 determines the content of information to be presented to the driver based on the determined tendency of the driver's concentration level of the vehicle 1. Specifically, when the tendency of the driver's concentration level is a first tendency, the determination unit 25 determines to present to the driver first information for improving the driver's concentration level. On the other hand, when the tendency of the driver's concentration level is a second tendency, the determination unit 25 determines to present to the driver second information, which is different from the first information and is for improving the driver's concentration level.

[0042] The first information may include information encouraging the driver to improve their lifestyle habits. Examples of such information include information about products or services that exhibit delayed effects. Specifically, examples of products that exhibit delayed effects include products or services that enable the driver to recover from fatigue or improve sleep quality over a period of several days to several weeks. More specifically, examples include foods and beverages containing lactic acid bacteria, etc., and products or bedding that contain aromatic components such as aromas. Product information includes product advertising information, but the present disclosure is not limited thereto. Product coupon information may also be included to increase the driver's motivation to take a break. However, in the present disclosure, information encouraging the driver to improve their lifestyle habits is not limited thereto.

[0043] The second information may include information that promotes at least temporary recovery of the driver's physical and mental state. Examples of such information include information about products or services that have an immediate effect. Specifically, examples of products or services that have an immediate effect include products or services that enable the driver to reduce drowsiness or improve concentration by taking a break of several tens of minutes to several hours. More specifically, examples of products or services that have an immediate effect include products containing caffeine, products that have a relaxation effect, or relaxation services such as aromatherapy. Furthermore, examples of the product or service information include advertising information for the product or service, but the present disclosure is not limited thereto. Coupon information for the product or service may also be included to increase the driver's motivation to take a break. However, in the present disclosure, information for improving the driver's concentration is not limited thereto.

[0044] In addition, the determination unit 25 is configured to be able to execute a determination process required for the process described below.

[0045] (Storage Processing Unit) The storage processing unit 26 stores the current and past driving concentration levels of the driver of the vehicle 1 calculated by the calculation unit 24 in the storage unit 22 in association with time information.

[0046] (Presentation Unit) The presentation unit 27 presents the information determined by the determination unit 25 to the driver of the vehicle 1. Specifically, the presentation unit 27 controls the driving of the notification device 16 to present the information determined by the determination unit 25 to the driver by audio output or image or text display.

[0047] The presentation unit 27 is configured to be able to present information to be presented to the driver in the process described below, in addition to the information described above.

[0048] (1-2-3. First Operation Example of Driving Assistance Device) A first operation example of the driving assistance device 20 according to this embodiment will be described with reference to a flowchart in FIG.

[0049] In step S10, the system including the driving assistance device 20 is started up. After that, the process proceeds to step S11.

[0050] In step S11, the calculation unit 24 calculates the state of the driver of the vehicle 1. Specifically, the calculation unit 24 performs publicly known or arbitrary image processing on image data including the driver acquired by the acquisition unit 23 from the in-vehicle image camera 11. As a result, the calculation unit 24 calculates, as the state of the driver, for example, an average value of the eye opening degree, which indicates the degree to which the driver's eyes are open, over a certain period of time. The certain period may be, for example, several seconds to several tens of seconds, but the present disclosure is not limited thereto. However, the index used to calculate the state of the driver in the present disclosure is not limited to the eye opening degree, and any index related to the degree of leeway (amount of attention resources) for processing various information acquired by the driver while driving through vision, hearing, or the like can be used. Examples of such indexes include the amount of displacement of the driver's line of sight or head direction, or the amplitude of head movement. The process then proceeds to step S12.

[0051] In step S12, the calculation unit 24 calculates the driver's concentration level for driving based on the state of the driver of the vehicle 1 acquired in step S11. Specifically, the calculation unit 24 calculates the driver's concentration level according to the average value of the driver's eye opening level over a certain period of time calculated in step S11. In other words, the calculation of the concentration level is performed so that the smaller the average value of the driver's eye opening level, the lower the driver's concentration level. Note that the concentration level may be a continuous value linked to the eye opening level, or may be a discrete value evaluated in multiple stages such as "low," "medium," and "high." The process then proceeds to step S13.

[0052] Here, in steps S11 and S12, the calculation unit 24 may calculate the driver's concentration level on driving using a trained model such as a deep neural network (DNN). Specifically, the storage unit 22 pre-stores a trained model constructed by machine learning using image data including the driver in past driving sessions and the driver's concentration level in past driving sessions as training data, so that the trained model can be referenced by the calculation unit 24. The trained model is then stored in the storage unit 22 in advance, and the calculation unit 24 calculates the driver's concentration level on driving by inputting the image data including the driver acquired in step S11 into the trained model stored in the storage unit 22. That is, when the image data including the driver is input into the trained model, the trained model outputs the driver's concentration level on driving as an estimation result. Note that learning using the trained model does not necessarily have to be performed on the driving assistance device 20 side; it may be performed on an external server side, and only the estimation result may be received by the driving assistance device 20 side.

[0053] In step S13, the storage processing unit 26 associates the degree of concentration on driving of the driver of the vehicle 1 calculated in step S12 with time information and stores the information in the storage unit 22. The time information may be, for example, the start time, end time, or any time between the start time and end time of the certain period in step S11. The process then proceeds to step S14.

[0054] In step S14, the determination unit 25 determines whether the system including the driving assistance device 20 has stopped. If it is determined that the system has stopped (step S14: YES), the process ends. On the other hand, if it is not determined that the system has stopped (step S14: NO), the process returns to step S11.

[0055] As a result, the degree of concentration on driving of the driver of the vehicle 1 is stored in the storage unit 22 as information representing the change in the degree of concentration over time from when the system is started to when it is stopped (hereinafter, may be abbreviated as "information representing the change in the degree of concentration over time"). As an example, information representing a graph such as that shown in FIG. 4 may be stored in the storage unit 22.

[0056] (1-2-4. Second Operation Example of Driving Assistance Device) A second operation example of the driving assistance device 20 according to this embodiment will be described with reference to a flowchart in FIG.

[0057] In step S20, the acquisition unit 23 acquires the driver's concentration level on past driving of the vehicle 1 (hereinafter, sometimes abbreviated as "past concentration level"). Specifically, the acquisition unit 23 refers to the storage unit 22 to acquire information representing the change over time in the driver's past concentration level calculated by the first operation example. As an example, information representing a graph such as that shown in FIG. 4 is acquired. Thereafter, the process proceeds to step S21.

[0058] In step S21, the determination unit 25 determines whether the driver of the vehicle 1 has driven for the target period. Specifically, the determination unit 25 determines whether the driver has driven for the target period based on the information indicating the temporal change in concentration level acquired in step S20. The target period may include the current trip and one or more past trips, and may be, for example, the most recent week. If it is determined that the driver has driven for the target period (step S21: YES), the process proceeds to step S22. On the other hand, if it is not determined that the driver has driven for the target period (step S21: NO), the process ends. However, step S21 is not essential, and the process may always proceed from step S20 to step S22.

[0059] In step S22, similarly to steps S11 and S12 in the first operation example, the calculation unit 24 calculates the current concentration level of the driver of the vehicle 1 on driving (hereinafter sometimes abbreviated as "current concentration level") based on the state of the driver of the vehicle 1. Note that the current concentration level may be overwritten and saved in information representing a graph such as that shown in FIG. 4. Thereafter, the process proceeds to step S23.

[0060] In step S23, the determination unit 25 determines whether or not to determine the trend of the driver's concentration level of the vehicle 1, based on the current concentration level calculated in step S22. Specifically, the determination unit 25 determines that the trend of the driver's concentration level should be determined if the current concentration level calculated in step S22 remains below a predetermined value for a certain period of time or more. If it is determined that the trend of the concentration level should be determined (step S23: YES), the process proceeds to step S24. On the other hand, if it is not determined that the trend of the concentration level should be determined (step S23: NO), the process returns to step S22.

[0061] The predetermined value in step S23 can be set appropriately, and may be, for example, a concentration level that may lead to a state of drowsiness or a state of distraction, which is derived in advance through experiments or simulations.

[0062] In step S24, the judgment unit 25 determines the tendency of the driver's concentration level based on a comparison between the driver's concentration level on current driving of the vehicle 1 calculated in step S23 and the driver's concentration level on past driving of the vehicle 1 obtained in step S20.

[0063] Specifically, the determination unit 25 determines that the concentration level trend is the first trend if the frequency of occurrence of a state in which the concentration level is less than a predetermined value is equal to or greater than a predetermined frequency during the target period from the past to the present. The predetermined frequency is a frequency that can be deemed to be chronic and can be set appropriately. As an example, if a state in which the concentration level is less than a predetermined value has continuously occurred over the past week, the determination unit 25 determines that the concentration level trend is the first trend. The process then proceeds to step S25.

[0064] On the other hand, if the frequency of occurrence of a state in which the concentration level is less than the predetermined value is less than the predetermined frequency during the target period from the past to the present, the determination unit 25 determines that the concentration level trend is the second trend. As an example, if a state in which the concentration level is less than the predetermined value has not continuously occurred over the past week, and the current concentration level is accidentally less than the predetermined value, the determination unit 25 determines that the concentration level trend is the second trend. Then, the process proceeds to step S26.

[0065] In this way, the determination unit 25 determines the tendency of the degree of concentration based on the driver's current and past degrees of concentration on driving.

[0066] However, the present disclosure is not limited to this, and the determination unit 25 may determine that the trend of the concentration level is the first trend if the frequency of occurrence of a state in which the concentration level is less than a predetermined value increases over time during the target period from the past to the present.

[0067] The determination unit 25 may also determine the driver's concentration tendency based on a comparison of the driver's current and past concentration level during driving with the current and past concentration levels of other drivers other than the driver. Specifically, the memory unit 22 pre-stores a trained model constructed by machine learning using training data including the time changes in the other driver's concentration level during driving at a reference time and prior to the reference time, and the other driver's concentration tendency. The training data can be appropriately constructed by monitoring the driving behavior of multiple other drivers through testing, experiments, or the like. The determination unit 25 then inputs the time changes in the driver's concentration level during current and past driving into the trained model stored in the memory unit 22 to determine the driver's concentration tendency. That is, when the time changes in the driver's concentration level during current and past driving are input into the trained model, the trained model outputs the driver's concentration tendency as an estimated result. Learning using the trained model does not necessarily have to be performed on the driving assistance device 20 side; it may be performed on an external server side, and only the estimated result may be received by the driving assistance device 20 side.

[0068] In step S25, the presentation unit 27 presents first information for improving the concentration of the driver of the vehicle 1. Specifically, the presentation unit 27 controls the driving of the notification device 16 to output the first information to the driver as audio or display an image or text. As described above, the first information may include information encouraging the driver to improve their lifestyle habits, such as information about products or services that have a delayed effect. Then, the process ends.

[0069] In step S26, the presentation unit 27 presents second information, which is different from the first information and is intended to improve the concentration of the driver of the vehicle 1. Specifically, the presentation unit 27 controls the driving of the notification device 16 to output the second information to the driver as audio or display an image or text. As described above, the second information may include information intended to improve the driver's concentration, such as information about a product or service that has an immediate effect. The process then ends.

[0070] The presentation unit 27 may present, based on the information on the current location of the vehicle 1, advertising information or coupon information for a store or the like located in a roadside rest area or the like where the driver can stop within a predetermined time after the second information is presented in step S26, for example. The current location of the vehicle 1 can be acquired from the GNSS sensor 14 via the acquisition unit 23. Examples of roadside rest areas include service areas or parking areas along expressways. The store or the like is a facility that can provide the product or service in step S26. At this time, the congestion status of the store or the like at the current time, which is acquired from an external server or the like via the acquisition unit 23, may be taken into consideration. Specifically, the presentation unit 27 may present advertising information or coupon information for a store or the like where the driver can most quickly enjoy a service, based on the information on the current location of the vehicle 1 and the congestion status of the store or the like.

[0071] (Effect) As described above, the processing unit 21 of the driving assistance device 20 according to this embodiment determines the concentration level tendency based on the current and past concentration levels of the driver of the vehicle 1. Then, the processing unit 21 determines the content of information to be presented to the driver based on the determined concentration level tendency.

[0072] With this configuration, not only the current concentration level of the driver but also the past concentration levels of the driver are taken into consideration, and the information required to improve the driver's concentration level is determined according to the tendency of the driver's concentration level. Therefore, the driver's concentration level can be appropriately improved according to the driver's state. As a result, the occurrence of near misses and the like can be reduced.

[0073] 2. Second embodiment A driving assistance device 20 according to a second embodiment of the present disclosure will be described. The following mainly describes the driving assistance device 20 according to this embodiment, focusing on differences from the first embodiment.

[0074] (2-1. Configuration Example of Driving Assistance Device) Unlike the first embodiment, the acquisition unit 23 is configured to be able to acquire information indicating the driving environment of the vehicle 1. Examples of the information indicating the driving environment include information indicating weather conditions such as strong winds, rainfall, or snowfall, but the present disclosure is not limited to this. For example, the information indicating the driving environment may be information indicating an area with poor visibility such as a series of curved roads, or information indicating an area such as in front of a station where crowds are expected. The acquisition unit 23 may acquire the information indicating the driving environment of the vehicle 1 from an external server or the like via the communication device 15. Alternatively, the acquisition unit 23 may acquire the information indicating the driving environment of the vehicle 1 by performing publicly known or arbitrary image processing on image data acquired from the exterior image capture camera 12.

[0075] The storage unit 22 stores in advance information indicating the required concentration levels required in various driving environments so that it can be referenced by the processing unit 21. For example, the required concentration level required in strong winds, rainfall, or snowfall is set higher than that required in fine weather. In addition, the required concentration level required in areas with poor visibility is set higher than that required in areas with good visibility. Note that the required concentration level may be calculated based on statistical values ​​(average values, etc.) of other drivers' current and past driving concentration levels in various driving environments.

[0076] (2-2-1. First Operation Example of Driving Assistance Device) A first operation example of the driving assistance device 20 according to this embodiment will be described with reference to a flowchart in FIG.

[0077] In step S30, the system including the driving assistance device 20 is started up. After that, the process proceeds to step S31.

[0078] In step S31, the acquisition unit 23 acquires information indicating the traveling environment of the vehicle 1. Thereafter, the process proceeds to step S32.

[0079] In step S32, the acquisition unit 23 acquires a required concentration degree required in the driving environment of the vehicle 1 acquired in step S31. Specifically, the acquisition unit 23 acquires a required concentration degree corresponding to the driving environment acquired in step S31 by referring to the storage unit 22. Thereafter, the process proceeds to step S33.

[0080] In step S33, similarly to steps S11 and S12 in the first embodiment, the calculation unit 24 calculates the degree of concentration on the current driving of the driver of the vehicle 1 based on the state of the driver of the vehicle 1. Thereafter, the process proceeds to step S34.

[0081] In step S34, the storage processing unit 26 associates the current concentration level of the driver of the vehicle 1 calculated in step S33 with the required concentration level and time information acquired in step S32, and stores the result in the storage unit 22. Thereafter, the process proceeds to step S35.

[0082] In step S35, the determination unit 25 determines whether the system including the driving assistance device 20 has stopped. If it is determined that the system has stopped (step S35: YES), the process ends. On the other hand, if it is not determined that the system has stopped (step S35: NO), the process returns to step S31.

[0083] As a result, the driver's concentration level on driving of the vehicle 1 is linked to the required concentration level as information representing the change in concentration level over time from when the system is started to when it is stopped (hereinafter, this may be referred to as "information representing the change in concentration level over time"), and is stored in the storage unit 22. As an example, information representing a graph such as that shown in FIG.

[0084] (2-2-2. Second Operation Example of Driving Assistance Device) A second operation example of the driving assistance device 20 according to this embodiment will be described with reference to a flowchart in FIG.

[0085] In step S40, the acquisition unit 23 acquires the driver's concentration level for past driving of the vehicle 1 (hereinafter, sometimes abbreviated as "past concentration level"). Specifically, the acquisition unit 23 acquires information representing the change over time in the driver's past concentration level calculated by the first operation example by referring to the storage unit 22. Note that, unlike the first embodiment, the information representing the change over time in the concentration level acquired in step S40 includes information representing the required concentration level required in the driving environment of the vehicle 1. As an example, information representing a graph such as that shown in FIG. 7 is acquired. Thereafter, the process proceeds to step S41.

[0086] In step S41, the determination unit 25 determines whether or not the driver of the vehicle 1 has driven for the target period, similarly to step S21 in the first embodiment. If it is determined that the driver has driven for the target period (step S41: YES), the process proceeds to step S42. On the other hand, if it is determined that the driver has not driven for the target period (step S41: NO), the process ends. However, step S41 is not essential, and the process may always proceed from step S40 to step S42.

[0087] In step S42, the acquisition unit 23 acquires information indicating the traveling environment of the vehicle 1, in the same manner as in step S31 of the first operation example. Thereafter, the process proceeds to step S43.

[0088] In step S43, the acquisition unit 23 acquires the required concentration degree required in the traveling environment of the vehicle 1 acquired in step S42, in the same manner as in step S32 of the first operation example. Thereafter, the process proceeds to step S44.

[0089] In step S44, similarly to steps S11 and S12 in the first embodiment, the calculation unit 24 calculates the degree of concentration on the current driving of the driver of the vehicle 1 (hereinafter sometimes abbreviated as "current concentration degree") based on the state of the driver of the vehicle 1. Thereafter, the process proceeds to step S45.

[0090] In step S45, the determination unit 25 determines whether or not to determine the trend of the driver's concentration level of the vehicle 1, based on the concentration level calculated in step S44. Specifically, if the current concentration level calculated in step S44 remains lower than the required concentration level acquired in step S43 for a certain period of time or longer, the determination unit 25 determines that the trend of the driver's concentration level should be determined. If it is determined that the trend of the concentration level should be determined (step S45: YES), the process proceeds to step S46. On the other hand, if it is not determined that the trend of the concentration level should be determined (step S45: NO), the process returns to step S42.

[0091] In step S46, the judgment unit 25 determines the tendency of the concentration level of the driver of vehicle 1 based on a comparison between the past concentration level obtained in step S40 and the current concentration level obtained in step S44 and the required concentration level required according to the driving environment of vehicle 1.

[0092] Specifically, the determination unit 25 determines that the concentration level trend is the first trend if the frequency of occurrence of a state in which the concentration level is less than the required concentration level required according to the driving environment is equal to or greater than a predetermined frequency during the target period from the past to the present. As an example, if a state in which the concentration level is less than the required concentration level has continuously occurred over the past week, the determination unit 25 determines that the concentration level trend is the first trend. Then, the process proceeds to step S47.

[0093] On the other hand, if the frequency of occurrence of a state in which the concentration level is less than the required concentration level required according to the driving environment during the target period from the past to the present is less than a predetermined frequency, the determination unit 25 determines that the concentration level trend is the second trend. As an example, if a state in which the concentration level is less than the required concentration level has not continuously occurred during the past week, and the current concentration level is accidentally less than the required concentration level, the determination unit 25 determines that the concentration level trend is the second trend. Then, the process proceeds to step S48.

[0094] However, the present disclosure is not limited to this, and in step S46, the judgment unit 25 may determine that the trend in the concentration level is a first trend if the frequency of occurrence of a state in which the concentration level is less than the required concentration level required according to the driving environment increases over time during the target period from the past to the present.

[0095] In step S47, the presenting unit 27 presents first information for improving the concentration level of the driver of the vehicle 1, similar to step S25 in the first embodiment. Thereafter, the process ends. Note that, similar to the first embodiment, the first information may include information for encouraging the driver to improve their lifestyle habits.

[0096] In step S48, the presenter 27 presents second information, which is different from the first information and is intended to improve the concentration level of the driver of the vehicle 1, in the same manner as in step S26 of the first embodiment. The process then ends. Note that the second information may include information intended to improve the concentration level of the driver, as in the first embodiment.

[0097] (Effect) As described above, the processing unit 21 of the driving assistance device 20 according to this embodiment determines the concentration level trend based on the current and past levels of concentration on driving of the driver of the vehicle 1. In particular, the processing unit 21 determines the concentration level trend based on a comparison between the current and past levels of concentration on driving of the driver of the vehicle 1 and a required concentration level required in accordance with the driving environment of the vehicle 1. Then, the processing unit 21 determines the content of information to be presented to the driver of the vehicle 1 based on the determined concentration level trend.

[0098] According to this configuration, the driver's concentration level can be appropriately improved depending on the state of the driver, as in the first embodiment. In addition, by taking into consideration the required concentration level required depending on the driving environment of the vehicle 1, information required to improve the driver's concentration level can be appropriately presented to the driver who encounters a driving environment that requires a higher level of concentration than in clear weather, such as strong winds, rainfall, or snowfall.

[0099] Although the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art to which the present disclosure pertains can conceive of various modifications or alterations within the scope of the technical ideas described in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure. For example, the functions included in each component or step can be rearranged so as not to be logically inconsistent, and multiple components or steps can be combined or divided into one.

[0100] As a variant example, the processing unit 21 of the driving assistance device 20 may perform the following processing after the second operation example of the first embodiment or after the second operation example of the second embodiment.

[0101] That is, when or after presenting the first information or the second information to the driver of vehicle 1, the presentation unit 27 of the processing unit 21 presents a question encouraging the driver to obtain a coupon for the product or service by stopping by a location where the product or service is provided.

[0102] The determination unit 25 of the processing unit 21 then determines whether or not the driver of the vehicle 1 has responded to the question presented by the presentation unit 27. The response from the driver can be acquired by the acquisition unit 23 from a microphone or the like provided in the vehicle 1.

[0103] If there is an answer from the driver, the determination unit 25 of the processing unit 21 determines to guide the driver to the location where the product or service is provided, and if there is no answer from the driver, the determination unit 25 determines to present a warning by the presentation unit 27. In the case of guidance, a route from the current location of the vehicle 1 to the location where the product or service is provided is provided by a publicly known or arbitrary method using a navigation system provided in the vehicle 1. On the other hand, in the case of a warning, a warning sound may be output from a speaker provided in the vehicle 1, or the steering wheel 7 may be vibrated by a publicly known or arbitrary vibration generator provided in the steering wheel 7.

[0104] Note that, instead of issuing a warning, if the vehicle 1 is a vehicle capable of executing automatic driving control, the processing unit 21 may generate driving information, steering information, and braking information for automatically driving the vehicle 1 to a location where a product or service is provided or a safe stopping position, and transmit the information to the vehicle control device 10. This allows the vehicle 1 to automatically drive to a location where a product or service is provided or a safe stopping position.

[0105] According to this modification, an additional effect can be obtained in that the possibility that the driver of the vehicle 1 will continue driving without taking a break at his / her own discretion can be reduced.

[0106] The technology of the present disclosure can also be realized as a vehicle 1 equipped with the driving assistance device 20 described in the above-mentioned embodiment, a driving assistance method executed by the driving assistance device 20, a computer program that causes a computer to function as the above-mentioned driving assistance device 20, and a non-transitory tangible recording medium on which the computer program is recorded.

[0107] 1: vehicle, 20: driving assistance device, 21: processing unit, 22: storage unit, 23: acquisition unit, 24: calculation unit, 25: determination unit, 26: storage processing unit, 27: presentation unit

Claims

1. A driving assistance device that assists in driving a vehicle, comprising one or more processors and one or more memories communicatively connected to the one or more processors, wherein the one or more processors determine a tendency of the driver of the vehicle to concentrate on driving, based on the current and past concentration level of the driver, and determine the content of information to be presented to the driver based on the determined tendency of the concentration level.

2. The driving assistance device of claim 1, wherein the one or more processors determine the tendency of the driver's concentration level based on a comparison of the driver's current and past concentration level on driving with the current and past concentration levels of other drivers other than the driver on driving.

3. The driving assistance device of claim 1, wherein the one or more processors acquire a required level of concentration required in the vehicle's driving environment, and determine the tendency of the driver's level of concentration based on a comparison between the driver's current and past levels of concentration for the driving and the acquired required level of concentration.

4. A driving assistance device as described in any one of claims 1 to 3, wherein the one or more processors, as the tendency of the concentration level, present first information for improving the concentration level when the frequency of occurrence of a state in which the concentration level is less than a predetermined value is equal to or greater than a predetermined frequency, and present second information for improving the concentration level, which is different from the first information, when the frequency of occurrence of a state in which the concentration level is less than the predetermined frequency.

5. The driving assistance device according to claim 4, wherein the first information includes information encouraging the driver to improve their lifestyle habits.

6. The driving assistance device according to claim 4, wherein the second information includes information that encourages at least temporary recovery of the driver's physical and mental state.

7. A vehicle equipped with the driving assistance device according to claim 1.

8. A driving assistance method for assisting driving of a vehicle, comprising: a computer determining a tendency of the degree of concentration based on the current and past degree of concentration of the driver of the vehicle on driving; and determining content of information to be presented to the driver based on the determined tendency of the degree of concentration.

9. A non-transitory tangible recording medium having recorded thereon a computer program applied to a driving assistance device that assists in the driving of a vehicle, the non-transitory tangible recording medium having recorded thereon a computer program that causes a computer to perform the following: determining a tendency in the degree of concentration based on the current and past degree of concentration of the driver of the vehicle on driving; and determining the content of information to be presented to the driver based on the determined tendency in the degree of concentration.

Images