Driver assistance device, driver assistance system, and driver assistance method

Abstract

To provide a driver-supporting device capable of estimating factors that cause diminishment of a driver's cognitive function, and to provide a driver-supporting system and a driver-supporting method therefor.SOLUTION: A driver-supporting device comprises: a driving state detection part for detecting at least one of a driver's vehicle-driving action, biological information during driving, and behavior of a vehicle; a cognitive function score calculation part for calculating a numerical value indicating a level of a driver's cognitive function, based on a detection result of the driving state detection part; a cognitive function property analysis part for analyzing the calculated numerical value as a cognitive function property related to one or more different brain functions; a cognitive function storage part for time-sequentially storing the numerical values calculated by the cognitive function score calculation part with respect to the same driver, and a result analyzed by the cognitive function property analysis part; a cognitive function diminishment factor estimation part for estimating main factors among a plurality of variable factors that cause diminishment of a driver's cognitive function, based on the stored content; and a driver-supporting part for supporting the driver based on an estimation result or information corresponding to the estimation result.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present disclosure relates to a driver assistance device, a driver assistance system, and a driver assistance method. [Background technology]

[0002] When analyzing traffic accidents by human factors, "delayed detection," such as inattention to the road ahead (including distracted driving and looking away) and failure to confirm safety, accounts for approximately 80% of accidents (Non-Patent Document 1). In other words, the cognitive aspect of the "cognition, judgment, and operation" component of driving is the primary cause. Factors that affect cognitive decline related to driving include drowsiness, alcohol / drugs, aging, dementia, and neuropsychiatric disorders, including higher brain dysfunction (Non-Patent Document 2). Therefore, if we could prevent cognitive decline while driving, which is caused by various factors, it is believed that traffic accidents could be reduced. Furthermore, research is being conducted from various perspectives on human cognitive function, driver cognitive function, and driver behavior analysis while driving, as shown in Non-Patent Documents 3 to 24.

[0003] Patent Document 1 discloses a driving assistance device that detects a state in which driving ability has declined due to drinking, drowsiness, etc., and notifies the driver of the decline in driving ability. Patent Document 2 discloses a dementia risk assessment system that detects traffic violations that are likely to be committed when cognitive function declines, and can determine whether a driver is fit to drive. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2009-101714 [Patent Document 2] Japanese Patent Application Publication No. 2019-124975 [Non-patent literature]

[0005] [Non-Patent Document 1] Traffic Accident Comprehensive Analysis Center: "Traffic Accident Statistics Table Data: Total Number of Accidents (per Vehicle) by Human Factor and Accident Type," 2020 [Non-patent document 2] Masaru Mimura, Yoshio Fujita: "Safe driving and cognitive function", Journal of the Japan Geriatrics Society, vol. 55, No. 2, pp. 191-196, 2018 [Non-patent document 3] Supervised by Takao Suzuki: "Mild Cognitive Impairment (MCI) from the Basics - Aiming for Effective Dementia Prevention", pp.7-8, p.34, pp.111-123, p.225, Igaku-Shoin, 2015 [Non-patent document 4] Japanese Society of Neurology: "Dementia Disease Treatment Guidelines 2017", Igaku-Shoin, pp.19-22, 2017 [Non-patent document 5] Shinya Iida, Noriaki Kato, Kenji Hachisuka, Satoru Saeki: "Assessing the Driving Ability of Elderly People," Journal of the Japan Geriatrics Society, vol. 55, No. 2, pp. 202-207, 2018 [Non-patent document 6] Naoto Uemura: "Assessing Driving Ability of People with Dementia and Its Challenges," Journal of the International Association for Traffic Safety, vol. 42, No. 3, pp. 12-22, 2018 [Non-Patent Document 7] Katsuya Urakami: “Dementia and Driving”, Automotive Technology, Vol. 71, No. 12, pp. 90-95, 2017 [Non-patent document 8] Ryoko Fukuda, Fumio Harada, and Taisaku Okumura: "The nature of cars supporting a super-aging society: Aiming for cars that deeply embrace each individual's uniqueness," Cognitive Studies, 25(3), pp. 259-278, September 2018. [Non-Patent Document 9] Shinya Takagi and Keiichi Yamada: "Relationship between Vehicle Behavior and Driver Reaction Time", Transactions of the Society of Automotive Engineers of Japan, Vol. 43, No. 5, pp. 1131-1137, 2012 [Non-Patent Document 10] Li Bo, Zhang Xiaolin, Sato Makoto: Pitch Angle Estimation Using an In-Vehicle Monocular Camera for Measuring Inter-Vehicle Distance, Journal of the Institute of Image Information and Television Engineers, vol.69, No.4, pp.J169-J176, 2015 [Non-Patent Document 11] Ryusuke Uesaka, Masafumi Noda, Yoshito Mekada, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase: "Driving behavior prediction using driver gaze information", Technical Report of the Institute of Electronics, Information and Communication Engineers. MI, Medical Imaging 111(49), 105-110, 2011-05-12 [Non-Patent Document 12] Akito Yamazaki, Pongsathorn Raksincheransak, and Motoki Kotake: "Extracting Gaze Area by Estimating Driver's Face Direction Using an In-Vehicle Camera," Transactions of the Society of Automotive Engineers of Japan, Vol. 48, No. 5, pp. 1113-1119, 2017 [Non-Patent Document 13] Masanari Takagi, Hironobu Fujiyoshi: "Traffic Sign Recognition Using SIFT Features", Transactions of the Institute of Electrical Engineers of Japan, Vol. 129, No. 5, pp. 824-831, 2009 [Non-Patent Document 14] David W. Eby, Lisa J. Molnar, and Paula S. Katoji (eds. and translators: Etsuo Horikawa and Tomoko Mine): "Mobility for the Elderly (From Driving Eligibility to Mobility Assistance)", Kyoto University Press, pp. 15-33, 2020 [Non-Patent Document 15] Tsuneo Matsuura: "Safety Psychology of Elderly Drivers", University of Tokyo Press, pp.48-62, 2017 [Non-Patent Document 16] Kazumi Isaji, Naohiko Tsuru, Takahiro Wada, Shunichi Doi, Hiroshi Kaneko: "Analysis of Braking Initiation Timing Using Approach and Separation State Evaluation Index", Transactions of the Society of Automotive Engineers of Japan, Vol. 41, No. 3, pp. 593-598, 2010 [Non-Patent Document 17] Tsuyoshi Nakagawa, et al.: "Health Management While Driving," DENSO TECHNICAL REVIEW, vol. 21, 2016 [Non-Patent Document 18] Osamu Watanabe: "Cognitive Function and Driving," Journal of the Japan Society of Traffic Science, Vol. 17, No. 2, pp. 3-10, 2017 [Non-Patent Document 19] Noriyasu Kitamura: "Safe Driving Lifespan", Corporate Development Center, Transportation Research Laboratory, pp.44-46, pp.60-65, pp.133-136, 2009 [Non-Patent Document 20] Atsuo Murata and Makoto Moriwaka: "Driver's visual information processing characteristics in a risk prediction task - Comparison between beginner and experienced drivers -", ​​Journal of Ergonomics, Vol. 46, No. 6, pp. 393-397, 2010 [Non-Patent Document 21] Nakata, Daiki, and Shibasaki, Manabu: "Cognitive function and environmental stress", Journal of the Japanese Society of Biometeorology, 56(1), 3-11, 2019 [Non-Patent Document 22] Miyuki Sakurai and Shoichi Iwasaki: "Daytime Attention and Cognitive Failure Tendency in Elderly People," Applied Psychology Research, Vol. 42, No. 3, pp. 185-193, 2017 [Non-Patent Document 23] Chiyomi Miyajima, Kazuya Takeda: "Construction of a Driving Behavior Database and Its Applications", Vol.55, No.1, pp.20-25, 2011 [Non-Patent Document 24] Inagaki Gushi, Harada Noritake, Kashiwa Yuki, Takehira Seiji, Kobayakawa Satoru: "Basic Analysis of Elderly Drivers' Driving Behavior and Personal Characteristics Based on Drive Recorder Data", Vol. 5, No. 2, pp. A_208-A216, 2019 Summary of the Invention [Problem to be solved by the invention]

[0006] In Patent Documents 1 and 2, the factors that caused the decline in cognitive function were not estimated.

[0007] The present disclosure aims to provide a driver assistance device, a driver assistance system, and a driver assistance method that can estimate factors that cause decline in a driver's cognitive function.

[0008] This disclosure discloses an improved invention of a previously filed patent application (Patent Application No. 2021-052309). Therefore, the present specification appropriately cites the contents of the previously filed application. [Means for solving the problem]

[0009] The driver assistance device according to the present disclosure includes a driving state detection unit, a cognitive function score calculation unit, a cognitive function characteristic analysis unit, a cognitive function memory unit, a cognitive function decline factor estimation unit, and a driver assistance unit. The driving state detection unit detects at least one of the driver's driving behavior, the driver's biological information while driving, and the vehicle's behavior. The cognitive function score calculation unit calculates a numerical value indicating whether the driver's cognitive function is high or low based on the information detected by the driving state detection unit. The cognitive function characteristic analysis unit analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic related to one or more different brain functions. The cognitive function memory unit stores the numerical values ​​calculated by the cognitive function score calculation unit for the same driver and the analysis results of the cognitive function characteristic analysis unit in chronological order. The cognitive function decline factor estimation unit estimates factors causing the decline in the driver's cognitive function based on the contents stored in the cognitive function memory unit. , including at least one of the driver's aging factor, physical condition factor, and skill factor. The driver assistance unit calculates the influence of the variable factors and estimates the main factor. The driver assistance unit supports the driver based on the estimation results by the cognitive decline factor estimation unit or information based on the estimation results. The driver assistance unit further includes an assistance content determination unit that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit and a threshold value, whether to enable an information provision function that assists in providing information to suppress further decline in the driver's cognitive function, or a driving assistance function that assists in driving operations associated with the declined cognitive function characteristics, from among the multiple functions possessed by the vehicle; and an output unit that, when the assistance function determined by the assistance content determination unit becomes enabled, outputs the estimation result by the cognitive function decline factor estimation unit, or information corresponding to the estimation result, in a form corresponding to past numerical values ​​related to the main factors and current numerical values ​​related to the main factors. [Effects of the Invention]

[0010] According to the driver assistance device of the present disclosure, it is possible to estimate the cause of the decline in the driver's cognitive function. [Brief explanation of the drawings]

[0011] [Figure 1A] FIG. 1A is a diagram illustrating the decline in cognitive function characteristics with aging. [Figure 1B] FIG. 1B is a diagram illustrating the deterioration of cognitive function characteristics over time. [Figure 2] FIG. 2 is a diagram illustrating cognitive function characteristics determined by the driver assistance device according to the embodiment. [Figure 3] FIG. 3 is a hardware block diagram showing an example of the hardware configuration of the driver assistance device according to the embodiment. [Figure 4] FIG. 4 is an external view showing an example of a cockpit of a vehicle equipped with a driver assistance device according to an embodiment. [Figure 5] FIG. 5 is a functional block diagram illustrating an example of a functional configuration of a driver assistance device according to the embodiment. [Figure 6] FIG. 6 is a diagram illustrating an example of information detected by the driving state detection unit. [Figure 7] FIG. 7 is a flowchart showing an example of the flow of processing by the cognitive function score calculation unit to calculate the evaluation score of the cognitive function level. [Figure 8] FIG. 8 is a diagram illustrating the relationship between cognitive function characteristics related to different brain functions and driving behaviors that occur while driving. [Figure 9] FIG. 9 is a first diagram illustrating an example of assistance provided by the driver assistance device in accordance with cognitive function characteristics. [Figure 10] FIG. 10 is a second diagram illustrating an example of assistance provided by the driver assistance device in accordance with cognitive function characteristics. [Figure 11] FIG. 11 is a diagram illustrating an example of a factor that causes a decline in cognitive function. [Figure 12] FIG. 12 is a diagram showing an example of changes in cognitive function over time. [Figure 13A] FIG. 13A is a first diagram showing an example of a factor analysis of cognitive decline. [Figure 13B] FIG. 13B is a second diagram showing an example of a factor analysis of cognitive decline. [Figure 14] FIG. 14 is a diagram illustrating an example of a method for identifying a state of cognitive decline. [Figure 15] FIG. 15 is a diagram showing an example of changes over time in the cognitive function level of a driver. [Figure 16] FIG. 16 is a diagram showing an example of information presentation content according to a change in cognitive function level. [Figure 17] FIG. 17 is a diagram showing an example of information presented to the driver when the main cause of cognitive decline is aging. [Figure 18] FIG. 18 is a diagram showing an example of information presented to the driver when the main cause of cognitive decline is a physical condition factor. [Figure 19]FIG. 19 is a diagram showing an example of information presented to the driver when the main cause of cognitive decline is a skill factor. [Figure 20] FIG. 20 is a diagram showing an example of a method for calculating the degree of influence of aging factors on the decline in cognitive function. [Figure 21] FIG. 21 is a flowchart showing an example of another method for estimating the causes of cognitive decline. [Figure 22] FIG. 22 is a flowchart showing an example of the flow of processing performed by the driver assistance device of this embodiment. [Figure 23] FIG. 23 is a diagram illustrating a function of presenting information related to the main cause of the decline in cognitive function when the driver assistance device changes the operation mode. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, an embodiment of a driver assistance device according to the present disclosure will be described with reference to the drawings.

[0013] (Explanation of cognitive function characteristics) The cognitive function characteristics of a driver will be described using Figures 1A, 1B, and 2. Figure 1A is a diagram illustrating the state of cognitive function decline with aging. Figure 1B is a diagram illustrating the state of cognitive function decline over time. In particular, Figure 1B is a diagram illustrating the state of cognitive function decline over a shorter period of time than Figure 1A. Figure 1A illustrates an example of fluctuations over a yearly basis, and Figure 1B illustrates an example of fluctuations in driving time. Figure 2 is a diagram illustrating the cognitive function characteristics determined by a driver assistance device of an embodiment.

[0014] As shown in Figure 1A, cognitive function may decline with age (Non-Patent Document 3). Furthermore, as shown in Figure 1B, cognitive function fluctuates over time in daily life (Non-Patent Document 22). Here, the cognitive function level evaluation score E is a numerical representation of whether a person's cognitive function is high or low. When the cognitive function level evaluation score E calculated using an appropriate evaluation method exceeds a first threshold Th1, i.e., when the cognitive function level evaluation score E is in region R1, the person's cognitive function is determined to be in a state where safe driving is possible. When the cognitive function level evaluation score E is below the first threshold Th1 and above a second threshold Th2 that is smaller than the first threshold Th1, i.e., when the cognitive function level evaluation score E is in region R2, the person's cognitive function is determined to be in a "caution required" state, which impairs continued safe driving. Furthermore, when the cognitive function level evaluation score E is smaller than the second threshold Th2, i.e., when the cognitive function level evaluation score E is in region R3, the person's cognitive function level is determined to be in a "dangerous" state, where the person's cognitive function level has deteriorated to the point where it is difficult to continue driving. A driver's cognitive function characteristics can be measured by a doctor through cognitive function tests such as the MMSE (Mini-Mental State Examination) (Non-Patent Document 3), but here we aim to quantify cognitive function that fluctuates over time while driving.

[0015] Note that cognitive function also declines when driving aimlessly, looking away, or when attention temporarily declines, as shown in Figure 1B. Even when cognitive function declines due to aging or when mild cognitive impairment (MCI) is present, cognitive function can be evaluated in a similar manner to that shown in Figures 1A and 1B, and fluctuations can also be observed.

[0016] The driver assistance device 10 of this embodiment quantifies the cognitive function of the driver, analyzes the state of the cognitive function characteristics based on the quantified value, and provides appropriate driving assistance based on the analysis results.

[0017] Cognitive functions can be classified into a plurality of different cognitive functions each associated with a different brain region (brain function) (Non-Patent Document 3). In the driver assistance device 10 of this embodiment, with reference to Non-Patent Document 3, a plurality of different cognitive functions shown in FIG. 2 are evaluated. Specifically, these are memory 80, executive ability 81, attention 82, information processing ability 83, and visuospatial cognition 84. The impact of a decline in each cognitive function on driving is described in Non-Patent Documents 2, 5, 6, and 7. Note that, although five cognitive functions are selected as evaluation targets in FIG. 2, only one or any combination of two or more may be selected. Furthermore, cognitive functions not listed here may also be evaluated.

[0018] Memory 80 is a cognitive function that stores new experiences and reproduces them in consciousness and actions (Non-Patent Document 4). In the context of driving behavior, memory 80 is reflected, for example, in the ability to retain information written on signs and the ability to remember where one is going (Non-Patent Document 5).

[0019] Executive ability 81 is a cognitive function that aims to make plans, executes things, and proceeds while receiving feedback on the results (Non-Patent Document 4). In terms of driving behavior, executive ability 81 is reflected in, for example, the ability to properly step on the accelerator and brake, the ability to process multiple pieces of information, etc. (Non-Patent Document 5).

[0020] Attention 82 is a cognitive function that serves as the basis for receiving and selecting stimuli from the surroundings and acting consistently in response to them (Non-Patent Document 4). In the context of driving behavior, attention 82 is reflected in the ability to pay attention to the surrounding environment, such as signs and traffic lights (Non-Patent Document 5).

[0021] Information processing ability 83 is a cognitive function that accomplishes a specified task within a certain time period (Non-Patent Document 3). In the context of driving behavior, information processing ability 83 is reflected in, for example, the ability to detect and respond to dangers while driving (Non-Patent Document 15).

[0022] Visual-spatial cognition 84 is a cognitive function that processes visual information and grasps the state of a space. In the context of driving behavior, visual-spatial cognition 84 is reflected in, for example, the ability to maintain an accurate sense of distance from the vehicle ahead and the ability to avoid straying from one's lane when going around a curve (Non-Patent Document 5).

[0023] As shown in Figures 1A and 1B, all of these cognitive functions are known to fluctuate with age and time (Non-Patent Document 3). That is, as shown in Figure 2, the level of each of the above-mentioned cognitive functions can be evaluated based on the magnitude relationship between the first threshold value Th1 and the second threshold value Th2. Note that Figure 2 shows a normalized horizontal axis, and the first threshold value Th1 and the second threshold value Th2 for each cognitive function are not necessarily the same value.

[0024] (Overall configuration of driver assistance devices) The overall configuration of the driver assistance device 10 will be described with reference to Figures 3 and 4. Figure 3 is a hardware block diagram showing an example of the hardware configuration of the driver assistance device according to the embodiment. Figure 4 is an external view showing an example of the cockpit of a vehicle equipped with the driver assistance device according to the embodiment.

[0025] The driver assistance device 10 calculates an evaluation score E of the cognitive function level of the driver of the vehicle 30, and provides driving assistance according to the deterioration of the cognitive function of the driver.

[0026] The driver assistance device 10 includes an ECU (Electronic Control Unit) 11, sensor controllers 12, 21, a steering control device 13, a driving force control device 14, a braking force control device 15, a GPS receiver 22, a map database 24, a display device 25, an operation device 26, and a communication interface 27.

[0027] The ECU 11 is configured as a computer including, for example, a CPU (Central Processing Unit) 11a, a RAM (Random Access Memory) 11b, and a ROM (Read Only Memory) 11c. The ECU 11 may also include a built-in storage device 11d including a hard disk drive (HDD). The ECU 11 also includes I / O (Input / Output) ports 11e and 11f capable of transmitting and receiving detection signals and various information to and from various sensors. The I / O port 11e is connected to a bus line 16 through which information related to driving control of the vehicle 30 flows, and controls the input and output of information related to a control system that provides various driving assistance for the vehicle 30. The I / O port 11f is connected to a bus line 28 through which information related to the information system of the vehicle 30 flows, and controls the input and output of information related to detection of the driver's driving behavior and information presented to the driver.

[0028] The RAM 11b, ROM 11c, storage device 11d, and I / O ports 11e and 11f of the ECU 11 are configured to be able to send and receive various types of information to and from the CPU 11a via an internal bus 11g.

[0029] The ECU 11 controls various processes performed by the driver assistance device 10 by the CPU 11a reading and executing programs installed in the ROM 11c.

[0030] The program executed by the driver assistance device 10 of this embodiment may be provided by being pre-installed in the ROM 11c, or may be provided by being recorded in an installable or executable file format on a computer-readable recording medium such as a CD-ROM, a flexible disk (FD), a CD-R, or a DVD (Digital Versatile Disk).

[0031] Furthermore, the program executed by the driver assistance device 10 of this embodiment may be stored on a computer connected to a network such as the Internet and provided by being downloaded via the network. Also, the program executed by the driver assistance device 10 of this embodiment may be provided or distributed via a network such as the Internet.

[0032] The storage device 11d stores a table and the like for calculating an evaluation score E of the driver's cognitive function level, which will be described in detail later.

[0033] The sensor controller 12 acquires sensor outputs for detecting the behavior of the vehicle 30 and transfers them to the ECU 11. For example, an accelerator position sensor 12a, a brake depression force sensor 12b, a steering angle sensor 12c, etc. are connected to the sensor controller 12. Note that the sensors connected to the sensor controller 12 are not limited to these examples, and other sensors may also be connected.

[0034] The accelerator position sensor 12a detects the degree of depression of the accelerator of the vehicle 30 (accelerator opening degree).

[0035] The brake pedal force sensor 12b detects the force applied to the brake pedal of the vehicle 30, that is, the force applied to the brake pedal.

[0036] The steering angle sensor 12c detects the steering direction and the steering amount of the steering wheel of the vehicle 30.

[0037] In addition, a steering control device 13, a driving force control device 14, and a braking force control device 15 are connected to the bus line 16. These control devices cooperate with each other to control the behavior of the vehicle 30 based on various sensor information acquired by the sensor controller 12 and various sensor information acquired by the sensor controller 21, thereby forming a so-called ADAS (Advanced Driver Assistance System) system.

[0038] The steering control device 13 controls the steering angle of the vehicle 30 based on instructions from the ECU 11 .

[0039] The driving force control device 14 controls the driving force of the vehicle 30 based on instructions from the ECU 11. Specifically, the driving force control device 14 controls the accelerator opening of the engine of the vehicle 30 based on instructions from the ECU 11.

[0040] The braking force control device 15 controls the braking force of the vehicle 30 based on instructions from the ECU 11. The steering control device 13, the driving force control device 14, and the braking force control device 15 cooperate with each other to enable the vehicle 30 to travel automatically.

[0041] The ADAS system installed in the vehicle 30 is not limited to the above-mentioned devices, and other devices may be installed.

[0042] The sensor controller 21 is connected to the surrounding camera 21a, the driver monitor camera 21b, the distance measurement sensor 21c, etc., and transfers the outputs of these sensors to the ECU 11. Based on the acquired information, the ECU 11 senses the surrounding environment of the vehicle 30 and detects the driver's biological signals. Note that the sensors connected to the sensor controller 21 are not limited to these examples, and other sensors may also be connected.

[0043] The surrounding cameras 21 a are installed facing different directions around the vehicle 30 and acquire image information of the surroundings of the vehicle 30 .

[0044] The driver monitor camera 21b is installed on the instrument panel of the vehicle 30 and captures images including the face of the driver while driving. The driver monitor camera 21b may also be installed at the driver's feet to monitor the driver's accelerator and brake operations.

[0045] The distance measurement sensors 21c are installed facing different directions around the vehicle 30 and measure the distances to obstacles around the vehicle 30. The distance measurement sensors 21c are, for example, ultrasonic sensors that measure short distances, millimeter-wave radars that measure medium to long distances, or LiDARs (Light Detection and Ranging).

[0046] The GPS receiver 22 acquires GPS signals transmitted from GPS (Global Positioning System) satellites to determine the current position and calculate the traveling direction of the vehicle 30. The ECU 11 also identifies the road on which the vehicle 30 is traveling and the traveling direction by comparing (map matching) the identified current position and traveling direction of the vehicle 30 with a map database 24. Note that the method of identifying the current position and traveling direction of the vehicle using GPS signals and a map database is widely used in car navigation systems, and therefore a detailed description thereof will be omitted.

[0047] The display device 25 displays information related to the driving state of the vehicle 30 and information to be presented to the driver. The display device 25 is, for example, a center monitor 25a, an indicator 25b, a meter 25c, etc., as shown in Fig. 4. The contents of each display device 25 will be described later (see Fig. 4). The display device 25 may be a device that presents information not only to the driver's vision but also to the driver's hearing or tactile senses, such as a speaker or a vibration device.

[0048] The operation device 26 acquires various operation information for the vehicle 30. The operation device 26 is, for example, a touch panel laminated on the display surface of the center monitor 25a, a physical switch installed on the instrument panel, or the like.

[0049] The communication interface 27 wirelessly connects the vehicle 30 to a mobile terminal (e.g., a pre-registered smartphone or wearable terminal) outside the vehicle. The communication interface 27 transmits, for example, an evaluation score E of the cognitive function level calculated by the driver assistance device 10 from the vehicle 30 to the mobile terminal.

[0050] Next, the schematic configuration of the cockpit of the vehicle 30 equipped with the driver assistance device 10 will be described with reference to FIG.

[0051] A center monitor 25a, which is an example of a display device 25, is installed in the center cluster of the vehicle 30. The center monitor 25a is installed as high up as possible to improve visibility while driving. The driver assistance device 10 displays, on the center monitor 25a, an evaluation score E of the cognitive function level, driving assistance content based on the evaluation score E, and the like.

[0052] An indicator 25b, which is an example of a display device 25, is provided along the upper end of the spoke of the steering wheel 31. The indicator 25b is formed, for example, of a rod-shaped light guide, and emits light in a color corresponding to incident light incident from one end. The driver assistance device 10 causes the indicator 25b to emit light in a color corresponding to the driving assistance content based on the cognitive function level evaluation score E. The indicator 25b is provided in the peripheral vision area of ​​the driver while driving, and the emitted color of the indicator 25b can be recognized without directing the driver's line of sight toward the indicator 25b. This allows the driver to easily recognize the driving assistance content.

[0053] Furthermore, a gauge 25c, which is an example of the display device 25, is installed in the meter cluster of the vehicle 30. The gauge 25c is, for example, a speedometer, an engine tachometer, a fuel gauge, a water temperature gauge, and the like.

[0054] Furthermore, a driver monitor camera 21b is installed in the meter cluster of the vehicle 30. The driver monitor camera 21b is installed in the meter cluster so as to capture an image of the entire area (eye range) where the eyes of the driver are located while driving.

[0055] (Functional configuration of driver assistance devices) The functional configuration of the driver assistance device 10 will be described with reference to Fig. 5. Fig. 5 is a functional block diagram showing an example of the functional configuration of the driver assistance device according to the embodiment.

[0056] The ECU 11 of the driver assistance device 10 loads the control program stored in the ECU 11 into the RAM 11b and causes the CPU 11a to run the program, thereby realizing, as functional units, a driving environment detection unit 40, a driver identification unit 41, a driving state detection unit 42, a cognitive function score calculation unit 43, a cognitive function characteristic analysis unit 44, a cognitive function memory unit 45, a cognitive function decline factor estimation unit 46, and a driver assistance unit 60, all of which are shown in FIG. 5 . The driver assistance unit 60 includes, as functional units, a cognitive function characteristic output unit 47, an assistance content determination unit 48, an assistance content display unit 49, an assistance information presentation unit 50, and a driving assistance control unit 51. The driver assistance device 10 may realize some or all of these functions using dedicated hardware.

[0057] The driving environment detection unit 40 detects the state of the surrounding environment of the road on which the vehicle 30 is traveling. The state of the surrounding environment of the road includes, for example, information on the road shape ahead in the direction of travel, the number of lanes, the speed limit, the distance to the intersection, the shape of the intersection, the presence or absence of a preceding vehicle and the distance therebetween, the presence or absence and location of an oncoming vehicle, the presence or absence and location of a pedestrian, etc. This information can be obtained, for example, by analyzing the images captured by the surrounding camera 21a and the information acquired by the distance measurement sensor 21c, and by comparing the current position of the vehicle 30 acquired from a GPS signal with the map database 24.

[0058] The driver identification unit 41 identifies the driver who is driving the vehicle 30. For example, the driver identification unit 41 identifies the driver currently driving by comparing the face image of the driver captured by the driver monitor camera 21b with face images of pre-registered drivers. If no matching result is obtained, the driver is considered to be a new driver and a new registration is performed.

[0059] The driving state detection unit 42 detects at least one of the driving behavior of the driver of the vehicle 30, the biological information of the driver while driving, and the behavior of the vehicle 30.

[0060] The cognitive function score calculation unit 43 calculates an evaluation score E that indicates whether the cognitive function of the driver is high or low, based on the information detected by the driving state detection unit 42. Note that the evaluation score E is an example of a numerical value in the present disclosure.

[0061] The cognitive function characteristic analysis unit 44 analyzes the evaluation score E of the cognitive function level calculated by the cognitive function score calculation unit 43 as a cognitive function characteristic related to one or more different brain functions. Note that the cognitive function characteristic related to one or more different brain functions is, for example, the memory ability 80, executive ability 81, attention ability 82, information processing ability 83, visuospatial cognition ability 84, etc.

[0062] The cognitive function storage unit 45 stores the evaluation scores E for the same driver calculated by the cognitive function score calculation unit 43 and the analysis results of the cognitive function characteristic analysis unit 44 in chronological order.

[0063] The cognitive function decline factor estimation unit 46 calculates the influence of multiple variable factors that cause the decline in the driver's cognitive function and estimates the main factor based on the memory contents of the cognitive function memory unit 45. Furthermore, the cognitive function decline factor estimation unit 46 estimates the variable factors of cognitive function by comparing the memory contents corresponding to the present in the cognitive function memory unit 45 with the memory contents corresponding to a predetermined past point in time.

[0064] The driver assistance unit 60 assists the driver based on the estimation result by the cognitive decline factor estimation unit 46 or information according to the estimation result.

[0065] The cognitive function characteristic output unit 47 outputs information on the analysis result by the cognitive function characteristic analysis unit 44. In addition, the cognitive function characteristic output unit 47 outputs the estimation result by the cognitive function decline factor estimation unit 46. Note that the cognitive function characteristic output unit 47 is an example of an output unit in the present disclosure.

[0066] The assistance content determination unit 48 determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit 44 and a threshold, whether to enable a function that assists in providing information to suppress further decline in the driver's cognitive function characteristics or a function that assists in driving operations associated with the declined cognitive function characteristics, from among the multiple functions of the vehicle 30. In addition, the assistance content determination unit 48 determines the content of information to be presented to the driver depending on the main cause of cognitive function decline estimated by the cognitive function decline factor estimation unit 46.

[0067] The support content display unit 49 displays the information determined by the support content determination unit 48 on, for example, the center monitor 25a.

[0068] When the assistance content determination unit 48 determines to enable a function for assisting in providing information to suppress further deterioration of the driver's cognitive function characteristics, the assistance information presenting unit 50 provides the information. Note that enabling the function for assisting in providing information to suppress further deterioration of the driver's cognitive function characteristics will be referred to as a training mode in the following description.

[0069] When the assistance content determination unit 48 determines to enable a function for assisting driving operations associated with cognitive function characteristics, the driving assistance control unit 51 activates the function. Note that enabling a function for assisting driving operations associated with cognitive function characteristics is referred to as a driving assistance mode in the following description.

[0070] (Operation of the driving condition detection unit) The detailed operation of the driving state detection unit 42 will be described using Figure 6. Figure 6 is a diagram illustrating an example of information detected by the driving state detection unit. Examples of analysis of general driving behavior are summarized in Non-Patent Documents 23 and 24. Examples of detected information include the driver's driving behavior, vehicle behavior, and driver's biological information, and examples of the driving environment include road shape, weather, and time of day.

[0071] The driving state detection unit 42 detects the driver's biological information by analyzing an image including the driver's face captured by the driver monitor camera 21b shown in FIG. 3. Specifically, the driving state detection unit 42 detects the driver's line of sight, facial orientation, body movement (changes in facial position), number of blinks, intervals, etc. Note that the biological information to be detected and the detection method thereof are not limited to those described above. For example, the driver's heart rate, body temperature, respiratory state, etc. may also be detected. Specific methods for detecting the driver's state, vehicle information, operation information, and biological information may include the methods summarized in Non-Patent Document 8, or other methods.

[0072] The driving state detection unit 42 detects the behavior of the vehicle 30 based on the outputs of the accelerator position sensor 12a, the brake pedal force sensor 12b, the steering angle sensor 12c, and the distance measurement sensor 21c shown in FIG. 3, as well as the outputs of various sensors (such as a vehicle speed sensor and a shift position sensor) not shown in FIG. 3 that the vehicle 30 is equipped with. Specifically, the driving state detection unit 42 detects the behavior of the vehicle 30, such as the vehicle speed, the inter-vehicle distance, whether or not the vehicle has departed from its lane, sudden acceleration, sudden deceleration, and the driving trajectory. The method for measuring the vehicle behavior, such as the displacement of the vehicle position relative to the road, the displacement of the steering angle, and the pedal reaction time, may be the method described in Non-Patent Document 9, or other methods may be used. The inter-vehicle distance can be measured using the method described in Non-Patent Document 10, or by using information detected by a general ADAS system. The detected behavior of the vehicle 30 is not limited to the above.

[0073] Furthermore, the driving state detection unit 42 detects the driving behavior of the driver based on the detected biometric information of the driver, the behavior of the vehicle 30, and the road environment on which the vehicle 30 is traveling. Specifically, the driving behavior detection unit 42 detects the distribution of gaze points, whether the driver is looking aside, whether the driver is checking to the left and right, whether the driver is checking behind the vehicle, whether the driver is stopping, whether the driver is following signs, whether the driver is following traffic lights, and the continuous driving time. Note that the driving behavior of the driver that is detected is not limited to the above.

[0074] The distribution of gaze points can be obtained by analyzing the measured gaze direction. A gaze point is a point where the gaze direction remains fixed for a predetermined period of time or more. If the gaze points are distributed over a wide area, it is estimated that the driver is paying attention to a wide range. On the other hand, if the gaze points are concentrated in a narrow range, it is estimated that the driver's attention is drawn to a specific range. As a method for detecting where the gaze is directed, for example, the method described in Non-Patent Document 11 or Non-Patent Document 12 may be used, or other methods may be used.

[0075] Whether or not the driver is looking aside can be determined by analyzing the measured gaze direction and face orientation. The method for detecting whether or not the driver is looking aside may be, for example, the method described in Non-Patent Document 12, or another method.

[0076] Whether or not the vehicle has checked left and right can be confirmed by determining whether the face has moved left or right or whether the gaze is directed in a direction where safety checks should be performed when the vehicle is in a location where left and right checks should be performed. The location where left and right checks should be performed can be determined by comparing the current position of the vehicle 30 obtained from the GPS signal with the map database 24, for example, by identifying whether the vehicle is traveling just before an intersection where left and right checks are required. Furthermore, the technology described in Non-Patent Document 12, for example, may be used to detect whether pedestrians are being checked, or other methods may be used.

[0077] Whether or not the driver has checked the rear can be confirmed by determining whether the driver has turned his / her face backward or turned toward the room mirror or rearview mirror when the driver is in a place where the driver should check the rear. The presence or absence of the driver checking the rear may be confirmed by using, for example, the technology described in Non-Patent Document 12, or by other methods. The fact that the driver is in a place where the driver should check the rear can be estimated by, for example, the shift position of the vehicle 30 being in the reverse position.

[0078] The presence or absence of a stop sign can be confirmed by determining whether the vehicle 30 has stopped at a place where a stop sign is required. The fact that a stop sign is required can be identified by the surrounding camera 21a detecting a stop sign. The sign recognition method may be, for example, the method described in Non-Patent Document 13, or another method.

[0079] Compliance with the sign can be determined based on whether the content of the sign detected by the surrounding camera 21a matches the detected behavior of the vehicle 30.

[0080] Compliance with traffic signals can be determined based on whether the state of the traffic signals detected by the surrounding camera 21a matches the detected behavior of the vehicle 30.

[0081] The continuous operation time can be determined, for example, by the time that has elapsed since the ignition was turned on.

[0082] Since the driving environment of the vehicle 30 is constantly changing, it is undesirable to continue detecting the above-mentioned detection targets because it would increase the load on the computer. Therefore, based on the driving environment of the vehicle 30, the driving state detection unit 42 detects at least one of the driving behavior of the driver of the vehicle 30, the biological information of the driver while driving, and the behavior of the vehicle 30, which are expected to occur in the driving environment.

[0083] Specifically, based on the driving environment detected by the driving environment detection unit 40, the driving state detection unit 42 estimates the biometric information, behavior of the vehicle 30, and driving behavior that are expected to occur in the driving environment, and narrows down the detection targets by detecting at least only the estimated information.

[0084] 6, the horizontal axis indicates an example of a driving environment detected by the driving environment detection unit 40, and the vertical axis indicates each of the detection targets described above. The circles in FIG. 6 indicate detection targets to be detected in the detected driving environment.

[0085] For example, when it is detected that the vehicle 30 is traveling before an intersection, the driving state detection unit 42 detects information related to the driver's behavior that is expected to occur at the intersection. For example, the gaze direction and face orientation are detected as biometric information. Furthermore, the vehicle speed, sudden acceleration, sudden deceleration, and driving trajectory are detected as the behavior of the vehicle 30. Furthermore, the distribution of the gaze point, whether or not the driver checked to the left and right, whether or not the driver stopped, whether or not the driver followed signs, and whether or not the driver followed traffic lights are detected as the driver's driving behavior. Note that the circles in FIG. 6 are merely examples, and the present invention is not limited to these examples.

[0086] Since estimating the detection target according to the driving environment every time would increase the calculation load, for example, the map of Figure 6 can be stored in the storage device 11d, and the driving state detection unit 42 can select the detection target by referring to the map.

[0087] (Method of calculating cognitive function) A method for calculating the cognitive function level evaluation score E by the cognitive function score calculation unit 43 will be described with reference to Fig. 7. Fig. 7 is a flowchart showing an example of the processing flow for calculating the cognitive function level evaluation score by the cognitive function score calculation unit.

[0088] The driving environment detection unit 40 detects the driving environment of the vehicle 30 (step S11).

[0089] The driving state detection unit 42 selects information to be detected in order to calculate the cognitive function based on the driving environment detected by the driving environment detection unit 40 (step S12).

[0090] The driving state detection unit 42 detects the information selected in step S12 (step S13).

[0091] Based on the information detected by the driving state detection unit 42, the cognitive function score calculation unit 43 adds up the occurrence frequency of each event that matches the driving environment detected by the driving environment detection unit 40 (step S14).

[0092] The cognitive function score calculation unit 43 determines whether a predetermined time has elapsed (step S15). If it is determined that the predetermined time has elapsed (step S15: Yes), the process proceeds to step S16. On the other hand, if it is not determined that the predetermined time has elapsed (step S15: No), the process returns to step S11. Note that the predetermined time may be set arbitrarily, but the determination is made in units of, for example, one minute.

[0093] If it is determined in step S15 that a predetermined time has elapsed, the cognitive function score calculation unit 43 calculates an evaluation score E of the cognitive function level (step S16). For example, the occurrence frequency of each event calculated in step S14 is used as the evaluation score E. For example, since the distribution state of the gaze points cannot be expressed in terms of frequency, a numerical value representing the width of the distribution range may be used as the evaluation score E. For other information that cannot be expressed in terms of frequency, the evaluation score E may also be calculated based on a calculation method set for each piece of information.

[0094] The cognitive function storage unit 45 stores the evaluation score E in association with the date and the driver (step S17). Thereafter, the cognitive function score calculation unit 43 ends the processing of FIG.

[0095] The cognitive function storage unit 45 stores the evaluation score E calculated in step S16 in association with the date and the driver in the storage device 11d (see FIG. 3) (step S17). Thereafter, the cognitive function score calculation unit 43 ends the processing in FIG.

[0096] In step S14, the frequency of occurrence of an event is incremented, but if it is detected that a desirable driving behavior has been performed, the accumulated frequency of occurrence of the event may be decremented.

[0097] (Analysis of cognitive function) The analysis method of the cognitive function level evaluation score E performed by the cognitive function characteristic analysis unit 44 will be described with reference to Fig. 8. Fig. 8 is a diagram illustrating the relationship between cognitive function characteristics related to different brain functions and driving behaviors that occur while driving.

[0098] As shown in Fig. 8, the cognitive function characteristic analysis unit 44 analyzes the degree of decline for each cognitive function associated with different brain functions based on the type of driving behavior detected and its frequency of occurrence. The impact of decline in each cognitive function on driving is described in Non-Patent Documents 2, 5, 6, and 7. The impact of a decline in information processing speed is described in Non-Patent Documents 14 and 15. Note that the driving behaviors shown in Fig. 8 are just an example, and a different correspondence table may be used.

[0099] For example, when memory ability 80 declines, it becomes difficult to retain information written on signs, people may forget where they are going and get lost (Non-Patent Document 5), or they may forget past experiences such as crashing cars or getting into trouble (Non-Patent Document 6). They may also become unable to understand road signs and traffic laws (Non-Patent Document 2). The cognitive function characteristic analysis unit 44 calculates the evaluation score Ea of memory ability 80 based on, for example, the frequency of following signs and the frequency of following traffic lights, etc., from the evaluation score E calculated by the cognitive function score calculation unit 43. The sign recognition method may be, for example, the method described in Non-Patent Document 13, or another method. It may also be determined that the contents of the sign have been recognized based on whether the driver has performed driving behavior that is appropriate for the contents of the sign.

[0100] When the executive ability 81 declines, the driver may mistake the accelerator for the brake, or have difficulty processing multiple pieces of information (Non-Patent Document 5). Furthermore, the driver may be unable to determine what to do next when the planned route is not taken (Non-Patent Document 6), or may be unable to respond flexibly to the situation (Non-Patent Document 2). The driver may also be unable to operate a car navigation system (Non-Patent Document 6). The cognitive function characteristic analysis unit 44 calculates the evaluation score Eb of the executive ability 81 from the evaluation score E calculated by the cognitive function score calculation unit 43, for example, based on the frequency of sudden acceleration and sudden deceleration.

[0101] When attention 82 declines, the driver is unable to pay attention to the surrounding environment, such as signs and traffic lights (Non-Patent Document 5). They may miss traffic lights or fail to notice people approaching (Non-Patent Document 6). Furthermore, they may fail to allocate their attention to their surroundings when changing lanes, resulting in dangerous maneuvers, or fail to notice pedestrians or motorcycles when turning right or left (Non-Patent Document 5). When attention is distracted, the driver becomes distracted by events inside or outside the vehicle (Non-Patent Document 14), causing them to look away. The cognitive function characteristic analysis unit 44 calculates the evaluation score Ec of attention 82 from the evaluation score E calculated by the cognitive function score calculation unit 43, based on, for example, the distribution of gaze points, the frequency of following signs, and the frequency of following traffic lights. Methods for detecting where the driver's gaze is directed may be, for example, those described in Non-Patent Document 11 or Non-Patent Document 12, and it is possible to evaluate whether the driver is looking at important points, such as signs or pedestrians, based on their gaze movements. Furthermore, the evaluation score Ec of attention 82 may be calculated by weighting the evaluation scores E calculated for whether or not the driver insufficiently checked for safety around the vehicle and whether or not the driver overlooked signs, etc., in the driving behavior example shown in Fig. 8. The weighting coefficient may be a predetermined coefficient, or a correlation with cognitive function may be learned sequentially.

[0102] When the information processing ability 83 declines, it takes time to spot dangers on congested roads or roads with fast traffic, resulting in delayed response (Non-Patent Document 15). It also increases the risk of slow driving, hesitant driving, and unexpected operational errors (Non-Patent Document 14). The cognitive function characteristic analysis unit 44 calculates the evaluation score Ed of the information processing ability 83 based on, for example, the braking reaction time, which is a driving operation, from the evaluation score E calculated by the cognitive function score calculation unit 43. For example, the braking timing is evaluated and calculated using the method of Non-Patent Document 16.

[0103] When visuospatial cognition 84 declines, the sense of distance to the vehicle ahead becomes distorted, and the driver may drift out of the lane when turning (Non-Patent Document 5). It also becomes difficult to grasp the relationship between the size of one's own vehicle and objects (Non-Patent Document 7). The cognitive function characteristic analysis unit 44 calculates the evaluation score Ee of visuospatial cognition 84 based on, for example, the average inter-vehicle distance and the number of lane departures from the evaluation score E calculated by the cognitive function score calculation unit 43. Measurement of vehicle behavior, such as the displacement of the vehicle position relative to the road, the displacement of the steering angle, and the pedal reaction time, uses, for example, the method described in Non-Patent Document 9. Methods for measuring the inter-vehicle distance include the method described in Non-Patent Document 10, and it may also be calculated using information detected by a general ADAS system.

[0104] It is efficient to calculate the evaluation scores Ea, Eb, Ec, Ed, and Ee for each cognitive function level based on, for example, a table created in advance that shows the relationship between the detection results of the driving state and the evaluation scores Ea, Eb, Ec, Ed, and Ee.

[0105] The cognitive function characteristic analysis unit 44 evaluates the degree of each of the driver's cognitive functions by comparing the evaluation scores Ea, Eb, Ec, Ed, and Ee calculated in this manner with the first threshold value Th1 and the second threshold value Th2 described above.

[0106] In this embodiment, the driver assistance device 10 determines that the driver's cognitive function is normal, i.e., safe, when the evaluation scores Ea, Eb, Ec, Ed, and Ee are greater than a first threshold value Th1. Furthermore, when the evaluation scores Ea, Eb, Ec, Ed, and Ee are smaller than the first threshold value Th1 and greater than a second threshold value Th2 that is smaller than the first threshold value Th1, the driver assistance device 10 determines that the corresponding cognitive function is in a caution-requiring state, requiring careful driving. Furthermore, when the evaluation scores Ea, Eb, Ec, Ed, and Ee are smaller than the second threshold value Th2, the driver assistance device 10 determines that the corresponding cognitive function is in a dangerous state, making it difficult to continue safe driving.

[0107] The cognitive function characteristic analysis unit 44 may analyze only the cognitive function currently calculated by the cognitive function score calculation unit 43, or may also analyze past cognitive functions associated with the driver and stored by the cognitive function storage unit 45. By performing an analysis including past cognitive functions, it is possible to estimate whether the cognitive function is on a recovery trend or a decline trend. Then, a training mode may be actively activated for cognitive functions that are on a recovery trend. Furthermore, if a long-term decline in cognitive function is observed, the training mode may be activated to prevent further decline.

[0108] Furthermore, depending on the driving environment of the vehicle 30, the events that are the subject of analysis by the cognitive function score calculation unit 43 and the cognitive function characteristic analysis unit 44 may not occur constantly. Therefore, the evaluation scores Ea, Eb, Ec, Ed, and Ee for all the target cognitive functions may not necessarily be obtained at the same time.

[0109] (Method for determining support content according to cognitive function level assessment score) A method for determining the content of assistance provided by the driver assistance device 10 in accordance with cognitive function characteristics will be described using Figures 9 and 10. Figure 9 is a first diagram illustrating an example of the content of assistance provided by the driver assistance device in accordance with cognitive function characteristics. Figure 10 is a second diagram illustrating an example of the content of assistance provided by the driver assistance device in accordance with cognitive function characteristics.

[0110] As shown in FIG. 9 , when the driver is in a state where he or she needs to pay attention to driving (attention level), the assistance content determination unit 48 assists in providing information to prevent further decline in the driver's cognitive function. That is, the assistance content determination unit 48 activates driving assistance by providing information (training mode). This is because the driver's cognitive function is not completely declined, and by continuing to drive while undergoing training related to the cognitive function, it is possible that the declined cognitive function can be restored to a normal level. For example, if the cognitive function decline is temporary, it is expected that cognitive function can be restored while receiving driving assistance. Furthermore, if the cognitive function decline is chronic, such as in a state known as mild cognitive impairment (MCI), which is a precursor to dementia, it is possible that cognitive function can be restored through such training. This training mode is expected to restore the cognitive function necessary for driving a vehicle, thereby enabling the driver to continue safe driving.

[0111] 9, when the cognitive function of the driver is at a dangerous level, the assistance content determination unit 48 activates a function that assists the corresponding cognitive function among the driving assistance functions provided in the vehicle 30. That is, the assistance content determination unit 48 activates driving assistance (driving assistance mode) using the driving assistance function.

[0112] Since the driver assistance device 10 evaluates the states of multiple cognitive function characteristics, there is a possibility that multiple cognitive functions will be determined to be at a caution level. In such a case, the assistance content determination unit 48 determines which cognitive functions to enable the training mode for and which cognitive functions to enable the driving assistance mode for. The assistance content determination unit 48 enables the training mode for only one of the cognitive functions. This is because simultaneously enabling the training modes for multiple cognitive functions may result in an increase in the amount of information presented, which may confuse the driver. Then, the assistance content determination unit 48 enables a driving assistance mode to support cognitive functions other than the cognitive function for which the training mode is enabled, among the multiple cognitive functions determined to be at a caution level. Furthermore, if the assistance content determination unit 48 determines that multiple cognitive functions are at a dangerous level, it enables the driving assistance mode for the corresponding multiple cognitive functions.

[0113] Next, specific details of the training mode and driving assistance mode related to each cognitive function will be described with reference to FIG.

[0114] When the memory 80 has deteriorated to a level requiring caution, the assistance content determination unit 48 operates, as a training mode, for example, a function of recognizing the contents of signs and outputting a message conveying the contents, a function of providing detailed route guidance, etc. This assists in the recovery of the memory 80 of the driver who is estimated to have deteriorated. Furthermore, when the memory 80 has deteriorated to a dangerous level, the assistance content determination unit 48 operates, for example, a traffic sign recognition function provided in the vehicle 30. Furthermore, the assistance content determination unit 48 may set an upper speed limit for the vehicle 30 based on the contents of the recognized traffic sign, for example, a speed limit. This makes it possible to reduce careless mistakes due to carelessness.

[0115] When the performance 81 has fallen to a level requiring caution, the assistance content determination unit 48 operates a training mode, for example, a function that outputs a message recommending early braking. This assists the driver in recovering the performance 81 that is estimated to have fallen. Furthermore, when the performance 81 has fallen to a dangerous level, the assistance content determination unit 48 operates functions provided in the vehicle 30, such as a rear-end collision warning function, a vehicle distance maintenance function, or a sudden acceleration prevention function. This makes it possible to assist the driver in performing some of his driving operations.

[0116] When the attentiveness 82 has decreased to a level requiring caution, the assistance content determination unit 48 operates a training mode, for example, a function that outputs guidance related to the driving environment or guidance related to driving behavior. This assists the driver, whose attentiveness 82 is estimated to have decreased, in recovering the driver's attentiveness 82. Furthermore, when the attentiveness 82 has decreased to a dangerous level, the assistance content determination unit 48 operates functions provided in the vehicle 30, such as a pedestrian detection function and a following distance maintenance function. This allows the vehicle 30 to take over part of the area in which the driver should pay attention.

[0117] When the information processing ability 83 has decreased to a level requiring caution, the assistance content determination unit 48 operates a training mode, for example, by slowing down the vehicle's speed to encourage the driver to be more attentive to pedestrians and the like, or by outputting a message encouraging the driver to take a break. This assists the driver in recovering the information processing ability 83 that is estimated to have decreased. Furthermore, when the information processing ability 83 has decreased to a dangerous level, the assistance content determination unit 48 operates functions provided in the vehicle 30, such as a function for maintaining a safe distance between vehicles and a collision warning. This allows the vehicle 30 to perform part of the information processing that should be performed by the driver.

[0118] When the visuospatial cognition ability 84 has decreased to a level requiring caution, the assistance content determination unit 48 operates, for example, a function that outputs guidance related to the driving environment as a training mode. This assists the recovery of the visuospatial cognition ability 84 of the driver that is estimated to have decreased. Furthermore, when the visuospatial cognition ability 84 has decreased to a dangerous level, the assistance content determination unit 48 operates a function such as a following distance maintenance function, a lane departure prevention function, or a parking assist function that the vehicle 30 is equipped with. This allows the vehicle 30 to perform part of the visuospatial cognition that should be performed by the driver.

[0119] The driver assistance device 10 continuously calculates the cognitive function even when various assistance modes are active, and stops the operation of the currently active assistance mode when the cognitive function returns to a normal level.

[0120] (Changes in cognitive function over time) Changes in cognitive function over time will be described with reference to Figures 11 and 12. Figure 11 is a diagram illustrating an example of factors that cause decline in cognitive function. Figure 12 is a diagram illustrating an example of changes in cognitive function over time.

[0121] The cognitive function of a driver is not always constant, but changes depending on various factors, such as aging factors 90, physical condition factors 91, and skill factors 92 shown in Figure 11.

[0122] Aging factor 90 is a factor associated with the driver's aging among factors that change cognitive function. As a driver ages, brain function declines. This can lead to a decline in cognitive function. Generally, the decline in physical function related to aging factor 90 progresses over a very long period of time. Therefore, for example, by comparing current cognitive function with that of several months or several years ago, it can be estimated that the decline in cognitive function due to aging factor 90 is progressing.

[0123] Physical condition factors 91 are factors associated with the driver's physical condition that can cause changes in cognitive function. Residual fatigue is likely to affect attention and executive function (Non-Patent Document 18). Other factors that fall under this category include a narrowing of the range of attention due to fatigue, a decline in memory (Non-Patent Document 19), and difficulty in maintaining concentration due to drowsiness (Non-Patent Document 19). Specific examples of physical condition factors 91 include factors related to illnesses such as depression and mental illnesses, factors related to physical conditions such as poor physical condition, stress, and drowsiness, and factors related to mental activities such as distraction and preoccupation. Changes in cognitive function due to physical condition factors 91 often fluctuate over intervals of a week or several days. Therefore, by monitoring changes in cognitive function over a relatively short period of time, it is possible to estimate that a decline in cognitive function due to physical condition factors 91 is occurring.

[0124] Skill factor 92 is a factor associated with the driver's driving skill, among factors that change cognitive function. Novice drivers tend to spend more time gazing at areas important for hazard prediction than experienced drivers (Non-Patent Document 20), and in road environments where there is a lot of information to process, their information processing ability and attention may decline. The occurrence of a change in cognitive function associated with skill factor 92 can be estimated, for example, by observing specific driving behaviors (e.g., driving behavior when turning right or left at an intersection, driving behavior when overtaking, driving behavior when parking). Furthermore, cognitive function associated with skill factor 92 also changes depending on the driving environment (e.g., road environment, weather, time of day or night).

[0125] Note that a driver's cognitive function does not fluctuate due to any one of aging factors 90, physical condition factors 91, and skill factors 92, but rather due to a combination of multiple factors. Factors other than those listed here also exist. For example, cognitive function fluctuates due to various factors, such as a high driving environment that can cause mental dizziness (Non-Patent Document 21). The driver assistance device 10 of this embodiment estimates the main factor among these factors. Although there are other possible factors that can cause fluctuations in a driver's cognitive function, the driver assistance device 10 of this embodiment assumes that fluctuations in a driver's cognitive function are caused by aging factors 90, physical condition factors 91, and skill factors 92. Note that, although three factors are selected here, factors other than those listed here may also be evaluated. Factors that cause cognitive decline may also be broken down using a different approach. Furthermore, attention may be focused on only one factor of interest, or any combination of two or more factors.

[0126] Next, the fluctuation of a driver's cognitive function will be qualitatively explained using Fig. 12. Graph G1 in Fig. 12 is a graph showing an example of time-series changes in the evaluation score E of a certain driver's cognitive function level. Graph G1 shows that the evaluation score E decreases around time ta and around time tc, falling below the second threshold value Th2. In other words, it can be seen that the risk of an accident increases around time ta and around time tc.

[0127] Graph G2 is an example of the amount of cognitive decline due to aging for the same driver, plotted on the same time axis as graph G1. Graph G3 is an example of the amount of cognitive decline due to physical condition for the same driver, plotted on the same time axis as graph G1. Graph G4 is an example of the amount of cognitive decline due to skill for the same driver, plotted on the same time axis as graph G1.

[0128] The vertical axis of graph G2 indicates the degree of cognitive decline due to aging, with the downward movement along the vertical axis indicating a greater degree of cognitive decline due to aging. Graph G2 shows that, after time tb, the degree of cognitive decline due to aging exceeds the threshold Tha that affects safe driving. In such cases, it is desirable to urge the driver to take daily precautions after time tb.

[0129] The vertical axis of graph G3 indicates the degree of cognitive decline due to physical condition, with the degree of cognitive decline increasing as one moves downward along the vertical axis. Graph G3 shows that, around time tc, the degree of cognitive decline due to the driver's physical condition exceeds the threshold Thb that affects safe driving and reaches a maximum. Comparing graph G3 with graph G1, it can be seen that the decline in cognitive function around time tc is primarily due to physical condition. In such cases, it is desirable to have the driver rest around time tc to encourage recovery.

[0130] The vertical axis of graph G4 indicates the degree of cognitive decline due to skill, with the downward movement along the vertical axis indicating a greater degree of cognitive decline due to skill. Graph G4 shows that the degree of cognitive decline due to the driver's driving skill exceeds the threshold Thc that affects safe driving at the time shown in graph G4. This indicates that the road environment of the section shown in graph G4 is likely to be a road environment that the driver finds difficult. Furthermore, it can be seen that around time ta, the degree of cognitive decline due to the driver's skill exceeds the threshold Thc that affects safe driving and reaches a maximum. Comparing graph G4 with graph G1 reveals that the decline in cognitive function around time ta is primarily due to skill. In such cases, it is desirable to warn the driver about roads that are difficult for the driver around time ta.

[0131] In this way, the driver assistance device 10 of this embodiment estimates whether the primary cause of the decline in cognitive function is aging, physical condition, or skill, and then provides appropriate information and driving assistance depending on the primary cause of the decline in cognitive function to promote recovery of cognitive function.

[0132] (Estimation of the main cause of cognitive decline) The factor analysis of cognitive decline will be described with reference to Figures 13A and 13B. Figure 13A is a first diagram showing an example of the factor analysis of cognitive decline. Figure 13B is a second diagram showing an example of the factor analysis of cognitive decline.

[0133] As explained in Figure 12, a driver's cognitive function constantly changes over time. Figure 13A shows an example of comparing the current (April 2022) cognitive function with the cognitive function one year ago (April 2021). Figure 13A shows that the cognitive function level assessment score E was at a safe level above the first threshold Th1 one year ago, but is now between the first threshold Th1 and the second threshold Th2, i.e., a level requiring caution.

[0134] When the evaluation score E of the driver's cognitive function level declines in this manner, the cognitive function decline factor estimation unit 46 of the driver assistance device 10 of this embodiment estimates whether the main factor is an aging factor (first variation factor), a physical condition factor (second variation factor), or a skill factor (third variation factor).

[0135] 13B shows an example of a factor analysis of cognitive decline. The cognitive decline factor estimation unit 46 compares the evaluation value of cognitive function related to aging factors one year ago with the evaluation value of cognitive function related to current aging factors. As a result, it is determined that the cognitive function related to aging factors has declined compared to one year ago. That is, as indicated by the left-pointing arrow in FIG. 13B, it is determined that the cognitive function related to aging factors (first variable factor) has declined.

[0136] Furthermore, the cognitive function decline factor estimation unit 46 compares the evaluation value of the cognitive function related to the physical condition factor one year ago with the evaluation value of the cognitive function related to the current physical condition factor. As a result, it is determined that the cognitive function related to the physical condition factor has significantly declined compared to one year ago and exceeds the threshold value Thb that affects safe driving. That is, as shown by the long left-pointing arrow in Fig. 13B, it is determined that the cognitive function related to the physical condition factor (second variation factor) has significantly declined.

[0137] Furthermore, the cognitive function decline factor estimation unit 46 compares the evaluation value of the cognitive function related to the skill factor one year ago with the evaluation value of the cognitive function related to the current skill factor. As a result, it is determined that the cognitive function related to the skill factor has improved compared to one year ago. That is, as shown by the short right-facing arrow in FIG. 13B, it is determined that the cognitive function related to the skill factor (third variation factor) has improved. Note that in FIG. 13B, the thresholds Tha, Thb, and Thc are written in the same position for convenience, but in reality, these thresholds have different values.

[0138] Based on the results of FIG. 13B , the cognitive function decline factor estimation unit 46 estimates that the main cause of the cognitive decline is the physical condition factor, which has the longest left-facing arrow. Then, the support content determination unit 48 determines to present information related to the main cause of the cognitive decline, such as, for example, "Your physical condition factor score is rapidly declining. Please take a break." The support content display unit 49 displays the information on, for example, the center monitor 25a, thereby encouraging the driver to change their behavior in accordance with the main cause of the cognitive decline.

[0139] When the estimation results of FIG. 13B are superimposed on FIG. 13A and the current cognitive function is compared with that of one year ago, it can be seen that cognitive function related to aging and physical condition factors has declined, while skill factors have improved. It can also be seen that the decline in cognitive function due to physical condition factors is greater than the decline in cognitive function due to aging factors. Note that, although an example of comparing the current cognitive function with that of one year ago is shown here, the timing of the comparison is not limited to one year ago.

[0140] (Identifying fluctuating cognitive functions) A method for identifying the fluctuation state of a driver's cognitive function will be described with reference to Fig. 14. Fig. 14 is a diagram showing an example of a method for identifying a state of decline in cognitive function. Fig. 14 shows the flow of the process for identifying the fluctuation state of a driver's cognitive function, which is performed by the cognitive function decline factor estimation unit 46 of the driver assistance device 10 of this embodiment. Here, it is assumed that the factors that cause fluctuations in cognitive function are aging factors, physical condition factors, and skill factors.

[0141] The cognitive decline factor estimation unit 46 determines whether the amount of cognitive decline due to aging is below the threshold Tha (step S61). If it is determined that the amount of cognitive decline due to aging is below the threshold Tha (step S61: Yes), the process proceeds to step S62. On the other hand, if it is not determined that the amount of cognitive decline due to aging is below the threshold Tha (step S61: No), the process proceeds to step S65.

[0142] In step S61, if it is determined that the amount of cognitive decline due to aging is below the threshold Tha, the cognitive decline factor estimation unit 46 determines whether the amount of cognitive decline due to skill factors is below the threshold Thc (step S62). If it is determined that the amount of cognitive decline due to skill factors is below the threshold Thc (step S62: Yes), the process proceeds to step S63. On the other hand, if it is not determined that the amount of cognitive decline due to skill factors is below the threshold Thc (step S62: No), the process proceeds to step S64.

[0143] If it is determined in step S62 that the amount of cognitive decline due to skill factors is below the threshold Thc, the cognitive decline factor estimation unit 46 determines whether the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S63). If it is determined that the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S63: Yes), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function is normal (state 1) (step S68). On the other hand, if it is not determined that the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S63: No), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function has declined due to physical condition factors (state 2) (step S69).

[0144] If it is determined in step S62 that the amount of cognitive decline due to skill factors is not below the threshold Thc, the cognitive decline factor estimation unit 46 determines whether the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S64). If it is determined that the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S64: Yes), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function has declined due to skill factors (state 3) (step S70). On the other hand, if it is not determined that the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S64: No), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function has declined due to physical condition factors and skill factors (state 4) (step S71).

[0145] In step S61, if it is determined that the amount of cognitive decline due to aging is not below the threshold Tha, the cognitive decline factor estimation unit 46 determines whether the amount of cognitive decline due to skill factors is below the threshold Thc (step S65). If it is determined that the amount of cognitive decline due to skill factors is below the threshold Thc (step S65: Yes), the process proceeds to step S66. On the other hand, if it is not determined that the amount of cognitive decline due to skill factors is below the threshold Thc (step S65: No), the process proceeds to step S67.

[0146] If it is determined in step S65 that the amount of cognitive decline due to skill factors is below the threshold Thc, the cognitive decline factor estimation unit 46 determines whether the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S66). If it is determined that the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S66: Yes), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function has declined due to aging factors (state 5) (step S72). On the other hand, if it is not determined that the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S66: No), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function has declined due to aging factors and physical condition factors (state 6) (step S73).

[0147] If it is determined in step S65 that the amount of cognitive decline due to skill factors is not below the threshold Thc, the cognitive decline factor estimation unit 46 determines whether the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S67). If it is determined that the amount of cognitive decline due to physical condition factors is below the threshold Thb (step S67: Yes), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function has declined due to aging factors and skill factors (state 7) (step S74). On the other hand, if it is determined that the amount of cognitive decline due to physical condition factors is not below the threshold Thb (step S67: No), the cognitive decline factor estimation unit 46 determines that the driver's cognitive function has declined due to aging factors, skill factors, and physical condition factors (state 8) (step S75).

[0148] (State transition of cognitive function level) An example of state transition of the driver's cognitive function level will be described with reference to Fig. 15. Fig. 15 is a diagram showing an example of temporal change in the driver's cognitive function level.

[0149] The driver assistance device 10 of this embodiment monitors fluctuations in the driver's cognitive function over time. As a result, a transition diagram showing the fluctuation state of the cognitive function is generated, as shown in FIG. 15. The vertical axis of FIG. 15 indicates the state of the cognitive function before the fluctuation. States 1 to 8 described in FIG. 14 are plotted on the vertical axis. The horizontal axis of FIG. 15 indicates the state of the cognitive function after the fluctuation. States 1 to 8 described in FIG. 14 are also plotted on the horizontal axis.

[0150] Because the state of the driver's cognitive function fluctuates over time, the driver assistance device 10 observes the transition from state m (m = 1 to 8) one time before to state n (n = 1 to 8) one time after. When it is determined that the state has transitioned from state m to state n, the state of change in the cognitive function fluctuation factors at that time is identified. The contents written in each item in Figure 15 indicate the state of change in the cognitive function fluctuation factors. For convenience, lowercase identifiers ((a) to (c)) are used to indicate areas where the fluctuation factors have worsened, and uppercase identifiers ((A) to (C)) are used to indicate areas where the fluctuation factors have improved.

[0151] For example, if the state one time ago was State 2 and the current state is State 7, the driver assistance device 10 determines that the aging factor and skill factor, among the factors that cause fluctuations in the driver's cognitive function, have deteriorated. The driver assistance device 10 also determines that the physical condition factor, among the factors that cause fluctuations in the driver's cognitive function, has improved.

[0152] The driver support device 10 presents the driver with information according to the fluctuation state of the cognitive function shown in FIG. 15, thereby encouraging the driver to change his / her behavior, particularly when the cognitive function has deteriorated.

[0153] (Providing information according to fluctuations in cognitive function) An example of information presentation according to a change in the cognitive function of the driver will be described with reference to Fig. 16. Fig. 16 is a diagram showing an example of information presentation content according to a change in the cognitive function level.

[0154] As shown in FIG. 16 , the driver assistance device 10 of this embodiment presents the driver with information corresponding to at least the current state m (m = 1 to 8). In this case, the driver assistance device 10 presents information related to the main cause of the decline in cognitive function and what the driver should pay attention to when driving. Although not shown in FIG. 16 , the driver assistance device 10 preferably presents information corresponding to the driver's past and current cognitive function levels. For example, if an improvement in cognitive function is observed, it is preferable to convey the effect of the driver's behavioral change by presenting information related to the variable factors that led to the improvement. Furthermore, if the deterioration in cognitive function continues, the driver assistance device 10 preferably provides further attention or recommends the operation of a driving assistance function.

[0155] (Example of information presentation (aging factors)) An example of information presented to a driver when aging is the main cause will be described with reference to Fig. 17. Fig. 17 is a diagram showing an example of information presented to a driver when aging is the main cause of cognitive decline.

[0156] When the primary cause of cognitive decline is aging, the driver assistance device 10 notifies the driver that cognitive decline due to aging is occurring. The driver is then encouraged to undergo recovery training. After the driver has finished driving, the device informs the driver of changes in cognitive decline due to aging, i.e., the degree of daily improvement. Note that if the cognitive decline due to aging improves and the improvement continues for, for example, several days or more, the device stops presenting information related to aging.

[0157] Specifically, as shown in FIG. 17, if a state in which no decline in cognitive function due to aging is observed continues (state transition A in FIG. 17), information related to aging is not presented.

[0158] When cognitive function deteriorates from a good state to a state that affects driving due to aging factors (state transition B in Figure 17), information such as "A decline in the aging factor score has been observed. We recommend that you conduct recovery training" is displayed. This makes the driver aware that cognitive function is declining due to aging.

[0159] When the decline in cognitive function due to aging has improved (state transition C in Figure 17), information such as "Your aging-related score has improved. It appears that your recovery training has been effective" is presented, allowing the driver to recognize that their cognitive function has improved.

[0160] If the decline in cognitive function due to aging continues (state transition D in Figure 17), information such as "Your aging-related score continues to decline. Continue your recovery training" is displayed, making the driver aware that the decline in cognitive function due to aging is not improving.

[0161] Furthermore, by continuously monitoring the decline in cognitive function due to aging, the driver's risk of dementia can be determined. Therefore, if the decline in cognitive function due to aging continues, in addition to the various information presented in Figure 17, a notification that there is a risk of dementia may be provided.

[0162] (Example of information presentation (health factors)) An example of information presented to the driver when a physical condition factor is the main factor will be described with reference to Fig. 18. Fig. 18 is a diagram showing an example of information presented to the driver when a physical condition factor is the main factor of cognitive decline.

[0163] When the primary cause of cognitive decline is physical condition, the driver assistance device 10 displays a message to the driver to make him / her aware of his / her poor physical condition and the impact it has on his / her driving. It also urges him / her to take a break or drive carefully as necessary.

[0164] Specifically, as shown in FIG. 18, if a state in which no decline in cognitive function due to physical condition factors is observed continues (state transition E in FIG. 18), information related to physical condition factors is not presented.

[0165] When cognitive function deteriorates from a good state to a state that affects driving due to physical condition factors (state transition F in Figure 18), information such as "Your physical condition factor score is decreasing. Drive more carefully than usual" is presented, making the driver aware that their physical condition is deteriorating.

[0166] When the decline in cognitive function due to physical condition factors improves (state transition G in Figure 18), information such as "Your physical condition factor score has improved. Please continue driving safely" is displayed, allowing the driver to recognize that their cognitive function has improved.

[0167] If the decline in cognitive function due to physical condition factors continues (state transition H in Figure 18), information such as "Your physical condition factor score is declining, which is affecting safe driving. We recommend you take a break" is displayed. This makes the driver aware that the decline in cognitive function due to physical condition factors is not improving.

[0168] (Example of information presentation (skill factors)) An example of information presented to a driver when a skill factor is the main factor will be described with reference to Fig. 19. Fig. 19 is a diagram showing an example of information presented to a driver when a skill factor is the main factor of cognitive decline.

[0169] When the main cause of cognitive decline is a skill factor, the driver assistance device 10 presents the driver with a message to make the driver aware of the impact on driving.

[0170] Specifically, as shown in FIG. 19, if a state in which no decline in cognitive function due to skill factors is observed continues (state transition I in FIG. 19), information related to skill factors is not presented.

[0171] When cognitive function deteriorates from a good state to a state that affects driving due to skill factors (state transition J in Figure 19), information such as "Your driving skills are declining. Drive carefully and do not become overconfident." is presented. This makes the driver aware that their driving skills are declining. It also urges them not to become overconfident in their own driving skills.

[0172] When the decline in cognitive function due to skill factors improves (state transition K in Figure 19), information such as "Your driving skills have improved. Please continue to drive safely" is presented, helping the driver recognize that their cognitive function has improved.

[0173] If the decline in cognitive function due to skill factors continues (state transition L in Figure 19), information such as "Your driving skills are declining. Please be careful to drive safely" is presented. This makes the driver aware that the decline in cognitive function due to skill factors is not improving.

[0174] If it is known based on the results of an analysis of the driver's past cognitive functions that the driver is not good at driving in certain driving environments (such as turning right at an intersection, driving in a busy area, or parking), information indicating that the road is difficult to drive may be presented in advance. Also, while the driver is driving on a road that the driver is not good at, a proposal may be made to provide support through driving assistance. Furthermore, when the driver starts driving, information about the destination may be obtained from the driver and a proposal may be made to change the route to avoid roads that the driver is not good at. Information related to skill factors may be presented to the driver before, during, or after the start of driving.

[0175] For example, if there is a road environment along the route that requires assistance before starting driving, information such as "Please be especially careful when turning right" may be presented.

[0176] Furthermore, if there is a road environment that requires assistance while driving, information such as "There is a merging area ahead. Would you like to activate merging assistance?" may be presented.

[0177] In addition, after the drive is completed, the driver may be given a summary of the drive, with information such as "Please be careful when turning right at XX intersection," or "Recently, your cognitive function has tended to decline when driving through intersections, so please be careful."

[0178] The skill factors not only fluctuate in the short term depending on the road environment on which the vehicle is currently traveling, but also fluctuate over the long term depending on the driver's level of driving proficiency. Therefore, the state transition shown in Figure 19 may compare the evaluation value of the driver's driving skill when the driver was younger (when the driver obtained his / her driver's license) with the evaluation value of the driver's current driving skill.

[0179] (Method of calculating factors of cognitive decline (aging factors)) A method for calculating the influence of aging factors on the decline in cognitive function will be described with reference to Fig. 20. Fig. 20 is a diagram showing an example of a method for calculating the degree of influence of aging factors on the decline in cognitive function.

[0180] The cognitive function decline factor estimation unit 46 of the driver assistance device 10 calculates evaluation values ​​for aging factors, physical condition factors, and skill factors, which are factors that cause fluctuations in cognitive function, using separate, independent methods. The evaluation value for aging factors is calculated by, for example, comparing the fluctuations in cognitive function of the same driver over the past month one year ago with the fluctuations in cognitive function over the most recent month, thereby calculating changes in cognitive function due to aging factors.

[0181] Specifically, as shown in Figure 20, the current (e.g., April 2022) fluctuation in cognitive function is compared with the fluctuation in cognitive function one year ago (e.g., April 2021). The fluctuation in cognitive function for a certain month is calculated, for example, by averaging the cognitive function assessment results for each day of that month. Note that, since cognitive function assessment values ​​cannot be obtained on days when driving is not performed, the cognitive function assessment values ​​for days when driving is performed can be averaged over the number of days when driving was performed.

[0182] 20 shows that the current average value of cognitive function has declined compared to one year ago. In this way, the cognitive function decline factor estimation unit 46 of the driver assistance device 10 performs evaluation on the assumption that long-term fluctuations in cognitive function are due to aging factors.

[0183] (Calculation method for factors of cognitive decline (physical condition factors)) The cognitive decline factor estimation unit 46 of the driver assistance device 10 calculates an evaluation value related to a physical condition factor based on the number of blinks and eye movement of the driver, or the driver's body temperature, etc., measured by the driver monitor camera 21b mounted on the vehicle 30. Alternatively, the evaluation may be based on the output of a sensor (not shown) that measures an electrocardiogram, pulse wave, etc., installed on the steering wheel of the vehicle 30 (Non-Patent Document 17).

[0184] The cognitive function score calculation unit 43 calculates the evaluation score E of the driver's cognitive function level from the information obtained by these various sensors. Then, the cognitive function decline factor estimation unit 46 determines that the fluctuation in the cognitive function level evaluation score E calculated in this manner is due to factors related to the driver's physical condition.

[0185] (Calculation method for factors of cognitive decline (skill factors)) The cognitive function decline factor estimation unit 46 of the driver assistance device 10 calculates an evaluation value related to the skill factor based on the behavior of the vehicle 30 that appears as a result of the driving operation.

[0186] For example, for basic driving behavior (driving straight, driving around curves, braking, etc.), an evaluation value related to the driver's skill factors can be calculated based on the difference between the average or preferred movement pattern and the movement pattern actually performed by the driver.

[0187] More specifically, the road environment on which vehicle 30 is traveling can be recognized by the car navigation device and surrounding cameras equipped in vehicle 30, so an evaluation value related to driving skills can be calculated for each traffic environment (when going straight, when changing lanes, when turning right or left, when parking, etc.).

[0188] (Another method for calculating the causes of cognitive decline) Another method for calculating the causes of cognitive decline will be described with reference to Fig. 21. Fig. 21 is a flowchart showing an example of another method for estimating the causes of cognitive decline.

[0189] The cognitive function decline factor estimation unit 46 of the driver assistance device 10 may calculate the evaluation values ​​for the aging factor, physical condition factor, and skill factor, which are factors that cause cognitive function fluctuations, using a method other than the method described above. Specifically, when comparing the aging factor, physical condition factor, and skill factor, which are factors that cause cognitive function decline, the aging factor is considered to have a gradual effect over a long period of time (e.g., years). Furthermore, the physical condition factor is considered to have an effect in a shorter period of time (e.g., months or weeks) than the aging factor. Furthermore, the skill factor is considered to have an effect depending on the road environment on which the vehicle is traveling at the time. Therefore, by setting the period for averaging the evaluation values ​​for cognitive function to a period corresponding to each factor, the degree of impact of each factor on cognitive function can be easily quantified.

[0190] More specifically, the maximum value Lmax of the driver's cognitive function level and the cognitive function level L(t) at each time t are acquired. The cognitive function level L(t) is equivalent to the cognitive function level evaluation score E described above. The cognitive function decline factor estimation unit 46 calculates the average value Lminute(t) (third average value) of the acquired cognitive function level L(t) for the past minute (third predetermined period), the average value Lhour(t) (second average value) for the past hour (second predetermined period), and the average value Lmonth(t) (first average value) for the past month (first predetermined period). Then, the cognitive function decline factor estimation unit 46 estimates the difference between the maximum value Lmax of the cognitive function level and the average value Lmonth(t) of the cognitive function level for the past month as the fluctuation amount ΔLage of cognitive function due to aging. The cognitive function decline factor estimation unit 46 also estimates the difference between the average cognitive function level for the past hour Lhour(t) and the average cognitive function level for the past month Lmоnth(t) as the amount of cognitive function fluctuation ΔLhealth due to physical condition factors. Furthermore, the cognitive function decline factor estimation unit 46 estimates the difference between the cognitive function level L(t) at time t and the sum of the maximum cognitive function level Lmax, the amount of cognitive function fluctuation due to aging factors, the amount of cognitive function fluctuation ΔLage, and the amount of cognitive function fluctuation ΔLhealth due to physical condition factors as the amount of cognitive function fluctuation due to skill factors.

[0191] The flow of processing for estimating the cause of cognitive decline will be described below with reference to the flowchart in FIG.

[0192] The cognitive function decline factor estimation unit 46 acquires the maximum value Lmax of the cognitive function level of the driver (step S21). Specifically, the cognitive function decline factor estimation unit 46 acquires the maximum value of the cognitive function level L(t) of the corresponding driver stored in the cognitive function storage unit 45.

[0193] The cognitive function score calculation unit 43 calculates the cognitive function level L(t) at time t (step S22).

[0194] The cognitive decline factor estimation unit 46 calculates the average value Lminute(t) of the cognitive function level L(t) for the past minute (step S23).

[0195] The cognitive function decline factor estimation unit 46 calculates the average value Lhour(t) of the cognitive function level L(t) for the past hour (step S24).

[0196] The cognitive decline factor estimation unit 46 calculates the average value Lmоnth(t) of the cognitive function level L(t) for the past month (step S25).

[0197] The cognitive function decline factor estimation unit 46 estimates a change in cognitive function due to aging (step S26). Specifically, the cognitive function decline factor estimation unit 46 estimates the amount of fluctuation ΔLage in cognitive function due to aging using equation (1). Although not shown in the flowchart, the estimated amount of fluctuation ΔLage in cognitive function due to aging is stored in the cognitive function storage unit 45 in association with information identifying the driver.

[0198] ΔLage = Lmоnth(t) - Lmax…(1)

[0199] The cognitive function decline factor estimation unit 46 estimates a change in cognitive function due to physical condition factors (step S27). Specifically, the cognitive function decline factor estimation unit 46 estimates the amount of fluctuation in cognitive function due to physical condition factors, ΔLhealth, using equation (2). Although not shown in the flowchart, the estimated amount of fluctuation in cognitive function due to physical condition factors, ΔLhealth, is stored in the cognitive function storage unit 45 in association with information identifying the driver.

[0200] ΔLhealth=Lhour(t)-Lmonth(t)…(2)

[0201] The cognitive function decline factor estimation unit 46 estimates the change in cognitive function due to skill factors (step S28). Specifically, the cognitive function decline factor estimation unit 46 estimates the amount of fluctuation in cognitive function due to skill factors, ΔLskill, using equation (3). Although not shown in the flowchart, the estimated amount of fluctuation in cognitive function due to skill factors, ΔLskill, is associated with information identifying the driver and stored in the cognitive function storage unit 45. Note that, because skill factors are significantly affected by the road environment on which the driver is traveling at the time, it is desirable for the driver assistance device 10 to acquire information related to the road environment, for example, for the past one minute, from a car navigation system, surrounding cameras, etc., and store the acquired information related to the road environment in the cognitive function storage unit 45.

[0202] ΔLskill=Lminute(t)-(Lmax+ΔLage+ΔLhealth)…(3)

[0203] The cognitive function decline factor estimation unit 46 estimates the main factor of the decline in cognitive function level L(t) by comparing the magnitude of the cognitive function fluctuation ΔLage due to aging factors, the magnitude of the cognitive function fluctuation ΔLhealth due to physical condition factors, and the magnitude of the cognitive function fluctuation ΔLskill due to skill factors (step S29). Thereafter, the cognitive function decline factor estimation unit 46 ends the processing of FIG.

[0204] (Processing flow performed by the driver assistance device) The flow of processing performed by the driver assistance device 10 of this embodiment will be described with reference to Fig. 22. Fig. 22 is a flowchart showing an example of the flow of processing performed by the driver assistance device of this embodiment.

[0205] The driving state detection unit 42 determines whether the ignition switch of the vehicle 30 is ON (step S41). If it is determined that the ignition switch of the vehicle 30 is ON (step S41: Yes), the process proceeds to step S42. On the other hand, if it is not determined that the ignition switch of the vehicle 30 is ON (step S41: No), the determination of step S41 is repeated. Note that if the vehicle 30 is an electric vehicle, instead of determining whether the ignition switch is ON, it is sufficient to determine whether the main switch is ON.

[0206] If it is determined in step S41 that the ignition switch of the vehicle 30 is ON, the driver identification unit 41 identifies the driver (step S42).

[0207] The cognitive function score calculation unit 43 performs a pre-driving cognitive function assessment on the driver (step S43). The pre-driving cognitive function assessment, for example, reads out past cognitive function assessment results of the driver stored in the cognitive function storage unit 45 and acquires the transition of the driver's cognitive function over time. In addition, the cognitive function is assessed based on the driver's physical condition information before driving by acquiring outputs from sensors that measure the driver's body temperature, electrocardiogram, pulse wave, etc.

[0208] The cognitive function characteristic output unit 47 presents the result of the evaluation made in step S43 to the driver (step S44).

[0209] The driving state detection unit 42 determines whether driving of the vehicle 30 has started (step S45). If it is determined that driving of the vehicle 30 has started (step S45: Yes), the process proceeds to step S46. On the other hand, if it is not determined that driving of the vehicle 30 has started (step S45: No), the determination of step S45 is repeated.

[0210] The cognitive function score calculation unit 43 and the cognitive function characteristic analysis unit 44 perform a cognitive function evaluation on the driver while driving (step S46). The cognitive function evaluation while driving is performed, for example, according to the flowchart of FIG.

[0211] The cognitive function storage unit 45 stores the analysis result in step S46 in association with information that identifies the driver (step S47).

[0212] The cognitive function characteristic analysis unit 44 determines whether the cognitive function level evaluation score E (or cognitive function level L(t)) calculated in step S46 is at a caution level or a dangerous level (step S48). If the cognitive function level evaluation score E is determined to be at a caution level or a dangerous level (step S48: Yes), the process proceeds to step S49. On the other hand, if the cognitive function level evaluation score E is not determined to be at a caution level or a dangerous level (step S48: No), the process proceeds to step S51.

[0213] In step S48, when the assessment score E of the cognitive function level is determined to be at a caution level or a dangerous level, the cognitive function decline factor estimation unit 46 estimates the main cause of the cognitive function decline (step S49). The estimation of the main cause of the cognitive function decline is performed, for example, according to the flowchart of FIG. 21.

[0214] The cognitive function characteristic output unit 47 presents information according to the main cause of the decline in cognitive function to the driver (step S50). Examples of the information to be presented are as described in FIGS. 16 to 19. In step S50, the cognitive function characteristic output unit 47 may output the state of the driver's cognitive function to a pre-registered smartphone, wearable device, or the like via the communication interface 27 (see FIG. 3). Referencing the information output in this manner can be useful for the driver's daily health management and lifestyle management.

[0215] The driving state detection unit 42 determines whether the ignition switch of the vehicle 30 is OFF (step S51). If it is determined that the ignition switch of the vehicle 30 is OFF (step S51: Yes), the driver assistance device 10 ends the processing of Fig. 22. On the other hand, if it is not determined that the ignition switch of the vehicle 30 is OFF (step S51: No), the process returns to step S46.

[0216] (Training mode and driving assistance mode for cognitive decline) The driver assistance device 10 of this embodiment may present information related to the main cause of the decline in cognitive function when transitioning to the training mode or the driving assistance mode. Fig. 23 is a diagram illustrating a function of presenting information related to the main cause of the decline in cognitive function when the driver assistance device changes the operation mode.

[0217] When the assistance content determination unit 48 of the driver assistance device 10 decides to operate the training mode to suppress further deterioration of the driver's cognitive function characteristics, the assistance information presentation unit 50 may present to the driver the main cause of the deterioration of the cognitive function.

[0218] For example, as shown in Fig. 23, when it is detected that attention, one of the cognitive functions, has declined to a level requiring caution, the driver assistance device 10 decides to improve the driver's attention function by activating the training mode. At this time, if the driver's cognitive function has declined due to a physical condition factor, the assistance information presenting unit 50 presents to the driver information related to the main cause of the decline in cognitive function, i.e., information to make the driver aware of poor physical condition and urge caution, such as, for example, "The physical condition factor score has declined and attention has declined. Recovery training will begin."

[0219] In addition, when the assistance content determination unit 48 of the driver assistance device 10 decides to operate the driving assistance mode to assist driving operations associated with cognitive function characteristics, the assistance information presentation unit 50 may present the main cause of the decline in cognitive function to the driver.

[0220] For example, as shown in Fig. 23, when it is detected that attention, one of the cognitive functions, has declined to a level requiring caution, the driver assistance device 10 decides to compensate for the decline in the driver's cognitive function related to attention by activating the driving assistance mode. At this time, if the driver's cognitive function has declined due to a physical condition factor, the assistance information presenting unit 50 presents to the driver information related to the main cause of the decline in cognitive function, such as, for example, "The physical condition factor score has further declined. Driving assistance related to attention will be turned on."

[0221] The driver assistance device 10 presents the driver with information relating to the main cause of the decline in cognitive function at the timing of transition to the training mode or the driving assistance mode.

[0222] (Effects of the embodiment) As described above, the driver assistance device 10 of this embodiment includes a driving state detection unit 42 that detects at least one of the driver's driving behavior, the driver's biological information while driving, and the behavior of the vehicle 30, a cognitive function score calculation unit 43 that calculates a numerical value indicating whether the driver's cognitive function is high or low based on the information detected by the driving state detection unit 42, a cognitive function characteristic analysis unit 44 that analyzes the numerical value calculated by the cognitive function score calculation unit 43 as a cognitive function characteristic related to one or more different brain functions, a cognitive function memory unit 45 that chronologically stores the numerical values ​​calculated by the cognitive function score calculation unit 43 for the same driver and the analysis results of the cognitive function characteristic analysis unit 44, a cognitive function decline factor estimation unit 46 that calculates the influence of multiple variable factors that cause a decline in the driver's cognitive function based on the contents stored in the cognitive function memory unit 45 and estimates the main factor, and a driver assistance unit 60 that assists the driver based on the estimation results by the cognitive function decline factor estimation unit 46 or information corresponding to the estimation results. Therefore, the factors of the decline in the driver's cognitive function can be estimated.

[0223] Furthermore, in the driver assistance device 10 of this embodiment, the cognitive function decline factor estimation unit 46 estimates factors that cause fluctuations in cognitive function by comparing the current stored content of the cognitive function storage unit 45 with the stored content corresponding to a predetermined past point in time. Therefore, fluctuations in the driver's cognitive state can be estimated easily and with high accuracy based on the chronological information related to cognitive function.

[0224] Furthermore, in the driver assistance device 10 of this embodiment, the variation factors include at least one of a driver's aging factor 90, a physical condition factor 91, and a skill factor 92. Therefore, the variation factors of the driver's cognitive function can be estimated in association with the physical or mental state of the driver.

[0225] Furthermore, in the driver assistance device 10 of this embodiment, the driver assistance unit 60 includes a cognitive function characteristic output unit 47 (output unit) that outputs information according to the estimation result of the cognitive function decline factor estimation unit 46 in a form according to past values ​​related to the main factors that cause the decline in the driver's cognitive function and current values ​​related to the main factors. Therefore, when the cognitive function declines, the driver can be made to accurately recognize his or her own condition by presenting information according to the amount of decline.

[0226] Furthermore, in the driver assistance device 10 of this embodiment, when the aging factor 90 is the main factor causing the decline in the driver's cognitive function, the cognitive function characteristic output unit 47 (output unit) outputs to the driver information indicating that the driver has a decline in cognitive function due to aging or information related to recovery training for the decline in cognitive function due to aging. Therefore, it is possible to reliably inform the driver that the decline in cognitive function is due to aging.

[0227] Furthermore, in the driver assistance device 10 of this embodiment, when the physical condition factor 91 is the main factor causing the decline in the driver's cognitive function, the cognitive function characteristic output unit 47 (output unit) outputs information to the driver to make him / her aware of his / her poor physical condition and urge him / her to take a break, or information to urge him / her to take a rest. Therefore, it is possible to reliably inform the driver that his / her cognitive function is declining due to his / her physical condition.

[0228] Furthermore, in the driver assistance device 10 of this embodiment, when the skill factor 92 is the main factor causing the decline in the driver's cognitive function, the cognitive function characteristic output unit 47 (output unit) outputs information indicating that the road condition is difficult for the driver or suggests a route change that avoids the road that is difficult for the driver. Therefore, it is possible to reliably notify the driver that the decline in cognitive function is caused by driving skill.

[0229] Furthermore, in the driver assistance device 10 of this embodiment, the driver assistance unit 60 further includes an assistance content determination unit 48 that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit 44 and a threshold, whether to enable an information provision function that assists in providing information to suppress further decline in the driver's cognitive function, or a driving assistance function that assists in driving behavior associated with the declined cognitive function characteristics, from among multiple functions possessed by the vehicle 30, and the cognitive function characteristic output unit 47 (output unit) outputs the estimation result by the cognitive function decline factor estimation unit 46 or information corresponding to the estimation result, when the assistance function determined by the assistance content determination unit 48 becomes enabled. Therefore, the reason for transitioning to the training mode or the driving assistance mode can be reliably communicated to the driver.

[0230] Furthermore, in the driver assistance device 10 of this embodiment, the driver assistance unit 60 further includes an assistance content determination unit 48 that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit 44 and a threshold, whether to enable an information provision function that assists in providing information to suppress further decline in the driver's cognitive function, or a driving assistance function that assists in driving behavior associated with the declined cognitive function characteristics, from among multiple functions possessed by the vehicle 30. The assistance content determination unit 48 provides assistance to the driver when a road condition that is difficult for the driver, extracted in accordance with the estimation result of the skill factor by the cognitive function decline factor estimation unit 46, is on the driving route. Therefore, driving support can be provided when traveling on a road that the driver is difficult for.

[0231] Furthermore, in the driver assistance device 10 of this embodiment, the cognitive function characteristic output unit 47 (output unit) outputs information according to the estimation result of the cognitive function decline factor estimation unit 46 to a device connected to the driver assistance device 10 via a network. Therefore, fluctuations in the estimation result of the driver's cognitive function characteristic can be monitored on a mobile terminal outside the vehicle. This can be useful for the driver to manage his or her own health. Furthermore, transmitting the estimation result of the driver's cognitive function characteristic to a hospital can help doctors when giving guidance on lifestyle management for the driver.

[0232] Furthermore, in the driver assistance device 10 of this embodiment, the cognitive function decline factor estimation unit 46 estimates fluctuations in cognitive function related to aging factors 90 based on a first average value of the evaluation score E (numerical value) over the past one month (first predetermined period), estimates fluctuations in cognitive function related to physical condition factors 91 based on a second average value of the evaluation score E over the past one hour (second predetermined period) that is shorter than the first predetermined period, and estimates fluctuations in cognitive function related to skill factors 92 based on a third average value of the evaluation score E over the past one minute (third predetermined period) that is shorter than the second predetermined period. Therefore, the main factors causing fluctuations in cognitive function can be estimated by simple calculation processing.

[0233] Although the embodiments of the present invention have been described above, the above-described embodiments are presented as examples and are not intended to limit the scope of the present invention. This novel embodiment can be embodied in various other forms. Furthermore, various omissions, substitutions, and modifications can be made without departing from the spirit of the invention. Furthermore, this embodiment is included within the scope and spirit of the invention, and is also included in the inventions and their equivalents as defined in the claims.

[0234] The present disclosure may be configured as follows.

[0235] (1) a driving state detection unit that detects at least one of a driving behavior of a driver of a vehicle, biological information of the driver while driving, and a behavior of the vehicle; a cognitive function score calculation unit that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection unit; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage unit that stores the numerical values ​​calculated by the cognitive function score calculation unit for the same driver and the analysis results of the cognitive function characteristic analysis unit in chronological order; a cognitive function decline factor estimation unit that calculates the influence of a plurality of variable factors that cause a decline in the cognitive function of the driver based on the stored contents of the cognitive function memory unit and estimates the main factor; a driver assistance unit that assists the driver based on an estimation result by the cognitive decline factor estimation unit or information according to the estimation result; A driver assistance device comprising: (2) The cognitive function decline factor estimation unit estimates a factor of fluctuation in cognitive function by comparing a memory content corresponding to the present in the cognitive function memory unit with a memory content corresponding to a predetermined past point in time. The driver assistance device according to (1) above. (3) The variation factors include at least one of an aging factor, a physical condition factor, and a skill factor of the driver. The driver assistance device according to (1) or (2) above. (4) The driver assistance unit further includes an output unit that outputs information according to the estimation result of the cognitive decline factor estimation unit in a form according to a past numerical value related to the main factor and a current numerical value related to the main factor. The driver assistance device according to any one of (1) to (3) above. (5) When the aging factor is the main factor, the output unit outputs, to the driver, information indicating that the driver has cognitive function decline due to aging or information related to recovery training for cognitive function decline due to aging. The driver assistance device according to (4) above. (6) When the physical condition factor is the main factor, the output unit outputs information to the driver to make the driver aware of poor physical condition and urge him / her to take a break. The driver assistance device according to (4) or (5) above. (7) When the skill factor is the main factor, the output unit outputs information indicating that the road condition is difficult for the driver, or suggests a route change to avoid the road condition that is difficult for the driver. The driver assistance device according to any one of (4) to (6) above. (8) The driver assistance unit The vehicle further includes an assistance content determination unit that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit and a threshold value, whether to enable an information provision function that supports information provision to suppress further deterioration of the driver's cognitive function, or whether to enable a driving assistance function that supports driving operations associated with the deteriorated cognitive function characteristics, from among a plurality of functions possessed by the vehicle, the output unit outputs the estimation result by the cognitive function decline factor estimation unit or information according to the estimation result at a timing when the assistance function determined by the assistance content determination unit becomes enabled. The driver assistance device according to any one of (4) to (7) above. (9) The driver assistance unit The vehicle further includes an assistance content determination unit that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit and a threshold value, whether to enable an information provision function that supports information provision to suppress further deterioration of the driver's cognitive function, or whether to enable a driving assistance function that supports driving operations associated with the deteriorated cognitive function characteristics, from among a plurality of functions possessed by the vehicle, the assistance content determination unit provides assistance to the driver when a road condition that is difficult for the driver and that is extracted in accordance with the estimation result of the skill factor by the cognitive function decline factor estimation unit is on the driving route. The driver assistance device according to (7) or (8) above. (10) The output unit outputs information according to the estimation result of the cognitive decline factor estimation unit to a device connected to the driver assistance device via a network. The driver assistance device according to any one of (4) to (9). (11) The cognitive function decline factor estimation unit estimates the fluctuation in cognitive function related to the aging factor based on a first average value of the numerical value over a first predetermined period, estimating a fluctuation in cognitive function related to the physical condition factor based on a second average value of the numerical value over a second predetermined period that is shorter than the first predetermined period; estimating a fluctuation in the cognitive function related to the skill factor based on a third average value of the numerical value over a third predetermined period that is shorter than the second predetermined period; The driver assistance device according to any one of (3) to (10) above. (12) a driving state detection unit that detects at least one of a driving behavior of a driver of a vehicle, biological information of the driver while driving, and a behavior of the vehicle; a cognitive function score calculation unit that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection unit; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage unit that stores the numerical values ​​calculated by the cognitive function score calculation unit for the same driver and the analysis results of the cognitive function characteristic analysis unit in chronological order; a cognitive function decline factor estimation unit that calculates the influence of a plurality of variable factors that cause a decline in the cognitive function of the driver based on the stored contents of the cognitive function memory unit and estimates the main factor; a driver assistance unit that assists the driver based on an estimation result by the cognitive decline factor estimation unit or information according to the estimation result; A driver assistance system equipped with: (13) a driving state detection process for detecting at least one of a driver's driving behavior, biometric information of the driver while driving, and a behavior of the vehicle; a cognitive function score calculation process that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection process; a cognitive function characteristic analysis process that analyzes the numerical value calculated by the cognitive function calculation process as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage process that stores, in chronological order, the numerical values ​​calculated by the cognitive function score calculation process for the same driver and the analysis results of the cognitive function characteristic analysis process; a cognitive function decline factor estimation process that calculates the influence of multiple variable factors that cause the decline in the driver's cognitive function based on the memory contents of the cognitive function memory process and estimates the main factor; a driver assistance process that assists the driver based on an estimation result by the cognitive decline factor estimation process or information according to the estimation result; A driver assistance method comprising: [Explanation of symbols]

[0236] 10 Driver assistance devices 30 vehicles 40 Driving environment detection unit 41 Driver Identification Department 42 Driving state detection unit 43 Cognitive function score calculation section 44 Cognitive Function Characteristics Analysis Department 45 Cognitive function memory unit 46 Cognitive decline factor estimation section 47 Cognitive function characteristic output unit (output unit) 48 Support content determination department 49 Support content display area 50 Support information presentation section 51 Driving assistance control unit 60 Driver Support Department 80 Memory 81 Execution 82 Attention 83 Information Processing Ability 84 Visual-spatial cognition 90 Aging Factors 91 Physical Condition Factors 92 Skill Factors E,Ea,Eb,Ec,Ed,Ee Evaluation score (numerical value) Th1 First threshold (threshold) Th2 Second threshold (threshold) Tha, Thb, Thc thresholds

Claims

1. a driving state detection unit that detects at least one of a driving behavior of a driver of a vehicle, biological information of the driver while driving, and a behavior of the vehicle; a cognitive function score calculation unit that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection unit; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage unit that stores, in chronological order, the numerical values ​​calculated by the cognitive function score calculation unit for the same driver and the analysis results of the cognitive function characteristic analysis unit; a cognitive function decline factor estimation unit that calculates the influence of variable factors that cause a decline in the cognitive function of the driver, including at least one of an aging factor, a physical condition factor, and a skill factor of the driver, based on the memory contents of the cognitive function memory unit, and estimates the main factor; a driver assistance unit that assists the driver based on the estimation result by the cognitive decline factor estimation unit or information according to the estimation result, The driver assistance unit further an assistance content determination unit that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit and a threshold, whether to enable an information provision function that assists in providing information to suppress further deterioration of the driver's cognitive function, or to enable a driving assistance function that assists in driving operations associated with the deteriorated cognitive function characteristics, from among a plurality of functions possessed by the vehicle; an output unit that outputs the estimation result by the cognitive decline factor estimation unit or information corresponding to the estimation result in a format corresponding to a past numerical value related to the main factor and a current numerical value related to the main factor at a timing when the assistance function determined by the assistance content determination unit becomes effective; A driver assistance device comprising:

2. The cognitive function decline factor estimation unit estimates a factor of fluctuation in cognitive function by comparing a memory content corresponding to the present in the cognitive function memory unit with a memory content corresponding to a predetermined past point in time.

10. The driver assistance device of claim 1.

3. When the aging factor is the main factor, the output unit outputs, to the driver, information indicating that the driver has cognitive function decline due to aging or information related to recovery training for cognitive function decline due to aging.

10. The driver assistance device of claim 1.

4. When the physical condition factor is the main factor, the output unit outputs information to the driver to make the driver aware of poor physical condition and urge him / her to take a break.

10. The driver assistance device of claim 1.

5. When the skill factor is the main factor, the output unit outputs information indicating that the road condition is difficult for the driver, or suggests a route change to avoid the road that is difficult for the driver.

10. The driver assistance device of claim 1.

6. A driving state detection unit that detects at least one of a driver's driving behavior of a vehicle, biometric information of the driver while driving, and behavior of the vehicle; a cognitive function score calculation unit that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection unit; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage unit that stores, in chronological order, the numerical values ​​calculated by the cognitive function score calculation unit for the same driver and the analysis results of the cognitive function characteristic analysis unit; a cognitive function decline factor estimation unit that calculates the influence of variable factors that cause a decline in the cognitive function of the driver, including at least one of an aging factor, a physical condition factor, and a skill factor of the driver, based on the memory contents of the cognitive function memory unit, and estimates the main factor; a driver assistance unit that assists the driver based on the estimation result by the cognitive decline factor estimation unit or information according to the estimation result, The driver assistance unit further an assistance content determination unit that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit and a threshold, whether to enable an information provision function that assists in providing information to suppress further deterioration of the driver's cognitive function, or to enable a driving assistance function that assists in driving operations associated with the deteriorated cognitive function characteristics, from among a plurality of functions possessed by the vehicle; an output unit that outputs information according to the estimation result by the cognitive decline factor estimation unit in a form according to past numerical values ​​related to the main factor and current numerical values ​​related to the main factor; When the skill factor is the main factor, the output unit outputs information indicating that the road condition is difficult for the driver or suggests a route change that avoids the road condition that is difficult for the driver, the assistance content determination unit provides assistance to the driver when a road condition that is difficult for the driver and that is extracted in accordance with the estimation result of the skill factor by the cognitive function decline factor estimation unit is on the driving route. Driver assistance devices.

7. The output unit outputs information according to the estimation result of the cognitive decline factor estimation unit to a device connected to the driver assistance device via a network.

10. The driver assistance device of claim 1.

8. A driving state detection unit that detects at least one of a driver's driving behavior of a vehicle, biometric information of the driver while driving, and behavior of the vehicle; a cognitive function score calculation unit that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection unit; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage unit that stores, in chronological order, the numerical values ​​calculated by the cognitive function score calculation unit for the same driver and the analysis results of the cognitive function characteristic analysis unit; a cognitive function decline factor estimation unit that calculates the influence of variable factors that cause a decline in the cognitive function of the driver, including at least one of an aging factor, a physical condition factor, and a skill factor of the driver, based on the memory contents of the cognitive function memory unit, and estimates the main factor; a driver assistance unit that assists the driver based on the estimation result by the cognitive decline factor estimation unit or information according to the estimation result, The cognitive function decline factor estimation unit estimates the fluctuation in cognitive function related to the aging factor based on a first average value of the numerical value over a first predetermined period, estimating a fluctuation in cognitive function related to the physical condition factor based on a second average value of the numerical value over a second predetermined period that is shorter than the first predetermined period; estimating a fluctuation in the cognitive function related to the skill factor based on a third average value of the numerical value over a third predetermined period that is shorter than the second predetermined period; Driver assistance devices.

9. a driving state detection unit that detects at least one of a driving behavior of a driver of a vehicle, biological information of the driver while driving, and a behavior of the vehicle; a cognitive function score calculation unit that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection unit; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage unit that stores, in chronological order, the numerical values ​​calculated by the cognitive function score calculation unit for the same driver and the analysis results of the cognitive function characteristic analysis unit; a cognitive function decline factor estimation unit that calculates the influence of variable factors that cause a decline in the cognitive function of the driver, including at least one of an aging factor, a physical condition factor, and a skill factor of the driver, based on the memory contents of the cognitive function memory unit, and estimates the main factor; a driver assistance unit that assists the driver based on the estimation result by the cognitive decline factor estimation unit or information according to the estimation result, The driver assistance unit further an assistance content determination unit that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis unit and a threshold, whether to enable an information provision function that assists in providing information to suppress further deterioration of the driver's cognitive function, or to enable a driving assistance function that assists in driving operations associated with the deteriorated cognitive function characteristics, from among a plurality of functions possessed by the vehicle; an output unit that outputs the estimation result by the cognitive decline factor estimation unit or information corresponding to the estimation result in a format corresponding to a past numerical value related to the main factor and a current numerical value related to the main factor at a timing when the assistance function determined by the assistance content determination unit becomes effective; A driver assistance system equipped with:

10. A computer that controls a driver assistance device, a driving state detection process for detecting at least one of a driver's driving behavior, biometric information of the driver while driving, and a behavior of the vehicle; a cognitive function score calculation process that calculates a numerical value indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection process; a cognitive function characteristic analysis process that analyzes the numerical value calculated by the cognitive function score calculation process as a cognitive function characteristic related to one or more different brain functions; a cognitive function storage process that stores, in chronological order, the numerical values ​​calculated by the cognitive function score calculation process for the same driver and the analysis results of the cognitive function characteristic analysis process; a cognitive function decline factor estimation process that calculates the influence of variable factors that cause the decline in the cognitive function of the driver, including at least one of an aging factor, a physical condition factor, and a skill factor of the driver, based on the memory contents of the cognitive function memory process, and estimates the main factor; a driver assistance process that assists the driver based on the estimation result by the cognitive decline factor estimation process or information according to the estimation result, The driver assistance process further comprises: an assistance content determination process that determines, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristic analysis process and a threshold, whether to enable an information provision function that assists in providing information to suppress further deterioration of the driver's cognitive function, or whether to enable a driving assistance function that assists in driving operations associated with the deteriorated cognitive function characteristics, from among a plurality of functions possessed by the vehicle; an output process that outputs the estimation result of the cognitive decline factor estimation process or information corresponding to the estimation result in a format corresponding to past numerical values ​​related to the main factors and current numerical values ​​related to the main factors when the assistance function determined by the assistance content determination process becomes effective; A driver assistance method for performing the following.

Images