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

Abstract

A driver assistance device is provided with: a driving state detection unit that detects at least one of a driving behavior of a driver with respect to a vehicle, biometric information during driving, and a behavior of the vehicle; a cognitive function score calculation unit that calculates a numerical value indicating the height of the cognitive function of the driver on the basis of the detection result of the driving state detection unit; a cognitive function characteristic analysis unit that analyzes the calculated values as cognitive function characteristics relating to one or more different brain functions; a cognitive function storage unit for storing, in time series, the numerical values for the same driver calculated by the cognitive function score calculation unit and the analysis results of the cognitive function characteristic analysis unit; a cognitive function decline factor estimation unit that estimates, on the basis of the stored content, a main factor among a plurality of variation factors that cause a decline in the driver's cognitive function; and a driver assistance unit that assists the driver on the basis of the estimation result or information corresponding to the estimation result.

Description

Technical Field

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

[0002] If traffic accidents are analyzed according to various human factors, "discovery delays" such as not paying attention to the front (including careless driving, looking around) and not confirming safety account for about 80% (Non-Patent Document 1). That is, the cognitive part of "cognition, judgment, and operation" during driving becomes the main factor. As factors that affect the decline in cognitive function associated with driving, mental and neurological diseases including drowsiness, alcohol / drugs, aging, dementia, and higher brain dysfunction can be cited (Non-Patent Document 2). Therefore, it is believed that if the decline in cognitive function during driving caused by various factors can be prevented, traffic accidents can be reduced. In addition, as shown in Non-Patent Documents 3 to 24, research has been conducted from various viewpoints on human cognitive function or driver's cognitive function, driver's action analysis during driving, etc.

[0003] Patent document 1 discloses a driving assistance device that detects a state in which driving ability is reduced due to drinking, dozing off, etc., and notifies the driver of the reduced driving ability. Patent document 2 discloses a dementia risk determination system that can detect traffic rule violations that are likely to occur when cognitive function is reduced, and determine whether the driver is able to drive.

[0004] Prior art literature

[0005] Patent Literature

[0006] Patent Document 1: Japanese Patent Application Publication No. 2009-101714

[0007] Patent Document 2: Japanese Patent Application Publication No. 2019-124975

[0008] Non-patent literature

[0009] Non-patent document 1: Traffic Accident Cluster Analysis: "Traffic Accident Statistical Table: Number of Total Accidents by Person's Factors and Accident Types (1 Case) - Vehicles", 2020

[0010] Non-patent literature 2: Mimura Masaru, Fujita Yoshio: "Safe Exercise and Cognitive Function", Journal of the Japanese Geriatrics Society, vol.55, No.2, pp.191-196, 2018

[0011] Non-profit article 3: Edited by Takao Suzuki: “Mild Cognitive Impairment (MCI) from the Basics – Aiming for Effective Dementia Prevention”, p.7-8, p.34, pp.111-123, p.225, Igaku-Shoin, 2015

[0012] Non-proprietary reference 4: Japanese Society of Neurology: “Dementia Disease Treatment Guidelines 2017”, Igaku-Shoin, pp.19-22, 2017

[0013] Non-profit article 5: Shinya Iida, Noriaki Kato, Kenji Hachisuka, Satoru Saeki: “Assessment of driving ability of elderly people”, Journal of the Japan Geriatrics Society, vol.55, No.2, pp.202-207, 2018

[0014] Non-profit article 6: Naoto Uemura, “Assessment of Driving Ability of People with Dementia and Its Challenges,” Journal of International Society for Traffic Safety, vol. 42, No. 3, pp. 12-22, 2018

[0015] Non-profit article 7: Katsuya Urakami, “Dementia and Driving”, Jidosha Gijutsu (Journal of Automotive Technology), vol. 71, No. 12, pp. 90-95, 2017

[0016] Non-profit article 8: Ryoko Fukuda, Fumio Harada, and Taisaku Okumura, “The state of cars that support a super-aging society: Aiming for cars that deeply support each individual’s personality,” Cognitive Studies, 25(3), pp. 259-278, September 2018.

[0017] Non-profit article 9: Shinya Takagi, 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

[0018] Non-proprietary reference 10: Li Bo, Zhang Xiaolin, Sato Makoto, Pitch angle estimation using an in-vehicle monocular camera for measuring distance between vehicles, Journal of the Institute of Image Information and Television Engineers, vol.69, No.4, pp.J169-J176, 2015

[0019] Non-profit article 11: Ryuji Uesaka, Masafumi Noda, Yoshito Mekada, Daisuke Deguchi, Ichiro Ide, Hiroshi Murase: “Driving behavior prediction using driver's gaze information”, Technical Report of the Institute of Electronics, Information and Communication Engineers.MI, Medical Imaging 111(49), 105-110, 2011-05-12

[0020] Non-proprietary reference 12: Akito Yamazaki, Pongsathorn Raksincheransak, Motoki Kodake, “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

[0021] Non-proprietary Reference 13: Masanari Takagi, Hironobu Fujiyoshi, “Traffic Sign Recognition Using SIFT Features”, Journal of the Institute of Electrical Engineers of Japan, vol. 129, No. 5, pp. 824-831, 2009

[0022] Non-profit article 14: David W. Eby, Lisa J. Molnar, Paula S. Katoji (ed. and translat. by Etsuo Horikawa and Tomoko Mine): “Elderly Mobility (From Driving Decision-Making to Mobility Support)”, Kyoto University Press, pp.15-33, 2020

[0023] Non-profit article 15: Tsuneo Matsuura: “Safety Psychology of Elderly Drivers”, University of Tokyo Press, pp.48-62, 2017

[0024] Non-profit article 16: Kazumi Isaji, Naohito Tsutome, Takahiro Wada, Shunichi Doi, Hiroshi Kaneko, “Analysis of braking start timing using approach / separation state evaluation index”, Transactions of the Society of Automotive Engineers of Japan, vol. 41, No. 3, pp. 593-598, 2010

[0025] Non-profit article 17: Tsuyoshi Nakagawa et al., “Health management while driving a car,” DENSOTECHNICALREVIEW, vol. 21, 2016

[0026] Non-profit article 18: Osamu Watanabe: “Cognitive function and driving”, Journal of the Japan Society of Traffic Sciences, vol. 17, No. 2, pp. 3-10, 2017

[0027] Non-profit literature 19: Noriyasu Kitamura: “Safe Driving Lifespan”, Corporate Development Center, Transportation Problems Research Laboratory, pp.44-46, pp.60-65, pp.133-136, 2009

[0028] Non-profit article 20: Atsuo Murata, Makoto Moriwaka, “Visual information processing characteristics of drivers in a risk prediction task - Comparison between novice drivers and experienced drivers”, Ergonomics, Vol. 46, No. 6, pp. 393-397, 2010

[0029] Non-Patent Document 21: Daisuke Nakata, Manabu Shibasaki: "Cognitive Function and Environmental Stress", Journal of the Japanese Society of Biometeorology, 56(1), 3-11, 2019

[0030] Non-Patent Document 22: Miyuki Sakurai, Shoichi Iwasaki: "Attention Arousal and Cognitive Failure Tendency during the Day in the Elderly", Applied Psychological Research, Vol. 42, No. 3, pp. 185-193, 2017 Non-Patent Document 23: Chiyomi Miyajima, Kazuya Takeda: "Construction and Application of a Driving Behavior Database", Vol. 55, No. 1, pp. 20-25, 2011

[0031] Non-Patent Document 24: Tomoki Inagaki, Noritake Harada, Yuki Kashiwada, Seiji Takehira, Satoru Koga: "Basic Analysis of Driving Behavior and Personal Characteristics of Elderly Drivers Based on Drive Recorder Data", Vol. 5, No. 2, pp. A_208-A216, 2019 Summary of the Invention

[0032] In the cases of Patent Document 1 and Patent Document 2, the estimation of factors for cognitive function decline has not been carried out yet.

[0033] An object of the present disclosure is to provide a driver assistance device, a driver assistance system, and a driver assistance method capable of estimating factors for decline in a driver's cognitive function.

[0034] Furthermore, the present disclosure discloses an improved invention of a prior application (Japanese Patent Application No. 2021-052309). Therefore, in this specification, the description content of the prior application is appropriately cited.

[0035] The driver assistance device involved in the present disclosure includes a driving state detection unit, a cognitive function score calculation unit, a cognitive function characteristic analysis unit, a cognitive function storage 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 action on the vehicle, the driver's biological information during driving, and the behavior of the vehicle. 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 associated with one or more different brain functions. The cognitive function storage unit stores the numerical value calculated by the cognitive function score calculation unit for the same driver and the analysis result of the cognitive function characteristic analysis unit in time series. The cognitive function decline factor estimation unit calculates the influence of multiple variable factors that cause the driver's cognitive function decline based on the storage content of the cognitive function storage unit, and estimates the variable factor that becomes the main factor. The driver assistance unit assists the driver based on the estimation result of the cognitive function decline factor estimation unit or information corresponding to the estimation result.

[0036] Effects of the Invention

[0037] According to the driver assistance device according to the present disclosure, it is possible to estimate factors causing the driver's cognitive function to decline. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1A This is a diagram for explaining the decline in cognitive function characteristics that occurs with aging.

[0039] Figure 1B This is a diagram for explaining the decline in cognitive function characteristics over time.

[0040] Figure 2 It is a diagram for explaining the cognitive function characteristics determined by the driver assistance device according to the embodiment.

[0041] Figure 3 This is a hardware block diagram showing an example of the hardware configuration of the driver assistance device according to the embodiment.

[0042] Figure 4 This is an external view showing an example of a cockpit of a vehicle equipped with the driver assistance device according to the embodiment.

[0043] Figure 5 This is a functional block diagram showing an example of a functional configuration of a driver assistance device according to the embodiment.

[0044] Figure 6 This is a diagram for explaining an example of information detected by the driving state detection unit.

[0045] Figure 7 This is a flowchart showing an example of the flow of a process in which the cognitive function score calculation unit calculates the evaluation score of the cognitive function level.

[0046] Figure 8 This is a diagram for explaining the relationship between cognitive function characteristics associated with different brain functions and driving actions that occur during driving.

[0047] Fig. 9 This is a first diagram for explaining an example of the content of assistance provided by the driver assistance device based on the cognitive function characteristics.

[0048] Fig.10 This is a second diagram for explaining an example of the content of assistance provided by the driver assistance device based on the cognitive function characteristics.

[0049] Fig.11 This is a diagram for explaining an example of factors that may cause cognitive decline.

[0050] Fig.12 This is a diagram showing an example of changes in cognitive function over time.

[0051] Fig.13A The first figure shows an example of factor analysis of cognitive decline.

[0052] Fig. 13B The second figure shows an example of factor analysis of cognitive decline.

[0053] Fig.14 This is a diagram showing an example of a method for identifying a state of cognitive decline.

[0054] Fig.15 This is a diagram showing an example of changes over time in the driver's cognitive function level.

[0055] Fig.16 This is a diagram showing an example of information presentation content according to changes in cognitive function levels.

[0056] Fig.17 This is a diagram showing an example of information presented to the driver when the main factor of cognitive function decline is aging.

[0057] Fig.18 This is a diagram showing an example of information presented to the driver when the main factor of cognitive function decline is the physical condition factor.

[0058] Fig.19 This is a diagram showing an example of information presented to the driver when the main factor of cognitive function decline is a skill factor.

[0059] Fig. 20 This is a diagram showing an example of a method for calculating the degree of influence of the aging factor on the decline in cognitive function.

[0060] Fig.21 This is a flowchart showing an example of another method for estimating factors of cognitive function decline.

[0061] Fig. 22 This is a flowchart showing an example of the flow of processing performed by the driver assistance device according to the present embodiment.

[0062] Fig.23 This is a diagram for explaining a function of presenting information related to a major factor of cognitive function decline when the driver assistance device changes its operation mode. DETAILED DESCRIPTION

[0063] Hereinafter, embodiments of a driver assistance device according to the present disclosure will be described with reference to the drawings.

[0064] (Description of cognitive function characteristics)

[0065] use Figure 1A , Figure 1B as well as Figure 2 To illustrate the cognitive function characteristics of the driver. Figure 1A This is a diagram for explaining the decline in cognitive function that occurs with aging. Figure 1B This is a diagram for explaining the decline of cognitive function over time. In particular, Figure 1B It is used to illustrate the accompanying ratio Figure 1A A diagram showing the decline in cognitive function over a short period of time. Figure 1A The example shows the change in years. Figure 1B An example is the change in the time during driving. Figure 2 It is a diagram for explaining the cognitive function characteristics determined by the driver assistance device according to the embodiment.

[0066] like Figure 1A As shown in , cognitive function sometimes declines with age (Non-patent Document 3). Figure 1BAs shown, it also changes over time in daily life (non-patent literature 22). Here, the value obtained by quantifying whether the cognitive function is high or low is called the evaluation score E of the cognitive function level. When the evaluation score E of the cognitive function level calculated by an appropriate evaluation method exceeds the first threshold Th1, that is, when the evaluation score E of the cognitive function level is in area R1, it is determined that the cognitive function is in a state where safe driving can be maintained. Moreover, when the evaluation score E of the cognitive function level is lower than the first threshold Th1 and higher than the second threshold Th2 which is smaller than the first threshold Th1, that is, when the evaluation score E of the cognitive function level is in area R2, it is determined that the cognitive function is in a "need to pay attention" state that hinders continued safe driving. And, when the evaluation score E of the cognitive function level is less than the second threshold Th2, that is, when the evaluation score E of the cognitive function level is in area R3, it is determined to be in a "dangerous" state where the cognitive function level has dropped to a level that makes it difficult to continue driving. The cognitive function characteristics of the driver are sometimes measured by a doctor's cognitive function test such as MMSE (Mini-Mental State Examination) (Non-Patent Document 3), but here it is assumed that the cognitive function that changes over time during driving is quantified.

[0067] In addition, if you are driving carelessly, looking around, or your attention is temporarily reduced, Figure 1B In addition, even in the case of cognitive decline due to aging or mild cognitive impairment (MCI), it is possible to evaluate Figure 1A , Figure 1B Changes were also observed in the same cognitive functions shown.

[0068] The driver assistance device 10 of the present embodiment quantifies the cognitive function of the driver, analyzes the state of cognitive function characteristics based on the quantified value, and performs appropriate driving assistance based on the analysis result.

[0069] In addition, cognitive functions can be classified into a plurality of different cognitive functions associated with different brain parts (brain functions) (Non-Patent Document 3). Figure 2The multiple different cognitive functions shown are evaluated as objects. Specifically, they are memory 80, executive function 81, attention 82, information processing ability 83, and visual spatial cognition 84. The impact of the decline of each cognitive function on driving is recorded in Non-Patent Documents 2, 5, 6, and 7. In addition, as the evaluation object of cognitive function, Figure 2 Five are selected, but only one may be selected, or any combination of two or more may be selected. In addition, cognitive functions not described here may be selected as evaluation objects.

[0070] Memory 80 is a cognitive function that preserves new experiences and reproduces them in consciousness and behavior (Non-Patent Document 4). Referring to driving behavior, memory 80 is reflected in, for example, the ability to retain information recorded on a sign, the ability to remember where to go, etc. (Non-Patent Document 5).

[0071] Execution 81 is a cognitive function that makes plans and executes things according to the purpose, and advances while feeding back the results (Non-Patent Document 4). If referring to driving behavior, execution 81 is reflected in, for example, the ability to correctly step on the accelerator and brake, the ability to perform multiple information processing, etc. (Non-Patent Document 5).

[0072] Attention 82 is a cognitive function that is used to receive / select surrounding stimuli and to perform consistent actions on them (Non-Patent Document 4). Referring to driving behavior, attention 82 is reflected in, for example, the ability to direct attention to the surrounding environment such as signs and signals (Non-Patent Document 5).

[0073] Information processing ability 83 is a cognitive function that performs a specified task within a certain period of time (Non-Patent Document 3). Referring to driving behavior, information processing ability 83 is reflected in, for example, the ability to detect danger and respond to it while driving (Non-Patent Document 15).

[0074] Visual spatial cognition 84 is a cognitive function that processes information seen by the eyes to grasp the state of space. If referring to driving behavior, visual spatial cognition 84 is reflected in, for example, the ability to correctly maintain a sense of distance from the vehicle in front, the ability not to go out of the lane when turning, etc. (Non-patent Document 5).

[0075] like Figure 1A , Figure 1B As shown in , it is known that these cognitive functions change with age and time (Non-patent Document 3). Figure 2 As shown, the above-mentioned cognitive functions can be evaluated according to the magnitude relationship between the first threshold value Th1 and the second threshold value Th2. Figure 2The horizontal axis is normalized in the graph, and the first threshold value Th1 and the second threshold value Th2 for each cognitive function are not necessarily the same value.

[0076] (Overall structure of driver assistance device)

[0077] use Figure 3 and Figure 4 The overall structure of the driver assistance device 10 will be described. Figure 3 This is a hardware block diagram showing an example of the hardware configuration of the driver assistance device according to the embodiment. Figure 4 This is an external view showing an example of a cockpit of a vehicle equipped with the driver assistance device according to the embodiment.

[0078] The driver assistance device 10 calculates an evaluation score E of the cognitive function level of the driver of the vehicle 30 , and performs driving assistance according to a decrease in the cognitive function of the driver.

[0079] 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 operating device 26 , and a communication interface 27 .

[0080] 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. In addition, a storage device 11d including an HDD (Hard Disk Drive) or the like may be built into the ECU 11. In addition, the ECU 11 includes I / O (Input / Output) ports 11e and 11f that can send and receive detection signals and various information with various sensors or the like. The I / O port 11e is connected to a bus 16 for the flow of information related to the driving control of the vehicle 30, and is used to control the input and output of information related to the control system for various driving assistance of the vehicle 30. The I / O port 11f is connected to a bus 28 for the flow of information related to the information system of the vehicle 30, and is used to control the input and output of information related to the detection of the driver's driving behavior and the information presented to the driver.

[0081] The RAM 11 b , the ROM 11 c , the storage device 11 d , and the I / O ports 11 e and 11 f of the ECU 11 are configured to be able to transmit and receive various types of information with the CPU 11 a via the internal bus 11 g .

[0082] The ECU 11 controls various processes performed by the driver assistance device 10 by having the CPU 11 a read out and execute a program installed in the ROM 11 c .

[0083] In addition, the program executed by the driver assistance device 10 of the present embodiment may be provided by being pre-installed in the ROM 11c, or may be provided by being recorded in a computer-readable recording medium such as a CD-ROM, a floppy disk (FD), a CD-R, or a DVD (Digital Versatile Disk) in an installable or executable form.

[0084] Furthermore, the program executed by the driver assistance device 10 of the present embodiment may be stored on a computer connected to a network such as the Internet and downloaded via the network. Alternatively, the program executed by the driver assistance device 10 of the present embodiment may be provided or distributed via a network such as the Internet.

[0085] The storage device 11 d stores a table and the like for calculating the evaluation score E of the driver's cognitive function level. Details will be described later.

[0086] The sensor controller 12 acquires sensor outputs for detecting the behavior of the vehicle 30 and transmits the sensor outputs to the ECU 11. The sensor controller 12 is connected to, for example, an accelerator position sensor 12a, a brake pedal force sensor 12b, and a steering angle sensor 12c. In addition, the sensors connected to the sensor controller 12 are not limited to these examples, and other sensors may also be connected.

[0087] The accelerator position sensor 12 a detects the degree of depression of the accelerator of the vehicle 30 (accelerator opening degree).

[0088] The brake pedal force sensor 12 b detects a pedal force applied to a brake pedal of the vehicle 30 , that is, a pedal force applied to the brake pedal.

[0089] The steering angle sensor 12 c detects the steering direction and steering amount of the steering wheel of the vehicle 30 .

[0090] In addition, the bus 16 is connected to the steering control device 13, the driving force control device 14, and the braking force control device 15. These control devices form a so-called ADAS (Advanced Driver Assistance System) system that controls the behavior of the vehicle 30 by cooperating with each other based on various sensor information acquired by the sensor controller 12 and various sensor information acquired by the sensor controller 21.

[0091] The steering control device 13 controls the steering angle of the vehicle 30 based on an instruction from the ECU 11 .

[0092] The driving force control device 14 controls the driving force of the vehicle 30 based on the instruction of the ECU 11. Specifically, based on the instruction of the ECU 11, the accelerator opening degree of the engine of the vehicle 30 is controlled.

[0093] The braking force control device 15 controls the braking force of the vehicle 30 based on the instruction of 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, whereby the vehicle 30 can be driven automatically.

[0094] In addition, the ADAS system mounted on the vehicle 30 is not limited to the above-mentioned devices, and other devices may be mounted.

[0095] The sensor controller 21 is connected to the surrounding camera 21a, the driver monitoring camera 21b, the distance measuring sensor 21c, etc., and is used to transmit these sensor outputs to the ECU 11. The ECU 11 senses the surrounding environment of the vehicle 30 and detects the biological signal of the driver based on the acquired information. In addition, the sensors connected to the sensor controller 21 are not limited to these examples, and other sensors may also be connected.

[0096] The surrounding cameras 21 a are provided to face different directions around the vehicle 30 , and are used to acquire image information around the vehicle 30 .

[0097] The driver monitoring camera 21b is installed on the dashboard of the vehicle 30 to obtain an image including the face of the driver while driving. In addition, the driver monitoring camera 21b may also be installed under the driver's feet to monitor the driver's accelerator operation and brake operation.

[0098] The distance measuring sensors 21c are provided in different directions around the vehicle 30 to measure the distance to obstacles around the vehicle 30. The distance measuring sensors 21c are, for example, ultrasonic sensors for short-range distance measurement, millimeter wave radars for medium- and long-range distance measurement, and LiDAR (Light Detection and Ranging).

[0099] The GPS receiver 22 acquires GPS signals sent from GPS (Global Positioning System) satellites to locate the current position of the vehicle 30 and calculate the traveling direction. In addition, the ECU 11 compares the determined current position and traveling direction of the vehicle 30 with the map database 24 (map matching) to determine the road and traveling direction on which the vehicle 30 is traveling. In addition, the method of determining the current position and traveling direction of the vehicle using the GPS signal and the map database is widely used in car navigation systems, so a detailed description is omitted.

[0100] The display device 25 displays information related to the driving state of the vehicle 30 and information for the driver. The display device 25 is, for example, Figure 4 The central monitor 25a, indicator 25b, measuring instrument 25c, etc. are shown. The contents of each display device 25 will be described later (refer to Figure 4 ). In addition, the display device 25 may be a device that provides information not only to the driver's vision but also to the driver's hearing and touch, such as a speaker or a vibration device.

[0101] The operation device 26 acquires various operation information for the vehicle 30. The operation device 26 is, for example, a touch panel stacked on the display surface of the center monitor 25a, a physical switch provided on the instrument panel, or the like.

[0102] The communication interface 27 connects the vehicle 30 to a portable terminal outside the vehicle (eg, a pre-registered smartphone, wearable terminal, etc.) by wireless communication. The communication interface 27 transmits, for example, the evaluation score E of the cognitive function level calculated by the driver assistance device 10 from the vehicle 30 to the portable terminal.

[0103] Next, use Figure 4 Next, a schematic structure of a cockpit of a vehicle 30 on which the driver assistance device 10 is mounted will be described.

[0104] A central monitor 25a as an example of the display device 25 is provided in the center cluster of the vehicle 30. The central monitor 25a is provided as high as possible to improve visibility during driving. The driver assistance device 10 displays the evaluation score E of the cognitive function level, the driving assistance content based on the evaluation score E, etc. on the central monitor 25a.

[0105] An indicator 25b as 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 of, for example, 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 evaluation score E of the cognitive function level. The indicator 25b is provided in the peripheral vision area of ​​the driver who is driving, and the luminous color of the indicator 25b can be recognized without directing the line of sight toward the indicator 25b. As a result, the driver can easily recognize the driving assistance content.

[0106] Furthermore, a meter cluster of the vehicle 30 is provided with a measuring instrument 25c as an example of the display device 25. The measuring instrument 25c is, for example, a speedometer, an engine tachometer, a fuel gauge, a water temperature gauge, and the like.

[0107] Furthermore, a driver monitoring camera 21b is provided in the instrument cluster of the vehicle 30. The driver monitoring camera 21b is provided in the instrument cluster so as to be able to capture an image of the area where the eyeballs of the driver (eye range) are located while driving.

[0108] (Functional structure of driver assistance device)

[0109] use Figure 5 Next, the functional structure of the driver assistance device 10 will be described. Figure 5 This is a functional block diagram showing an example of a functional configuration of a driver assistance device according to the embodiment.

[0110] The ECU 11 of the driver assistance device 10 expands the control program stored in the ECU 11 into the RAM 11b and causes the CPU 11a to operate, thereby achieving Figure 5The driving environment detection unit 40, the driver identification unit 41, the driving state detection unit 42, the cognitive function score calculation unit 43, the cognitive function characteristic analysis unit 44, the cognitive function storage unit 45, the cognitive function decline factor estimation unit 46 and the driver assistance unit 60 are shown as functional units. In addition, the driver assistance unit 60 includes 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 as functional units. The driver assistance device 10 may also realize some or all of these functions by dedicated hardware.

[0111] 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 refers to, for example, information such as the shape of the road ahead in the traveling direction, the number of lanes, the speed limit, the distance to the intersection, the shape of the intersection, the presence of a preceding vehicle and the distance between the vehicles, the presence and location of an oncoming vehicle, and the presence and location of pedestrians. This information can be obtained, for example, by analyzing the images captured by the surrounding camera 21a and the information obtained by the distance measuring sensor 21c, and by comparing the current position of the vehicle 30 obtained from the GPS signal with the map database 24.

[0112] The driver identification unit 41 identifies the driver who is driving the vehicle 30. The driver identification unit 41 identifies the driver who is currently driving the vehicle 30 by, for example, comparing the driver's facial image captured by the driver monitoring camera 21b with the facial images of pre-registered drivers. If no comparison result is obtained, the driver is considered to be a new driver and is newly registered.

[0113] The driving state detection unit 42 detects at least one of a driver's driving action on the vehicle 30 , biological information of the driver during driving, and a behavior of the vehicle 30 .

[0114] The cognitive function score calculation unit 43 calculates an evaluation score E indicating whether the cognitive function of the driver is high or low based on the information detected by the driving state detection unit 42. The evaluation score E is an example of a numerical value in the present disclosure.

[0115] 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 associated with one or more different brain functions. In addition, the cognitive function characteristics associated with one or more different brain functions refer to, for example, the aforementioned memory 80, executive ability 81, attention 82, information processing ability 83, visual spatial cognition 84, etc.

[0116] The cognitive function storage unit 45 stores the evaluation score E calculated by the cognitive function score calculation unit 43 for the same driver and the analysis result of the cognitive function characteristic analysis unit 44 in time series.

[0117] The cognitive function decline factor estimation unit 46 calculates the influence of a plurality of variable factors causing the cognitive function decline of the driver and estimates the variable factor that is the main factor based on the storage content of the cognitive function storage unit 45. In addition, the cognitive function decline factor estimation unit 46 estimates the variable factor of cognitive function by comparing the storage content corresponding to the current state of the cognitive function storage unit 45 with the storage content corresponding to a predetermined past time point.

[0118] The driver assistance unit 60 assists the driver based on the estimation result of the cognitive function decline factor estimation unit 46 or information corresponding to the estimation result.

[0119] The cognitive function characteristic output unit 47 outputs information on the analysis result of the cognitive function characteristic analysis unit 44. The cognitive function characteristic output unit 47 also outputs the estimation result of the cognitive function decline factor estimation unit 46. The cognitive function characteristic output unit 47 is an example of an output unit in the present disclosure.

[0120] The assistance content determination unit 48 determines whether to enable a function of providing information to assist in suppressing further deterioration of the driver's cognitive function characteristics or to enable a function of assisting driving actions associated with deteriorated cognitive function characteristics, from among a plurality of functions of the vehicle 30, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristics analysis unit 44 and the threshold. In addition, the assistance content determination unit 48 determines the content of information presented to the driver based on the main factors of cognitive function deterioration estimated by the cognitive function deterioration factor estimation unit 46.

[0121] The auxiliary content display unit 49 displays the information determined by the auxiliary content determination unit 48 on, for example, the central monitor 25 a .

[0122] When the auxiliary content determination unit 48 determines to enable the function of providing auxiliary information for suppressing further deterioration of the driver's cognitive function characteristics, the auxiliary information presentation unit 50 provides the information. In the following description, enabling the function of providing auxiliary information for suppressing further deterioration of the driver's cognitive function characteristics is referred to as a training mode.

[0123] When the assistance content determination unit 48 determines to enable the function of assisting the driving action associated with the cognitive function characteristics, the driving assistance control unit 51 activates the function. In the following description, enabling the function of assisting the driving action associated with the cognitive function characteristics is referred to as a driving assistance mode.

[0124] (Function of driving status detection unit)

[0125] use Figure 6 The detailed operation of the driving state detection unit 42 will be described. Figure 6 This is a diagram for explaining an example of information detected by the driving state detection unit. Examples of analysis of common driving actions are summarized in non-patent literature 23, non-patent literature 24, etc. Examples of the detected information include the driver's driving action, the behavior of the vehicle, and the driver's biological information. Examples of the driving environment include road shape, weather, and time period.

[0126] The driving state detection unit 42 detects Figure 3 The image including the driver's face captured by the driver monitoring camera 21b shown is analyzed to detect the driver's biological information. Specifically, the driver's line of sight direction, face orientation, body movements (changes in the position of the face), number and interval of blinking, etc. are detected. In addition, the detected biological information and its detection method are not limited to the aforementioned contents. For example, the driver's heartbeat, body temperature, breathing state, etc. can also be detected. As a specific method for detecting the driver's state, vehicle information, operation information, and biological information, the method summarized in non-patent document 8 can be used, or other methods can be used.

[0127] In addition, the driving state detection unit 42 is based on Figure 3 The outputs of the accelerator position sensor 12a, the brake pedal force sensor 12b, the steering angle sensor 12c, and the distance sensor 21c are shown. Figure 3 The behavior of the vehicle 30 is detected by using the outputs of various sensors (vehicle speed sensor, gear position sensor, etc.) that the vehicle 30, which is not shown in the figure, has. Specifically, the behaviors of the vehicle 30, such as vehicle speed, vehicle-to-vehicle distance, whether or not the vehicle is leaving the lane, sudden acceleration, sudden deceleration, and driving trajectory, are detected. Regarding 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, the method described in non-patent document 9 may be used, or other methods may be used. In addition to the method described in non-patent document 10, the method for measuring the vehicle-to-vehicle distance can also be achieved by using information detected by a conventional ADAS system. In addition, the detected behavior of the vehicle 30 is not limited to the aforementioned content.

[0128] In addition, the driving state detection unit 42 detects the driving behavior of the driver based on the detected biological 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 such as the distribution of gaze points, whether the driver looks around, whether the driver checks the left and right, whether the driver checks the rear, whether the driver stops temporarily, whether the driver obeys signs, whether the driver obeys signals, and the continuous driving time is detected. In addition, the detected driving behavior of the driver is not limited to the above-mentioned content.

[0129] The distribution state of the gaze point can be obtained by analyzing the measured line of sight direction. In addition, the gaze point refers to a point where the line of sight stays for a time longer than a specified time. When the gaze points are distributed over a wide range, it is estimated that the driver pays attention to the wide range. On the other hand, when the gaze points are concentrated in a narrow range, it is estimated that the driver is attracted to a specific range. As a method for detecting where the line of sight is directed, for example, the method described in non-patent document 11 or non-patent document 12 can be used, or other methods can be used.

[0130] Whether the person is looking around can be obtained by analyzing the measured sight line direction and the orientation of the face. As a method for detecting whether the person is looking around, for example, the method described in Non-Patent Document 12 can be used, or other methods can be used.

[0131] Whether there is left-right confirmation can be confirmed by determining whether the face is moving left-right at the place where left-right confirmation should be performed, or whether the line of sight is facing the direction where safety confirmation should be performed. In addition, with respect to the place where left-right confirmation should be performed, by comparing the current position of the vehicle 30 obtained from the GPS signal with the map database 24, it can be determined that the vehicle is traveling near an intersection where left-right confirmation is required, for example. In addition, whether a pedestrian is confirmed can be detected by using, for example, the technology described in non-patent document 12, or other methods can be used.

[0132] Whether there is rearward confirmation can be confirmed by determining whether the face is facing rearward or in the direction of the interior mirror or rearview mirror at the place where rearward confirmation should be performed. Whether there is rearward confirmation can be confirmed by using, for example, the technology described in non-patent document 12, or by other methods. In addition, the place where rearward confirmation should be performed can be estimated, for example, based on whether the shift position of the vehicle 30 enters the reverse gear.

[0133] Whether or not there is a temporary stop can be confirmed by determining whether the vehicle 30 stops at the place where the temporary stop should be made. In addition, the place where the temporary stop should be made can be determined based on the temporary stop sign detected by the surrounding camera 21a. As a method for sign recognition, for example, the method described in non-patent document 13 can be used, or other methods can be used.

[0134] Compliance with the sign can be determined based on whether the content of the sign detected by the surrounding camera 21 a matches the behavior of the detected vehicle 30 .

[0135] The compliance signal can be determined based on whether the state of the signal detected by the surrounding camera 21 a matches the behavior of the detected vehicle 30 .

[0136] The continuous driving time can be determined based on, for example, the elapsed time from when the ignition switch is turned on.

[0137] The driving environment of the vehicle 30 is constantly changing, so it is not preferable to continuously detect the aforementioned detection object because the load on the computer increases. Therefore, the driving state detection unit 42 detects at least one of the driver's driving action on the vehicle 30, the driver's biological information during driving, and the behavior of the vehicle 30 that is expected to occur in the driving environment based on the driving environment of the vehicle 30.

[0138] Specifically, the driving state detection unit 42 estimates biological information, behavior of the vehicle 30, and driving action that are expected to occur in the driving environment based on the driving environment detected by the driving environment detection unit 40, and locks the detection target by detecting at least only the estimated information.

[0139] Figure 6 The horizontal axis represents an example of the driving environment detected by the driving environment detection unit 40, and the vertical axis represents the aforementioned detection objects. Figure 6 The circle marked in the figure represents the detection object to be detected in the detected driving environment.

[0140] For example, when it is detected that the vehicle 30 is traveling near 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, as biological information, the line of sight direction and the orientation of the face are detected. In addition, as the behavior of the vehicle 30, the vehicle speed, sudden acceleration, sudden deceleration, and driving trajectory are detected. Moreover, as the driving action of the driver, the distribution of the gaze point, the presence or absence of left and right confirmation, the presence or absence of temporary stops, compliance with signs, and compliance with signals are detected. In addition, in Figure 6 The circle indicated in the figure is an example, and the present invention is not limited to this example.

[0141] The computational load increases when the estimation of the detection object according to the driving environment is performed each time. Therefore, for example, Figure 6 The map is stored in the storage device 11d, and the driving state detection unit 42 refers to the map to select the detection target.

[0142] (Calculation method of cognitive function)

[0143] use Figure 7 A method in which the cognitive function score calculation unit 43 calculates the evaluation score E of the cognitive function level will be described. Figure 7 This is a flowchart showing an example of the flow of a process in which the cognitive function score calculation unit calculates the evaluation score of the cognitive function level.

[0144] The running environment detection unit 40 detects the running environment of the vehicle 30 (step S11 ).

[0145] The driving state detection unit 42 selects information detected for calculating the cognitive function based on the driving environment detected by the driving environment detection unit 40 (step S12 ).

[0146] The driving state detection unit 42 detects the information selected in step S12 (step S13 ).

[0147] The cognitive function score calculation unit 43 adds the occurrence frequency of each event suitable for the driving environment detected by the driving environment detection unit 40 based on the information detected by the driving state detection unit 42 (step S14).

[0148] The cognitive function score calculation unit 43 determines whether the prescribed time has passed (step S15). If it is determined that the prescribed time has passed (step S15: "Yes"), the process proceeds to step S16. On the other hand, if it is not determined that the prescribed time has passed (step S15: "No"), the process returns to step S11. In addition, the prescribed time can be set arbitrarily, for example, it is determined in units of 1 minute.

[0149] If it is determined in step S15 that the prescribed time has passed, the cognitive function score calculation unit 43 calculates the evaluation score E of the cognitive function level (step S16). In addition, for example, the occurrence frequency of each event calculated in step S14 is set as the evaluation score E. In addition, for example, the distribution state of the gaze point cannot be expressed by frequency, so it is sufficient to set the numerical value indicating the size of the distribution range as the evaluation score E. In addition, for other information that cannot be expressed by frequency, it is sufficient to calculate the evaluation score E based on the calculation method set for each information.

[0150] The cognitive function storage unit 45 stores the evaluation score E in association with the year, month, day, and driver (step S17). Figure 7 processing.

[0151] The cognitive function storage unit 45 stores the evaluation score E calculated in step S16 in association with the year, month, day and driver in the storage device 11d (see Figure 3 )(Step S17). Then, the cognitive function score calculation unit 43 ends Figure 7 processing.

[0152] In step S14 , the occurrence frequency of the event is added, but when it is detected that the desired driving action has been performed, the accumulated occurrence frequency of the event may be subtracted.

[0153] (Analysis of cognitive function)

[0154] use Figure 8 Next, a method for analyzing the evaluation score E of the cognitive function level by the cognitive function characteristic analysis unit 44 will be described. Figure 8 This is a diagram for explaining the relationship between cognitive function characteristics associated with different brain functions and driving actions that occur during driving.

[0155] like Figure 8 As shown, the cognitive function characteristic analysis unit 44 analyzes the degree of decline of each cognitive function associated with different brain functions based on the type of driving action detected and its occurrence frequency. The impact of the decline of each cognitive function on driving is recorded in Non-Patent Documents 2, 5, 6, and 7. In addition, the impact caused by the decline of information processing speed is shown in Non-Patent Documents 14 and 15. In addition, Figure 8 The driving action shown is just an example, and a correspondence table different from this may be used.

[0156] For example, if the memory 80 decreases, it becomes difficult to keep the information recorded on the sign, or forget where to go and get lost (non-patent document 5), or forget past experiences of crashing or getting into trouble (non-patent document 6). Sometimes road signs and traffic laws are not known (non-patent document 2). The cognitive function characteristic analysis unit 44 calculates the evaluation score Ea of the memory 80 from the evaluation score E calculated by the cognitive function score calculation unit 43 based on, for example, the frequency of complying with the sign and the frequency of complying with the signal. As a method of sign recognition, the method described in non-patent document 13, for example, or other methods can be used. In addition, it can also be determined that the content of the sign has been recognized based on whether a driving action consistent with the content of the sign has been taken.

[0157] When the execution force 81 decreases, the accelerator and brake may be incorrectly stepped on, or multiple information processing may become difficult (Non-Patent Document 5). In addition, it is impossible to judge the next action to be taken when the predetermined path cannot be passed (Non-Patent Document 6), or it is impossible to take flexible measures according to the situation (Non-Patent Document 2). Sometimes it is also impossible to operate the car navigation (Non-Patent Document 6). The cognitive function characteristic analysis unit 44 calculates the evaluation score Eb of the execution force 81 from the evaluation score E calculated by the cognitive function score calculation unit 43, for example, based on the frequency of occurrence of sudden acceleration and sudden deceleration.

[0158] If the attention 82 decreases, it is impossible to direct attention to the surrounding environment such as signs and signals (non-patent document 5). Signals may be missed, or people may not be noticed (non-patent document 6). In addition, it is impossible to allocate attention to the surroundings when changing lanes, which may become a dangerous operation, or pedestrians and motorcycles may not be noticed when turning left or right (non-patent document 5). When attention becomes unfocused, the attention will be attracted by things inside or outside the car (non-patent document 14), and the person will start to look around. 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, for example, based on the distribution of gaze points, the frequency of following signs, and the frequency of following signals. As a method for detecting where the line of sight is directed, for example, the method described in non-patent document 11 or non-patent document 12 can be used, and it is possible to evaluate whether points of attention such as signs and pedestrians are seen based on their movement. In addition, it is also possible to perform a detection on the points of attention such as signs and pedestrians. Figure 8 The evaluation score Ec of the attention 82 is calculated by weighting the evaluation scores E calculated for the driving action example shown, whether the surrounding safety confirmation is insufficient, whether the sign is missed, etc. The weighting coefficient may be a predetermined coefficient or the correlation with the cognitive function may be learned sequentially.

[0159] If the information processing power 83 decreases, it will take time to detect danger on a crowded road or a road with fast traffic, resulting in delayed response (Non-Patent Document 15). In addition, slow driving, hesitant driving, and unexpected operational errors increase (Non-Patent Document 14). The cognitive function characteristic analysis unit 44 calculates the evaluation score Ed of the information processing power 83 from the evaluation score E calculated by the cognitive function score calculation unit 43 based on, for example, the reaction time of braking as a driving operation. For example, the method of Non-Patent Document 16 is used to evaluate and calculate the braking timing.

[0160] If the visual-spatial cognitive ability 84 decreases, the sense of distance from the vehicle in front will deviate, or the vehicle will go out of the lane when turning (non-patent document 5). In addition, it is difficult to grasp the relationship between the size of one's own car and the object (non-patent document 7). The cognitive function characteristic analysis unit 44 calculates the evaluation score Ee of the visual-spatial cognitive ability 84 from the evaluation score E calculated by the cognitive function score calculation unit 43, for example, based on the average value of the vehicle distance, the number of times the vehicle leaves the lane, etc. The determination 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 of non-patent document 9. In addition to the method of non-patent document 10, the method for measuring the vehicle distance can also be calculated using information detected by a conventional ADAS system.

[0161] In addition, it is efficient to calculate the evaluation scores Ea, Eb, Ec, Ed, and Ee for each cognitive function level based on, for example, a pre-made table showing the relationship between the detection results of the driving state and the evaluation scores Ea, Eb, Ec, Ed, and Ee.

[0162] The cognitive function characteristic analysis unit 44 compares the evaluation scores Ea, Eb, Ec, Ed, and Ee calculated in this way with the first threshold value Th1 and the second threshold value Th2 described above, thereby evaluating the degree of each cognitive function of the driver.

[0163] When the evaluation scores Ea, Eb, Ec, Ed, and Ee are greater than the first threshold Th1, the driver assistance device 10 of the present embodiment determines that the driver's cognitive function is in a normal state, that is, a safe state. In addition, when the evaluation scores Ea, Eb, Ec, Ed, and Ee are less than the first threshold Th1 and greater than the second threshold Th2 which is smaller than the first threshold Th1, the driver assistance device 10 determines that the corresponding cognitive function is in a state requiring attention that requires careful driving. Furthermore, when the evaluation scores Ea, Eb, Ec, Ed, and Ee are less than the second threshold Th2, the driver assistance device 10 determines that the corresponding cognitive function is in a dangerous state that makes it difficult to continue safe driving.

[0164] In addition, the cognitive function characteristic analysis unit 44 may analyze only the cognitive function calculated by the cognitive function score calculation unit 43 at the current time point, or may include the analysis of past cognitive functions stored in a manner associated with the driver by the cognitive function storage unit 45. By including the analysis of past cognitive functions, it is possible to estimate whether the cognitive function is in a recovery trend or a decline trend. Moreover, the training mode may be actively enabled for the cognitive function in a recovery trend. In addition, when a long-term decline trend of cognitive function is observed, the training mode may be enabled to prevent further decline.

[0165] In addition, events that are analyzed by the cognitive function score calculation unit 43 and the cognitive function characteristic analysis unit 44 may not occur frequently depending on the driving environment of the vehicle 30. Therefore, the evaluation scores Ea, Eb, Ec, Ed, and Ee related to all cognitive functions as targets may not be obtained all at once.

[0166] (Method for determining support content according to the evaluation score of cognitive function level)

[0167] use Fig. 9 and Fig.10 A method for determining the content of assistance performed by the driver assistance device 10 based on the cognitive function characteristics will be described below. Fig. 9This is a first diagram for explaining an example of the content of assistance provided by the driver assistance device based on the cognitive function characteristics. Fig.10 This is a second diagram for explaining an example of the content of assistance provided by the driver assistance device based on the cognitive function characteristics.

[0168] like Fig. 9 As shown, when the driver is in a state where he needs to pay attention to driving (level of attention required), the assistance content determination unit 48 assists in providing information for suppressing further decline of the driver's cognitive function. That is, the driving assistance (training mode) based on the information provision is made to function. This is because: since the driver's cognitive function is not in a completely declined state, there is a possibility of restoring the declined cognitive function to a normal level by continuing to drive while performing training related to the corresponding cognitive function. For example, if it is a temporary decline in cognitive function, it is expected that the cognitive function will be restored while receiving driving assistance. In addition, in the case of chronic cognitive decline and being in a state such as mild cognitive impairment (MCI) which is the pre-stage of dementia, there is a possibility that the cognitive function can be restored through such training. By restoring the cognitive function required for driving the vehicle through this training mode, it can be expected to continue safe driving.

[0169] In addition, if Fig. 9 As shown, when the driver's cognitive function is at a dangerous level, the support content determination unit 48 activates a function that assists the corresponding cognitive function among the driving support functions provided in the vehicle 30. That is, the driving support (driving support mode) based on the driving support function is activated.

[0170] In addition, the driver assistance device 10 evaluates the states of the characteristics of multiple cognitive functions, so there is a possibility that multiple cognitive functions are determined to be at a level that requires attention. In such a case, the auxiliary content determination unit 48 determines for which cognitive function the training mode is effective and for which cognitive function the driving assistance mode is effective. In addition, the auxiliary content determination unit 48 only makes the training mode effective for any one cognitive function. This is because: when the training modes for multiple cognitive functions are activated at the same time, the information prompted becomes more, so there is a possibility of causing confusion to the driver. Moreover, the auxiliary content determination unit 48 activates the driving assistance mode, in which the cognitive functions other than the cognitive functions that activate the training mode among the multiple cognitive functions that are determined to be at a level that requires attention are assisted. In addition, when it is determined that multiple cognitive functions are at a dangerous level, the auxiliary content determination unit 48 activates the driving assistance mode related to the corresponding multiple cognitive functions.

[0171] Next, use Fig.10To explain the specific contents of the training mode and driving assistance mode related to each cognitive function.

[0172] When the memory 80 drops to a level that requires attention, the auxiliary content determination unit 48 operates, for example, a function of recognizing the content of a sign and outputting a message conveying the content, a function of providing detailed route guidance, etc. as a training mode. In this way, the recovery of the driver's memory 80 estimated to be reduced is assisted. In addition, when the memory 80 drops to a dangerous level, the auxiliary content determination unit 48 operates, for example, a traffic sign recognition function of the vehicle 30. In addition, the upper speed limit of the vehicle 30 may be set based on the content of the recognized traffic sign, such as a speed limit. In this way, careless errors caused by inattention can be reduced.

[0173] When the execution force 81 drops to a level requiring attention, the assistance content determination unit 48 activates, for example, a function of outputting a message for recommending early braking as a training mode. Thus, the recovery of the driver's execution force 81 estimated to be reduced is assisted. In addition, when the execution force 81 drops to a dangerous level, the assistance content determination unit 48 activates, for example, a rear-end collision warning function, a vehicle distance maintenance function, or a sudden start prevention function, which are provided in the vehicle 30. Thus, the driver can be assisted in executing a part of the driving action.

[0174] When the attention 82 drops to a level that requires attention, the auxiliary content determination unit 48, for example, operates a function that outputs guidance related to the driving environment and guidance related to driving behavior as a training mode. In this way, the recovery of the driver's attention 82, which is estimated to be reduced, is assisted. In addition, when the attention 82 drops to a dangerous level, the auxiliary content determination unit 48 operates functions such as pedestrian detection and vehicle distance maintenance functions of the vehicle 30. In this way, the vehicle 30 can act as a substitute for a part of the area that the driver should pay attention to.

[0175] When the information processing power 83 drops to a level that requires attention, the auxiliary content determination unit 48, for example, reduces the speed of the car to encourage the driver to have room to pay attention to pedestrians, etc., or outputs a message to encourage rest, etc., as a training mode. In this way, the recovery of the driver's information processing power 83, which is estimated to be reduced, is assisted. In addition, when the information processing power 83 drops to a dangerous level, the auxiliary content determination unit 48 activates, for example, a function of maintaining the distance between vehicles and a collision alarm, etc., which are provided by the vehicle 30. In this way, the vehicle 30 can perform part of the information processing that the driver should perform.

[0176] When the visual-spatial cognition 84 drops to a level requiring attention, the auxiliary content determination unit 48, for example, activates a function of outputting guidance related to the driving environment as a training mode. Thus, the recovery of the driver's visual-spatial cognition 84, which is estimated to be decreased, is assisted. In addition, when the visual-spatial cognition 84 drops to a dangerous level, the auxiliary content determination unit 48 activates a function of maintaining a distance between vehicles, a function of preventing lane departure, or a parking assist function, etc., which are provided by the vehicle 30. Thus, the vehicle 30 can perform a part of the visual-spatial cognition that the driver should perform.

[0177] The driver assistance device 10 also continuously executes the calculation of the cognitive function when various assistance modes are in effect, and stops the operation of the assistance mode in effect when the cognitive function returns to a normal level.

[0178] (Changes in cognitive function over time)

[0179] use Fig.11 and Fig.12 The following describes the changes in cognitive function over time. Fig.11 This is a diagram for explaining an example of factors that may cause cognitive decline. Fig.12 This is a diagram showing an example of time-series changes in cognitive function.

[0180] The driver's cognitive function is not always constant, but changes according to various factors. For example, Fig.11 The shown factors change due to age growth factor 90, physical condition factor 91, skill factor 92, etc.

[0181] The aging factor 90 is a factor that occurs with the driver's aging, among the factors that cause changes in cognitive function. As the driver ages, the brain function declines accordingly. As a result, there is a possibility that cognitive function decline will occur. Generally speaking, the decline in physical function associated with the aging factor 90 progresses over a very long period of time, so, for example, by comparing the current cognitive function with the cognitive function a few months or years ago, it can be estimated that the decline in cognitive function caused by the aging factor 90 is progressing.

[0182] Physical condition factor 91 is a factor that is caused by the driver's physical condition among the factors that cause changes in cognitive function. If fatigue remains, attention function and executive function are easily affected (non-patent document 18). In addition, the narrowing of the scope of attention due to fatigue, or memory loss (non-patent document 19), or difficulty in maintaining attention with concentration due to sleepiness (non-patent document 19) belong to this situation. As specific examples of physical condition factor 91, factors related to diseases such as depression and mental illness, factors related to physical conditions such as poor physical condition, stress, and sleepiness, and factors related to mental activities such as absent-mindedness and thinking about problems can be cited. Since the changes in cognitive function caused by physical condition factor 91 mostly vary at intervals of 1 week or several days, by monitoring the changes in cognitive function over a relatively short period of time, it can be estimated that a decline in cognitive function caused by physical condition factor 91 has occurred.

[0183] Skill factor 92 is a factor that is caused by the driver's driving skills among the factors that cause changes in cognitive functions. Compared with skilled drivers, novice drivers tend to focus on areas that are important for predicting danger for a longer time (non-patent document 20), and in a road environment where there is a lot of information that must be processed, there is a possibility that information processing ability and attention will decrease. Changes in cognitive functions caused by skill factor 92 can be estimated by observing specific driving actions (for example, driving actions when turning left or right at an intersection, driving actions when overtaking, and driving actions when a car is parked). In addition, cognitive functions related to skill factor 92 also change according to the driving environment (for example, road environment, weather, time (day or night)).

[0184] In addition, the cognitive function of the driver does not change according to any one of the age growth factor 90, the physical condition factor 91 and the skill factor 92, but changes according to a combination of multiple factors. In addition, there are factors other than those shown here. For example, when the driving environment becomes high temperature, the cognitive function changes due to various factors such as dizziness and other environmental factors that affect the cognitive function (non-patent literature 21). The driver assistance device 10 of this embodiment estimates the main factors. In addition, the factors that change the cognitive function of the driver also consider factors other than these factors, but in the driver assistance device 10 of this embodiment, the changes in the cognitive function of the driver are caused by the age growth factor 90, the physical condition factor 91 and the skill factor 92. In addition, three factors are selected as factors here, but factors not recorded here can also be used as evaluation objects. In addition, the cognitive function decline factor can also be decomposed with other insights. In addition, it is also possible to focus on only one factor that you want to focus on, or it can be any combination of more than two.

[0185] Next, use Fig.12To qualitatively illustrate the changes in the driver's cognitive function. Fig.12 The graph G1 is a graph showing an example of the time series change of the evaluation score E of the cognitive function level of a certain driver. According to the graph G1, the evaluation score E decreases and falls below the second threshold value Th2 near the time ta and the time tc. That is, it is understood that the risk of an accident increases near the time ta and the time tc.

[0186] In addition, graph G2 is an example of plotting the amount of cognitive function decline due to aging of the same driver on the same time axis as graph G1. Graph G3 is an example of plotting the amount of cognitive function decline due to physical condition of the same driver on the same time axis as graph G1. Graph G4 is an example of plotting the amount of cognitive function decline due to skills of the same driver on the same time axis as graph G1.

[0187] The vertical axis of the graph G2 indicates the amount of cognitive function decline due to aging, indicating that the amount of cognitive function decline due to aging increases as the vertical axis direction goes downward. According to the graph G2, after time tb, the amount of cognitive function decline due to aging of the driver exceeds the threshold value Tha that affects safe driving. In such a case, it is desirable to urge the driver to pay attention to daily life after time tb.

[0188] The vertical axis of the graph G3 indicates the amount of cognitive function decline caused by physical condition, indicating that the amount of cognitive function decline caused by physical condition increases as the vertical axis direction goes downward. According to the graph G3, the amount of cognitive function decline caused by the driver's physical condition near the time tc exceeds the threshold value Thb that affects safe driving, and is extremely large. Then, if the graph G3 is compared with the graph G1, it can be seen that the physical condition factor is the main factor for the decline in cognitive function near the time tc. In such a case, it is desirable to encourage the driver to rest and recover near the time tc.

[0189] The vertical axis of the graph G4 indicates the amount of cognitive function decline caused by skills, indicating that the amount of cognitive function decline caused by skills increases as it goes downward in the vertical axis direction. According to the graph G4, the amount of cognitive function decline caused by driving skills of the driver exceeds the threshold value Thc that affects safe driving within the time displayed in the graph G4. This is because the road environment of the section displayed in the graph G4 is likely to be a road environment that the driver is not good at. And it can be seen that near the moment ta, the amount of cognitive function decline caused by skills of the driver exceeds the threshold value Thc that affects safe driving, and is extremely large. Then, if the graph G4 is compared with the graph G1, it can be seen that the skill factor is the main factor for the decline in cognitive function near the moment ta. In such a case, it is desired to prompt attention on the road that is not good at near the moment ta.

[0190] Thus, the driver assistance device 10 of this embodiment estimates whether the main factor of cognitive function decline is caused by aging, physical condition, or skills, and provides appropriate information and driving assistance according to the main factor of cognitive function decline to promote cognitive function recovery.

[0191] (Estimates of the main factors of cognitive decline)

[0192] use Fig.13A and Fig. 13B This paper explains the analysis of factors leading to cognitive decline. Fig.13A The first figure shows an example of factor analysis of cognitive decline. Fig. 13B The second figure shows an example of factor analysis of cognitive decline.

[0193] As in Fig.12 As explained in , drivers' cognitive functions change over time. Fig.13A An example is shown of comparing current (April 2022) cognitive function with cognitive function one year ago (April 2021). Fig.13A The evaluation score E of the cognitive function level indicates that the evaluation score E was at a safe level exceeding the first threshold Th1 one year ago, but is currently between the first threshold Th1 and the second threshold Th2, that is, at a level requiring attention.

[0194] When the evaluation score E of the driver's cognitive function level decreases as described above, the cognitive function decline factor estimation unit 46 of the driver assistance device 10 of this embodiment estimates whether the main factor is the aging factor (the first variable factor), the physical condition factor (the second variable factor), or the skill factor (the third variable factor).

[0195] Fig. 13BAn example of factor analysis of cognitive function decline is shown. The cognitive function decline factor estimation unit 46 compares the evaluation value of cognitive function related to the aging factor one year ago with the current evaluation value of cognitive function related to the aging factor. As a result, it is determined that the cognitive function related to the aging factor has declined compared to the cognitive function one year ago. That is, Fig. 13B As indicated by the leftward arrow in the figure, it is judged that cognitive function decline is related to the aging factor (the first variable factor).

[0196] In addition, 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 physical condition factor at present. As a result, it is determined that the cognitive function related to the physical condition factor has declined significantly compared with the cognitive function one year ago and exceeds the threshold value Thb that affects safe driving. That is, if Fig. 13B As indicated by the long leftward arrow in the figure, it is judged that the cognitive function related to the physical condition factor (the second variable factor) has declined significantly.

[0197] In addition, 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 skill factor at present. As a result, it is determined that the cognitive function related to the skill factor is improved compared with the cognitive function one year ago. Fig. 13B In the figure, the short rightward arrow indicates that the cognitive function related to the skill factor (the third variable factor) has improved. Fig. 13B In FIG. 1 , for convenience, the threshold value Tha, the threshold value Thb, and the threshold value Thc are recorded in the same position, but in fact, these threshold values ​​have different values.

[0198] The cognitive function decline factor estimation unit 46 is based on Fig. 13B The main factor of cognitive decline is estimated to be the physical condition factor with the longest leftward arrow based on the result. Then, the auxiliary content determination unit 48 determines to provide information related to the main factor of cognitive decline, such as "The physical condition factor score has dropped sharply. Please take a rest." The auxiliary content display unit 49 prompts the driver to make action changes corresponding to the main factor of cognitive decline by displaying this information on, for example, the central monitor 25a.

[0199] When the general Fig. 13B The estimated results are superimposed on Fig.13AWhen the current cognitive function is compared with the cognitive function one year ago, it can be seen that the cognitive function related to the aging factor and the physical condition factor has declined, and the skill factor has improved. Moreover, it can be seen that the decline in cognitive function caused by the physical condition factor is greater than the decline in cognitive function caused by the aging factor. In addition, an example of comparing the current cognitive function with the cognitive function one year ago is shown here, but the past time for comparison is not limited to one year ago.

[0200] (Recognition of changing states of cognitive function)

[0201] use Fig.14 A method for identifying a changing state of a driver's cognitive function will be described below. Fig.14 : is a diagram showing an example of a method for identifying a state in which cognitive function has declined. Fig.14 The following is a flow of a process for identifying a change state of the driver's cognitive function by the cognitive function decline factor estimation unit 46 of the driver assistance device 10 of this embodiment. Here, the change factors of cognitive function are three factors: aging factor, physical condition factor, and skill factor.

[0202] The cognitive function decline factor estimation unit 46 determines whether the amount of cognitive function decline caused by the aging factor is lower than the threshold value Tha (step S61). If it is determined that the amount of cognitive function decline caused by the aging factor is lower than the threshold value Tha (step S61: "Yes"), the process proceeds to step S62. On the other hand, if it is not determined that the amount of cognitive function decline caused by the aging factor is lower than the threshold value Tha (step S61: "No"), the process proceeds to step S65.

[0203] If it is determined in step S61 that the amount of cognitive function decline caused by the aging factor is lower than the threshold value Tha, the cognitive function decline factor estimation unit 46 determines whether the amount of cognitive function decline caused by the skill factor is lower than the threshold value Thc (step S62). If it is determined that the amount of cognitive function decline caused by the skill factor is lower than the threshold value Thc (step S62: "Yes"), the process proceeds to step S63. On the other hand, if it is not determined that the amount of cognitive function decline caused by the skill factor is lower than the threshold value Thc (step S62: "No"), the process proceeds to step S64.

[0204] If it is determined in step S62 that the amount of cognitive function decline caused by skill factors is lower than the threshold value Thc, the cognitive function decline factor estimation unit 46 determines whether the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S63). If it is determined that the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S63: "Yes"), the cognitive function 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 function decline caused by physical condition factors is lower than the threshold value Thb (step S63: "No"), the cognitive function decline factor estimation unit 46 determines that the driver's cognitive function declines due to physical condition factors (state 2) (step S69).

[0205] If it is not determined in step S62 that the amount of cognitive function decline caused by skill factors is lower than the threshold value Thc, the cognitive function decline factor estimation unit 46 determines whether the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S64). If it is determined that the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S64: "Yes"), the cognitive function decline factor estimation unit 46 determines that the driver's cognitive function declines due to skill factors (state 3) (step S70). On the other hand, if it is not determined that the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S64: "No"), the cognitive function decline factor estimation unit 46 determines that the driver's cognitive function declines due to physical condition factors and skill factors (state 4) (step S71).

[0206] If it is not determined in step S61 that the amount of cognitive function decline caused by the aging factor is lower than the threshold value Tha, the cognitive function decline factor estimation unit 46 determines whether the amount of cognitive function decline caused by the skill factor is lower than the threshold value Thc (step S65). If it is determined that the amount of cognitive function decline caused by the skill factor is lower than the threshold value Thc (step S65: "Yes"), the process proceeds to step S66. On the other hand, if it is not determined that the amount of cognitive function decline caused by the skill factor is lower than the threshold value Thc (step S65: "No"), the process proceeds to step S67.

[0207] If it is determined in step S65 that the amount of cognitive function decline caused by skill factors is lower than the threshold value Thc, the cognitive function decline factor estimation unit 46 determines whether the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S66). If it is determined that the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S66: "Yes"), the cognitive function decline factor estimation unit 46 determines that the driver's cognitive function declines due to age factors (state 5) (step S72). On the other hand, if it is not determined that the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S66: "No"), the cognitive function decline factor estimation unit 46 determines that the driver's cognitive function declines due to age factors and physical condition factors (state 6) (step S73).

[0208] If it is not determined in step S65 that the amount of cognitive function decline caused by skill factors is lower than the threshold value Thc, the cognitive function decline factor estimation unit 46 determines whether the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S67). If it is determined that the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S67: "Yes"), the cognitive function decline factor estimation unit 46 determines that the driver's cognitive function declines due to age growth factors and skill factors (state 7) (step S74). On the other hand, if it is not determined that the amount of cognitive function decline caused by physical condition factors is lower than the threshold value Thb (step S67: "No"), the cognitive function decline factor estimation unit 46 determines that the driver's cognitive function declines due to age growth factors, skill factors and physical condition factors (state 8) (step S75).

[0209] (State transition of cognitive function level)

[0210] use Fig.15 An example of the state transition of the driver's cognitive function level will be described. Fig.15 This is a diagram showing an example of changes over time in the driver's cognitive function level.

[0211] The driver assistance device 10 of the present embodiment monitors the change of the driver's cognitive function in time series. Fig.15 A transition diagram showing the changing state of cognitive function as shown. Fig.15 The vertical axis represents the state of cognitive function before the change. Fig.14 State 1 to state 8 described in. Fig.15 The horizontal axis shows the state of cognitive function after the change. Fig.14 State 1 to state 8 described in.

[0212] Since the state of the driver's cognitive function changes over time, the driver assistance device 10 observes the transition from the state m (m=1 to 8) at the previous moment to the state n (n=1 to 8) at the next moment. When the transition from state m to state n is detected, the change of the cognitive function change factor at that time is determined. Fig.15 The contents recorded in each item represent the changes in the variable factors of cognitive function. For convenience, the parts where the variable factors have deteriorated are marked with lowercase identifiers ((a) to (c)), and the parts where the variable factors have improved are marked with uppercase identifiers ((A) to (C)).

[0213] For example, when the state at the previous moment is state 2 and the current state is state 7, the driver assistance device 10 determines that the age factor and skill factor among the factors of variation of the driver's cognitive function have deteriorated. In addition, the driver assistance device 10 determines that the physical condition factor among the factors of variation of the driver's cognitive function has improved.

[0214] The driver assistance device 10 provides the driver with Fig.15 Information corresponding to the changing state of cognitive function is provided to prompt a change in behavior, particularly when cognitive function deteriorates.

[0215] (Information tips corresponding to changes in cognitive function)

[0216] use Fig.16 An example of presenting information according to a change in the driver's cognitive function will be described. Fig.16 This is a diagram showing an example of information presentation content according to changes in cognitive function levels.

[0217] like Fig.16 As shown, the driver assistance device 10 of this embodiment at least prompts the driver with information corresponding to the current state m (m=1 to 8). At this time, the driver assistance device 10 prompts the driver with information related to the main factors of cognitive decline and what points to pay attention to when driving. Fig.16 Although not described in the specification, it is desirable that the driver assistance device 10 prompts information corresponding to the state of the past cognitive function level and the current cognitive function level. For example, when an improvement in cognitive function is observed, it is desirable to convey the effect of the driver's behavior change by prompting information related to the variable factor that caused the improvement. In addition, when the state of cognitive function deterioration continues, it is desirable that the driver assistance device 10 further awakens attention or recommends the action of the driving assistance function.

[0218] (Information example (age growth factor))

[0219] use Fig.17 An example of providing information to a driver when age is a major factor will be described below. Fig.17 This is a diagram showing an example of information presented to the driver when the main factor of cognitive function decline is aging.

[0220] In the case where the main factor of cognitive function decline is the aging factor, the driver assistance device 10 prompts the driver that cognitive function decline due to aging is observed. Then, the driver is prompted to perform recovery training. After that, after driving, the driver is notified of the change in cognitive function decline due to aging, that is, the daily improvement. In addition, when the cognitive function decline due to aging has improved and the improved state has continued for more than a few days, for example, the information prompt related to the aging factor is stopped.

[0221] Specifically, if Fig.17 As shown, when the decline in cognitive function due to aging is not observed, Fig.17 The state transition A) does not provide any information prompts related to the age growth factor.

[0222] In the case where cognitive function deteriorates from a good state to a state that affects driving due to aging factors ( Fig.17 The driver is prompted with a message such as "Age factor score decreases. Recovery training is recommended." This allows the driver to recognize that cognitive function decreases with age.

[0223] When the decline in cognitive function caused by aging is improved ( Fig.17 The driver is prompted with information such as "The age growth factor score has improved. It seems that there is an effect of recovery training." This allows the driver to recognize that cognitive function has improved.

[0224] In the case of continued decline in cognitive function due to aging ( Fig.17 The driver is prompted with a message such as "The score of the age-related factor continues to decline. Please continue the recovery training." This allows the driver to realize that the decline in cognitive function caused by the age-related factor has not been improved.

[0225] In addition, by continuously monitoring the decline in cognitive function due to aging, it is possible to determine the risk of dementia for the driver. Fig.17 In addition to the various information displayed, you can also be notified that you are at risk of dementia.

[0226] (Information example (physical condition factors))

[0227] use Fig.18 An example of providing information to the driver when the physical condition factor is the main factor will be described below. Fig.18 This is a diagram showing an example of information presented to the driver when the main factor of cognitive function decline is a physical condition factor.

[0228] When the main factor of cognitive function decline is physical condition, the driver assistance device 10 presents a message to the driver to make him aware of the poor physical condition and the impact on driving caused by it, and also encourages the driver to take a rest and drive with caution as needed.

[0229] Specifically, if Fig.18 As shown, when the decline in cognitive function due to physical condition factors is not observed to continue ( Fig.18 Status transition E), no information prompts related to physical condition factors are given.

[0230] In the case where cognitive function deteriorates from a good state to a state that affects driving due to physical factors ( Fig.18 The driver is reminded of the deterioration of his physical condition by receiving a message such as "The score of the physical condition factor has decreased. Please drive more carefully than usual."

[0231] In cases where the decline in cognitive function caused by physical conditions has been improved ( Fig.18 The driver is prompted with a message such as "The score of the physical condition factor has improved. Please continue to drive safely." This allows the driver to realize that the cognitive function has improved.

[0232] In cases where cognitive decline due to physical conditions persists ( Fig.18 The driver is prompted with a message such as "The score of the physical condition factor has decreased, which affects safe driving. Rest is recommended." This makes the driver realize that the decline in cognitive function caused by the physical condition factor has not been improved.

[0233] (Information Proposal Example (Skill Factor))

[0234] use Fig.19 An example of providing information to a driver when the skill factor is a main factor will be described below. Fig.19 This is a diagram showing an example of information presented to the driver when the main factor of cognitive function decline is a skill factor.

[0235] When the main factor of cognitive function decline is a skill factor, the driver assistance device 10 presents a message to the driver to make him aware of the influence on driving.

[0236] Specifically, if Fig.19 As shown, when the state of cognitive function decline caused by skill factors is not observed to continue ( Fig.19 Status transition I), no information prompts related to skill factors are given.

[0237] In the case where cognitive function deteriorates from a good state to a state that affects driving due to skill factors ( Fig.19 The state transition J) is performed, and a message such as "Driving skills have slightly decreased. Please do not over-trust and drive carefully." is given. Thus, the driver is made aware of the decrease in driving skills. In addition, the driver is prompted to pay attention in a way that does not over-trust his own driving skills.

[0238] In cases where the decline in cognitive function caused by skill factors has been improved ( Fig.19 The driver is prompted with a message such as "Driving skills have improved. Please continue to drive safely." This allows the driver to recognize that cognitive function has improved.

[0239] In cases where the decline in cognitive function caused by skill factors continues ( Fig.19 The state transition L) is displayed, and a message such as "Driving skills have declined. Please be careful for safe driving." is given. As a result, the driver is made aware that the decline in cognitive function caused by skill factors has not been improved.

[0240] In addition, when the analysis results of the driver's past cognitive functions indicate that the driver is not good at driving environments (right turns at intersections, driving on busy streets, parking actions, etc.), information prompts indicating that the roads are not good can be given in advance. In addition, it is also possible to suggest support based on driving assistance while driving on the roads that the driver is not good at. In addition, it is also possible to obtain information about the destination from the driver at the beginning of driving and suggest route changes to avoid the roads that the driver is not good at. In addition, it is also possible to provide information prompts related to skill factors to the driver before, during, and after driving.

[0241] For example, before starting driving, if there is a road environment on the route that requires assistance, a message such as "Please be especially careful when turning right." may be provided.

[0242] In addition, when the road environment requires assistance during driving, a message such as "There is a merge ahead. Do you want to activate the merge assistance?" is displayed.

[0243] In addition, after driving is finished, the driving experience is summarized and information such as "Please be careful when turning right at the 00 intersection." and "There is a tendency for cognitive function to decline when driving at intersections recently, so be careful." is given.

[0244] In addition, the skill factor changes in the short term depending on the road environment on which the vehicle is traveling, and also changes over a long period of time depending on the driver's driving proficiency. Fig.19 The state transition shown may also compare the evaluation value related to driving skills when one was young (when one obtained a driver's license) with the current evaluation value related to driving skills.

[0245] (Calculation method of cognitive decline factor (age increase factor))

[0246] use Fig. 20 To illustrate how to calculate the effect of aging on cognitive decline. Fig. 20 This is a diagram showing an example of a method for calculating the degree of influence of the aging factor on the decline in cognitive function.

[0247] The cognitive function decline factor estimation unit 46 of the driver assistance device 10 calculates evaluation values ​​related to the age growth factor, the physical condition factor, and the skill factor, which are cognitive function change factors, by different independent methods. Regarding the evaluation value related to the age growth factor, for example, by comparing the cognitive function change during the month before one year ago with the cognitive function change during the most recent month of the same driver, the change in cognitive function caused by the age growth factor is calculated.

[0248] Specifically, if Fig. 20 As shown, the change in cognitive function at present (for example, April 2022) is compared with the change in cognitive function one year ago (for example, April 2021). The change in cognitive function in a certain month is calculated, for example, by averaging the evaluation results of cognitive function for each day of the month. In addition, since the evaluation value of cognitive function cannot be obtained on days when driving is not performed, it is sufficient to average the evaluation values ​​of cognitive function on days when driving is performed using the number of days when driving is performed.

[0249] Fig. 20 The example shown shows that the current average value of cognitive function is lower than the average value one year ago. In this way, the cognitive function decline factor estimation unit 46 of the driver assistance device 10 evaluates the change in cognitive function over a long period of time assuming that the change is caused by the aging factor.

[0250] (Calculation method of factors affecting cognitive function decline (physical condition factors))

[0251] The cognitive function decline factor estimation unit 46 of the driver assistance device 10 calculates an evaluation value related to the physical condition factor based on the number of blinks of the driver, the movement of the line of sight, or the body temperature of the driver measured by the driver monitoring camera 21b installed in the vehicle 30. In addition, the evaluation may be performed based on the output of a sensor for measuring an electrocardiogram, a pulse, etc., which is not shown in the figure, for example, provided on the steering wheel of the vehicle 30 (Non-Patent Document 17).

[0252] The cognitive function score calculation unit 43 calculates the evaluation score E of the driver's cognitive function level based on the information obtained from these various sensors. Then, the cognitive function decline factor estimation unit 46 determines that the change in the evaluation score E of the cognitive function level calculated in this way is caused by the driver's physical condition factor.

[0253] (Calculation method of cognitive decline factor (skill factor))

[0254] The cognitive function decline factor estimation section 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 occurs as a result of the driving operation.

[0255] For example, regarding basic driving behaviors (straight ahead driving, turning driving, braking operation, etc.), the evaluation value related to the driver's skill factor can be calculated based on the difference between the average or preferred action pattern and the action pattern actually performed by the driver.

[0256] More specifically, the road environment on which the vehicle 30 is traveling can be identified by the car navigation device and surrounding cameras of the vehicle 30, so that an evaluation value related to driving skills can be calculated for each traffic environment (when going straight, changing lanes, turning left or right, parking, etc.).

[0257] (Other calculation methods for cognitive decline factors)

[0258] use Fig.21 Other calculation methods to account for factors of cognitive decline. Fig.21 This is a flowchart showing an example of another method for estimating factors of cognitive function decline.

[0259] The cognitive function decline factor estimation unit 46 of the driver assistance device 10 can also calculate the evaluation values ​​related to the age growth factor, physical condition factor, and skill factor as the variable factors of cognitive function by a method different from the above-mentioned method. Specifically, if the age growth factor, physical condition factor, and skill factor as factors that cause cognitive function decline are compared, the age growth factor is considered to be a factor that gradually has an impact over a long period of time (for example, in years). In addition, the physical condition factor is considered to be a factor that has an impact in a shorter period of time (for example, in months or weeks) than the age growth factor. Moreover, the skill factor is considered to be a factor that has an impact depending on the road environment on which the vehicle is traveling at the time. Therefore, by setting the period for taking the average of the evaluation values ​​related to cognitive function to the period corresponding to each factor, the degree of impact of each factor on cognitive function can be simply quantified.

[0260] More specifically, regarding the cognitive function level of the driver, its maximum value Lmax and the cognitive function level L(t) at each time t are obtained. The cognitive function level L(t) is equivalent to the evaluation score E of the cognitive function level 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) in the past minute (third prescribed period), the average value Lhour(t) (second average value) in the past hour (second prescribed period), and the average value Lmonth(t) (first average value) in the past month (first prescribed 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 in the past month as the change amount ΔLage of the cognitive function caused by the aging factor. In addition, the cognitive function decline factor estimation unit 46 estimates the difference between the average value Lhour(t) of the cognitive function level in the past hour and the average value Lmonth(t) of the cognitive function level in the past month as the change amount ΔLhealth of the cognitive function caused by the physical condition factor. Furthermore, the cognitive function decline factor estimation unit 46 estimates the difference between the cognitive function level L(t) at time t and the total as the change in cognitive function caused by skill factors ΔLskill, which is the sum of the maximum value Lmax of the cognitive function level, the change in cognitive function caused by aging factors, the change in cognitive function caused by aging factors ΔLage, and the change in cognitive function caused by physical condition factors ΔLhealth.

[0261] Next, follow Fig.21 The flowchart of the process of estimating factors of cognitive decline is described below.

[0262] The cognitive function decline factor estimation unit 46 obtains the maximum value Lmax of the cognitive function level of the driver (step S21 ). Specifically, the cognitive function decline factor estimation unit 46 obtains the maximum value of the cognitive function level L(t) of the driver stored in the cognitive function storage unit 45 .

[0263] The cognitive function score calculation unit 43 calculates the cognitive function level L(t) at time t (step S22 ).

[0264] The cognitive function decline factor estimation unit 46 calculates the average value Lminute(t) of the cognitive function level L(t) for the past minute (step S23).

[0265] 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 ).

[0266] The cognitive function decline factor estimation unit 46 calculates the average value Lmonth(t) of the cognitive function level L(t) for the past month (step S25 ).

[0267] The cognitive function decline factor estimation unit 46 estimates the change in cognitive function due to the aging factor (step S26). Specifically, the cognitive function decline factor estimation unit 46 estimates the change ΔLage of cognitive function due to the aging factor by using formula (1). In addition, although not described in the flowchart, the estimated change ΔLage of cognitive function due to the aging factor is stored in the cognitive function storage unit 45 in a manner associated with the information used to identify the driver.

[0268] ΔLage=Lmonth(t)-Lmax… (1)

[0269] The cognitive function decline factor estimation unit 46 estimates the change in cognitive function caused by the physical condition factor (step S27). Specifically, the cognitive function decline factor estimation unit 46 estimates the change ΔLhealth of the cognitive function caused by the physical condition factor by using formula (2). In addition, although not described in the flowchart, the estimated change ΔLhealth of the cognitive function caused by the physical condition factor is stored in the cognitive function storage unit 45 in a manner associated with the information used to identify the driver.

[0270] ΔLhealth=Lhour(t)-Lmonth(t)… (2)

[0271] The cognitive function decline factor estimation unit 46 estimates the change in cognitive function caused by the skill factor (step S28). Specifically, the cognitive function decline factor estimation unit 46 estimates the change in cognitive function caused by the skill factor ΔLskill by formula (3). In addition, although not recorded in the flowchart, the estimated change in cognitive function caused by the skill factor ΔLskill is stored in the cognitive function storage unit 45 in a manner associated with the information used to identify the driver. In addition, for the skill factor, the road environment on which the vehicle is traveling at this time has a greater impact, so it is expected that the driver assistance device 10 obtains information related to the road environment in the past minute, for example, from the car navigation system, surrounding cameras, etc., and also stores the acquired information related to the road environment in the cognitive function storage unit 45.

[0272] ΔLskill=Lminute(t)-(Lmax+ΔLage+ΔLhealth)… (3)

[0273] The cognitive function decline factor estimation unit 46 estimates the main factor causing the decline in cognitive function level L(t) by comparing the magnitude of the change in cognitive function ΔLage due to the aging factor, the magnitude of the change in cognitive function ΔLhealth due to the physical condition factor, and the magnitude of the change in cognitive function ΔLskill due to the skill factor (step S29). The cognitive function decline factor estimation unit 46 then ends the process. Fig.21 processing.

[0274] (Processing Flow of Driver Assistance Device)

[0275] use Fig. 22 The flow of processing performed by the driver assistance device 10 according to the present embodiment will be described. Fig. 22 This is a flowchart showing an example of the flow of processing performed by the driver assistance device according to the present embodiment.

[0276] The driving state detection unit 42 determines whether the ignition switch of the vehicle 30 is turned on (step S41). If it is determined that the ignition switch of the vehicle 30 is turned 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 turned on (step S41: "No"), the determination of step S41 is repeated. In addition, in the case where the vehicle 30 is an electric vehicle, it is sufficient to determine whether the main switch is turned on instead of determining whether the ignition switch is turned on.

[0277] If it is determined in step S41 that the ignition switch of the vehicle 30 is turned on, the driver identification unit 41 identifies the driver (step S42 ).

[0278] The cognitive function score calculation unit 43 performs a pre-driving cognitive function evaluation on the driver (step S43). In the pre-driving cognitive function evaluation, for example, the evaluation results of the driver's past cognitive function stored in the cognitive function storage unit 45 are read out, and the driver's cognitive function changes from the past are obtained. In addition, by obtaining the output of sensors that measure the driver's body temperature, electrocardiogram, pulse, etc., the cognitive function is evaluated based on the driver's physical condition information before starting driving.

[0279] The cognitive function characteristic output unit 47 presents the result evaluated in step S43 to the driver (step S44 ).

[0280] The driving state detection unit 42 determines whether the driving of the vehicle 30 has started (step S45). If it is determined that the 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 the driving of the vehicle 30 has started (step S45: "No"), the determination of step S45 is repeated.

[0281] The cognitive function score calculation unit 43 and the cognitive function characteristic analysis unit 44 evaluate the driver's cognitive function during driving (step S46). The cognitive function evaluation during driving is performed, for example, according to Figure 7 The flowchart is carried out.

[0282] The cognitive function storage unit 45 stores the analysis result in step S46 in association with the information for specifying the driver (step S47 ).

[0283] The cognitive function characteristic analysis unit 44 determines whether the evaluation score E of the cognitive function level (or cognitive function level L(t)) calculated in step S46 is a level requiring attention or a dangerous level (step S48). If it is determined that the evaluation score E of the cognitive function level is a level requiring attention or a dangerous level (step S48: "Yes"), the process proceeds to step S49. On the other hand, if it is not determined that the evaluation score E of the cognitive function level is a level requiring attention or a dangerous level (step S48: "No"), the process proceeds to step S51.

[0284] If it is determined in step S48 that the evaluation score E of the cognitive function level is at a level requiring attention or a dangerous level, the cognitive function decline factor estimation unit 46 estimates the main factors of cognitive function decline (step S49). The main factors of cognitive function decline are estimated, for example, according to Fig.21 The flowchart is carried out.

[0285] The cognitive function characteristic output unit 47 presents information corresponding to the main factors of cognitive function decline to the driver (step S50). Examples of the presented information are as follows: Figures 16 to 19In addition, in step S50, the cognitive function characteristic output unit 47 may also transmit the state of the driver's cognitive function via the communication interface 27 (see Figure 3 ) is output to a pre-registered smartphone, wearable terminal, etc. By referring to the information output in this way, it can help the driver's daily health management and life management.

[0286] 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. 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.

[0287] (Execution of training mode and driving assistance mode for cognitive impairment)

[0288] The driver assistance device 10 of the present embodiment may present information related to the main factors of cognitive function decline when switching to the training mode or the driving assistance mode. Fig.23 This is a diagram for explaining a function of presenting information related to a major factor of cognitive function decline when the driver assistance device changes its operation mode.

[0289] When the assistance content determination unit 48 of the driver assistance device 10 determines to operate the training mode in order to suppress further deterioration of the driver's cognitive function characteristics, the assistance information presentation unit 50 may present the driver with a major factor of cognitive function deterioration.

[0290] For example Fig.23 As shown, it is assumed that when it is detected that the attention in the cognitive function has dropped to a level requiring attention, it is decided to start the training mode by the driver assistance device 10 to achieve functional improvement related to the driver's attention. At this time, when the driver's cognitive function has dropped due to physical condition factors, the auxiliary information prompting unit 50 prompts the driver with information related to the main factors of the decline in cognitive function, such as "physical condition factor score has dropped, attention has dropped. Start recovery training", that is, information that makes the driver aware of the poor physical condition and prompts attention.

[0291] Furthermore, when the assistance content determination unit 48 of the driver assistance device 10 determines to activate the driving assistance mode to assist the driving action associated with the cognitive function characteristics, the assistance information presentation unit 50 may present the driver with the main factors of cognitive function decline.

[0292] For example Fig.23As shown, when it is detected that the attention in the cognitive function has dropped to the level requiring attention, it is assumed that it is determined to start the driving assistance mode by the driver assistance device 10 to compensate for the decline in the cognitive function related to the driver's attention. At this time, when the driver's cognitive function has dropped due to physical condition factors, the auxiliary information prompting unit 50 prompts the driver with information related to the main factor of the decline in cognitive function, such as "The physical condition factor score has further dropped. Turn on the driving assistance related to attention."

[0293] Furthermore, the driver assistance device 10 presents information on the main factors of cognitive function decline to the driver at the timing of transition to the training mode or the driving assistance mode.

[0294] (Effects of the Implementation Methods)

[0295] As described above, the driver assistance device 10 of the present embodiment includes: a driving state detection unit 42 that detects at least one of the driver's driving action on the vehicle, the driver's biological information during 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 associated with one or more different brain functions; a cognitive function storage unit 45 that stores the numerical value calculated by the cognitive function score calculation unit 43 for the same driver and the analysis result of the cognitive function characteristic analysis unit 44 in time series; a cognitive function decline factor estimation unit 46 that calculates the influence of a plurality of variable factors that cause the driver's cognitive function decline based on the storage content of the cognitive function storage unit 45 and estimates the variable factor that becomes a main factor; and a driver assistance unit 60 that assists the driver based on the estimation result of the cognitive function decline factor estimation unit 46 or information corresponding to the estimation result. Therefore, it is possible to estimate the decline factor of the driver's cognitive function.

[0296] In the driver assistance device 10 of the present embodiment, the cognitive function decline factor estimation unit 46 estimates the change factor of the cognitive function by comparing the storage content corresponding to the current state of the cognitive function storage unit 45 with the storage content corresponding to a predetermined past time point. Therefore, based on the information on the cognitive function over time, the change of the cognitive state of the driver can be easily and accurately estimated.

[0297] In the driver assistance device 10 of the present embodiment, the variable factor includes at least one of the driver's age factor 90, physical condition factor 91, and skill factor 92. Therefore, the variable factor of the driver's cognitive function can be estimated in association with the driver's physical state or mental state.

[0298] In the driver assistance device 10 of the present embodiment, the driver assistance unit 60 includes a cognitive function characteristic output unit 47 (output unit) that outputs information corresponding to the estimation result of the cognitive function decline factor estimation unit 46 in a manner corresponding to past numerical values ​​related to the main factors causing the cognitive function decline of the driver and current numerical values ​​related to the main factors. Therefore, when the cognitive function declines, the driver can accurately recognize his or her own state by presenting information corresponding to the decline amount.

[0299] In addition, in the driver assistance device 10 of the present embodiment, when the aging factor 90 is the main factor causing the cognitive function decline of the driver, the cognitive function characteristic output unit 47 (output unit) outputs information indicating the existence of cognitive function decline due to aging or information related to recovery training for cognitive function decline due to aging to the driver. Therefore, the situation of cognitive function decline due to aging can be reliably communicated to the driver.

[0300] In addition, in the driver assistance device 10 of the present embodiment, when the physical condition factor 91 is the main factor causing the driver's cognitive function to decline, the cognitive function characteristic output unit 47 (output unit) outputs information to the driver to make the driver aware of the poor physical condition and urge attention, or information to urge rest. Therefore, the situation of cognitive function decline caused by the physical condition can be reliably communicated to the driver.

[0301] In addition, in the driver assistance device 10 of the present embodiment, when the skill factor 92 is the main factor causing the driver's cognitive function to decline, the cognitive function characteristic output unit 47 (output unit) outputs information indicating that the driver is in an unfamiliar road state or recommends a route change to avoid an unfamiliar road. Therefore, the driver can be reliably informed of the decline in cognitive function due to driving skills.

[0302] In the driver assistance device 10 of the present embodiment, the driver assistance unit 60 further includes an assistance content determination unit 48, which determines whether to enable an information provision function that assists in providing information for suppressing further decline of the driver's cognitive function or to enable a driving assistance function that assists in driving actions associated with the declined cognitive function characteristics from among a plurality of functions possessed by the vehicle 30, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristics analysis unit 44 and a threshold value, and when the assistance function determined by the assistance content determination unit 48 becomes effective, the cognitive function characteristics output unit 47 (output unit) outputs an estimation result of the cognitive function decline factor estimation unit 46 or information corresponding to the estimation result. Therefore, the reason for transitioning to the training mode and the reason for transitioning to the driving assistance mode can be reliably communicated to the driver.

[0303] In the driver assistance device 10 of the present embodiment, the driver assistance unit 60 further includes an assistance content determination unit 48, which determines whether to enable an information provision function that assists in providing information for suppressing further decline of the driver's cognitive function or to enable a driving assistance function that assists in driving actions associated with the declined cognitive function characteristics from among a plurality of functions possessed by the vehicle 30, based on a comparison between the cognitive function characteristics calculated by the cognitive function characteristics analysis unit 44 and a threshold value, and assists the driver when an unfavorable road state extracted based on the estimation result of the skill factor by the cognitive function decline factor estimation unit 46 exists on the driving route. Therefore, driving support can be provided when the driver is driving on a road that is unfavorable to the driver.

[0304] In addition, in the driver assistance device 10 of the present embodiment, the cognitive function characteristic output unit 47 (output unit) outputs information corresponding 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, the change of the estimation result of the driver's cognitive function characteristics can be monitored by a portable terminal outside the vehicle. This can help the driver's own health management. In addition, by sending the estimation result of the driver's cognitive function characteristics to the hospital, it can help the doctor to guide the driver's life management.

[0305] In the driver assistance device 10 of the present embodiment, the cognitive function decline factor estimation unit 46 estimates the change in cognitive function related to the aging factor 90 based on the first average value of the evaluation score E (numerical value) in the past month (first prescribed period), estimates the change in cognitive function related to the physical condition factor 91 based on the second average value of the evaluation score E in the past hour (second prescribed period) shorter than the first prescribed period, and estimates the change in cognitive function related to the skill factor 92 based on the third average value of the evaluation score E in the past minute (third prescribed period) shorter than the second prescribed period. Therefore, the main factor in which the cognitive function has changed can be estimated by simple calculation processing.

[0306] The embodiments of the present invention have been described above, but the above embodiments are presented as examples and are not intended to limit the scope of the present invention. The new embodiments can be implemented in various other ways. In addition, various omissions, substitutions, and changes can be made without departing from the scope of the main purpose of the invention. In addition, the embodiments are included in the scope and main purpose of the invention, and are included in the invention described in the claims and their equivalents.

[0307] In addition, the present disclosure may also have the following structures. (1)

[0309] A driver assistance device, comprising:

[0310] a driving state detection unit for detecting at least one of a driver's driving action on the vehicle, the driver's biological information during driving, and a behavior of the vehicle;

[0311] a cognitive function score calculation section 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 section;

[0312] a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic associated with one or more different brain functions;

[0313] a cognitive function storage unit that stores the numerical value calculated by the cognitive function score calculation unit and the analysis result of the cognitive function characteristic analysis unit for the same driver in time series;

[0314] a cognitive function decline factor estimation unit that calculates the influence of a plurality of variable factors that cause the cognitive function decline of the driver based on the storage content of the cognitive function storage unit and estimates a variable factor that becomes a main factor; and

[0315] A driver assistance unit assists the driver based on the estimation result of the cognitive function decline factor estimation unit or information corresponding to the estimation result. (2)

[0317] The driver assistance device according to the above (1), wherein:

[0318] The cognitive function decline factor estimation unit estimates a change factor of the cognitive function by comparing the storage content corresponding to the present time in the cognitive function storage unit with the storage content corresponding to a predetermined past time point. (3)

[0320] The driver assistance device according to (1) or (2), wherein:

[0321] The variable factor includes at least one of the driver's age increase factor, physical condition factor, and skill factor. (4)

[0323] The driver assistance device according to any one of (1) to (3), wherein:

[0324] The driver assistance unit further includes an output unit configured to output information corresponding to an estimation result of the cognitive function decline factor estimation unit in a manner corresponding to a past numerical value related to the main factor and a current numerical value related to the main factor. (5)

[0326] The driver assistance device according to the above (4), wherein:

[0327] When the aging factor is the main factor, the output unit outputs information indicating the presence of aging-related cognitive function decline or information related to recovery training for aging-related cognitive function decline to the driver. (6)

[0329] The driver assistance device according to (4) or (5), wherein:

[0330] When the physical condition factor is the main factor, the output unit outputs information to the driver to make the driver aware of the poor physical condition and to urge the driver to pay attention, or information to urge the driver to take a rest. (7)

[0332] The driver assistance device according to any one of (4) to (6), wherein:

[0333] When the skill factor is the main factor, the output unit outputs information indicating that the driver is in an unfamiliar road state or recommends a route change to avoid an unfamiliar road to the driver. (8)

[0335] The driver assistance device according to any one of (4) to (7), wherein:

[0336] The driver assistance unit further includes an assistance content determination unit that determines whether to enable an information provision function or a driving assistance function from among a plurality of functions possessed by the vehicle based on a comparison between the cognitive function characteristic calculated by the cognitive function characteristic analysis unit and a threshold value, wherein the information provision function is a function of assisting in providing information for suppressing further decline in the cognitive function of the driver, and the driving assistance function is a function of assisting in driving actions associated with the declined cognitive function characteristic.

[0337] The output unit outputs an estimation result of the cognitive function decline factor estimation unit or information corresponding to the estimation result when the auxiliary function determined by the auxiliary content determination unit becomes effective. (9)

[0339] The driver assistance device according to (7) or (8), wherein:

[0340] The driver assistance unit further includes an assistance content determination unit that determines whether to enable an information provision function or a driving assistance function from among a plurality of functions possessed by the vehicle based on a comparison between the cognitive function characteristic calculated by the cognitive function characteristic analysis unit and a threshold value, wherein the information provision function is a function of assisting in providing information for suppressing further decline in the cognitive function of the driver, and the driving assistance function is a function of assisting in driving actions associated with the declined cognitive function characteristic.

[0341] The assistance content determination unit assists the driver when an unfamiliar road state extracted based on the estimation result of the skill factor by the cognitive function decline factor estimation unit exists on the driving route. (10)

[0343] The driver assistance device according to any one of (4) to (9), wherein:

[0344] The output unit outputs information according to an estimation result of the cognitive function decline factor estimation unit to a device connected to the driver assistance apparatus via a network. (11)

[0346] The driver assistance device according to any one of (3) to (10), wherein:

[0347] The cognitive function decline factor estimation unit estimates a change in cognitive function associated with the aging factor based on a first average value of the numerical value during a first predetermined period.

[0348] The cognitive function decline factor estimation unit estimates a change in cognitive function related to the physical condition factor based on a second average value of the numerical value during a second predetermined period shorter than the first predetermined period.

[0349] The cognitive function decline factor estimation unit estimates a change in cognitive function related to the skill factor based on a third average value of the numerical values ​​during a third predetermined period that is shorter than the second predetermined period. (12)

[0351] A driver assistance system comprising:

[0352] a driving state detection unit for detecting at least one of a driver's driving action on the vehicle, the driver's biological information during driving, and a behavior of the vehicle;

[0353] a cognitive function score calculation section 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 section;

[0354] a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic associated with one or more different brain functions;

[0355] a cognitive function storage unit that stores the numerical value calculated by the cognitive function score calculation unit and the analysis result of the cognitive function characteristic analysis unit for the same driver in time series;

[0356] a cognitive function decline factor estimation unit that calculates the influence of a plurality of variable factors that cause the cognitive function decline of the driver based on the storage content of the cognitive function storage unit and estimates a variable factor that becomes a main factor; and

[0357] A driver assistance unit assists the driver based on the estimation result of the cognitive function decline factor estimation unit or information corresponding to the estimation result. (13)

[0359] A driver assistance method, comprising:

[0360] A driving state detection process, detecting at least one of a driver's driving action on the vehicle, the driver's biological information during driving, and the behavior of the vehicle;

[0361] a cognitive function score calculation process, which calculates a value indicating whether the driver's cognitive function is high or low based on the information detected in the driving state detection process;

[0362] a cognitive function characteristic analysis process of analyzing the numerical value calculated in the cognitive function calculation process as a cognitive function characteristic associated with one or more different brain functions;

[0363] a cognitive function storage process for storing, in time series, the numerical value calculated in the cognitive function score calculation process and the analysis result of the cognitive function characteristic analysis process for the same driver;

[0364] a cognitive function decline factor estimation process for calculating the influence of a plurality of variable factors causing the cognitive function decline of the driver based on the stored content of the cognitive function storage process, and estimating a variable factor that becomes a main factor; and

[0365] The driver assistance process assists the driver based on the estimation result of the cognitive function decline factor estimation process or information corresponding to the estimation result.

[0366] Industrial Applicability

[0367] 10: driver assistance device; 30: vehicle; 40: driving environment detection unit; 41: driver determination unit; 42: driving status detection unit; 43: cognitive function score calculation unit; 44: cognitive function characteristic analysis unit; 45: cognitive function storage unit; 46: cognitive function decline factor estimation unit; 47: cognitive function characteristic output unit (output unit); 48: auxiliary content determination unit; 49: auxiliary content display unit; 50: auxiliary information prompt unit; 51: driving assistance control unit; 60: driver assistance unit; 80: memory; 81: execution ability; 82: attention; 83: information processing ability; 84: visual spatial cognition; 90: age growth factor; 91: physical condition factor; 92: skill factor; E, Ea, Eb, Ec, Ed, Ee: evaluation score (numerical value); Th1: first threshold value (threshold value); Th2: second threshold value (threshold value); Tha, Thb, Thc: threshold values.

Claims

1. A driver assistance device comprising: a driving state detection unit for detecting at least one of a driver's driving action on the vehicle, the driver's biological information during driving, and a behavior of the vehicle; a cognitive function score calculation section 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 section; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic associated with one or more different brain functions; a cognitive function storage unit that stores the numerical value calculated by the cognitive function score calculation unit and the analysis result of the cognitive function characteristic analysis unit for the same driver in time series; a cognitive function decline factor estimation unit that calculates the influence of a plurality of variable factors that cause the cognitive function decline of the driver based on the stored content of the cognitive function storage unit, and estimates a variable factor that is a main factor; as well as A driver assistance unit assists the driver based on the estimation result of the cognitive function decline factor estimation unit or information corresponding to the estimation result.

2. The driver assistance device according to claim 1, wherein: The cognitive function decline factor estimation unit estimates a change factor of the cognitive function by comparing the storage content corresponding to the present time in the cognitive function storage unit with the storage content corresponding to a predetermined past time point.

3. The driver assistance device according to claim 1, wherein: The variable factor includes at least one of the driver's age increase factor, physical condition factor, and skill factor.

4. The driver assistance device according to claim 3, wherein: The driver assistance unit further includes an output unit configured to output information corresponding to an estimation result of the cognitive function decline factor estimation unit in a manner corresponding to a past numerical value related to the main factor and a current numerical value related to the main factor.

5. The driver assistance device according to claim 4, wherein: When the aging factor is the main factor, the output unit outputs information indicating the presence of aging-related cognitive function decline or information related to recovery training for aging-related cognitive function decline to the driver.

6. The driver assistance device according to claim 4, wherein: When the physical condition factor is the main factor, the output unit outputs information to the driver to make the driver aware of the poor physical condition and to urge the driver to pay attention, or information to urge the driver to take a rest.

7. The driver assistance device according to claim 4, wherein: When the skill factor is the main factor, the output unit outputs information indicating that the driver is in an unfamiliar road state or recommends a route change to avoid an unfamiliar road to the driver.

8. The driver assistance device according to claim 4, wherein: The driver assistance unit further includes an assistance content determination unit that determines whether to enable an information provision function or a driving assistance function from among a plurality of functions possessed by the vehicle based on a comparison between the cognitive function characteristic calculated by the cognitive function characteristic analysis unit and a threshold value, wherein the information provision function is a function of assisting in providing information for suppressing further decline in the cognitive function of the driver, and the driving assistance function is a function of assisting in driving actions associated with the declined cognitive function characteristic. The output unit outputs an estimation result of the cognitive function decline factor estimation unit or information corresponding to the estimation result when the auxiliary function determined by the auxiliary content determination unit becomes effective.

9. The driver assistance device according to claim 7, wherein: The driver assistance unit further includes an assistance content determination unit that determines whether to enable an information provision function or a driving assistance function from among a plurality of functions possessed by the vehicle based on a comparison between the cognitive function characteristic calculated by the cognitive function characteristic analysis unit and a threshold value, wherein the information provision function is a function of assisting in providing information for suppressing further decline in the cognitive function of the driver, and the driving assistance function is a function of assisting in driving actions associated with the declined cognitive function characteristic. The assistance content determination unit assists the driver when an unfamiliar road state extracted based on the estimation result of the skill factor by the cognitive function decline factor estimation unit exists on the driving route.

10. The driver assistance device according to claim 4, wherein: The output unit outputs information according to an estimation result of the cognitive function decline factor estimation unit to a device connected to the driver assistance apparatus via a network.

11. The driver assistance device according to claim 3, wherein: The cognitive function decline factor estimation unit estimates a change in cognitive function associated with the aging factor based on a first average value of the numerical value during a first predetermined period. The cognitive function decline factor estimation unit estimates a change in cognitive function related to the physical condition factor based on a second average value of the numerical value during a second predetermined period shorter than the first predetermined period. The cognitive function decline factor estimation unit estimates a change in cognitive function related to the skill factor based on a third average value of the numerical values ​​during a third predetermined period that is shorter than the second predetermined period.

12. A driver assistance system comprising: a driving state detection unit for detecting at least one of a driver's driving action on the vehicle, the driver's biological information during driving, and a behavior of the vehicle; a cognitive function score calculation section 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 section; a cognitive function characteristic analysis unit that analyzes the numerical value calculated by the cognitive function score calculation unit as a cognitive function characteristic associated with one or more different brain functions; a cognitive function storage unit that stores the numerical value calculated by the cognitive function score calculation unit and the analysis result of the cognitive function characteristic analysis unit for the same driver in time series; a cognitive function decline factor estimation unit that calculates the influence of a plurality of variable factors that cause the cognitive function decline of the driver based on the storage content of the cognitive function storage unit, and estimates a variable factor that becomes a main factor; as well as A driver assistance unit assists the driver based on the estimation result of the cognitive function decline factor estimation unit or information corresponding to the estimation result.

13. A driver assistance method, comprising: A driving state detection process, detecting at least one of a driver's driving action on the vehicle, the driver's biological information during driving, and the behavior of the vehicle; a cognitive function score calculation process, which calculates a value indicating whether the driver's cognitive function is high or low based on the information detected in the driving state detection process; a cognitive function characteristic analysis process of analyzing the numerical value calculated in the cognitive function score calculation process as a cognitive function characteristic associated with one or more different brain functions; a cognitive function storage process for storing, in time series, the numerical value calculated in the cognitive function score calculation process and the analysis result of the cognitive function characteristic analysis process for the same driver; a cognitive function decline factor estimation process for calculating the influence of a plurality of variable factors causing the cognitive function decline of the driver based on the stored content of the cognitive function storage process, and estimating a variable factor that becomes a main factor; as well as The driver assistance process assists the driver according to the estimation result of the cognitive function decline factor estimation process or information corresponding to the estimation result.

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