Driving assistance device and computer program

Abstract

To provide a driving assistance device and a computer program with which it is possible to present causes and improvement methods to a driver when having caused anxiety or stress to surrounding drivers by his own driving for improving a driving technique of a driver.SOLUTION: A driving assistance device for assisting in driving a vehicle comprises one or a plurality of processors, and one or a plurality of memories which is communicably connected to the one or plurality of processors. The processors execute the processes including: acquiring information regarding a travel state of the host vehicle and an ambient environment of the host vehicle, comparing stored data of information regarding the travel states of a plurality of vehicles in a drive condition belonging to a same category as the drive condition of the host vehicle with information regarding the travel state of the host vehicle and determining a factor that provokes road rage, and presenting feedback information that pertains to a driving behavior of the driver of the host vehicle on the basis of the factor that provokes road rage.SELECTED DRAWING: Figure 10

Description

[Technical Field]

[0001] The present disclosure relates to a driving assistance device and a computer program that assist a driver in driving a vehicle. [Background technology]

[0002] Tailgating is known as a nuisance type of vehicle driving. Patent Document 1 discloses a driving assistance device that detects tailgating behavior and prevents accidents and trouble with following vehicles. Specifically, the driving assistance device in Patent Document 1 determines the surrounding situation from outputs of a navigation device, a road information collection device, and a camera, determines the state of the vehicle itself from outputs of a speed sensor, an acceleration sensor, a camera, a lighting system, and a vehicle control system, determines the state of other vehicles from outputs of a camera, an inter-vehicle communication device, and a radar, calculates the risk of tailgating from the surrounding situation, the state of the vehicle itself, and the state of other vehicles, and executes notification control and operation control based on the calculation results.

[0003] Furthermore, Patent Document 2 discloses a driving assistance device for suppressing tailgating. Specifically, the driving assistance device in Patent Document 2 acquires driving information related to the driving of the vehicle, determines based on the driving information whether the vehicle is engaging in tailgating, which is driving that makes the vehicle more likely to be tailgated by other vehicles, and executes notification processing and driving control according to the determination result. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2006-205773 [Patent Document 2] Patent Publication No. 2021-33529 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the driving assistance devices disclosed in Patent Documents 1 and 2 do not present the driver of the vehicle with the causes of tailgating or ways to improve the situation, and therefore are unlikely to provide a fundamental solution. For example, if a driver with poor driving skills causes anxiety or stress to surrounding drivers through his or her driving, the driving assistance devices disclosed in Patent Documents 1 and 2 enable the driver of the vehicle to avoid the immediate danger through notification processing and driving control of the driving assistance device, but do not allow the driver of the vehicle to understand the causes of tailgating or ways to improve the situation. As a result, there remains the possibility that the driver of the vehicle will continue to drive in the same way and be tailgated by surrounding vehicles.

[0006] The present disclosure has been made in consideration of the above-mentioned problems, and the purpose of the present disclosure is to provide a driving assistance device and a computer program that can improve the driver's driving skills by presenting to the driver the causes and ways to improve the situation when the driver's driving causes anxiety or stress to other drivers around them. [Means for solving the problem]

[0007] In order to solve the above problems, according to one aspect of the present disclosure, a driving assistance device that assists in driving a vehicle is provided, which includes one or more processors and one or more memories communicatively connected to the one or more processors, and the processor acquires information on the driving state of the vehicle and information on the surrounding environment of the vehicle, compares accumulated data on information on the driving states of multiple vehicles in driving conditions that belong to the same classification as the driving condition of the vehicle with the information on the driving state of the vehicle to determine factors that induce aggressive driving, and presents feedback information regarding the driving behavior of the driver of the vehicle based on the factors that induce aggressive driving.

[0008] In addition, in order to solve the above problem, according to another aspect of the present disclosure, there is provided a computer program applied to a driving assistance device that assists in driving a vehicle, the computer program causing a processor to execute processing including acquiring information on the driving conditions of the vehicle and information on the surrounding environment of the vehicle, comparing accumulated data on the driving conditions of multiple vehicles in driving conditions that belong to the same category as the driving conditions of the vehicle with the information on the driving conditions of the vehicle to determine factors that induce aggressive driving, and presenting feedback information regarding the driving behavior of the driver of the vehicle based on the factors that induce aggressive driving. [Effects of the Invention]

[0009] As described above, according to the present disclosure, when a driver's driving causes anxiety or stress to other drivers around them, the driver can be informed of the cause and remedy, thereby improving the driver's driving skills. [Brief explanation of the drawings]

[0010] [Figure 1] 1 is a schematic diagram illustrating a configuration example of a vehicle equipped with a driving assistance device according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a block diagram showing a configuration example of a driving assistance device according to the embodiment; [Figure 3] 10 is a flowchart showing a tailgating determination process performed by the driving assistance device according to the embodiment. [Figure 4] FIG. 10 is an explanatory diagram showing an example of an image display of a survey result. [Figure 5] 4 is a flowchart showing a main routine of processing operations executed by the driving assistance device according to the embodiment; [Figure 6] 4 is a flowchart showing a process during driving performed by the driving assistance device according to the embodiment. [Figure 7] 4 is a flowchart showing a driving behavior modification process performed by the driving assistance device according to the embodiment. [Figure 8] 10 is a flowchart showing a first example of a tailgating cause determination process according to the embodiment. [Figure 9] 10 is a flowchart showing a second example of the tailgating factor determination process according to the embodiment. [Figure 10] FIG. 10 is an explanatory diagram showing an example of a comparison result of driving behaviors. [Figure 11] 10 is a flowchart showing a post-driving process performed by the driving assistance device according to the embodiment. [Figure 12] FIG. 10 is an explanatory diagram showing an example of the layout of a feedback screen. [Figure 13] FIG. 10 is an explanatory diagram showing an example of a moving image pattern to be played back. [Figure 14] FIG. 10 is an explanatory diagram showing an example of a moving image pattern to be played back. [Figure 15] FIG. 10 is an explanatory diagram showing an example of a moving image pattern to be played back. [Figure 16] 10 is a flowchart showing a post-driving process performed by the driving assistance device according to the embodiment. [Figure 17] FIG. 10 is an explanatory diagram showing data on the frequency of occurrence of dangerous driving in a travel area. [Figure 18] FIG. 10 is an explanatory diagram showing data on average cruising speeds in a travel area. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, preferred embodiments of the present disclosure will be described in detail with reference to the accompanying drawings. In this specification and drawings, components having substantially the same functional configurations are designated by the same reference numerals, and redundant description will be omitted.

[0012] <1. Overall vehicle configuration> First, an example of the overall configuration of a vehicle to which a driving assistance device according to an embodiment of the present disclosure can be applied will be described.

[0013] Fig. 1 is a schematic diagram showing an example of the configuration of a vehicle 1 equipped with a driving assistance device 50 according to this embodiment. The vehicle 1 shown in Fig. 1 is configured as a four-wheel drive vehicle in which drive torque output from a drive force source 9 that generates drive torque for the vehicle is transmitted to a left front wheel 3LF, a right front wheel 3RF, a left rear wheel 3LR, and a right rear wheel 3RR (hereinafter collectively referred to as "wheels 3" unless a distinction is required). The drive force source 9 may be an internal combustion engine such as a gasoline engine or a diesel engine, a drive motor, or both an internal combustion engine and a drive motor.

[0014] The vehicle 1 may be an electric vehicle equipped with two drive motors, for example, a front-wheel drive motor and a rear-wheel drive motor, or an electric vehicle equipped with drive motors corresponding to each of the wheels 3. If the vehicle 1 is an electric vehicle or a hybrid electric vehicle, the vehicle 1 is equipped with a secondary battery that stores power to be supplied to the drive motors, and a motor or a generator such as a fuel cell that generates power to charge the battery.

[0015] The vehicle 1 is equipped with a driving force source 9, an electric steering device 15, and a brake fluid pressure control unit 20 as devices used to control the operation of the vehicle 1. The driving force source 9 outputs driving torque that is transmitted to the front drive shaft 5F and the rear drive shaft 5R via a transmission, a front wheel differential mechanism 7F, and a rear wheel differential mechanism 7R (not shown). The operation of the driving force source 9 and the transmission is controlled by a vehicle control device 41 that includes one or more electronic control units (ECUs: Electronic Control Units).

[0016] The front-wheel drive shaft 5F is provided with an electric steering device 15. The electric steering device 15 includes an electric motor and a gear mechanism (not shown), and is controlled by a vehicle control device 41 to adjust the steering angles of the left front wheel 3LF and the right front wheel 3RF. During manual driving, the vehicle control device 41 controls the electric steering device 15 based on the steering angle of the steering wheel 13 by the driver. During automatic driving, the vehicle control device 41 controls the electric steering device 15 based on a target steering angle set by the driving assistance device 50.

[0017] The brake system of the vehicle 1 is configured as a hydraulic brake system. A brake fluid pressure control unit 20 adjusts the hydraulic pressure supplied to brake calipers 17LF, 17RF, 17LR, and 17RR (hereinafter collectively referred to as "brake calipers 17" unless a distinction is required) provided on the front, rear, left, and right drive wheels 3LF, 3RF, 3LR, and 3RR, respectively, to generate braking force. The operation of the brake fluid pressure control unit 20 is controlled by a vehicle control device 41. If the vehicle 1 is an electric vehicle or a hybrid electric vehicle, the brake fluid pressure control unit 20 is used in conjunction with regenerative braking using the drive motor.

[0018] The vehicle control device 41 includes one or more electronic control devices that control the drive of the driving force source 9 that outputs the driving torque of the vehicle 1, the electric steering device 15 that controls the steering wheel 13 or the steering angle of the steering wheels, and the brake fluid pressure control unit 20 that controls the braking force of the vehicle 1. The vehicle control device 41 may also have a function of controlling the drive of a transmission that changes the speed of the output output from the driving force source 9 and transmits it to the wheels 3. The vehicle control device 41 is configured to be able to acquire information transmitted from the driving assistance device 50, and is configured to be able to execute automatic driving control of the vehicle 1. Furthermore, when the vehicle 1 is being manually driven, the vehicle control device 41 acquires information on the amount of operation by the driver, and controls the drive of the driving force source 9 that outputs the driving torque of the vehicle 1, the electric steering device 15 that controls the steering wheel 13 or the steering angle of the steering wheels, and the brake fluid pressure control unit 20 that controls the braking force of the vehicle 1.

[0019] The vehicle 1 also includes front-facing cameras 31LF, 31RF, a rear-facing camera 31R, a LiDAR (Light Detection And Ranging) 31S, an in-vehicle camera 33, a biometric sensor 34, a vehicle status sensor 35, a GPS (Global Positioning System) sensor 37, a vehicle-to-vehicle communication unit 39, a navigation system 40, and an HMI (Human Machine Interface) 43.

[0020] The front photographing cameras 31LF, 31RF, the rear photographing camera 31R, and the LiDAR 31S constitute a surrounding environment sensor for acquiring information about the surrounding environment of the vehicle 1. The front photographing cameras 31LF, 31RF and the rear photographing camera 31R capture images of the area in front of or behind the vehicle 1 and generate image data. The front photographing cameras 31LF, 31RF and the rear photographing camera 31R are equipped with imaging elements such as CCDs (Charged-Coupled Devices) or CMOSs ​​(Complementary Metal-Oxide-Semiconductors), and transmit the generated image data to the driving assistance device 50.

[0021] 1, the front imaging cameras 31LF, 31RF are configured as stereo cameras including a pair of left and right cameras, and the rear imaging camera 31R is configured as a so-called monocular camera, but each may be either a stereo camera or a monocular camera. In addition to the front imaging cameras 31LF, 31RF and the rear imaging camera 31R, the vehicle 1 may also be equipped with cameras that are provided on the side mirrors 11L, 11R, for example, to capture images of the left rear or right rear.

[0022] The LiDAR 31S transmits optical waves and receives reflected waves of the optical waves, and detects an object and the distance to the object based on the time between transmitting the optical waves and receiving the reflected waves. The LiDAR 31S transmits the detection data to the driving assistance device 50. The vehicle 1 may be equipped with one or more sensors, instead of or in addition to the LiDAR 31S, of a radar sensor such as a millimeter-wave radar and an ultrasonic sensor as a surrounding environment sensor for acquiring information about the surrounding environment.

[0023] The interior camera 33 is made up of one or more sensors that detect information about the driver of the vehicle 1. The interior camera 33 is equipped with an imaging element such as a CCD or CMOS, captures images of the interior of the vehicle, and generates image data. The interior camera 33 transmits the generated image data to the driving assistance device 50. In this embodiment, the interior camera 33 is positioned so that it can capture images of the driver of the vehicle 1. Only one interior camera 33 may be installed, or multiple interior cameras 33 may be installed.

[0024] The biosensor 34 detects the driver's biometric information and transmits the detected data to the driving assistance device 50. The biosensor 34 may be, for example, a radio wave Doppler sensor for detecting the driver's heartbeat, or a non-wearable pulse sensor for detecting the driver's pulse. The biosensor 34 may also be an electrode set embedded in the steering wheel 13 for measuring the driver's heartbeat or electrocardiogram. The biosensor 34 may also be a pressure measuring instrument embedded in the driver's seat for measuring the seat pressure distribution while the driver is seated in the seat. The biosensor 34 may also be a displacement sensor for detecting changes in the position of a seat belt to measure the driver's heartbeat or respiration. The biosensor 34 may also be a Time of Flight (TOF) sensor for detecting information about the driver's position. The biosensor 34 may also be a thermograph for measuring the surface temperature of the driver's skin.

[0025] The biosensor 34 may also be a wearable sensor that is attached to the driver to detect the driver's biometric information. The wearable biosensor 34 may be, for example, a wristwatch-type sensor or a wearable device that is attached to the head or arm. These wearable devices may have a function for detecting the driver's biometric information, such as heart rate, pulse, blood pressure, and body temperature. The wearable biosensor 34 may be connected to the driving assistance device 50 directly or via a communication means such as a Controller Area Network (CAN) or a Local Internet (LIN). Alternatively, the wearable biosensor 34 may be configured to be able to communicate with the driving assistance device 50 via a wireless communication means such as Bluetooth (registered trademark), Near Field Communication (NFC), Wi-Fi (wireless fidelity), or a Local Area Network (WLAN).

[0026] The vehicle state sensor 35 is composed of one or more sensors that detect the operation state and behavior of the vehicle 1. The vehicle state sensor 35 includes at least one of a steering angle sensor, an accelerator position sensor, a brake stroke sensor, a brake pressure sensor, and an engine RPM sensor, and detects the operation state of the vehicle 1, such as the steering angle of the steering wheel 13 or the steering wheels, the accelerator position, the brake operation amount, or the engine RPM. The vehicle state sensor 35 also includes at least one of a vehicle speed sensor, an acceleration sensor, and an angular velocity sensor, and detects the vehicle behavior, such as the vehicle speed, longitudinal acceleration, lateral acceleration, and yaw rate. The vehicle state sensor 35 also includes a sensor that detects the operation of a turn signal, and detects the operation state of the turn signal. The vehicle state sensor 35 also includes a sensor that detects the inclination state of the vehicle 1, and detects the inclination state of the road. The vehicle state sensor 35 transmits a sensor signal containing the detected information to the driving assistance device 50.

[0027] The vehicle-to-vehicle communication unit 39 is an interface for communicating with vehicles traveling around the vehicle 1 (hereinafter also referred to as "other vehicles").

[0028] The navigation system 40 is a known navigation system that sets a driving route to a destination set by the occupant and notifies the driver of the driving route. A GPS sensor 37 is connected to the navigation system 40, and receives satellite signals from GPS satellites via the GPS sensor 37 to obtain position information on map data of the vehicle 1. Note that instead of the GPS sensor 37, an antenna that receives satellite signals from another satellite system that identifies the position of the vehicle 1 may be used.

[0029] The HMI 43 is driven by the driving assistance device 50 and presents various information to the driver by means of image display, audio output, etc. The HMI 43 includes, for example, a display device provided in the instrument panel and a speaker provided in the vehicle. The display device may have the function of the display device of the navigation system 40. The HMI 43 may also include a head-up display that displays an image on the front window of the vehicle 1.

[0030] <2. Driving assistance devices> Next, the driving assistance device 50 according to this embodiment will be described in detail.

[0031] (2-1. Configuration example) FIG. 2 is a block diagram showing an example of the configuration of the driving assistance device 50 according to this embodiment. The driving assistance device 50 is connected to an ambient environment sensor 31, an in-vehicle camera 33, a biometric sensor 34, and a vehicle state sensor 35 via a dedicated line or communication means such as CAN or LIN. The driving assistance device 50 is also connected to an inter-vehicle communication unit 39, a navigation system 40, a vehicle control device 41, and an HMI 43 via a dedicated line or communication means such as CAN or LIN. The driving assistance device 50 is not limited to an electronic control device mounted on the vehicle 1, and may be a terminal device such as a smartphone or a wearable device.

[0032] The driving assistance device 50 functions as a device that assists in driving the vehicle 1 by having one or more processors, such as CPUs (Central Processing Units), execute a computer program. The computer program is a computer program that causes the processor to execute the operations, described below, that should be performed by the driving assistance device 50. The computer program executed by the processor may be recorded on a recording medium that functions as a storage unit (memory) 53 provided in the driving assistance device 50, or may be recorded on a recording medium built into the driving assistance device 50 or any recording medium that can be externally attached to the driving assistance device 50.

[0033] Recording media for recording computer programs include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical recording media such as CD-ROMs (Compact Disk Read Only Memory), DVDs (Digital Versatile Disks), and Blu-ray (registered trademark), magneto-optical media such as floptical disks, memory elements such as RAMs (Random Access Memory) and ROMs (Read Only Memory), flash memories such as USB (Universal Serial Bus) memories and SSDs (Solid State Drives), and other media capable of storing programs.

[0034] The driving assistance device 50 includes a control unit 51 and a memory unit 53. The control unit 51 is configured with one or more processors such as CPUs. Part or all of the control unit 51 may be configured with updatable firmware or the like, or may be a program module or the like executed by instructions from the CPU or the like. The memory unit 53 is configured with a recording medium (memory) such as RAM or ROM. However, the number and type of memory units 53 are not particularly limited. The memory unit 53 records information such as computer programs executed by the control unit 51, various parameters used in arithmetic processing, detection data, and arithmetic results.

[0035] (2-2. Database) The driving assistance device 50 is communicatively connected to a driving database 71, a tailgating case database 73, a normal driving database 75, and a driver database 77. The driving database 71, the tailgating case database 73, the normal driving database 75, and the driver database 77 are each configured by a memory element such as a RAM, or an updatable recording medium such as an HDD (Hard Disk Drive), a CD (Compact Disk), a DVD (Digital Versatile Disk), an SSD (Solid State Drive), a USB flash, or a storage device. However, the type of recording medium is not particularly limited.

[0036] One or all of the driving database 71, tailgating case database 73, normal driving database 75, and driver database 77 may be mounted on the vehicle 1, or may be stored on a server that can communicate with the driving assistance device 50 via wireless communication means such as mobile communication. Also, some or all of the databases may be configured as a single database.

[0037] (Driving database) The driving database 71 is a database that records information about the driving state of the vehicle 1. The driving state information recorded in the driving database 71 includes, for example, vehicle behavior data, driving behavior data, and surrounding environment data. The vehicle behavior data includes, for example, data on vehicle speed, longitudinal acceleration, lateral acceleration, longitudinal jerk, and lateral jerk. The driving behavior data includes, for example, data on accelerator operation amount, brake operation amount, and steering angle operated by the driver. The vehicle behavior data and driving behavior data are generated and recorded based on information about the vehicle behavior and operating state detected by the vehicle state sensor 35.

[0038] The surrounding environment data includes at least one of data on the traffic environment in which the vehicle 1 is traveling, such as the shape of the curve of the road on which the vehicle is traveling, the slope, the lane in which the vehicle is traveling, the road width, surrounding obstacles, the relative relationship with other vehicles (relative speed, relative position, and relative distance), the speed limit, or the traffic time period. The surrounding environment data also includes at least one of information on the location, section, or area in which the vehicle 1 is traveling (hereinafter collectively referred to as "travel area information"). The surrounding environment data is generated and recorded based on information detected by the surrounding environment sensor 31 and position information acquired via the GPS sensor 37.

[0039] The driving state information recorded in the driving database 71 may be all driving data collected while the vehicle 1 is traveling, or may be driving data when the tailgating determination unit 63 described later determines that the vehicle is in a situation where it is being tailgated by another vehicle. However, among the driving state information recorded in the driving database 71, the driving data when the tailgating determination unit 63 determines that the vehicle is in a situation where it is being tailgated by another vehicle includes information on the type of tailgating that has occurred, along with a tailgating flag.

[0040] (Database of tailgating cases) The tailgating case database 73 is a database that records information about driving conditions when tailgating occurs. The information about driving conditions recorded in the tailgating case database 73 includes, for example, vehicle behavior data, driving behavior data, and surrounding environment data, similar to the information recorded in the driving database 71. The information about driving conditions recorded in the tailgating case database 73 includes data collected in cases where a driver of another vehicle felt anxious, angry, or stressed by a certain vehicle, and data collected in cases where another vehicle tailgated a certain vehicle (each of these cases is collectively referred to as a "tailgating event").

[0041] Data on tailgating incidents includes information on the driving conditions of vehicles that caused surrounding vehicles to feel anxious, angry, or stressed, or vehicles that were tailgated (hereinafter collectively referred to as "tailgated vehicles"), and information on the driving conditions of vehicles in which drivers who felt anxious, angry, or stressed about surrounding vehicles or vehicles that performed tailgating (hereinafter collectively referred to as "tailgating vehicles").The driving condition information recorded in the tailgating case database 73 includes information on the driving conditions of tailgating vehicles and tailgated vehicles for a certain period of time before and after the occurrence of the tailgating incident.

[0042] In addition, the data of each tailgating event recorded in the tailgating case database 73 is classified into tailgating scenes that are set based on vehicle behavior data, driving behavior data, and surrounding environment data. The classification of tailgating scenes is associated with factors that induce tailgating, such as driving scenes that involve driving behavior that leaves a large distance between the vehicle and the vehicle in front, or driving scenes that involve a large speed difference between the vehicle and other vehicles traveling in adjacent lanes on roads with two or more lanes in each direction.

[0043] (Normal operation database) The normal driving database 75 is a database that records information about driving conditions in which the host vehicle 1 is not subject to tailgating. The driving condition information recorded in the normal driving database 75 includes, for example, vehicle behavior data, driving behavior data, and surrounding environment data, similar to the information recorded in the driving database 71. The driving condition information recorded in the normal driving database 75 may be data collected and recorded by the driving assistance devices 50 of multiple vehicles including the host vehicle, or may be data that has been created and stored in advance as model driving data, or may be data that includes both of these.

[0044] (driver database) The driver database 77 is a database that records information about drivers. In this embodiment, the driver database 77 records feature data extracted from facial images of each driver and identification information associated with each feature data. The identification information is not particularly limited and may be data consisting of letters, numbers, and symbols, for example. The driver database 77 also records data on the tailgating driving characteristics of each driver. The tailgating driving characteristic data is recorded in association with the driver's identification information.

[0045] (2-3. Functional configuration of the control unit) The control unit 51 of the driving assistance device 50 acquires information on the driving state of the vehicle (own vehicle) 1, information on the driving state of other vehicles driving around the own vehicle 1, information on the relative position between the own vehicle 1 and the other vehicles, and information on the tailgating characteristics of the driver of the other vehicle, and performs processing to determine whether or not the own vehicle 1 is in a situation where it is being tailgated by another vehicle based on the acquired information.

[0046] 2, the control unit 51 of the driving assistance device 50 includes a driver determination unit 61, an acquisition unit 62, a tailgating determination unit 63, a tailgating factor determination unit 64, and a feedback presentation unit 65. Each of these units may be a function realized by a processor such as a CPU executing a computer program, but may also be configured partially or entirely by analog circuits.

[0047] Below, the function of each part of the control unit 51 will be briefly explained, and then the processing operation of the control unit 51 will be specifically explained.

[0048] (Driver determination section) The driver determination unit 61 executes a process of identifying the driver of the vehicle 1 (hereinafter also referred to as "own vehicle") equipped with the driving assistance device 50, based on image data transmitted from the in-vehicle imaging camera 33. The driver determination unit 61 may also identify the driver of the own vehicle 1 based on information input by the driver or a passenger via an input device such as a touch panel.

[0049] (Acquisition Department) The acquisition unit 62 executes a process of acquiring various information related to the host vehicle 1 and the other vehicle. Specifically, the acquisition unit 62 acquires information on the driving state of the host vehicle 1, information on the driving state of the other vehicle, information on the driving position such as the driving lane in which the host vehicle 1 is driving, information on the relative positions of the host vehicle 1 and the other vehicle, and information on the surrounding environment of the host vehicle 1. The acquisition unit 62 also acquires information on the detected driver of the other vehicle. Specifically, the acquisition unit 62 acquires information on the emotions of the driver of the other vehicle and information on the tailgating driving characteristics of the driver of the other vehicle. The acquisition unit 62 records the acquired information in the storage unit 53 as time-series data.

[0050] The information on tailgating characteristics is information that can be used to estimate the likelihood that an individual driver will engage in tailgating. The information on tailgating characteristics includes, for example, data on the individual driver's history of tailgating or dangerous driving. The information on tailgating characteristics may also include data on acceleration / deceleration, steering, flashing, and high beam operation performed per certain period of time. This information may be recorded data collected by a control device installed in each vehicle while the individual driver is driving the vehicle. Whether tailgating or dangerous driving has been performed can be detected using known determination techniques. Furthermore, the more frequently a driver repeats acceleration / deceleration and steering operations, or the more times the driver flashes or turns on the high beams per certain period of time, the more likely the driver is to engage in tailgating.

[0051] The information on the driver's tailgating behavior may also include information on the results of a questionnaire collected from each driver in advance and stored in the control device. The information on the results of the questionnaire may include, for example, information on the frequency with which the driver feels irritated while driving, the actions taken when irritated (such as honking the horn, flashing the lights, or shouting), and the causes of the irritation.

[0052] The acquisition unit 62 may acquire identification information for identifying the driver of the other vehicle and extract information on the driver's tailgating characteristics from data recorded in the driver database 77. For example, the acquisition unit 62 may extract facial features of the driver of the other vehicle based on detection data transmitted from the surrounding environment sensor 31 and identify the driver of the other vehicle by referring to the driver database 77. The acquisition unit 62 may also recognize the number printed on the license plate of the other vehicle based on image data transmitted from the surrounding environment sensor 31 and identify the driver based on the number. Data associating the number with the driver may be recorded in the driver database 77, for example, or may be acquired from metadata accessible via mobile communication or the like. The acquisition unit 62 may also acquire identification information for identifying the driver of the other vehicle from the other vehicle through vehicle-to-vehicle communication.

[0053] (Tailgating Determination Unit) The tailgating determination unit 63 executes a process of determining whether or not the host vehicle 1 is in a situation where it is being tailgated by another vehicle, based on information on the driving state of the host vehicle 1, information on the driving state of the other vehicle, information on the relative position between the host vehicle 1 and the other vehicle, and information on the tailgating driving characteristics of the driver of the other vehicle. In this embodiment, a determination formula is generated based on information on the driving state of the host vehicle 1, information on the driving state of the other vehicle, information on the relative position between the host vehicle 1 and the other vehicle, and information on the tailgating driving characteristics of the driver of the other vehicle, and the determination formula is used to determine whether or not the host vehicle 1 is in a situation where it is being tailgated by the other vehicle.

[0054] (Tailgating factor determination unit) When it is determined that the host vehicle 1 is in a situation where it is being tailgated by another vehicle, the tailgating factor determination unit 64 executes a process of determining factors that induce tailgating in the host vehicle 1. For example, the tailgating factor determination unit 64 determines factors that induce tailgating by comparing information on the driving state recorded in a normal driving database 75, which accumulates information on the driving states of multiple vehicles in surrounding environments that belong to the same classification as the surrounding environment of the host vehicle 1, with information on the driving state of the host vehicle 1. The tailgating factor determination unit 64 records information on the determined factors that induce tailgating in the memory unit 53.

[0055] (Feedback presentation section) The feedback presentation unit 65 executes a process of presenting feedback information regarding the driving behavior of the driver of the vehicle 1 based on factors that induce tailgating. In this embodiment, the feedback presentation unit 65 is configured to be able to execute a process of presenting evasive action when it is determined that the vehicle 1 is in a situation where it is subject to tailgating. In addition, in this embodiment, the feedback presentation unit 65 is configured to be able to execute a pre-driving process of presenting feedback information before driving starts and a post-driving process of presenting feedback information after driving ends.

[0056] <3. Operation of driving assistance device> Next, an example of the processing operation by the control unit 51 of the driving assistance device 50 according to this embodiment will be specifically described. In the following description, an example will be given in which the other vehicle is a rear vehicle traveling behind the host vehicle 1.

[0057] [Tailgating driving detection processing] Before describing a series of processing operations by the control unit 51, a tailgating determination process by the tailgating determination unit 63 of the driving assistance device 50 according to this embodiment will be described.

[0058] FIG. 3 shows a flowchart of the tailgating determination process. The tailgating determination unit 63 recognizes the driving environment of the vehicle 1 (step S11). Specifically, the tailgating determination unit 63 acquires information about the surrounding environment of the vehicle 1 based on the detection data transmitted from the surrounding environment sensor 31, and recognizes the driving situation of the vehicle 1. The driving situation includes information about the curve shape, inclination state, driving lane, road width, positions of surrounding obstacles, and the number and positions of vehicles behind the vehicle 1 on the road on which the vehicle 1 is traveling.

[0059] The driving situation of the vehicle 1 may also include information on the speed limit of the road on which the vehicle 1 is traveling and information on the driving area. The speed limit information and driving area information may be detected based on image data transmitted from the surrounding environment sensor 31, may be acquired through road-to-vehicle communication or a beacon, or may be determined based on position information on map data transmitted from the GPS sensor 37. Furthermore, the driving situation of the vehicle 1 may also include information on the current time. Note that the driving situation of the vehicle 1 may also include information other than the exemplified information.

[0060] Next, the tailgating determination unit 63 generates a determination formula for determining whether or not the vehicle 1 is in a situation where it is being tailgated (step S13). As an example, the tailgating determination unit 63 generates the following determination formula (1) according to the driving situation.

[0061] Driving evaluation value (a × X1 + b × X2 + c × X3 + d × X4) > judgment threshold (X0 - X5) ... (1) X0: Criterion threshold X1: Vehicle 1's driving state evaluation value X2: Evaluation value of the driving condition of the rear vehicle X3: Relative position evaluation value between the vehicle 1 and the vehicle behind X4: Emotion evaluation value of the driver of the rear vehicle X5: Evaluation value of tailgating driving characteristics of the driver of the rear vehicle a, b, c, d: Coefficients set according to driving conditions

[0062] In the above judgment formula (1), if the driving evaluation value calculated based on the driving state of the vehicle 1, the driving state of the vehicle behind, the relative position between the vehicle 1 and the vehicle behind, and the emotions of the driver of the vehicle behind exceeds a judgment threshold corrected by the tailgating driving characteristics of the driver of the vehicle behind, it is judged that the vehicle 1 is in a situation where it is being tailgated.

[0063] For example, the driving state evaluation value X1 of the host vehicle 1 is the evaluation value of the vehicle speed (km / h) of the host vehicle 1, the driving state evaluation value X2 of the following vehicle is the evaluation value of the vehicle speed (km / h) of the following vehicle, and the relative position evaluation value X3 between the host vehicle 1 and the following vehicle is the evaluation value of the inter-vehicle distance (m) between the host vehicle 1 and the following vehicle. Also, the emotion evaluation value X4 of the driver of the following vehicle is an evaluation value that indicates the degree of anxiety, anger, or stress of the driver of the following vehicle, and is relatively evaluated between 0 and 100, for example, with 0 representing a normal state and 100 representing an angry state.

[0064] The acquisition unit 62 analyzes the facial expression of the driver of the following vehicle based on the detection data transmitted from the surrounding environment sensor 31, and estimates the driver's emotions. For example, the acquisition unit 62 can estimate the driver's emotions using an emotion estimation program based on FACS (Facial Action Coding System). Alternatively, if vehicle-to-vehicle communication is possible between the host vehicle 1 and the following vehicle, the acquisition unit 62 may acquire data on the driver's facial expression or data on the estimation result of the emotion from the following vehicle. Alternatively, the acquisition unit 62 may acquire biometric data, such as heart rate and pulse rate, from the following vehicle from which emotions can be estimated, and estimate the emotion of the driver of the following vehicle based on the biometric data. The tailgating determination unit 63 relatively evaluates the emotion evaluation value X4 between 0 and 100 based on the estimated emotion of the driver of the following vehicle.

[0065] The coefficients a, b, c, and d of the evaluation values ​​X1, X2, X3, and X4 are variables set according to the driving scenario that determines whether or not the subject vehicle is being tailgated. For example, when the subject vehicle 1 is traveling on a highway, the slower the vehicle speed of the subject vehicle 1, the more likely the subject vehicle is to be tailgated. For this reason, the coefficient a of the driving state evaluation value (vehicle speed) X1 of the subject vehicle 1 is set so that the value of "a×X1" increases as the evaluation value X1 of the subject vehicle 1's vehicle speed decreases. Specifically, for example, assuming that the evaluation value X1 when the subject vehicle 1's vehicle speed is 60 km / h is taken as the reference (X1=0), and the evaluation value X1 when the subject vehicle 1 is traveling at 40 km / h is "-20," if the value of coefficient a is a negative value, the slower the vehicle speed of the subject vehicle 1, the larger the value of "a×X1." In this way, the coefficient a is set according to the driving scenario so that the value of "a×X1" increases as the vehicle speed of the subject vehicle 1 increases at a speed at which the subject vehicle 1 is more likely to be tailgated.

[0066] Similarly, coefficient b is set depending on the driving scene so that the value of "b x X2" increases as the vehicle speed of the rear vehicle increases, making the driver of the rear vehicle more likely to feel anxious, angry, or stressed toward the host vehicle 1. Furthermore, coefficient c is set depending on the driving scene so that the value of "c x X3" increases as the inter-vehicle distance increases, making the host vehicle 1 more likely to be tailgated or the driver of the rear vehicle more likely to feel anxious, angry, or stressed toward the host vehicle 1. Furthermore, coefficient d is set depending on the driving scene so that the value of "d x X4" increases as the driving state of the host vehicle 1 has a greater impact on the emotions of the driver of the rear vehicle. These coefficients a, b, c, and d are set, for example, using a learning model (tailgating determination model) described below.

[0067] The judgment criterion threshold X0 may be a value that is set arbitrarily, but when the vehicle speed (km / h) of the host vehicle 1, the vehicle speed (km / h) of the rear vehicle, the inter-vehicle distance (m) between the host vehicle 1 and the rear vehicle, and the emotion evaluation value (0 to 100) of the driver of the rear vehicle are used as the respective evaluation values ​​X1, X2, X3, and X4 as described above, the judgment criterion threshold X0 can be set to, for example, 100. In addition, the tailgating characteristic evaluation value X5 of the driver of the rear vehicle is an evaluation value that indicates the possibility that the driver of the rear vehicle will engage in tailgating, and is relatively evaluated, for example, between 0 and 100. The tailgating characteristic evaluation value X5 is set to a larger value if the driver of the rear vehicle is more likely to engage in tailgating, such as if the driver has a history of tailgating in the past, so that the host vehicle 1 is determined to be in a situation where it is being tailgated sooner.

[0068] For example, the acquisition unit 62 acquires information about the tailgating driving characteristics of the driver of the rear vehicle from the rear vehicle through vehicle-to-vehicle communication. The information about the driver's tailgating driving characteristics includes, for example, data about the individual driver's history of tailgating or dangerous driving. The information about the driver's tailgating driving characteristics may also include data about acceleration / deceleration operations, steering operations, the number of times the headlights are turned on, and the number of times the high beams are turned on per certain period of time.

[0069] The information on the driver's tailgating characteristics may also include information on the results of a questionnaire collected in advance from each driver and stored in the control device. The information on the results of the questionnaire may include, for example, information on how often the driver feels irritated while driving, the actions taken when irritated (such as honking the horn, flashing the lights, or yelling), and the cause of the irritation. The tailgating determination unit 63 relatively evaluates the tailgating characteristic evaluation value X5 between 0 and 100 based on the acquired tailgating characteristic information, for example, using a preset calculation formula.

[0070] The acquisition unit 62 may acquire identification information for identifying the driver of the other vehicle and extract information on the driver's tailgating characteristics from data recorded in the driver database 77. For example, the acquisition unit 62 may extract facial features of the driver of the other vehicle based on detection data transmitted from the surrounding environment sensor 31 and identify the driver of the other vehicle by referring to the driver database 77. The acquisition unit 62 may also recognize the number printed on the license plate of the other vehicle based on image data transmitted from the surrounding environment sensor 31 and identify the driver based on the number. Data associating the number with the driver may be recorded in the driver database 77, for example, or may be acquired from metadata accessible via mobile communications or the like.

[0071] The driving condition evaluation value X1 of the host vehicle 1 is not limited to the evaluation value of the vehicle speed. The driving condition evaluation value X1 of the host vehicle 1 may be calculated using any one or all of the following, in addition to the vehicle speed: a speed change or acceleration / deceleration change per predetermined fixed time period; the relative speed of the vehicle behind the host vehicle 1 with respect to the host vehicle 1; the speed limit of the road on which the vehicle is traveling; and the time difference between when the turn signal is turned on and when the vehicle changes course. In this case, the arithmetic expression is set so that the driving condition evaluation value X1 increases as the speed change or acceleration change per predetermined time period increases in the negative direction, i.e., the deceleration state of the host vehicle 1 increases. The arithmetic expression is also set so that the driving condition evaluation value X1 increases as the relative speed of the vehicle behind the host vehicle 1 increases, the speed limit increases, and the time difference between when the turn signal is turned on and when the vehicle changes course is shorter. The fixed time period may be set to any time period.

[0072] Furthermore, the traveling condition evaluation value X2 of the following vehicle is not limited to the evaluation value of the vehicle speed. The traveling condition evaluation value X2 of the following vehicle may be calculated using either or both of the speed change amount and the acceleration / deceleration change amount per certain time period in addition to the vehicle speed. In this case, the calculation formula is set so that the traveling condition evaluation value X2 increases as the speed change amount or the acceleration change amount per certain time period increases in the positive direction, i.e., as the acceleration state of the following vehicle increases.

[0073] Furthermore, the relative position evaluation value X3 between the host vehicle 1 and the rear vehicle is not limited to the evaluation value of the inter-vehicle distance between the host vehicle 1 and the rear vehicle. The relative position evaluation value X3 between the host vehicle 1 and the rear vehicle may be calculated using any one or all of the following, in addition to the inter-vehicle distance: the deviation between the lane in which the host vehicle 1 is traveling and the lane in which the rear vehicle is traveling; the change in the inter-vehicle distance between the host vehicle 1 and the rear vehicle per certain time; and the change in the inter-vehicle distance between the host vehicle 1 and the front vehicle per certain time. In this case, the arithmetic expression is set so that the smaller the deviation between the lane in which the host vehicle 1 is traveling and the lane in which the rear vehicle is traveling, the larger the relative position evaluation value X3. Furthermore, the arithmetic expression is set so that the larger the change in the inter-vehicle distance between the host vehicle 1 and the rear vehicle per certain time, the larger the change in the inter-vehicle distance between the host vehicle 1 and the front vehicle per certain time, in the negative direction, or the larger the change in the inter-vehicle distance between the host vehicle 1 and the front vehicle per certain time, the larger the relative position evaluation value X3.

[0074] The coefficients a, b, c, and d in the above-mentioned judgment formula (1) are set using a learning model (tailgating judgment model) generated by machine learning using, for example, the driving situation of the host vehicle 1 when tailgating or dangerous driving is performed on the host vehicle 1 by a vehicle behind, the driving behavior of the driver of the host vehicle 1, and the feelings of the driver of the vehicle behind due to the driving behavior as learning data. The tailgating judgment model may be pre-installed in the host vehicle 1 or may be recorded on a server or the like accessible via mobile communication means. This makes it possible to generate a judgment formula that weights information that is likely to cause anxiety, anger, or stress to the driver of the vehicle behind, depending on the driving situation.

[0075] The learning data for generating the above-mentioned tailgating judgment model can be collected, for example, by having a driver corresponding to the above-mentioned rear vehicle report situations in which he or she felt anxiety, anger, or stress toward the front vehicle corresponding to the above-mentioned host vehicle 1. The respective coefficients a, b, c, and d set using the tailgating judgment model are set so that the values ​​obtained by multiplying the respective evaluation values ​​X1, X2, X3, and X4 by the coefficients a, b, c, and d become larger depending on the driving scene, the more likely the host vehicle 1 is to be tailgated or the more likely the driver of the rear vehicle is to feel anxiety, anger, or stress toward the host vehicle 1. A large amount of learning data is required to generate the tailgating judgment model. An example of a method for collecting the learning data is described below.

[0076] For example, if an unspecified driver feels anxiety, anger, or stress about a vehicle ahead while driving a vehicle, a control device mounted on the host vehicle starts recording information on the driving behavior of the driver of the host vehicle (corresponding to the rear vehicle), information on the driving behavior of the driver of the front vehicle, information on the driving conditions of the host vehicle and the front vehicle, and information on the emotions of the driver of the host vehicle. This information may be, for example, data detected by the surrounding environment sensor 31, the in-vehicle camera 33, the vehicle state sensor 35 mounted on the host vehicle, and the biological sensor 34, or data calculated based on these detected data. Recording of various information may be started by an operation of the driver, or may be started automatically when the control device detects the driver's anxiety, anger, or stress in a situation where a vehicle ahead is present.

[0077] Thereafter, when the host vehicle stops, the control device displays predetermined questionnaire items as images and prompts the driver to answer them. FIG. 4 shows an example of an image display of the questionnaire results. As illustrated in FIG. 4, the driver inputs "emotions," "level of emotions," "driving conditions," and "what the driver wanted" for a scene in which the driver felt anxiety, anger, or stress toward the vehicle ahead. After the driver inputs his / her responses, the control device transmits the questionnaire result data to a server or the like via mobile communication means. The transmitted data may include all of the recorded detection data from the vehicle state sensor 35 and the biometric sensor 34 or all of the data calculated based on these detection data, and may also include data converted into information on the driving behavior of the driver of the host vehicle (corresponding to the rear vehicle) (what driving behavior was performed), information on the driving behavior of the driver of the front vehicle (what driving behavior was performed), information on the driving conditions of the host vehicle and the front vehicle (what the driving conditions were), and information on the emotions of the driver of the host vehicle (what emotions were they feeling).

[0078] The submitted survey result data is automatically or manually converted into learning data, and the learning data is subjected to machine learning to generate a tailgating detection model. In order to collect a large amount of learning data, a predetermined incentive may be given in response to the submission of the survey result data.

[0079] The method for constructing the tailgating judgment model is not particularly limited, and known methods such as support vector machines, nearest neighbor methods, deep learning neural networks, or Bayesian networks can be appropriately adopted.

[0080] In step S13, after generating the judgment formula (1) according to the driving situation of the host vehicle 1, the acquisition unit 62 acquires judgment information for determining whether or not the host vehicle 1 is being tailgated (step S15). The judgment information includes information on the driving state of the host vehicle 1, information on the surrounding environment of the host vehicle 1, information on the driving state of other vehicles, and information on the relative positions of the host vehicle 1 and other vehicles. The acquisition unit 62 records the acquired various data in the driving database 71 as time-series data.

[0081] Specifically, the acquisition unit 62 acquires information on the driving state of the host vehicle 1 at a predetermined calculation cycle based on the detection data transmitted from the vehicle state sensor 35. The information on the driving state of the host vehicle 1 includes information on the operation state of the vehicle 1, such as the steering angle of the steering wheel or steering wheels, accelerator operation amount, brake operation amount, and operation state of the turn signal, as well as information on the behavior of the vehicle, such as the vehicle speed, longitudinal acceleration, lateral acceleration, longitudinal jerk, and lateral jerk.

[0082] The acquisition unit 62 also acquires information about the environment surrounding the vehicle 1 at a predetermined calculation cycle based on the detection data transmitted from the surrounding environment sensor 31. The information about the environment surrounding the vehicle 1 includes information about the curve shape, inclination state, lane, road width, surrounding obstacles, and other vehicles of the road on which the vehicle 1 is traveling. The information about the environment surrounding the vehicle 1 may also include information about the speed limit of the road on which the vehicle 1 is traveling. The speed limit information may be detected based on image data transmitted from the surrounding environment sensor 31, may be acquired through road-to-vehicle communication or a beacon, or may be determined based on position information on map data transmitted from the GPS sensor 37.

[0083] The acquisition unit 62 also acquires information on the driving state of other vehicles and information on the relative position between the host vehicle 1 and other vehicles at a predetermined calculation period based on the detection data transmitted from the surrounding environment sensor 31. The information on the driving state of other vehicles includes at least information on the behavior of the other vehicles, such as the speed, longitudinal acceleration, and lateral acceleration of the other vehicles. The information on the relative position between the host vehicle 1 and other vehicles includes at least information on the relative speed of the other vehicles with respect to the host vehicle 1, the relative position of the other vehicles as seen from the host vehicle 1, and the distance between the host vehicle 1 and other vehicles.

[0084] Next, the tailgating determination unit 63 inputs the acquired determination information into the determination formula (1) and determines whether or not the driving evaluation value exceeds the determination threshold (step S17). If the driving evaluation value does not exceed the determination threshold (S17 / No), it is not determined that the host vehicle 1 is in a situation where it is being tailgated, and the determination processing routine is terminated. On the other hand, if the driving evaluation value exceeds the determination threshold (S17 / Yes), the tailgating determination unit 63 determines that the host vehicle 1 is in a situation where it is being tailgated by a vehicle behind (step S18).

[0085] Next, the tailgating judgment unit 63 sets a tailgating flag for various data acquired within a certain period of time before and after the time when it is judged that the vehicle is in a situation where it is being subjected to tailgating, records this in the driving database 71 (step S19), and terminates the judgment processing routine.

[0086] As described above, in the driving assistance device 50 according to this embodiment, the tailgating determination unit 63 acquires information on the driving state of the host vehicle 1, information on the driving state of the rear vehicle, information on the relative position between the host vehicle 1 and the rear vehicle, and information on the tailgating characteristics of the driver of the rear vehicle, and determines whether the host vehicle 1 is in a situation where it is being tailgated by the rear vehicle using the above-described determination formula (1). For example, if the driver of the rear vehicle has a history of tailgating in the past, the determination threshold becomes smaller. Therefore, the more likely the driver of the rear vehicle is to engage in tailgating, the lower the determination threshold becomes, and it becomes more likely that the host vehicle 1 is in a situation where it is being tailgated by the rear vehicle.

[0087] Furthermore, in this embodiment, a determination is made that further reflects the emotion evaluation value X4 of the driver of the following vehicle. Therefore, whether or not the host vehicle 1 is in a situation where it is being tailgated by the following vehicle is determined based on the tailgating driving characteristics of the driver of the following vehicle as well as the emotional state of the driver of the following vehicle. For example, if the driver of the following vehicle is feeling angry, the driving evaluation value becomes larger. Therefore, for example, the angrier the driver of the following vehicle is feeling, the larger the driving evaluation value becomes, and it becomes more likely that the host vehicle 1 is in a situation where it is being tailgated by the following vehicle.

[0088] Therefore, the method for determining whether or not the vehicle 1 is being tailgated by a vehicle behind can more appropriately determine whether or not the vehicle 1 is being tailgated by a vehicle behind.

[0089] [Driving assistance processing operation] Next, a series of processing operations performed by the driving assistance device 50 according to this embodiment will be described. FIG. 5 is a flowchart showing the main routine of the processing operations executed by the control unit 51.

[0090] First, when the in-vehicle system including the driving assistance device 50 is started (step S21), the driver determination unit 61 of the control unit 51 executes a process of identifying the driver of the host vehicle 1 (step S23). For example, the driver determination unit 61 executes a process of recognizing the face of the driver sitting in the driver's seat based on image data transmitted from the in-vehicle camera 33. The driver determination unit 61 also executes a process of extracting features of the recognized driver's face and determines whether information about the driver that matches the extracted features is recorded in the driver database 77. If information about the driver that matches the extracted features is not recorded in the driver database 77, the driver determination unit 61 assigns identification information to each recognized driver and records the data about the features in the driver database 77 and the identification information in the storage unit 53. On the other hand, if information about the driver that matches the extracted features is recorded in the driver database 77, the driver determination unit 61 records identification information that identifies the detected driver in the storage unit 53.

[0091] Next, the feedback presentation unit 65 of the control unit 51 determines whether or not driving of the host vehicle 1 has started (step S25). For example, the feedback presentation unit 65 determines that driving of the host vehicle 1 has started when, after the in-vehicle system is started, the position of the shift lever is switched to the drive (D) range or when the target drive torque of the host vehicle 1 is set to a positive value exceeding zero. However, the method of determining whether or not driving of the host vehicle 1 has started is not limited to the above example.

[0092] For ease of understanding, the case where the vehicle 1 starts to be driven will be explained first, and the case where the vehicle 1 does not start to be driven will be explained later.

[0093] If it is determined that driving of the vehicle 1 has started (S25 / Yes), the feedback presentation unit 65 determines whether or not driving of the vehicle 1 has ended (step S27). For example, the feedback presentation unit 65 determines that driving of the vehicle 1 has ended when the position of the shift lever is switched to the parking (P) range, when the switch of the in-vehicle system is switched off, or when the vehicle 1 has reached the set destination. However, the method of determining whether or not driving of the vehicle 1 has ended is not limited to the above example.

[0094] If it is not determined that the driving of the vehicle 1 has ended (S27 / No), the control unit 51 executes the driving process (step S29).

[0095] [Processing during operation] FIG. 6 shows a flowchart of the in-driving process. In the driving process, the tailgating determination unit 63 executes the tailgating determination process in accordance with the processing procedure of the flowchart shown in Fig. 3 (step S41). The tailgating determination unit 63 determines whether or not the vehicle 1 is in a situation where it may be subjected to tailgating from the vehicle behind, based on information on the driving state of the vehicle 1, information on the driving state of the vehicle behind, information on the relative position between the vehicle 1 and the vehicle behind, and information on the tailgating characteristics of the driver of the vehicle behind.

[0096] After executing the tailgating determination process in step S41, the feedback presentation unit 65 determines whether or not it has been determined that the vehicle 1 is in a situation where it is subject to tailgating (step S43), and if it has not been determined that the vehicle 1 is in a situation where it is subject to tailgating (S43 / No), the process returns to step S41 and the tailgating determination process is executed again.

[0097] On the other hand, if it is determined that the host vehicle 1 is in a situation where it is being tailgated (S43 / Yes), the feedback presentation unit 65 executes a process of notifying the driver of the host vehicle 1 that there is a possibility that the host vehicle 1 is being tailgated by a vehicle behind (step S45). Specifically, the feedback presentation unit 65 drives the HMI 43 to notify the driver that there is a possibility that the host vehicle 1 is being tailgated by a vehicle behind, by using sound, or by using a voice and an image display, or by using either one of these means. The notification at this time may simply notify the driver of the possibility of tailgating by a vehicle behind, but may also notify the driver of the position of the vehicle behind and the current driving situation.

[0098] Next, the tailgating determination unit 63 determines whether the driver of the host vehicle 1 has performed a driving behavior to avoid tailgating (step S47). For example, the tailgating determination unit 63 may determine that the driver of the host vehicle 1 has performed a driving behavior to avoid tailgating when the emotion evaluation value X4 calculated based on the emotion of the driver of the following vehicle acquired by the acquisition unit 62 falls below a predetermined threshold value set in advance. On the other hand, the tailgating determination unit 63 may determine that the driver of the host vehicle 1 has not performed a driving behavior to avoid tailgating when it is not determined that the driver of the host vehicle 1 has performed a driving behavior to avoid tailgating within a predetermined time period set in advance.

[0099] If it is determined that the driver of the vehicle 1 has performed driving behavior to avoid tailgating (S47 / Yes), the process proceeds to step S51. On the other hand, if it is not determined that the driver of the vehicle 1 has performed driving behavior to avoid tailgating (S47 / No), the feedback presentation unit 65 performs processing to have the driver of the vehicle 1 correct their driving behavior (step S49).

[0100] [Driving behavior correction processing] FIG. 7 shows a flowchart of the driving behavior modification process. The tailgating determination unit 63 executes tailgating determination processing in accordance with the processing procedure of the flowchart shown in Fig. 3 (step S61). The tailgating determination unit 63 determines whether or not the vehicle 1 is in a situation where it may be subjected to tailgating from the vehicle behind, based on information on the driving state of the vehicle 1, information on the driving state of the vehicle behind, information on the relative position between the vehicle 1 and the vehicle behind, and information on the tailgating driving characteristics of the driver of the vehicle behind.

[0101] Next, the feedback presentation unit 65 determines whether or not it has been determined that the host vehicle 1 is in a situation where it is being subjected to tailgating as a result of the tailgating determination process (step S63). If it is subsequently determined that the host vehicle 1 is in a situation where it is being subjected to tailgating (S63 / Yes), the feedback presentation unit 65 executes a notification instructing the driver of the host vehicle 1 to take a driving action (hereinafter also referred to as "avoidance action") to avoid the tailgating (step S65). Specifically, the feedback presentation unit 65 sets the evasive action based on information on the driving state of the host vehicle 1, information on the driving state of the following vehicle, and information on the surrounding environment of the host vehicle 1, and drives the HMI 43 to notify the driver of the host vehicle 1 of the evasive action.

[0102] For example, if the vehicle speed of the host vehicle 1 is significantly lower than the legal speed, the feedback presentation unit 65 notifies the driver to accelerate the host vehicle 1. Furthermore, if the host vehicle 1 is traveling on a road with two or more lanes in each direction and the adjacent lane is open, the feedback presentation unit 65 notifies the driver to change lanes with the host vehicle 1. Furthermore, if there is sufficient space on the shoulder of the road, the feedback presentation unit 65 notifies the driver to move the host vehicle 1 into the space. However, the content of the evasive action notified is not limited to these examples, and is set appropriately depending on the driving situation of the host vehicle 1. After the feedback presentation unit 65 has notified the driver to take evasive action, the process returns to step S61, and the road rage determination unit 63 repeatedly executes the road rage determination process.

[0103] If the result of the tailgating determination process does not determine that the host vehicle 1 is in a situation where it is being tailgated (S63 / No), the tailgating determination unit 63 determines that the situation where the host vehicle 1 is being tailgated has been resolved (step S67). Next, the tailgating determination unit 63 associates the data of the evasive action where the host vehicle 1 is no longer determined to be in a situation where it is being tailgated with information on the driving state of the host vehicle 1 when it was determined that it was in a situation where it was being tailgated, information on the driving state of the vehicle behind, and information on the relative position between the host vehicle 1 and the vehicle behind, and records the data of the evasive action where the host vehicle 1 is no longer determined to be in a situation where it is being tailgated as tailgating resolution data in the tailgating case database 73 (step S69), and terminates the driving behavior correction process.

[0104] When it is determined that the driver of the host vehicle 1 has performed driving behavior to avoid tailgating (S47 / Yes), or when the driving behavior correction process of step S39 is completed, the tailgating factor determination unit 64 of the control unit 51 executes a process to determine factors that induce tailgating in the host vehicle 1 (step S51). In this embodiment, the tailgating factor determination unit 64 executes a process (first example) to determine factors that induce tailgating by comparing data related to the driving state of the host vehicle 1 when it is determined that the host vehicle is in a situation where it is subject to tailgating with data of normal driving without tailgating, and a process (second example) to determine factors that induce tailgating by comparing data related to the driving behavior of the driver of the host vehicle 1 when it is determined that the host vehicle is in a situation where it is subject to tailgating with data of driving behavior when evasive behavior is appropriately taken. However, it may be configured to be able to execute only one of the first example or the second example.

[0105] [Processing to determine the cause of tailgating] FIG. 8 shows a flowchart of a first example of the tailgating factor determination process. First, the tailgating factor determination unit 64 refers to the driving database 71 and acquires determination information used when the tailgating determination unit 63 determines that the host vehicle 1 is in a situation where it is being tailgated (step S71). Next, the tailgating factor determination unit 64 refers to the normal driving database 75 and extracts data on normal driving in driving situations that belong to the same category as the driving situation when it is determined that the host vehicle 1 is in a situation where it is being tailgated (step S73). Driving situations that belong to the same category may be those that share a predetermined appropriate number of data items, such as the curve shape, inclination state, driving lane, road width, positions of surrounding obstacles, and the number and positions of vehicles behind the host vehicle 1. Furthermore, driving situations that belong to the same category may also be driving data of vehicles that have traveled the same section. If the data is from the same section, a more accurate comparison result with the data of the host vehicle 1 can be obtained.

[0106] Furthermore, the conditions for determining that driving situations belong to the same category may include that the driving area or the driving time is the same. The extracted data is data to be compared with the data of the determination information, and may be an appropriate number of data selected from information about the driving state of the vehicle 1, and may include, for example, the amount of change in acceleration / deceleration, the amount of change in speed, the amount of change in inter-vehicle distance per certain time, etc.

[0107] Next, the tailgating factor determination unit 64 compares the data in the determination information with the extracted data in the normal driving database and calculates the degree of deviation for each data (step S75). The degree of deviation is calculated, for example, as the ratio of the difference between the normal driving data and the target data in the determination information to the value of the target data (normal driving data) in the normal driving database. Next, the tailgating factor determination unit 64 stores the information resulting from the comparison between the data in the determination information and the extracted data in the normal driving database in the driving database 71 (step S79), and ends the tailgating factor determination process.

[0108] FIG. 9 shows a flowchart of a second example of the tailgating factor determination process. First, similar to the process of step S71, the tailgating factor determination unit 64 refers to the driving database 71 and acquires determination information when the tailgating determination unit 63 determines that the vehicle 1 is in a situation where it is being tailgated (step S81). The determination information includes information that can identify the driving behavior taken by the driver of the vehicle 1. The determination information may include information of the driver's line of sight detected and recorded by the in-vehicle camera 33.

[0109] Next, the tailgating factor determination unit 64 refers to the tailgating case database 73 and extracts data on evasive actions taken appropriately in tailgating cases in driving situations that belong to the same category as the driving situation when it was determined that the vehicle 1 was in a situation where it was being tailgated (step S83). The data on evasive actions taken appropriately is data on the driving actions of the driver taken when the situation where it was being tailgated was quickly resolved, and includes the data recorded in step S69 above.

[0110] Next, the tailgating driving factor determination unit 64 compares the data of the determination information with the extracted data of evasive behavior from the tailgating driving case database, and calculates the degree of deviation for each data (step S85). Next, the tailgating driving factor determination unit 64 stores the information of the comparison result between the driving behavior data of the determination information and the extracted data of evasive behavior from the tailgating driving case database in the driving database 71 (step S79), and ends the tailgating driving factor determination process.

[0111] FIG. 10 shows an example of the comparison result between the data of the determination information and the extracted data of the normal operation database. The example shown in FIG. 10 shows the results of comparing data from the judgment information with data from the normal driving database in a driving situation in which the speed of the subject vehicle 1 is significantly slower than the speed limit, causing the driver of the following vehicle to feel irritated. In this example, the deviation from the normal driving data for the amount of change in acceleration / deceleration per certain period of time is 20%, the deviation from the normal driving data for the amount of change in speed per certain period of time is 40%, and the change in the inter-vehicle distance between the subject vehicle 1 and the preceding vehicle per certain period of time is 70%. In this case, the ranking of influences on inducing tailgating is as follows: the amount of change in inter-vehicle distance between the subject vehicle 1 and the preceding vehicle per certain period of time has the highest influence, followed by the amount of change in speed per certain period of time, and then the amount of change in acceleration / deceleration per certain period of time. Note that the comparison data items shown in FIG. 10 are merely examples, and other data may be compared.

[0112] 5, while the host vehicle 1 is being driven, the control unit 51 repeatedly executes the above-described in-driving process unless it is determined in step S35 that the in-vehicle system has stopped, and unless it is determined in step S27 that the driving of the host vehicle 1 has ended. This allows the control unit 51 to determine, at an appropriate timing, whether the host vehicle 1 is in a situation where it is being tailgated by a vehicle behind, taking into account the tailgating characteristics of the driver of the vehicle behind while the host vehicle 1 is being driven. Furthermore, when it is determined that the host vehicle 1 is in a situation where it is being tailgated by a vehicle behind, the factors that induce the tailgating can be determined and recorded.

[0113] On the other hand, if it is determined in step S27 that driving of the vehicle 1 has ended (S27 / Yes), the feedback presenter 65 executes post-driving processing (step S31).

[0114] [Processing after operation] FIG. 11 shows a flowchart of the post-operation processing. First, the feedback presentation unit 65 refers to the driving database 71 (step S91). As described above, the driving database 71 stores driving data associated with each driver. The driver type of the driver of the vehicle 1 is calculated based on data related to the driving behavior of the driver of the vehicle 1 (step S93). The driver type is information on driving characteristics that classify driving behaviors that the driver of the vehicle 1 is not good at, and is classified into one or more categories, such as "not good at changing lanes," "not good at maintaining speed," or "not good at determining an appropriate inter-vehicle distance." Specifically, the feedback presentation unit 65 compares the data related to the driving behavior of the driver of the vehicle 1 with driving data recorded in the normal driving database 75 that is not determined to be driving that induces aggressive driving, and estimates driving behaviors that the driver of the vehicle 1 is not good at. The feedback presentation unit 65 records the calculated driver type information in the storage unit 53.

[0115] Next, the feedback presentation unit 65 determines whether or not the data recorded in the driving database 71 contains a record indicating that the driver was in a situation where he or she was subject to tailgating during the period from the start to the end of the current drive (step S95). If there is no record indicating that the driver was in a situation where he or she was subject to tailgating (S95 / No), the feedback presentation unit 65 presents feedback information indicating that the driver was not in a situation where he or she was subject to tailgating (step S99). For example, the feedback presentation unit 65 generates appropriate feedback screen data and drives the HMI 43 to display the feedback screen as an image. The presentation of the feedback information is not limited to the method of displaying the feedback screen, and may be a method of audio output, or a combination of the methods of image display and audio output.

[0116] On the other hand, if there is a record indicating that the vehicle is in a situation where it is subject to tailgating (S95 / Yes), the feedback presentation unit 65 performs a process of creating a driving improvement comment based on the data recorded in the driving database 71 (step S97). The "driving improvement comment" is a comment intended to make the driver of the vehicle 1 aware of the driving behavior that induces tailgating and encourage improvement. The feedback presentation unit 65 automatically generates the "driving improvement comment" using the factors determined by the tailgating factor determination unit 64 and the vehicle behavior data, driving behavior data, and surrounding environment data that record the tailgating situation at that time. For example, the feedback presentation unit 65 automatically generates the "driving improvement comment" by extracting appropriate comments from pre-prepared text data according to the driving situation that led to the tailgating situation. Specifically, the feedback presentation unit 65 generates advice such as, "In a situation such as XX, you are performing a certain driving behavior. If there is a following vehicle, this may have a significant impact. Please drive more carefully in the future."

[0117] The method of creating the driving improvement comment and the content of the driving improvement comment are not limited to the above example, and any conventionally known method or content can be applied.

[0118] Next, the feedback presenting unit 65 presents feedback information using the created driving improvement comment (step S99). Fig. 12 shows an example of the layout of a feedback screen for notifying advice to avoid being a victim of tailgating. In the example shown in Fig. 12, the feedback screen includes information on the "driver type" of the driver of the vehicle 1, information on the "classification of the driving situation" that was the situation in which the vehicle was subjected to tailgating, information on the factors that trigger tailgating ("causes of occurrence"), and information on "advice (points for improvement)."

[0119] The driver type is information on driving characteristics that classifies the driving behavior that the driver of the host vehicle 1 is not good at, calculated and recorded in step S93 above. The information on the classification of the driving situation that resulted in the subject of tailgating is a classification of the driving situation determined in step S73 above, and is classified based on the behavior of the host vehicle 1, the driving behavior of the driver of the host vehicle 1, and information on the surrounding environment of the host vehicle 1. The information on the factors that induce tailgating is information determined and recorded in step S51 above. The advice information is information on driving improvement comments created in step S97 above. By including this information in the presented feedback information, the driver of the host vehicle 1 can learn about his or her own poor driving behavior, the actual situation in which the subject of tailgating occurred, and the causes of that occurrence, and can easily understand what driving behavior to take in that situation.

[0120] In the example shown in Fig. 12, a "video" is played back that records a driving scene that is determined to be a situation where the driver is being tailgated. Figs. 13 to 15 show examples of video patterns that are played back. All of Figs. 13 to 15 are driving scenes that correspond to the example of the comparison results shown in Fig. 10, and are examples of playing back video patterns of driving scenes in which the speed of the subject vehicle 1 is significantly slower than the speed limit, causing the driver of the vehicle behind to feel irritated.

[0121] Fig. 13 is an example of playing a video pattern of a driving scene viewed from the driver's perspective, Fig. 14 is an example of playing a video pattern of a driving scene viewed from above, and Fig. 15 is an example of playing a video pattern of a driving scene displayed in 3D. In each case, when playing back the video pattern, an explanation is displayed indicating that the speed of the host vehicle 1 and the distance between the host vehicle and the preceding vehicle are increasing, resulting in an increase in relative speed. This allows the driver to easily understand how the host vehicle 1 was being tailgated, and they can understand the advice being presented.

[0122] The feedback presentation unit 65 may create each moving image pattern as an animation, or may create it from image data from the front imaging cameras 31LF, 31RF and the rear imaging camera 31R, or from cameras (not shown) provided on the left and right side mirrors, etc. The moving image pattern to be displayed may be determined to be any one of the moving image patterns, or may be selected, for example, depending on the driving scene and the factors that induce aggressive driving, so that the driving scene and the factors that induce aggressive driving can be easily understood.

[0123] 12, the feedback screen further includes "area characteristics" information relating to driving tendencies in the travel area in which the vehicle 1 has traveled, and "graph" information representing the area characteristics. The area characteristics information and graph information displayed on the feedback screen will be described in detail later.

[0124] In this way, the feedback presenting unit 65 executes post-driving processing when driving of the vehicle 1 has ended. Returning to FIG. 5, after completing the post-driving processing, the feedback presenting unit 65 determines whether the in-vehicle system has stopped (step S45). If the in-vehicle system has stopped (S45 / Yes), the control unit 51 ends the processing operation. On the other hand, if the in-vehicle system has not stopped (S45 / No), the process returns to step S35.

[0125] In step S35, if it is not determined that driving of the vehicle 1 has started (S35 / No), the feedback presenter 65 executes pre-driving process (step S43).

[0126] [Pre-operation processing] FIG. 16 shows a flowchart of the pre-operation processing. First, the feedback presenter 65 refers to the driving database 71 (step S101), and calculates the driver type of the driver of the vehicle 1 based on data related to the driving behavior of the driver of the vehicle 1, similar to step S93 above (S103).

[0127] Next, the feedback presentation unit 65 determines whether or not to execute a process for setting a driving route plan (step S105). For example, setting information of a destination is acquired from the navigation system 40, and if a destination is set, the feedback presentation unit 65 determines to execute a process for setting a driving route plan. Furthermore, a condition may be that the driver or the like has input that the process for setting a driving route plan is to be executed.

[0128] If it is determined that the process of setting a travel route plan is to be executed (S105 / Yes), the feedback presenter 65 acquires travel route setting information from the navigation system 40 (step S107). The travel route information includes information such as the departure point or current location, intermediate points, destination or departure time.

[0129] Next, the feedback presentation unit 65 sets occupants who can be set as drivers who will drive the vehicle 1 (step S109). For example, the feedback presentation unit 65 recognizes occupants who are aboard the vehicle 1 based on image data transmitted from the in-vehicle imaging camera 33, and sets occupants who can be set as drivers. For example, the feedback presentation unit 65 may set all occupants whose driving data has been recorded as drivers in the past as occupants who can be set as drivers, or may display the recognized occupants on the HMI 43 and set an occupant selected by the occupant or the like as an occupant who can be set as a driver. However, the method of setting occupants who can be set as drivers is not limited to the above example.

[0130] Next, the feedback presentation unit 65 refers to the tailgating case database 73 and extracts data on tailgating events related to the travel route (step S111). Specifically, the feedback presentation unit 65 extracts data on driving scenes of tailgating events that occur frequently from data on tailgating events that have occurred in the past on the travel route from the departure point to the destination via intermediate points, which is included in the travel route information acquired in step S107. At this time, data on tailgating events that overlap in travel time zone may be extracted, taking into account the current time and the scheduled time of arrival at the destination.

[0131] Next, the feedback presentation unit 65 generates a region characteristic comment based on the extracted data of the tailgating incident (step S113). The "region characteristic comment" is information generated to notify the driver of driving characteristics, such as traffic manners and driving customs, specific to the driving area including the driving route of the vehicle 1. Specifically, the driving characteristics of drivers differ depending on the region due to cultural background, racial background, etc. Examples of region characteristics include frequent sudden lane changes, slow average cruising speed, and wide inter-vehicle distances. For this reason, if each driver performs their usual driving behavior in an unfamiliar region, there is a risk that they will be tailgated by other vehicles. Therefore, the feedback presentation unit 65 generates a region characteristic comment based on the extracted data of the tailgating incident.

[0132] The area characteristic comment is created in accordance with the method for creating the "driving improvement comment" described above. For example, the area characteristic comment is automatically generated by mapping data on tailgating incidents, including information on factors that induce tailgating, to text data of output comments previously stored in the storage unit 53, regarding what driving situation, timing, and what driving behavior should (or should have) be performed. In addition, in this embodiment, the feedback presentation unit 65 generates a graph representing data related to the driving characteristics of the driving area in question, along with the area characteristic comment.

[0133] 17 and 18 show examples of graphs representing data related to driving characteristics of each driving area. FIG. 17 shows data on the frequency of dangerous driving in the driving area, and is a graph showing the number of dangerous driving incidents by the time of occurrence. FIG. 18 shows data on average cruising speeds in the driving area, and is a graph showing average cruising speeds by traffic time period. However, data related to driving characteristics of a driving area is not limited to the above examples.

[0134] Next, the feedback presentation unit 65 creates and outputs a drive plan for the destination (step S115). Specifically, the possibility that the vehicle 1 is subject to tailgating varies depending on the driving characteristics of the driver, depending on the road shape of the driving route and regional characteristics. Therefore, the feedback presentation unit 65 analyzes the driver type of each occupant who can be set as a driver, and creates a drive plan that minimizes the risk of being subject to tailgating, depending on the road shape of the driving route from the current location to the destination and regional characteristics. More specifically, the feedback presentation unit 65 creates a plan for switching drivers and a plan for rest stops for switching drivers, so as to minimize the risk of being subject to tailgating.

[0135] For example, the feedback presentation unit 65 outputs the created drive plan to the navigation system 40. As a result, rest points (stop-off points) are set on the driving route to the destination in the navigation system 40. However, the created drive plan does not have to be reflected in the settings of the navigation system 40, and may be displayed on the HMI 43, a smartphone, or the like.

[0136] Next, the feedback presenting unit 65 performs a process of creating a driving improvement comment (step S127). The "driving improvement comment" created here is a comment that is presented as feedback information together with the area characteristic comment, and may be a comment that advises one or more drivers set as drivers in the drive plan on what timing and driving behavior they should take in response to driving problems. The process of creating the driving improvement comment may be the same as the process of creating the driving improvement comment in step S97 above, except that the comment is presented together with the area characteristic comment.

[0137] Next, the feedback presenting unit 65 presents feedback information using the created area characteristic comment and driving improvement comment (step S129). Specifically, the feedback presenting unit 65 may present the feedback information using a feedback screen exemplified in FIG. 12. In this case, the advice (points for improvement) information includes the driving improvement comment created in step S127. Furthermore, the area characteristic information includes the area characteristic comment created in step S113. The area characteristic information may include map information indicating the corresponding area together with the area characteristic comment.

[0138] Furthermore, the graph information may include graphs such as those shown in Figures 17 and 18. Displaying the data on the frequency of tailgating as shown in Figure 17 can raise awareness of the need to drive more carefully when driving a vehicle during times when tailgating is more frequent. In addition, the driver can be encouraged to set a driving plan that allows them to pass through areas where tailgating is less frequent. Displaying the data on the average cruising speed as shown in Figure 18 allows the driver to know the approximate vehicle speed in the driving area and drive in line with the flow of traffic. In addition, drivers who are not good at driving in high-speed situations can be encouraged to set a driving plan that avoids times when the average cruising speed is high. In addition, displaying graphs showing various data can make it less likely for drivers to engage in driving that induces tailgating.

[0139] On the other hand, in the above step S105, if it is not determined that the process of setting a travel route plan is to be executed (S105 / No), the feedback presentation unit 65 determines whether or not to present feedback information to the driver of the vehicle 1 before starting driving (step S121). For example, if the driver performs an operation input requesting the presentation of feedback information, the feedback presentation unit 65 determines that the feedback information will be presented. If it is set in advance to present feedback information when a travel route plan is not set, the determination process of step S121 may be omitted.

[0140] If it is determined that the feedback information is not to be presented (S121 / No), the feedback presenting unit 65 terminates the pre-driving process. On the other hand, if it is determined that the feedback information is to be presented (S121 / Yes), the feedback presenting unit 65 selects a learning scene to be used for presenting the feedback information (step S123). The feedback presenting unit 65 may select a learning scene to present advice to the driver about driving difficulties, depending on the driver type item, such as "poor at changing lanes," "poor at maintaining speed," or "poor at determining an appropriate following distance." Alternatively, the feedback presenting unit 65 may display the learning scene items and select multiple scenes selected by the driver, or may select a learning scene randomly.

[0141] Next, the feedback presentation unit 65 refers to the tailgating case database 73 and extracts data on tailgating events that correspond to the selected learning scene (step S125). Specifically, the feedback presentation unit 65 may extract data on tailgating events that overlap in driving time zones or driving areas, taking into account the current time and current location.

[0142] Next, the feedback presenter 65 performs a process of creating a driving improvement comment (step S127). The "driving improvement comment" created here may be a comment that advises a driver who wants to improve their driving behavior on what driving behavior and when to take in response to poor driving. The process of creating the driving improvement comment may be the same as the process of creating the driving improvement comment in step S97 described above.

[0143] Next, the feedback presenting unit 65 presents feedback information using the created driving improvement comment (step S129). Specifically, the feedback presenting unit 65 may present the feedback information using a feedback screen exemplified in FIG. 12. In this case, the advice (points for improvement) information includes the driving improvement comment created in step S127. Furthermore, the information on regional characteristics and the information on the graph may display information on an arbitrarily selected driving area, such as the current location of the vehicle 1 or an area where the driver frequently drives.

[0144] In this way, the feedback presenting unit 65 executes the pre-driving process when driving of the vehicle 1 has not started. Returning to FIG. 5, after completing the pre-driving process, the feedback presenting unit 65 determines whether the in-vehicle system has stopped (step S45). If the in-vehicle system has stopped (S45 / Yes), the control unit 51 ends the processing operation. On the other hand, if the in-vehicle system has not stopped (S45 / No), the process returns to step S35 and executes the processing of each step described above.

[0145] In this way, the driving support device 50 according to this embodiment compares the driving state information of the vehicle 1 when it is determined that the vehicle 1 is in a situation where it is being subjected to aggressive driving with accumulated data on the driving states of multiple vehicles in driving situations that belong to the same category as the driving situation at that time, and determines the factors that induce aggressive driving. Furthermore, the driving support device 50 provides feedback information regarding the driving behavior of the driver of the vehicle 1 based on the determined factors.

[0146] By comparing data on the driving state of the vehicle 1 when it is determined that the vehicle is in a situation where it is being tailgated with data on normal driving without being tailgated, and executing a process to determine the factors that induce tailgating, it is possible to present driving methods to avoid being tailgated by vehicles behind, based on data on the difference between the driving behavior of the driver of the vehicle 1 and the driving behavior of other drivers.

[0147] For example, if a driver with a tendency to "drive at a speed they consider appropriate even if the distance between them and the vehicle in front is large" is driving in an area with regional characteristics of "heavy traffic volume and a tendency for following distances to be relatively short," the comment "This is an area where there is a high tendency for drivers to drive at a speed that they consider appropriate, even if the distance between them and the vehicle in front is large" will be written in the "regional characteristics" section, and the advice section will read "Try to drive faster than usual, or try to stay in the left lane whenever possible."

[0148] Alternatively, if a driver with a tendency to "drive at a speed close to that of other vehicles, including vehicles in adjacent lanes," drives in an area with a regional characteristic of "roads with two or more lanes on each side, where there is a tendency for speed differences between vehicles in adjacent lanes to be large," the comment "This is an area where speed differences between vehicles in adjacent lanes tend to be large" will be written in the "Regional Characteristics" section, and the comment "Please accelerate sufficiently when overtaking" will be written in the advice section.

[0149] Therefore, even if a driver is driving in an area different from the area in which he or she normally drives, feedback information is presented based on factors that induce tailgating specific to that driving area, allowing the driver to drive in a way that prevents the driver from being tailgated by other vehicles.

[0150] In addition, by performing a process to determine the factors that induce tailgating by comparing data regarding the driving behavior of the driver of the vehicle 1 when it is determined that the vehicle is in a situation where it is subject to tailgating with data regarding the driving behavior when appropriate evasive action is taken, it is possible to present driving methods to avoid tailgating or to prevent tailgating in the first place, based on the data on the difference between the driving behavior of the driver of the vehicle 1 and appropriate evasive action taken.

[0151] For example, in an area with regional characteristics of "many single-lane roads and few overtaking points," if the appropriate evasive action is to "turn on your hazard lights, pull over to the shoulder, and slow down," the "regional characteristics" section will include the comment "This is an area with few overtaking lanes," and the advice section will include the comment "A vehicle behind is approaching. Turn on your hazard lights on the straight ahead, pull over to the shoulder, slow down, and encourage the vehicle behind to overtake."

[0152] Alternatively, in an area with regional characteristics where "there are many lanes and vehicles may change lanes from adjacent lanes on either side," if the appropriate evasive action is to "keep more than twice the normal distance between you and the vehicle ahead," the "regional characteristics" section will include the comment "This is an area where lane changes occur frequently," and the advice section will include the comment "Keep a large distance between you and the vehicle ahead, so that other vehicles can easily change into your lane."

[0153] Therefore, even if the driver is driving in an area different from the area in which he or she normally drives, feedback information regarding avoidance actions specific to that driving area is presented, and if the driver finds himself or herself in a situation where he or she is being tailgated by a vehicle, the driver can drive in a way that allows the driver to quickly avoid that driving situation.

[0154] As described above, the driving assistance device 50 according to this embodiment compares information about the driving state of the host vehicle 1 when the host vehicle 1 is subjected to tailgating by another vehicle with accumulated data about the driving states of other vehicles in driving situations belonging to the same category, determines factors that induce tailgating, and presents feedback information about the driving behavior of the driver of the host vehicle 1. This makes it possible to present appropriate advice tailored to the driving characteristics of the driver of the host vehicle 1, and effectively enables the driver to acquire driving skills that will enable them to avoid tailgating.

[0155] Furthermore, the driving assistance device 50 according to this embodiment can provide advice on driving behavior to avoid situations where the driver is subject to aggressive driving, and advice on driving behavior to prevent situations where the driver is subject to aggressive driving. This allows the driver to provide appropriate advice that does not induce aggressive driving, in accordance with the driving characteristics of the driver of the vehicle 1.

[0156] Furthermore, the driving assistance device 50 according to this embodiment presents feedback information together with image data from the time before and after the time when it is determined that the vehicle 1 is subject to aggressive driving. In this case, the driving assistance device 50 switches the video pattern depending on the factors that induce aggressive driving and the driving situation, thereby enabling the driver to more effectively understand the factors that induce aggressive driving.

[0157] Furthermore, the driving assistance device 50 according to this embodiment provides feedback information after the driver has finished driving if the driver has experienced a situation where the driver has been subjected to aggressive driving during the current driving. Therefore, advice is provided to the driver promptly after the situation where the driver has experienced aggressive driving, and the driver can be prevented from repeating driving that induces aggressive driving.

[0158] Furthermore, the driving assistance device 50 according to this embodiment is configured to be able to create a drive plan so that the vehicle 1 will not be subjected to tailgating on the way to the destination when a destination is set in the navigation system 40. This allows the driver to be switched or a driving route plan to be created so that each occupant does not engage in driving that they are not good at, thereby minimizing the risk of the vehicle 1 being tailgated.

[0159] The processes of steps S121 to S129 described above may be executed by receiving an instruction signal from another external device that can communicate with the driving assistance device 50 via wireless communication means such as mobile communication means. This allows the device to be used as a learning device for improving driving skills without being in the vehicle.

[0160] Although the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the present disclosure is not limited to such examples. It is clear that a person skilled in the art to which the present disclosure pertains can conceive of various modifications or alterations within the scope of the technical ideas set forth in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure.

[0161] For example, in the above embodiment, all of the functions of the driving assistance device are installed in the vehicle, but the present disclosure is not limited to such an example. For example, some of the functions of the driving assistance device may be provided in a server device that can communicate via mobile communication means, and the driving assistance device may be configured to transmit and receive data to the server device. Furthermore, the driving assistance device may be a server device that can communicate with an on-board vehicle control device, HMI, or head-mounted display.

[0162] In addition, in the above embodiment, feedback information was presented during driving, before driving started, and after driving ended using the result of determining whether the host vehicle 1 is in a situation where it is being tailgated by another vehicle, reflecting the tailgating characteristics of the driver of the other vehicle, but the technology of the present disclosure is not limited to this example. For example, based on the tailgating determination result, it may be used as a determination means for switching to automatic driving when the driving of the host vehicle 1 is causing stress to the driver of the other vehicle, or it may learn driving conditions under which the driving of the host vehicle 1 does not cause stress to the driver of the other vehicle and use the learned driving conditions as setting standards for the vehicle speed during automatic driving control.

[0163] The following aspects also fall within the technical scope of the present disclosure. In the driving assistance device according to the above embodiment, the processor records information on factors that induce aggressive driving, and at the end of driving the vehicle, if information on factors that induce aggressive driving has been recorded during the current driving period, the driving assistance device presents feedback information regarding driving behavior. In the driving assistance device according to the above embodiment, a processor records information on factors that induce tailgating and sets a driving route to a set destination so as to reduce the risk of being subjected to tailgating. In the driving assistance device according to the above embodiment, the processor records information on factors that induce tailgating along with information on the driving state of the vehicle, and when a request for learning data is received from another device, transmits the recorded information on factors that induce tailgating and information on the driving state of the vehicle to the device. In the driving assistance device according to the above embodiment, a processor records information on factors that induce tailgating in association with information on the driving area, and presents feedback information regarding driving behavior based on factors that induce tailgating specific to the driving area. In the driving assistance device according to the above embodiment, the processor records information about the fact that the vehicle has been subjected to tailgating, and when the driving of the vehicle ends, if information about the fact that the vehicle has been subjected to tailgating during the current driving period has been recorded, the driving assistance device presents feedback information about evasive actions to be taken after the vehicle has been subjected to tailgating. In the driving assistance device according to the above embodiment, the processor records information about the driving conditions of the vehicle before and after it is determined that the vehicle has been subjected to tailgating, and when a request for learning data is received from another device, transmits the recorded information about the driving conditions of the vehicle and feedback information regarding evasive actions taken after being subjected to tailgating to the device. In the driving assistance device according to the above embodiment, the processor records information on the driving conditions of the vehicle before and after the time when it is determined that the vehicle has been subjected to tailgating, in association with information on the driving area, and presents feedback information regarding evasive actions specific to the driving area. A driving assistance device that assists in driving a vehicle, comprising: an acquisition unit that acquires information on the driving conditions of the subject vehicle and information on the surrounding environment of the subject vehicle; a tailgating factor determination unit that determines factors that induce tailgating by comparing accumulated data on the driving conditions of multiple vehicles in driving conditions that belong to the same category as the driving conditions of the subject vehicle with information on the driving conditions of the subject vehicle; and a feedback presentation unit that presents feedback information regarding the driving behavior of the driver of the subject vehicle based on the factors that induce tailgating. A recording medium having recorded thereon a computer program applied to a driving assistance device that assists in the driving of a vehicle, the recording medium having recorded thereon a computer program that causes one or more processors to execute processes including acquiring information on the driving conditions of the vehicle itself and information on the surrounding environment of the vehicle itself, comparing accumulated data on the driving conditions of multiple vehicles in driving conditions that belong to the same category as the driving conditions of the vehicle itself with the information on the driving conditions of the vehicle itself to determine factors that induce aggressive driving, and presenting feedback information regarding the driving behavior of the driver of the vehicle itself based on the factors that induce aggressive driving. [Explanation of symbols]

[0164] 1: Vehicle (own vehicle), 31: Surrounding environment sensor, 33: In-vehicle camera, 34: Biometric sensor, 35: Vehicle condition sensor, 37: GPS sensor, 39: Vehicle-to-vehicle communication unit, 40: Navigation system, 50: Driving assistance device, 51: Control unit, 53: Memory unit, 61: Driver determination unit, 62: Acquisition unit, 63: Tailgating determination unit, 64: Tailgating factor determination unit, 65: Feedback presentation unit, 71: Driving database, 73: Driving case database, 75: Normal driving database, 77: Driver database

Claims

1. A driving assistance device that assists driving of a vehicle, one or more processors; and one or more memories communicatively coupled to the one or more processors; the one or more processors: acquiring information about a running state of the host vehicle and information about a surrounding environment of the host vehicle while the host vehicle is being driven; Determine whether or not the host vehicle is in a situation where it is being tailgated by a vehicle traveling behind the host vehicle, and determine whether or not the driver of the host vehicle has performed a driving behavior to avoid the tailgating after it has been determined that the host vehicle is in a situation where it is being tailgated, The factors that induce tailgating are determined by comparing the accumulated data of information on the driving conditions of a plurality of vehicles in the same driving conditions as the driving conditions of the subject vehicle before and after the time when the situation is determined to be one in which the subject vehicle is subjected to tailgating with the information on the driving conditions of the subject vehicle; If the driver of the vehicle does not take driving actions to avoid the tailgating, feedback information regarding the avoidance driving actions after being subjected to the tailgating is presented based on information on the driving state of the vehicle, information on the driving state of the rear vehicle, and information on the surrounding environment of the vehicle after it is determined that the vehicle is subjected to the tailgating. A driving assistance device that performs processing including the steps of:

2. The one or more processors:

2. The driving assistance device according to claim 1, wherein after driving of the vehicle has ended and it has been determined that the vehicle is being tailgated, feedback information regarding the driving behavior of the driver of the vehicle is presented based on information about the driving state of the vehicle, information about the driving state of the vehicle behind, and information about the surrounding environment of the vehicle.

3. the one or more processors: The driving assistance device of claim 1, which determines factors that induce aggressive driving by comparing accumulated data on the driving conditions of the multiple vehicles that occurred in the same section as the section in which the vehicle was traveling with information on the driving conditions of the vehicle.

4. the one or more processors: The driving assistance device of claim 1 determines factors that induce tailgating by comparing accumulated data on the driving conditions of the multiple vehicles that are not subject to tailgating in driving conditions that belong to the same category as the driving conditions of the vehicle with information on the driving conditions of the vehicle.

5. The information about the surrounding environment includes information about the area in which the vehicle is traveling, the one or more processors: The information on the driving state of the subject vehicle is compared with accumulated data on the driving state of a plurality of vehicles in driving situations that belong to the same category as the driving situation of the subject vehicle, which is recognized based on the information on the surrounding environment, to determine factors that induce the tailgating; Recording information on factors that induce aggressive driving in association with information on the area in which the vehicle is traveling; The driving assistance device according to claim 1 , wherein feedback information regarding the driving behavior of the driver of the vehicle is presented based on factors that induce aggressive driving specific to the region in which the vehicle is traveling.

6. The accumulated data includes at least an amount of change in acceleration / deceleration, an amount of change in speed, and an amount of change in inter-vehicle distance per certain period of time, the one or more processors: A deviation degree is calculated by comparing the acceleration / deceleration change amount, the speed change amount, and the inter-vehicle distance change amount of a vehicle that is not subjected to the tailgating in a driving situation that belongs to the same category as the driving situation of the subject vehicle in the accumulated data with the acceleration / deceleration change amount, the speed change amount, and the inter-vehicle distance change amount of the subject vehicle; The driving assistance device according to claim 1 , wherein the factors that induce tailgating are determined in descending order of the degree of deviation.

7. A computer program applied to a driving assistance device that assists driving of a vehicle, one or more processors, acquiring information on a running state of the host vehicle and information on a surrounding environment of the host vehicle while the host vehicle is being driven; Determining whether or not the subject vehicle is in a situation where it is being tailgated by a vehicle traveling behind the subject vehicle, and determining whether or not the driver of the subject vehicle has performed a driving action to avoid the tailgating after determining that the subject vehicle is in a situation where it is being tailgated; Comparing the accumulated data of information on the driving conditions of a plurality of vehicles in the same driving conditions as the driving conditions of the subject vehicle before and after the time when the driving conditions are determined to be subject to the tailgating with the information on the driving conditions of the subject vehicle, and determining factors that induce tailgating; If the driver of the vehicle does not take driving actions to avoid the tailgating, after it is determined that the vehicle is in a situation where it is subjected to the tailgating, present feedback information regarding the avoidance driving actions after being subjected to the tailgating based on information on the driving state of the vehicle, information on the driving state of the vehicle behind, and information on the surrounding environment of the vehicle. A computer program that causes a process including the steps of:

Images