Driving assistance device, driving assistance method, and recording medium

Abstract

A driving assistance device for assisting in driving a vehicle, the driving assistance device comprising one or more processors, and one or more memories communicably connected to the one or more processors. In the driving assistance device, the one or more processors execute: an inclination angle calculation process for calculating the angle of inclination of a bicycle with respect to the vertical direction, the bicycle being recognized by an ambient environment recognition device for recognizing the peripheral environment of the vehicle; a prediction process for predicting that the bicycle will perform a course change in instances where the angle of inclination calculated through the inclination angle calculation process exceeds a prescribed angle threshold value; a determination process for determining whether there is a factor causing inclination of the bicycle different from the course change; and an angle threshold value setting process for setting the angle threshold value on the basis of the factor in instances where it is determined in the determination process that there is a factor causing inclination of the bicycle.

Description

Driving assistance device, driving assistance method, and recording medium

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

[0002] Various driving assistance devices that assist vehicle drivers have been available for some time. In recent years, a technology has become known in which the vehicle being assisted predicts the direction of a bicycle's movement based on the pedal position of the bicycle and the driver's body tilt while the bicycle is in motion, and then issues warnings and performs braking control processing to avoid collisions.

[0003] For example, Patent Document 1 discloses a technology that uses the bicycle's characteristic of determining whether a bicycle is changing course when it leans. Specifically, this technology uses the bicycle's lean angle and a preset angle threshold for determining whether a bicycle is changing course. This technology determines that the bicycle is changing course if the bicycle's lean angle is greater than the angle threshold.

[0004] JP 2015-14948 A

[0005] The technology described in Patent Document 1 assumes that the cyclist intentionally leans the bicycle and his or her body, but does not take into account the possibility that the bicycle may unintentionally sway due to various factors, such as the environment and circumstances surrounding the bicycle. As a result, for example, if the bicycle sways while traveling straight and the lean angle exceeds an angle threshold, the assisted vehicle that recognizes the bicycle may mistakenly believe that the bicycle is changing course. As a result, the assisted vehicle may frequently perform avoidance control, such as steering or decelerating, which may cause discomfort to the occupants of the vehicle.

[0006] The present disclosure has been made in consideration of the above circumstances, and an object of the present disclosure is to provide a driving assistance device, a driving assistance method, and a recording medium that can accurately predict whether a bicycle ridden by a rider will change course.

[0007] In order to solve the above problem, according to one aspect of the present disclosure, a driving assistance device that assists in driving a vehicle includes one or more processors and one or more memories communicatively connected to the one or more processors, wherein the one or more processors perform a tilt angle calculation process that calculates the tilt angle of the bicycle with respect to the vertical direction recognized by a surrounding environment recognition device that recognizes the environment surrounding the vehicle; a prediction process that predicts that the bicycle will change course if the tilt angle calculated by the tilt angle calculation process exceeds a predetermined angle threshold; a determination process that determines whether there is a factor other than a change in course that would cause the bicycle to tilt; and an angle threshold setting process that sets the angle threshold based on the factor if it is determined in the determination process that there is a factor that would cause the bicycle to tilt.

[0008] Furthermore, in order to solve the above problem, according to another aspect of the present disclosure, a driving assistance method is provided that includes the steps of: one or more processors calculating the tilt angle of the bicycle relative to the vertical direction recognized by a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; predicting that the bicycle will change course if the tilt angle exceeds a predetermined angle threshold; determining whether there is a factor other than a change in course that would cause the bicycle to tilt; and, if it is determined that there is a factor that would cause the bicycle to tilt, setting the angle threshold based on that factor.

[0009] Furthermore, in order to solve the above problem, according to another aspect of the present disclosure, there is provided a non-transitory tangible recording medium having recorded thereon a computer program that causes a processor to execute processes including calculating the tilt angle of a bicycle with respect to the vertical direction recognized by a surrounding environment recognition device that recognizes the surrounding environment of a vehicle, predicting that the bicycle will change course if the tilt angle exceeds a predetermined angle threshold, determining whether there is a factor other than a change in course that may cause the bicycle to tilt, and if it is determined that there is a factor that may cause the bicycle to tilt, setting the angle threshold based on that factor.

[0010] As described above, according to the present disclosure, it is possible to accurately predict whether a bicycle ridden by a rider will change course.

[0011] FIG. 1 is a schematic diagram showing an example configuration of a vehicle according to an embodiment of the present disclosure; FIG. 2 is an explanatory diagram for explaining the roll axis, pitch axis, and yaw axis of the vehicle; FIG. 3 is a block diagram showing an example configuration of a driving assistance device for the vehicle; FIG. 4 is an explanatory diagram for explaining the pitch angle of the vehicle; FIG. 5 is an explanatory diagram for explaining the pitch angle of the vehicle; FIG. 6 is a flowchart showing an example of a driving assistance method according to the present disclosure; FIG. 7 is a schematic diagram showing a bicycle ridden by a driver; FIG. 8 is a schematic diagram showing a bicycle ridden by a driver; FIG. 9 is a schematic diagram showing a bicycle ridden by a driver; FIG. 10 is a schematic diagram showing a bicycle ridden by a driver; FIG. 11 is a schematic diagram showing a bicycle ridden by a driver; FIG. 12 is a schematic diagram showing a bicycle ridden by a driver; 1 is a diagram showing a bicycle ridden by a rider. 2 is a diagram showing a bicycle ridden by a rider. 3 is a diagram showing a bicycle ridden by a rider. 4 is a diagram showing a bicycle ridden by a rider. 5 is a diagram showing a bicycle ridden by a rider.

[0012] 1. Embodiments Preferred embodiments of the present disclosure will be described below with reference to the accompanying drawings. Note that the dimensions and scale of each part in the drawings may differ from the actual dimensions. The drawings may also be shown schematically to facilitate understanding. Furthermore, the scope of the present disclosure is not limited to the following exemplary embodiments unless otherwise specified to limit the present disclosure.

[0013] [First embodiment] <Vehicle configuration> Fig. 1 is a schematic diagram showing an example configuration of a vehicle 10 according to a first embodiment. The vehicle 10 is equipped with a driving assistance device 11. The vehicle 10 is configured as a two-wheel-drive four-wheel vehicle in which a driving force source 17 generates driving torque and outputs the driving torque to a left front wheel and a right front wheel. The driving force source 17 may be an internal combustion engine such as a gasoline engine or a diesel engine, or may be a driving motor. Furthermore, the vehicle 10 may be equipped with both an internal combustion engine and a driving motor as the driving force source 17.

[0014] The vehicle 10 may be a four-wheel drive vehicle that transmits drive torque to the front and rear wheels. The vehicle 10 may also 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 the respective wheels. If the vehicle 10 is an electric vehicle or a hybrid electric vehicle, the vehicle 10 is equipped with a secondary battery that stores power 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 10 is equipped with a driving force source 17, an electric steering device 15, and brake devices 13A to 13D (hereinafter collectively referred to as "brake devices 13" unless a distinction is required) as devices used to control the operation of the vehicle 10. The driving force source 17 outputs driving torque that is transmitted to a front-wheel drive shaft F via a transmission and a differential mechanism 14 (not shown). The operation of the driving force source 17 and the transmission is controlled by a vehicle control unit 21 that includes one or more electronic control units (ECUs: Electronic Control Units).

[0016] An electric steering device 15 is provided on the front wheel drive shaft F. The electric steering device 15 includes an electric motor and a gear mechanism (not shown), and is controlled by a vehicle control unit 21 to adjust the steering angle of the front wheels. During manual driving, the vehicle control unit 21 controls the electric steering device 15 based on the steering angle of the steering wheel 16 by the driver. During automatic driving, the vehicle control unit 21 controls the electric steering device 15 based on the set steering angle or steering angular velocity.

[0017] Brake devices 13A to 13D apply braking force to the respective wheels. Brake devices 13 are configured as hydraulic brake devices, for example, and vehicle control unit 21 adjusts the hydraulic pressure supplied to each brake device 13 by controlling the drive of hydraulic unit 24. If vehicle 10 is an electric vehicle or a hybrid electric vehicle, brake devices 13 are used in combination with regenerative braking using a drive motor.

[0018] The vehicle control unit 21 includes one or more electronic control devices that control the driving of the driving force source 17, the electric steering device 15, and the hydraulic unit 24. If the vehicle 10 is equipped with a transmission that changes the speed of the output from the driving force source 17 and transmits it to the wheels, the vehicle control unit 21 has a function of controlling the driving of the transmission.

[0019] The vehicle control unit 21 is configured to be able to acquire information transmitted from the driving assistance device 11 and to be able to execute automatic driving control of the vehicle 10. The vehicle control unit 21 according to this embodiment is configured to be able to control the acceleration / deceleration and steering angle of the vehicle 10 based on the control of a collision avoidance processing unit 111F described below.

[0020] The vehicle 10 also includes front imaging cameras 12A and 12B, a rear imaging camera 12C, a vehicle position detection sensor 33, a vehicle speed sensor 34, and a display device 18.

[0021] The front imaging cameras 12A, 12B and the rear imaging camera 12C are included in the surrounding environment recognition device 12 for acquiring information about the surrounding environment of the vehicle 10. The front imaging cameras 12A, 12B capture images of the area in front of the vehicle 10 and generate image data. The rear imaging camera 12C captures images of the area behind the vehicle 10 and generates image data. The front imaging cameras 12A, 12B and the rear imaging camera 12C are equipped with imaging elements such as CCDs (Charged Coupled Devices) or CMOS (Complementary Metal Oxide Semiconductors), and transmit the generated image data to the driving assistance device 11 at predetermined calculation intervals. In the vehicle 10 shown in FIG. 1, the front imaging cameras 12A, 12B are configured as stereo cameras including a pair of left and right cameras, but the front imaging cameras may also be monocular cameras.

[0022] The surrounding environment recognition device 12 also includes a side detection sensor and a direction detection sensor that detect the sides of the vehicle 10. In addition, the surrounding environment recognition device 12 may include one or more sensors selected from the group consisting of a light detection and ranging (LiDAR) sensor, a radar sensor such as a millimeter wave radar, and an ultrasonic sensor.

[0023] The side detection sensors include side cameras 12D. The side cameras 12D are provided, for example, on the side mirrors 40, and capture images of the left rear, right rear, and sides of the vehicle 10. The side detection sensors transmit information on the detection results to the driving assistance device 11.

[0024] The direction detection sensor includes, for example, an inertial sensor. Ｖ The direction detection sensor detects angular velocities around three axes of the roll axis X, pitch axis Y, and yaw axis Z of the vehicle 10, and accelerations of translational motion along these three axes. The direction detection sensor transmits information of the detection results to the driving assistance device 11. The information of the detection results is transmitted to the driving assistance device 11. Ｖ The information includes the angular velocity information and the acceleration information.

[0025] FIG. 2 is an explanatory diagram illustrating the roll axis X, pitch axis Y, and yaw axis Z of the vehicle 10, and is a top view of the vehicle 10. The yaw axis Z is an axis extending in the vehicle height direction of the vehicle 10. The pitch axis Y is an axis extending in the vehicle width direction of the vehicle 10. The roll axis X is an axis extending in the vehicle length direction of the vehicle 10. The roll axis X, pitch axis Y, and yaw axis Z are three axes that pass through a center point O of the vehicle 10 and are perpendicular to each other at the center point O. The center point O is located at the center of the width, length, and height of the vehicle 10. As shown in FIG. 2 , the roll axis X according to this embodiment is composed of an axis X1 (dotted line in FIG. 2 ) extending forward from the center point O in the traveling direction of the vehicle 10, and an axis X2 (two-dot chain line in FIG. 2 ) extending backward from the center point O in the traveling direction of the vehicle 10.

[0026] The vehicle position detection sensor 33 receives satellite signals from positioning satellites of the Global Navigation Satellite System (GNSS), such as Global Positioning System (GPS) satellites. The vehicle position detection sensor 33 transmits the position information of the vehicle 10 contained in the received satellite signals to the driving assistance device 11. Note that the vehicle position detection sensor 33 may be provided with an antenna, in addition to the GPS sensor, that receives satellite signals from other satellite systems that identify the position of the vehicle 10.

[0027] The vehicle speed sensor 34 is a sensor that detects the traveling speed of the vehicle 10. The vehicle speed sensor 34 may be, for example, an encoder that detects the wheel speed, an encoder that detects the rotation speed of the drive motor serving as the drive power source 17, or a laser Doppler sensor. Alternatively, the vehicle speed sensor 34 may be a speed estimation module that utilizes self-position estimation technology using LiDAR or SLAM (Simultaneous Localization And Mapping) with a camera or the like. The vehicle speed sensor 34 is not particularly limited, and a normal sensor that can detect the speed of the vehicle 10 while it is traveling may be used.

[0028] The driving assistance device 11 may generate information indicating the movement speed of the vehicle 10 based on information indicating the position acquired from the vehicle position detection sensor 33. The driving assistance device 11 may calculate the movement speed of the vehicle 10, for example, based on a change in the position of the vehicle 10. Specifically, the driving assistance device 11 may calculate the movement speed of the vehicle 10 by dividing the distance from the position of the vehicle 10 acquired in the previous calculation cycle to the current position of the vehicle 10 acquired in the current calculation cycle by a unit time corresponding to the calculation cycle.

[0029] The display device 18 is driven by the driving assistance device 11 and displays various information visible to the driver. The display device 18 may be, for example, a display device provided in an instrument panel or a display device of a navigation system. The display device 18 may also be a HUD (head-up display) that displays information visible to the driver on the windshield, superimposed on the real space around the vehicle 10.

[0030] The driving assistance device 11 functions as a device that assists the driver in driving the vehicle 10 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 11. The computer program executed by the processor may be recorded on a recording medium that functions as a storage device 112 (memory) provided in the driving assistance device 11, or may be recorded on a recording medium built into the driving assistance device 11 or any recording medium that can be externally attached to the driving assistance device 11.

[0031] The recording medium for recording a computer program may be a magnetic medium such as a hard disk, a floppy disk, or a magnetic tape, an optical recording medium such as a CD-ROM, a DVD, or a Blu-ray (registered trademark), a magneto-optical medium such as a floptical disk, a memory element such as a RAM or a ROM, a flash memory such as a USB memory or an SSD, or any other medium capable of storing a program.

[0032] (Functional Configuration of Driving Assistance Device) Fig. 3 is a block diagram showing an example configuration of the driving assistance device 11. The surrounding environment recognition device 12 and the vehicle control unit 21 are connected to the driving assistance device 11 via communication means such as a dedicated line, a controller area network (CAN), or a local internet (LIN). Note that the driving assistance device 11 is not limited to an electronic control device mounted on the vehicle 10, and may also be a terminal device such as a touchpad or a wearable device.

[0033] The driving assistance device 11 includes a processing device 111 and a storage device 112. The processing device 111 includes one or more processors such as a CPU and various peripheral components. A part or all of the processing device 111 may be configured with updatable firmware or the like, or may be a program module or the like that is executed by instructions from the CPU or the like.

[0034] The storage device 112 is a recording medium such as one or more RAMs, ROMs, HDDs (Hard Disk Drives), CDs (Compact Discs), DVDs (Digital Versatile Discs), SSDs (Solid State Drives), USBs (Universal Serial Bus) flash drives, or storage devices that are communicably connected to the processing device 111. However, the type and number of storage devices 112 are not particularly limited, and there may be one or more.

[0035] The storage device 112 records data related to the computer program executed by the processing device 111, various parameters used in the calculation process, detection data, calculation results, etc. A part of the storage device 112 is used as a work area for the processing device 111.

[0036] The storage device 112 according to this embodiment stores a reference angle θ ＲＢ , θ ＬＢ The information on the reference angle θ, the information on the reference speed range, the information on the appropriate posture, and the pre-trained face detection model are stored in advance. ＲＢ , θ ＬＢ The information is used in the angle threshold setting process (step S5) described later. The information on the reference speed range is used in the determination process (step S4) of the sixth embodiment described later. The information on the correct posture is used in the determination process (step S4) of the seventh embodiment described later. The pre-trained face detection model is used in the determination process (step S4) of the eighth embodiment described later.

[0037] The processing device 111 includes a surrounding environment recognition processing unit 111A, a determination processing unit 111B, an angle threshold setting processing unit 111C, a tilt angle calculation processing unit 111D, a prediction processing unit 111E, and a collision avoidance processing unit 111F. The functions of these units are realized by a processor executing a computer program. Note that some of the surrounding environment recognition processing unit 111A, the determination processing unit 111B, the angle threshold setting processing unit 111C, the tilt angle calculation processing unit 111D, the prediction processing unit 111E, and the collision avoidance processing unit 111F may be configured using hardware such as an analog circuit.

[0038] The surrounding environment recognition processing unit 111A acquires information on the surrounding environment of the vehicle 10. The information on the surrounding environment of the vehicle 10 is information indicating the measurement results of the surrounding environment recognition device 12, for example.

[0039] The surrounding environment recognition processing unit 111A executes processing to recognize the surrounding environment of the vehicle 10 (hereinafter referred to as the surrounding environment recognition processing) based on information about the surrounding environment of the vehicle 10 acquired from the surrounding environment recognition device 12 mounted on the vehicle 10. The surrounding environment recognition processing unit 111A recognizes moving objects and stationary objects around the vehicle 10 through the surrounding environment recognition processing.

[0040] The determination processing unit 111B determines whether there is a factor other than a change in course that could cause the bicycle ridden by the driver to lean, based on the information from the measurement results of the surrounding environment recognition device 12. If the determination processing unit 111B determines that there is a factor that could cause the bicycle to lean, the angle threshold setting processing unit 111C sets an angle threshold according to that factor. In the following description, the bicycle ridden by the driver will be referred to as a "bicycle."

[0041] The tilt angle calculation processor 111D identifies the vertical direction based on the measurement result information obtained from the direction detection sensor. The tilt angle calculation processor 111D calculates the tilt angle θ of the bicycle recognized by the surrounding environment recognition process relative to the vertical direction. The prediction processor 111E predicts that the recognized bicycle will change course if the tilt angle θ calculated by the tilt angle calculation processor 111D exceeds the angle threshold set by the angle threshold setting processor 111C.

[0042] 4 and 5 are explanatory diagrams for explaining the pitch angle of the vehicle 10. The tilt angle calculation processing unit 111D according to this embodiment calculates the roll angle, pitch angle, and yaw angle of the vehicle 10 based on information on the detection results acquired from the direction detection sensor. The roll angle is the rotation angle of the vehicle 10 about the roll axis X. The pitch angle is the rotation angle of the vehicle 10 about the pitch axis Y. The yaw angle is the rotation angle of the vehicle 10 about the yaw axis Z.

[0043] In this embodiment, the pitch angle is defined as 0° when the roll axis X of the vehicle 10 is parallel to the horizontal direction H. In addition, the pitch angle is defined as a positive value when the axis X1 of the roll axis X is tilted vertically upward from the horizontal direction H as shown in Fig. 4, and the pitch angle is defined as a negative value when the axis X1 of the roll axis X of the vehicle 10 is tilted vertically downward from the horizontal direction H as shown in Fig. 5.

[0044] The collision avoidance processing unit 111F determines whether or not there is a possibility that the bicycle predicted to change course by the prediction processing unit 111E will collide with the vehicle 10. If the collision avoidance processing unit 111F determines that there is a possibility that the bicycle predicted to change course will collide with the vehicle 10, it controls the vehicle control unit 21 to cause the vehicle 10 to perform an operation to avoid a collision between the bicycle and the vehicle 10.

[0045] <Driving Assistance Method> Figure 6 is a flowchart showing an example of the driving assistance method of the present disclosure. An example of the driving assistance method of the present disclosure will be described below with reference to Figure 6. Note that the above flowchart is repeatedly executed at a predetermined calculation cycle when the function of the present disclosure is activated. Note that the driving assistance method described below will be described under the assumption that the bicycle is traveling ahead of the vehicle 10 in the direction of travel.

[0046] (Step S1: Acquire information on the surrounding environment of the vehicle) When the processing device 111 of the driving assistance device 11 detects activation of the assistance function, in step S1, the surrounding environment recognition processing unit 111A acquires information on the surrounding environment of the vehicle 10. Specifically, the surrounding environment recognition processing unit 111A acquires image data from the surrounding environment recognition device 12 (forward-facing imaging cameras 12A, 12B) that captures images of the surroundings of the vehicle 10, for example.

[0047] (Step S2: Surrounding environment recognition processing) Subsequently, in step S2, the surrounding environment recognition processing unit 111A executes surrounding environment recognition processing based on the information on the surrounding environment acquired from the surrounding environment recognition device 12. Specifically, the surrounding environment recognition processing unit 111A extracts feature points from the image data acquired from the surrounding environment recognition device 12, for example, by edge detection processing or the like, and performs matching processing (pattern matching) with pre-recorded pattern data of a group of feature points of various objects, thereby recognizing detected objects present around the vehicle 10, identifying the type of the detected objects, and identifying the position of the detected objects.

[0048] The surrounding environment recognition processing unit 111A recognizes detected objects present around the vehicle 10 and identifies the type of detected object by matching the extracted feature point group with pattern data of feature point groups representing, for example, vehicles, bicycles, rear wheels of bicycles, pedestrians, guardrails, curbs, roads, the road surfaces on which the bicycles travel, unevenness and puddles on the road surfaces, luggage carried on the bicycle, passengers on the bicycle, buildings, or vehicle lane boundaries. The surrounding environment recognition processing unit 111A also identifies the position of the detected object in real space based on the position of the detected object within the measurement range and the distance to the detected object.

[0049] Next, if the recognized detection object is a moving object, the surrounding environment recognition processing unit 111A calculates the moving speed and moving direction of the recognized moving object. For example, the surrounding environment recognition processing unit 111A calculates the moving speed and moving direction of the detection object in real space based on the change in the position of the same detection object over time, using the measurement data acquired in the current calculation cycle and the measurement data acquired in the previous calculation cycle.

[0050] The surrounding environment recognition process executed in step S2 may be executed using any known technology, and is not particularly limited to this. For example, if one of the surrounding environment recognition devices 12 is a LiDAR, the measurement data includes information on the speed of the measurement point, and therefore the process of calculating the movement speed by the surrounding environment recognition processing unit 111A may be omitted.

[0051] (Step S3: Is there a bicycle ahead in the direction of travel?) In step S3, the surrounding environment recognition processing unit 111A determines, as a result of the surrounding environment recognition processing, whether or not there is a bicycle ahead in the direction of travel of the vehicle 10. If the surrounding environment recognition processing unit 111A recognizes a bicycle through the surrounding environment recognition processing, it determines that there is a bicycle ahead in the direction of travel of the vehicle 10. On the other hand, if the surrounding environment recognition processing unit 111A does not recognize a bicycle through the surrounding environment recognition processing, it determines that there is no bicycle ahead in the direction of travel of the vehicle 10.

[0052] If the surrounding environment recognition processing unit 111A determines that a bicycle is present ahead of the vehicle 10 in the direction of travel (YES in step S3), the determination processing unit 111B executes step S4, which will be described later. On the other hand, if the processing device 111 determines that a bicycle is not present ahead of the vehicle 10 in the direction of travel (NO in step S3), the processing device 111 executes the previous step S1 again.

[0053] (Step S4: Are there any factors that cause the bicycle to lean other than a change in lane?) In step S4, the determination processing unit 111B determines whether there are any factors that cause the bicycle to lean other than a change in lane. Specifically, the determination processing unit 111B determines whether there are any factors that cause the bicycle to lean based on the unevenness of the road surface on which the bicycle is traveling. More specifically, the processing device 111 executes the following process 1 or 2.

[0054] (Process 1) In the surrounding environment recognition process of step S2, the surrounding environment recognition processing unit 111A recognizes a convex portion on the road surface on which the vehicle 10 is traveling. The determination processing unit 111B estimates the height of the convex portion based on image data of the convex portion.

[0055] Generally, if there is a protrusion of a predetermined height or more on the road surface on which the bicycle is traveling, the bicycle's tires may trip over the protrusion, causing the bicycle to lean even without changing course. Therefore, the determination processing unit 111B according to this embodiment determines that there is a factor causing the bicycle to lean other than changing course if the estimated height of the protrusion is equal to or greater than the predetermined height, and determines that there is no factor causing the bicycle to lean other than changing course if the estimated height of the protrusion is less than the predetermined height.

[0056] (Process 2) In the preceding surrounding environment recognition process of step S2, the surrounding environment recognition processing unit 111A recognizes a puddle on the road surface on which the vehicle 10 is traveling. The determination processing unit 111B estimates the depth of the puddle based on image data of the puddle. Specifically, for example, the determination processing unit 111B measures the vertical dimension D1 of the wheel of the bicycle or other vehicle from image data of the puddle before the bicycle or other vehicle enters it. Next, the determination processing unit 111B measures the vertical dimension D2 of the portion of the wheel that is not submerged in the puddle from image data of the puddle that the bicycle or other vehicle has entered, and estimates the depth of the puddle by calculating the difference (D1-D2) between the dimension D1 and the dimension D2.

[0057] Generally, if a puddle of a predetermined depth or greater exists on the road surface on which a bicycle is traveling, the bicycle's tires may get stuck in the puddle, causing the bicycle to lean even without changing course. Therefore, the determination processing unit 111B according to this embodiment determines that there is a factor causing the bicycle to lean other than changing course if the estimated puddle depth is greater than the predetermined depth, and determines that there is no factor causing the bicycle to lean other than changing course if the estimated puddle depth is less than the predetermined depth.

[0058] If the determination processing unit 111B determines that there is a factor other than a course change (YES in step S4), the angle threshold setting processing unit 111C executes step S5, which will be described later. On the other hand, if the determination processing unit 111B determines that there is no factor other than a course change (NO in step S4), the processing device 111 executes the previous step S3 again.

[0059] The method for estimating the height of the bumps on the road surface on which the bicycle is traveling and the depth of the puddles is not particularly limited, and they may be detected using known techniques. For example, the height of the bumps on the road surface is not limited to estimation based on image data acquired from the front-view cameras 12A and 12B, and may be estimated using LiDAR.

[0060] (Step S5: Angle Threshold Setting Process) Figure 7 is an explanatory diagram for explaining the angle threshold setting process, and is a diagram that schematically shows the bicycle 20. In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor.

[0061] Specifically, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to tilt, the angle threshold setting processing unit 111C sets the angle threshold on the right side of the traveling direction of the bicycle 20 to the reference angle θ ＲＢ Angle θ greater than Ａ and the angle threshold value on the left side of the bicycle 20 in the traveling direction is set to the reference angle θ ＬＢ Angle θ greater than Ｂ Set to.

[0062] Angle θ Ａ (for example, 20° or 30°) is the reference angle θ ＲＢ (e.g., 15°) １ (for example, 5° or 15°) is added to the angle θ Ｂ (for example, 20° or 30°) is the reference angle θ ＬＢ (e.g., 15°) １ (for example, 5° or 15°) is added.

[0063] The "angle threshold" is a threshold for determining whether or not the bicycle 20 should change course. The "reference angle" is a preset angle threshold (prescribed value) that assumes that the bicycle 20 will be traveling on a flat road.

[0064] (Step S6: Tilt Angle Calculation Process) Figures 8 and 9 are explanatory diagrams for explaining the tilt angle calculation process. Figure 8 is a diagram schematically showing the bicycle 20 facing backward relative to the vehicle 10, and Figure 9 is a diagram schematically showing the bicycle 20 facing forward relative to the vehicle 10.

[0065] In step S6, the tilt angle calculation processing unit 111D calculates the vertical direction D of the bicycle 20 recognized by the surrounding environment recognition device 12 that recognizes the surrounding environment of the vehicle 10. ＶSpecifically, the processing device 111 executes the following process 3 or 4.

[0066] (Process 3) In the surrounding environment recognition process of the previous step S2, the surrounding environment recognition processing unit 111A recognizes the rear wheel R of the bicycle 20. Ｗ The tilt angle calculation processing unit 111D recognizes the vertical direction D based on the information of the detection result obtained from the direction detection sensor. Ｖ The tilt angle calculation processing unit 111D identifies the recognized rear wheel R Ｗ Central axis D Ｆ and the specified vertical direction D Ｖ The angle between the left and right angles is calculated as the tilt angle θ of the bicycle 20.

[0067] (Process 4) The surrounding environment recognition processing unit 111A recognizes the frame f (e.g., head tube) of the bicycle 20 in the surrounding environment recognition processing of the previous step S2. The tilt angle calculation processing unit 111D calculates the vertical direction D based on the information of the detection result obtained from the direction detection sensor. Ｖ The tilt angle calculation processing unit 111D determines the central axis D of the recognized frame f. Ｃ and the specified vertical direction D Ｖ The angle between the left and right angles is calculated as the tilt angle θ of the bicycle 20.

[0068] (Step S7: Has the lean angle of the bicycle exceeded the angle threshold?) Figures 10 to 13 are explanatory diagrams for explaining step S7, and are diagrams that schematically show bicycle 20. In step S7, prediction processing unit 111E determines whether the lean angle θ calculated in the previous step S6 exceeds the angle threshold set in the previous step S5.

[0069] Specifically, as shown in FIG. 10, the prediction processing unit 111E calculates the calculated tilt angle θ as an angle θ set as the angle threshold. Ａ or less, or as shown in FIG. 11, the calculated tilt angle θ is equal to or less than the angle θ set as the angle threshold. Ｂ If it is equal to or less than this, it is determined that the tilt angle of the bicycle 20 does not exceed the angle threshold value.

[0070] On the other hand, as shown in FIG. 12, the prediction processing unit 111E calculates the calculated tilt angle θ as the angle θ set as the angle threshold. Ａ If the calculated tilt angle θ is larger than the angle θ set as the angle threshold, or as shown in FIG. 13, Ｂ If it is greater than the threshold value, it is determined that the lean angle of the bicycle 20 has exceeded the threshold angle.

[0071] If the prediction processing unit 111E determines that the tilt angle of the bicycle 20 exceeds the angle threshold (YES in step S7), it executes step S8, which will be described later. On the other hand, if the processing unit 111 determines that the tilt angle of the bicycle 20 does not exceed the angle threshold (NO in step S7), it sets the angle threshold to the angle θ Ａ , θ Ｂ From the reference angle θ ＲＢ , θ ＬＢ Then, the previous step S3 is executed again.

[0072] (Step S8: Integrating the duration for which the tilt angle θ of the bicycle 20 exceeds the angle threshold value) In step S8, the prediction processing unit 111E integrates the duration for which the tilt angle θ of the bicycle 20 exceeds the angle threshold value set in the previous step S5. １ If the angle threshold value continues to be exceeded until the tilt angle θ starts to exceed the angle threshold value, ０ From time t １ The difference (t １ -t ０ ) is measured.

[0073] (Step S9: Is the duration longer than or equal to a predetermined time?) In step S9, the prediction processing unit 111E determines whether the duration measured in the previous step S8 is longer than or equal to a predetermined time. If the measured duration is longer than or equal to the predetermined time, that is, if the difference (t １ -t ０ If the measured duration is less than the predetermined time, that is, if the difference (t １ -t ０If the time interval is less than the predetermined time interval (NO in step S9), the previous step S7 is executed again.

[0074] (Step S10: Prediction Process) In step S10, the prediction processing unit 111E predicts that the bicycle 20 will change course if the tilt angle θ calculated by the tilt angle calculation process in step S6 exceeds a predetermined angle threshold.

[0075] Specifically, if the tilt angle θ of the bicycle 20 exceeds the angle threshold set in the previous step S5 for a predetermined period of time or longer, the prediction processing unit 111E predicts that the bicycle 20 will change course. This prevents the bicycle 20 from immediately determining that a course change has occurred when the tilt angle θ exceeds the angle threshold due to the bicycle 20 swaying. Therefore, the prediction processing unit 111E can accurately determine whether the bicycle 20 is swaying or will change course.

[0076] (Step S11: Determine the possibility of the bicycle colliding with the vehicle) In step S11, the collision avoidance processing unit 111F determines whether there is a possibility that the bicycle 20, which was predicted to change course by the prediction processing in the previous step S10, will collide with the vehicle 10.

[0077] Specifically, the collision avoidance processing unit 111F estimates the expected path of the vehicle 10 based on the yaw angle of the vehicle 10 or the steering angle of the vehicle 10 calculated by the tilt angle calculation processing unit 111D.

[0078] Next, the collision avoidance processing unit 111F estimates the expected route of the bicycle 20 based on the travel speed of the bicycle 20 calculated in the previous step S2 and the lean angle θ of the bicycle 20. Specifically, the collision avoidance processing unit 111F sequentially calculates the turning radius of the bicycle 20 based on the travel speed of the bicycle 20 and the lean angle θ of the bicycle 20, and estimates the expected route of the bicycle 20 from the calculated turning radius.

[0079] Next, the collision avoidance processing unit 111F determines whether the estimated predicted route R1 of the bicycle 20 intersects with the estimated predicted route R2 of the vehicle 10. If the collision avoidance processing unit 111F determines that the estimated route R1 and the estimated route R2 intersect, it calculates the time t at which the vehicle 10 will arrive at the intersection XP based on the current traveling speed of the vehicle 10. ２ , and calculates the time t when the bicycle 20 will arrive at the intersection XP based on the current traveling speed of the bicycle 20. ３ Calculate.

[0080] Next, the collision avoidance processing unit 111F ２ and time t ３ The collision avoidance processing unit 111F determines whether the time interval between the vehicle 10 and the bicycle 20 is equal to or greater than a predetermined interval. If the collision avoidance processing unit 111F determines that the time interval is equal to or greater than the predetermined interval, it determines that there is no possibility of a collision between the vehicle 10 and the bicycle 20. On the other hand, if the collision avoidance processing unit 111F determines that the time interval is less than the predetermined interval, it determines that there is a possibility of a collision between the vehicle 10 and the bicycle 20.

[0081] On the other hand, if the collision avoidance processing unit 111F determines that the predicted route R1 and the predicted route R2 do not intersect, it determines that there is no possibility that the bicycle 20 will collide with the vehicle 10.

[0082] If the collision avoidance processing unit 111F determines that there is a possibility that the bicycle 20 will collide with the vehicle 10 (YES in step S11), it executes step S12, which will be described later. On the other hand, if the processing unit 111 determines that there is no possibility that the bicycle 20 will collide with the vehicle 10 (NO in step S11), it sets the angle threshold to the angle θ Ａ , θ Ｂ From the reference angle θ ＲＢ , θ ＬＢ Then, the previous step S3 is executed again.

[0083] (Step S12: Collision Avoidance Processing) If the collision avoidance processing unit 111F determines that there is a possibility that the bicycle 20 will collide with the vehicle 10, it executes collision avoidance processing to avoid a collision between the vehicle 10 and the bicycle 20. Specifically, the collision avoidance processing unit 111F outputs command information to the vehicle control unit 21 to avoid a collision between the vehicle 10 and the bicycle 20. Upon receiving this command information, the vehicle control unit 21 controls the steering angle and / or acceleration / deceleration of the vehicle 10 so that the predicted path of the vehicle 10 and the predicted path of the bicycle 20 do not intersect.

[0084] In the process of step S12, the vehicle control unit 21 calculates the control amount of the steering angle and / or acceleration / deceleration of the vehicle 10 by calculating, for example, the difference between the tilt angle θ of the bicycle 20 and the angle threshold (θ - θ Ａ or θ-θ Ｂ That is, the vehicle control unit 21 increases the control amount as the difference increases, and decreases the control amount as the difference decreases.

[0085] The collision avoidance process for avoiding a collision between the vehicle 10 and the bicycle 20 is not limited to the process described above, and any conventionally known technology may be used.

[0086] (Step S13: Overtaking or passing completed?) The collision avoidance processing unit 111F determines whether the vehicle 10 has completed overtaking or passing the bicycle 20. Specifically, if the result of executing the previous step S12 is that the vehicle 10 has overtaken or passed the bicycle 20 and the bicycle 20 is not detected by the side detection sensors or the front imaging cameras 12A, 12B, the collision avoidance processing unit 111F determines that the vehicle 10 has completed overtaking or passing the bicycle 20 (YES in step S13).

[0087] On the other hand, if the bicycle 20 has been detected by the side detection sensors or the front-facing cameras 12A, 12B as a result of executing the previous step S12, the collision avoidance processing unit 111F determines that the vehicle 10 has not completed overtaking or passing the bicycle 20 (NO in step S13). In this case, the processing device 111 sets the angle threshold to the angle θ Ａ , θ ＢFrom the reference angle θ ＲＢ , θ ＬＢ Then, the previous step S3 is executed again.

[0088] As can be understood from the above description, the driving assistance device 11 according to this embodiment includes one or more processors and one or more memories communicably connected to the one or more processors. The one or more processors recognize the surrounding environment of the vehicle 10 in the vertical direction D of the bicycle 20 recognized by the surrounding environment recognition device 12. Ｖ a prediction process that predicts that the bicycle 20 will change course if the tilt angle θ calculated by the tilt angle calculation process exceeds a predetermined angle threshold; a determination process that determines whether there is a factor that will cause the bicycle 20 to tilt other than a change of course; and an angle threshold setting process that sets an angle threshold based on the factor if it is determined in the determination process that there is a factor that will cause the bicycle 20 to tilt.

[0089] According to the driving assistance device 11, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ The angle threshold after resetting is set to an angle θ that is suitable for various factors that may cause the bicycle 20 to lean, other than course changes. Ａ , θ Ｂ As a result, the prediction processing unit 111E determines whether the tilt angle θ of the bicycle 20 is equal to the predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether the bicycle 20 will change course than by simply predicting that the bicycle 20 will change course when the speed exceeds 100 km / h.

[0090] As explained above, in the determination process, the one or more processors determine whether there is a factor that could cause the bicycle 20 to tilt based on the unevenness of the road surface on which the bicycle 20 is traveling. Specifically, in the determination process, the one or more processors determine that there is a factor that could cause the bicycle 20 to tilt if the height of the protrusion on the road surface is equal to or greater than a predetermined height, and in the angle threshold setting process, determine that there is a factor that could cause the bicycle 20 to tilt based on the predetermined reference angle θ ＲＢ , θ ＬＢ a first angle θ １ The angle θ addedＡ , θ Ｂ is set as the angle threshold.

[0091] According to the above aspect, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Therefore, even if the bicycle 20 leans, the lean angle θ is unlikely to exceed the angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that the swaying of the bicycle 20 caused by a bump on the road surface is a course change, improving the judgment accuracy of the prediction processing unit 111E.

[0092] Second Embodiment Next, an example of a driving assistance method according to a second embodiment of the present disclosure will be described with reference to Fig. 6. In the description of the driving assistance methods of second to eighth embodiments described below, the same components and steps as those in the first embodiment will be denoted by the same reference numerals, and the description thereof will be omitted.

[0093] (Step S4: Are there any factors that cause the bicycle 20 to lean other than a change in lane?) Figure 14 is a diagram that schematically shows the bicycle 20 traveling on an inclined surface that slopes in the width direction of the vehicle 10 and the bicycle 20 (hereinafter sometimes referred to as a lateral inclined surface). The determination processing unit 111B determines whether there is a factor that causes the bicycle to lean other than a change in lane. Specifically, the determination processing unit 111B determines whether there is a factor that causes the bicycle 20 to lean based on the inclination of the road surface R on which the bicycle 20 is traveling. More specifically, the determination processing unit 111B executes the following process 5, 6, or 7.

[0094] (Process 5) Generally, if the road surface on which a bicycle is traveling is laterally inclined, the bicycle traveling on the laterally inclined surface is likely to tilt vertically downward without changing course. Therefore, the determination processing unit 111B according to this embodiment determines that there is a factor causing the bicycle 20 to tilt other than a lane change if the roll angle of the vehicle 10 is equal to or greater than a predetermined angle, i.e., if the road surface R on which the vehicle 10 and bicycle 20 are traveling is inclined at an angle greater than a predetermined angle in the width direction of the vehicle 10 (YES in step S4). On the other hand, if the roll angle, pitch angle, and yaw angle of the vehicle 10 are less than the predetermined angles, the determination processing unit 111B determines that there is no factor causing the bicycle 20 to tilt other than a lane change (NO in step S4).

[0095] (Process 6) Generally, when a bicycle is traveling on an uphill road, the rider of the bicycle may pedal hard, causing the bicycle to lean even without changing course. Therefore, the determination processor 111B according to this embodiment determines that there is a factor causing the bicycle 20 to lean other than a lane change if the positive value of the pitch angle of the vehicle 10 is equal to or greater than a predetermined threshold, i.e., if the road surface R on which the vehicle 10 and bicycle 20 are traveling is an uphill slope that slopes at an angle greater than a predetermined angle in the direction of travel of the bicycle 20 (YES in step S4). On the other hand, if the roll angle, pitch angle, and yaw angle of the vehicle 10 are less than the predetermined angles, the determination processor 111B determines that there is no factor causing the bicycle 20 to lean other than a lane change (NO in step S4).

[0096] (Process 7) Generally, when a bicycle travels downhill, an increase in speed can cause it to lean even without changing course. Therefore, the determination processing unit 111B according to this embodiment determines that there is a factor causing the bicycle 20 to lean other than a change in course if the negative value of the pitch angle of the vehicle 10 is less than a predetermined threshold, i.e., if the road surface R on which the vehicle 10 and bicycle 20 are traveling is a downhill slope that inclines at a predetermined angle or more in the direction of travel of the bicycle 20 (YES in step S4). On the other hand, if the roll angle, pitch angle, and yaw angle of the vehicle 10 are less than the predetermined angles, the determination processing unit 111B determines that there is no factor causing the bicycle 20 to lean other than a change in course (NO in step S4).

[0097] The determination processing unit 111B may use a conventionally known technique to determine whether the road surface R on which the vehicle 10 and bicycle 20 are traveling is an uphill, downhill, or lateral slope. For example, the determination processing unit 111B may determine whether the road surface R is an uphill, downhill, or lateral slope based on image data of an image of the road surface R, information about the steering amount of the vehicle 10, or driving data of the vehicle 10 such as the engine load.

[0098] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor. Specifically, the angle threshold setting processor 111C executes the following process 8, 9, or 10.

[0099] (Process 8) When the determination processing unit 111B determines in process 5 that there is a factor that causes the bicycle 20 to tilt, the angle threshold setting processing unit 111C sets the angle threshold of the lateral inclined surface on the slope side vertically above the contact point S between the bicycle 20 and the lateral inclined surface to a reference angle θ ＬＢ The angle threshold value of the horizontally inclined surface on the slope side vertically downward from the contact point S is set to the reference angle θ ＲＢ As shown in FIG. 14 , the road surface R on which the bicycle 20 is traveling is a laterally inclined surface, so that a bicycle attempting to travel straight will lean against the inclination of the road surface R toward the slope vertically upward from the contact point S as shown in the figure. Accordingly, the angle threshold setting processing unit 111C sets the angle threshold for the slope vertically upward from the contact point S between the bicycle 20 and the laterally inclined surface to the reference angle θ ＬＢ An angle θ greater than (for example, 15°) Ｂ (for example, 20°), and the angle threshold value of the horizontally inclined surface on the side of the slope vertically downward from the contact point S is the reference angle θ ＲＢ An angle θ smaller than (for example, 15°) Ａ (For example, 10°).

[0100] In process 8, the angle threshold setting processing unit 111C sets the angle threshold on the slope side vertically above the contact point S between the bicycle 20 and the slope to an angle θ Ｂand the angle threshold value on the slope side vertically downward from the contact point S between the bicycle 20 and the slope is set to an angle θ Ａ That is, the angle threshold setting processing unit 111C according to the present embodiment may uniformly set the angle threshold on the slope side vertically above the ground contact point S and the angle threshold on the slope side vertically below the ground contact point S, or may variably set the angle threshold according to the roll angle of the vehicle 10 (the inclination angle of the inclined surface).

[0101] The method for estimating the inclination angle of the inclined surface is not particularly limited, and any conventionally known technology may be used. For example, the determination processing unit 111B may estimate the inclination angle of the inclined surface based on image data of an image of the inclined surface (road surface R), information on the steering amount of the vehicle 10, or driving data such as the engine load of the vehicle 10.

[0102] (Process 9) When the determination processing unit 111B determines in process 6 that there is a factor that causes the bicycle 20 to tilt, the angle threshold setting processing unit 111C sets the angle threshold to the reference angle θ ＲＢ , θ ＬＢ FIG. 15 is a diagram showing a bicycle 20 traveling uphill. When a bicycle traveling uphill is pedaling hard, the rider may lean to the right or left in the direction of travel, compared to when the bicycle is traveling on a road surface R as shown in FIG. 14 . Therefore, when the road surface R on which the vehicle 10 and bicycle 20 are traveling is an uphill slope that inclines at a predetermined angle or more in the direction of travel of the bicycle 20, the angle threshold setting processing unit 111C sets a predetermined reference angle θ as shown in FIG. 15 to prevent the inclination from being erroneously determined to be due to a lane change. ＲＢ , θ ＬＢ (e.g., 15°) to the second angle θ ２ (for example, 15°) plus the angle θ Ａ , θ Ｂ (for example, 30°) is set as the angle threshold, and the angle threshold is set as the reference angle θ ＲＢ , θ ＬＢ Make it bigger than.

[0103] (Process 10) When the determination processing unit 111B determines in process 7 that there is a factor that causes the bicycle 20 to tilt, the angle threshold setting processing unit 111C sets the angle threshold to the reference angle θ ＲＢ , θ ＬＢ 16 is a diagram showing a bicycle 20 traveling downhill. When traveling downhill, the bicycle's speed increases compared to when traveling on a road surface R (laterally inclined surface) such as that shown in FIG. 14 or a road surface R (uphill) such as that shown in FIG. 15, and the bicycle may change course at a smaller inclination angle θ. Therefore, when the road surface R on which the vehicle 10 and bicycle 20 are traveling is a downhill slope that inclines at a predetermined inclination angle or more in the direction of travel of the bicycle 20, the angle threshold setting processing unit 111C sets a predetermined reference angle θ as shown in FIG. 16 to improve the detection accuracy of detecting the inclination associated with a course change of the bicycle 20 traveling downhill. ＲＢ , θ ＬＢ (e.g., 15°) to a third angle θ ３ (for example, 5°) Ａ , θ Ｂ (for example, 10°) is set as the angle threshold, and the angle threshold is set as the reference angle θ ＲＢ , θ ＬＢ Make it smaller than.

[0104] As described above, in the judgment process of step S4, one or more processors according to the second embodiment determine whether there is a factor other than a change in course that would cause the bicycle 20 to tilt, based on the inclination state of the road surface R on which the bicycle 20 is traveling.

[0105] Specifically, in the judgment process of step S4, if the road surface R on which the vehicle 10 and bicycle 20 are traveling is an inclined surface that inclines in the width direction of the vehicle 10 at a predetermined angle or more, the one or more processors determine that there is a factor that will cause the bicycle 20 to tilt, and in the angle threshold setting process of step S5, they set the angle threshold of the slope side of the inclined surface above the contact point S between the bicycle 20 and the inclined surface to an angle greater than a predetermined reference angle, and set the angle threshold of the slope side of the inclined surface below the contact point S to an angle smaller than the predetermined reference angle.

[0106] According to the above aspect, the angle threshold for the slope on the side of the inclined surface that is vertically upward from the contact point S is set to an angle greater than the reference angle. Therefore, even if the bicycle 20 leans toward the slope vertically upward from the contact point S, the tilt angle θ is less likely to exceed the increased angle threshold. This prevents the prediction processing unit 111E from erroneously predicting that swaying of the bicycle 20 caused by the road surface R on which the vehicle 10 and bicycle 20 are traveling is a lateral slope as a course change, improving the determination accuracy of the prediction processing unit 111E.

[0107] In particular, in the second embodiment, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ The angle threshold is reset from the angle θ Ａ , θ Ｂ As a result, the prediction processing unit 111E determines whether the tilt angle θ of the bicycle 20 is equal to the predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether the bicycle 20 will change course than by simply predicting that the bicycle 20 will change course when the speed exceeds 100 km / h.

[0108] Furthermore, as explained above, in the determination process of step S4, if the road surface R on which the vehicle 10 and bicycle 20 are traveling is an uphill slope that inclines at a predetermined angle or more in the direction of travel of the bicycle 20, the one or more processors according to the second embodiment determine that there is a factor that will cause the bicycle 20 to tilt, and in the angle threshold setting process of step S5, determine that there is a factor that will cause the bicycle 20 to tilt. ＲＢ , θ ＬＢ a second angle θ ２ The angle θ added Ａ , θ Ｂ is set as the angle threshold.

[0109] According to the above aspect, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ ＢTherefore, even if the bicycle 20 leans while traveling uphill, the tilt angle θ is unlikely to exceed the angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that the swaying of the bicycle 20 caused by traveling uphill is a course change, improving the judgment accuracy of the prediction processing unit 111E.

[0110] Furthermore, in the determination process of step S4, if the road surface R on which the vehicle 10 and the bicycle 20 are traveling is a downhill slope that inclines at an angle of more than a predetermined angle in the direction of travel of the bicycle 20, the one or more processors according to the second embodiment determine that there is a factor that will cause the bicycle 20 to tilt, and in the angle threshold setting process of step S5, determine that a predetermined reference angle θ ＲＢ , θ ＬＢ to the third angle θ ３ The angle θ subtracted from Ａ , θ Ｂ is set as the angle threshold.

[0111] According to the above aspect, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ Angle θ smaller than Ａ , θ Ｂ Therefore, when the bicycle 20 traveling downhill leans due to a lane change, the lean angle θ is likely to exceed the angle threshold. As a result, the prediction processing unit 111E determines whether the lean angle θ of the bicycle 20 is greater than the predetermined reference angle θ ＲＢ , θ ＬＢ This improves the accuracy of detecting the tilt of the bicycle 20 that accompanies a change in course, compared to simply predicting that the bicycle will change course when the bicycle 20 exceeds this threshold.

[0112] [Third embodiment] <Driving assistance method> Next, the configuration of a vehicle 10 according to a third embodiment of the present disclosure will be described. The vehicle 10 according to the third embodiment differs from the vehicle 10 according to the first embodiment in that it includes a wind direction and wind speed sensor. Note that in the description of the configurations of the third and fourth embodiments described below, description of the same configuration as the vehicle 10 according to the first embodiment will be omitted.

[0113] <Vehicle Configuration> The wind direction and speed sensor can be a known sensor capable of measuring wind direction and wind speed, and can be installed at any position on the vehicle 10 so as to be able to measure wind direction and wind speed. The wind direction and speed sensor transmits information on the measurement results to the processing device 111.

[0114] <Driving Assistance Method> Next, an example of a driving assistance method according to the third embodiment of the present disclosure will be described with reference to FIG. 6 .

[0115] (Step S4: Are there any factors that cause the bicycle to tilt other than a change in course?) The determination processing unit 111B determines whether there are any factors that cause the bicycle to tilt other than a change in course. Specifically, the determination processing unit 111B determines whether there are any factors that cause the bicycle 20 to tilt based on wind conditions.

[0116] More specifically, the determination processor 111B obtains information on wind direction and wind speed from the measurement results obtained from the wind direction and wind speed sensor. Next, if the wind speed is equal to or greater than a predetermined threshold, the determination processor 111B determines that there is a factor that may cause the bicycle 20 to tilt other than the lane change (YES in step S4). On the other hand, if the wind speed is less than the predetermined threshold, the determination processor 111B determines that there is no factor that may cause the bicycle 20 to tilt other than the lane change (NO in step S4).

[0117] The method for measuring wind direction and wind speed is not limited to the above method, and conventionally known techniques may be used. For example, instead of or in addition to providing a wind direction and wind speed sensor in the vehicle 10, the determination processing unit 111B may measure wind direction and wind speed by acquiring and analyzing image data of windsocks, small wind turbines, etc. installed around the vehicle 10 while it is moving using an imaging device (such as a camera) mounted on the vehicle 10. Furthermore, an external wind speed measurement device that can provide wind direction and wind speed information to the vehicle 10 via a known external communication device may function as the wind direction and wind speed sensor. For example, wind direction and wind speed information from weather information surrounding the vehicle 10 while it is moving may be acquired via the external communication device. Furthermore, the wind measured by the wind direction and wind speed sensor is not limited to natural wind. For example, it may be wind generated when another vehicle passes by the vehicle 10.

[0118] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor. Specifically, the angle threshold setting processor 111C executes process 11 or 12 described below.

[0119] (Process 11) Figure 17 is a diagram showing a bicycle 20 traveling while being subjected to wind. For example, in a situation where the wind is blowing from the left to the right of the bicycle 20's direction of travel, the bicycle 20 may be tilted to the right (downwind) of the direction of travel without changing course. Therefore, when the bicycle 20 is blown by wind from the above-mentioned wind direction, the angle threshold setting processing unit 111C sets the angle threshold for the right side (downwind) of the direction of travel of the bicycle 20 to the reference angle θ ＲＢ Angle θ greater than Ａ and the angle threshold value on the left side (upwind side) of the bicycle 20 in the traveling direction is set to the reference angle θ ＬＢ Angle θ smaller than Ｂ or set the reference angle θ ＬＢ Maintain it.

[0120] In process 11, the angle threshold setting processing unit 111C sets the angle thresholds on the right and left sides (upwind and downwind sides) of the bicycle 20 in the traveling direction as an angle θ Ａ , θ Ｂ That is, the angle threshold setting processing unit 111C according to this embodiment may set the angle thresholds on the right and left sides (upwind and downwind sides) in the traveling direction of the bicycle 20 uniformly, or may set them variably according to the wind speed.

[0121] (Process 12) When a headwind is blowing, the bicycle 20 may lean to the right or left side of its traveling direction without changing course. Therefore, when the bicycle 20 is blown into a headwind, the angle threshold setting processing unit 111C sets the angle thresholds for the right and left sides of the traveling direction of the bicycle 20 based on the reference angle θ ＲＢ , θ ＬＢ An angle θ greater than (for example, 15°)Ａ , θ Ｂ (for example, 30°).

[0122] As described above, in the judgment process of step S4, one or more processors according to the third embodiment determine whether there is a factor that could cause the bicycle 20 to tilt based on wind conditions, and in the angle threshold setting process of step S5, the angle threshold on the windward side can be set to a predetermined reference angle or to an angle smaller than that angle threshold, and the angle threshold on the downwind side can be set to an angle larger than the predetermined reference angle.

[0123] According to the above-described embodiment, the downwind angle threshold is set to an angle greater than the reference angle. Therefore, even if the bicycle 20 leans to the downwind side, the tilt angle θ is unlikely to exceed the downwind angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that a sway in the bicycle 20 due to wind is a course change, improving the prediction processing unit 111E's determination accuracy.

[0124] In particular, in the third embodiment, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ The angle threshold is reset from the angle θ Ａ , θ Ｂ As a result, the prediction processing unit 111E determines whether the tilt angle θ of the bicycle 20 is equal to the predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether the bicycle 20 will change course than by simply predicting that the bicycle 20 will change course when the speed exceeds 100 km / h.

[0125] Fourth Embodiment Next, a configuration of a vehicle 10 according to a fourth embodiment of the present disclosure will be described. The vehicle 10 according to the fourth embodiment differs from the vehicle 10 according to the first embodiment in that it includes a raindrop sensor.

[0126] <Vehicle Configuration> The raindrop sensor is installed, for example, near the windshield of the vehicle 10. The raindrop sensor has a vibration pickup that detects vibrations of the windshield caused by raindrops hitting the windshield and outputs a signal corresponding to the vibration acceleration. Alternatively, the raindrop sensor may be a sensor that detects the capacitance of electrostatic changes caused by water adhesion and outputs a signal corresponding to the electrostatic changes. Alternatively, the raindrop sensor may be a sensor that calculates the number or area ratio of raindrops that fall within a predetermined range on the windshield in a predetermined time based on image data from a camera, thereby estimating the amount of rainfall. The raindrop sensor outputs information on the detection results to the processing device 111. The information on the detection results includes the signal corresponding to the vibration acceleration or the signal corresponding to the electrostatic changes.

[0127] <Driving Assistance Method> Next, an example of a driving assistance method according to the fourth embodiment of the present disclosure will be described with reference to FIG. 6 .

[0128] (Step S4: Are there any factors that cause the bicycle to lean other than a change in course?) The determination processing unit 111B determines whether there are any factors that cause the bicycle to lean other than a change in course. Specifically, the determination processing unit 111B determines whether there are any factors that cause the bicycle 20 to lean based on the amount of rainfall.

[0129] More specifically, the determination processor 111B estimates the amount of rainfall based on the detection result information acquired from the raindrop sensor. Next, if the estimated amount of rainfall is equal to or greater than a predetermined threshold, the determination processor 111B determines that there is a factor that causes the bicycle 20 to tilt other than the lane change (YES in step S4). On the other hand, if the estimated amount of rainfall is less than the predetermined threshold, the determination processor 111B determines that there is no factor that causes the bicycle 20 to tilt other than the lane change (NO in step S4).

[0130] The method for estimating the amount of rainfall is not limited to the above method, and any conventionally known technique may be used. For example, the determination processing unit 111B may estimate the amount of rainfall based on information from the measurement results of a hygrometer.

[0131] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor.

[0132] Generally, when it is raining, a bicycle may lean to the right or left side of its traveling direction without changing course, for example, by getting stuck in a puddle or mud. Therefore, when the bicycle 20 is traveling in the rain, the angle threshold setting processing unit 111C sets the angle thresholds for the right and left sides of the traveling direction of the bicycle 20 relative to the reference angle θ ＲＢ , θ ＬＢ An angle θ greater than (for example, 15°) Ａ , θ Ｂ (for example, 30°).

[0133] In the process of step S5, the angle threshold setting processing unit 111C sets the angle thresholds on the right and left sides of the bicycle 20 in the traveling direction to an angle θ Ａ , θ Ｂ That is, the angle threshold setting processing unit 111C according to this embodiment may set the angle thresholds for the right and left sides of the bicycle 20 in the traveling direction to a uniform value, or may set them variably according to the amount of rainfall.

[0134] As explained above, in the determination process of step S4, one or more processors according to the fourth embodiment determine whether there is a factor that causes the bicycle 20 to tilt based on the amount of rainfall, and in the angle threshold setting process of step S5, set the angle threshold to a predetermined reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Set to

[0135] According to the above aspect, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ ＢTherefore, even if the bicycle 20 leans due to rainfall, the tilt angle θ is unlikely to exceed the angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that the swaying of the bicycle 20 caused by rainfall is a course change, improving the judgment accuracy of the prediction processing unit 111E.

[0136] In particular, in the fourth embodiment, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ The angle threshold is reset from the angle θ Ａ , θ Ｂ As a result, the prediction processing unit 111E determines whether the tilt angle θ of the bicycle 20 is equal to the predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether the bicycle 20 will change course than by simply predicting that the bicycle 20 will change course when the speed exceeds 100 km / h.

[0137] Fifth Embodiment <Driving Assistance Method> Next, an example of a driving assistance method according to a fifth embodiment of the present disclosure will be described with reference to FIG. 6 .

[0138] (Step S4: Is there a factor that could cause the bicycle 20 to lean other than a change in course?) Fig. 18 is a diagram that schematically shows the bicycle 20 loaded with luggage L, and Fig. 19 is a diagram that schematically shows the bicycle 20 with a passenger P on board. In step S4, the determination processing unit 111B determines whether or not there is a factor that could cause the bicycle 20 to lean other than a change in course. Specifically, in the determination processing of step S4, the determination processing unit 111B determines whether or not there is a factor that could cause the bicycle 20 to lean based on the presence or absence of luggage L loaded on the bicycle 20 or a passenger P other than the driver of the bicycle 20.

[0139] More specifically, if the surrounding environment recognition processing unit 111A recognizes the luggage L or the passenger P through the surrounding environment recognition processing in the previous step S2, the determination processing unit 111B determines that there is a factor that causes the bicycle to tilt other than a change in course (YES in step S4). On the other hand, if the surrounding environment recognition processing does not recognize the luggage L or the passenger P, the determination processing unit 111B determines that there is no factor that causes the bicycle to tilt other than a change in course (NO in step S4).

[0140] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor.

[0141] Specifically, the angle threshold setting processing unit 111C sets the angle threshold for the side of the bicycle 20, either the right or left side in the direction of travel where the luggage L or passenger P is biased, to an angle (e.g., 20°) greater than the reference angle (e.g., 15°).

[0142] As described above, in the judgment process of step S4, one or more processors in the fifth embodiment determine whether there is a factor that would cause the bicycle 20 to tilt based on the state of the luggage L loaded on the bicycle 20 or the state of a passenger P other than the driver of the bicycle 20, and in the angle threshold setting process of step S5, set the angle threshold for either the right or left side of the direction of travel of the bicycle 20 to an angle greater than a predetermined reference angle.

[0143] According to the above aspect, the angle threshold for the right or left side of the bicycle 20 in the direction of travel, on the side toward which the luggage L or passenger P is leaning, is set to an angle greater than the reference angle. Therefore, even if the bicycle 20 tilts due to loss of balance caused by the luggage L or passenger P, the tilt angle θ is unlikely to exceed the angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that swaying of the bicycle 20 caused by the luggage L or passenger P is a course change, improving the determination accuracy of the prediction processing unit 111E.

[0144] Sixth Embodiment <Driving Assistance Method> Next, an example of a driving assistance method according to a sixth embodiment of the present disclosure will be described with reference to FIG. 6 .

[0145] (Step S4: Is there a factor that causes the bicycle to lean other than a lane change?) In step S4, the determination processing unit 111B determines whether or not there is a factor that causes the bicycle to lean other than a lane change. Specifically, in the determination process of step S4, the determination processing unit 111B determines that there is a factor that causes the bicycle 20 to lean if the speed of the bicycle 20 is not equal to or greater than the lower limit value and not equal to or less than the upper limit value of a predetermined reference speed range. The above-mentioned "lower limit value and upper limit value of the reference speed range" are threshold values ​​for determining whether or not there is a factor that causes the bicycle 20 to lean other than a lane change, and are predetermined specified values.

[0146] More specifically, the surrounding environment recognition processing unit 111A recognizes the bicycle 20 and calculates the traveling speed of the recognized bicycle 20 in the surrounding environment recognition processing of the previous step S2. Generally, a bicycle tends to lean even at a small angle as its speed increases, and also tends to lean more easily as its speed decreases due to reduced riding stability. Therefore, if the calculated traveling speed of the bicycle 20 is not equal to or greater than the lower limit nor equal to the upper limit of a predetermined reference speed range, the determination processing unit 111B determines that there is a factor that causes the bicycle 20 to lean other than a lane change (YES in step S4). On the other hand, if the calculated traveling speed of the bicycle 20 is equal to or greater than the lower limit nor equal to the upper limit of the reference speed range, the determination processing unit 111B determines that there is no factor that causes the bicycle 20 to lean other than a lane change (NO in step S4).

[0147] The method for calculating the travel speed of the recognized bicycle 20 is not limited to the method described in step S2 above, and any conventionally known technology may be used.

[0148] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor.

[0149] Generally, bicycles tend to turn more easily as the speed increases, even with a small tilt angle θ, and so may change course at a small tilt angle θ. On the other hand, bicycles tend to become unstable as the speed decreases, making them more likely to wobble. Therefore, the angle threshold setting processing unit 111C according to this embodiment sets the angle threshold to a reference angle θ when the calculated traveling speed of the bicycle 20 is faster than the upper limit of a predetermined reference speed range, in order to improve the detection accuracy of detecting tilt due to a change in course of the bicycle 20. ＲＢ , θ ＬＢ Angle θ smaller than Ａ , θ Ｂ On the other hand, when the calculated moving speed of the bicycle 20 is slower than the lower limit of a predetermined reference speed range, the angle threshold setting processing unit 111C sets the angle threshold to the reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Set to.

[0150] In the process of step S5, the angle threshold setting processing unit 111C sets the angle thresholds on the right and left sides of the bicycle 20 in the traveling direction to the angle θ Ａ , θ Ｂ That is, the angle threshold setting processing unit 111C may increase the angle threshold as the movement speed of the bicycle 20 increases, and may decrease the angle threshold as the movement speed of the bicycle 20 decreases.

[0151] As explained above, in the determination process of step S4, one or more processors according to the sixth embodiment determine that there is a factor causing the bicycle 20 to lean if the speed of the bicycle 20 is not equal to or greater than the lower limit value and equal to or less than the upper limit value of a predetermined reference speed range, and in the angle threshold setting process of step S5, if the speed of the bicycle 20 is faster than the upper limit value, set the angle threshold to a predetermined reference angle θ ＲＢ , θ ＬＢ Angle θ smaller than Ａ , θ Ｂ If the speed of the bicycle 20 is slower than the lower limit, the angle threshold is set to a predetermined reference angle θ ＲＢ , θ ＬＢ Angle θ greater thanＡ , θ Ｂ Set to.

[0152] According to the above aspect, when the traveling speed of the bicycle 20 is slower than the lower limit of the predetermined reference speed range, the angle threshold is set to the reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Therefore, even if the bicycle 20 leans, the lean angle θ is less likely to exceed the expanded angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that the swaying of the bicycle 20 caused by low speed is a course change, improving the judgment accuracy of the prediction processing unit 111E.

[0153] Furthermore, according to the above aspect, when the traveling speed of the bicycle 20 is faster than the upper limit of the predetermined reference speed range, the angle threshold is set to the reference angle θ ＲＢ , θ ＬＢ Angle θ smaller than Ａ , θ Ｂ Therefore, when the bicycle 20 leans due to a lane change, the lean angle θ is likely to exceed the angle threshold. As a result, the prediction processing unit 111E is able to predict the lean angle θ of the bicycle 20 from the predetermined reference angle θ ＲＢ , θ ＬＢ This improves the accuracy of detecting the tilt of the bicycle 20 that accompanies a change in course, compared to simply predicting that the bicycle will change course when the bicycle 20 exceeds this threshold.

[0154] In particular, in the sixth embodiment, the angle threshold is set to the reference angle θ ＲＢ , θ ＬＢ The angle threshold value after resetting is the angle θ Ａ , θ Ｂ As a result, the prediction processing unit 111E determines whether the tilt angle θ of the bicycle 20 is equal to the predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether the bicycle 20 will change course than by simply predicting that the bicycle 20 will change course when the speed exceeds 100 km / h.

[0155] Seventh Embodiment <Driving Assistance Method> Next, an example of a driving assistance method according to a seventh embodiment of the present disclosure will be described with reference to FIG. 6 .

[0156] (Step S4: Are there any factors that cause the bicycle 20 to lean other than a change in lane?) In step S4, the determination processing unit 111B determines whether there are any factors that cause the bicycle 20 to lean other than a change in lane. Specifically, in the determination processing of step S4, the determination processing unit 111B determines whether there are any factors that cause the bicycle 20 to lean based on the movement of the rider of the bicycle 20 or the posture of the rider of the bicycle 20. More specifically, the processing device 111 executes, for example, process 13 or 14 below.

[0157] (Process 13) The surrounding environment recognition processing unit 111A recognizes the bicycle 20 through the surrounding environment recognition processing in the previous step S2. The determination processing unit 111B determines whether the rider of the bicycle 20 is performing an action other than driving based on image data of the bicycle 20.

[0158] 20 is a schematic diagram showing a bicycle 20 in which the rider is distracted while holding a smartphone. If the determination processing unit 111B determines that the rider of the bicycle 20 is performing an action other than driving, it determines that there is a factor causing the bicycle to lean other than a change in lane (YES in step S4). Specifically, for example, if the rider of the bicycle 20 is holding a smartphone in one hand and gripping the handlebars with the other while looking away, as shown in FIG. 21, the rider's steering of the handlebars becomes unstable, making the bicycle 20 more likely to wobble. Therefore, if the rider is performing an action other than driving as shown in FIG. 21, the determination processing unit 111B determines that there is a factor causing the bicycle to lean other than a change in lane.

[0159] On the other hand, if the determination processing unit 111B determines that the rider of the bicycle 20 is not performing an action other than driving, it determines that there is no factor that would cause the bicycle to lean other than changing course (NO in step S4). Note that the method for determining whether the rider of the bicycle 20 is performing an action other than driving is not limited to the above method, and any conventionally known technology may be used.

[0160] (Process 14) Figure 21 is a diagram showing a bicycle 20 in which the rider is leaning backward. The surrounding environment recognition processing unit 111A recognizes the bicycle 20 through the surrounding environment recognition processing of the previous step S2. The determination processing unit 111B estimates the riding posture of the rider of the bicycle 20 based on image data of the bicycle 20.

[0161] If the estimated driving posture is not the correct posture, the determination processing unit 111B determines that there is a factor that causes the bicycle to lean other than changing course (YES in step S4). Specifically, for example, if the rider of bicycle 20 leans excessively backward with the saddle positioned low as shown in Figure 22, the determination processing unit 111B determines that there is a factor that causes the bicycle to lean other than changing course. On the other hand, if the estimated driving posture is the correct posture, the determination processing unit 111B determines that there is no factor that causes the bicycle to lean other than changing course (YES in step S4).

[0162] The above-mentioned "proper posture" means, for example, a posture in which the rider's gaze and knees are facing the direction of travel while sitting on the saddle, the rider's hands gripping the handlebars are positioned vertically below the shoulders, and the rider's waist is positioned vertically above the head tube of the bicycle from the road surface.

[0163] The method for estimating the riding posture of the rider of the bicycle 20 is not limited to the above method, and any conventionally known technology may be used.

[0164] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor.

[0165] Specifically, when it is determined that the behavior of the rider of the bicycle 20 is different from that of driving, or when it is determined that the riding posture of the rider is not proper, the angle threshold setting processing unit 111C sets the angle thresholds on the right and left sides of the bicycle 20 in the traveling direction to the reference angle θ ＲＢ , θ ＬＢ An angle θ greater than (for example, 15°) Ａ , θ Ｂ(for example, 30°).

[0166] As explained above, in the determination process of step S4, one or more processors according to the seventh embodiment determine whether there is a factor that causes the bicycle 20 to lean based on the movement or posture of the rider of the bicycle 20, and in the angle threshold setting process of step S5, set the angle threshold to a predetermined reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Set to.

[0167] According to the above aspect, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Therefore, even if the bicycle 20 leans, the lean angle θ is unlikely to exceed the angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that the swaying of the bicycle 20 caused by the rider's movement or riding posture is a course change. Therefore, the prediction processing unit 111E sets the lean angle θ of the bicycle 20 at a predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether or not the bicycle 20 will change course, rather than simply predicting that the bicycle 20 will change course if the speed exceeds this threshold.

[0168] Eighth Embodiment <Driving Assistance Method> Next, an example of a driving assistance method according to an eighth embodiment of the present disclosure will be described with reference to FIG. 6 .

[0169] (Step S4: Are there any factors that cause the bicycle 20 to lean other than a change in course?) In step S4, the determination processing unit 111B determines whether there are any factors that cause the bicycle 20 to lean other than a change in course. Specifically, in the determination processing of step S4, the determination processing unit 111B estimates the driving ability of the rider of the bicycle 20, and determines whether there are any factors that cause the bicycle 20 to lean based on the estimated driving ability.

[0170] More specifically, for example, the surrounding environment recognition processing unit 111A recognizes the rider of the bicycle 20 through the surrounding environment recognition processing in the previous step S2. The determination processing unit 111B estimates the approximate age of the rider of the bicycle 20 from the rider's appearance, etc., by processing image data of the rider.

[0171] For example, the judgment processing unit 111B may detect the face of the rider of the bicycle 20 from image data captured of the rider, and estimate the rider's age by applying the detected face data to a pre-trained face detection model (e.g., MTCNN (Multi-task Cascaded Convolutional Neural Networks for Face Detection, based on TensorFlow) or DSFD (Dual Shot Face Detector)).

[0172] Generally, if the bicycle driver is elderly, the driver's poor driving ability may cause the bicycle to sway even without changing course. Therefore, if the estimated age is equal to or greater than a predetermined threshold, the determination processing unit 111B according to this embodiment determines that the driver of the bicycle 20 has poor driving ability and that there is a factor causing the bicycle to lean other than changing course (YES in step S4). On the other hand, if the estimated age is less than the predetermined threshold, the determination processing unit 111B determines that the driver of the bicycle 20 does not have poor driving ability and that there is no factor causing the bicycle to lean other than changing course (NO in step S4).

[0173] The method for estimating the driving ability of the rider of the bicycle 20 is not particularly limited, and any conventionally known method may be used.

[0174] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor.

[0175] Specifically, if the driving ability of the rider of the bicycle 20 is determined to be low, the angle threshold setting processing unit 111C sets the angle thresholds on the right and left sides of the bicycle 20 in the traveling direction relative to the reference angle θＲＢ , θ ＬＢ An angle θ greater than (for example, 15°) Ａ , θ Ｂ (for example, 30°).

[0176] As explained above, in the determination process of step S4, one or more processors according to the eighth embodiment estimate the driving ability of the rider of the bicycle 20, and determine whether there is a factor that causes the bicycle 20 to lean other than a change in course based on the estimated driving ability. In the setting process of step S5, the angle threshold is set to a predetermined reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Set to.

[0177] According to the above aspect, the angle threshold is the reference angle θ ＲＢ , θ ＬＢ Angle θ greater than Ａ , θ Ｂ Therefore, even if the bicycle 20 leans, the tilt angle θ is less likely to exceed the expanded angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting that the swaying of the bicycle 20 caused by the driver's driving ability is a course change. Therefore, the prediction processing unit 111E sets the tilt angle θ of the bicycle 20 to a predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether or not the bicycle 20 will change course, rather than simply predicting that the bicycle 20 will change course if the speed exceeds this threshold.

[0178] 2. Modifications Although the embodiments of the present disclosure have been described above, the present disclosure is not limited to the above embodiments and various modifications may be made. Specific modifications that may be made to the above embodiments are exemplified below. For example, the sixth embodiment described above may be modified to the extent that the modifications are not inconsistent with the following exemplary modifications.

[0179] [Modification of Sixth Embodiment] <Driving Assistance Method> Next, an example of a driving assistance method according to a modification of the sixth embodiment of the present disclosure will be described with reference to Fig. 6. In the description of the driving assistance method according to the modification described below, the same components and steps as those in the above embodiment will be denoted by the same reference numerals, and description thereof will be omitted.

[0180] (Step S4: Are there any factors that could cause the bicycle 20 to lean other than a change in course?) Figure 22 is a diagram that shows a bicycle 20 loaded with luggage L, and Figure 23 is a diagram that shows a bicycle 20 with a passenger P on board. In step S4, the determination processing unit 111B determines whether or not there is a factor that could cause the bicycle 20 to lean other than a change in course. Specifically, in the determination processing of step S4, the determination processing unit 111B determines whether or not there is a factor that could cause the bicycle 20 to lean based on the state of the luggage L loaded on the bicycle 20 or the state of the passenger P who is different from the driver of the bicycle 20. More specifically, the processing device 111 executes, for example, process 15 or 16 described below.

[0181] (Process 15) The surrounding environment recognition processing unit 111A recognizes the bicycle 20 carrying luggage L through the surrounding environment recognition processing of the previous step S2. The determination processing unit 111B measures the width and height of the bicycle 20 based on image data of the bicycle 20, and estimates the center of gravity position G1 of the bicycle 20 from the center positions of the width and height. Similarly, the determination processing unit 111B measures the width and height of the luggage L based on the image data, and estimates the center of gravity position G2 of the luggage L from the center positions of the width and height.

[0182] Next, if the estimated center of gravity position G1 of the bicycle 20 and the estimated center of gravity position G2 of the luggage L are eccentric, the determination processing unit 111B determines that there is a factor causing the bicycle to tilt other than a change in course (YES in step S4). On the other hand, if the estimated center of gravity position G1 of the bicycle 20 and the estimated center of gravity position G2 of the luggage L are not eccentric, the determination processing unit 111B determines that there is no factor causing the bicycle to tilt other than a change in course (NO in step S4). The above "eccentricity" means that the center of gravity position G1 of the bicycle 20 and the center of gravity position G2 of the luggage L do not coincide and are not located on the same straight line.

[0183] (Process 16) The surrounding environment recognition processing unit 111A recognizes the bicycle 20 ridden by the passenger P through the surrounding environment recognition processing in the previous step S2. The determination processing unit 111B measures the width and height of the bicycle 20 based on image data of the bicycle 20, and estimates the center of gravity position G1 of the bicycle 20 from the center positions of the width and height. Similarly, the determination processing unit 111B measures the width and height of the passenger P based on the image data, and estimates the center of gravity position G2 of the passenger P from the center positions of the width and height.

[0184] Next, if the estimated center of gravity position G1 of the bicycle 20 and the estimated center of gravity position G2 of the passenger P are eccentric, the determination processing unit 111B determines that there is a factor causing the bicycle to tilt other than a change in course (YES in step S4).On the other hand, if the estimated center of gravity position G1 of the bicycle 20 and the estimated center of gravity position G2 of the passenger P are not eccentric, the determination processing unit 111B determines that there is no factor causing the bicycle to tilt other than a change in course (NO in step S4).

[0185] The method for estimating the center of gravity G1 of the bicycle 20 and the center of gravity G2 of the luggage L and passenger P is not limited to the above method, and any conventionally known technology may be used.

[0186] (Step S5: Angle Threshold Setting Process) In step S5, if it is determined in the previous determination process of step S4 that there is a factor that causes the bicycle 20 to lean, the angle threshold setting processor 111C sets an angle threshold based on that factor.

[0187] Specifically, if the estimated center of gravity position G1 of the bicycle 20 and the estimated center of gravity position G2 of the baggage L or passenger P are eccentric, the angle threshold setting processor 111C sets the angle threshold for the side of the bicycle 20, either the right or left side in the direction of travel toward which the center of gravity position G2 is eccentric, to an angle greater than the reference angle. More specifically, the angle threshold setting processor 111C executes, for example, process 17 or 18 described below.

[0188] (Process 17) When the center of gravity G2 of the luggage L is shifted to the left side of the center of gravity G1 of the bicycle 20 in the traveling direction as shown in FIG. 22, the angle threshold setting processing unit 111C sets the angle threshold on the right side of the traveling direction of the bicycle 20 as shown in the same figure, using the reference angle θ ＲＢ (for example, 15°), and the angle threshold on the left side of the bicycle 20 in the traveling direction is set to the reference angle θ ＬＢ An angle θ greater than (for example, 15°) Ｂ (for example, 20°).

[0189] (Process 18) When the center of gravity G2 of the passenger P is shifted to the right side of the center of gravity G1 of the bicycle 20 in the traveling direction as shown in FIG. 23, the angle threshold setting processing unit 111C sets the angle threshold on the left side of the traveling direction of the bicycle 20 to the reference angle θ ＬＢ (for example, 15°), and the angle threshold on the right side of the bicycle 20 in the traveling direction is set to the reference angle θ ＲＢ An angle θ greater than (for example, 15°) Ａ (for example, 20°).

[0190] In the processing of step S5, the angle threshold setting processing unit 111C may set the angle threshold for the side of the bicycle 20, either the right or left side in the traveling direction to which the center of gravity position G2 is biased, to an angle corresponding to the difference ΔG between the center of gravity positions G1 and G2. In other words, the angle threshold setting processing unit 111C may set the angle threshold uniformly or variably according to the difference ΔG.

[0191] As described above, in the judgment process of step S4, one or more processors according to the modified example of the present disclosure determine whether there is a factor that would cause the bicycle 20 to tilt based on the state of the luggage L loaded on the bicycle 20 or the state of a passenger P other than the driver of the bicycle 20, and in the angle threshold setting process of step S5, set the angle threshold for either the right or left side of the direction of travel of the bicycle 20 to an angle greater than a predetermined reference angle.

[0192] According to the above aspect, the angle threshold for the side of the bicycle 20 to which the center of gravity G2 is biased, either to the right or left side in the direction of travel, is set to an angle greater than the reference angle. Therefore, even if the bicycle 20 leans to the side to which the center of gravity G2 is biased, the tilt angle θ is unlikely to exceed the angle threshold. This prevents the prediction processing unit 111E from mistakenly predicting a sway of the bicycle 20 caused by luggage L or passenger P as a course change, improving the judgment accuracy of the prediction processing unit 111E.

[0193] In particular, in the fifth embodiment, the angle threshold is reset from the reference angle, and the reset angle threshold becomes an angle that matches the difference ΔG between the center of gravity G1 of the bicycle 20 and the center of gravity G2 of the luggage L or the passenger P. As a result, the prediction processing unit 111E determines whether the tilt angle θ of the bicycle 20 is equal to the predetermined reference angle θ ＲＢ , θ ＬＢ This makes it possible to more accurately predict whether the bicycle 20 will change course than by simply predicting that the bicycle 20 will change course when the speed exceeds 100 km / h.

[0194] 3. Supplementary Note: The driving assistance device and driving assistance method exemplified in the above embodiment are typically applied to passenger cars, but the driving assistance device and driving assistance method of the present disclosure may also be applied to moving bodies other than passenger cars, and the applications of the present disclosure are not particularly limited.

[0195] Furthermore, the effects described herein are merely descriptive or exemplary and are not limiting. That is, the present invention may exhibit other effects in addition to or in place of the above-described effects that would be apparent to a person skilled in the art from the description of this specification.

[0196] Although the preferred embodiments of the present disclosure have been described in detail above with reference to the accompanying drawings, the technology of the present disclosure is not limited to the above embodiments. It is clear that a person skilled in the art of the technology to which the present disclosure pertains can conceive of various modified or altered examples within the scope of the technical ideas described in the claims, and it is understood that these also naturally fall within the technical scope of the present disclosure.

[0197] For example, some of the functions of the driving assistance device exemplified in the above embodiment may be provided in another device. Specifically, for example, some or all of the steps (steps S1 to S13) in the driving assistance method of the present disclosure may be executed by an information processing device (e.g., a cloud server) that is communicably connected to the assisted vehicle via a communication network.

[0198] In the above embodiment, the driving assistance device is an electronic control device mounted on a vehicle, but the technology of the present disclosure is not limited to this example. For example, the driving assistance device may be a mobile terminal configured to be able to communicate with a device other than the vehicle and to issue drive commands to any display device. Examples of such a mobile terminal include a laptop computer, a mobile phone, a smartphone, and a tablet terminal.

[0199] Furthermore, the technology of the present disclosure can also be realized as a vehicle equipped with the driving assistance device described in the above embodiment, a driving assistance method using the driving assistance device, a computer program that causes a computer to function as the above driving assistance device, and a non-transitory tangible recording medium on which the computer program is recorded.

[0200] 10: Vehicle to be assisted 11: Driving assistance device 12: Surrounding environment recognition device 20: Bicycle ridden by driver 21: Vehicle control unit

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 a tilt angle calculation process for calculating the tilt angle of the bicycle with respect to the vertical direction recognized by a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; a prediction process for predicting that the bicycle will change course when the tilt angle calculated by the tilt angle calculation process exceeds a predetermined angle threshold; a determination process for determining whether there is a factor other than a change in course that may cause the bicycle to tilt; an angle threshold setting process that sets the angle threshold for determining whether the course change in the direction in which the bicycle will lean due to the factor to an angle greater than a predetermined reference angle based on the factor if the determination process determines that there is a factor that will cause the bicycle to lean; A driving assistance device that performs the following:

2. the one or more processors In the determination process, if the height of the protrusion on the road surface is equal to or greater than a predetermined height, it is determined that there is a factor that may cause the bicycle to tilt, The driving assistance device according to claim 1 , wherein in the angle threshold value setting process, an angle obtained by adding a first angle to the predetermined reference angle is set as the angle threshold value.

3. the one or more processors In the determination process, if the road surface is an inclined surface that is inclined at a predetermined angle or more in the width direction of the vehicle, it is determined that there is a factor that causes the bicycle to lean, 2. The driving assistance device according to claim 1, wherein the angle threshold setting process sets the angle threshold for the slope side of the slope above the contact point between the bicycle and the slope to an angle greater than the predetermined reference angle.

4. the one or more processors In the determination process, if the road surface is an uphill slope that inclines at a predetermined angle or more in the direction of travel of the bicycle, it is determined that there is a factor that may cause the bicycle to lean, The driving assistance device according to claim 1 , wherein in the angle threshold value setting process, an angle obtained by adding a second angle to the predetermined reference angle is set as the angle threshold value.

5. the one or more processors In the determination process, it is determined whether there is a factor that may cause the bicycle to tilt based on wind conditions, The driving assistance device according to claim 1 , wherein the angle threshold value setting process sets the downwind angle threshold value to an angle greater than the predetermined reference angle.

6. the one or more processors In the determination process, it is determined whether there is a factor that may cause the bicycle to tilt based on the amount of rainfall; The driving assistance device according to claim 1 , wherein the angle threshold value is set to an angle greater than the predetermined reference angle in the angle threshold value setting process.

7. the one or more processors In the determination process, it is determined whether there is a factor that causes the bicycle to tilt based on the presence or absence of luggage loaded on the bicycle or a passenger other than the bicycle driver, The driving assistance device according to claim 1 , wherein the angle threshold value is set to an angle greater than the predetermined reference angle in the angle threshold value setting process.

8. the one or more processors In the determination process, the driving ability of the bicycle rider is estimated, and based on the estimated driving ability, it is determined whether there is a factor that causes the bicycle to lean; The driving assistance device according to claim 1 , wherein the angle threshold value is set to a value greater than the predetermined reference angle in the angle threshold value setting process.

9. the one or more processors In the determination process, if the bicycle speed is not equal to or greater than the lower limit value and not equal to or less than the upper limit value of a predetermined reference speed range, it is determined that there is a factor that causes the bicycle to lean, 2. The driving assistance device according to claim 1, wherein, in the angle threshold setting process, if the speed of the bicycle is slower than the lower limit, the angle threshold is set to an angle greater than the predetermined reference angle.

10. 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 a tilt angle calculation process for calculating the tilt angle of the bicycle with respect to the vertical direction recognized by a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; a prediction process for predicting that the bicycle will change course when the tilt angle calculated by the tilt angle calculation process exceeds a predetermined angle threshold; a determination process for determining whether there is a factor other than a change in course that may cause the bicycle to tilt; an angle threshold setting process that sets the angle threshold for determining whether or not a course change in the direction opposite to the direction in which the bicycle will lean due to the factor to an angle smaller than a predetermined reference angle, based on the factor, if the determination process determines that there is a factor that will cause the bicycle to lean; A driving assistance device that performs the following:

11. The one or more processors: In the determination process, if the road surface is an inclined surface that is inclined at a predetermined angle or more in the width direction of the vehicle, it is determined that there is a factor that causes the bicycle to lean, 11. The driving assistance device according to claim 10, wherein the angle threshold setting process sets the angle threshold on the slope side below the contact point between the bicycle and the slope to an angle smaller than the predetermined reference angle.

12. The one or more processors: In the determination process, if the road surface is a downhill slope that slopes in the direction of travel of the bicycle by a predetermined angle or more, it is determined that there is a factor that causes the bicycle to lean, The driving assistance device according to claim 10 , wherein in the angle threshold value setting process, an angle obtained by subtracting a third angle from the predetermined reference angle is set as the angle threshold value.

13. The one or more processors: In the determination process, it is determined whether there is a factor that may cause the bicycle to tilt based on wind conditions, The driving assistance device according to claim 10 , wherein in the angle threshold setting process, the windward angle threshold is set to the predetermined reference angle or to an angle smaller than the reference angle.

14. The one or more processors: In the determination process, if the bicycle speed is not equal to or greater than the lower limit value and not equal to or less than the upper limit value of a predetermined reference speed range, it is determined that there is a factor that causes the bicycle to lean, The driving assistance device according to claim 10 , wherein, in the angle threshold setting process, when the speed of the bicycle is faster than the upper limit, the angle threshold is set to an angle smaller than the predetermined reference angle.

15. one or more processors Calculating the inclination angle of the bicycle relative to the vertical direction as recognized by a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; predicting that the bicycle will make a lane change if the lean angle exceeds a predetermined angle threshold; determining whether there is a factor other than a change in course that may cause the bicycle to lean; If it is determined that there is a factor that causes the bicycle to lean, based on the factor, the angle threshold for determining whether or not the course change will be in a direction that causes the bicycle to lean due to the factor is set to an angle greater than a predetermined reference angle. A driving assistance method comprising:

16. One or more processors: Calculating the inclination angle of the bicycle relative to the vertical direction as recognized by a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; predicting that the bicycle will make a lane change if the lean angle exceeds a predetermined angle threshold; determining whether there is a factor other than a change in course that may cause the bicycle to lean; If it is determined that there is a factor that causes the bicycle to lean, based on the factor, the angle threshold for determining whether or not the course change is to be made in the opposite direction to the direction in which the bicycle leans due to the factor is set to an angle smaller than a predetermined reference angle. A driving assistance method comprising:

17. Calculating the inclination angle of the bicycle relative to the vertical direction as recognized by a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; predicting that the bicycle will make a lane change when the lean angle exceeds a predetermined angle threshold; Determining whether there is a factor other than a change in course that causes the bicycle to lean; If it is determined that there is a factor that will cause the bicycle to lean, the angle threshold for determining whether the course change will be in a direction that will cause the bicycle to lean due to the factor is set to an angle greater than a predetermined reference angle based on the factor. A non-transitory tangible recording medium on which a computer program is recorded that causes a processor to perform processes including the above.

18. Calculating the inclination angle of the bicycle relative to the vertical direction recognized by a surrounding environment recognition device that recognizes the surrounding environment of the vehicle; predicting that the bicycle will make a lane change when the lean angle exceeds a predetermined angle threshold; Determining whether there is a factor other than a change in course that causes the bicycle to lean; If it is determined that there is a factor that causes the bicycle to lean, the angle threshold for determining whether the course change should be made in the opposite direction to the direction in which the bicycle would lean due to the factor is set to an angle smaller than a predetermined reference angle based on the factor. A non-transitory tangible recording medium on which a computer program is recorded that causes a processor to perform processes including the above.