Yaw rate estimation device

Abstract

This invention provides a yaw rate estimation device that can accurately estimate the yaw rate of a vehicle's yaw motion, which varies over time. The yaw rate estimation device includes: an information acquisition unit that acquires information about a forward image and vehicle speed; a lane recognition unit that identifies a driving lane and its curvature drawn on the vehicle's driving path based on the forward image information; a direction change rate calculation unit that calculates the rate of change of the driving lane's direction based on the curvature of the driving lane and vehicle speed information; a yaw rate change rate calculation unit that calculates the rate of change of the vehicle's yaw angle relative to the driving lane's direction based on the curvature of the driving lane and vehicle speed information; and a lane yaw rate estimation unit that estimates the lane yaw rate based on the rate of change of the driving lane's direction and the rate of change of the vehicle's yaw angle relative to the driving lane's direction, and uses the estimated lane yaw rate as the vehicle's yaw rate.

Description

Technical Field

[0001] This invention relates to a yaw rate estimation device for estimating the yaw rate of a vehicle. Background Technology

[0002] Previously, there were known yaw rate estimation devices mounted on vehicles for estimating the yaw rate of the vehicle (see Patent Document 1).

[0003] The yaw rate estimation device in Patent Document 1 includes a yaw rate sensor for detecting the yaw rate of the vehicle and an image capture unit for capturing an image of the front of the vehicle. Based on the image of the front of the vehicle captured by the image capture unit, it determines whether the vehicle is traveling straight. If it is determined that the vehicle is traveling straight, the output value of the yaw rate sensor is set to zero.

[0004] According to the yaw rate inference device in Patent Document 1, the zero-point calibration of the output value (yaw rate) of the yaw rate sensor can be performed even during driving.

[0005] Existing technical documents

[0006] Patent documents

[0007] Patent Document 1: JP Japanese Patent Application Publication No. 2006-199242 Summary of the Invention

[0008] However, in the yaw rate estimation device of Patent Document 1, it is assumed that the target driving path of the vehicle is determined based on the image in front of the vehicle, the vehicle drives along the estimated target driving path, and the yaw rate of the vehicle is estimated based on the yaw angle and driving speed at a future time point (after a predetermined time has passed from the present) under this assumption (see paragraphs 0022-0025 of Patent Document 1).

[0009] Therefore, in the yaw rate estimation device of Patent Document 1, the yaw rate at a future point in time can be estimated, but the current yaw rate cannot be estimated. In addition, if the above-mentioned assumption that the vehicle travels along the estimated target driving path is not valid, it is not possible to estimate the yaw rate of the vehicle's yaw motion (hereinafter referred to as "yaw motion") which reflects the change in time with high accuracy.

[0010] The present invention was proposed to solve the above-mentioned problems, and its purpose is to provide a yaw rate estimation device that can accurately estimate the yaw rate of a vehicle that reflects the yaw motion of the vehicle at any given time.

[0011] To achieve the above objectives, the most important feature of the invention (1) is that it comprises: an information acquisition unit that acquires information about the front image of the vehicle and information about the vehicle speed; a lane recognition unit that identifies a driving lane drawn on the vehicle's driving path and the curvature of the driving lane based on the acquired information about the front image of the vehicle; a direction change rate calculation unit that calculates the direction change rate of the driving lane in the vehicle's reference coordinates based on the identified curvature of the driving lane and the acquired vehicle speed information; and a yaw angle change rate calculation unit that calculates the yaw angle change rate based on the identified curvature of the driving lane and the acquired information about the vehicle speed. The system calculates the rate of change of the vehicle's yaw angle relative to the direction of the driving lane in the reference coordinates of the vehicle, based on the rate of change of the direction of the driving lane calculated by the rate of change of direction calculation unit and the rate of change of the vehicle's yaw angle relative to the direction of the driving lane calculated by the yaw angle rate of change calculation unit. The system infers the lane yaw rate, which is a yaw rate derived from the curvature of the driving lane and the vehicle's speed information. The system uses the inferred lane yaw rate as the vehicle's yaw rate.

[0012] According to the invention of (1), the yaw rate of the lane is inferred based on the curvature of the driving lane drawn on the driving path of the vehicle and the vehicle speed. The inferred yaw rate of the lane is used as the yaw rate of the vehicle. Therefore, the yaw rate of the vehicle's yaw motion, which reflects the change of time, can be inferred with high accuracy.

[0013] Invention Effects

[0014] According to the present invention, the yaw rate of the vehicle's yaw motion, which reflects the change of time, can be calculated with high accuracy. Attached Figure Description

[0015] Figure 1 This is an overall structural diagram of an autonomous vehicle equipped with the vehicle control device of the present invention, which has a yaw rate inference device.

[0016] Figure 2 This is a functional block diagram showing the configuration of a vehicle control device with a yaw rate estimation device according to the present invention and its peripheral parts.

[0017] Figure 3 This is a schematic diagram of the HMI (Human Interface) of a vehicle control unit.

[0018] Figure 4 This is a diagram showing the front structure of the cabin of an autonomous vehicle.

[0019] Figure 5This is a block diagram conceptually representing the lane yaw rate estimation function of the yaw rate estimation device of the present invention.

[0020] Figure 6 This is a top view of the vehicle, which provides a summary description of the yaw rate estimation device used in this invention.

[0021] Figure 7 This is a functional block diagram showing the general configuration of the yaw rate estimation device in the first modified example.

[0022] Figure 8 The figure is a comparison of the input signal waveform and the output signal waveform of the low-pass filter (LPF) of the yaw rate estimation device in the first variation.

[0023] Figure 9A This is a functional block diagram showing the general configuration of the yaw rate estimation device in the second variation.

[0024] Figure 9B The figure shows a comparison of the frequency characteristics of the lane yaw rate and the filter gain related to the detection yaw rate with the complementary filter of the yaw rate in the second variation and the complementary filter of the yaw rate in the yaw rate inference device.

[0025] Figure 10A This is a functional block diagram showing the general configuration of the yaw rate estimation device in the third variation.

[0026] Figure 10B This is a diagram showing the lane length-gain characteristics of the judgment unit of the yaw rate estimation device in the third variation.

[0027] The reference numerals in the attached figures are explained as follows:

[0028] 30 Vehicle sensors (yaw rate sensor)

[0029] 300 The yaw rate estimation device of the present invention

[0030] 311 Information Acquisition Department

[0031] Lane Recognition Unit 313

[0032] 315 Calculation of Directional Change Rate

[0033] 317 Calculation of the rate of change of yaw angle

[0034] 319 Lane Yaw Rate Inference Unit

[0035] 320 Yaw rate estimation device of the first variation

[0036] 325 Low-pass filter

[0037] 327 Blind Spot Handling Department

[0038] 340 Yaw rate estimation device of the second variation

[0039] 343 Complementary Filter Section (Synthetic Yaw Velocity Generation Section)

[0040] 345 Integration Unit (Comprehensive Yaw Rate Generation Unit)

[0041] 360 Yaw rate estimation device of the third variation

[0042] 361 Judgment Department

[0043] 363 Integrated Yaw Rate Generator

[0044] YRsr detects yaw rate

[0045] YRln Lane yaw rate

[0046] YRfs Combined Yaw Rate Detailed Implementation

[0047] Hereinafter, the yaw rate estimation device according to embodiments of the present invention will be described in detail with reference to the accompanying drawings.

[0048] Furthermore, in the accompanying drawings shown below, components with the same function are labeled with the same reference numerals. Additionally, for ease of explanation, the dimensions and shapes of components are sometimes depicted schematically in a distorted or exaggerated manner.

[0049] In the description of the autonomous vehicle (hereinafter, sometimes referred to as "the vehicle" or "the car") 1 equipped with the vehicle control device 100 having the yaw rate estimation device 300 of the present invention, when the vehicle 1 is referred to as left or right, the direction in which the vehicle 1 travels is forward is taken as the reference. Specifically, for example, when the vehicle 1 is a right-hand drive configuration, the driver's side is referred to as the right side and the passenger side is referred to as the left side.

[0050] [Composition of the autonomous vehicle (this vehicle) 1]

[0051] First, refer to Figure 1 The configuration of an autonomous vehicle (this vehicle) 1 equipped with a vehicle control device 100 having a yaw rate estimation device 300 according to the present invention is described.

[0052] Figure 1 This is an overall structural diagram of an autonomous vehicle (this vehicle) 1 equipped with a vehicle control device 100 having a yaw rate estimation device 300 according to the present invention.

[0053] The vehicle 1 equipped with the vehicle control device 100 having the yaw rate estimation device 300 of the present invention is as follows: Figure 1 As shown, for example, a car with two wheels, three wheels, or four wheels.

[0054] This vehicle 1 includes automobiles powered by internal combustion engines such as diesel / gasoline engines, electric vehicles powered by electric motors, and hybrid vehicles that combine internal combustion engines and electric motors. Among them, electric vehicles are driven by electricity discharged from batteries such as secondary batteries, hydrogen fuel cells, metal fuel cells, and alcohol fuel cells.

[0055] like Figure 1 As shown, the vehicle 1 is equipped with an external sensor 10 that has the function of detecting external information related to objects or signs existing around the vehicle 1, a navigation device 20 that has the function of mapping the current position of the vehicle 1 onto a map and providing route guidance to the destination, and a vehicle control device 100 that has the function of autonomous driving control of the vehicle 1, including maneuvering / accelerating / decelerating the vehicle 1.

[0056] These devices or machines are configured to communicate with each other via communication media such as CAN (Controller Area Network).

[0057] [External Sensor 10]

[0058] The external sensor 10 consists of a camera (or camera) 11, a radar 13, and a lidar 15.

[0059] The camera 11 has an optical axis that is angled downwards and forwards the vehicle, and is capable of capturing images of the vehicle 1 in its direction of travel. For example, a CMOS (Complementary Metal Oxide Semiconductor) camera or a CCD (Charge Coupled Device) camera can be appropriately used as the camera 11. The camera 11 is located near the rearview mirror (not shown) inside the vehicle 1, and outside the vehicle 1, at the front of the right / left door, etc.

[0060] Camera 11 periodically and repeatedly captures images of the surroundings of the vehicle 1, specifically the areas in front, to the left and right, and behind in the direction of travel. In this embodiment, a pair of SLR cameras are arranged side-by-side near the rearview mirror. Camera 11 can also be a video camera.

[0061] The image information of the vehicle 1 in front of, to the left and right sides of, and behind in the direction of travel captured by the camera 11 is sent to the vehicle control device 100 via the communication medium.

[0062] Radar 13 has the following functions: it illuminates radar waves at targets, including vehicles ahead that are being followed and are traveling in front of vehicle 1; and it receives radar waves reflected from the targets to obtain information about the distribution of targets, including the distance to the target or the orientation of the target. The radar waves can appropriately utilize lasers, microwaves, millimeter waves, ultrasonic waves, etc.

[0063] In this embodiment, radar 13, as Figure 1 As shown, there are three targets on the front and two on the rear, for a total of five. The distribution information of the targets based on radar 13 is transmitted to the vehicle control device 100 via a communication medium.

[0064] The LiDAR 15 (Light Detection and Ranging) has, for example, the function of detecting the presence or absence of an object and the distance to the object by measuring the time required to detect the scattered light relative to the illuminating light. In this embodiment, the LiDAR 15, as... Figure 1 As shown, there are three on the front and two on the rear, for a total of five. The distribution information of the targets based on the lidar 15 is transmitted to the vehicle control device 100 via a communication medium.

[0065] [Navigation device 20]

[0066] The navigation device 20 includes a GNSS (Global Navigation Satellite System) receiver, map information (navigation map), an internal touch panel-type display device 61 that functions as a human-computer interaction interface, and a speaker 63 (all referenced). Figure 3 It is composed of a GNSS receiver, a microphone, etc. The navigation device 20 uses the GNSS receiver to infer the current position of the vehicle 1 and derives the path from the current position to the destination specified by the user.

[0067] The path derived by the navigation device 20 is provided to the target driving lane determination unit 110 of the vehicle control device 100 (described later). The current position of the vehicle 1 can also be determined using the vehicle sensor 30 (see...). Figure 2 The output of the navigation device 20 is specific to or supplements the INS (Inertial Navigation System). Additionally, when the vehicle control device 100 is in manual driving mode, the navigation device 20 provides guidance on the route to the destination using sound or map display.

[0068] Furthermore, the function for determining the current location of vehicle 1 can be set independently of the navigation device 20. Additionally, the navigation device 20 can be implemented, for example, through the functions of a user-held smartphone or tablet. In this case, information is transmitted and received between the terminal device and the vehicle control device 100 using wireless or wired communication.

[0069] [A vehicle control unit 100 having a yaw rate estimation device 300 and its surrounding parts are configured.]

[0070] Next, refer to Figure 2 The vehicle control device 100, which is equipped with the yaw rate estimation device 300 according to an embodiment of the present invention, and its peripheral components are described.

[0071] Figure 2 This is a functional block diagram illustrating the configuration of a vehicle control device 100 having a yaw rate estimation device 300 according to an embodiment of the present invention and its peripheral parts.

[0072] like Figure 2 As shown, in this vehicle 1, in addition to the aforementioned external sensor 10, navigation device 20, and vehicle control device 100, it is also equipped with a communication device 25, vehicle sensor 30, HMI (Human Machine Interface) 35, driving force output device 200, steering device 210, and braking device 220.

[0073] The communication device 25, vehicle sensor 30, HMI 35, driving force output device 200, steering device 210, and braking device 220 are configured to be connected to the vehicle control device 100 via a communication medium for data communication.

[0074] [Communication device 25]

[0075] The communication device 25 has, for example, the ability to communicate via wireless communication media such as cellular networks, Wi-Fi networks, Bluetooth, and DSRC (Dedicated Short Range Communication).

[0076] The communication device 25 wirelessly communicates with a server providing information about a system that monitors road traffic conditions, such as a VICS (Vehicle Information and Communication System, VICS being a registered trademark), allowing the vehicle 1 to acquire traffic information indicating the traffic conditions of the road during its journey or on a predetermined route. This traffic information includes information about traffic jams ahead, the time required to pass through traffic jams, accident / disruption / construction information, speed limits / lane restrictions, parking lot locations, and information on the full / empty status of parking lots / service areas / parking zones.

[0077] The communication device 25 can obtain the traffic information by communicating with wireless beacons located on the side of the road or by vehicle-to-vehicle communication with other vehicles traveling around the vehicle 1.

[0078] Additionally, the communication device 25 wirelessly communicates with, for example, a traffic signal prediction system (TSPS) information provider server to obtain signal information from traffic lights on the route the vehicle 1 is traveling on or along the designated road. The TSPS utilizes traffic light signal information to support smooth driving through signalized intersections.

[0079] The communication device 25 can communicate with light beacons such as those located on the side of the road, and can also communicate with other vehicles traveling around the vehicle 1 to obtain the signal information.

[0080] [Vehicle Sensor 30]

[0081] The vehicle sensor 30 has the function of detecting various information related to the vehicle 1. The vehicle sensor 30 includes a vehicle speed sensor for detecting the vehicle speed of the vehicle 1, an acceleration sensor for detecting the acceleration of the vehicle 1, a yaw rate sensor for detecting the angular velocity about the vertical axis of the vehicle 1, an orientation sensor for detecting the direction of the vehicle 1, a tilt angle sensor for detecting the tilt angle of the vehicle 1, an illuminance sensor for detecting the illuminance of the location where the vehicle 1 is located, and a raindrop sensor for detecting the amount of raindrops at the location where the vehicle 1 is located, etc.

[0082] [HMI35 Composition]

[0083] Next, refer to Figure 3 , Figure 4 Explanation of HMI35.

[0084] Figure 3 This is a schematic structural diagram of the HMI35 connected to the vehicle control device 100 according to an embodiment of the present invention. Figure 4This is a diagram showing the front structure of the passenger compartment of a vehicle 1 equipped with a vehicle control device 100.

[0085] HMI35 Figure 3 As shown, it includes components of a driving operating system and components of a non-driving operating system. The boundaries between these components are not clearly defined or fixed; it is also possible for the components of the driving operating system to have the functions of a non-driving operating system (or vice versa).

[0086] like Figure 3 As shown, the HMI35, as a component of the driving operating system, includes an accelerator pedal 41, an accelerator opening sensor 43, an accelerator pedal reaction force output device 45, a brake pedal 47 and a brake pedal pressure sensor 49, a gear shift lever 51 and a gear shift position sensor 53, a steering wheel 55, a steering angle sensor 57 and a steering torque sensor 58, and other driving operation devices 59.

[0087] The accelerator pedal 41 is an acceleration operation element used to receive the driver's acceleration instruction (or deceleration instruction based on the retraction operation). The throttle opening sensor 43 detects the amount of accelerator pedal 41 being pressed and outputs a throttle opening signal indicating the amount of pressing to the vehicle control unit 100.

[0088] Alternatively, instead of outputting the throttle opening signal to the vehicle control unit 100, a configuration can be adopted in which the signal is directly output to the driving force output device 200, the steering device 210, or the braking device 220. The configuration is the same for other driving operating systems described below. The throttle pedal reaction force output device 45 outputs a force (operation reaction force) in the opposite direction to the operation direction relative to the throttle pedal 41, based on an instruction from, for example, the vehicle control unit 100.

[0089] The brake pedal 47 is a deceleration operating element used to receive the driver's deceleration instruction. The brake pedal pressure sensor 49 detects the amount (or force) of the brake pedal 47 being pressed and outputs a brake signal indicating the detection result to the vehicle control unit 100.

[0090] The gear shift lever 51 is a gear shifting operation element used to receive the driver's instruction to change gears. The gear position sensor 53 detects the gear indicated by the driver and outputs a gear position signal indicating the detection result to the vehicle control unit 100.

[0091] The steering wheel 55 is a control element for receiving the driver's steering instructions. The steering angle sensor 57 detects the steering angle of the steering wheel 55 and outputs a steering angle signal indicating the detection result to the vehicle control unit 100. The steering torque sensor 58 detects the torque applied to the steering wheel 55 and outputs a steering torque signal indicating the detection result to the vehicle control unit 100.

[0092] Other driving control devices 59 include, for example, a control handle, buttons, a dial switch, a GUI (Graphical User Interface) switch, etc. These other driving control devices 59 receive acceleration instructions, deceleration instructions, steering instructions, etc., and output them to the vehicle control unit 100.

[0093] like Figure 3 As shown, the HMI35, as a component of the non-driving operating system, includes, for example, an internal display device 61, a speaker 63, a touch operation detection device 65 and a content playback device 67, various operation switches 69, a seat 73 and a seat drive device 75, a window glass 77 and a window drive device 79, an in-vehicle camera 81, and an external display device 83.

[0094] The interior display device 61 is preferably a touch panel type display device that has the function of displaying various information to passengers in the vehicle interior. The interior display device 61, as... Figure 4 The diagram shows the instrument panel 85 in the instrument panel 60, positioned directly opposite the driver's seat, and extending along the vehicle width direction along the driver's side and the passenger side. Figure 4 The vehicle includes a multi-functional panel 87 that is horizontally elongated in the Y-axis direction, a right-side panel 89a on the driver's side in the vehicle width direction, and a left-side panel 89b on the passenger side in the vehicle width direction. Additionally, an internal display device 61 may be added to a position opposite the rear seats (on the back side of the front seats).

[0095] For example, the instrument panel displays the speedometer, tachometer, odometer, gear position information, and headlight illumination status information.

[0096] For example, the multi-function panel 87 displays various information such as map information around the vehicle 1, the current location information of the vehicle 1 on the map, traffic information (including signal information) related to the current driving path / planned path of the vehicle 1, traffic participant information (including pedestrians / bicycles / motorcycles / other vehicles, etc.) around the vehicle 1, and messages sent to traffic participants in the direction of the vehicle 1.

[0097] The right-side panel 89a displays images of the rear right side and the bottom right side of the vehicle 1 captured by the camera 11 located on the right side of the vehicle 1.

[0098] The left panel 89b displays images of the left rear and lower sides of the vehicle 1 captured by the camera 11 located on the left side of the vehicle 1.

[0099] The internal display device 61 is not particularly limited, and may be made of, for example, an LCD (Liquid Crystal Display) or an organic EL (Electroluminescence). The internal display device 61 may also be a HUD (Head-Up Display) that projects the desired image onto the window glass 77.

[0100] The speaker 63 has the function of outputting sound. The speaker 63 is installed in appropriate locations such as the dashboard 60, door panels, and rear cargo panel (not shown) in the vehicle interior, in an appropriate number of these locations.

[0101] The touch operation detection device 65 has the following function: when the internal display device 61 is a touch panel type, it detects the touch position on the display screen of the internal display device 61 and outputs the detected touch position information to the vehicle control device 100. Furthermore, when the internal display device 61 is not a touch panel type, this function of the touch operation detection device 65 can be omitted.

[0102] Content playback device 67 may include, for example, a DVD (Digital Versatile Disc) playback device, a CD (Compact Disc) playback device, a television receiver, and various guide image generation devices. The internal display device 61, speaker 63, touch operation detection device 65, and content playback device 67 may also have some or all of the same configuration as the navigation device 20.

[0103] Various operating switches 69 are disposed in appropriate locations within the vehicle interior. These operating switches 69 include an automatic driving selector switch 71 that indicates immediate start (or future start) and stop of automatic driving. The automatic driving selector switch 71 may also be a GUI (Graphical User Interface) switch or a mechanical switch. Additionally, the various operating switches 69 may also include switches for actuating the seat drive mechanism 75 or the window drive mechanism 79.

[0104] Seat 73 is the seating area for passengers of vehicle 1. Seat drive unit 75 freely drives the adjustment angle, fore-aft position, and lateral angle of seat 73. Window glass 77 is provided, for example, in each door. Window drive unit 79 drives the opening and closing of window glass 77.

[0105] The in-vehicle camera 81 is a digital camera that utilizes a solid-state imaging element such as CCD or CMOS. The in-vehicle camera 81 is located in the rearview mirror or steering wheel connection area (not shown), the instrument panel 60, etc., and is capable of capturing at least the head positions of the passenger in the driver's seat and the front passenger. The in-vehicle camera 81, for example, periodically and repeatedly captures images of the in-vehicle interior, including those of the driver and front passenger.

[0106] The external display device 83 has the function of displaying various information to traffic participants (including pedestrians / bicycles / motorcycles / other vehicles, etc.) around the vehicle 1. The external display device 83 includes a right front headlight section and a left front headlight section that are separately arranged in the width direction in the front grille of the vehicle 1, and a front display section (not shown) located between the left and right front headlight sections.

[0107] [Composition of the vehicle control device 100]

[0108] Next, return to Figure 2 This explains the composition of the vehicle control device 100.

[0109] The vehicle control device 100 may be implemented, for example, using a hard disk with one or more processors or similar functions. The vehicle control device 100 may be a combination of a processor such as a CPU (Central Processing Unit), a storage device, and a communication interface connected by an internal bus, such as an ECU (Electronic Control Unit) or an MPU (Micro-Processing Unit).

[0110] The vehicle control device 100 includes a target driving lane determination unit 110, a driving support control unit 120, a driving control unit 160, an HMI control unit 170, and a storage unit 180.

[0111] The functions of the target driving lane determination unit 110, the driving support control unit 120, and some or all of the functions of the driving control unit 160 are implemented by a processor executing a program (software). In addition, some or all of these functions can be implemented using a hard disk such as an LSI (Large Scale Integration) or ASIC (Application Specific Integrated Circuit), or a combination of software and hard disk.

[0112] In the following description, with "○○" referred to as the main body, the driver support control unit 120 reads each program from the ROM / EEPROM (Electrically Erasable Programmable Read-Only Memory) as needed, loads it into RAM, and executes the functions of "○○". Each program can be stored in the storage unit 180 in advance, or it can be combined with the vehicle control device 100 via other storage media or communication media as needed.

[0113] [Target Driving Lane Determination Unit 110]

[0114] The target lane determination unit 110 is implemented, for example, by an MPU (Micro Processing Unit). The target lane determination unit 110 divides the path provided by the navigation device 20 into multiple blocks (e.g., every 100 [m] in the vehicle's direction of travel), and determines the target lane for each block with high precision, referring to the reference information 181. The target lane determination unit 110, for example, determines which lane to travel in from the left.

[0115] When the target driving lane determination unit 110 determines the target driving lane, for example, when there are forks or merging points in the path, the vehicle 1 determines the target driving lane in a manner that allows it to travel on a reasonable driving path to the destination of the fork. The target driving lane determined by the target driving lane determination unit 110 is stored in the storage unit 180 as target driving lane information 182.

[0116] [Driver Support Control Unit 120]

[0117] The driving support control unit 120 includes a driving support mode control unit 130, an identification unit 140, and a switching control unit 150.

[0118] <Driving Support Mode Control Unit 130>

[0119] The driving support mode control unit 130 determines the automatic driving mode (automatic driving support state) to be executed by the driving support control unit 120 based on the driver's operation of the HMI35, the events determined by the action plan generation unit 144, and the driving mode determined by the track generation unit 147. The automatic driving mode is then notified to the HMI control unit 170.

[0120] In any autonomous driving mode, it is possible to switch to (rewrite as) a lower-level autonomous driving mode by operating on the components of the driving operating system in HMI35.

[0121] The rewrite will begin under the following circumstances: when the driver of vehicle 1 operates the components of the driving operating system of HMI35 for a period of time or longer than the specified amount of operation change (e.g., the accelerator pedal 41 throttle opening, the brake pedal 47 braking amount, the steering wheel 55 steering angle), or the driver operates the components of the driving operating system more than the specified number of times.

[0122] <Identification Department 140>

[0123] The identification unit 140 includes a vehicle position identification unit 141, an external identification unit 142, an area-specific unit 143, an action plan generation unit 144, and a track generation unit 147.

[0124] <Vehicle Position Recognition Unit 141>

[0125] The vehicle location recognition unit 141 identifies the driving path 91 of the vehicle 1 based on the high-precision map information 181 stored in the storage unit 180, the camera 11, the radar 13, the lidar 15, the navigation device 20, or information input from the vehicle sensors 30. (Refer to...) Figure 6 Lane 93 (see reference) is drawn on the road. Figure 6 ), and the relative position of vehicle 1 with respect to lane 93 (details of the relative coordinates will be explained later).

[0126] The vehicle location recognition unit 141 identifies the driving lane, for example, by comparing the pattern of road markings (e.g., the arrangement of solid and dashed lines) identified from high-precision map information 181 with the pattern of road markings around the vehicle 1 identified from images captured by camera 11. In this recognition, the current position of the vehicle 1 obtained from navigation device 20 or the processing results based on INS can be appropriately used.

[0127] <External Identification Department 142>

[0128] External Identification Department 142 Figure 2 As shown, based on external information input from external sensors 10, including camera 11, radar 13, and lidar 15, the system identifies external conditions, such as the position, speed, and acceleration of surrounding vehicles. Surrounding vehicles refer to, for example, vehicles traveling around vehicle 1 and other vehicles (vehicles in front, vehicles traveling alongside, and vehicles behind) traveling in the same direction as vehicle 1.

[0129] The positions of surrounding vehicles can be represented using representative points such as the center of gravity or corners of other vehicles, or using areas outlined by the contours of other vehicles. The status of surrounding vehicles can include information gathered from the aforementioned machines, such as the speed / acceleration of surrounding vehicles, and whether they have changed lanes (or intend to change lanes). In addition, the external recognition unit 142 can identify the positions of objects including guardrails, utility poles, parked vehicles, pedestrians, and traffic signs, in addition to surrounding vehicles including those in front and behind.

[0130] <Regional Specific Section 143>

[0131] The area-specific unit 143 acquires information about specific areas (interchanges / transportation hubs / locations where driving lanes are added / reduced) located around the vehicle 1 based on map information. Thus, even when the area-specific unit 143 is hidden from vehicles ahead, including those traveling in front, and cannot acquire images of the direction of travel via external sensors 10, it can still acquire information about specific areas used to assist the smooth movement of the vehicle 1.

[0132] Furthermore, the area-specific unit 143 can replace the acquisition of information about a specific area based on map information, and instead determine the same object based on image processing of the travel direction image acquired by the external sensor 10, or identify the object based on the outline of the travel direction image according to the internal processing of the external identification unit 142, thereby acquiring the information about the specific area.

[0133] Additionally, as will be explained later, the accuracy of information about a specific region acquired by the region-specific unit 143 can be improved by using VICS information acquired by the communication device 25.

[0134] <Action Plan Generation Department 144>

[0135] The action plan generation unit 144 sets the starting point and / or the destination of autonomous driving. The starting point of autonomous driving can be the current location of the vehicle 1 or the location where the autonomous driving operation was instructed. The action plan generation unit 144 generates an action plan within the interval between the starting point and the destination of autonomous driving. Furthermore, not limited to this, the action plan generation unit 144 can also generate an action plan within any interval.

[0136] The action plan may consist of a series of events executed sequentially. These events may include, for example, a deceleration event that slows down vehicle 1, an acceleration event that accelerates vehicle 1, a lane-keeping event that keeps vehicle 1 in its lane without leaving its lane, a lane-changing event that changes lanes, an overtaking event that allows vehicle 1 to pass the vehicle in front, a fork in the road where vehicle 1 changes to a desired lane or moves in its current lane without leaving its lane, a merging event where vehicle 1 accelerates or decelerates or changes lanes in a merging lane for merging onto the main road, and a handover event where vehicle 1 transitions from manual to automatic driving mode (automatic driving support state) at the start of automatic driving or from automatic driving mode to manual driving mode at the predetermined end point of automatic driving.

[0137] The action plan generation unit 144 sets up a lane change event, a branching event, or a merging event at the location where the target driving lane is switched, as determined by the target driving lane determination unit 110. Information representing the action plan generated by the action plan generation unit 144 is stored in the storage unit 180 as action plan information 183.

[0138] The action plan generation department 144 includes a pattern change department 145 and a notification control department 146.

[0139] <Model Change Section 145>

[0140] The mode change unit 145, for example, selects a driving mode corresponding to the recognition result from driving modes including preset multi-level automatic driving modes and manual driving modes based on the recognition result of the object present in the direction of travel of the vehicle 1 identified by the external recognition unit 142, and uses the selected driving mode to perform driving actions of the vehicle 1.

[0141] <Notification to Control Department 146>

[0142] The notification control unit 146 notifies the vehicle 1 that the driving mode has been changed by the mode change unit 145. The notification control unit 146 notifies the vehicle 1 of the change in driving mode, for example, by having the speaker 63 output sound information previously stored in the storage unit 180.

[0143] Furthermore, if the driver can be informed of changes in the driving mode of the vehicle 1, the notification is not limited to sound-based notification, but can also be made using display, light, vibration, or a combination thereof.

[0144] <Orbit Generation Section 147>

[0145] The track generation unit 147 generates the track that the vehicle 1 should travel on based on the action plan generated by the action plan generation unit 144.

[0146] <Switching Control Unit 150>

[0147] Switching control unit 150, etc. Figure 2 As shown, based on the automatic driving switch 71 (refer to...) Figure 3 The system alternately switches between automatic driving mode and manual driving mode based on input signals and other signals. Furthermore, the switching control unit 150 switches the current automatic driving mode to a lower-level driving mode based on acceleration, deceleration, or manipulation operations indicated by the components of the driving operating system relative to the HMI 35. For example, if the operation quantity represented by a signal input from a component of the driving operating system of the HMI 35 exceeds a threshold for a specified duration, the switching control unit 150 switches the current automatic driving mode to (or rewrite as) a lower-level driving mode.

[0148] In addition, the switching control unit 150 can also perform switching control to restore the original automatic driving mode if no operation of the driving operating system components relative to HMI35 is detected within a specified period after switching to the rewritten lower-level driving mode.

[0149] <Traffic Control Unit 160>

[0150] The driving control unit 160 controls the driving of the vehicle 1 by controlling the driving drive output device 200, the steering device 210, and the braking device 220, so that the vehicle 1 passes through the track to be driven by the track generation unit 147 at a predetermined time.

[0151] <HMI Control Unit 170>

[0152] When the HMI control unit 170 is notified by the driving support control unit 120 of the setting information of the automatic driving mode of the vehicle 1, it refers to the information 184 on whether it can be operated according to each mode and controls the HMI 35 according to the setting content of the automatic driving mode.

[0153] HMI control unit 170, etc. Figure 2 The system is based on driving mode information of the vehicle 1 obtained from the driving support control unit 120. Furthermore, by referring to the operability information 184 for each mode, it determines which devices are permitted to be used (part or all of the navigation device 20 and HMI 35) and which are not permitted to be used. Additionally, based on the above determination results, the HMI control unit 170 controls whether driver operations related to the driving operating system's HMI 35 or navigation device 20 can be accepted.

[0154] For example, when the driving mode executed by the vehicle control unit 100 is manual driving mode, the HMI control unit 170 accepts driver operations related to the HMI 35 of the driving operating system (e.g., accelerator pedal 41, brake pedal 47, gear shift lever 51, and steering wheel 55).

[0155] The HMI control unit 170 includes a display control unit 171.

[0156] <Display Control Unit 171>

[0157] The display control unit 171 performs display control related to the internal display device 61 and the external display device 83. Specifically, for example, when the driving mode executed by the vehicle control device 100 is a highly automated automatic driving mode, the display control unit 171 performs control such as displaying information such as attention-grabbing / warning / driving assistance information relative to traffic participants around the vehicle 1 on the internal display device 61 and / or the external display device 83.

[0158] Furthermore, the display control unit 171 controls the display to show digital content, including chat communication content and key content extracted from chat conversations, on the multi-function panel (display unit) 87 in the internal display device 61. This will be explained in detail later.

[0159] <Storage Department 180>

[0160] The storage unit 180 stores information such as high-precision map information 181, target driving lane information 182, action plan information 183, and whether operation can be performed in various modes 184. The storage unit 180 is implemented using ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), flash memory, etc. The program executed by the processor can be stored in the storage unit 180 in advance, or it can be downloaded from an external device such as an in-vehicle internet device. Alternatively, the program can be installed in the storage unit 180 by installing a portable storage medium containing the program onto a drive device (not shown).

[0161] The high-precision map information 181 is more precise than the map information typically provided by the navigation device 20. The high-precision map information 181 includes, for example, information about the center of the driving lane and information about the boundaries of the driving lane. The boundaries of the driving lane include the type / color / length / road width / curb width / mainline width / driving lane width / boundary location / boundary type (guardrail / vegetation / kerbstone) / zebra crossing, etc., and these boundaries are included within the high-precision map.

[0162] In addition, high-precision map information 181 may include road information, traffic restriction information, address information (address / postal code), facility information, telephone number information, etc. Road information includes information indicating the road type, such as highways, toll roads, national roads, prefectural roads, or the number of driving lanes, the width of each driving lane, the road gradient, the road location (including three-dimensional coordinates including longitude, latitude, and altitude), the curvature of driving lanes, the location of merging and branching points of driving lanes, and road signs. Traffic restriction information includes information such as driving lanes being closed due to construction, traffic accidents, traffic jams, etc.

[0163] [Driving drive force output device 200, steering device 210, and braking device 220]

[0164] Vehicle control device 100 Figure 2 As shown, the driving of the driving force output device 200, the steering device 210, and the braking device 220 are controlled according to the driving control command of the driving control unit 160.

[0165] <Driving drive force output device 200>

[0166] The driving force output device 200 outputs driving force (torque) for driving the vehicle 1 to the drive wheels. The driving force output device 200 includes, for example, an engine ECU (Electronic Control Unit, not shown), which controls the internal combustion engine, transmission, and internal combustion engine when the vehicle 1 is a car that uses an internal combustion engine as its power source.

[0167] In addition, the driving force output device 200 includes a motor ECU (not shown), which controls the driving motor and the driving motor when the vehicle 1 is an electric vehicle that uses an electric motor as its power source.

[0168] Furthermore, when the vehicle 1 is a hybrid vehicle, the driving force output device 200 includes an internal combustion engine, a transmission, an engine ECU, a driving motor, and a motor ECU (none of which are shown).

[0169] When the driving force output device 200 only includes an internal combustion engine, the engine ECU adjusts the throttle opening or gear of the internal combustion engine based on information input from the driving control unit 160 (described later).

[0170] When the driving force output device 200 only includes a driving motor, the motor ECU adjusts the duty cycle of the PWM signal applied to the driving motor based on the information input from the driving control unit 160.

[0171] When the driving force output device 200 includes an internal combustion engine and a driving motor, the engine ECU and the motor ECU coordinate with each other to control the driving force according to the information input from the driving control unit 160.

[0172] <Steering device 210>

[0173] The steering system 210 includes, for example, a steering ECU and an electric motor (neither shown). The electric motor, for example, applies force to a rack and pinion mechanism to change the direction of the steering wheel. The steering ECU drives the electric motor to change the direction of the steering wheel according to information input from the vehicle control unit 100, or information on the input steering angle or steering torque.

[0174] <Brake device 220>

[0175] The braking device 220 may be, for example, an electric servo braking device comprising a brake caliper, a hydraulic cylinder for transmitting hydraulic pressure to the brake caliper, an electric motor for generating hydraulic pressure in the hydraulic cylinder, and a braking control unit (none shown). The braking control unit of the electric servo braking device controls the electric motor based on information input from the driving control unit 160, outputting braking torque corresponding to the braking operation to each wheel. As a backup, the electric servo braking device may also include a mechanism for transmitting hydraulic pressure generated by the operation of the brake pedal 47 to the hydraulic cylinder via the master hydraulic cylinder.

[0176] Furthermore, the braking device 220 is not limited to the electric servo braking device described above, but may also be an electronically controlled hydraulic braking device. The electronically controlled hydraulic braking device controls the actuator based on information input from the driving control unit 160 to transmit hydraulic pressure from the master hydraulic cylinder to the hydraulic cylinder. Additionally, the braking device 220 may also include regenerative braking generated by a driving motor that can be installed within the driving force output device 200.

[0177] [Summary of the Yaw Rate Deduction Device 300 of the Invention]

[0178] Next, refer to Figure 5 This section describes the outline of the yaw rate estimation device 300 of the present invention included in the vehicle control device 100.

[0179] Figure 5 This is a block diagram conceptually illustrating the lane yaw rate estimation function of the yaw rate estimation device 300 of the present invention. Figure 6 This is a top view of the vehicle 1, which provides a general description of the yaw rate estimation device 300.

[0180] For example, in the case of vehicle 1 being an autonomous vehicle, in order to properly control the driving of vehicle 1, it is strongly required to obtain the yaw rate that reflects the yaw motion of vehicle 1 with high precision.

[0181] Therefore, in the yaw rate inference device 300 of the present invention, the conventional yaw rate detected by the yaw rate sensor is replaced by the detection yaw rate as the detection value, or the concept of "lane yaw rate" is introduced on this basis.

[0182] The yaw rate estimation device 300 has the function of inferring the yaw rate based on information related to the direction of the driving lane 93 at the reference coordinate 90 of the vehicle 1 (described in detail later) and information related to the yaw angle of the vehicle 1 relative to the direction of the driving lane 93. In other words, it infers the yaw rate based on information related to the driving lane 93.

[0183] In this specification, the yaw rate inferred based on information related to the driving lane 93 is specifically referred to as the "lane yaw rate". In this invention, this is because it is necessary to distinguish between the detected yaw rate YRsr, which is detected as a value by the yaw rate sensor, and the lane yaw rate YRln.

[0184] In detail, the yaw rate estimation device 300 of the present invention is as follows: Figure 5 As shown, the configuration includes an information acquisition unit 311, a lane recognition unit 313, a direction change rate calculation unit 315, a yaw rate change rate calculation unit 317, and a lane yaw rate inference unit 319.

[0185] <Information Acquisition Department 311>

[0186] Information Acquisition Department 311, etc. Figure 5 The device shown has the function of acquiring information about the frontal image of the vehicle 1 and the vehicle speed. The information about the frontal image of the vehicle 1 can be acquired simply by the camera 11 in the external sensor 10. In addition, the information about the vehicle speed of the vehicle 1 can be acquired simply by the vehicle speed sensor in the vehicle sensor 30.

[0187] The information of the frontal image of the vehicle 1 acquired by the information acquisition unit 311 and the vehicle speed information are sent to the lane recognition unit 313.

[0188] Information acquisition unit 311 is included Figure 2 The functional units within the input / output interface (not shown) of the vehicle control device 100 shown.

[0189] <Lane Recognition Unit 313>

[0190] Lane recognition unit 313, etc. Figure 5 , Figure 6The device has the following function: based on the information of the front image of the vehicle 1 acquired by the information acquisition unit 311, it identifies the driving lane 93 drawn on the driving path 91 of the vehicle 1 and the curvature of the driving lane 93.

[0191] In the lane recognition unit 313, each pixel constituting the frontal image (peripheral image) of the vehicle 1 acquired by the camera 11 is unfolded and mapped to a three-dimensional coordinate system with the mounting part of the camera 11 (e.g., near the interior mirror) as the origin. This three-dimensional coordinate system defines the width direction of the vehicle 1 as the x-axis, the length direction (travel direction) as the y-axis, and the height direction (vertical direction) as the z-axis.

[0192] In an embodiment of the present invention, in the lane recognition unit 313, each pixel constituting the front image of the vehicle 1 in the aforementioned three-dimensional coordinate system is as follows: Figure 6 As shown, each pixel is transformed one-to-one by a coordinate transformation (projective transformation) to form a top-view image (top view image) of the vehicle 1 as viewed from above. Each pixel constituting this top view image is unfolded and mapped to a two-dimensional coordinate system with a specified origin. The two-dimensional coordinate system unfolded from the top view image of the vehicle 1 (hereinafter referred to as "the reference coordinates 90 of the vehicle 1") is as follows: Figure 6 As shown, the width direction of vehicle 1 is defined as the x-axis, and the length direction is defined as the y-axis.

[0193] exist Figure 6 In the example shown, vehicle 1 travels along a gentle left-turn lane 93 drawn on the driving path 91, and at any location P1 on the reference coordinates 90 of vehicle 1.

[0194] Lane recognition unit 313 is for in Figure 2 The functional unit included in the identification unit 140 in the vehicle control device 100 shown.

[0195] In detail, the lane recognition unit 313 establishes a correlation with an approximate curve composed of an nth-degree polynomial (where n is an integer greater than 2) as the trajectory of the driving lane 93 drawn on the driving path 91 of the vehicle 1, thereby recognizing the driving lane 93 and the curvature of the driving lane 93.

[0196] In fact, the lane recognition unit 313 calculates the aforementioned nth-degree polynomial based on (n+1) or more consecutive time series values ​​(past sample values ​​traced back from the current), including the attention value (current value) of the trajectory of the driving lane 93. For example, if n=2, Figure 6 The trajectory (approximate curve) of the driving lane 93 shown can be represented by the following quadratic polynomial (Equation 1).

[0197]

Mathematical Formula 1

[0198] x = f(y) = k²·y 2 +k1·y 1 +k0 (Equation 1)

[0199] In Equation 1, k2, k1, and k0 are the second-order coefficients, the first-order coefficients, and the zero-order coefficients, respectively.

[0200] The second-order coefficient k2 corresponds to the curvature component of the driving lane 93. The first-order coefficient k1 corresponds to the yaw angle component of the vehicle 1 in the direction relative to the driving lane 93. The zero-order coefficient k0 corresponds to the dimensional component in the x-axis direction (vehicle width direction) relative to the driving lane 93 of the vehicle 1.

[0201] Furthermore, when using a quadratic polynomial to represent the trajectory (approximate curve) of the driving lane 93, it is sufficient, for example, to refer appropriately to the technical matters described in paragraphs 0020-0021 of the patent document (JP 2019-131149).

[0202] <Directional Change Rate Calculation Section 315>

[0203] Directional change rate calculation part 315 Figure 5 , Figure 6 As shown, based on the curvature of the driving lane 93 identified by the lane recognition unit 313 and the vehicle speed information acquired by the information acquisition unit 311, the rate of change Ψc of the direction of the driving lane 93 in the reference coordinates 90 of the vehicle 1 is calculated (refer to...). Figure 6 ).

[0204] Furthermore, the direction change rate calculation unit 315 can also calculate the curvature of the driving lane 93 based on the quadratic coefficients of the above-mentioned nth degree polynomial obtained by the lane recognition unit 313.

[0205] Here, the curvature of the driving lane 93 refers to an index representing the degree of curvature of the line at any point P1 on the driving lane 93. The greater the curvature of the line at any point P1 (a sharp turn), the greater the curvature of the driving lane 93; on the other hand, the less curvature of the line at any point P1 (a gentle turn), the smaller the curvature of the driving lane 93.

[0206] Furthermore, the rate of change of direction of the driving lane 93 in the reference coordinate 90 of vehicle 1 refers to the change of direction of vehicle 1 from the reference point P0 (reference point) on the driving lane 93. Figure 6 When moving to any location P1, the direction at any location P1 relative to the direction of the driving lane 93 at the reference location P0 changes to the extent of the change within a specified elapsed time (t(P1) - t(P0): the time at any location P1 - the time at the reference time point P0).

[0207] Specifically, the rate of change Ψc of the direction of the driving lane 5 at any point P1 in the reference coordinates 90 of vehicle 1 (refer to...) Figure 6 It can be calculated by multiplying the curvature at any point P1 on the driving lane 93 in the reference coordinates 90 of the vehicle 1 by the vehicle speed (m / s).

[0208] The rate of change of direction Ψc of the driving lane 93 calculated by the rate of change of direction calculation unit 315 is sent to the lane yaw rate inference unit 319.

[0209] Directional change rate calculation part 315 is Figure 2 The functional unit included in the identification unit 140 in the vehicle control device 100 shown.

[0210] <Calculation of the rate of change of yaw angle 317>

[0211] The calculation of the rate of change of yaw angle is as follows: Part 317 Figure 5 , Figure 6 As shown, based on the curvature of the driving lane 93 identified by the lane recognition unit 313 and the vehicle speed information acquired by the information acquisition unit 311, the rate of change Ψv of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93 in the reference coordinates 90 of the vehicle 1 is calculated (refer to...). Figure 6 ).

[0212] Furthermore, the yaw rate calculation unit 317 can also calculate the yaw angle of the vehicle 1 relative to the driving lane 93 based on the first-order coefficient of the above-mentioned nth-order polynomial obtained by the lane recognition unit 313, and calculate the yaw rate Ψv of the vehicle 1.

[0213] Here, the yaw angle of vehicle 1 relative to the driving lane 93 in the reference coordinate 90 of vehicle 1 refers to the degree to which vehicle 1 is tilted relative to the driving lane 93.

[0214] Additionally, the rate of change Ψv of the yaw angle of vehicle 1 relative to the direction of the driving lane 93 in the reference coordinate 90 of vehicle 1 (refer to...) Figure 6 ) refers to the reference point P0 (reference) on the driving lane 93 of vehicle 1. Figure 6 When the vehicle 1 moves to any location P1, the degree to which the yaw angle of the vehicle 1 relative to the direction of the driving lane 93 at the arbitrary location P1 changes over a specified elapsed time (time t(P1) at any location P1 - time t(P0) at the reference time point P0).

[0215] The rate of change of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93 calculated by the yaw angle change rate calculation unit 317 is sent to the lane yaw rate inference unit 319.

[0216] The calculation part 317 for the rate of change of yaw angle is... Figure 2 The functional units included in the identification unit 140 of the vehicle control device 100 shown.

[0217] <Lane Yaw Rate Inference Unit 319>

[0218] Lane yaw rate inference unit 319 (reference) Figure 2 as well as Figure 5 Based on the direction change rate Ψc of the driving lane 93 calculated by the direction change rate calculation unit 315 and the yaw angle of the vehicle 1 relative to the direction change rate Ψv of the driving lane 93 calculated by the yaw angle change rate calculation unit 317, the lane yaw rate YRln, derived from the curvature of the driving lane 93 and the vehicle speed of the vehicle 1, is inferred.

[0219] Specifically, the lane yaw rate inference unit 319 infers the lane yaw rate YRln by adding the rate of change of the direction of the driving lane 93 Ψc and the rate of change of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93 Ψv.

[0220] Lane yaw rate inference unit 319 Figure 2 The functional units included in the identification unit 140 of the vehicle control device 100 shown.

[0221] [Operation of the yaw rate estimation device 300 of the present invention]

[0222] Next, refer to the appropriate Figure 5 , Figure 6 This describes the operation of the yaw rate estimation device 300 of the present invention.

[0223] Information Acquisition Department 311, etc. Figure 5 As shown, information about the frontal image of vehicle 1 and its speed are obtained.

[0224] Lane recognition unit 313, etc. Figure 5 , Figure 6 As shown, based on the information of the front image of the vehicle 1 acquired by the information acquisition unit 311, the driving lane 93 drawn on the driving path 91 of the vehicle 1 and the curvature of the driving lane 93 are identified.

[0225] The direction change rate calculation unit 315 calculates the direction change rate Ψc of the driving lane 93 in the reference coordinates 90 of the vehicle 1 based on the curvature of the driving lane 93 identified by the lane recognition unit 313 and the vehicle speed information acquired by the information acquisition unit 311. Figure 6 ).

[0226] The yaw rate calculation unit 317 calculates the rate of change Ψv of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93 in the reference coordinate 90 of the vehicle 1, based on the curvature of the driving lane 93 identified by the lane recognition unit 313 and the vehicle speed information acquired by the information acquisition unit 311. Figure 6 ).

[0227] The lane yaw rate inference unit 319 infers the lane yaw rate YRln, which is derived from the curvature of the driving lane 93 and the vehicle speed of the vehicle 1, based on the direction change rate calculation unit 315 calculating the direction change rate Ψc of the driving lane 93 and the yaw rate change rate calculation unit 317 calculating the yaw rate change rate of the vehicle 1 relative to the direction of the driving lane 93.

[0228] [The configuration of the yaw rate estimation device 320 in the first variation]

[0229] Next, refer to Figure 7 , Figure 8 The configuration of the yaw rate estimation device 320 in the first modified example is explained.

[0230] Figure 7 This is a functional block diagram showing the general configuration of the yaw rate estimation device 320 in the first modified example. Figure 8 The figure is shown by comparing the input signal waveform and the output signal waveform of the low-pass filter (LPF) 325 of the yaw rate estimation device 320 in the first modified example.

[0231] The yaw rate estimation device 320 of the first modification has the function of estimating the lane yaw rate based on the yaw angle (sometimes abbreviated as "lane yaw angle") of the vehicle 1 relative to the direction of the driving lane 93 based on the trajectory of the driving lane 93, the curvature of the driving lane 93 based on the trajectory of the driving lane 93 (sometimes abbreviated as "lane curvature"), and the vehicle speed of the vehicle 1.

[0232] Comparing the yaw rate estimation device 300 of the present invention with the yaw rate estimation device 320 of the first modified example, the difference between the yaw rate estimation device 300 of the present invention, which has the basic concept of the present invention, and the yaw rate estimation device 320 of the first modified example, which has a configuration that embodies the present invention, is that, based on the basic concept of the present invention, it has a configuration that embodies the present invention.

[0233] To achieve the function of inferring the lane yaw rate, the yaw rate inference device 320 of the first modification example is as follows: Figure 7As shown, it is configured to include a past value storage unit 321, a differential operation unit 323, a low-pass filter (LPF) 325, a blind zone processing unit 327, a first gain adjustment unit 329, a multiplication unit 331, an addition unit 333, and a second gain adjustment unit 335.

[0234] The past value storage unit 321 has the function of temporarily storing time-series data (including the current value and a predetermined number of past values) of lane yaw angle acquired sequentially at predetermined time intervals (not particularly limited, for example, about 50 to 100 ms). The time-series data of lane yaw angle stored in the past value storage unit 321 is sent to the differential calculation unit 323.

[0235] The differential calculation unit 323 has the function of performing differential calculations on the time series data of the lane yaw angle stored in the past value storage unit 321 to appropriately grasp the changing trend of the time series data of the lane yaw angle of the vehicle 1 as the time changes. The time series data of the lane yaw angle after differential calculation by the differential calculation unit 323 is sent to the LPF 325.

[0236] LPF325 has the function of smoothing the time series data of the lane yaw angle of the vehicle 1, which varies with time, by removing high-frequency components contained in the time series data of the lane yaw angle after the differential operation performed by the differential operation unit 323. Figure 8 The input signal waveforms at signal input point 324 and output signal waveforms at signal output point 326 of the LPF325 are compared to illustrate this. It can be seen that by using the LPF325 to remove high-frequency components, high-frequency noise contained in the time series data of lane yaw angle is removed.

[0237] The result is that the time series data of the lane yaw angle after removing the high-frequency components became a highly valuable piece of information that reproduced the actual motion of vehicle 1.

[0238] The time series data of lane yaw angle after removing the high-frequency components based on LPF325 is equivalent to the rate of change Ψv of the yaw angle of vehicle 1 relative to the direction of the driving lane 93.

[0239] The time series data of the lane yaw angle after removing high-frequency components using LPF325 is sent to the adder 333.

[0240] The blind spot processing unit 327 has the function of treating lane curvature values ​​within a predetermined range that fall within a predetermined curvature range relative to zero (meaning the driving lane 93 is a straight line) as straight lines in time-series data of lane curvature acquired sequentially at predetermined time intervals. Therefore, driving lanes 93 with gentle right and left turns are not considered when inferring the lane yaw rate YRln and are treated as straight lines. The time-series data of lane curvature after blind spot processing by the blind spot processing unit 327 is sent to the multiplication unit 331.

[0241] The first gain adjustment unit 329 has the function of performing a predetermined gain adjustment relative to the time series data of the vehicle speed of the vehicle 1. As a result, the time series data of the vehicle speed of the vehicle 1 after gain adjustment becomes vehicle speed information suitable for inferring the yaw rate YRln.

[0242] The time-series data of the vehicle speed of the vehicle 1 after gain adjustment based on the first gain adjustment unit 329 is sent to the multiplication unit 331.

[0243] The multiplication unit 331 has the function of multiplying the time series data of lane curvature after blind spot processing based on the blind spot processing unit 327 and the time series data of the vehicle speed of the vehicle 1 after gain adjustment based on the first gain adjustment unit 329. Based on this multiplication, the rate of change Ψc of the direction of the vehicle 1 in the driving lane 5 at any location P1 in the reference coordinate 90 is obtained (refer to...). Figure 6 ).

[0244] The rate of change Ψc of the direction of the driving lane 5, which is the result of multiplication by multiplication unit 331, is sent to addition unit 333.

[0245] The adder 333 has the function of adding the rate of change of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93, which is the output of LPF325, and the rate of change of the direction of the driving lane 5, which is the result of multiplication by the multiplier 331. Based on this addition, the estimated value of the lane yaw rate YRln of the vehicle 1 is obtained.

[0246] The inferred value of the lane yaw rate YRln of the vehicle 1, which is the result of addition by the addition unit 333, is sent to the second gain adjustment unit 335.

[0247] The second gain adjustment unit 335 has the function of performing a predetermined gain adjustment on the inferred value of the lane yaw rate YRln of the vehicle 1. Based on this gain adjustment, a highly accurate inferred value of the lane yaw rate YRln that reproduces the motion of the vehicle 1 is obtained.

[0248] [Operation of the yaw rate estimation device 320 in the first variation]

[0249] Next, refer to Figure 7 Explain the operation of the yaw rate estimation device 320 in the first modified example.

[0250] Past value storage unit 321, such as Figure 7 The temporary storage shown represents time-series data of lane yaw angles acquired sequentially at specified time intervals.

[0251] The differential operation unit 323 performs differential operations on the time series data of the lane yaw angle stored in the past value storage unit 321. As a result, it is possible to accurately grasp the changing trend of the time series data of the lane yaw angle of the vehicle 1 as it changes over time.

[0252] LPF325 removes high-frequency components from the time-series data of lane yaw angle after differential calculation based on differential calculation unit 323. This allows for smoothing of the time-series data of the lane yaw angle of the vehicle 1, which varies over time.

[0253] The blind spot processing unit 327 performs blind spot processing on time-series data of lane curvature acquired sequentially at predetermined time intervals, treating lanes 93 with curvature values ​​within a predetermined curvature range that are zero relative to lane curvature (the driving lane 93 is a straight line) as straight lines. Therefore, driving lanes 93 with gentle right and left turns are not considered when calculating the lane yaw rate YRln and are treated as straight lines.

[0254] The first gain adjustment unit 329 performs a prescribed gain adjustment on the time series data of the vehicle speed of the vehicle 1. As a result, the time series data of the vehicle speed of the vehicle 1 after gain adjustment becomes vehicle speed information suitable for inferring the scale of lane yaw rate.

[0255] The multiplication unit 331 multiplies the time-series data of lane curvature after blind spot processing based on the blind spot processing unit 327, and the time-series data of the vehicle speed of the vehicle 1 after gain adjustment based on the first gain adjustment unit 329. Based on this multiplication, the rate of change Ψc of the direction of the vehicle 1 in the driving lane 5 at any location P1 in the reference coordinate 90 is obtained (refer to...). Figure 6 ).

[0256] The adder 333 adds the rate of change of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93, which is the output of LPF325, and the rate of change of the direction of the driving lane 5, which is the result of multiplication by the multiplier 331. Based on this addition, the estimated value of the lane yaw rate YRln of the vehicle 1 is obtained.

[0257] The second gain adjustment unit 335 performs a predetermined gain adjustment relative to the inferred value of the lane yaw rate YRln of the vehicle 1. Through this gain adjustment, a highly accurate inferred value of the lane yaw rate YRln that reproduces the motion of the vehicle 1 is obtained.

[0258] The yaw rate estimation device 320 of the first modification uses the estimated value of the lane yaw rate YRln output by the second gain adjustment unit 335 as the yaw rate of the vehicle 1.

[0259] [The configuration of the yaw rate estimation device 340 in the second variation]

[0260] Next, refer to Figure 9A , Figure 9B The configuration of the yaw rate estimation device 340 in the second variation is explained.

[0261] Figure 9A This is a functional block diagram showing the approximate configuration of the yaw rate estimation device 340 in the second variation. Figure 9B The figure shows a comparison of the frequency characteristics of the filter gain related to the detection of yaw rate YRsr and lane yaw rate YRln in the complementary filter 347 of the yaw rate estimation device 340 in the second modification example.

[0262] The yaw rate estimation device 340 of the second modification has the following function: it estimates the lane yaw rate YRln based on the lane yaw angle, lane curvature, and vehicle speed of the vehicle 1, and generates a composite yaw rate YRfs that integrates the estimated lane yaw rate YRln and the detected yaw rate YRsr detected by the yaw rate sensor at a predetermined ratio.

[0263] The difference between the yaw rate estimation device 320 of the first modification and the yaw rate estimation device 340 of the second modification is that, unlike the yaw rate estimation device 320 of the first modification, which estimates the lane yaw rate YRln and uses the estimated lane yaw rate YRln as the yaw rate of the vehicle 1, the combined yaw rate YRfs, which integrates the detected yaw rate YRsr and the lane yaw rate YRln estimated by the yaw rate estimation device 340 of the second modification using a predetermined contribution ratio, is used as the yaw rate of the vehicle 1.

[0264] Furthermore, the yaw rate estimation device 340 of the second modification is the same as the yaw rate estimation device 320 of the first modification in that it is constructed based on the basic concept of the present invention.

[0265] To achieve the aforementioned comprehensive yaw rate generation function, the yaw rate inference device 340 of the second modification example is as follows: Figure 9A As shown, it is configured to include a merging unit 341, the multiplication unit 331, and the addition unit 333 (all refer to...). Figure 7 ), complementary filter section 343, and integration section 345.

[0266] The merging unit 341 has the function of merging the past value storage unit 321, the differential calculation unit 323, and the LPF 325 of the yaw rate estimation device 320 of the first modified example.

[0267] In other words, the merging unit 341 temporarily stores time-series data of lane yaw angles acquired sequentially at predetermined time intervals, performs a differential operation on the stored time-series data of lane yaw angles, and removes high-frequency components contained in the time-series data of lane yaw angles after the differential operation. As a result, the merging unit 341 outputs the rate of change Ψv of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93.

[0268] The rate of change Ψv of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93, output by the merging unit 341, is sent to the adding unit 333.

[0269] The multiplication unit 331 multiplies the time-series data of lane curvature with the time-series data of vehicle speed 1. Based on this multiplication, the rate of change Ψc of the direction of travel of vehicle 1 in lane 5 at any location P1 in the reference coordinate system 90 is obtained (refer to...). Figure 6 ).

[0270] The rate of change Ψc of the direction of the driving lane 5, which is the result of multiplication by multiplication unit 331, is sent to addition unit 333.

[0271] The addition unit 333 adds the rate of change of the yaw angle of the vehicle 1 relative to the direction of the driving lane 93 output by the merging unit 341, Ψv, to the rate of change of the direction of the driving lane 5, which is the result of the multiplication by the multiplication unit 331. Based on this addition, the estimated value of the lane yaw rate YRln of the vehicle 1 is obtained.

[0272] The inferred value of the lane yaw rate YRln of the vehicle 1, which is the result of addition by the addition unit 333, is sent to the complementary filter unit 343.

[0273] The complementary filter unit 343 has the following function: it takes into input time-series data of the detected yaw rate YRsr detected by the yaw rate sensor and time-series data of the inferred value of the lane yaw rate YRln of the vehicle 1, performs prescribed filtering processing on each time-series data, and outputs the filtered time-series data. The complementary filter unit 343 can be constructed by a digital filter.

[0274] To achieve the above-mentioned filtering function, the complementary filter unit 343 includes a first filter (HPF) 351 and a second filter (LPF) 353.

[0275] The first filter (HPF) 351 takes as input the time-series data of the detected yaw rate YRsr from the yaw rate sensor, performs a prescribed high-pass filtering process on this time-series data (details are described later), and outputs the high-pass filtered time-series data. This high-pass filtering process is based on reducing the impact of yaw rate errors caused by the midpoint drift of the yaw rate sensor in the low-frequency band on the overall yaw rate YRfs.

[0276] That is, in high-pass filtering, the detection frequency fsr of the time series data for detecting yaw rate YRsr belongs to the low-frequency band (detection frequency fsr ≤ first frequency threshold f1: refer to...). Figure 9B In the case of YR, the detection filter gain Gsr, which is used to detect the yaw rate YRsr, is set to a fixed value (0).

[0277] Additionally, when the detected YR frequency fsr belongs to the middle frequency band (first frequency threshold f1 < detected YR frequency fsr < second frequency threshold f2: refer to...) Figure 9B In the case of ), the detection YR filter gain Gsr is set to a variable value that increases linearly up to (0~1) as the detection YR frequency fsr gradually increases.

[0278] Additionally, the detected YR frequency fsr belongs to the high-frequency band (detected YR frequency fsr => second frequency threshold f2: refer to...). Figure 9B In the case of ), a fixed value (1) is set as the detection YR filter gain Gsr.

[0279] Furthermore, the first frequency threshold f1 and the second frequency threshold f2 are set to appropriate values ​​based on the purpose of the yaw rate inference device 340 of the second variant.

[0280] Regarding the first filter (HPF) 351, in order to variably set the contribution ratio of the detected yaw rate YRsr according to the level of the detected YR frequency fsr, the detection YR filter gain Gsr is applied as the contribution ratio of the detected yaw rate YRsr.

[0281] Therefore, minimizing the impact of yaw error caused by the midpoint drift of the yaw rate sensor in the low frequency band on the overall yaw rate YRfs helps to improve the accuracy of the overall yaw rate YRfs.

[0282] The output data of the first filter (HPF) 351 is sent to the integration unit 345.

[0283] On the other hand, the second filter (LPF) 353 takes into account the time-series data of the lane yaw rate YRln of vehicle 1, performs a prescribed low-pass filtering process on this time-series data (details will be explained later), and outputs the filtered time-series data. This low-pass filtering process is performed to reduce the impact on the overall yaw rate YRfs caused by the poor real-time response of the lane yaw rate YRln in the high-frequency band compared to the detected yaw rate YRsr (because the acquisition period of lane yaw angle and lane curvature is relatively long).

[0284] In other words, regarding low-pass filtering, the lane YR frequency fln presented in the time series data of lane yaw rate YRln belongs to the high-frequency band (fln≤f2: reference). Figure 9B In the case of YR, the lane filter gain Gln, which is the lane yaw rate YRln, is set to a fixed value (0).

[0285] Additionally, in lane YR, the frequency fln belongs to the mid-band (f1 < fln < f2: refer to...). Figure 9B In the case of ), the variable value Gln, which is the lane YR filter gain, is set to increase linearly up to (0~1) as the lane YR frequency fln gradually decreases.

[0286] Then, in lane YR, the frequency fln belongs to the low frequency band (fln≤f1: reference). Figure 9B In the case of ), a fixed value (1) is set as the lane YR filter gain Gln.

[0287] Regarding the second filter (LPF) 353, in order to variably set the contribution ratio of the lane yaw rate YRln in accordance with the high or low of the lane YR frequency fln, the lane YR filter gain Gln is applied as the contribution ratio of the lane yaw rate YRln.

[0288] Therefore, minimizing the impact of the poor instantaneous response of the lane yaw rate YRln in the high-frequency band compared to the detected yaw rate YRsr on the comprehensive yaw rate YRfs helps to improve the accuracy of the comprehensive yaw rate YRfs.

[0289] The output data of the second filter (LPF) 353 is sent to the integration unit 345.

[0290] Furthermore, the sum of the filter gains of the first filter (HPF) 351 and the second filter (LPF) 353 is as follows: Figure 9B As shown, it is set to 1 across the entire frequency band. This allows for mutual compensation of the shortcomings of both the detection yaw rate YRsr and the lane yaw rate YRln, while leveraging their respective advantages. As a result, the accuracy of the combined yaw rate YRfs can be expected to be further improved.

[0291] Integration unit 345 adds the time series data of the detected yaw rate YRsr, which is the output of the first filter (HPF) 351, and the time series data of the lane yaw rate YRln, which is the output of the second filter (LPF) 353, using a prescribed contribution ratio (refer to...). Figure 9B The "filter gain" shown integrates the two time series data. Thus, the integration unit 345 outputs a high-precision composite yaw rate YRfs, which integrates the detected yaw rate YRsr and the lane yaw rate YRln.

[0292] The complementary filter section 343 and the integration section 345 are equivalent to the "integrated yaw rate generation section" of the present invention.

[0293] [Operation of the yaw rate estimation device 340 in the second variation]

[0294] Next, refer to Figure 9A , Figure 9B Explain the operation of the yaw rate estimation device 340 in the second variation.

[0295] Here, the merging part 341, the multiplication part 331, and the addition part 333 (all refer to) are used. Figure 7 The method of inferring the lane yaw rate YRln using the combination of the two components is the same as that of the yaw rate inference device 320 in the first modification. Therefore, the operation description for inferring the lane yaw rate YRln is omitted. Instead of describing the operation of the yaw rate inference device 340 in the second modification, the operation description will focus on the operation of the complementary filter unit 343 and the integration unit 345.

[0296] The first filter (HPF) 351 of the complementary filter unit 343 takes into input the time series data of the detected yaw rate YRsr detected by the yaw rate sensor, performs a prescribed high-pass filtering on the time series data, and outputs the high-pass filtered time series data. This high-pass filtering is performed to reduce the time series data in the low-frequency band (refer to...). Figure 9B The purpose of this study is to investigate the impact of the yaw rate error caused by the midpoint drift of the yaw rate sensor on the overall yaw rate YRfs.

[0297] On the other hand, the second filter (LPF) 353 of the complementary filter unit 343 takes into input the time series data of the lane yaw rate YRln of the vehicle 1, applies a predetermined low-pass filter to the time series data, and outputs filtered time series data. This low-pass filter is used to reduce the lane yaw rate in the high-frequency band (refer to...). Figure 9B The purpose of this study is to assess the impact of the poor instantaneous response of the lane yaw rate YRln compared to the detected yaw rate YRsr on the overall yaw rate YRfs.

[0298] The integration unit 345 combines the time-series data of the detected yaw rate YRsr (output of the first filter (HPF)) 351 and the time-series data of the lane yaw rate YRln (output of the second filter (LPF)) 353) using a predetermined contribution ratio. As a result, the integration unit 345 outputs a high-precision composite yaw rate YRfs that combines the detected yaw rate YRsr and the lane yaw rate YRln.

[0299] The yaw rate estimation device 340 in the second modification uses the comprehensive yaw rate YRfs output by the integration unit 345 as the yaw rate of the vehicle 1.

[0300] According to the yaw rate inference device 340 of the second modification, it is possible to suppress the yaw rate in the low frequency band (see reference). Figure 9B The midpoint drift of the yaw rate sensor causes yaw angle error, and in the high-frequency band (refer to...) Figure 9B The lane yaw rate YRln has a poorer instantaneous response compared to the detected yaw rate YRsr, which affects the overall yaw rate YRfs. The result is that the accuracy of the overall yaw rate YRfs can be further improved.

[0301] [The configuration of the yaw rate estimation device 360 ​​in the third variation]

[0302] Next, refer to Figure 10A , Figure 10B The configuration of the yaw rate estimation device 360 ​​in the third variation is explained.

[0303] Figure 10A This is a functional block diagram showing the approximate configuration of the yaw rate estimation device 360 ​​in the third variation. Figure 10B This is a diagram showing the lane length-gain characteristics of the judgment unit 361 of the yaw rate estimation device 360 ​​in the third modification example.

[0304] The yaw rate estimation device 360 ​​of the third modification, in addition to the comprehensive yaw rate generation function of the yaw rate estimation device 340 of the second modification, also has the following function: the contribution ratio of the lane yaw rate YRln can be variably set according to the length LL of the driving lane 93 identified in the lane recognition unit 313.

[0305] The reason for variably setting the contribution ratio of the lane yaw rate YRln based on the length LL of the driving lane 93 is as follows: When the lane length LL of the driving lane 93 is relatively short, the accuracy of inferring the lane yaw angle and lane curvature (the accuracy of inferring the lane yaw rate YRln) decreases. Therefore, the aim is to reduce the contribution ratio of the lane yaw rate YRln when the lane length LL of the driving lane 93 is relatively short, thereby improving the accuracy of the overall yaw rate YRfs.

[0306] Furthermore, the yaw rate estimation device 360 ​​of the third modification is the same as the yaw rate estimation devices 320 and 340 of the first and second modifications, which are based on the basic concept of the present invention.

[0307] To achieve the function of variably setting the contribution ratio of the lane yaw rate YRln, the yaw rate inference device 360 ​​of the third modification example is as follows: Figure 10A As shown, it is configured to include the lane recognition unit 313 (see reference). Figure 5 ), judgment unit 361, and comprehensive yaw rate generation unit 363.

[0308] The lane recognition unit 313 described above is based on the information acquisition unit 311 (refer to...) Figure 5 The information obtained from the front image of vehicle 1 is used to identify the driving lane 93 drawn on the driving path 91 of vehicle 1 (refer to the driving lane 93 drawn on the front image 91 of vehicle 1). Figure 6 In addition to its basic functions of recognizing the curvature of the driving lane 93, the system also has the function of recognizing the continuous length of the identified driving lane 93, i.e., the lane length LL. Furthermore, if the driving lane 93 cannot be recognized by the lane recognition unit 313, the lane length LL of the driving lane 93 is considered to be zero.

[0309] The information of the lane length LL of the driving lane 93 identified by the lane recognition unit 313 is sent to the judgment unit 361.

[0310] The determination unit 361 determines whether the lane length LL of the driving lane 93 identified by the lane recognition unit 313 is within the specified first lane length threshold LLth1 (refer to...). Figure 10B Below that. Furthermore, if the lane length LL identified by the lane recognition unit 313 exceeds the first lane length threshold LLth1, the determination unit 361 further determines whether the lane length LL is within the predetermined second lane length threshold LLth2 (see reference). Figure 10B )the following.

[0311] The judgment result of the driving lane 93 based on the judgment unit 361 is sent to the comprehensive yaw rate generation unit 363.

[0312] The determination result of the determination unit 361 on the lane length LL of the driving lane 93 is that the lane length LL is determined to be at the first lane length threshold LLth1 (refer to...). Figure 10B In the following cases, the integrated yaw rate generation unit 363 sets the value of the lane length gain GLL to a fixed value (0) that indicates that the lane yaw rate YRln is invalid.

[0313] Furthermore, the determination result of the determination unit 361 on the lane length LL of the driving lane 93 is that the lane length LL is determined to exceed the first lane length threshold LLth1 and be lower than the second lane length threshold LLth2 (refer to...). Figure 10B In the case of lane length gain GLL, the integrated yaw rate generation unit 363 sets the value of lane length gain GLL to a variable value (0-1: a value greater than 0 and less than 1) based on lane length LL, and the lane yaw rate YRln is a valid value.

[0314] Then, the determination result of the determination of the lane length LL of the driving lane 93 by the determination unit 361 is that the lane length LL is determined to be the second lane length threshold LLth2 (refer to...). Figure 10B In the above cases, the integrated yaw rate generation unit 363 sets the value of the lane length gain GLL to a fixed value (1) that indicates that the lane yaw rate YRln is effective and particularly excellent.

[0315] Next, refer to Figure 10B The configuration of the integrated yaw rate generation unit 363 is described, which allows the contribution ratio of the lane yaw rate YRln to be variably set according to the length LL of the driving lane 93 identified in the lane recognition unit 313.

[0316] like Figure 10BAs shown, the integrated yaw rate generation unit 363 stores the values ​​of the lane length gain GLL relative to the lane length LL of the driving lane 93 and establishes a lane length-lane length gain table 365.

[0317] like Figure 10B As shown, when the lane length LL of driving lane 93 is below the first lane length threshold LLth1, a fixed value (0) is associated with the lane length gain GLL in the lane length-lane length gain table 365.

[0318] In addition, in the lane length-lane length gain table 365, when the lane length LL of the driving lane 93 exceeds the first lane length threshold LLth1 but is below the second lane length threshold LLth2, the value of the lane length gain GLL is associated with a variable value that increases linearly up to (0 to 1) as the lane length LL increases.

[0319] Furthermore, in the lane length-lane length gain table 365, when the lane length LL of the driving lane 93 exceeds the second lane length threshold LLth2, a fixed value (1) is associated with the lane length gain GLL.

[0320] The contribution ratio of the yaw rate generation unit 363 to the lane yaw rate YRln, which is variably set according to the lane YR frequency fln, is multiplied by the lane length gain GLL, which is variably set according to the lane length LL of the driving lane 93 (here, GLL≤1). Thus, the contribution ratio of the lane yaw rate YRln is variably set in two stages according to the lane YR frequency fln and the lane length LL of the driving lane 93.

[0321] The result is that the factor based on low frequency bands (refer to) is suppressed as much as possible. Figure 9B The influence of the yaw rate sensor's midpoint drift and yaw rate error on the overall yaw rate YRfs, and the impact of high-frequency band (refer to) Figure 9B The lane yaw rate YRln has a poorer instantaneous response compared to the detected yaw rate YRsr, which affects the overall yaw rate YRfs. When the lane length LL of the driving lane 93 is relatively short, the contribution ratio of the lane yaw rate YRln is reduced, thus further improving the accuracy of the overall yaw rate YRfs.

[0322] Furthermore, when the lane length LL of the driving lane 93 is relatively short, and the contribution ratio of the lane yaw rate YRln (lane YR filter gain Gln) is reduced by a variable setting, the contribution ratio of the detected yaw rate YRsr (detection YR filter gain Gsr) is increased in conjunction with this. This is because, as described above, the sum of the filter gains of the first filter (HPF) 351 and the second filter (LPF) 353 is set to be 1 across all frequency bands.

[0323] [Operation of the yaw rate estimation device 360 ​​in the third variation]

[0324] Next, refer to Figure 10A , Figure 10B Explain the operation of the yaw rate estimation device 360 ​​in the third variation.

[0325] Lane recognition unit 313, etc. Figure 10A As shown, based on the information acquisition unit 311 (refer to...) Figure 5 The information obtained from the front image of vehicle 1 is used to identify the driving lane 93 drawn on the driving path 91 of vehicle 1 (refer to the driving lane 93 drawn on the front image 91 of vehicle 1). Figure 6 The system identifies the curvature of the driving lane 93 and the continuous length of the identified driving lane 93, i.e., the lane length LL.

[0326] The determination unit 36 ​​determines whether the lane length LL of the driving lane 93 identified by the lane recognition unit 313 is within the first lane length threshold LLth1 (refer to...). Figure 10B Below that. Furthermore, if the lane length LL identified by the lane recognition unit 313 exceeds the first lane length threshold LLth1, the determination unit 361 further determines whether the lane length LL is within the second lane length threshold LLth2 (see reference). Figure 10B )the following.

[0327] The yaw rate generation unit 363 variably sets the contribution ratio of the lane yaw rate YRln based on the judgment result of the judgment unit 361 on the lane length LL of the driving lane 93.

[0328] That is, when the lane length LL of the driving lane 93 identified by the lane recognition unit 313 is less than or equal to the first lane length threshold LLth1, the comprehensive yaw rate generation unit 363 sets the lane length yaw rate YRln contribution ratio (lane length gain GLL) to 0 (GLL=0) compared to the case where the lane length LL exceeds the first lane length threshold LLth1.

[0329] Furthermore, the yaw rate generation unit 363 determines the lane length LL of the driving lane 93 identified by the lane recognition unit 313, which exceeds the first lane length threshold LLth1 and the second lane length threshold LLth2 (see reference). Figure 10B In cases where the lane length LL exceeds the second lane length threshold LLth2 (GLL=1), the lane length gain GLL is variably set to reduce the contribution ratio of lane yaw rate YRln (0<GLL<1).

[0330] Furthermore, the yaw rate generation unit 363 determines that the lane length LL of the driving lane 93 identified by the lane recognition unit 313 exceeds the second lane length threshold LLth2 (refer to...). Figure 10B In the case of lane yaw rate YRln, the contribution ratio (lane length gain GLL) is set to a fixed value that is in accordance with the standard (GLL = 1).

[0331] Next, the contribution ratio of the yaw rate generation unit 363 to the lane yaw rate YRln, which is variably set according to the lane YR frequency fln, is multiplied by the lane length gain GLL, which is variably set according to the lane length LL of the driving lane 93. Thus, the contribution ratio of the lane yaw rate YRln, set according to the lane YR frequency fln, is corrected accordingly to the length of the lane length LL of the driving lane 93.

[0332] Here, the lane length gain GLL is set to a value not exceeding 1 (GLL≤1). Therefore, even when the lane length LL exceeds the second lane length threshold LLth2 (GLL=1), the contribution ratio of the lane yaw rate YRln, which is set according to the lane YR frequency fln, will not increase.

[0333] Next, the yaw rate generation unit 363 adds the time series data of the detected yaw rate YRsr and the time series data of the lane yaw rate YRln. Then, using a contribution ratio of the lane yaw rate YRln set according to the lane YR frequency fln and corrected according to the length LL of the driving lane 93, the two time series data of the detected yaw rate YRsr and the lane yaw rate YRln are integrated.

[0334] The integrated yaw rate generator 363 outputs a high-precision integrated yaw rate YRfs that combines the detected yaw rate YRsr and the lane yaw rate YRln.

[0335] The yaw rate estimation device 360 ​​of the third modification uses the comprehensive yaw rate YRfs, which integrates the detected yaw rate YRsr and the lane yaw rate YRln, as the yaw rate of the vehicle 1.

[0336] Based on the yaw rate inference device 360 ​​of the third variation, the yaw rate is suppressed as much as possible in the low frequency band (refer to...). Figure 9B The yaw angle error caused by the midpoint drift of the yaw rate sensor, and the error in the high-frequency band (refer to...) Figure 9B The influence of lane yaw rate YRln and detected yaw rate YRsr on the overall yaw rate YRfs is considered due to their relatively poor instantaneous response. Furthermore, given the relatively short lane length LL of lane 93, the contribution ratio of lane yaw rate YRln is reduced. This aims to minimize the impact on the overall yaw rate YRfs caused by decreased accuracy in inferring lane yaw angle and lane curvature. The result is a further improvement in the accuracy of the overall yaw rate YRfs.

[0337] [The effect of the yaw rate estimation device 300 of the present invention]

[0338] Next, the effects of the yaw rate estimation device 300 of the present invention will be explained with reference to the appropriate accompanying drawings.

[0339] Furthermore, the yaw rate estimation device 320 of the first modification, the yaw rate estimation device 340 of the second modification, and the yaw rate estimation device 360 ​​of the third modification all fall within the scope of the yaw rate estimation device 300 of the present invention.

[0340] Therefore, in the description of the yaw rate estimation device 300 of the present invention, the corresponding cases are marked with parentheses in the case of a certain modified example of the yaw rate estimation device.

[0341] Yaw rate estimation device 300 based on the first point of view Figure 5 As shown, the system includes: an information acquisition unit 311 that acquires information about the front image of the vehicle 1 and information about the vehicle speed; and a driving lane 93 (see reference 91) drawn on the driving path 91 of the vehicle 1 based on the acquired information about the front image of the vehicle 1. Figure 6 The lane recognition unit 313, which identifies the curvature of the driving lane 93, calculates the position of the vehicle 1 at reference coordinate 90 based on the identified curvature of the driving lane 93 and the acquired vehicle speed information. Figure 6The system includes: a direction change rate calculation unit 315 for the direction change rate Ψc of the driving lane 93; a yaw angle change rate calculation unit 317 for calculating the yaw angle of the vehicle 1 in the reference coordinate 90 relative to the direction change rate Ψv of the driving lane 93 based on the identified curvature of the driving lane 93 and the acquired vehicle speed information; and a lane yaw rate inference unit 319 for inferring the lane yaw rate, which infers the lane yaw rate YRln derived from the curvature of the driving lane 93 and the vehicle speed information based on the direction change rate Ψc of the driving lane 93 calculated by the direction change rate calculation unit 315 and the yaw angle of the vehicle 1 relative to the direction change rate Ψv of the driving lane 93 calculated by the yaw angle change rate calculation unit 317.

[0342] The yaw rate estimation device 300 based on the first viewpoint uses the estimated lane yaw rate YRln as the yaw rate of the vehicle 1.

[0343] In the yaw rate inference device 300 based on the first viewpoint, the information acquisition unit 311 acquires information about the forward image of the vehicle 1 and information about the vehicle speed. The lane recognition unit 313 identifies the driving lane 93 drawn on the driving path 91 of the vehicle 1 and the curvature of the driving lane 93 based on the acquired information about the forward image of the vehicle 1. The direction change rate calculation unit 315 calculates the direction change rate Ψc of the driving lane 93 in the reference coordinates 90 of the vehicle 1 based on the identified curvature of the driving lane 93 and the acquired vehicle speed information. The yaw rate change rate calculation unit 317 calculates the yaw rate change rate Ψv of the vehicle 1 in the reference coordinates 90 relative to the direction of the driving lane 93 based on the identified curvature of the deleted driving lane 93 and the acquired vehicle speed information. The lane yaw rate inference unit 319 infers the lane yaw rate YRln, which is derived from the curvature of the lane 93 and the vehicle speed of the vehicle 1, based on the direction change rate Ψc of the driving lane 93 calculated by the direction change rate calculation unit 315 and the yaw rate change rate calculation unit 317.

[0344] The yaw rate estimation device 300 based on the first viewpoint uses the lane yaw rate YRln inferred by the lane yaw rate estimation unit 319 as the yaw rate of the vehicle 1.

[0345] According to the yaw rate estimation device 300 based on the first viewpoint, the lane yaw rate YRln is estimated based on the curvature of the driving lane 93 drawn on the driving path 91 of the vehicle 1 and the vehicle speed of the vehicle 1. The estimated lane yaw rate YRln is used as the yaw rate of the vehicle 1. Therefore, the yaw rate reflecting the yaw motion of the vehicle 1 that changes over time can be estimated with high accuracy.

[0346] Furthermore, the yaw rate estimation device 300 based on the second viewpoint can also be configured as follows, based on the yaw rate estimation device 300 based on the first viewpoint: the lane recognition unit 313 is associated with the trajectory of the driving lane 93 drawn on the driving path 91 of the vehicle 1 and an approximate curve composed of an nth degree polynomial (here, n is an integer of 2 or more), thereby recognizing the driving lane 93 and the curvature of the driving lane 93; the direction change rate calculation unit 315 calculates the curvature of the driving lane 93 based on the second degree coefficient of the above-mentioned nth degree polynomial; and the yaw rate change rate calculation unit 317 calculates the direction of the yaw angle of the vehicle 1 relative to the driving lane 93 based on the first degree coefficient of the above-mentioned nth degree polynomial.

[0347] According to the yaw rate estimation device 300 based on the second viewpoint, the direction change rate calculation unit 315 calculates the curvature of the driving lane 93 based on the quadratic coefficients of the nth degree polynomial representing the trajectory of the driving lane 93 drawn on the driving path 91 of the vehicle 1, and the yaw rate change rate calculation unit 317 calculates the direction of the yaw angle of the vehicle 1 relative to the driving lane 93 based on the first degree coefficients of the aforementioned nth degree polynomial. Therefore, in addition to the effect of the yaw rate estimation device 300 based on the first viewpoint, it is also possible to properly obtain information that forms the basis for estimating the lane yaw rate YRln.

[0348] Furthermore, the yaw rate estimation device 300 based on the third viewpoint can also be configured as follows, based on the yaw rate estimation device 300 based on the second viewpoint: the lane recognition unit 313 calculates the above-mentioned nth degree polynomial based on (n+1) or more consecutive time series values ​​including the attention value of the trajectory of the driving lane 93, and the yaw rate change calculation unit 317 calculates the yaw rate change of the vehicle 1 based on the first degree coefficient of the above-mentioned nth degree polynomial.

[0349] According to the yaw rate estimation device 300 based on the third viewpoint, the yaw rate change calculation unit 317 calculates the yaw rate change of the vehicle 1 based on the first-order coefficient of the nth-order polynomial obtained above. Therefore, in addition to the effect of the yaw rate estimation device 300 based on the second viewpoint, it is possible to obtain more appropriate information that forms the basis for estimating the lane yaw rate YRln.

[0350] Furthermore, the yaw rate estimation device 300 based on the fourth viewpoint (the yaw rate estimation device 320 of the first modification) can, based on the yaw rate estimation device 300 based on the third viewpoint, employ a low-pass filter 325 (see reference 325) that also extracts the low-frequency component of the time-series signal of the rate of change of the yaw angle of the vehicle 1 calculated by the yaw rate change calculation unit 317. Figure 7 The composition of ).

[0351] According to the yaw rate estimation device 300 based on the fourth viewpoint (the yaw rate estimation device 320 of the first modification), it also includes a low-pass filter 325 for extracting the low-frequency component of the time series signal of the yaw rate change rate of the vehicle 1 calculated by the yaw rate change rate calculation unit 317. Therefore, in addition to the effect of the yaw rate estimation device 300 based on the third viewpoint, it is also possible to remove high-frequency noise components and properly infer the yaw motion of the vehicle 1.

[0352] Furthermore, the yaw rate estimation device 300 based on the fifth viewpoint (the yaw rate estimation device 320 of the first modification) can also be configured as follows, based on the yaw rate estimation device 300 based on one of the first to fourth viewpoints: it further includes a blind spot processing unit 327 (see reference) that performs blind spot processing on the signal of the curvature of the driving lane identified by the lane recognition unit. Figure 7 The direction change rate calculation unit 315 calculates the direction change rate of the driving lane 93 in the reference coordinate 90 of the vehicle 1 based on the curvature of the driving lane 93 after the above-mentioned blind spot processing and the information of the vehicle speed obtained.

[0353] According to the yaw rate estimation device 300 based on the fifth viewpoint (yaw rate estimation device 320 of the first modification), the direction change rate calculation unit calculates the direction change rate of the vehicle 1 in the driving lane 93 in the reference coordinate 90 based on the curvature of the driving lane 93 after the above-mentioned blind spot processing and the obtained vehicle speed information. Therefore, in addition to the effect of the yaw rate estimation device 300 based on one of the first to fourth viewpoints, it can also remove the noise near the midpoint of the steering angle mixed in with the signal of the curvature of the driving lane, and appropriately infer the yaw rate of the vehicle 1 that reflects the yaw motion of the vehicle 1 that changes over time.

[0354] Furthermore, the yaw rate estimation device 300 based on the sixth viewpoint (the yaw rate estimation device 340 of the second modification) can also adopt the following configuration based on the yaw rate estimation device 300 based on one of the first to fifth viewpoints: the information acquisition unit 311 also acquires information on the yaw rate of the vehicle 1 detected by the yaw rate sensor 30, and the yaw rate estimation device 300 based on the sixth viewpoint also includes a comprehensive yaw rate generation unit (343, 345). The comprehensive yaw rate generation unit generates a comprehensive yaw rate YRfs by adding the detection value of the yaw rate sensor 30, i.e., the detected yaw rate YRsr, and the estimation value of the lane yaw rate estimation unit 319, i.e., the lane yaw rate YRln, with a predetermined contribution ratio, and uses the generated comprehensive yaw rate YRfs as the yaw rate of the vehicle 1.

[0355] According to the yaw rate estimation device 300 based on the sixth viewpoint (the yaw rate estimation device 340 of the second modification), the comprehensive yaw rate YRfs generated by adding the detected yaw rate YRsr and the lane yaw rate YRln with a predetermined contribution ratio is used as the yaw rate of the vehicle 1. Therefore, in addition to the effect of the yaw rate estimation device 300 based on one of the first to fifth viewpoints, the estimation accuracy of the yaw rate reflecting the yaw motion of the vehicle 1 that changes over time can also be improved.

[0356] Furthermore, the yaw rate estimation device 300 based on the seventh viewpoint (the yaw rate estimation device 340 of the second modification) can also adopt the following configuration based on the yaw rate estimation device 300 based on the sixth viewpoint: the information acquisition unit 311 also acquires information on the frequency of the signal of the detected yaw rate YRsr (detection YR frequency fsr) and the frequency of the signal of the lane yaw rate YRln (lane YR frequency fln), and integrates the information from the yaw rate generation unit (343, 345) as follows: Figure 9B As shown, in the frequency band (high frequency band) where the frequency of the signal detecting yaw rate YRsr (detection YR frequency fsr) exceeds the predetermined second frequency threshold f2, the contribution ratio of the detected yaw rate YRsr is increased relative to the contribution ratio of the lane yaw rate YRln. On the other hand, in the frequency band (low frequency band) where the frequency of the signal detecting lane yaw rate YRln (lane YR frequency fln) is lower than the predetermined first frequency threshold f1, the contribution ratio of the lane yaw rate YRln is increased relative to the contribution ratio of the detected yaw rate YRsr.

[0357] Here, in the high-frequency band where the frequency of the signal detecting the yaw rate YRsr (detection frequency fsr) exceeds the specified second frequency threshold f2, there is concern about the impact on the overall yaw rate YRfs caused by the poor instantaneous response of the lane yaw rate YRln in the high-frequency band compared to the detected yaw rate YRsr (because the acquisition period of lane yaw angle and lane curvature is relatively long).

[0358] On the other hand, in the low-frequency band where the frequency of the lane yaw rate YRln signal (lane YR frequency fln) is below the specified first frequency threshold f1, there is concern about the impact on the overall yaw rate YRfs caused by yaw error based on the midpoint drift of the yaw rate sensor in the low-frequency band.

[0359] Therefore, the yaw rate estimation device 300 based on the seventh viewpoint (the yaw rate estimation device 340 of the second modification) adopts the following configuration: the integrated yaw rate generation unit (343, 345) increases the contribution ratio of the detected yaw rate YRsr to the lane yaw rate YRln in the frequency band (high frequency band) where the frequency of the detected yaw rate YRsr signal (detection YR frequency fsr) exceeds a predetermined second frequency threshold f2; on the other hand, it increases the contribution ratio of the lane yaw rate YRln to the lane yaw rate YRln in the frequency band (lane YR frequency fln) where the frequency of the lane yaw rate YRln signal (lane YR frequency fln) is lower than a predetermined first frequency threshold f1.

[0360] According to the yaw rate estimation device 300 based on the seventh viewpoint (the yaw rate estimation device 340 of the second modification), in addition to the effects of the yaw rate estimation device 300 based on the sixth viewpoint, it can also suppress the yaw rate in the low frequency band (see reference) as much as possible. Figure 9B Yaw angle error is caused by the midpoint drift of the yaw rate sensor, and also by errors in the high-frequency band (refer to...). Figure 9B The lane yaw rate YRln has a poorer instantaneous response compared to the detected yaw rate YRsr. These two factors affect the overall yaw rate YRfs.

[0361] The result is that the accuracy of the overall yaw rate YRfs can be further improved.

[0362] Furthermore, the yaw rate estimation device 300 based on the eighth viewpoint (the yaw rate estimation device 360 ​​of the third variation) can also be configured as follows, based on the yaw rate estimation device 300 based on the seventh viewpoint: it further includes a determination unit 361, which determines whether the lane length LL of the driving lane 93 identified by the lane recognition unit 31 is below a predetermined lane length threshold (the first lane length threshold LLth1 and the second lane length threshold LLth2). When the yaw rate generation unit 363 identifies the lane length LL of the driving lane 93 as being below the lane length thresholds LLth1 and LLth2, it further reduces the contribution ratio of the lane yaw rate YRln compared to the case where the lane length LL of the driving lane 93 is identified as exceeding the lane length thresholds LLth1 and LLth2.

[0363] According to the yaw rate estimation device 300 based on the eighth viewpoint (yaw rate estimation device 360 ​​of the third modification), when the lane length LL of the driving lane 93 is relatively short, the contribution ratio of the lane yaw rate YRln is reduced. Therefore, in addition to the effect of the yaw rate estimation device 300 based on the seventh viewpoint, the influence on the comprehensive yaw rate YRfs caused by the decrease in the estimation accuracy of lane yaw angle and lane curvature is suppressed as much as possible.

[0364] The result is that the accuracy of the overall yaw rate YRfs can be further improved.

[0365] [Other implementation methods]

[0366] The various embodiments described above illustrate specific examples of the invention. Therefore, these embodiments are not intended to limit the scope of the invention. This is because the invention can be implemented in various ways without departing from its spirit or key features.

[0367] For example, in the description of the yaw rate estimation device 300 of the present invention, an example is given of a method for capturing and acquiring image information of the vehicle 1 in front of, to the left and right sides of, and behind in the direction of travel using the camera 11, but the present invention is not limited to this example. As for the camera 11, any method can be used as long as it is at least able to capture and acquire image information of the vehicle 1 in front of the direction of travel.

Claims

1. A yaw angular velocity inferring apparatus characterized by comprising: Possessing: an information acquisition unit that acquires information of an image of a front of a host vehicle and information of a vehicle speed; a lane recognition unit that recognizes a travel lane drawn on a travel path of the host vehicle and a curvature of the travel lane based on the acquired information of the image of the front of the host vehicle; a direction change rate calculation unit that calculates a change rate of a direction of the travel lane in a reference coordinate of the host vehicle based on the recognized curvature of the travel lane and the acquired information of the vehicle speed; a yaw angle change rate calculation unit that calculates a change rate of a yaw angle of the host vehicle with respect to the direction of the travel lane in the reference coordinate of the host vehicle based on the recognized curvature of the travel lane and the acquired information of the vehicle speed; and a lane yaw angular velocity estimation unit that estimates a lane yaw angular velocity, which is a yaw angular velocity derived using the curvature of the travel lane and the information of the vehicle speed of the host vehicle, based on the change rate of the direction of the travel lane calculated by the direction change rate calculation unit and the change rate of the yaw angle of the host vehicle with respect to the direction of the travel lane calculated by the yaw angle change rate calculation unit, uses the estimated lane yaw angular velocity as a yaw angular velocity of the host vehicle.

2. The yaw angular velocity estimation device according to claim 1, wherein the lane recognition unit recognizes the travel lane by associating an approximation curve composed of an n-th degree polynomial with a trajectory of the travel lane drawn on the travel path of the host vehicle, recognizes the curvature of the travel lane based on a 2nd degree coefficient of the n-th degree polynomial, n being an integer of 2 or more, the direction change rate calculation unit calculates the change rate of the direction of the travel lane based on the recognized curvature and the acquired information of the vehicle speed, the yaw angle change rate calculation unit calculates the yaw angle of the host vehicle with respect to the direction of the travel lane based on a 1st degree coefficient of the n-th degree polynomial.

3. The yaw angular velocity estimation device according to claim 2, wherein the lane recognition unit calculates the n-th degree polynomial based on n+1 or more continuous time series values including a value of interest of the trajectory of the travel lane, the yaw angle change rate calculation unit calculates the change rate of the yaw angle of the host vehicle based on the calculated 1st degree coefficient of the n-th degree polynomial.

4. The yaw angular velocity estimation device according to claim 3, further comprising a low-pass filter that extracts a low frequency component of a time series signal of the change rate of the yaw angle of the host vehicle calculated by the yaw angle change rate calculation unit.

5. The yaw angular velocity estimation device according to any one of claims 1 to 4, further comprising a blind zone processing unit that performs blind zone processing with respect to a signal of the curvature of the travel lane recognized by the lane recognition unit, the direction change rate calculation unit calculates the change rate of the direction of the travel lane in the reference coordinate of the host vehicle based on the curvature of the travel lane after the blind zone processing and the acquired information of the vehicle speed. Possessing: an information acquisition unit that acquires information of an image of a front of a host vehicle and information of a vehicle speed; 6. A yaw angular velocity inferring apparatus characterized by comprising: ​ ​ a lane recognition unit that recognizes a travel lane drawn on a travel path of the host vehicle and a curvature of the travel lane on the basis of information on an image of a front of the host vehicle acquired; a direction change rate calculation unit that calculates a change rate of a direction of the travel lane in a reference coordinate of the host vehicle on the basis of the curvature of the travel lane recognized and information on the vehicle speed acquired; a yaw angle change rate calculation unit that calculates a change rate of a yaw angle of the host vehicle with respect to the direction of the travel lane in the reference coordinate of the host vehicle on the basis of the curvature of the travel lane recognized and information on the vehicle speed acquired; a lane yaw angular velocity estimation unit that estimates a lane yaw angular velocity, which is a yaw angular velocity derived from the curvature of the travel lane and the information on the vehicle speed of the host vehicle, on the basis of the change rate of the direction of the travel lane calculated by the direction change rate calculation unit and the change rate of the yaw angle of the host vehicle with respect to the direction of the travel lane calculated by the yaw angle change rate calculation unit; and a yaw angular velocity sensor that detects information on a yaw angular velocity of the host vehicle, the information acquisition unit further acquires information on the yaw angular velocity of the host vehicle detected by the yaw angular velocity sensor, the yaw angular velocity estimation device further includes a comprehensive yaw angular velocity generation unit that generates a comprehensive yaw angular velocity by adding a detected yaw angular velocity, which is a detection value of the yaw angular velocity sensor, and a lane yaw angular velocity, which is an estimation value of the lane yaw angular velocity estimation unit, at a prescribed contribution rate, and uses the generated comprehensive yaw angular velocity as the yaw angular velocity of the host vehicle.

7. The yaw angular velocity estimation device according to claim 6, wherein the information acquisition unit further acquires information on a frequency of a signal of the detected yaw angular velocity and a frequency of a signal of the lane yaw angular velocity, the comprehensive yaw angular velocity generation unit increases the contribution rate of the lane yaw angular velocity with respect to the detected yaw angular velocity in a frequency band in which the frequency of the signal of the detected yaw angular velocity exceeds a prescribed second frequency threshold value, and increases the contribution rate of the detected yaw angular velocity with respect to the lane yaw angular velocity in a frequency band in which the frequency of the signal of the lane yaw angular velocity is lower than a prescribed first frequency threshold value.

8. The yaw angular velocity estimation device according to claim 7, further comprising a determination unit that determines whether a lane length of the travel lane recognized by the lane recognition unit is equal to or less than a prescribed lane length threshold value, the comprehensive yaw angular velocity generation unit decreases the contribution rate of the lane yaw angular velocity more in a case where the lane length of the travel lane recognized is equal to or less than the lane length threshold value than in a case where the lane length of the travel lane recognized exceeds the lane length threshold value. ​ ​

Images