Rudder angle control device

Abstract

This invention provides a rudder angle control device comprising: a model prediction control unit (161c) that acquires a vehicle state quantity representing the motion state of the vehicle based on sensor values ​​from onboard sensors, predicts the vehicle's movement based on the vehicle state quantity, and calculates a rudder angle indication value for a steering actuator using the prediction result; an estimation unit (161a) that estimates the interference components of the rudder angle included in the vehicle state quantity and calculates a first rudder angle correction amount based on the estimation result; and a cross slope compensation unit (161b) that calculates a rudder angle to compensate for the cross slope angle of the road surface based on the vehicle state quantity, and calculates a second rudder angle correction amount based on the calculation result. The model prediction control unit (161c) corrects the rudder angle included in the vehicle state quantity used for predicting vehicle movement based on a third rudder angle correction amount that combines the first and second rudder angle correction amounts. Furthermore, the model prediction control unit (161c) outputs the rudder angle indication value corrected based on the third rudder angle correction amount to the steering actuator.

Description

Technical Field

[0001] This invention relates to a rudder angle control device for controlling the rudder angle of a vehicle. Background Technology

[0002] In recent years, measures aimed at providing sustainable transportation systems for vulnerable traffic participants have become increasingly active. To achieve this goal, research and development related to driver assistance technologies are dedicated to further improving traffic safety and convenience. As such devices, those that determine the auxiliary torque applied to the steering system in a manner that eliminates interference torque corresponding to changes in road conditions are known (see Patent Document 1). In the device described in Patent Document 1, the auxiliary torque is determined by feedback control based on the deviation between the steering wheel torque acting on the steering wheel and the steering torque detected by a steering torque sensor located midway through the steering system.

[0003] However, since road conditions vary to different degrees depending on the location, the device described in Patent Document 1, which determines the auxiliary torque through feedback control, may not achieve a high level of responsiveness to changes in road conditions.

[0004] Existing technical documents

[0005] Patent documents Patent document 1: Japanese Patent Application Publication No. 2002-154450 (JP2002-154450A). Summary of the Invention

[0006] A rudder angle control device according to one embodiment of the present invention includes: an acquisition unit that acquires a vehicle state quantity representing the vehicle's motion state based on sensor values ​​from onboard sensors; a prediction unit that predicts the vehicle's movement based on the vehicle state quantity acquired by the acquisition unit; a rudder angle indication unit that uses the prediction result obtained by the prediction unit to calculate a rudder angle indication value for a rudder actuator for the vehicle, thereby maintaining the vehicle's driving state along a target path; a first correction amount calculation unit that estimates an interference component of the vehicle's rudder angle based on the vehicle state quantity and calculates a first rudder angle correction amount based on the estimation result; and a second correction amount calculation unit that calculates a rudder angle to compensate for the cross slope angle of the road surface, which is part of the interference component, based on the vehicle state quantity, and calculates a second rudder angle correction amount based on the calculation result. The prediction unit corrects the vehicle's rudder angle included in the vehicle state quantity used to predict the vehicle's movement based on a third rudder angle correction amount that combines the first and second rudder angle correction amounts. The rudder angle indication unit outputs the rudder angle indication value corrected based on the third rudder angle correction amount to the rudder actuator. Attached Figure Description

[0007] The objectives, features, and advantages of the present invention are further illustrated by the following description of embodiments in conjunction with the accompanying drawings.

[0008] Figure 1 This is a diagram illustrating the structure of a vehicle control system having an embodiment of the rudder angle control device of the present invention; Figure 2 This is a block diagram showing the main structural components of the rudder angle control device; Figure 3A This is a block diagram illustrating the rudder angle control process; Figure 3B This is a detailed explanation. Figure 3A A block diagram detailing the rudder angle control unit; Figure 3C This diagram is used to illustrate the integration of rudder angle interference; Figure 4 It is shown by Figure 2 A flowchart illustrating an example of computational processing performed by the arithmetic unit of the controller; Figure 5A This is an example diagram illustrating a driving scenario for this vehicle; Figure 5B It is shown that... Figure 5A A diagram showing the rudder angle correction amount corresponding to the driving scenario; Figure 6A This is another example of a driving scenario for this vehicle; Figure 6B It is shown that... Figure 6A The diagram shows the rudder angle correction amount corresponding to the driving scenario. Detailed Implementation

[0009] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. One embodiment of the present invention provides a rudder angle control device that controls the rudder angle of the steering mechanism (e.g., power steering) of a vehicle, causing the vehicle to follow a target path (also referred to as a target trajectory). The rudder angle control device can be applied to both manually driven vehicles equipped with ADAS (Advanced Driver-Assistance Systems) and vehicles with autonomous driving capabilities, i.e., autonomous vehicles. However, for ease of explanation, the following example will focus on its application to autonomous vehicles.

[0010] Furthermore, in this embodiment, the vehicle equipped with the steering angle control device is sometimes distinguished from other vehicles and referred to as "this vehicle". This vehicle can be any of the following: an engine vehicle with an internal combustion engine as the driving source, an electric vehicle with a drive motor as the driving source, or a hybrid vehicle with both an engine and a drive motor as driving sources. This vehicle can operate not only in an automated driving mode that does not require driver intervention, but also in a manual driving mode based on driver input.

[0011] First, a general description of the structure of vehicles related to autonomous driving will be given. Figure 1 This is a block diagram illustrating the structure of a vehicle control system 100 of the present vehicle having a rudder angle control device according to an embodiment of the present invention. Figure 1 As shown, the vehicle control system 100 mainly includes a controller 10, an external sensor group 1 that is communicatively connected to the controller 10, an internal sensor group 2, an input / output device 3, a positioning unit 4, a map database 5, a navigation device 6, a communication unit 7, and a driving actuator AC.

[0012] External sensor group 1 is a collective term for multiple sensors (external sensors) that detect information about the vehicle's surroundings, i.e., external conditions. External sensor group 1 may include, for example, a lidar that measures the distance from the vehicle to surrounding obstacles by measuring the scattered light from the vehicle's omnidirectional illumination; a radar that detects other vehicles or obstacles around the vehicle by illuminating electromagnetic waves and detecting the reflected waves; and a camera mounted on the vehicle and equipped with imaging elements (image sensors) such as CCD (charge-coupled device) or CMOS (complementary metal-oxide-semiconductor) sensors to capture images of the vehicle's surroundings (front, rear, and sides).

[0013] Internal sensor group 2 is a collective term for multiple sensors (internal sensors) that detect the driving status of the vehicle. Internal sensor group 2 includes, for example, a vehicle speed sensor to detect the vehicle's speed, acceleration sensors to detect the vehicle's acceleration in the longitudinal (traveling direction) and lateral (lane width) directions (lateral acceleration), a speed sensor to detect the rotational speed of the driving source, and a yaw rate sensor to detect the angular velocity of the vehicle's center of gravity about its vertical axis. Sensors that detect driver operations in manual driving mode, such as operation of the accelerator pedal, brake pedal, and steering wheel, are also included in internal sensor group 2.

[0014] The input / output device 3 is a general term for devices that input commands to the driver or output information to the driver. Examples of input / output devices 3 include: various switches for the driver to input various commands through operation of control components, microphones for the driver to input commands by voice, displays that provide information to the driver via images, and speakers that provide information to the driver by sound.

[0015] The positioning unit (GNSS (Global Navigation Satellite System) unit) 4 has a positioning sensor that receives positioning signals transmitted from positioning satellites. Positioning satellites are artificial satellites such as GPS (Global Positioning System) satellites and quasi-zenith satellites. The positioning unit 4 uses the positioning information received by the positioning sensor to determine the vehicle's current position (latitude, longitude, and altitude).

[0016] Map database 5 is a device that stores general map information used by navigation device 6, and may be composed of, for example, a hard disk or semiconductor components. The map information includes road location information, road shape (curvature, etc.) information, and the location information of intersections or forks in the road. It should be noted that the map information stored in map database 5 is different from the high-precision map information stored in storage unit 12 of controller 10.

[0017] The navigation device 6 is, for example, a device that searches for a path on the road leading to a destination input by the driver and provides driving guidance along the searched path. The input of the destination and the driving guidance along the searched path are performed via the input / output device 3. The path search is based on the current position of the vehicle determined by the positioning unit 4, the position of the input destination, and map information stored in the map database 5. Alternatively, the current position of the vehicle can be determined using the detection values ​​of the external sensor group 1, and a path can be searched based on this current position and high-precision map information stored in the storage unit 12.

[0018] Communication unit 7 communicates with various servers (not shown) via wireless communication networks, including the Internet and mobile phone networks, to periodically or at any time obtain map information, driving history information, and traffic information from the servers. In addition to obtaining driving history information, communication unit 7 can also send the vehicle's driving history information to the servers. The network includes not only public wireless communication networks but also closed communication networks set up for each designated management area, such as wireless LAN, Wi-Fi (registered trademark), and Bluetooth (registered trademark). The obtained map information is output to map database 5 and storage unit 12 to update the map information.

[0019] An actuator (AC) is a driving actuator used to control the movement of the vehicle. When the driving source is an engine, the actuator AC includes a throttle actuator for adjusting the opening of the engine's throttle valve (throttle opening). When the driving source is a drive motor, the drive motor is included in the actuator AC. Braking actuators that operate the vehicle's braking system and steering actuators that drive the steering mechanism are also included in the actuator AC.

[0020] The controller 10 is composed of an electronic control unit (ECU). More specifically, the controller 10 is configured as a computer having an arithmetic unit 11 such as a CPU (microprocessor), a storage unit 12 such as ROM (read-only memory) and RAM (random access memory), and other peripheral circuits (not shown) such as I / O interfaces. It should be noted that multiple ECUs with different functions, such as an engine control ECU, a drive motor control ECU, and a braking device ECU, can be separately configured, but... Figure 1 For convenience, controller 10 is shown as a collection of these ECUs.

[0021] Storage unit 12 stores high-precision, detailed map information for autonomous driving. This high-precision map information includes road location information, road shape (curvature, etc.), road slope information, location information of intersections or forks in the road, the type or location information of road markings such as white lines, the number of lanes (driving lanes), lane width, and the location information of each lane (center position of the lane, information of lane boundary lines), location information of landmarks (traffic lights, signs, buildings, etc.) used as markers on the map, and information on road surface contours such as road surface undulations. The high-precision map information stored in storage unit 12 can include high-precision map information obtained from outside the vehicle via communication unit 7, or high-precision map information generated by the vehicle itself using detection values ​​from external sensor group 1 or detection values ​​from external sensor group 1 and internal sensor group 2. Storage unit 12 can also store various control programs, thresholds used in the programs, and other information.

[0022] The computing unit 11 includes a vehicle position recognition unit 13, an external recognition unit 14, an action plan generation unit 15, and a driving control unit 16 as its functional structure.

[0023] The vehicle position recognition unit 13 identifies the vehicle's position on the map (vehicle position) based on the vehicle's position information obtained from the positioning unit 4 and the map information from the map database 5. Alternatively, it can use high-precision map information stored in the storage unit 12 and surrounding information detected by the external sensor group 1 to identify the vehicle's position, thereby enabling high-precision position recognition. Furthermore, it can also calculate the vehicle's movement information (movement direction, movement distance) based on the detection values ​​from the internal sensor group 2, thereby identifying the vehicle's position. It should be noted that when the vehicle's position can be determined using external sensors installed on or beside the road, the vehicle's position can also be identified by communicating with those sensors via the communication unit 7.

[0024] The external identification unit 14 identifies the external conditions around the vehicle based on signals from the external sensor group 1, such as cameras, lidar, and radar. For example, it identifies the position, speed, or acceleration of surrounding vehicles (vehicles in front and behind) traveling around the vehicle, the position of surrounding vehicles parked or stationary around the vehicle, and the position or state of other objects, and generates landmark information. Other objects include signs, traffic lights, roads, buildings, guardrails, utility poles, billboards, pedestrians, bicycles, etc. Road markings (white lines, etc.) and stop lines on the road surface are also included among other objects (roads). The state of other objects includes the color of traffic lights (red, blue, yellow), the speed and direction of pedestrians and bicycles, etc. A portion of stationary objects among other objects constitutes a landmark that serves as an indicator of location on a map; the external identification unit 14 also identifies the location and category of the landmark.

[0025] The action plan generation unit 15 generates, for example, the vehicle's driving trajectory (target path) from the current moment to a predetermined time elapsed on the path searched by the navigation device 6, the high-precision map information stored in the storage unit 12, the vehicle's position identified by the vehicle position recognition unit 13, and the external conditions identified by the external environment recognition unit 14. When multiple trajectories may exist as candidate paths for the target path on the path searched by the navigation device 6, the action plan generation unit 15 selects the best trajectory from among them that complies with laws and regulations and meets the criteria of efficient and safe driving, and generates the selected trajectory as the target path.

[0026] Then, the action plan generation unit 15 generates an action plan corresponding to the generated target path. The action plan generation unit 15 generates various action plans corresponding to driving modes such as overtaking (passing ahead of a vehicle), lane changing (changing lanes), following (following ahead of a vehicle), lane keeping (maintaining lane position without deviating from the lane), deceleration, and acceleration. When generating the target path, the action plan generation unit 15 first determines the driving mode and generates the target path based on the driving mode.

[0027] The driving control unit 16 controls each actuator AC to enable the vehicle to travel along the target path generated by the action plan generation unit 15 in automatic driving mode. For example, the driving control unit 16 considers the driving resistance determined by road gradient and other factors in automatic driving mode, and calculates the required driving force to obtain the target acceleration per unit time calculated by the action plan generation unit 15. Then, for example, feedback control is performed on the actuator ACs in such a way that the actual acceleration detected by the internal sensor group 2 becomes the target acceleration. That is, the drive actuator ACs are controlled to make the vehicle travel at the target speed and target acceleration.

[0028] Furthermore, the driving control unit 16 calculates the optimal steering angle for the vehicle to follow the target path based on vehicle state parameters observed by the internal sensor group 2 and other sensors during automatic driving mode. Then, it outputs a steering angle indication signal corresponding to the calculated steering angle to control the steering actuator AC.

[0029] It should be noted that in manual driving mode, the driving control unit 16 controls each actuator AC according to the driving commands (steering operations, etc.) from the driver obtained by the internal sensor group 2.

[0030] However, in lane-keeping maneuvers, the steering actuator (hereinafter also referred to as the steering actuator) is controlled to move the vehicle to a target position in the lane width direction. However, in the event of disturbances such as changes in road surface slope (changes in the gradient in the lane width direction) or strong crosswinds, there is a possibility that the vehicle's position in the lane width direction may deviate from the target position, or that the vehicle's orientation may deviate from the direction of travel. Therefore, in this embodiment, a steering angle control device is configured to eliminate the positional deviation and orientation deviation of the vehicle that occur during driving, as follows.

[0031] Figure 2 This is a block diagram showing the main structural components of the rudder angle control device 50 according to this embodiment. As an example, the rudder angle control device 50 is configured as follows: Figure 1 This is part of the functionality of the controller 10. The controller 10 is connected to a camera 1a, a steering angle sensor 2a, a steering angular velocity sensor 2b, a steering torque sensor 2c, an IMU (Inertial Measurement Unit) 2d, a navigation device 6, and a steering actuator AC1. It should be noted that the aforementioned steering angle sensor 2a, steering angular velocity sensor 2b, steering torque sensor 2c, and IMU 2d constitute... Figure 1 It is part of the internal sensor group 2.

[0032] Camera 1a is a single-lens reflex camera with a shooting element, consisting of... Figure 1 It is part of the external sensor group 1. Camera 1a can be a stereo camera. Camera 1a is mounted, for example, at a predetermined position at the front of the vehicle, and continuously captures images of the space in front of the vehicle to obtain images of objects (camera images). Objects include road markings on lanes on a designated road. It should be noted that objects can also be detected by radar or lidar, either in place of camera 1a or together with camera 1a.

[0033] The steering angle sensor 2a, for example, detects the rotation angle (steering angle) of the steering shaft connected to a steering wheel (not shown). The steering angular velocity sensor 2b detects the rotational angular velocity (steering angular velocity) of the steering shaft. The steering angular velocity can also be simply referred to as the rudder angular velocity.

[0034] The steering torque sensor 2c detects the driver's steering input, and more specifically, detects the steering torque acting on the steering wheel. For example, the steering angle detected by the steering angle sensor 2a when the steering wheel is rotated to the left (counterclockwise) from the neutral position is set to a positive value, and the steering angle detected by the steering angle sensor 2a when the steering wheel is rotated to the right (clockwise) from the neutral position is set to a negative value.

[0035] IMU2d detects the translational and rotational movements of the vehicle along three axes (X-axis, Y-axis, and Z-axis). It should be noted that the X-axis corresponds to the vehicle's forward / backward direction, the Y-axis corresponds to the vehicle's left-right direction, and the Z-axis corresponds to the vertical direction.

[0036] The controller 10 includes a path error calculation unit 131, a target calculation unit 141, a travel path calculation unit 151, a target path calculation unit 152, and a rudder angle control unit 161, which are configured by the arithmetic unit 11 ( Figure 1 The controller 10 has a functional structure. In addition, as mentioned above, the controller 10 has a storage unit 12.

[0037] It should be noted that the path error calculation unit 131 can also be part of the vehicle position recognition unit 13. The target calculation unit 141 can also be part of the external recognition unit 14. The driving path calculation unit 151 and the target path calculation unit 152 can also be part of the action plan generation unit 15. The rudder angle control unit 161 can also be part of the driving control unit 16.

[0038] The path error calculation unit 131 compares the position and orientation of the vehicle identified by the vehicle position recognition unit 13 with the target path set by the target path calculation unit 152 (described later), and calculates the lateral position deviation and azimuth deviation of the vehicle relative to the target path on the side of the vehicle.

[0039] The path error calculation unit 131 first identifies the position and shape of the road markings for the designated lane based on the camera image from camera 1a, and then identifies the lane based on the identification result. Next, the path error calculation unit 131 compares the identified lane's position, angle, and shape with the target path set by the target path calculation unit 152 (described later), and calculates the deviation between the vehicle's position and its position on the target path (lane center) on the side of the vehicle as the path lateral position deviation. Additionally, the path error calculation unit 131 calculates the deviation between the vehicle's orientation and the azimuth angle of the target path on the side of the vehicle as the path azimuth angle deviation.

[0040] The path error calculation unit 131 can also use the vehicle's position and orientation identified based on the high-precision map information stored in the storage unit 12 and the vehicle's surrounding information detected by the external sensor group 1, or the vehicle's position and orientation determined by the positioning unit 4, to calculate the path lateral position deviation and path azimuth angle deviation.

[0041] The object calculation unit 141 calculates information representing objects existing around the vehicle. Based on signals input from the external sensor group 1 such as camera 1a, lidar, and radar, the object calculation unit 141 identifies objects including moving objects such as other vehicles, bicycles, and pedestrians, as well as stationary objects (also referred to as ground features) such as guardrails and signs, and outputs object information representing the identified objects.

[0042] The driving route calculation unit 151 calculates (searches) a driving route (called a basic driving route) based on the current position of the vehicle determined by the positioning unit 4, the location of the destination input by the driver, and map information stored in the map database 5. The calculation of the basic driving route is the same as the path search of the navigation device 6. The driving route calculation unit 151 may also obtain the route set by the navigation device 6 as the basic driving route.

[0043] The target path calculation unit 152 sets a target position in the lane width direction that the vehicle should pass through on the basic driving path based on the basic driving path calculated by the driving path calculation unit 151 and the external conditions identified by the external conditions identification unit 14. When the vehicle is, for example, performing lane-keeping driving, the target path calculation unit 152 repeatedly sets the target position along the direction of travel. As a result, a target path (a trajectory obtained by connecting the target positions) is generated along the basic driving path.

[0044] It should be noted that when the external identification unit 14 identifies obstacles such as utility poles or parked vehicles in front of the vehicle's direction of travel, the target path calculation unit 152 uses the object information output from the object calculation unit 141 to set a target position so that when the vehicle passes the side of the obstacle, the distance between the vehicle and the obstacle in the lane width direction is not less than a certain distance. Furthermore, when a lane change instruction from the driver is input via the direction indicator (not shown), the target path calculation unit 152 sets a target position so that the vehicle's driving position gradually moves towards the center of the lane where the destination is changed along the direction of travel.

[0045] For example, when the lane keeping assist function is active, the rudder angle control unit 161 controls the rudder angle of the vehicle via the steering actuator AC1, so that the vehicle follows the target path. Specifically, the rudder angle control unit 161 calculates the rudder angle required to make the vehicle's position follow the target path.

[0046] The rudder angle control unit 161 obtains the target path generated by the target path calculation unit 152. Additionally, the rudder angle control unit 161 obtains vehicle-related design information (hereinafter referred to as vehicle characteristic information) from the storage unit 12. The vehicle characteristic information includes the vehicle's mass [kg] and yaw moment of inertia [kgm]. 2 [ ], the distance between the center of gravity G and the front axle [m], the distance between the center of gravity G and the rear axle lr [m], the equivalent lateral stiffness of a single front wheel [N / rad], the equivalent lateral stiffness of a single rear wheel [N / rad], the stability coefficient [-], etc.

[0047] Furthermore, the rudder angle control unit 161 also acquires vehicle status quantities. These vehicle status quantities include vehicle speed (body speed), yaw rate (yaw ratio), rudder angle (front wheel rudder angle), gravitational acceleration, rudder angle velocity, and vehicle orientation, obtained based on the output values ​​of the sensors constituting the internal sensor group 2 or calculated using the sensor output values. Additionally, the vehicle status quantities also include path lateral position deviation, path azimuth deviation, and yaw rate deviation.

[0048] As an example, the vehicle's orientation is calculated based on the direction of extension of the target path and the vehicle's length direction (sometimes referred to as longitudinal direction) identified from camera images from camera 1a, etc. The lateral position deviation of the path, as described above, is the offset of the vehicle's position from the target path in the lane width direction. The azimuth deviation of the path is the offset angle of the vehicle's orientation (vehicle orientation) relative to the target path. The yaw rate deviation is the deviation between the yaw rate detected by the IMU2d included in the internal sensor group 2 and the target yaw rate (= vehicle speed × path curvature). The path curvature is the curvature of the target path ahead of the vehicle's direction of travel, calculated, for example, by the steering angle control unit 161.

[0049] The rudder angle control unit 161 uses a state estimation model described later to estimate state quantities that cannot be observed using the internal sensor group 2. Specifically, the rudder angle control unit 161 estimates the rudder angle disturbance δd [rad] and the vehicle sideslip angle β [rad], and calculates the effective front wheel rudder angle δ^ [rad] excluding the rudder angle disturbance δd. "^" indicates an estimated value. The relationship between the front wheel rudder angle δ and the effective front wheel rudder angle δ^ and rudder angle disturbance δd is expressed by the formula δ = δ^ + δd. The rudder angle disturbance δd is the disturbance component included in the vehicle's rudder angle (observed value), referring to a rudder angle that does not affect the vehicle's behavior, such as steering correction for the cross slope angle. The cross slope angle refers to the slope in the lane width direction (road lateral slope). Steering corrections caused by crosswinds or midpoint offset of the steering device can also be included in the rudder angle disturbance δd. The vehicle sideslip angle β is the offset angle between the vehicle's speed direction and the vehicle's body direction.

[0050] The rudder angle control unit 161 inputs the acquired vehicle state variables and vehicle characteristic information into the driving simulation model (hereinafter referred to as the predictive model). Using the predictive model, the rudder angle control unit 161 calculates the optimal rudder angle (described later as the optimal rudder angle series) for the future driving position of the vehicle following the target path through model predictive control. Model predictive control is prior art. Model predictive control is one of the control methods that uses predictive estimation of the controlled object to calculate the optimal control input. In model predictive control, an optimizer is used to evaluate the actions of the predictive model and calculate the optimal control input. The predictive model is a model used to mimic the controlled object.

[0051] The rudder angle control unit 161 extracts the rudder angle that should be indicated after the pre-aiming time from the above-mentioned optimal rudder angle series, and outputs the target rudder angle with the rudder angle interference (fusion rudder angle interference δ12 described later) that has been eliminated in advance as the rudder angle indication value, and controls the rudder angle of the rudder actuator AC1.

[0052] It should be noted that when the rudder angle control unit 161 is performing rudder angle control based on the target rudder angle, if the steering torque is detected by the steering torque sensor 2c, it may determine that the driver has performed a steering operation (issued a change instruction for the rudder angle) and interrupt the rudder angle control based on the aforementioned rudder angle indication value.

[0053] In addition, when performing target rudder angle control, the rudder angle control unit 161 can continue to perform target rudder angle control as long as the steering torque sensor 2c does not detect a large steering torque that clearly indicates the driver's intention to disengage from path following. In other words, as long as no steering operation is performed that changes the rudder angle by more than a specified value, the rudder angle control unit 161 can continue to perform target rudder angle control.

[0054] Figure 3A This is a block diagram illustrating the rudder angle control process of the rudder angle control unit 161. Figure 3A The middle picture shows Figure 2 The illustrated structure includes the object calculation unit 141, the travel path calculation unit 151, the target path calculation unit 152, the rudder angle control unit 161, the rudder actuator AC1, and the body of the vehicle 101.

[0055] Figure 3B This is a detailed explanation. Figure 3A A block diagram of the rudder angle control unit 161. The rudder angle control unit 161 includes an estimation unit 161a, a cross slope compensation unit 161b, and a model prediction control unit 161c.

[0056] The estimation unit 161a, for example, models vehicle state variables affected by factors such as the rudder angle velocity δ´ [rad / s] of the front wheels. Using these factors, observed vehicle state variables, and previous estimation values, it calculates estimated values ​​for the rudder angle disturbance δd and the vehicle sideslip angle β using Kalman filtering. Furthermore, generally, the actually observed vehicle state variables stably contain noise components (observation noise) and also noise components representing model uncertainties (process noise). By repeatedly performing Kalman filter-based estimation calculations, considering the uncertainties of the observation values ​​and the model, the estimation with the least error is performed. Hereinafter, the estimated value of the rudder angle disturbance δd is referred to as the estimated rudder angle disturbance δ1.

[0057] The slope compensation unit 161b observes the slope angle. Specifically, the slope compensation unit 161b calculates the slope angle of the vehicle 101's travel position based on the lateral component of gravitational acceleration included in the vehicle state variables (hereinafter referred to as lateral gravitational acceleration). The slope compensation unit 161b also predicts the effect of the slope angle (the vehicle's orientation shift relative to the direction of travel) through feedforward compensation and calculates the amount of rudder angle to offset this effect (hereinafter referred to as the slope compensation rudder angle).

[0058] The model prediction control unit 161c includes a prediction calculation unit 161c1 and a target rudder angle calculation unit 161c2. The prediction calculation unit 161c1 performs model prediction calculations with the target path and observed vehicle state variables of the vehicle 101 as input. By performing model prediction calculations, the prediction calculation unit 161c1 performs the following processing (solution search calculation): At a predetermined calculation interval (e.g., several milliseconds to several seconds), it predicts the speed and direction of travel (predicted path) of the vehicle 101 in the model for the next few seconds (prediction time domain), while simultaneously calculating the optimal rudder angle sequence for the next few seconds (prediction time domain). The optimal rudder angle sequence includes the optimal rudder angles predicted in each step based on the sampling time. The sampling time for each step in the prediction time domain can be adjusted. The prediction calculation unit 161c1 outputs the calculation results (optimal rudder angle sequence) of the model prediction calculations to the target rudder angle calculation unit 161c2.

[0059] It should be noted that, as Figure 3B As shown, the model prediction control unit 161c excludes the estimated rudder angle disturbance δ1 calculated by the estimation unit 161a and the slope compensation rudder angle δ2 calculated by the slope compensation unit 161b from the rudder angle (actual rudder angle) included in the vehicle state variables that serve as input values ​​for model prediction calculation. Thus, in the model prediction calculation of the prediction calculation unit 161c1, the actual rudder angle is replaced by the rudder angle from which the estimated rudder angle disturbance δ1 and the slope compensation rudder angle δ2 are excluded (hereinafter referred to as the effective rudder angle) as the input value. Figure 3B δ12 represents the combined value of the estimated rudder angle disturbance δ1 and the slope-compensated rudder angle δ2 (referred to as the fused rudder angle disturbance). The model predictive control unit 161c subtracts the fused rudder angle disturbance δ12 from the actual rudder angle, thereby eliminating the estimated rudder angle disturbance δ1 and the slope-compensated rudder angle δ2 from the actual rudder angle.

[0060] The target rudder angle calculation unit 161c2 receives the optimal rudder angle sequence calculated by the prediction calculation unit 161c1 and the fused rudder angle interference δ12. The target rudder angle calculation unit 161c2 extracts the rudder angle to be indicated after a predetermined aiming time tp from the optimal rudder angle sequence. The target rudder angle calculation unit 161c2 corrects the extracted rudder angle by adding the fused rudder angle interference δ12. In this way, the target rudder angle is calculated taking into account the influence of the rudder angle interference δd. The target rudder angle calculation unit 161c2 outputs the calculated target rudder angle as the rudder angle indication value several milliseconds later to the steering actuator AC1.

[0061] Figure 3C It is used for explanation Figure 3B The diagram shows the fusion rudder angle interference δ12. (See figure.) Figure 3C As shown, the estimated rudder angle disturbance δ1 output from the estimation unit 161a and the slope-compensated rudder angle δ2 output from the slope compensation unit 161b are combined by the filter CF. The filter CF is a complementary filter designed so that the sum of the gains (amplification) of the low-pass filter (LPF) and the high-pass filter (HPF) is 1 over the entire frequency range. It should be noted that the time constant of the complementary filter CF is set according to the required responsiveness (the responsiveness of the rudder angle control to changes in slope).

[0062] The estimated rudder angle disturbance δ1 output from the estimation unit 161a is input to a low-pass filter (LPF) according to the gain of the frequency component (speed changing with time) of the estimated rudder angle disturbance δ1 as shown in characteristic f1. On the other hand, the slope compensation rudder angle δ2 output from the slope compensation unit 161b is input to a high-pass filter (HPF) according to the gain of the frequency component (speed changing with time) of the slope compensation rudder angle δ2 as shown in characteristic f2. Through as... Figure 3C The filtered estimated rudder angle interference δ1 and the cross slope compensated rudder angle δ2 are combined (added) to obtain the fused rudder angle interference δ12.

[0063] Figure 4 It shows the procedure determined in advance. Figure 2 The flowchart illustrates an example of the computational processing performed by the arithmetic unit 11 of the controller 10. This processing is repeated, for example, when the vehicle 101 is driving in autonomous driving mode. Furthermore, it is repeated when the vehicle 101 is driving in manual driving mode, for example, when lane keeping assist, one of the driving assistance functions, is active, i.e., during lane keeping operation.

[0064] In step S1, the controller 10 obtains the target path of the vehicle 101. More specifically, it obtains path information representing the target path generated by the target path calculation unit 152. In step S2, the controller 10 obtains vehicle state quantities based on the output values ​​of the sensors constituting the internal sensor group 2 or through calculations using the sensor output values.

[0065] In step S3, the controller 10 calculates the rudder angle correction (fusion rudder angle interference δ12). Specifically, the controller 10 estimates the interference component of the rudder angle (actual rudder angle) included in the vehicle state variables, obtaining the estimated result as the estimated rudder angle interference δ1. Additionally, the controller 10 calculates the rudder angle that compensates for the slope angle as part of the interference component of the actual rudder angle (slope-compensated rudder angle) δ2. The controller 10 combines the estimated rudder angle interference δ1 and the slope-compensated rudder angle δ2 using a complementary filter CF to calculate the fusion rudder angle interference δ12.

[0066] In step S4, the controller 10 performs model prediction calculations using the target path obtained in step S1 and the vehicle state variables obtained in step S2 as inputs, and calculates the optimal rudder angle sequence. It should be noted that during the model prediction calculation, the controller 10 uses the fused rudder angle disturbance δ12 calculated in step S3 to correct (perform a subtraction operation) the rudder angle (actual rudder angle) included in the vehicle state variables as input values.

[0067] In step S5, controller 10 extracts the rudder angle to be indicated after the pre-aiming time from the calculation results (optimal rudder angle column) of the model prediction calculation, adds the fused rudder angle interference δ12 calculated in step S3 to the extracted rudder angle, and calculates the target rudder angle. Controller 10 outputs the target rudder angle as the rudder angle indication value for the next few milliseconds to the rudder actuator AC1.

[0068] In step S6, the controller 10 determines whether the process is complete. For example, when the autonomous driving mode is deactivated, the controller 10 determines that step S6 is affirmative (S6: Yes) and ends the process. Figure 4On the other hand, if the autonomous driving mode continues, the controller 10 determines that step S6 is negative (S6: No), returns to step S1, and repeats the above process.

[0069] Reference Figures 5A to 6B This explains the effects of this implementation method. Figure 5A The image roughly shows the state of the vehicle 101 traveling in lane LN as viewed from the rear. Figure 5A As shown, the slope (cross slope) of the driving position in the lane width direction at time t0 is α1%. On the other hand, the cross slope of the driving position at time t1, which is after time t0, is -α1.

[0070] Figure 5B It is shown that... Figure 5A The diagram shows the rudder angle correction for the driving scenario. Characteristic f11 represents the estimated rudder angle disturbance δ1. Characteristic f12 represents the slope-compensated rudder angle δ2. Characteristic f13 represents the fused rudder angle disturbance δ12 obtained by combining the estimated rudder angle disturbance δ1 represented by characteristic f11 and the slope-compensated rudder angle δ2 represented by characteristic f12.

[0071] The estimated rudder angle disturbance δ1 calculated using Kalman filtering has high accuracy (data reliability) in stable conditions without cross slope changes, but its responsiveness to cross slope changes deteriorates in the transition region of the cross slope (times t0 to t1). Figure 5B In the example, the response delay time d for the estimated rudder angle disturbance δ1 in response to cross slope changes. On the other hand, the cross slope compensated rudder angle δ2 calculated from the observed cross slope angle through feedforward compensation is as follows: Figure 5B As shown, the response to cross slope changes is relatively high. However, even in a stable state, when the cross slope angle is not 0 (the road surface has a slope in the lane width direction), a shift occurs in the cross slope compensation rudder angle δ2 to compensate for this cross slope angle. Figure 5B In the example, the slope-compensated rudder angle δ2 at steady state is offset to the positive side (upper in the figure) compared to the estimated rudder angle disturbance δ1.

[0072] The two rudder angle corrections with these characteristics (estimated rudder angle disturbance δ1 and cross slope compensation rudder angle δ2) are transmitted via Figure 3C The complementary filters CF are combined to obtain a rudder angle correction amount with high responsiveness and accuracy to cross slope changes, as shown in characteristic f13 (integrated rudder angle interference δ12). Using such a rudder angle correction amount, such as Figure 3B As shown, by correcting the input values ​​(actual rudder angle) and output values ​​(the rudder angle to be indicated after a specified pre-aiming time in the optimal rudder angle column) of the model prediction calculation, robustness to cross slopes during path following can be improved. As a result, the vehicle 101 can follow the target path with high accuracy in the transition region of the cross slope and in the stable state without cross slope changes.

[0073] Figure 6A This diagram shows the vehicle 101 traveling sequentially on curve IN1, straight road IN2, and curve IN3 of the loop route RD. The cross slope near the apex of the curve on the loop route RD is α21%. On the other hand, the cross slope of the straight road is α22 (<α21)%.

[0074] Figure 6B It is shown that... Figure 6A The diagram shows the rudder angle correction amount corresponding to the driving scenario. Characteristic f21 represents the estimated rudder angle disturbance δ1. Characteristic f22 represents the cross slope compensation rudder angle δ2. Characteristic f23 represents the fused rudder angle disturbance δ12 obtained by combining the estimated rudder angle disturbance δ1 represented by characteristic f21 and the cross slope compensation rudder angle δ2 represented by characteristic f22. As shown by characteristic f23, even when driving on roads with gentle cross slope changes, such as the loop route RD, a highly responsive and accurate rudder angle correction amount (fused rudder angle disturbance δ12) can be obtained in the transition region of the cross slope (times t20~t21, t22~t23). As a result, regardless of the swiftness of the change in the cross slope angle in the transition region of the cross slope, the vehicle 101 can follow the target path with high accuracy.

[0075] The following effects can be achieved by adopting this implementation method.

[0076] (1) The rudder angle control device 50 includes: a model prediction control unit 161c, which obtains a vehicle state quantity representing the motion state of the vehicle 101 based on the sensor value of the vehicle sensor, predicts the action of the vehicle 101 based on the obtained vehicle state quantity, and calculates the rudder angle indication value of the rudder actuator AC1 using the prediction result, so as to maintain the vehicle 101 traveling along the target path; an estimation unit 161a, which estimates the interference component of the rudder angle included in the vehicle state quantity, and calculates the estimated rudder angle interference δ1 as a first rudder angle correction amount based on the estimation result; and a cross slope compensation unit 161b, which calculates the rudder angle that compensates for the cross slope angle of the road surface as part of the interference component based on the vehicle state quantity, and calculates the cross slope compensation rudder angle δ2 as a second rudder angle correction amount based on the calculation result. The model predictive control unit 161c corrects the rudder angle (actual rudder angle) included in the vehicle state quantity used to predict vehicle behavior based on the fused rudder angle disturbance δ12, which combines the estimated rudder angle disturbance δ1 and the cross slope compensation rudder angle δ2 as a third rudder angle correction quantity. Furthermore, the model predictive control unit 161c, acting as a rudder angle indication unit, outputs the rudder angle indication value corrected based on the fused rudder angle disturbance δ12 to the steering actuator AC1. Among the disturbance components of the rudder angle included in the vehicle state quantity, at least one is included: a rudder angle compensating for the cross slope angle of the road surface (steering correction) and a rudder angle compensating for the midpoint offset of the steering device of the vehicle 101 (steering correction). This improves the responsiveness of rudder angle control to changes in road conditions. As a result, in driving scenarios where the cross slope changes within the same lane, and in driving scenarios where different road surfaces with different cross slopes are crossed due to lane changes, the vehicle 101 can also travel appropriately along the target path. Additionally, when traveling on a lane with a certain cross slope over a specified distance, the vehicle 101 can also travel appropriately along the target path. In this way, the vehicle 101 can follow the target path with high precision in both the transition zone of the cross slope and in the stable state where there is no change in cross slope.

[0077] (2) The model predictive control unit 161c changes the merging ratio of the estimated rudder angle disturbance δ1 and the slope compensation rudder angle δ2 according to the degree of change of the slope angle at the driving position of the vehicle 101 with respect to time. Specifically, the model predictive control unit 161c merges the estimated rudder angle disturbance δ1 and the slope compensation rudder angle δ2 in the merging rudder angle disturbance δ12 in such a way that the greater the degree of change of the slope angle with respect to time, the higher the proportion of the slope compensation rudder angle δ2 included in the merging rudder angle disturbance δ12. As a result, the rudder angle can be appropriately controlled according to the degree of change of the slope.

[0078] (3) The estimation unit 161a estimates the interference component of the rudder angle contained in the vehicle state quantity based on the sensor values ​​obtained from the on-board sensors by using Kalman filtering. As a result, the tracking accuracy of the target path can be improved when there is no change in cross slope.

[0079] (4) The cross slope compensation unit 161b calculates the rudder angle of the compensated cross slope angle through feedforward compensation based on the vehicle state quantity. As a result, the following accuracy of the target path in the transition area of ​​the cross slope can be improved.

[0080] The above-described embodiments can be modified in various ways. Hereinafter, modifications will be described. In the above-described embodiment, the model prediction control unit 161c, as the acquisition unit, acquires the vehicle speed, yaw rate, front wheel rudder angle, acceleration, rudder angle velocity, vehicle orientation, path lateral position deviation, vehicle path azimuth deviation, yaw rate deviation, and vehicle sideslip angle as vehicle state quantities. However, the acquisition unit may also acquire state quantities other than those described above as vehicle state quantities.

[0081] Furthermore, in the above embodiment, the estimation unit 161a estimates the interference component of the rudder angle included in the vehicle state quantity using Kalman filtering based on the vehicle state quantity. However, the estimation unit 161a may also use state estimation methods other than Kalman filtering to estimate the interference component of the rudder angle included in the vehicle state quantity.

[0082] Furthermore, in the above embodiment, the estimated rudder angle interference δ1 calculated by the estimation unit 161a (which is the first correction calculation unit) and the slope-compensated rudder angle δ2 calculated by the slope compensation unit 161b (which is the second correction calculation unit) are combined using the complementary filter CF to calculate the fused rudder angle interference δ12. However, the method for calculating the fused rudder angle interference δ12 is not limited to this. That is, the estimated rudder angle interference δ1 and the slope-compensated rudder angle δ2 can also be combined using a mechanism other than the complementary filter.

[0083] The above description is merely an example. As long as the characteristics of the present invention are not impaired, the present invention is not limited to the above embodiments and variations.

[0084] Using this invention, the path following performance of rudder angle control in response to changes in road conditions can be improved.

[0085] The present invention has been described above in conjunction with preferred embodiments, but those skilled in the art should understand that various modifications and changes can be made without departing from the scope of the claims.

Claims

1. A rudder angle control device, characterized in that, have: The acquisition unit acquires vehicle state quantities representing the vehicle's motion state based on the sensor values ​​from the on-board sensors. The prediction unit predicts the vehicle's actions based on the vehicle state quantities obtained by the acquisition unit. The rudder angle indicator uses the prediction result obtained by the prediction unit to calculate the rudder angle indication value of the rudder actuator for the vehicle, so as to maintain the vehicle's driving state along the target path. The first correction calculation unit (161a) estimates the interference component of the vehicle's rudder angle based on the vehicle state quantity, and calculates the first rudder angle correction amount based on the estimation result. as well as The second correction calculation unit (161b) calculates the rudder angle that compensates for the cross slope angle of the road surface as part of the disturbance component based on the vehicle state quantity, and calculates the second rudder angle correction amount based on the calculation result. The prediction unit corrects the vehicle's rudder angle, which is included in the vehicle state quantity used to predict the vehicle's behavior, based on a third rudder angle correction amount that combines the first and second rudder angle correction amounts. The rudder angle indicator will output the rudder angle indicator value, which has been corrected according to the third rudder angle correction amount, to the rudder actuator.

2. The rudder angle control device according to claim 1, characterized in that, The prediction unit adjusts the ratio of combining the first rudder angle correction and the second rudder angle correction based on the degree of change of the cross slope angle relative to time.

3. The rudder angle control device according to claim 1, characterized in that, The prediction unit combines the first rudder angle correction and the second rudder angle correction in such a way that the greater the change in the cross slope angle relative to time, the higher the proportion of the second rudder angle correction included in the third rudder angle correction.

4. The rudder angle control device according to claim 1, characterized in that, The first correction calculation unit (161a) estimates the interference components by Kalman filtering based on the vehicle state quantity.

5. The rudder angle control device according to claim 1, characterized in that, The second correction calculation unit (161b) calculates the rudder angle to compensate for the cross slope angle by feedforward compensation based on the vehicle state quantity.

6. The rudder angle control device according to any one of claims 1 to 5, characterized in that, The interference components include at least the rudder angle that compensates for the cross slope angle and the rudder angle that compensates for the midpoint offset of the vehicle's steering mechanism.

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