Vehicle control device

Abstract

To provide a vehicle control device that further decreases oscillation of an occupant's head by vehicle motions coordinating forward, backward and lateral motions, in consideration of an individual difference and an influence exerted on the oscillation of the occupant's head by the vehicle motions not only in a lateral direction but also in a longitudinal direction, and a vehicle control method.SOLUTION: A vehicle control device includes: a head oscillation prediction model that evaluates a change applied to head oscillation of an occupant in a first direction, caused by vehicle motions in the first direction, by the vehicle motions in a second direction different from the first direction; and a vehicle motion generation part that generates the vehicle motions on the basis of the head oscillation prediction model.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The present invention relates to a vehicle control device and a vehicle control method for controlling the momentum of a vehicle, and more particularly to a vehicle control device and a vehicle control method for controlling the attitude of a vehicle so as to improve the riding comfort of occupants and prevent the onset of motion sickness (motion sickness). [Background technology]

[0002] BACKGROUND ART For example, the one disclosed in Patent Document 1 is known as a conventional vehicle control device that controls vehicle motion to reduce shaking of the occupant's head, which can lead to motion sickness (motion sickness) for the occupant.

[0003] The abstract of Patent Document 1 states that the system includes: "a deviation angle detection means for detecting the deviation angle between the vehicle's direction of travel and the direction of a target point on a target course along which the vehicle will travel after a look-ahead time; a target value calculation means for calculating a yaw angular velocity proportional to the detected deviation angle as a first target value for the yaw angular velocity after a dead time of one-third of the look-ahead time; a target value correction means for correcting the first target value for the yaw angular velocity to obtain a second target value for the yaw angular velocity when performing feedforward control to suppress head sway of the occupant; and a vehicle motion control means for controlling vehicle motion so that the second target value for the yaw angular velocity is realized after the dead time, wherein the dead time is a first dead time equivalent to a phase delay in the feedforward control, or a second dead time equivalent to the sum of the first dead time and a phase delay in the transfer function from the actual steering angle to the yaw angular velocity."

[0004] Furthermore, claim 2 of Patent Document 1 states that "the transfer function of the feedforward control is a second transfer function including an inverse model in which the numerator and denominator are swapped by inverting the sign of the unstable zero point present in the numerator of a first transfer function that obtains the occupant's head displacement from the lateral acceleration acting on the vehicle, defined using a human body behavior model." [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Patent Publication No. 2021-62821 Summary of the Invention [Problem to be solved by the invention]

[0006] However, the vehicle motion control method of Patent Document 1 only mentions controlling the lateral (roll) direction of the occupant's head, and it is thought that there may be cases where the vehicle must slow down when passing through a curve in order to further suppress the swaying of the occupant's head.

[0007] Furthermore, Patent Document 1 does not mention that the human body behavior model may differ depending on the occupant, and there is a possibility that feedforward control adapted to one occupant may not be very effective in suppressing head sway for another occupant. In order to more effectively reduce occupant motion sickness without impairing the convenience of improving curve-neighboring speed, i.e., shortening the time it takes to reach the destination, it is necessary to adapt the model to accommodate individual differences, taking into account not only the lateral (roll) direction but also the longitudinal (pitch) direction.

[0008] Therefore, the object of the present invention is to provide a vehicle control device and a vehicle control method that take into consideration the influence of vehicle movement not only in the lateral (roll) direction but also in the longitudinal (pitch) direction on occupant head sway and individual differences, and further reduces occupant head sway by coordinating longitudinal and lateral vehicle movement. [Means for solving the problem]

[0009] For the above reasons, in the present invention, Left and right or roll Occupant injuries caused by vehicle motion in the direction Left and right or roll For head movements in the direction Front to back or pitch Vehicle movement in the direction of the occupants Left and right or roll A head sway prediction model that calculates the change in head sway in the direction of the head, and a head sway prediction model based on the head sway prediction model. Reduce head sway in the side-to-side or roll direction. Reduce head sway in the front-to-back or pitch direction. a vehicle motion generating unit that generates a vehicle motion; The head sway prediction model is a spring-mass-damper dynamic model with different parameters for each occupant, and the vehicle motion generation unit generates vehicle motion in the longitudinal or pitch direction that suppresses a motion sickness susceptibility index calculated from the output of the dynamic model. The vehicle control device is characterized by the above. [Effects of the Invention]

[0012] According to the present invention, a vehicle control method can be realized that effectively reduces head sway and suppresses motion sickness for more occupants without compromising the convenience of improving curve-going speed, i.e., shortening the time it takes to reach a destination.

[0013] This will improve the ride comfort for passengers and reduce the onset of motion sickness (motion sickness).

[0014] Problems, configurations, and effects other than those described above will become apparent from the following description of the embodiments. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a plan view showing an example of the overall configuration of a vehicle 1 according to a first embodiment of the present invention. [Figure 2] 2 is a schematic diagram illustrating input and output signals of the vehicle control device 2 of the first embodiment. FIG. [Figure 3a] FIG. 10 is a diagram showing an example of an occupant characteristic acquisition unit in which the vehicle has the shape of an automatically driven passenger bus. [Figure 3b] FIG. 10 is a diagram showing an example of an occupant characteristic acquisition unit when the vehicle has the shape of an automatically driven passenger car. [Figure 4] 1 is a functional block diagram of a vehicle control device 2 according to a first embodiment of the present invention. [Figure 5] FIG. 1 is a functional block diagram showing a method for calculating the motion sickness incidence rate MSI. [Figure 6a] 1 is a diagram showing how a head roll angle is generated due to lateral acceleration of an occupant; [Figure 6b] A diagram showing an example of adopting a spring-mass-damper mechanical model as a physical model. [Figure 7] 1A and 1B are plan views showing a vehicle 1 changing lanes and diagrams showing an example of changes in lateral acceleration 72 of the vehicle 1 and head roll angle 74 of an occupant 52 at that time. [Figure 8] FIG. 2 is a diagram conceptually showing an example of the function of a vehicle motion generation unit 25 according to the first embodiment. [Figure 9] FIG. 10 is a diagram showing a method for measuring changes in the head behavior of an occupant due to GVC. [Figure 10] FIG. 10 is a diagram showing the results of measuring changes in the head behavior of an occupant due to GVC. [Figure 11] FIG. 10 is a diagram showing the results of measuring changes in the head behavior of an occupant due to GVC. [Figure 12a] A diagram showing the definitions of the front-to-back and left-to-right directions for the occupant's head. [Figure 12b] FIG. 10 is a diagram showing an example of setting the spring coefficient K65 of the left-right spring 61 in the head movement prediction model. [Figure 13] FIG. 2 is a diagram showing a specific example of the configuration of a vehicle motion generation unit 25. [Figure 14] 4 is a diagram showing an example of a change in vehicle motion caused by the vehicle motion generation unit 25 of the first embodiment. FIG. [Figure 15] FIG. 1 is a plan view showing a vehicle 1 entering a left curve. [Figure 16] 4 is a diagram showing an example of a change in vehicle motion caused by a vehicle motion generation unit 25 in the first embodiment. FIG. [Figure 17] 4 is a diagram showing an example of a change in vehicle motion caused by a vehicle motion generation unit 25 in the first embodiment. FIG. [Figure 18] FIG. 4 is a diagram showing an example of a change in vehicle motion generated by the vehicle motion generation unit 25 of the first embodiment. [Figure 19] FIG. 4 is a functional block diagram of a vehicle control device 2 according to a second embodiment of the present invention. [Figure 20] 10 is a flowchart showing the processing of a vehicle control device 2 according to a second embodiment. [Figure 21] 10 is a diagram showing an example of a change in vehicle motion caused by a vehicle motion generation unit 25 in the second embodiment. FIG. [Figure 22] 10 is a diagram showing an example of a change in vehicle motion caused by a vehicle motion generation unit 25 in the second embodiment. FIG. [Figure 23] FIG. 10 is a functional block diagram of a vehicle control device 2 according to a third embodiment. [Figure 24a] 10A and 10B are diagrams showing examples of information presentation methods and behaviors. [Figure 24b] 10A and 10B are diagrams showing examples of information presentation methods and behaviors. DETAILED DESCRIPTION OF THE INVENTION

[0016] Hereinafter, embodiments of the present invention will be described with reference to the drawings. In the drawings, the same components are designated by the same reference numerals, and detailed descriptions of overlapping parts may be omitted.

[0017] To clarify the basic concept of the present invention, in the past, attempts were made to reduce motion sickness caused by left-right head movement by suppressing and controlling the amount of left-right movement, but the present invention is based on the new finding that forward-backward head movement also affects motion sickness caused by left-right head movement.

[0018] The above finding of the present invention is, more specifically, that "vehicle movement in a second direction different from the first direction affects the occupant's head sway in the first direction caused by vehicle movement in the first direction."

[0019] For this reason, in the present invention, head movement in the forward and backward directions is suppressed and controlled in order to reduce motion sickness caused by head movement in the left and right directions, and a specific method for this will be described in the embodiments. [Example]

[0020] A vehicle control device according to a first embodiment of the present invention will be described with reference to FIGS.

[0021] Fig. 1 is a plan view showing an example of the overall configuration of a vehicle 1 according to an embodiment of the present invention. In Fig. 1, 2 is a vehicle control device, 3 is an external control device, 4 is a combine sensor, 11 is wheels, 12 is a motor, 13 is a brake mechanism, 14 is a steering mechanism, 15 is a suspension, 16 is an accelerator pedal, 17 is a brake pedal, and 18 is a steering wheel.

[0022] In the drawings, FL, FR, RL, and RR are symbols indicating the front left, front right, rear left, and rear right, respectively. For example, in the case of the wheel 11, 11FL , 11 FR , 11 RL , 11 RR are the left front wheel, the right front wheel, the left rear wheel, and the right rear wheel, respectively. Also, F is a symbol indicating a configuration corresponding to the front side, and R is a symbol indicating a configuration corresponding to the rear side.

[0023] Below, we will define the front-to-back direction of vehicle 1 as the x-axis (forward direction is positive), the left-to-right direction as the y-axis (left direction is positive), and the up-to-down direction as the z-axis (upward direction is positive), and then explain the details of each component in turn.

[0024] The vehicle control device 2 is a control device that performs integrated control of each actuator such as the motor 12, brake mechanism 13, steering mechanism 14, suspension 15, etc. in response to the driver's operation, external commands from the external control device 3, and detection signals from the combined sensor 4 (detection signals related to control axes with a total of six degrees of freedom: forward / backward, left / right, and up / down acceleration, and roll, pitch, and yaw rates).

[0025] Specifically, the vehicle control device 2 is an ECU (Electronic Control Unit) that includes hardware such as a calculation device such as a CPU (Central Processing Unit), a main storage device such as a semiconductor memory, an auxiliary storage device, and a communication device. The calculation device executes a program loaded from the auxiliary storage device to the main storage device, thereby realizing the functions described below, but the following description will omit such well-known techniques as appropriate.

[0026] The external control device 3 is a higher-level controller for executing driving assistance control and automatic driving control via the vehicle control device 2, and calculates speed command values ​​and acceleration command values ​​for realizing adaptive cruise control (ACC) that follows the vehicle ahead, or yaw command values ​​for realizing lane keep control (LKC) that keeps the vehicle traveling within the lane, based on external information acquired by external sensors 19 (camera, radar, LiDAR, etc.), and outputs these as external commands to the vehicle control device 2.

[0027] Although the vehicle control device 2 and the external control device 3 are shown as separate entities in FIG. 1, they may be realized as a single ECU.

[0028] As the external sensor 19, for example, a fish-eye camera with a 180° viewing angle is installed on the front, left and right sides, and rear of the vehicle 1 (19 F , 19 SL , 19 SR , 19 R ), it is possible to detect the relative distance and relative speed between the vehicle 1 and objects around it, such as other vehicles, bicycles, pedestrians, and obstacles.

[0029] In this embodiment, the above-mentioned combination of sensors is shown as an example of the sensor configuration, but the present invention is not limited to this, and a combination with an ultrasonic sensor, a stereo camera, an infrared camera, etc. may also be used, or a laser radar capable of sensing 360° around may be mounted on the ceiling of the vehicle 1. The above-mentioned sensor signals (signals output from the above-mentioned sensors) are input to the vehicle control device 2 or the external control device 3.

[0030] Here, the drive system of the vehicle 1 will be described. The vehicle 1 is equipped with a torque generating device, as a main part of the drive system, that provides driving force to each of the wheels 11. An example of this torque generating device is an engine or a motor that transmits driving force to a pair of left and right wheels 11 via a differential gear and a drive shaft. Another example of a torque generating device is an in-wheel motor 12 that drives each of the wheels 11 independently. Below, the details of this embodiment will be described assuming the vehicle structure of FIG. 1 in which an in-wheel motor 12 is mounted on each of the wheels 11.

[0031] When the driver wants to move the vehicle 1 forward (or backward), the driver sets the shift lever to the desired setting and then operates the accelerator pedal 16. At this time, the stroke sensor 16a detects the amount of depression of the accelerator pedal 16, and the acceleration control device 16b converts the amount of depression and outputs an accelerator command to the vehicle control device 2. The vehicle control device 2 supplies power corresponding to the input accelerator command from a battery (not shown) to the motors 12 of each wheel, and controls the torque of each motor. As a result, the vehicle 1 can be accelerated or decelerated in accordance with the operation of the accelerator pedal 16.

[0032] Furthermore, when driving assistance or automatic driving is performed in response to an external command from the external control device 3, the vehicle control device 2 controls the torque of each motor by supplying a desired amount of power to the motor 12 of each wheel in response to the input external command. As a result, the vehicle 1 is accelerated or decelerated, and the desired driving assistance or automatic driving is performed.

[0033] Next, a braking system of the vehicle 1 will be described. As a main part of the braking system, the vehicle 1 is equipped with wheel cylinders 13a that apply braking force to each of the wheels 11. The wheel cylinders 13a are composed of, for example, a cylinder, a piston, a pad, a disc rotor, etc. In the wheel cylinders 13a, the pistons are propelled by hydraulic fluid supplied from a master cylinder, and the pads connected to the pistons are pressed against the disc rotors that rotate together with the wheels 11, and the brake torque acting on the disc rotors becomes a braking force acting between the wheels 11 and the road surface.

[0034] When the driver wants to brake the vehicle 1, the driver operates the brake pedal 17. At this time, the force with which the driver depresses the brake pedal 17 is increased by a brake booster (not shown), and a hydraulic pressure approximately proportional to the depressing force is generated by the master cylinder. The generated hydraulic pressure is transmitted via the brake mechanism 13 to the wheel cylinders 13a of each wheel. FL , 13a FR , 13a RL , 13a RRTherefore, in response to the driver's brake pedal operation, the piston of the wheel cylinder 13a of each wheel is pressed against the disc rotor, generating a braking force on each wheel.

[0035] In addition, in a vehicle 1 equipped with a vehicle control device 2, the brake booster and master cylinder may be omitted, in which case the brake pedal 17 and the brake mechanism 13 may be directly connected, and the brake mechanism 13 may operate directly when the driver steps on the brake pedal 17.

[0036] Furthermore, when driving assistance or automatic driving is performed in response to an external command from the external control device 3, the vehicle control device 2 controls the brake mechanism 13 and the wheel cylinders 13a of each wheel via the braking control device 13b in response to the input external command. As a result, the vehicle 1 is braked, and the desired driving assistance or automatic driving is performed.

[0037] The braking control device 13b also has the function of converting the amount of operation of the brake pedal 17 by the driver into a braking command and outputting it to the vehicle control device 2 as an external command.

[0038] Next, a steering system of the vehicle 1 will be described. The vehicle 1 is equipped with a steering mechanism 14 as a main part of the steering system, which applies a steering force to each of the wheels 11. In FIG. F (Left front wheel 11 FL , right front wheel 11 FR ) front steering mechanism 14 F and rear wheel 11 R (Left rear wheel 11 RL , right rear wheel 11 RR ) rear steering mechanism 14 R However, it is not necessary to provide the steering mechanism 14 at the front and rear. For example, the rear steering mechanism 14 R may be omitted.

[0039] When the driver wants to steer the vehicle 1, the driver operates the steering wheel 18. At this time, the "steering torque" and "steering angle" input by the driver via the steering wheel 18 are detected by the steering torque detection device 18a and the steering angle detection device 18b. F based on the detected steering torque and steering angle, the front steering motor 14b F Control the front wheels 11 F Similarly, the rear steering control device 14a generates an assist torque for steering the rear wheel. R based on the detected steering torque and steering angle, the rear steering motor 14b R Control the rear wheel R This generates an assist torque for steering the vehicle.

[0040] Furthermore, when driving assistance or automatic driving is performed in response to an external command from the external control device 3, the vehicle control device 2 controls the steering torque of the steering motor 14b via the steering control device 14a. As a result, the vehicle 1 is steered, and the desired driving assistance or automatic driving is performed. In this case, the steering wheel 18 may be omitted.

[0041] Next, we will explain the suspension system of the vehicle 1. The vehicle 1 is equipped with suspensions 15 as a key part of the suspension system, which absorb vibrations and shocks generated at each wheel 11 and improve the stability of the vehicle body and the ride comfort. This suspension 15 is, for example, a semi-active suspension that combines a damper with adjustable viscosity and a coil spring, or a full-active suspension that combines an actuator with an adjustable length, a damper, and a coil spring, and can arbitrarily change the relative distance between the vehicle body and the wheels 11.

[0042] The vehicle control device 2 not only improves ride comfort by controlling the viscosity of the semi-active suspension and the length of the full-active suspension, but also appropriately controls the attitude of the vehicle 1 according to the environment.

[0043] Next, the input and output of the vehicle control device 2 will be described using Fig. 2. Fig. 2 is a schematic diagram listing input and output signals of the vehicle control device 2. As shown in Fig. 2, accelerator commands, brake commands, steering torque, steering angle, etc. generated by the driver operating an accelerator pedal 16, a brake pedal 17, a steering wheel 18, etc. are input to the vehicle control device 2 as external commands.

[0044] In addition, the vehicle control device 2 receives external commands with up to six degrees of freedom from among longitudinal acceleration command values, lateral acceleration command values, vertical acceleration command values, roll command values, pitch command values, and yaw command values ​​generated by the external control device 3 during driving assistance control or autonomous driving control.

[0045] Furthermore, the combined sensor 4 inputs to the vehicle control device 2 the detected values ​​of the longitudinal, lateral, and vertical accelerations, and the roll, pitch, and yaw rates.

[0046] Then, the vehicle control device 2 controls the motor 12 (12 FL ~12 RR ), brake mechanism 13 (wheel cylinder 13a FL ~13a RR ), steering mechanism 14 (steering motor 14b F , 14b R ), Suspension 15 (15 FL ~15 RR ) (hereinafter, reference numerals 12 to 15 may be collectively referred to as actuators) and the amount of operation of each is appropriately distributed to perform drive, braking, steering, and suspension control, thereby realizing desired vehicle control including attitude control.

[0047] 1 is compatible with manual driving, and therefore an external command initiated by the driver is also illustrated in FIG. 2, but the present invention can also be applied to a vehicle 1 that is compatible only with fully automated driving or remote control, in which case the external command initiated by the driver can be omitted. During automated driving, an external command with up to six degrees of freedom may be input from the external control device 3, or target values ​​for automated driving may be generated using external information from the external sensor 19 and map information stored inside the vehicle control device 2. In this embodiment, the description will be given on the assumption that target values ​​for automated driving are generated inside the vehicle control device 2.

[0048] Occupant characteristics 24 (representing the posture of the occupant, etc.) may also be input to the vehicle control device 2. For example, a camera may be mounted in the passenger compartment of the vehicle 1 as an occupant characteristics acquisition unit 23, which measures the head movement of the occupant to estimate the likelihood (susceptibility) of the occupant to develop motion sickness (motion sickness). Alternatively, a mechanism may be provided for acquiring information related to the occupant's susceptibility to motion sickness (motion sickness) from a mobile terminal carried by the occupant while in the vehicle.

[0049] An example of the occupant characteristic acquisition unit 23 will be described using Figures 3a and 3b. Figure 3a illustrates an example in which the vehicle 1a has the shape of an autonomously driven passenger bus. In Figure 3a, the occupant characteristic acquisition unit 23a is a camera attached to the ceiling with a 360-degree field of view. This camera detects the riding position, riding direction, posture, head posture, head movement, line of sight, riding task (reading, sleeping, etc.) of the occupants 52a, 52'a as the occupant characteristics 24. Note that the camera is not limited to this shape and position, and multiple cameras may be installed in the vehicle cabin, and the field of view may not be 360 ​​degrees.

[0050] Alternatively, as shown in Fig. 3b, if the vehicle 1b has the shape of a passenger car, the occupant characteristic acquisition unit 23b may be a camera installed near the connection point between the windshield and the ceiling (where the rearview mirror is usually located). In this case, the occupant characteristic 24 of the occupant 52b seated in the back seat is detected.

[0051] Fig. 4 is a functional block diagram of the vehicle control device 2. Fig. 2 illustrates an example of the vehicle control device 2 to which three types of external commands (accelerator command, brake command, steering torque / steering angle) originating from the driver are input, and to which up to six types of external commands are input from the external control device 3, but in this embodiment, as described above, the vehicle control device 2 of this embodiment will be described in detail using as an example a configuration in which target values ​​for automatic driving are generated inside the vehicle control device 2.

[0052] As shown in FIG. 4, the vehicle control device 2 of this embodiment is composed of at least a target value generation unit 21, a vehicle motion generation unit 25, and a head movement prediction model 28, and ultimately outputs vehicle motion 26 to actuators 12-15.

[0053] The target value generation unit 21 sets vehicle motion targets that achieve specific driving tasks in autonomous driving (such as following a route or traveling at the same speed as a preceding vehicle) as target values ​​22 and outputs them to the vehicle motion generation unit 25. The target values ​​22 are generally three types: longitudinal acceleration command value, lateral acceleration command value, and yaw command value. It is preferable to generate up to six types of command values ​​by adding a roll angle command value, a pitch angle command value, and a vertical acceleration command value. When three types of external commands (accelerator command, brake command, steering torque / steering angle) originating from the driver are input, the target value generation unit 21 converts these external commands into longitudinal acceleration command value, lateral acceleration command value, and yaw command value and outputs them as target values ​​22.

[0054] Vehicle motion generation unit 25 corrects target values ​​22 of the input types, generates target values ​​of types that were not input, and outputs vehicle motion 26, which is the vehicle's motion and attitude with up to six degrees of freedom (forward / backward, left / right, up / down, roll, pitch, and yaw). Here, vehicle motion generation unit 25 plays a role in generating vehicle motion targets that take into consideration improvement of ride comfort and reduction of motion sickness, and generates vehicle motion 26 that optimizes the motion sickness susceptibility index based on occupant head sway characteristics 29 calculated by head sway prediction model 28, which will be described later. A specific example of the generation method will be described later.

[0055] Head sway prediction model 28 inputs vehicle motion 26', which is the causal factor of head sway occurrence, and ultimately provides occupant head sway characteristics 29. Here, we will explain the motion sickness incidence rate MSI, which is the incidence rate of motion sickness (so-called "car sickness"), as an example of a motion sickness susceptibility index for evaluating occupant motion sickness susceptibility.

[0056] It is known from papers and the like that the motion sickness incidence rate MSI can be calculated, for example, by a calculation method such as that shown in Fig. 5. Although a detailed explanation of Fig. 5 will be omitted, this method inputs three-axis head acceleration plus gravitational acceleration 31, three-axis head angular velocity 32, and three-axis head acceleration 33 as vehicle motion 26', which is a causative factor of head motion occurrence, and calculates the motion sickness incidence rate MSI based on the processing shown in Fig. 5.

[0057] Note that "head acceleration" and "head angular velocity" in Figure 5 are the acceleration and angular velocity experienced by the head of an occupant riding in vehicle 1. The motion sickness incidence rate MSI is an index indicating that the smaller the value, the less likely motion sickness is to occur in vehicle motion, so it is desirable to generate a target value for vehicle motion that reduces the motion sickness incidence rate MSI. It is known that when inertial acceleration occurs in the head when driving around a curve, the MSI can be reduced by minimizing the roll or pitch sway that occurs in the head (or by generating a roll angle or pitch angle in the opposite direction to the inertial acceleration, i.e., in a direction that resists inertia).

[0058] Another example of a motion sickness susceptibility index is the Motion Sickness Dose Value (MSDV). This is a value extracted from the accelerations generated in the human body that are considered to be particularly susceptible to causing motion sickness, and it is generally known that the higher this value, the more likely a person is to develop motion sickness. Therefore, when focusing on this sensitivity index, vehicle motion is generated that controls the acceleration in the forward / backward, left / right, and up / down directions so as not to generate those specific frequency components.

[0059] Another example of a motion sickness susceptibility index is a biological signal (such as sweating or heart rate). It is generally known that when a passenger develops motion sickness, an increase in heart rate and sweating of the palms or forehead are observed. Therefore, when focusing on this susceptibility index, a target value for vehicle motion is generated so as to improve this biological signal.

[0060] Head sway prediction model 28 receives provisional or final vehicle motion 26' from vehicle motion generation unit 25 and has a physical model that calculates predicted values ​​of head sway (six-axis momentum and attitude angle of the occupant's head) that may occur due to vehicle motion 26' for the occupant currently aboard. Because the parameters of the physical model differ depending on the occupant, head sway prediction model 28 serves to store the parameters. Then, by transmitting the predicted values ​​of head sway that may occur due to vehicle motion 26' or the stored parameters to vehicle motion generation unit 25 as head sway features 29, the vehicle motion generation unit 25 is provided with information that serves as a reference for generating final vehicle motion 26.

[0061] An example of the operation of head movement prediction model 28 will be described using Figures 6a, 6b, and 7. Figure 6a shows how a head roll angle 74 occurs due to lateral acceleration 72 applied to occupant 52. Figure 6b shows an example in which a general spring-mass-damper mechanical model is used as the physical model for predicting head movement. Note that although Figures 6a and 6b use the roll direction as an example, the pitch direction can also be expressed using a similar model. Furthermore, as will be described later, the roll direction and pitch direction are characterized by a correlation between them.

[0062] First, as shown in Figure 6a, when lateral acceleration 72 is applied to occupant 52, inertial acceleration occurs in the head, causing a head roll angle 74. At this time, the neck (the connection between the shoulders and head) of occupant 52 is generally known to have the characteristics of a spring (generating a reaction force proportional to displacement) and a damper (generating a reaction force proportional to the change in displacement over time). If this configuration is simplified as a head swing model, it can be expressed as a configuration in which inertia 63 is in contact with the ground via spring 61 and damper 62, as shown in Figure 6b.

[0063] The dynamic input to this model is the inertial acceleration occurring at the center of gravity of inertia 63, and the resulting displacement 64 is equivalent to head roll angle 74. By assuming such a model, it becomes possible to estimate the change over time in the occupant's head roll angle 74 caused by the change over time in the lateral acceleration set by the target value 22.

[0064] The coefficients of spring 61 and damper 62 shown in Figure 6b are thought to differ from person to person (there are individual differences), and the coefficients of spring 61 and damper 62 are one example of parameters of head movement prediction model 28. Generally, the larger the coefficients of the spring and damper, the smaller the head movement. Now, let X be the displacement 64 corresponding to the roll angle of the occupant's head, X' be its first-order derivative with respect to time, X' be its second-order derivative, K be the spring coefficient of spring 61, C be the damping coefficient of damper 62, M be the mass of inertia 63, and Ax be the inertial acceleration generated at the center of gravity of inertia 63. Then, head movement prediction model 28 calculates the equation of motion shown in equation (1). [Number 1] MX´´=MAx-KX-Cx´ (1) An example of the difference in behavior due to differences in parameters (K, C) will be explained using Figure 7. The upper part of Figure 7 shows the lane change of the vehicle, the middle part shows the fluctuation in lateral acceleration at that time, and the lower part shows the head roll angle of the occupant at that time.

[0065] Here, it is assumed that vehicle 1 is changing lanes from left to right on a two-lane road, and lateral acceleration 72 occurs as shown in the middle of Figure 7. That is, first steering to the right generates negative lateral acceleration, and then steering to the left generates positive acceleration. At this time, occupant a, whose head does not sway easily, and occupant b, whose head sways easily, will have different head roll angles 74a and 74b for the same lateral acceleration 72. For example, in Figure 7, the amplitude of the head roll angle for 74b is roughly twice as large as that for 74a, so it is expected that the identified spring coefficient K and damping coefficient C for occupant b will be roughly half that of occupant a.

[0066] In addition to the spring, mass, and damper, a separate input proportional to lateral acceleration may be added to head movement prediction model 28. This simulates the active reaction of the human body, and assumes that when the head perceives lateral acceleration, it attempts to suppress head movement by generating a force proportional to the lateral acceleration in a direction that resists the lateral acceleration that has occurred. If the proportionality coefficient of this active movement is taken as L, then head movement prediction model 28 calculates the equation of motion shown in equation (2). [Number 2] MX´´=MAx-KX-CX´-LAx (2) The relationship between the roll direction and pitch direction in head movement prediction model 28 will be explained using Figures 8 to 11. Figure 8 is a schematic diagram showing the characteristics of vehicle motion in G-Vectoring control (GVC), which has been proposed as vehicle motion that achieves good steering characteristics and ride comfort. From the top, it shows lateral acceleration 72, lateral jerk 76 which is the time derivative of lateral acceleration, and longitudinal acceleration 77. This diagram assumes vehicle motion that occurs when entering a left curve.

[0067] When a vehicle enters a left curve with a transition curve and steers left, lateral acceleration 72 begins to increase at a certain point, and when the vehicle leaves the transition curve and reaches a curve with a constant curvature, the lateral acceleration shows a time lapse in which it becomes a constant value. At this time, the lateral jerk shows a value greater than 0 while the vehicle is traveling on the transition curve (the steering angle is gradually increasing). GVC is characterized by generating longitudinal acceleration proportional to the absolute value of this lateral jerk in the opposite direction (i.e., generating it in the deceleration direction when the magnitude of the lateral jerk is increasing).

[0068] The method for setting the proportional coefficient (GVC gain 66) of the longitudinal acceleration relative to the absolute value of the lateral jerk is a feature of the present invention.

[0069] In a vehicle without GVC, the longitudinal acceleration remains at 0 as shown in longitudinal acceleration 77a, and the vehicle enters the curve at a constant speed, but in a vehicle equipped with GVC, a longitudinal acceleration proportional to the lateral jerk 76 occurs in the deceleration direction as shown in longitudinal acceleration 77b.

[0070] 9 to 11 show the results of measuring how the occupant's head sway changes when GVC vehicle motion such as that shown in FIG. 8 is generated. First, as shown in FIG. 9, a slalom run was performed in which the vehicle continuously moves back and forth between lanes. The change over time in the occupant's head roll rate 78 (roll rate is the time derivative of the roll angle) at this time is shown in FIG. 10. Measurements were taken for three subjects A, B, and C, with the dashed line indicating "without GVC" and the solid line indicating "with GVC." Here, "without GVC" corresponds to the movement of longitudinal acceleration 77a in FIG. 8, and "with GVC" corresponds to the movement of longitudinal acceleration 77b in FIG. 8.

[0071] 10, it can be seen that for subject A, the amplitude of the head roll rate was larger for roll rate 78a' with GVC than for roll rate 78a without GVC. On the other hand, for subjects B and C, the amplitude of the head roll rate was smaller with GVC (78b', 78c') than without GVC (78b, 78c). This shows that the occurrence of longitudinal acceleration in the deceleration direction with a magnitude proportional to lateral jerk 76 during steering can reduce the sway of the occupant's head, and that the effect of this varies from person to person.

[0072] FIG. 11 shows a Lissajous waveform 79 for subject C, who had the greatest head sway reduction effect with GVC, with the roll rate generated in the vehicle on the horizontal axis and the head roll rate on the vertical axis. Looking at the range of values ​​on the horizontal axis, the dashed line without GVC and the solid line with GVC have roughly the same range of values. In other words, this shows that there is almost no difference in the amplitude of the vehicle's roll rate with or without GVC. This is because GVC only controls the longitudinal direction, and the changes it makes in the lateral (roll) direction are minimal. Meanwhile, the range of values ​​on the vertical axis is narrower with GVC compared to without GVC, and it can be seen that the amplitude of head roll rate 78 is smaller.

[0073] As described above, even though there is almost no difference in the vehicle's lateral (roll) motion, adding a change in longitudinal motion affects the roll rate of the occupant's head. The present invention utilizes this phenomenon (principle) to reduce the lateral (roll) sway of the occupant's head by controlling longitudinal motion.

[0074] 12a and 12b, an example will be described in which head movement prediction model 28 has the aforementioned correlation between the roll direction and pitch direction. Fig. 12a is an explanatory diagram showing the definitions of the front-to-back (pitch) direction and the left-to-right (roll) direction for the head of occupant 52. In the present invention, the direction in which occupant 52 is facing is defined as front-to-back, and the translation direction perpendicular to front-to-back is defined as left-to-right.

[0075] FIG. 12b shows an example of setting the spring coefficient K65 of the spring 61 in the left-right (roll) direction in head sway prediction model 28. In this diagram, the horizontal axis represents the magnitude of the longitudinal acceleration or pitch angle (which may be based on the vehicle body or the occupant's head), and the vertical axis represents the spring coefficient 65 assumed in head sway prediction model 28. Note that while longitudinal acceleration and pitch angle are used as examples of vehicle momentum in the longitudinal direction here, a configuration may also be used in which longitudinal jerk or pitch rate, which are the time derivatives of each, are controlled. In the following explanation, vehicle momentum in the longitudinal direction will be representatively referred to as "longitudinal acceleration."

[0076] In Figure 12b, occupant A is assumed to be test subject A in Figure 10, and shows characteristics in which the occurrence of longitudinal acceleration has no effect on reducing head movement (or in fact increases head movement). In this figure, spring coefficient 65a does not change with longitudinal acceleration or pitch angle and is plotted as a characteristic parallel to the horizontal axis, but the characteristics of test subject A in Figure 10 may also be set as a characteristic that slopes downward to the right. Furthermore, in areas where longitudinal acceleration is sufficiently large, occupant B may also have a characteristic in which spring coefficient K slopes downward to the right when the longitudinal acceleration exceeds a certain value.

[0077] On the other hand, when no longitudinal acceleration or pitch angle occurs, the spring coefficient 65b of occupant B is smaller than that of occupant A. In other words, when steering in the same way, if no longitudinal acceleration occurs, occupant B crew This suggests that head sway is greater than that of occupant A, which means that occupant A is more susceptible to developing motion sickness. On the other hand, when the magnitude of the longitudinal acceleration is greater than 0, spring coefficient 65b rises steadily to the right, and at a certain point is set to have characteristics that exceed those of occupant A. This suggests that applying longitudinal acceleration when steering can reduce head sway more than that of occupant A, which means that the susceptibility to developing motion sickness can be suppressed.

[0078] According to the above analysis results of the occupant's head shaking characteristics resulting from vehicle motion, in the present invention, the vehicle motion generator 25 of Fig. 4 is configured, for example, as shown in Fig. 13. In Fig. 13, the vehicle motion target 22, which is an input given to the input unit 30 in the vehicle motion generator 25, preferably includes a longitudinal acceleration command value 22a, a lateral acceleration command value 22b, and a yaw command value 22c, and further includes a roll angle command value 22d, a pitch angle command value 22e, and a vertical acceleration command value 22f, which are a maximum of six types of command values.

[0079] These vehicle motion targets 22 are also given to a head sway prediction model 28 as vehicle motion 26', and the three-axis head acceleration plus gravitational acceleration 31, three-axis head angular velocity 32, and three-axis head acceleration 33 generated from these are used to derive the MSI in Figure 4.

[0080] Vehicle motion generation unit 25 corrects target values ​​22 of the input type, generates target values ​​of types that were not input, and executes various processes to output vehicle motion 26, which is the vehicle's motion and attitude with up to six degrees of freedom (forward / backward, left / right, up / down, roll, pitch, and yaw), but Fig. 13 shows only the processing portion for longitudinal acceleration related to the present invention. Therefore, although not shown in Fig. 13, it is possible to provide a control circuit that reduces motion sickness caused by head movement in the left / right direction by suppressing and controlling the amount of momentum in the left / right direction.

[0081] In the basic processing for longitudinal acceleration, the vehicle motion generation unit 25 focuses on the longitudinal acceleration command value 22a and the pitch angle command value 22e, which are the vehicle motion targets 22 for longitudinal acceleration, among the input command values, and obtains a longitudinal acceleration target 77' in the longitudinal acceleration generation unit 34. The longitudinal acceleration target 77' is corrected in the subtraction unit 35 and then sent from the vehicle motion generation unit 25 to the actuators 12-15 as the longitudinal acceleration target 77.

[0082] In the correction process of the present invention, attention is focused on the left / right acceleration command value 22b and the roll angle command value 22d related to the lateral acceleration 72, which are differentiated in a differentiation circuit unit 31 to obtain a lateral jerk 76, and the magnitude of the lateral jerk 76 is then obtained in an absolute value circuit 32. The magnitude of the lateral jerk 76 is multiplied by a GVC gain 66 provided from a head shaking prediction model 28 in a multiplication circuit 33, and the resulting signal is corrected with respect to a longitudinal acceleration target 77' in a subtraction unit 35, after which it is output from the vehicle motion generation unit 25 as a longitudinal acceleration target 77.

[0083] As is clear from a comparison between FIG. 4 and FIG. 13, the occupant's head movement feature 29 from the head movement prediction model 28 in FIG. 4 is realized as a GVC gain 66 in FIG.

[0084] In this case, whether or not to apply GVC gain 66 and its magnitude are set individually for each occupant based on the determination of head sway prediction model 28. GVC gain 66 is normally a value in the range from 1 to 0. For occupants who are determined to be prone to motion sickness based on the processing results of head sway prediction model 28, GVC gain 66 is set to a large value to reduce longitudinal acceleration, and for occupants who are not determined to be prone to motion sickness, GVC gain 66 is set to a small value to adjust the longitudinal acceleration command determined by target value generation unit 21 to be reflected directly in driving.

[0085] 14 to 18, a specific example in which the vehicle motion generator 25 generates the vehicle motion 26 will be described. Fig. 14 shows an example in which the vehicle motion generator 25 generates a longitudinal acceleration 77 as the vehicle motion 26 when the lane change target value 22 described in Fig. 7 is generated. Here, the difference in behavior will be described using the same occupants A and B as in Fig. 12 as an example.

[0086] In the upper diagram of Figure 14, it can be seen that no longitudinal acceleration is generated for occupant A (driving at a constant speed), as shown by longitudinal acceleration 77a, whereas for occupant B, longitudinal acceleration 77b is generated in the deceleration direction when the steering angle is increased at the start of a lane change and when the steering angle is increased in the opposite direction to converge to the adjacent lane. This means that the proportionality coefficient (GVC gain 66) described in Figure 8 is set to 0 for occupant A and to a value greater than 0 for occupant B.

[0087] The lower diagram of Figure 14 shows an example of how the head roll angles 74 of occupant A and occupant B change over time due to the generation of the longitudinal acceleration. If the head roll angle 74a of occupant A occurs as shown by the dashed line, and the vehicle is driven without longitudinal acceleration (driving at a constant speed) as with occupant A, as shown by the dashed line in 77a, the head roll angle of occupant B occurs with a larger amplitude than that of occupant A, as shown by the dashed line in 74b.

[0088] On the other hand, when longitudinal acceleration 77b is applied to occupant B, the head roll angle of occupant B occurs with a smaller amplitude than that of occupant A, as shown by the solid line 74b'. This is the head swing reduction effect of the present invention.

[0089] Fig. 15 is a plan view showing a vehicle 1 entering a left curve. The road shape described here is a left curve, and the vehicle 1 enters a road with this left curve shape. The driving operation performed here is a left turn. The behavior examples described in Fig. 16 to Fig. 18 will be described using the left curve shown in Fig. 15 as an example.

[0090] The road shown in Figure 15 is divided into a first section (~A) with a curvature of 0 (straight line), a second section (A~B) with a gradually increasing curvature (monotonically increasing curvature: increasing lateral acceleration), a third section (B~C) with a constant curvature (steady turning), a fourth section (C~D) with a gradually decreasing curvature (monotonically decreasing curvature: decreasing lateral acceleration), and a fifth section (D~) with a curvature of 0 (straight line).

[0091] Fig. 16 shows an example of the behavior of vehicle 1 and the change over time in occupant head roll angle 74 when target value 22 is generated so that the vehicle passes through a left curve as shown in Fig. 15 at a constant speed. From top to bottom, Fig. 16 shows the changes in vehicle 1 speed 71, lateral acceleration 72, roll angle 73, and occupant head roll angle 74, with the horizontal axis representing the distance traveled from the position immediately before the curve. The dashed-dotted lines correspond to the positions of sections A to D shown in Fig. 15, respectively.

[0092] First, speed 71 indicates a case where the vehicle passes through at a constant speed, and therefore always remains constant. When traveling at this speed, lateral acceleration 72 generated in vehicle 1 increases as the curvature gradually increases in the second section (A to B), remains constant in the third section (B to C) where the curvature is constant (steady turning), and gradually decreases in the fourth section (C to D) where the curvature gradually decreases. Roll angle 73 also changes in substantially the same way as lateral acceleration 72.

[0093] The lateral acceleration 72 is defined as positive when the vehicle 1 moves to the left relative to the direction of travel, that is, when the vehicle 1 turns to the left, and the roll angle 73 calculated at this time is also positive (clockwise relative to the direction of travel), that is, a roll toward the outside of the turn (to the right).

[0094] An example of the transition of the occupant's head roll angle 74 during such vehicle behavior is shown in the bottom row of Figure 16. When vehicle 1 approaches a left curve, occupant 52's head perceives lateral inertial acceleration. Furthermore, inertia causes the head to sway to the outside of the turn, resulting in head roll angle 74. Even with the same vehicle behavior (lateral acceleration and roll angle), the head sway varies depending on the occupant, or even for the same occupant, depending on the task they are performing while riding. Specifically, the head roll angle of occupant A, whose head does not sway easily, transitions as shown in 74a, while the head roll angle of occupant B, whose head sways easily, transitions as shown in 74b. According to the principles of the MSI, one of the motion sickness susceptibility indices 27, the latter occupant, occupant B, is more likely to develop motion sickness.

[0095] Figure 17 shows an example of changing the speed 71 as vehicle motion 26. From top to bottom, the graph shows the transitions of the speed 71, lateral acceleration 72, and head roll angle 74 of the vehicle 1, with the horizontal axis representing the distance traveled from the position immediately before approaching the curve. The dashed dotted lines correspond to the positions of sections A to D shown in Figure 15, respectively.

[0096] The behavior of occupant A, whose head does not easily sway, i.e., the behavior of speed 71a, lateral acceleration 72a, and occupant head roll angle 74a, is the same as in Figure 16. In contrast, when occupant B, whose head tends to sway, passes through a left curve at the same speed 71a while riding, the head roll angle will be higher than 74a, as shown in 74b. Therefore, vehicle motion generator 25 generates vehicle motion 26 that reduces the speed as shown in 71b.

[0097] Specifically, a longitudinal acceleration (not shown) that sufficiently decelerates the vehicle before approaching the curve is generated as vehicle motion 26. As a result, the lateral acceleration while passing through the curve is reduced to 72b, and the head roll angle 74b becomes 74'b, which is equivalent to 74a. In other words, for occupant B who is highly susceptible to motion sickness, reducing the speed while passing through a curve suppresses the resulting head shaking, thereby preventing the onset of motion sickness.

[0098] FIG. 18 shows an example of reducing head sway of occupant B by generating longitudinal acceleration proportional to the change in lateral acceleration over time as vehicle motion 26. From top to bottom, the graph shows the changes in vehicle speed 71, lateral acceleration 72, longitudinal acceleration 77, and occupant head roll angle 74, with the horizontal axis representing the distance traveled from the position immediately before approaching the curve. The dashed-dotted lines correspond to the positions of sections A to D shown in FIG. 15. The changes in speed 71a, lateral acceleration 72a, and occupant head roll angle 74a for occupant A, whose head does not sway easily, are the same as those in FIG. 17, and therefore will not be described here. Furthermore, longitudinal acceleration 77a for subject A is always zero, as in FIG. 14, and is therefore not shown.

[0099] In contrast, for occupant B, whose head is prone to shaking, first reducing the speed as shown in 71b in the same manner as in Figure 17 reduces the lateral acceleration while going through the curve as shown in 72b, and the head roll angle 74b becomes equal to 74a, as shown in 77b. At this time, longitudinal acceleration occurs in the deceleration direction before approaching the curve (before point A), and occurs in the acceleration direction after exiting the curve (after point D).

[0100] On the other hand, in the present invention, the speed is changed as shown in 71b'. That is, the speed is reduced in the section A to B while traveling on the transition curve, the speed is maintained in the section B to C with constant curvature, and the speed is increased in the section C to D while traveling on the transition curve. At this time, compared to 71b, 71b' has a higher passing speed in the curve section (section B to C), and as a result, the lateral acceleration is also higher at 72b' than 72b. Looking at the longitudinal acceleration 77b', longitudinal acceleration in the deceleration direction proportional to the increase in lateral acceleration 72b' occurs in the section A to B, and longitudinal acceleration in the acceleration direction proportional to the decrease in lateral acceleration 72b' occurs in the section C to D. Due to this behavior, the head roll angle of 74b' becomes the same as 74b, even though the curve passing speed is high.

[0101] The above has been described by taking as an example a case where longitudinal acceleration 77 is generated in accordance with the time change of lateral acceleration 72 in order to reduce occupant head roll angle 74, but it is assumed that the same effect can be obtained by generating a pitch angle in the forward tilt direction of the vehicle using an actuator such as suspension 15 instead of longitudinal acceleration 77. Therefore, a configuration may be adopted in which vehicle motion generation unit 25 generates a pitch angle as vehicle motion 26.

[0102] As described above, the vehicle control device 2 of this embodiment generates vehicle motion 26 that takes into account the correlation between the longitudinal and lateral directions, thereby suppressing a decrease in vehicle speed when passing through curves compared to conventional technology, and suppressing the incidence of motion sickness among occupants while maintaining the convenience of quickly reaching a destination. By providing different head sway models 28 for different occupants, it is possible to provide a vehicle control device that responds to individual differences in occupant susceptibility to motion sickness and generates vehicle motion target values ​​that effectively reduce motion sickness.

[0103] The explanation of the first embodiment is based on the premise that autonomous driving is performed, that changes in momentum (target value generation) on the route to the destination are known in advance, and that head sway prediction model 28 in Fig. 4 predicts head sway at a future point in time, but it is also possible to realize Fig. 4 as a current response. It is also possible to realize a form in which the head sway that a change in momentum at the current point in time will have on the occupant is calculated and reflected in current control. [Example]

[0104] Second Embodiment A vehicle control device and a vehicle integrated control method according to a second embodiment of the present invention will be described with reference to FIGS.

[0105] In the first embodiment, the vehicle control device 2 has a head sway prediction model 28, and the parameters stored therein differ depending on the occupant. On the other hand, when considering that the present invention is implemented in an autonomous shared bus or the like as shown in FIG. 3a, it is expected that an unspecified number of occupants (passengers) will be on board. In such a case, in order to more effectively reduce motion sickness in occupants, it is desirable to learn parameters for each occupant. To achieve this, the head sway prediction model 28 may be configured to identify parameters for each occupant.

[0106] Fig. 19 is a functional block diagram of a vehicle control device 2 according to the second embodiment. As shown in Fig. 20, the vehicle control device 2 according to the second embodiment is composed of at least a target value generation unit 21, an occupant characteristic acquisition unit 23, a vehicle motion generation unit 25, and a head sway prediction model 28. The target value generation unit 21 is the same as in the first embodiment, and therefore a description thereof will be omitted.

[0107] As described in Figures 3a and 3b, the occupant characteristic acquisition unit 23 acquires occupant characteristics 24 (such as the riding posture and head posture of the occupant). For example, as shown in Figures 3a and 3b, a camera is mounted in the cabin of the vehicle 1 as the occupant characteristic acquisition unit 23, and the occupant's head movement is measured to estimate the likelihood (susceptibility) of developing motion sickness (motion sickness). Alternatively, a mechanism may be provided for acquiring information related to the occupant's susceptibility to motion sickness (motion sickness) from a mobile device carried by the occupant while riding.

[0108] An example of the occupant characteristics 24 is the amount of head movement of a maximum of six axes of an occupant 52 riding in the vehicle 1. In particular, it is necessary to acquire at least one of the roll angle and pitch angle of the head. As an example of a method of acquisition, as shown in Figures 3a and 3b, an image of the head of the occupant 52 is captured from an image of a camera mounted in the vehicle cabin, and the roll angle and pitch angle are recognized from the image. Note that if the occupant 52 is actively moving his or her head, that movement is excluded, and head movement caused by vehicle movement is extracted.

[0109] Vehicle motion generation unit 25 corrects target values ​​22 of the input types, generates target values ​​of types that were not input, and outputs vehicle motion 26, which is the vehicle's motion and attitude with up to six degrees of freedom (forward / backward, left / right, up / down, roll, pitch, and yaw). Similar to embodiment 1, vehicle motion 26 is generated to reduce the occupant's head sway. In addition, vehicle motion generation unit 25 of this embodiment has a role of generating vehicle motion 26' for a head sway prediction model 28, which will be described later, to learn the occupant's head sway characteristics.

[0110] Head sway prediction model 28 has a physical model that receives provisional or final vehicle motion 26' from vehicle motion generation unit 25 and calculates predicted values ​​for head sway (six-axis momentum and attitude angle of the occupant's head) that may occur due to vehicle motion 26' for the occupant currently riding in the vehicle. Its function is the same as that of embodiment 1, but head sway prediction model 28 of this embodiment additionally has a function to adapt the parameters of the head sway model to the occupant currently riding in the vehicle, using occupant characteristics 24 acquired by occupant characteristic acquisition unit 23 and vehicle motion 26'.

[0111] The head sway prediction model 28 may use vehicle motion of up to six axes (detected values ​​of longitudinal, lateral, and vertical accelerations, and roll, pitch, and yaw rates) acquired from the combined sensor 4 as vehicle motion 26'. The combined sensor 4 mounted on a typical vehicle 1 typically acquires a total of three axes: longitudinal and lateral accelerations and yaw rate. In this case, the roll and pitch rates or angles may be estimated by acquiring the vehicle motion and speed 71 of these three axes and the steering angle from the steering mechanism 14.

[0112] 20 is a flowchart showing the processing of the vehicle control device 2 of this embodiment. In this processing, for each calculation step, it is determined whether or not the identification of the parameters of the head movement model for the occupant 52 riding in the vehicle 1 has been completed, and if identification has not been completed, the occupant's head movement is predicted using general coefficients while identifying, and if identification has been completed, the identified coefficients are used.

[0113] First, in step S101, the occupant characteristic acquisition unit 23 identifies the individual occupant 52. For example, it is determined from a camera image whether or not the occupant 52 has ridden in the vehicle 1 in the past.

[0114] Next, in step S102, the head movement prediction model 28 determines whether or not the head movement model has been learned for the occupant 52. In other words, it determines whether or not the spring coefficient and damper coefficient for the occupant 52 are stored in the head movement prediction model 28.

[0115] If the head movement model for the occupant 52 has not been learned (No), in step S103, the head movement prediction model 28 acquires the vehicle movement 26'. Further, in step S104, the occupant characteristic acquisition unit 23 acquires the head movement of the occupant 52. Then, in step S105, the head movement prediction model 28 identifies the head movement model parameters of the occupant 52 based on the acquired vehicle movement 26' and the head movement of the occupant 52. Thereafter, in step S106, it is determined whether the identification is complete. Here, the identification requires time-series information on the vehicle movement and the head movement of the occupant 52 for a predetermined time. Therefore, the main criterion for determination is whether a predetermined time has elapsed since the start of learning.

[0116] If it is determined in step S106 that identification is not complete (No), in step S107, head movement prediction model 28 predicts the head movement of occupant 52 using the spring coefficient and damper coefficient of a typical human body. At this time, vehicle motion generator 25 generates special vehicle motion 26' necessary for learning as needed. Details of this will be described later.

[0117] On the other hand, if the head sway model for the occupant 52 has already been learned in step S102 (Yes), or if it is determined in step S106 that identification has been completed (Yes), then in step S108, the head sway of the occupant 52 is predicted using the identified spring coefficient and damper coefficient.

[0118] Then, in step S109, the vehicle motion generation unit 25 calculates the vehicle motion 26 based on the identified head movement model parameters of the occupant 52.

[0119] In the above series of processes shown in Fig. 20, it is assumed that there are multiple occupants. For example, occupant A uses vehicle 1 all the time, and therefore a head learning model for occupant A has already been formed. Occupants B and C do not use vehicle 1, but occupant B was able to be quickly learned in a short time, whereas occupant C could not be learned in a short time, and therefore was estimated using a model treating him as an ordinary person. According to this example, it is clear that an appropriate head sway prediction model is formed for each occupant, and driving that reflects individual differences is realized.

[0120] Using Fig. 21, an example will be described in which the vehicle motion generator 25 generates a vehicle motion 26' for learning in the head sway prediction model 28. Similar to Fig. 16, Fig. 21 shows an example of the vehicle motion 26' generated by the vehicle motion generator 25, the behavior of the vehicle 1, and the time change in the head roll angle 74 of the occupant when it is assumed that the vehicle traverses the left curve shown in Fig. 15 at a constant speed. Fig. 21 shows, from top to bottom, the transitions in the lateral acceleration 72, lateral jerk 76, longitudinal acceleration 77 (vehicle motion 26') of the vehicle 1, and the head roll angle 74 of the occupant, with the horizontal axis representing the distance traveled from the position immediately before approaching the curve. The dashed-dotted lines correspond to the positions of sections A to D shown in Fig. 15, respectively.

[0121] In Figure 21, the transition of lateral acceleration 72 is the same as in Figure 16. At this time, the lateral jerk, which is the time derivative of lateral acceleration 72, transitions as shown in 76. If head sway prediction model 28 has not yet completed learning, vehicle motion generator 25 generates longitudinal acceleration 77 shown in Figure 21 as vehicle motion 26'. This is longitudinal acceleration proportional to the absolute value of lateral jerk 76, similar to the GVC vehicle motion characteristics described in Figure 8. A feature of the present invention is that GVC gain 66, which is a proportionality coefficient, is set to an optimal value suited to the occupant, but here, because learning has not yet been completed, GVC gain 66 is set to an initial value.

[0122] Various methods can be applied to setting the initial value. For example, if the learning results of the head sway model for many occupants are stored as a database, one example is to set the GVC gain 66 that is suited to the occupant who is most likely to experience head sway as the initial value. Another option is to set the GVC gain 66 to the average value or the maximum value of the GVC gain 66 that is suited to each occupant. In order to more effectively learn the head sway model, it is generally desirable to set the GVC gain 66 to a large value. Furthermore, if learning cannot be performed for some reason, for example, if the occupant characteristics 24 cannot be acquired, or if the occupant characteristics acquisition unit 23 does not exist and there is no means for identifying the individual occupant, the GVC gain 66 will continue to be set to the initial value.

[0123] The head sway prediction model 28 identifies physical parameters by obtaining the time transitions of lateral acceleration 72, longitudinal acceleration 77, and occupant head roll angle 74 in Figure 21. Specifically, the K, C, and L parameters shown in Equation 2 and the characteristics of changes in K, C, and L due to longitudinal acceleration shown in Figure 12 are identified. For example, as shown in Figure 7, the smaller the amplitude of head roll angle 74 relative to lateral acceleration 72 for an occupant, the more likely the parameters are to be identified as large values. Furthermore, for an occupant whose head roll angle 74 amplitude decreases as the GVC gain 66 increases, the characteristics of changes in K, C, and L due to longitudinal acceleration are more likely to be identified as increasing characteristics.

[0124] Using FIG. 22, an example of the transition of the GVC gain 66 due to learning will be described when the initial value of the GVC gain 66 is set to the maximum value of the GVC gain 66 that suits each occupant. FIG. 22 shows an example of the vehicle motion 26 generated by the vehicle motion generation unit 25, the behavior of the vehicle 1, and the time change of the occupant's head roll angle 74 when lane changes as shown in FIG. 7 occur repeatedly on a straight road such as a highway. From top to bottom, FIG. 22 shows the transition of the lateral acceleration 72 of the vehicle 1, the longitudinal acceleration 77 (vehicle motion 26), the occupant's head roll angle 74, and the GVC gain 66, with the horizontal axis representing the elapsed distance from the point when the head sway model 28 started learning for the occupant currently riding in the vehicle. Here, lane changes occur repeatedly, and for ease of explanation, symbols A to G are assigned to each lane change that occurs, starting from the left. It is assumed that the amplitude and period of the lateral acceleration 72 are the same for each lane change. It is assumed that a long time elapses between lane changes D and E, and that multiple lane changes occur during this time. Multiple lane changes may also occur between each code. In this case, the time transition between the codes either repeats the same transition as the code to its left, or transitions in a way that complements the time change between the two codes.

[0125] First, at the time of lane change A, head movement prediction model 28 has just started learning, and GVC gain 66 in vehicle motion generator 25 is set as an initial value to the maximum gain that can be adapted to each occupant. At this time, the longitudinal acceleration has the maximum magnitude in the negative direction relative to the amplitude of lateral acceleration 72. Then, the occupant's head roll angle occurs at the same time as shown in 74.

[0126] Next, at the time of lane change B, vehicle motion generation unit 25 reduces GVC gain 66 by one step to train head sway prediction model 28. As a result, the magnitude of the negative longitudinal acceleration also decreases by one step. At this time, if the amplitude of the occupant's head roll angle is smaller than at the time of lane change A, as shown in the figure, head sway prediction model 28 identifies the K, C, and L parameters and identifies the characteristics of the changes in K, C, and L due to longitudinal acceleration as being nearly horizontal (not rising sharply to the right). As a result, at lane changes C and D after training is complete, GVC gain 66 is reduced by another step, and longitudinal acceleration does not occur very often. Thereafter, this GVC gain 66 is maintained for a predetermined time as a parameter suited to the occupant.

[0127] On the other hand, if the occupant continues to ride in vehicle 1 for a certain period of time, the manner in which head sway may change over time as the characteristics of the vehicle's behavior are acquired. This phenomenon occurs because the occupant's susceptibility to motion sickness decreases as the occupant becomes accustomed to the vehicle after riding for a long time, or because the occupant becomes more likely to make active movements to suppress head sway when forward / backward acceleration occurs as the characteristics of forward / backward and left / right movement are acquired. Therefore, head sway prediction model 28 may be configured to execute a re-learning process after a predetermined time has elapsed.

[0128] The behavior of the relearning process is shown after lane change E in Figure 22. First, at lane change E, GVC gain 66 in vehicle motion generator 25 is reset to the maximum gain suitable for each occupant as the initial value. At this time, longitudinal acceleration 77 reaches its maximum magnitude in the negative direction relative to the amplitude of lateral acceleration 72. Then, the occupant's head roll angle occurs at the same time as shown in 74.

[0129] Next, at lane change F, vehicle motion generation unit 25 decreases GVC gain 66 by one step to train head sway prediction model 28. As a result, the magnitude of the negative longitudinal acceleration also decreases by one step. At this time, if the amplitude of the occupant's head roll angle becomes larger compared to lane change E (the opposite change from lane change B), as shown in the figure, head sway prediction model 28 identifies the K, C, and L parameters and identifies the characteristics of the changes in K, C, and L due to longitudinal acceleration as rising to the right. As a result, at lane change G after training is complete, GVC gain 66 increases again, actively generating longitudinal acceleration. Thereafter, this GVC gain 66 is maintained for a predetermined time as a parameter suited to the occupant. In this way, when a new occupant whose head sway characteristics are still uncertain gets into the vehicle, the specific vehicle motion required for learning is generated, and head sway prediction model 28 can learn the head sway characteristics of the occupant from the relationship between lateral acceleration 72, longitudinal acceleration 77, and occupant head roll angle 74 at that time.

[0130] As described above, the vehicle control device 2 of this embodiment can predict how head shaking will occur in an unspecified number of occupants 52, taking into account individual differences, and modify the vehicle motion to more effectively reduce motion sickness in the occupants 52. [Example]

[0131] Third Embodiment A vehicle control device and a vehicle integrated control method according to a third embodiment of the present invention will be described with reference to FIGS.

[0132] In the first and second embodiments, the vehicle control device 2 is configured to output the vehicle motion 26 and determine the operation amount of each of the actuators 12 to 15 or a lower-level controller based on the vehicle motion 26. However, in the case of a vehicle that is manually driven and has few actuators that can accept control commands, instead of the vehicle motion 26, the configuration may be such that the driver 53 is assisted to manually achieve a vehicle motion equivalent to the vehicle motion 26 described in the first and second embodiments.

[0133] Fig. 23 is a functional block diagram of a vehicle control device 2 of Example 3. As shown in Fig. 23, the vehicle control device 3 of this example is composed of at least a target value generation unit 21, an information presentation generation unit 81, and a head shaking model 28. The target value generation unit 21 and the head shaking model 28 are similar to those of Examples 1 and 2, and therefore a description thereof will be omitted.

[0134] The information presentation generation unit 81 presents information to encourage the driver to generate vehicle motion that takes into consideration the improvement of ride comfort and the reduction of motion sickness. As in the first and second embodiments, the information presentation generation unit 81 generates a target for vehicle motion that optimizes the motion sickness susceptibility index 27 based on the occupant's head sway characteristics 29 calculated by the head sway prediction model 28, and presents information to the driver to encourage driving behavior in accordance with the target.

[0135] An example of the method and behavior of information presentation will be described using Figures 24a and 24b. Figure 24a is a schematic diagram showing a situation in which a driver 53 controls the acceleration and deceleration of the vehicle 1 by depressing the accelerator pedal 16, assuming that the vehicle 1 is a manually driven automobile. In this case, an example of a method of presenting information is to actively generate a reaction force (a force that resists the force applied by the driver) to the accelerator pedal 16.

[0136] FIG. 24b shows an example of behavior. This figure shows a case where the vehicle travels around the left curve shown in FIG. 15 with the same vehicle behavior as in FIG. 16. The behavior of lateral acceleration 72 is the same as in FIG. 16. In this case, if the reaction force against the accelerator pedal 16 over time is plotted as information display 83, with the force resisting the driver's pedaling force in the positive direction, the result will be as shown in the lower diagram of FIG. 24b. That is, as with GVC, a reaction force is generated in the positive direction between points A and B while traveling on a transition curve. This encourages the driver to release the accelerator and encourages the generation of longitudinal acceleration by engine braking. Conversely, the reaction force is reduced (generated in the negative direction) between points C and D to encourage the generation of longitudinal acceleration. However, because encouraging the driver to accelerate may be risky depending on road conditions, this information display may be implemented so that it is only generated on the deceleration side (between points A and B).

[0137] Although an example of changing the reaction force on the accelerator pedal 16 has been described here, other information presentation methods are also applicable. For example, the reaction force on the brake pedal may be changed. In this case, it is possible to encourage the driver to brake by decreasing (increasing in the negative direction) the reaction force between points A and B while traveling on a transition curve. Other methods include audio presentation.

[0138] As described above, the vehicle control device 2 of this embodiment can assist the driver in generating vehicle motion that achieves the effects described in the first and second embodiments, even in a vehicle that is manually driven and has few actuators that can accept control commands.

[0139] In the above, Examples 1 to 3 have been described for the case where one occupant is on board, but when there are multiple occupants in the cabin of the same vehicle 1, it is necessary to generate vehicle motion that is effective for people who are prone to motion sickness, while taking care not to cause motion sickness in people who are not prone to it. For example, when occupant A and occupant B shown in Fig. 12 are on board at the same time (the situation shown in Fig. 3a), the roll stiffness (spring constant K) of occupant A's head may actually become smaller due to the occurrence of longitudinal acceleration, so one example is to determine the GVC gain so that the head sway (amplitude of the roll angle) of both occupants becomes approximately the same as a result of the vehicle motion.

[0140] In the above, in Examples 1 to 3, the case where the occupant is riding facing forward has been described. However, the occupant may also be riding facing backward as shown in FIG. 3a or sideways. In particular, when the occupant is riding sideways, there may be a relationship between the occupant's head swing in the fore-and-aft (pitch) direction and the vehicle's lateral (roll) movement. Therefore, the present invention is effective not only for the relationship between the occupant's lateral head swing and the fore-and-aft vehicle movement, but also for other combinations, such as the occupant's head swing in the fore-and-aft direction and the vehicle's lateral movement.

[0141] The present invention is not limited to the above-described embodiments and includes various modifications. For example, the above-described embodiments have been described in detail to clearly explain the present invention, and the present invention is not necessarily limited to those including all of the described configurations. Furthermore, it is possible to replace part of the configuration of one embodiment with the configuration of another embodiment, or to add the configuration of another embodiment to the configuration of one embodiment. Furthermore, it is possible to add, delete, or replace part of the configuration of each embodiment with other configurations. [Explanation of symbols]

[0142] 1: vehicle, 11: wheel, 12: motor, 13: brake mechanism, 13a: wheel cylinder, 13b: braking control device, 14: steering mechanism, 14a: steering control device, 14b: steering motor, 15: suspension, 16: accelerator pedal, 16a: stroke sensor, 16b: acceleration control device, 17: brake pedal, 18: steering wheel, 18a: steering torque detection device, 18b: steering angle detection device, 18d: steering motor, 19: external sensor, 2: vehicle control device, 21: target value generation unit, 22: target value, 23: occupant characteristic acquisition unit, 24: occupant characteristic, 25: vehicle motion generation unit, 26: vehicle motion, 27: motion sickness susceptibility index, 28: Head sway prediction model, 29: Head sway characteristics, 3: External control device, 4: Combined sensor, 51: Seat, 52: Occupant, 53: Driver, 61: Head sway model spring, 62: Head sway model damping, 63: Head sway model inertia, 64: Head sway model inertial displacement, 65: Head sway model spring coefficient K, 66: GVC gain, 71: Speed, 72: Lateral acceleration, 73: Roll angle, 74: Occupant head roll angle, 75: Driving trajectory, 76: Lateral jerk, 77: Longitudinal acceleration, 78: Occupant head roll rate, 79: Lissajous waveform (vehicle roll rate and occupant head roll rate), 81: Information presentation generation unit, 82: Information presentation

Claims

1. A head sway prediction model that determines the change that vehicle movement in the front-to-back or pitch direction causes to the head sway of an occupant in the left-to-right or roll direction, in relation to the head sway of the occupant in the left-to-right or roll direction caused by vehicle movement in the left-to-right or roll direction; and a vehicle motion generation unit that generates vehicle movement in the front-to-back or pitch direction that reduces the head sway in the left-to-right or roll direction based on the head sway prediction model, the head movement prediction model is a spring-mass-damper dynamic model with different parameters for each occupant, The vehicle control device is characterized in that the vehicle motion generation unit generates vehicle motion in a forward / backward or pitch direction that suppresses a motion sickness susceptibility index calculated from the output of the dynamic model.

2. The vehicle control device according to claim 1, The vehicle control device is characterized in that the head movement prediction model includes a head movement characteristic learning unit that learns the head movement characteristics of each occupant corresponding to the vehicle motion.

3. The vehicle control device according to claim 2, The head movement characteristic learning unit learns the characteristics of the occupant's head movement based on the head posture acquired when a predetermined vehicle movement is generated.

4. The vehicle control device according to claim 3, A vehicle control device characterized in that the vehicle motion generation unit generates vehicle motion that combines at least one of the vehicle's forward / backward direction and pitch direction with the roll direction as the specified vehicle motion in the head shaking characteristic learning unit.

5. The vehicle control device according to claim 2, The head movement characteristic learning unit distinguishes between different riding posture patterns that the occupant may adopt and learns the characteristics of the occupant's head movement corresponding to the vehicle motion.

6. The vehicle control device according to claim 2, The vehicle control device according to claim 1, wherein the head movement characteristic learning unit sets predetermined parameters before learning, and modifies the predetermined parameters for each occupant through learning.

7. 7. The vehicle control device according to claim 6, A vehicle control device characterized in that a large parameter value is set as the predetermined parameter, and the large parameter value is corrected to a smaller value through learning.

8. The vehicle control device according to claim 7, a large parameter value being set as the predetermined parameter, and after the large parameter value is corrected in a smaller direction by learning to complete the learning, the corrected parameter value is corrected again in a larger direction.

9. 7. The vehicle control device according to claim 6, A vehicle control device, characterized in that an average value of statistically obtained parameters is set as the predetermined parameter.

10. 7. The vehicle control device according to claim 6, A vehicle control device comprising: correcting the predetermined parameters to complete learning; and, after a predetermined period of driving has elapsed based on the corrected parameters, correcting the corrected parameters again.

11. The vehicle control device according to claim 1, A vehicle control device comprising a display device that prompts the driver to make the vehicle movement in the forward / backward or pitch direction.

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