JP2021187398A - Travel support method and travel support apparatus - Google Patents

Abstract

To suppress the induction of an unstable vehicle behavior when the vehicle turns.SOLUTION: Provided is a travel control method by a controller that executes turning control so as to render a vehicular motion of a vehicle itself on the basis of at least one of an operation input by a driver and an instructed input from automatic operation control. The controller executes: calculating a first yaw inertia moment for suppressing a phasic delay of an actual yaw rate that actually occurs to the vehicle itself relative to a target yaw rate occurring to the vehicle itself under the turning control on the basis of a vehicle motion model of the vehicle itself (S3); obtaining information of a road shape of a road where the vehicle itself is predicted to travel (S4); determining whether the road shape is a transient shape in that its curvature changes (S6); calculating a target yaw moment that is generated to the vehicle itself in accordance with target yaw angular acceleration of the turning control and the first yaw inertia moment, in a case where the road shape is the transient shape (S7); and executing the turning control of the vehicle itself on the basis of the target yaw moment (S8).SELECTED DRAWING: Figure 7

Description

The present invention relates to a traveling support method and a traveling support device.

In Patent Document 1 below, the target yaw rate variated by the state quantity such as the stability factor is calculated, and the yaw moment amount that stabilizes the vehicle is calculated when the deviation between the target yaw rate and the actual yaw rate is large. , A vehicle motion control device that activates the brakes of each wheel is described.

International Publication No. 2014/136189 Pamphlet

According to the technique described in Patent Document 1, the yaw rate can be corrected when the vehicle behavior becomes unstable. However, it is not possible to turn the vehicle so as to suppress the induction of unstable vehicle behavior.
An object of the present invention is to suppress the induction of unstable vehicle behavior when the vehicle turns.

According to one aspect of the present invention, a controller that executes turning control so that the vehicle motion of the own vehicle is based on at least one of an operation input of the driver of the own vehicle and an instruction input from the automatic driving control of the own vehicle. Driving control method is given. The controller calculates the first yaw moment of inertia that suppresses the phase lag of the actual yaw rate that actually occurs in the own vehicle with respect to the target yaw rate that is generated in the own vehicle for turning control based on the vehicle motion model of the own vehicle. Information on the road shape of the road on which the vehicle is scheduled to travel is acquired, it is determined whether or not the road shape is a transient shape whose curvature changes, and if the road shape is a transient shape, the target inertia of turning control is obtained. The target yaw moment generated in the own vehicle is calculated according to the angular acceleration and the first yaw moment of inertia, and the own vehicle is turned and controlled based on the target yaw moment.

According to the present invention, it is possible to suppress the induction of unstable vehicle behavior when the vehicle turns.

It is a schematic block diagram of the traveling support device of an embodiment. It is explanatory drawing of an example of the architecture of the automatic driving control by the driving support device of embodiment. It is a block diagram which shows an example of the functional structure of the automatic driving control part of the driving support device of embodiment. It is explanatory drawing of an example of the Bode diagram of the frequency response of yaw rate. It is a block diagram which shows an example of the functional structure of the vehicle control part of the traveling support device of embodiment. It is a block diagram which shows an example of the functional structure of the road shape determination part of the vehicle control part shown in FIG. It is a flowchart of an example of the running support method of an embodiment.

Hereinafter, embodiments of the present invention will be described with reference to the drawings. It should be noted that each drawing is a schematic one and may differ from the actual one. Further, the embodiments of the present invention shown below exemplify devices and methods for embodying the technical idea of the present invention, and the technical idea of the present invention includes the structure, arrangement, etc. of components. Is not specified as the following. The technical idea of the present invention may be modified in various ways within the technical scope specified by the claims described in the claims.

(composition)
See FIG. The own vehicle 1 includes a running support device 10 that supports the running of the own vehicle 1. The driving support by the traveling support device 10 includes automatic driving control for automatically driving the own vehicle 1 without the driver's involvement based on the driving environment around the own vehicle 1, and driving of the own vehicle 1 by the driver. May include driving assistance control to assist.
The driving support control includes driving control that controls at least one of the steering device, the driving device, and the braking device of the own vehicle 1, such as automatic steering, automatic braking, constant speed driving control, lane keeping control, and merging support control. good.

The travel support device 10 includes an object sensor 11, a vehicle sensor 12, a positioning device 13, a map database 14, a navigation device 15, a communication device 16, a controller 17, and an actuator 18. In the drawings, the map database is referred to as "map DB".
The object sensor 11 detects an object around the own vehicle. The object sensor 11 has a plurality of different types of detecting objects around the own vehicle 1, such as a laser radar, a millimeter wave radar, a camera, and LIDAR (Light Detection and Ranging, Laser Imaging Detection and Ranging) mounted on the own vehicle 1. It is equipped with an object detection sensor.

The vehicle sensor 12 is mounted on the own vehicle 1 and detects various information (vehicle signals) obtained from the own vehicle 1. The vehicle sensor 12 includes, for example, a vehicle speed sensor that detects the traveling speed (vehicle speed) of the own vehicle 1, a wheel sensor that detects the rotation speed and the amount of rotation of each tire of the own vehicle 1, and a three-axis direction of the own vehicle 1. A 3-axis acceleration sensor (G sensor) that detects acceleration (including deceleration), a steering angle sensor that detects steering angle (including steering angle), a gyro sensor that detects angular speed generated in the own vehicle 1, and yaw rate detection. It includes a yaw rate sensor, an accelerator sensor that detects the accelerator opening degree of the own vehicle 1, and a brake sensor that detects the amount of brake operation by the driver.

The positioning device 13 includes a global positioning system (GNSS) receiver, receives radio waves from a plurality of navigation satellites, and measures the current position of the own vehicle 1. The GNSS receiver may be, for example, a Global Positioning System (GPS) receiver or the like. The positioning device 13 may be, for example, an inertial navigation system.

The map database 14 may store high-precision map data (hereinafter, simply referred to as “high-precision map”) suitable as a map for automatic driving. The high-precision map is map data with higher accuracy than the map data for navigation (hereinafter, simply referred to as "navigation map"), and includes information in lane units that is more detailed than information in road units.

For example, in a high-precision map, lane-based information includes lane node information indicating a reference point on a lane reference line (for example, a central line in a lane) and lane link information indicating a lane section mode between lane nodes. including.
The lane node information includes the identification number of the lane node, the position coordinates, the number of connected lane links, and the identification number of the connected lane link. The lane link information includes the lane link identification number, lane width, lane boundary type, lane shape, lane dividing line shape, and lane reference line shape.

Since the high-precision map includes node and link information for each lane, it is possible to specify the lane in which the own vehicle 1 travels in the traveling route. The high-precision map has coordinates that can represent positions in the extending direction and the width direction of the lane. The high-precision map has coordinates (for example, longitude, latitude and altitude) capable of expressing a position in three-dimensional space, and the lane or the above-mentioned feature may be described as a shape in three-dimensional space.

The navigation device 15 recognizes the current position of the own vehicle 1 by the positioning device 13 or the like. The navigation device 15 acquires road information and traffic information around the own vehicle 1 based on the recognized current position, and outputs the information to the controller 17. Further, the navigation device 15 provides route guidance to the occupants and also provides road information and traffic information.
The communication device 16 performs wireless communication with an external communication device of the own vehicle 1. The communication method by the communication device 16 may be, for example, wireless communication by a public mobile phone network, vehicle-to-vehicle communication, road-to-vehicle communication, or satellite communication.

The controller 17 is an electronic control unit (ECU) that includes a processor and peripheral parts such as a storage device and performs traveling support control of the own vehicle 1. The processor may be, for example, a CPU (Central Processing Unit) or an MPU (Micro-Processing Unit).
The storage device may include a semiconductor storage device, a magnetic storage device, an optical storage device, and the like. The storage device may include a memory such as a register, a cache memory, a ROM (Read Only Memory) and a RAM (Random Access Memory) used as the main storage device.
When the processor of the controller 17 executes a computer program stored in the storage device, the controller 17 functions as an automatic driving control unit 20, an input arbitration unit 21, and a vehicle control unit 22. The functions of the automatic driving control unit 20, the input arbitration unit 21, and the vehicle control unit 22 will be described later.

The controller 17 may be formed by dedicated hardware for executing each information processing described below.
For example, the controller may include a functional logic circuit set in a general purpose semiconductor integrated circuit. For example, the controller may have a programmable logic device (PLD: Programmable Logic Device) such as a field-programmable gate array (FPGA).

The actuator 18 operates the steering device, the driving device, and the braking device of the own vehicle 1 in response to the control signal from the controller 17 to generate the vehicle behavior of the own vehicle 1. The actuator 18 includes a steering actuator, an accelerator opening actuator, and a brake control actuator.
The steering actuator controls the steering direction and steering amount of the steering wheel of the own vehicle 1.

The steering actuator may be, for example, a steering assist motor that applies steering assist force in an electric power steering system, and steers the steering wheel in a steering-by-wire system in which the steering wheel and the steering wheel are mechanically separated. It may be a steering motor.
The accelerator opening actuator controls the accelerator opening of a drive device (for example, an engine or an electric motor) which is a power source for generating a driving force of the own vehicle 1. The brake control actuator controls the braking operation of the braking device of the own vehicle 1.

Next, an example of the running support control by the running support device 10 of the embodiment will be described. FIG. 2 shows an example of an architecture of automatic driving control by a driving support device. The automatic driving control includes an automatic driving layer (AD Layer) 30, an arbitration unit (Arbitration) 31, a reference model unit (Reference Model) 32, a vehicle body behavior control unit (Body Motion Control) 33, and a wheel behavior control unit (wheel behavior control unit). It is executed by the Wheel Motion Control) 34 and the actuator 18 described above.
The automatic driving layer 30 sets the destination of the own vehicle 1 and sets the traveling route from the current position of the own vehicle 1 to the destination.

The automatic driving layer 30 generates a target traveling track and a target speed profile of the own vehicle 1 traveling on the traveling route as an automatic driving input (AD input) which is an instruction input from the automatic driving layer 30.
The arbitration unit 31 arbitrates the manual driving input (MD input), which is the operation input of the steering wheel, accelerator, and brake by the driver, and the automatic driving input from the automatic driving layer 30, and the vehicle motion that the own vehicle 1 should perform. To set.

The normative model unit 32 uses vehicle motion model parameters (for example, yaw moment of inertia, wheel cornering stiffness) used to calculate the vehicle body behavior of the vehicle 1 for the vehicle 1 to realize the vehicle motion set by the arbitration unit 31. Etc.).
The vehicle body behavior control unit 33 has a vehicle body behavior (for example, vehicle speed, acceleration / deceleration, yaw rate, yaw angular acceleration) for realizing the vehicle motion set by the arbitration unit 31 based on the vehicle motion model set by the normative model unit 32. , Yaw moment, etc.) is calculated.

The wheel behavior control unit 34 calculates the wheel control amount (steering angle, braking amount, drive amount, etc.) for generating the vehicle body behavior calculated by the vehicle body behavior control unit 33 in the own vehicle 1, and the wheel behavior by the actuator 18. To control.
For example, the function of the automatic driving layer 30 is carried out by the automatic driving control unit 20 shown in FIG. 1, the function of the arbitration unit 31 is carried out by the input arbitration unit 21, the normative model unit 32, the vehicle body behavior control unit 33, and the wheel behavior control unit. The function of 34 may be carried by the vehicle control unit 22.

Next, an example of the functional configuration of the automatic operation control unit 20 will be described with reference to FIG. The automatic operation control unit 20 includes a localization unit (Localization) 40, a destination setting unit 41 (Destination Setting), a route planning unit (Route Planning) 42, an action decision unit (Decision Making) 43, and an operation zone planning unit. (Drive Zone Planning) 44 and a trajectory generator (Trajectory) 45 are provided.

The localization unit 40 recognizes the surrounding environment of the own vehicle 1 based on the detection signal of the object sensor 11. The localization unit 40 determines the current position of the own vehicle 1 on the high-precision map by map matching between the recognition result and the high-precision map of the map database 14.
Further, a local model 47, which is a model of the surrounding environment of the own vehicle 1, is generated based on the recognition result of the surrounding environment. Further, the world model 46 is generated by fusing the local model 47, the high-precision map, and the road information and the traffic information of the navigation device 15.

The destination setting unit 41 sets the destination of the own vehicle 1 based on the operation input of the driver via the navigation device 15.
The route planning unit 42 calculates a planned travel route from the current position to the destination based on the road information of the navigation device 15.
The action determination unit 43 determines the driving action plan of the own vehicle 1 to be executed by the travel support device 10 based on the recognition result of the surrounding environment, the current position of the own vehicle 1, the world model 46, and the planned travel route. do.

Driving behavior includes, for example, stopping, pausing, traveling speed, deceleration, acceleration, course change, right turn, left turn, straight ahead, lane change in merging section or multiple lanes, lane keeping, overtaking, obstacles. Actions such as correspondence are included.
The action determination unit 43 generates a driving action plan for the own vehicle 1 based on the current position and posture of the own vehicle 1, the surrounding environment of the own vehicle 1, and the world model 46.

The driving zone planning unit 44 calculates a driving zone, which is an area in which the own vehicle 1 can be driven, based on the generated driving action plan, the motion characteristics of the own vehicle 1, and the local model 47.
The track generation unit 45 generates a target travel track and a target speed profile of the own vehicle 1 so that the own vehicle 1 travels in the operation zone calculated by the operation zone planning unit 44.

See FIG. The input arbitration unit 21 arbitrates the automatic driving input of the target traveling track and the target speed profile set by the automatic driving control unit 20 and the manual driving input by the driver, and sets the vehicle motion to be performed by the own vehicle 1.
The vehicle control unit 22 controls the behavior of the own vehicle 1 so as to realize the vehicle motion set by the input arbitration unit 21.

Here, when the vehicle motion set by the input arbitration unit 21 includes a turning motion, it is preferable that the turning motion characteristic of the own vehicle 1 has a characteristic suitable for a stable turning motion.
In general, the following characteristics (1) and (2) are mentioned as the characteristics of the controlled object that are likely to become unstable.

(1) The gain (that is, peak gain) of the resonance frequency band in the frequency response is excessive.
(2) The cutoff frequency is too low, and a phase delay is likely to occur.

In the case of the turning motion of the own vehicle 1, it is the frequency response of the yaw rate (that is, the frequency response of the actual yaw rate to the target yaw rate) that affects the stability. FIG. 4 shows an example of a Bode diagram of the frequency response of the yaw rate.
The target yaw rate is a target value of the yaw rate generated in the own vehicle 1 in order to follow a specific target traveling track and travel. The actual yaw rate means the yaw rate actually generated in the own vehicle 1 as a result of turning control to realize the target yaw rate.

The vehicle behavior tends to be unstable during the turning control of the own vehicle 1, for example, when the vehicle speed of the own vehicle 1 is high or when the non-linearity of the cornering force with respect to the slip angle increases (that is, the friction limit is approached). If). When the rear wheel steering is performed, it is more likely to become unstable in these cases.

Therefore, the vehicle control unit 22 of the embodiment has a peak gain G in a resonance frequency band near the resonance frequency _{ω n} of the frequency response of the yaw rate, depending on the vehicle speed of the own vehicle 1, the cornering stiffness of the wheels, the presence or absence of rear wheel steering, and the like. Suppress _p.
Specifically, suppressing the peak gain G _p by adjusting the yaw inertia moment I _z ^* value is a parameter of the vehicle motion model used for calculation of the target yaw moment of the vehicle 1.

Further, the vehicle control unit 22 of the embodiment has a frequency (that is, a control cycle of turning control) in which the turning control of the own vehicle 1 is performed according to the vehicle speed of the own vehicle 1, the cornering stiffness of the wheels, the presence / absence of steering of the rear wheels, and the like. Reciprocal) Suppresses the phase lag in the frequency band 50 near _{ω κ.}
Specifically, suppressing the phase delay in the vicinity of the frequency omega _kappa by adjusting the value of the yaw inertia moment I _z ^*.

If the road shape of the road on which the own vehicle 1 is going to travel has a shape in which the curvature hardly changes (hereinafter referred to as "steady shape"), a phase delay occurs in the frequency response of the yaw rate. Also does not easily affect the turning motion of the own vehicle 1. Rather, if the peak gain G _p is excessive, the actual yaw rate may increase and the behavior may change.
On the other hand, if the road shape of the road on which the own vehicle 1 is going to travel has a shape in which the curvature changes (hereinafter referred to as "transient shape"), if there is a phase delay, the vehicle follows the target travel track. Performance is reduced.

Therefore, the vehicle control unit 22 determines whether or not the road shape of the road on which the own vehicle 1 is going to travel is a steady shape, and if the road shape is a steady shape, suppresses the peak gain Gp. Peak gain suppression Yaw moment of inertia I _zg ^* is calculated.
Further, the vehicle control unit 22 determines whether or not the road shape of the road on which the own vehicle 1 is going to travel is a transient region, and if the road shape is a transient shape, the phase that suppresses the phase delay. The delay suppression yaw moment of inertia I _zp ^* is calculated.

By thus adjusting the value of the yaw inertia moment I _z ^*, as less likely unstable turning control of the vehicle 1, the characteristics of the turning motion of the vehicle 1 can be previously optimized.
As a result, it is possible to suppress the induction of unstable vehicle behavior when the own vehicle 1 turns.
The peak gain suppressing yaw inertia moment I _zg ^* and the phase-delay reducing yaw inertia moment I _zp ^* is an example of the "second yaw moment of inertia" and "first yaw moment of inertia" recited in the respective claims ..

Next, an example of the functional configuration of the vehicle control unit 22 of the embodiment will be described with reference to FIG. The vehicle control unit 22 includes a target yaw angular acceleration calculation unit 50, a target yaw rate calculation unit 51, a peak gain suppression yaw moment of inertia calculation unit 52, a phase delay suppression yaw moment of inertia calculation unit 53, and a road shape determination unit 54. , The multipliers 55, 56 and 58, the adder 57, the target lateral force calculation unit 59, and the steering angle calculation unit 60.

The vehicle control unit 22, based on the vehicle movement of the vehicle 1 which is requested from the input arbitration section 21 sets the target lateral force F _y for turning the vehicle 1.
A target yaw angular acceleration calculation unit 50, the target yaw rate calculating section 51, based on the target lateral force F _y, and the target yaw angle acceleration gamma _'t is a target value of the yaw angular acceleration to be generated in the vehicle 1, the yaw rate _{The target yaw rate γ t} , which is the target value, is calculated.

Peak gain suppressing yaw inertia moment calculation unit 52, a vehicle speed V of the vehicle 1, a front wheel and a rear wheel cornering stiffness C _F ^* and C _R ^*, and presence or absence of wheel steering after the vehicle 1, depending on the calculates a peak gain suppressing yaw inertia moment I _zg ^* for suppressing a peak gain G _p.
Now, the transfer function of the actual yaw rate γ _{r with respect to the target yaw rate γ t} when the four-wheel steering is performed (that is, when the rear wheel steering is performed) is given by the following equation (1).

Variables with a supervised star symbol "*" indicate that they are parameters that can be set by the vehicle control unit 22, and variables without a superposed star symbol "*" are physical. Indicates the state quantity.
The symbol l is the wheelbase of the own vehicle 1, the symbol A is a stability factor, and the symbol s is a Laplace variable.
The symbol Tr is the read time constant of the yaw rate and is given by the following equation (2).

The symbol m is the mass of the own vehicle 1, and the symbol l _F is the distance between the center of gravity of the vehicle and the front wheel axle.
Further, the function D (s) of the equation (1) is given by the following equation (3).

The symbols ω _n and ζ are resonance frequencies and attenuation coefficients, respectively, and are given by the following equations (4) and (5), respectively. The symbol l _R is the distance between the center of gravity of the vehicle and the rear wheel axle.

Here, the components in the above formula (1)

_Is called "transient characteristic" with ^{f TRA *} as follows.

Then, the peak gain | G (jω _n ) | is given by the following equation (7) using the _{transient characteristic f TRA} ^*. The following equation (8) is obtained by solving the following equation (7) with _{respect to the transient characteristic f TRA} ^*.

Therefore, by setting the peak gain | G (jω _n ) | in the equation (8) to a sufficiently small value, the transient characteristic f _TRA ^* _{that suppresses the peak gain | G (jω n} ) | can be set. _{For example, the transient characteristic f TRA} ^* that suppresses the peak gain | G (jω _n ) | by a factor of 1 (that is, 0 [dB]) is obtained by the following equation (9).

The above equation (6) to give the following equation is solved for the yaw inertia moment _I ^{z *} (10), the peak gain | G (j [omega] _n) | Substituting suppressing transient characteristics _{f TRA} ^* and peak gain suppressing yaw inertia The moment of inertia I _zg ^* can be calculated.

_{Further, the peak gain suppression yaw moment of inertia Izg} ^* when two-wheel steering is performed (that is, when rear wheel steering is not performed) has a transient characteristic f _TRA ^* that suppresses peak gain | G (jω _{n) |.} It can be calculated by substituting into equation (11).

Then, the phase delay reducing yaw inertia moment calculation unit 53, a vehicle speed V of the vehicle 1, a front wheel and a rear wheel cornering stiffness C _F ^* and C _R ^*, and presence or absence of wheel steering after the vehicle 1, The phase delay suppression yaw moment of inertia I _zp ^* _{for suppressing the phase delay near the frequency ω κ at} which the turning control of the own vehicle 1 is performed is calculated accordingly.
The phase delay at the frequency ω is obtained for the following equation (12).

Here, it is considered that the phase delay θ (ω _{κ ) at the frequency ω κ} where the turning control of the own vehicle 1 is performed is suppressed as in the following equation (13).
θ _min <θ (ω _κ ) <θ _max … (13)
However, θ _max = + κ | θ (ω _n ) |, θ _min = −κ | θ (ω _n ) |, θ (ω _n ) is the phase delay at the resonance frequency, and κ is a constant less than 1. Is. For example, when κ is 0.1, the phase lag θ (ω _{κ ) at the frequency ω κ} where the turning control is performed is suppressed to about 1/10 of the phase lag θ (ω _{n) at the resonance frequency.} ..

Substituting the above equation (12) into the above equation (13) and _{solving the transient characteristic f TRA} ^* gives the following equation (14). The following equation (14) defines the range of the transient characteristic f _TRA ^* that suppresses the phase delay θ (ω _{κ ) at the frequency ω κ at} which the turning control of the own vehicle 1 is performed.

The phase delay suppression yaw moment of inertia calculation unit 53 sets the transient characteristic f _TRA ^* that satisfies the above equation (14) and substitutes it into the following equation (15) to perform four-wheel steering (that is, rear wheel steering). ) Phase lag suppression yaw moment of inertia I _zp ^* is calculated.

Further, the phase delay suppression yaw moment of inertia calculation unit 53 _{substitutes the transient characteristic f TRA} ^* satisfying the above equation (14) into the following equation (16) to perform two-wheel steering (that is, rear wheel steering). If not, calculate the phase delay suppression yaw moment of inertia I _zp ^*.

The road shape determination unit 54 determines that the road shape of the road on which the own vehicle 1 is going to travel does not change the curvature based on the road curvature information which is the information on the curvature of the road on which the own vehicle 1 is going to travel. It is determined whether the shape is a shape or a transient shape whose curvature changes.
The road shape determination unit 54 calculates a _{steady shape coefficient K s} indicating the degree to which the road shape is a steady shape _{and a transient shape coefficient K t} indicating the degree to which the road shape is a transient shape. The steady shape coefficient K _s and the transient shape coefficient K _t are normalized coefficients having a value in the range of 0 to 1, and have a relationship of _{K s} = (1-K _t).

See FIG. The road shape determination unit 54 inputs, as road curvature information, the standard deviation RhoStd of the curvature of the road on which the own vehicle 1 is going to travel, the left maximum curvature RhoMax, the right maximum curvature RhoMin, and the skewness SQN.
The maximum left curvature RhoMax is the maximum curvature of the left curve of the road on which the own vehicle 1 is going to travel. The maximum right curvature RhoMin is the maximum curvature of the right curve of the road on which the own vehicle 1 is going to travel.

The standard deviation RhoStd is the standard deviation of the curvature distribution, which is the distribution of a set of curvatures at each point on the road on which the own vehicle 1 is going to travel, and the skewness SQN is the skewness of the curvature distribution.
The skewness indicates how much the curvature distribution deviates from the normal distribution. The larger the skewness, the closer the road shape becomes to the transient shape, and the smaller the skewness, the closer the road shape becomes to the steady shape.
The road shape determination unit 54 includes a reference curvature calculation unit 70, a dimensionalization 71, a curvature component conversion unit 72, and a coefficient calculation unit 73.

The reference curvature calculation unit 70 calculates the reference curvature RhoRef as a reference when determining the traveling scene of the own vehicle 1 based on the following equation (17).
RhoRef = K _PTC・ G _max・ g / V ² … (17)
The symbol K _PTC is the base gain, the symbol G _max is the maximum allowable lateral acceleration set in the automatic operation layer 30, and the symbol g is the gravitational acceleration.

The dimensionless 71 makes the skewness SQN, which is a dimensionless quantity, dimensionalized into a value RhoSQN having the same unit as the curvature, based on the standard deviation RhoStd, the left maximum curvature RhoMax, and the right maximum curvature RhoMin. For example, the dimensionalization 71 may make the skewness SQN dimensional based on the following equations (18) to (20).
RhoSQN _L = 3 · RhoStd · | sign (RhoMax) | · max (SQN, 0) ... (18)
RhoSQN _R = 3 · RhoStd · | sign (RhoMin) | · min (SQN, 0) ... (19)
RhoSQN = RhoSQN _L + RhoSQN _R ... (20)

The curvature component conversion unit 72 normalizes (non-dimensionalizes) the dimensional skewness RhoSQN and the standard deviation RhoStd by using the reference curvature RhoRef so that the values are in the range of 0 to 1.
For example, the curvature component conversion unit 72 calculates the normalized skewness NormRhoSQN in which the skewness RhoSQN is normalized and the normalized standard deviation NormRhoStd in which the standard deviation RhoStd is normalized based on the following equations (21) and (22). ..
NormRhoSQN = RhoSQN / RhoRef ... (21)
NormRhoStd = RhoStd / RhoRef ... (22)

_{The coefficient calculation unit 73 calculates the steady shape coefficient K s} and the transient shape coefficient K _t according to the following equations (23) and (24) based on the normalized skewness NormRhoSQN and the normalized standard deviation NormRhoStd.
K _t = max (NormRhoSQN, NormRhoStd) ... (23)
K _s = 1-K _t ... (24)

With reference to FIG. 5, the multipliers 55 and 56 and the adder 57 have a steady shape coefficient K _s and a transient shape coefficient K _t, and have a peak gain suppression yaw moment of inertia I _zg ^* and a phase delay suppression yaw moment of inertia I _zp ^*. the weighted sum weighted respectively bets, calculates a yaw inertia moment I _z ^*.
I _z ^* = K _s x I _zg ^* + K _t x I _zp ^*

The multiplier 58 calculates a target yaw moment M _t by multiplying the yaw inertia moment I _z ^* to the target yaw angle acceleration gamma _'t.
Target lateral force calculating section 59 calculates the target lateral force F _y and the target yaw moment M _t target front wheel lateral force required to impart to the vehicle 1 and F _yf and target rear-wheel lateral force F _yr. For example, based on the vehicle motion model of the vehicle 1, may calculate the target front wheel lateral force F _yf and target rear-wheel lateral force F _yr.

The steering angle calculation unit 60 determines _{the target steering angle θ f of the} front wheels and the target of the rear wheels based on _{the target front wheel lateral force F yf, the} target rear wheel lateral force F _yr , the target yaw rate γ _t, and the target slip angle θ _st. and calculates the steering angle θ _r. The steering actuator included in the actuator 18 steers the front wheels and the rear wheels so that the steering angles of the front wheels and the rear wheels of the own vehicle 1 are the target steering angles θ _f and θ _r , respectively.
In addition to or changing the steering of the front wheels and the rear wheels, the braking force and / driving force of the front wheels and the rear wheels that generate _{the target front wheel lateral force Fyf} and the target rear wheel lateral force F _{yr, respectively, are calculated.} May be good. Brake control actuator and / or accelerator opening actuator included in the actuator 18 may control the braking device and the drive device so as to generate respectively a target front wheel lateral force F _yf and target rear-wheel lateral force F _yr.

(motion)
Next, an example of the vehicle traveling support method of the embodiment will be described with reference to FIG. 7.
Target yaw angular acceleration calculation unit in step S1 50 sets the target yaw angle acceleration gamma _'t to be generated in the vehicle 1.
Step peak gain suppressing yaw inertia moment calculation unit 52 in step S2 calculates a peak gain suppressing yaw inertia moment I _zg ^* for suppressing a peak gain G _p.

In step S3, the phase lag suppression yaw moment of inertia calculation unit 53 calculates the phase lag suppression yaw moment of inertia I _zp ^* for suppressing the phase lag θ (ω _{κ ) at the frequency ω κ where the turning control of the own vehicle 1 is performed.} do.
In step S4, the road shape determination unit 54 acquires information on the road shape of the road on which the own vehicle 1 is scheduled to travel.

In step S5, the road shape determination unit 54 calculates a _{steady shape coefficient K s} indicating the degree to which the road shape is a steady shape.
Road shape determining unit 54 in step S6, a road shape calculating a transient shape factor K _t representing the degree a transient shape.
In step S7, the multipliers 55 and 56 and the adder 57 have a steady shape coefficient K _s and a transient shape coefficient K _t, and have a peak gain suppressing yaw moment of inertia I _zg ^* and a phase delay suppressing yaw inertia moment I _zp ^* , respectively. the weighted weighted sum is calculated as the yaw moment of inertia I _z ^*.

Step multiplier 58 in S8, calculates a target yaw moment M _t by multiplying the yaw inertia moment I _z ^* to the target yaw angle acceleration gamma _'t.
Target lateral force calculating section 59 and the steering angle calculating unit 60 actuator 18 in step S9, the turning of the vehicle 1 based on the target yaw moment M _t.
After that, the process ends.

(Effect of embodiment)
(1) The target yaw angular acceleration calculation unit 50 sets the target yaw angular acceleration to be generated in the own vehicle 1. The phase delay suppression yaw moment of inertia calculation unit 53 has a phase delay of the _{actual yaw rate γ r} that actually occurs in the own vehicle 1 with respect _{to the target yaw rate γ t} generated in the own vehicle 1 at _{the frequency ω κ of the turning control of the own vehicle 1.} The phase lag suppression yaw moment of inertia I _zp ^* is calculated. The road shape determination unit 54 acquires information on the road shape of the road on which the own vehicle 1 is scheduled to travel, and determines whether or not the road shape is a transient shape whose curvature changes.

If the road shape is transient shape, multipliers 55, 56 and 58 and the adder 57, generated in the subject vehicle 1 in accordance with the target yaw angle acceleration gamma _'t and the phase-delay reducing yaw inertia moment I _zp ^* to calculate the target yaw moment M _t to be.
A target lateral force calculating section 59 a steering angle calculating unit 60 and the actuator 18 to pivot the vehicle 1 based on the target yaw moment M _t.

As a result, the phase delay in the control cycle of the driving support control system can be suppressed, so that errors and delays are suppressed with respect to the plans and strategies (trajectories, etc.) planned by the automatic driving layer 30 which is the upstream driving support system. You will be able to control it. As a result, it is possible to prevent the vehicle behavior from becoming unstable due to the phase delay of the frequency response of the yaw rate.

(2) The phase lag suppression yaw moment of inertia calculation unit 53 may calculate the phase lag suppression yaw moment of inertia _Izp ^* according to the vehicle speed of the own vehicle 1 and the cornering stiffness of the wheels of the own vehicle 1.
The vehicle behavior tends to be unstable when the vehicle speed of the own vehicle 1 increases or when the non-linearity of the cornering force with respect to the slip angle increases. By suppressing the phase lag according to the vehicle speed and the cornering stiffness, it is possible to suppress the instability of the vehicle behavior.

(3) The phase delay suppression yaw moment of inertia calculation unit 53 may calculate the phase delay suppression yaw moment of inertia _Izp ^* depending on the presence or absence of rear wheel steering of the own vehicle 1.
When rear wheel steering is being performed, the vehicle behavior is more likely to become unstable due to the increase in vehicle speed and the non-linearity of the cornering force with respect to the slip angle. By suppressing the phase lag depending on the presence or absence of rear wheel steering, it is possible to prevent the vehicle behavior from becoming unstable.

(4) The road shape determination unit 54 may determine whether or not the road shape is a transient shape according to the skewness of the curvature distribution of the road shape.
Thereby, it is possible to determine whether or not the road shape is a transient shape based on the map information of the map database 14 and the curvature information of the road shape obtained by the object sensor 11.

(5) the road shape determining unit 54, the road shape may calculate the transient shape factor K _t representing the degree a transient shape. The multipliers 55, 56 and 58 and the adder 57 may calculate the target yaw moment M _t according to the phase lag suppression yaw moment of inertia I _zp ^* _{weighted by the transient shape coefficient K t.}
As a result, the phase delay can be suppressed according to the degree to which the road shape is a transient shape.

(6) the road shape determining unit 54, in accordance with the distortion of the curvature distribution of the road shape may be calculated transient shape factor K _t.
Accordingly, and map information of the map database 14, the curvature information obtained road shape object sensor 11 can calculate the transient shape factor K _t.

(7) The peak gain suppression yaw moment of inertia calculation unit 52 may calculate the _{peak gain suppression yaw moment of inertia I zg} ^* that suppresses the peak gain of the frequency response of the actual yaw rate γ _{r with respect to the target yaw rate γ t.} The road shape determination unit 54 may determine whether or not the road shape is a steady shape whose curvature does not change.
If the road shape is normal shape, target lateral force calculating section 59 and the steering angle calculating unit 60 and the actuator 18, the target yaw depending on the target yaw angle acceleration gamma _'t and the peak gain suppressing yaw inertia moment I _zg ^* The moment M _t may be calculated.

When the road shape of the road on which the own vehicle 1 is scheduled to travel is a steady shape, that is, when the curvature is constant, even if the control delay is acceptable, the fluctuation of the gain characteristic is suppressed and the fluctuation of the gain characteristic is suppressed in any frequency band. It is desirable that the behavior does not fluctuate significantly.
Further, if the peak gain is large, the output to the input becomes large, and the behavior may change even in a situation where the curvature is constant and the vehicle can run relatively stably. By suppressing the peak gain when the road shape is a steady shape as described above, it is possible to suppress the induction of unstable vehicle behavior.

(8) The road shape determination unit 54 may calculate _{a steady shape coefficient K s} indicating the degree to which the road shape is a steady shape. Multipliers 55, 56 and 58 and the adder 57 in accordance with the weighted peak gain suppressing yaw inertia moment _{I zg} ^* by constant shape factor _{K s,} may calculate the target yaw moment _{M t.}
As a result, the peak gain can be suppressed according to the degree to which the road shape is a steady shape.

1 ... own vehicle, 10 ... driving support device, 11 ... object sensor, 12 ... vehicle sensor, 13 ... positioning device, 14 ... map database, 15 ... navigation device, 16 ... communication device, 17 ... controller, 18 ... actuator, 20 ... Automatic driving control unit, 21 ... Input arbitration unit, 22 ... Vehicle control unit, 30 ... Automatic driving layer, 31 ... Arbitration unit, 32 ... Standard model unit, 33 ... Vehicle body behavior control unit, 34 ... Wheel behavior control unit, 40 ... Localization section, 41 ... Destination setting section, 42 ... Route planning section, 43 ... Action decision section, 44 ... Driving zone planning section, 45 ... Track generation section, 46 ... World model, 47 ... Local model, 50 ... Target inertia Angular acceleration calculation unit, 51 ... Target yaw rate calculation unit, 52 ... Peak gain suppression yaw moment of inertia calculation unit, 53 ... Suppression yaw inertia moment calculation unit, 54 ... Road shape determination unit, 55 ... Multiplier, 56 ... Multiplier, 57 ... adder, 58 ... multiplier, 59 ... target lateral force calculation unit, 60 ... steering angle calculation unit, 70 ... reference curvature calculation unit, 71 ... dimensionalization, 72 ... curvature component conversion unit, 73 ... coefficient calculation unit

Claims (9)

In the driving control method of the controller that executes the turning control so as to obtain the vehicle motion of the own vehicle based on at least one of the operation input of the driver of the own vehicle and the instruction input from the automatic driving control of the own vehicle, the above-mentioned The controller is
Based on the vehicle motion model of the own vehicle, the first yaw moment of inertia that suppresses the phase delay of the actual yaw actually generated in the own vehicle with respect to the target yaw rate generated in the own vehicle of the turning control is calculated.
Obtain information on the road shape of the road on which the own vehicle is scheduled to travel,
It is determined whether or not the road shape is a transient shape whose curvature changes, and it is determined.
When the road shape is a transient shape, the target yaw moment generated in the own vehicle is calculated according to the target yaw angular acceleration of the turning control and the first yaw moment of inertia.
The own vehicle is turned and controlled based on the target yaw moment.
A driving support method characterized by that. The traveling support method according to claim 1, wherein the first yaw moment of inertia is calculated according to the vehicle speed of the own vehicle and the cornering stiffness of the wheels of the own vehicle. The traveling support method according to claim 2, wherein the first yaw moment of inertia is calculated according to the presence or absence of steering of the rear wheels of the own vehicle. The traveling support method according to any one of claims 1 to 3, wherein it is determined whether or not the road shape is the transient shape according to the skewness of the curvature distribution of the road shape. .. A transient shape coefficient representing the degree to which the road shape is the transient shape is calculated.
The target yaw moment is calculated according to the first yaw moment of inertia weighted by the transient shape coefficient.
The driving support method according to any one of claims 1 to 4, wherein the driving support method is characterized by the above. The traveling support method according to claim 5, wherein the transient shape coefficient is calculated according to the skewness of the curvature distribution of the road shape. The second yaw moment of inertia that suppresses the peak gain of the frequency response of the actual yaw rate with respect to the target yaw rate is calculated.
It is determined whether or not the road shape is a steady shape whose curvature does not change, and it is determined.
When the road shape is a steady shape, the target yaw moment is calculated according to the target yaw angular acceleration of the turning control and the second yaw moment of inertia.
The driving support method according to any one of claims 1 to 6, wherein the driving support method is characterized. A steady shape coefficient indicating the degree to which the road shape is the steady shape is calculated.
The target yaw moment is calculated according to the second yaw moment of inertia weighted by the steady shape coefficient.
The driving support method according to claim 7, wherein the vehicle is characterized by the above. A steering device that steers the steering wheel of the own vehicle,
A drive device that applies driving force to the wheels of the own vehicle,
A braking device that applies braking force to the wheels, and
A controller that executes turning control so as to cause the vehicle motion of the own vehicle based on at least one of the operation input of the driver of the own vehicle and the instruction input from the automatic driving control of the own vehicle is provided.
The controller suppresses the phase delay of the actual yaw rate actually generated in the own vehicle with respect to the target yaw rate generated in the own vehicle in the turning control based on the vehicle motion model of the own vehicle. Is calculated, information on the road shape of the road on which the own vehicle is scheduled to travel is acquired, it is determined whether or not the road shape is a transient shape whose curvature changes, and the road shape is a transient shape. In this case, the target yaw moment generated in the own vehicle is calculated according to the target yaw angular acceleration of the turning control and the first yaw moment of inertia, and the own vehicle is used as the steering device based on the target yaw moment. A traveling support device characterized by controlling the steering of the steering wheel, the driving force applied to the wheels by the driving device, or the braking force applied to the wheels by the braking device to control turning.

Images