JPH0399305A - Automatic operating controller for vehicle - Google Patents

Abstract

PURPOSE:To suppress the course deviation of a vehicle to a minimum by judging steady circular turning when the variation of a stability factor exceeds a prescribed value, storing the judged result and correcting a steering value in accordance with the size of the stored stability factor. CONSTITUTION:A stability factor detecting means D calculates a stability factor corresponding to a road state from a vehicle speed, a steering angle and a body turning variable obtained from a vehicle speed detecting means A, a steering angle detecting means B and a turning variable detecting means C and a stability factor variation detecting means E detects the stability factor variation obtained by the means D, and when the variation is less than a prescribed value, decides steady circular turning and stores the stability factor in a storage means F. A correction means G corrects a program steering value in accordance with the size of the stored stability factor obtained at the time of steady circular turning. Since only the stability factor obtained at the time of steady circular turning is stored and steering correction corresponding to the stability factor can be executed, steering corresponding to a change in the road state can be attained.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to an autopilot control system for a vehicle, and more particularly to control contents of an autopilot control system for automatically driving a vehicle along a predetermined taxiway.

[Prior Art] Automated vehicles that automatically travel along a predetermined taxiway (driving course) have been known for some time, and are used in unmanned guided vehicles in factories, durability tests, and the like. This self-piloted vehicle, for example, has a guidance cable attached to the driving course, and uses a magnetic field sensor to detect the position of the guidance cable, and automatically operates the steering wheel, etc., realizing autonomous driving along the guidance cable. .

Furthermore, the present applicant causes the driver to travel a driving course in advance and memorizes the course and steering amount, etc.
It is also proposed that the vehicle be operated automatically according to the steering values and other information taught by the driver, thereby realizing vehicle operation similar to that actually driven by a human.

[Problems to be Solved by the Invention] However, in the above-mentioned automatic driving, if the coefficient of friction μ of the road surface changes or if the vehicle cannot travel at the target speed,
The cornering force of the front and rear wheels changes in a curve, and the steering characteristics of the vehicle change accordingly. When the steering characteristics change, there is a problem in that the turning radius of the vehicle relative to the steering angle changes, resulting in course deviation.

For this reason, the applicant calculated the stability factor based on the vehicle speed, steering angle, and amount of vehicle body turning.
Correcting the steering angle based on this stability factor was proposed in Japanese Patent Application No. 1-18204. In this proposed method, a Kalman filter is used to estimate the state so that steady circular turns can be determined even on rough roads. This is because the stability factor can be calculated correctly only during steady circular turns; if the stability factor is calculated during other unsteady circular turns, the stability factor will be an incorrect value and the correct steering correction will not be possible. This is because it cannot be done.

If the state is estimated using a Kalman filter and the stability factor is calculated, steady circular turning can be estimated even on rough roads, and the correct stability factor can be calculated.

However, state estimation using such a Kalman filter has the problem that the calculation contents are complicated and the calculation time is long. In addition, Kalman filters can calculate correct results when the coefficients match the actual model, but depending on changes in driving conditions, errors may occur between the models and the coefficients may not match, making accurate state estimation impossible. There was also the problem that there were cases where it was not possible to calculate the stability factor.

This invention was made with the aim of solving the above-mentioned problems, and it is possible to determine a steady circular turn with a simple configuration, and it takes into account the accurate stability factor during this steady circular turn. An object of the present invention is to provide a vehicle automatic steering control device that can perform steering correction.

[Means for Solving the Problems] As shown in FIG. 1, the vehicle autopilot control device according to the present invention includes vehicle speed detection means A for detecting the traveling speed of the vehicle;
Steering angle detection means B for detecting the steering angle of the vehicle, turning amount detection means C for detecting the amount of turning of the vehicle body, and these detection means A
- a stability factor calculation means for calculating a stability factor corresponding to the road surface condition of the traveling course from the vehicle speed, steering angle, and amount of vehicle body turning obtained from C; stability factor change amount detection means E for detecting the factor change amount; storage means F for determining a steady circular turn when the stability factor change amount is less than a predetermined value and storing the stability factor at this time; and a correction means G that corrects the programmed steering value according to the stored stability factor during steady circular turning, and is characterized in that it performs steering according to changes in road surface conditions of the driving course. shall be.

[Operation] The vehicle automatic steering control device according to the present invention has the above-described configuration, and calculates the stability factor from the vehicle speed, steering angle, and vehicle turning state obtained from each detection means. Then, when the amount of change in the stability factor is less than or equal to a predetermined value, it is determined that the vehicle is turning in a steady circle, and the stability factor at this time is stored. Therefore, the stability factor only during a steady circular turn can be stored, and the steering correction can be made accordingly, making it possible to perform steering in accordance with changes in the road surface conditions of the travel course.

Here, the stability factor A can be expressed by the following formula.

A= −(m/2jri ((j!f −Kf −
j! r・Kr)/Kf −Kr) Here, M is the vehicle weight, I! f is the front wheel base (distance from the center of gravity to the front wheel), j! r is the rear wheel base (
distance from the center of gravity to the rear wheels), Kf is the front wheel cornering power (centripetal force), and Kr is the rear wheel cornering power (centripetal force).

As is clear from this equation, a small amount of change in the stability factor means that the difference between the front wheel cornering power and the rear wheel cornering power is small. Therefore, by reducing the amount of change in the stability factor, it is possible to approximate the vehicle characteristics of a steady circular turn in which changes in steering angle, yaw rate, and vehicle speed are zero.

[Embodiments] Hereinafter, embodiments of the present invention will be described based on the drawings.

FIG. 2 is a block diagram showing the processing functions of the vehicle autopilot control device according to the embodiment, and FIG. 3 is a schematic diagram showing the configuration of the mobile controlled vehicle.

In this embodiment, the guideway is set as a target course taught by the driver's driving, and the vehicle is maneuvered along this target course, and the steering amount is corrected based on the value of the stability factor.

Regarding the overall configuration, first, the configuration of the autopilot vehicle will be explained with reference to FIG. In the figure, in order to detect the lateral displacement Y of the vehicle, a front magnetic field sensor 110a, a front lateral displacement detection circuit 111a, a rear magnetic field sensor 110b, and a rear lateral displacement detection circuit 111b are provided, and a guidance cable provided in the taxiway is installed. The magnetic field output from 20 is detected to determine the lateral displacement and the yaw angle.

That is, as shown in Fig. 5, the lateral displacement of the front part is
``, If the rear lateral displacement Yr, then the center position O of the vehicle 28
The lateral displacement Y at is Y − (Yf + Yr) / 2 − (1)
And if the length of the vehicle is a, then the yaw angle θ of the vehicle is
is θ-(Yf-Yr)/a =-(2)
Therefore, from this, the lateral displacement Y1 yaw angle θ is determined.

Then, the yaw rate (yaw angular velocity) γ can be determined from the time change of the yaw angle using the following equation.

γ-dθ/dt - (θ-1-〇)/Δt (θ-1 is the previously detected yaw angle, Δ is the detection time interval)...
・(3) Also, the magnetic pickup 11 is used to find the vehicle speed.
The vehicle speed is detected by detecting the number of rotations of a magnet rotary plate 113, which is provided with a magnet rotary plate 113 and rotates in accordance with the rotation of the wheels.

An antenna 115 and a reference position detection circuit 116 are provided to detect the position of the vehicle on the taxiway, and a position beacon 22 is provided at each predetermined point on the taxiway.
The antenna 11 transmits radio waves representing a device code consisting of
5 and decoded by the reference position detection circuit 116, the reference position on the course can be detected.

In addition, an arithmetic processing circuit (ECU) 24 is used to input detection signals etc. from the various sensors mentioned above and perform various arithmetic processing.
A feedback processing circuit 26 is provided which performs predetermined processing by feeding back the operation amounts of various actuators that operate the vehicle. These processing circuits have a configuration as shown in FIG. 4 on the hardware of the microcomputer.

In addition to the illustrated steering angle drive motor 29, various actuators provided in the vehicle 28 for automatic steering include an accelerator, a brake, an actuator, etc., and the amount of operation of these is also controlled.

Further, detected values from sensors provided in various actuators, such as the steering amount sensor 32, are supplied to the feedback control circuit 26, and are each subjected to feedback control.

In addition, since this embodiment automatically steers the taxiway along a target course taught by a human, there is also a manual switch 34 for switching between the taught driving mode and the automatic driving mode, and a display lamp 36 for identifying this mode state. has been established.

In FIG. 2, a target course map 14a and a manipulated variable map 14b are provided as storage means, but in this embodiment, since the taught target course is automatically steered, the target course map 14a is stored in the target course map 14a detected from the position beacon 22 etc. during the taught operation. information on the position X and the lateral displacement Y during teaching operation at this position X. and yaw angle θ0 are averaged by the averaging unit 241 and stored. Lateral displacement Y0 and yaw angle θ0 in this case
is a value measured based on the guideway rather than the target course, and is a value measured from the guide cable 20 in the embodiment. In this way, if a target course is taught for a predetermined taxiway, there is an advantage that the actual travel course can be freely determined for the taxiway.

In the operation amount map 14b, the operation amounts when the driver operates various actuators during the teaching operation are averaged by the averaging section 242 and stored. for example,
Steering values (programmed steering values), accelerator amounts, and brake amounts for operating the vehicle at each position on the taxiway are stored, and autopilot control is performed according to the manipulated variables stored in the manipulated variable map 14b.

Regarding prediction errors, in the automatic pilot of this embodiment, steering control is performed using prediction errors.

Therefore, for the prediction 7111 error calculation, adder/subtractor 161, 162, prediction error calculation unit 163, and gain multiplier 164 are used.
is provided, thereby correcting the steering value read from the operation amount map 14b.

For example, when the vehicle is running in the state shown in FIG. 6, the following calculation is performed.

In the figure, the vehicle 28 is automatically traveling on a target course 800, but Δj! m (lateral displacement)
The yaw angle of the vehicle at this time is Δθ. This yaw angle Δθ is the tangent line 801 (801-
) is the direction of the vehicle.

In this state, under normal feedback control, 61
A steering angle is given to correct m, but in the present invention, a predicted error amount ε0 for Lm ahead is determined. Note that this distance is preferably 10 to 20 m.

In other words, the current yaw angle of the vehicle is Δθ, which means that at Lm ahead, L・Δθ (Δθ is small (sinΔθ
This corresponds to the occurrence of an error of the cape Δθ). Therefore, the prediction error ε for Lm ahead. −Δl−LφΔθ
...(4) is calculated, and the steering correction is performed based on this. Note that this calculation is performed by the error calculation section 163.

In order to use the lateral displacement and yaw angle, which are information for calculation in this case, as values based on the guide cable (taxiway), the current detected values are added to the adder/subtractor 161 from the output of the target course map 141.
, 162. That is, the above (4
) in the equation is Δ1-Y0-Y, and Δθ is Δθ-θ. −
becomes θ.

Then, the prediction error ε obtained by the error calculation unit 163.

is multiplied by the motion gain Kb by the gain multiplier 164 to calculate the steering correction amount Δu,).

ΔuQ smKbε. (5) If this steering correction amount Δtlo is output as is, the correction will be made too frequently. Therefore, a dead band within a predetermined range is provided, and the conversion unit 165 adjusts the steering correction amount so that the correction is performed only when the dead band exceeds this range. Convert to correction amount ΔU. This is then output to the adder 18, which is actuator operation amount calculation means.

Vehicle Steering Gain Estimation Mechanism A characteristic feature of the present invention is that it includes a vehicle steering gain estimation mechanism 40. This vehicle steering gain estimating mechanism 40 calculates the actuator operation amount stored in the above-mentioned operation amount map 14b by the road surface friction coefficient μ.
It is corrected according to changes in vehicle environmental conditions.

That is, the vehicle steering gain estimating mechanism 40 stores the correction gain Kp calculated by comparing the stability factor during the previous actual driving and the stability factor during the teaching, and supplies this to the multiplier 42. . Therefore, the steering value δ output from the manipulated variable 14b is corrected by the correction coefficient Kp in the multiplier 42.

δref-kp·δ Then, this corrected steering value δref is supplied to the adder 18, and is added to the steering correction value ΔU to calculate the steering amount U.

Since the steering is performed using the steering amount μ, it is possible to perform steering control according to the road surface condition. Note that the sample and hold circuit 166 is for smoothing control.

First Embodiment Next, a first embodiment of calculating the correction gain Kp in the vehicle steering gain estimating mechanism 40 will be described based on the flowchart of FIG.

First, constants specific to the vehicle, such as the wheelbase, are stored as initial settings (Sl). Next, the vehicle position x1 steering angle Δ and vehicle speed V are determined from various sensors.

The yaw rate γ is taken in (S2). Then, the stability factor A is calculated from these detected values (S3).
. Here, the stability factor A is calculated using one of the following two equations.

A-((ρ・δ/J)-11/v2-C6)A-(
(V-6/J2 ・7)-1+/V2-(7) Here,
ρ is a turning radius as a turning amount, and is detected by a turning amount detection means. For example, the turning radius ρ is determined by the lateral displacement Δ
It is calculated by adding the course deviation Δρ with a positive sign to l toward the outside in the radial direction. Note that the turning radius ρ may be stored in advance as a map in accordance with the travel distance 1. Further, the turning radius ρ may be determined by a signal from a beacon, or may be calculated based on a programmed steering value.

When the stability factor A has been calculated in this way, the time change ldA/dtl is then calculated and compared with a predetermined threshold M (S4).

Here, this differentiation usually takes the difference between the stability factor A calculated by the current control loop and the stability factor A a-1 obtained by the previous control loop, and calculates the difference between the stability factor A calculated by the current control loop and the stability factor A a-1 obtained by the previous control loop. It is calculated by dividing by the time Δt.

Then, the amount of change in stability factor A is the threshold value M
If it is smaller, it is considered a steady circular turn and the flag is set to 1.
(S5). On the other hand, stability factor A
If the change is large, a flag is set to 0 as an unsteady circular turn (S6).

When it is determined whether or not the vehicle is making a steady circular turn in this way, it is then determined whether or not this control loop is a driver instruction (S7).

If it is driver instruction, a target map is created (S8).

This target map is the manipulated variable map 14b in FIG.
It is written as , and the position XO+XI, X2...
The stability factor Alf, vehicle speed Vl, δ peak, etc. at * are stored. On the other hand, if it is not a driver instruction, a state map within the vehicle steering gain estimation mechanism 40 is created (S9). This state map stores the stability factor A1, vehicle speed v1, steering amount δ, etc. in correspondence with the position X, similar to the above-mentioned operation amount map, but here, the above-mentioned step S5. Whether the flag set in S6 is 1 or 0 is also stored.

When the state map has been created, it is then determined whether one lap of the driving course has been completed (S1
0). If the vehicle has not traveled for −1 lap, the process returns to step S2, and calculations are performed using the data at the next vehicle position X, and the state map creation is repeated. Then, when you have finished creating the state map for -1 cycle in this way,
A correction gain Kp is calculated (S12). That is,
The correction gain Kp is calculated by the following equation.

Kp - (1+A'-V")/(1+A-V") This relationship can be expressed by assuming that the turning radius ρ at the time of stability factor calculation described above is equal to the turning radius ρ at the time of driver instruction. It can be calculated.

Here, in calculating this correction gain Kp, the average value λ of stability factors A and AX, λ calculations are not performed for all A, but only for A when the flag in the state map is 1. . That is, in the above-mentioned SIO, a flag 1 or 0 is stored in the status map. Since the position where flag 1 is set is the steady circular turning part, in order to take the average value of only the stability factor A during steady circular turning, the average value λ of only the stability factor at flag 1 is required. All you have to do is calculate.

On the other hand, in the calculation of the correction coefficient Kp, the operation amount map 1
The average value of the stability factor Ajf in 4b is also
It must be the average value AX of only those at the same position. Therefore, the location of flag 1 in the state map is read out, the corresponding peak is read from the target map, and only the read A peaks are averaged to calculate the average value λ.

Then, the correction gain Kp is calculated by comparing the average values λ and λ ice of the stability factors during steady circular turning.

Then, the correction gain Kp obtained in this way is stored internally.

When the vehicle is running, the above-mentioned state map is always created, but the correction gain Kp during actual control is the one obtained during the immediately preceding run and is output.

As a result, when the vehicle is traveling around a large number of times, it is possible to perform steering correction according to changes in road conditions by using the immediately preceding correction gain Kp.

In the above explanation, only the steering angle was explained as the manipulated variable, but the accelerator actuator and the brake actuator are controlled so that the vehicle speed V* stored in the steering amount map 14b is achieved, and the vehicle steering It is preferable that the accelerator/brake control values are also corrected using the same method as the gain estimating mechanism 40, so that good automatic steering can be performed.

Here, in this invention, the stability factor A
Steady circular turning is determined by the amount of change in . Therefore,
The quality of this determination will be explained using the results of a simulation in which a four-wheel drive vehicle traveled on a figure-eight curve driving course.

In simulation 1, the road was good, the vehicle speed was -45km/
The experiment was conducted under conditions where h was constant and the friction coefficient μm was constant at 0.6. At this time, steering angle δ, yaw rate γ, turning radius ρ, stability factor A1, differential value of stability factor d
The values of A/dt are shown in FIGS. 8(A) to 8(E), respectively.

As is clear from the figure, it can be seen that in a portion where the turning radius is approximately constant, the stability factor A is also approximately constant in response to minute changes in the steering angle δ and yaw rate γ. Therefore, the rate of change in the stability factor at this time is also approximately 0.

Simulation 2 In simulation 2, the road is good, the friction coefficient μm0
．． 6 Under certain conditions, the vehicle speed was reduced from 45 km/h to 30 km/h, and then accelerated again to 45 km/h. Figure 9 (
A) and (B) respectively show the states of the turning radius and stability factor in this case, and it is understood that even in this case, when the turning radius is approximately constant, the stability factor is approximately constant. be done.

Simulation 3 In simulation 3, the road is rough, μm0゜6 constant,
The case where the vehicle speed was changed to 445-30-45 k/h as in Experiment 2 is shown. In this case as well, the 10th
As shown in FIGS. (A) to (C), the stability factor is constant in a portion where the turning radius is approximately constant.

From the above experimental examples, it can be seen that it is possible to determine whether or not a steady circular turn is occurring by changing the stability factor.

Second Embodiment Next, FIG. 11 is a flowchart of a vehicle autopilot control system according to a second embodiment of the present invention. It is determined whether not only the amount of change but also the amount of change in the yaw rate γ or the steering amount δ is less than or equal to predetermined values N and P. By looking at the amount of change in the yaw rate γ or the steering value δ in this manner, it is possible to more accurately determine whether or not the vehicle is making a steady circular turn, and accurate control can be performed.

[Effects of the Invention] As explained above, according to the automatic steering control device for a vehicle according to the present invention, it is possible to determine whether or not a steady circular turn is being made by simply determining whether the amount of change in the stability factor is less than or equal to a predetermined value. It is possible to determine whether Since the steering amount is corrected using the stability factor during steady circular turning, it is possible to minimize course deviations caused by changes in road surface conditions such as good roads and bad roads, which is suitable. Autopilot can be achieved.

[Brief explanation of drawings]

FIG. 1 is a block diagram showing the configuration of an autopilot control device for a vehicle according to the present invention, FIG. 2 is a functional block diagram of an embodiment, FIG. 3 is a block diagram of an autopilot vehicle according to the embodiment, and FIG. 4 5 is an explanatory diagram for calculating the yaw angle θ of the same embodiment. FIG. 6 is a prediction error ε of the same embodiment. An explanatory diagram for calculation, FIG. 7 shows the vehicle steering gain estimation mechanism 4 in the first embodiment.
8 to 10 are characteristic diagrams for explaining the experimental results in the same embodiment. FIG. 11 is a flowchart diagram of the vehicle steering gain estimating mechanism 40 in the second embodiment. 14a...Target course map 14b...Manipulation amount map 20...Guidance cable 22...Position beacon 28...Vehicle 40...Vehicle steering gain estimation mechanism 110...
Magnetic field sensor 114... Magnetic pickup 115...
・Antenna

Claims (1)

[Claims] (1) In a vehicle automatic steering control device that stores in advance a programmed steering value for traveling on a predetermined driving course and performs automatic steering according to the programmed steering value, the vehicle speed detecting means detects the traveling speed of the vehicle; , a steering angle detecting means for detecting the steering angle of the vehicle, a turning amount detecting means for detecting the amount of turning of the vehicle body, and a vehicle speed, a steering angle, and a turning amount of the vehicle body obtained from these detecting means to correspond to the road surface condition of the driving course. stability factor calculation means for calculating a stability factor that is calculated by the stability factor calculation means; stability factor change amount detection means for detecting the amount of change in the stability factor obtained by the stability factor calculation means; Storage means for determining a steady circular turn in the following cases and storing the stability factor at this time; and correction for correcting the programmed steering value according to the stored stability factor for the steady circular turn. What is claimed is: 1. An automatic steering control device for a vehicle, characterized in that the device comprises: and performs steering according to changes in road surface conditions on a driving course.