JP3511844B2 - Vehicle running condition prediction device, alarm device using the same, and medium recording prediction data - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a vehicle running condition predicting device for predicting a lateral acceleration of a vehicle which occurs when a vehicle is traveling through a curve, and the predicted lateral acceleration exceeds a predetermined reference value. In some cases, the present invention relates to a vehicle running state alarm device that issues an alarm, and a medium that records prediction data.

[0002]

2. Description of the Related Art Conventionally, a navigation device for guiding a route when a vehicle is running has been known, and it is often mounted on a vehicle. This navigation device has map data including road shape data, and always grasps the current position. Therefore, it is possible to know that there is a curve ahead in the traveling direction before entering the curve.

Therefore, using a navigation device,
It has also been proposed to optimize the vehicle speed when entering a curve. For example, in Japanese Unexamined Patent Publication No. 5-141979, the radius of curvature R of the curve ahead and the lateral acceleration G during traveling on the curve are calculated from the current vehicle speed, and this is compared with a predetermined reference value G ₀ . Then, the lateral acceleration G is the reference value G _0.
If it exceeds, it is judged that deceleration is necessary and a warning is issued.

Therefore, the driver decelerates in response to this warning, so that the vehicle speed at the time of entering the curve can be made appropriate and the vehicle can stably pass through the curve.

[0005]

However, the curve warning as described above has a problem in that the warning is issued even at a speed at which the vehicle can travel stably, and the warning feels troublesome. In particular, in the conventional device, a warning is often issued when the driver is trying to decelerate, which causes annoyance.

The present invention has been made in view of the above problems, and provides a vehicle running state predicting apparatus capable of appropriately predicting lateral acceleration and a vehicle running state warning apparatus capable of appropriately issuing a warning using the same. The purpose is to provide.

[0007]

SUMMARY OF THE INVENTION The present invention is a vehicle running condition predicting apparatus for predicting a lateral acceleration of a vehicle which occurs when a vehicle is going through a curve to be traveled, the vehicle speed detecting apparatus detecting a vehicle speed of a vehicle. Means and a database having data on curve curvature and data on road crossing slope as data relating to points in the road traveling direction,
It is characterized by further comprising: a prediction unit for predicting a lateral acceleration in a curve to be entered, based on a vehicle speed detected by the vehicle speed unit and a curve curvature and a transverse gradient in front of the road read from the database. .

The lateral acceleration when traveling on a curve can be basically predicted by the traveling speed of the vehicle and the curvature of the curve. However, generally in a curve, the road has a cross slope, so that the lateral force of the tire during turning is reduced. Whether or not a curve can be stably turned is evaluated by comparing the frictional force between the tire and the road surface in the road surface cross section and the road surface direction component of the centrifugal force of the vehicle. Therefore, the alarm generation condition can be set more appropriately by considering the road vertical gradient.

Further, according to the present invention, the predicting means predicts a vehicle speed when traveling ahead in a curve as a time function considering the detected current vehicle speed and an assumed acceleration / deceleration pattern, and based on the predicted vehicle speed. The lateral acceleration is predicted as a function of time.

For example, by setting a condition as the assumed acceleration / deceleration pattern so that the acceleration / deceleration at the present time is maintained for a predetermined time, it is possible to predict the future vehicle speed in consideration of the traveling state at the present time. As a result, it is possible to predict a suitable traveling speed on a curve that is about to enter.

Further, according to the present invention, the prediction of the lateral acceleration in the prediction means is a prediction of the maximum lateral acceleration in the entire curve to be entered, and when the predicted maximum lateral acceleration exceeds a predetermined reference value, the driver is informed. The feature is that an alarm is issued.

As described above, when the maximum lateral acceleration exceeds the reference value, it is predicted that stable running cannot be performed. Therefore, by issuing a warning prompting deceleration at the predicted time point, the speed at the time of entering the curve can be reduced, and stable traveling on the curve can be promoted.

[0013]

[0014]

[0015]

Further, the present invention is a medium which stores a program for operating a vehicle running state predicting device for predicting a lateral acceleration of a vehicle which occurs when passing through a curve which is about to travel. Causes the vehicle running state prediction device to capture the vehicle speed of the vehicle detected by the vehicle speed detection means, and as a data relating to the point in the road traveling direction, a database having data on the curve curvature and the data on the road crossing slope is used. It is characterized in that the curve curvature and the transverse gradient in front of the vehicle are captured, and the lateral acceleration in the curve to be entered is predicted based on the captured vehicle speed, the curve curvature, and the transverse gradient.

[0017]

BEST MODE FOR CARRYING OUT THE INVENTION Preferred embodiments of the present invention (hereinafter referred to as embodiments) will be described below with reference to the drawings.

[Overall Configuration] FIG. 1 is a block diagram showing the overall configuration of a driving support device to which the device and medium according to the present embodiment are applied. First, the arithmetic processing unit 10 performs arithmetic processing based on various input signals and outputs various control signals.

The GPS receiver 12 receives a radio wave from an artificial satellite and performs GPS (Global Positioning System) processing for detecting the current position, from which the current position signal is supplied to the arithmetic processing unit 10. To be done.
In the present embodiment, GP multiplex broadcasting is used to
The DGPS (differential / GPS) is used to obtain the error information of S and increase the accuracy of the current position detection. Therefore, the current position can be detected with an accuracy of 2 to 3 m or less. It is also preferable to combine map matching, beacon communication, and position detection by autonomous navigation.

The map database 14 has road map information for use in normal navigation. In particular, this map database 14 has an inadequacy flag for each point on the map (appropriate interval on the road), X, Y coordinates, curvature, road surface cant, vertical gradient, and deceleration necessity at each point. ing. These data are then processed as a function of the current and future vehicle position by the processor 10.
To provide. The map database 14 is a CD
-ROM or the like is used, but a relatively large capacity storage medium such as a magnetic disk or a DVD is used.

The wheel speed sensor 16 detects the rotation of the rotating shaft by an optical method or a magnetic method, and generates a pulse signal according to the number of rotations of the wheel. In this example, the rotational speeds of the left and right front wheels, which are non-driving wheels, are detected.
The arithmetic processing unit 10 detects state quantities related to vehicle motion such as vehicle speed and acceleration from the output of the wheel speed sensor 16. It should be noted that it is better to separately provide vertical and horizontal acceleration sensors, check the accuracy and calculation result of each sensor, and correct if necessary.

Further, the inadequacy sensor 18 is composed of a raindrop sensor, a wiper switch, an image pickup device for the road surface, etc., and provides the arithmetic processing unit 10 with an inadequate level for traveling according to the wet condition of the road surface as an inadequacy flag. .

The arithmetic processing unit 10 is based on the road shape, the current position, the vehicle speed, the acceleration, etc., and the future vehicle speed, position,
Predict lateral acceleration etc. The arithmetic processing unit 10
Uses the inadequacy flag at the time of lateral acceleration control.

An alarm output device 20 and a speed reducer 22 are connected to the arithmetic processing unit 10 as output side devices. The alarm output device 20 includes a speaker for sound output, a buzzer, an LED (light emitting diode), a display, and the like, and outputs an alarm for instructing deceleration. The display also displays for navigation. Speed reducer 22
Is composed of a throttle actuator, a shift actuator of an automatic transmission, a brake actuator, etc., and controls deceleration of the vehicle.

"Overall Operation" Next, the overall flow of the alarm output control in this embodiment will be described with reference to FIG. When the engine is started, the arithmetic processing unit 10 starts up and starts processing.

First, various control parameters (various flags, etc.) are set to initial values (S11). Next, the vehicle state quantity such as the vehicle speed is fetched from the wheel speed sensor 16 (S
12), the current position is fetched from the GPS receiver 12 (S13). In addition, the current position and the road shape data ahead are fetched from the map database 14 (S14).

In this way, when the current state of the vehicle and the shape of the road ahead are grasped, future lateral acceleration is predicted for advance warning and deceleration warning (S1).
5). The calculation of the lateral acceleration will be described later.
Next, a lateral acceleration that enables stable traveling at each point, that is, a control reference value that is a reference for control is calculated (S16). Although this control reference value is determined by the frictional force between the road surface and the tire, as will be described later, the pavement condition of roads stored in the map database 14, the visibility, and the road surface obtained by the inadequacy sensor 18 are used. It is corrected according to the wetness of.

The control reference value of the lateral acceleration thus obtained is compared with the predicted lateral acceleration obtained for the advance warning and the deceleration warning to judge the necessity of the advance warning and the deceleration warning, The content of the alarm is determined (S17). And
The alarm output device 20 and the speed reducer 22 are controlled to output the determined alarm (S18).

"Lateral acceleration prediction" Here, the prediction of the lateral acceleration in S15 will be described. The arithmetic processing unit 10 takes in the state quantities related to the vehicle motion such as the current vehicle speed, each wheel speed, and each wheel acceleration from the vehicle side from the wheel speed sensor 16 and takes in the longitudinal gradient data from the map database 14. Then, based on these data and the assumed deceleration pattern simulating the deceleration behavior of the driver,
Predict future vehicle motion (vehicle speed, position) by solving a motion equation.

(Assumed deceleration pattern) First, the assumed deceleration pattern will be described. This assumed deceleration pattern is based on the assumption that the current acceleration / deceleration state is maintained for τ0 seconds from the present and braking is performed such that deceleration is performed at a constant deceleration ax0 after τ0 seconds. An example of this is shown in FIGS.
FIG. 3 shows a case where the vehicle is traveling at a constant speed V0. During the period from τ0 to the present time, the vehicle travels at the same speed,
After that, the vehicle decelerates at a constant deceleration ax0. This ax0 is
For example, it may be set to about 0.2 G so that it can be appropriately changed according to an estimated value of a road surface friction coefficient described later.

Further, FIG. 4 shows a case where the vehicle is currently accelerating at the average acceleration value axmean.
In this case, the acceleration is continued at axmean until τ0, and then decelerated at ax0.

Further, in FIG. 5, as in the case of FIG. 4, the acceleration at the present time is axmean, and the longitudinal gradient in
This is in consideration of c (S). Here, S is the distance from the current position toward the traveling direction, and inc (S) is the inclination at each position. Further, g is a gravitational acceleration, and g × inc (S) is a deceleration in the traveling direction at each point. That is, g × inc (S) is the deceleration and is positive on the uphill. Since ax0 is also a deceleration, the acceleration when τ0 <τ is -ax0-gxinc.
(S).

When such an assumed deceleration pattern is assumed, the vehicle speed V (τ) after τ seconds from the present time and the moving distance S (τ) from the present position are obtained by solving the following differential equation. Note that deceleration due to the brake after τ0 is braking force Fb = m × when the vehicle mass is m, regardless of the gradient.
It shall be multiplied by ax0.

[0034]

[Equation 1] Here, axmean is an average vehicle speed in a certain period before t = 0, and is calculated from an average value of accelerations of the left and right wheels. Further, ax0 is a constant deceleration as described above. The initial condition of the above equation is t = 0, V = V0, S
= 0.

If the road has a vertical gradient, the above inc
Just load (S) as data with each point,
The equation of motion need only add g × inc (S) to the right side of the above equation. Note that the influence of the gradient is included in the axmean in the section of τ <= τ0. Therefore, τ> τ0
It is sufficient to consider the influence of the longitudinal gradient only for (see FIG. 5).

Further, as a weighting function for τ,
K1 (τ) and K2 (τ) are defined by the following equations.

[0037]

(2) K1 (τ) = 0 (0 <= τ <τ0) K1 (τ) = 1 (τ> = τ0) K2 (τ) = 1-K1 (τ) Such K1 (τ) and K2 (τ) are shown in FIG.

Therefore, the above equations (1) and (2) can be expressed as follows.

[0039]

[Equation 3] Then, by solving the equations (3) and (4), the vehicle speed V (τ) and the moving distance S based on the assumed deceleration pattern are obtained.
(Τ) can be obtained.

In the present embodiment, in order to be able to deal with various deceleration models, the terms FK1, FK2 and FK3 are multiplied to the respective terms on the right side of the equation (3). Thus, by setting the coefficient to 1, the term can be considered 100%, and by setting it to 0, the term can be ignored.

Therefore, the assumed deceleration pattern is FK1, F
It is represented by five parameters of K2, FK3, τ0, and ax0.

In general driver characteristics, FK1, F
K2, FK3 = 1.0, τ0 = 0.5 to 1.5 seconds, ax
It is preferably set to 0 = 2 to 3 m / sec ² . However, by changing the value of this parameter according to the purpose of control, it is possible to appropriately predict the vehicle behavior.

If the above equation of motion is solved, the vehicle will stop at a certain time, so no calculation is performed thereafter, and V (τ)
= 0 and S (τ) = constant.

(Consideration of road surface cant) First, the balance of the forces applied to the vehicle when turning a curve with a cant is as shown in FIG. That is, the centrifugal force applied to the vehicle is mV ² / R (m is the mass of the vehicle, V is the vehicle speed, R
Is the radius of the curve (the curvature value of 1 / R is used in the map database), and since the cant is θ, the force Fy acting in the lateral direction of the vehicle (direction parallel to the road surface) is m (V ² /
R) cos θ-mg sin θ.

Therefore, the acceleration in the direction parallel to the road surface of the vehicle body is represented by (V ² / R) cos θ−g sin θ. This is equivalent to the reading of a lateral accelerometer attached to the vehicle body, ignoring the roll angle due to the deflection of the suspension of the vehicle body, and is equivalent to the lateral acceleration felt by the occupant with the body.

This is the lateral acceleration ayh which is a function of τ.
If it is (τ), this ayh (τ) is

Ayh (τ) = (V ² (τ) / R (τ)) cos θ-g sin θ (τ) (5)

On the other hand, the normal force N applied to the tire of the vehicle
Is N = m (V ² / R) sin θ + mg cos θ. Therefore, to turn a curve,

[Equation 5] Must be established. The left side of this equation rapidly increases as V increases, and there exists V such that the left side = μ. Therefore, if V is calculated with = μ in this equation, this becomes the maximum vehicle speed at which the vehicle can stably turn around the curve, that is, the limit vehicle speed.

Here, the cant θ of the road surface is generally 0.1.
rad (about 5.7 °) or less, and the first term in the denominator is 1/10 or less of the second term. Therefore, the vertical drag (denominator) hardly changes depending on the vehicle speed. Therefore, the sharpness of turning when traveling on a curve can be almost evaluated by the size of ayh of the molecule. That is, the value of the acceleration ayh is μg.
Turning becomes unstable when approaching. Therefore, the control reference value is set to a value sufficiently smaller than this.

Whether or not the curve can be stably turned is as follows.
Regardless of whether the vehicle is turning to the right or to the left, the absolute value of the lateral acceleration ayh (τ) may be used as the maximum absolute value, and the maximum value of | ayh (τ) | is the control reference value in the prediction target section in front of the track. Need not exceed.

Therefore, the maximum value a of this | ayh (τ) |
yhmax is obtained, and this is set as a determination value for determining whether or not the vehicle is traveling on a curve. The target section for prediction is τm in time.
in <= τ <= τmax or V0 × τmin <in distance
= Τ <= V0 × τmax, but this τmin
Although τmax and τmax are set to appropriate values based on a survey by actual traveling, they can be set to, for example, about 2 to 10 seconds.

Here, the time τ0 for maintaining the current acceleration / deceleration is determined in consideration of the time required for the driver to switch from the accelerator to the brake. Further, it is also preferable to recognize the existence of a curve by actual traveling and consider the point where the vehicle decelerates. In this way, since the influence of the traveling condition at the present time is limited to the finite time τ0, it is possible to provide the assumed deceleration pattern that is realistic.

"Control Reference Value" Next, the setting of the control reference value used for comparison with ayhmax will be described. As mentioned above, in order to perform stable curve traveling, ayhma
x must be kept below a sufficiently small value depending on the road surface μ. For example, in general road design, ayhmax is suppressed to about 1.7 m / s ² when running at a design speed.

Therefore, in this embodiment, the control reference value is set in consideration of the following two factors, F1 and F2.

(Items to be input to the map database 14) Course width, visibility, road surface unevenness, pavement degree, etc. are comprehensively evaluated, and an unsuitability flag F1 is set as data of each point of the map database 14. . When the condition is good, F1 = 0, and when the condition is bad, F1 = 1. Instead of such a two-stage evaluation, a multi-stage evaluation may be used.

(Detection on Vehicle Side) In this embodiment, the inadequacy flag F2 is set according to the wetness of the road surface detected by the inadequacy sensor 18. This is because the friction coefficient μ of the road surface changes greatly due to the wetness of the road surface. It is also preferable to change the setting of the inadequacy flag not only for dry and wet but also for snow, freezing and the like. In addition, information about the tire may be detected. When the conditions are good, F2 = 0, and when the conditions are bad, F2 = 1.
And This evaluation should also be a multi-level evaluation instead of a two-level evaluation.

(Setting of control reference value) When the flags F1 and F2 are thus determined, the flag F3 is determined according to this combination.

[0057]

[Table 1] In this way, the flag F3 represents the inadequacy as a numerical value by the combination of the two flags, and the four combinations have the values of 0, 1, 2, and 3.

Then, using the value of this flag F3,
The value of the control reference value ayhmax for the lateral acceleration is changed. For example, when three a1, a2, and a3 are set as the control reference values for the deceleration warning, each of them is changed according to the value of F3, and the control reference value a1 is set.
^* , A2 ^* , a3 ^* are obtained. Here, this * indicates the value of the flag 3. For example, when F1 = 1 and F2 = 0, F3 = 1, so * is set to 1 and is a11, a21, a3.
A reference value such as 1 is used. In this way, the road environment,
The control reference value is changed according to the environment of the vehicle.

At this time, taking hysteresis into consideration, FIG.
, The three control reference values a1 ^* , a2 ^* , a3
^{Make *} different for increasing and decreasing directions. That is, corresponding to each of the control reference values a1 ^* , a2 ^* , a3 ^* ,
Set the hysteresis ha1 ^* , ha2 ^* , ha3 ^* . As a result, control hunting can be prevented.

Further, as shown in FIG. 9, the vehicle speed VCV1
Up to CV1, and if the vehicle speed is VCV2 or higher, CV2
It is also preferable to multiply the control reference value by a weighting coefficient CV (V) (1 or less) of a value that linearly decreases from CV1 to CV2 (a value smaller than CV1) and between vehicle speeds VCV1 and VCV2. With this, as the vehicle speed increases,
It is also possible to decrease the control reference value and make it the final control reference value. This is because the margin is increased in consideration of the fact that the higher the vehicle speed, the larger the fluctuation of the lateral acceleration due to a slight change in the condition such as the maneuvering operation.

[Alarm Judgment / Control] Next, the alarm output judgment will be described. First, this determination is made depending on whether or not the ayhmax obtained by the above prediction exceeds the control reference value set as described above. Figure 8
In the example, when ayhmax is a1 ^* or less, FWB =
0, FWB = 1 when ayhmax exceeds a1 ^* ,
FWB = 2, ayhmax exceeds a2 ^* , ay
When hmax exceeds a3 ^* , FWB = 3. Therefore, by determining the content of the warning according to the value of the flag FWB, it is possible to generate the warning according to the degree of instability during the curve running.

For example, depending on the value of the flag FWB, an alarm is issued: FWB = 0: No action FWB = 1: Primary warning by voice (one time only) FWB = 2: Secondary warning by voice (for example, Warning with buzzer sound together with brake and brake sound) FWB = 3: It is conceivable to give a warning such as a third warning (same as the second warning but increase the volume) by sound. .

As described above, as a method of issuing an alarm,
One or a combination of (i) voice warning, (ii) buzzer, (iii) lamp or LED lighting is considered suitable. Further, it is preferable that a plurality of arbitrary control reference values are provided and various alarm means are combined.

Further, it is preferable to control the deceleration by the following combinations. For example, the deceleration control may be performed when FWB = 2,3.

(I) Throttle control (to close the throttle to decelerate) (ii) On a downhill or the like, downshifting of gears in the automatic transmission (AT) (a sudden downshift is caused by a sudden change in the tire slip ratio, resulting in vehicle behavior failure). Therefore, it is effective to alleviate the shock at the time of shifting and to use stepless control. (Iii) Front and rear wheel brake pressure control (in this case, even when the driver is not operating the brake) Including this, the vehicle speed control is automatically performed by the brake pressure. By such control, desired deceleration control can be performed.

[Calculation of Lateral Acceleration in Advance Warning] In this embodiment, in addition to the warning control just before the curve performed when the deceleration is insufficient as described above, the warning is given from a considerable front under a slightly simpler condition. Give an alarm.

In this case, the lateral acceleration is calculated as follows, and this is compared with the control reference value to control the output of the alarm.

First, based on the data acquired from the map database 14, a specific section in front of the course (time tpm
in seconds to tpmax seconds, or distance tpmin × V to tp
(max x V) curvature roumax where the absolute value of curvature is maximum, and cant cant at that point
Find max. For example, it is conceivable to set the range of about 2 to 9 seconds as the specific section.

Then, the following pattern is used as the assumed deceleration pattern. That is, the passing speed of the curve is assumed as follows.

Vp = (Fpv × V + (1-Fpv) × V
c / 3.6) × Kv Here, Fpv is a weighting coefficient, which is 1 when it is assumed that the current speed remains unchanged, and 0 when it is assumed that the vehicle passes at the speed limit of the course. Vc is the speed limit (km / h) of the course. Kv is a correction coefficient.

On the other hand, the lateral acceleration ayp during turning can be expressed by ayp = roumax × Vp ² −g × cantmax. This equation also takes into consideration the turning direction (right turn or left turn).

For example, when Fpv = 0.5 and Kv = 1.0, V
When c = 50 km / h and the vehicle is traveling at 70 km / h, it is assumed that the vehicle enters the curve at Vp = 60 km / h. In this state, the lateral acceleration is estimated and an alarm is issued. The values of Kv and Fpv may be determined in advance, or may be statistically determined by monitoring the running state of the driver.

Thus, in this example, the passing speed (Vp) of the preceding curve is set to the speed limit (Vc) and the current vehicle speed (V).
And the weighted value based on the weighting coefficient (Fpv). The driver usually recognizes the speed limit of the road, and it is considered that the driver will travel on the basis of this speed limit when traveling on a curve. Therefore,
By using this as a reference, the prediction of the vehicle speed becomes realistic and the alarm becomes appropriate. Not only the speed limit but also various recommended speeds can be adopted. For example, considering the curve etc., determine and store the recommended speed,
It is also suitable to use this instead of the above-mentioned speed limit.

Then, the lateral acceleration ayp thus calculated is compared with the control reference value ap1 *. The control reference value ap1 * is determined in the same manner as in the case described above, and is set to the same value as the above-mentioned first reference value a1 *, for example. Further, * represents the value of F3, and ap1 * is changed according to the value of the flag F3.

Then, as shown in FIG. 10, the control reference value ap1 * is 2 which is ap1 * and -ap1 * considering the sign.
If the ayp exceeds ap1 *, the flag F
WP = 1, flag a when ayp falls below -ap1 *
Set WP = -1, and when FWP = 1, pay attention to the right curve, FW
When P = -1, the voice of the left curve is output. In addition,
Also in this case, the hysteresis hap1 * as shown in FIG. 10 is prepared for the determination.

[Data Acquisition] Here, the data in the map database 14 is prepared for each predetermined point (discrete point) on the road. For example, in FIG.
Predetermined distance (not necessarily fixed interval), as shown in
Points P1, P2, P3, ... Are set for each
Various data are stored for each point.

Therefore, when reading the data from the map database 14 based on the current position, the data at the point P0 immediately before the current position at that time is read. As shown in Table 2, the data read from the map database 14 has the position of each point, the curvature, the cant, the longitudinal gradient, and the inadequacy flag.

[0078]

[Table 2] When the arithmetic processing unit 10 reads this data,
As shown in Table 3, the distance to the previous point and the distance from the point P0 immediately before the current position are calculated and added.

[0079]

[Table 3] Then, this table 3 is prepared in a format. Therefore, the data in this map can be used in the calculation of lateral acceleration at each future point. Therefore, high-speed calculation becomes possible. In addition, rewriting the map as the vehicle travels is relatively easy.

Data between points may be linearly interpolated. That is, as shown in FIG. 12, the data between the points is interpolated by the data of the point at the corresponding position. Note that FIG. 12 shows the curvature data.

[Regarding Road Surface Friction Coefficient μ] Here, the road surface friction coefficient μ may be stored in the map database 14 for each point in wet and dry conditions. In this case, by turning the wiper on and off,
Relatively accurate friction coefficient μ can be obtained by recognizing whether wet or dry and selecting the friction coefficient μ.

Further, for each road, the friction coefficient μ is not stored, but according to the pavement state of the road, a table such as how many asphalts are dry and how many are wet is kept, and the road pavement condition ( The friction coefficient μ may be determined from the map database 14). Further, the friction coefficient μ of the traveling road may be transmitted from the roadside beacon, and the friction coefficient μ may be obtained by receiving the value by the communication device mounted on the vehicle.

Further, the friction coefficient μ may be estimated from the behavior of the vehicle such as slip during the past braking or acceleration, or the self-aligning torque (when the tire is rolling at a certain slip angle, It may be estimated from the torque acting on the contact surface in the direction of decreasing the slip angle.

In this way, if an accurate value of the road surface friction coefficient μ is obtained, it is not necessary to see the influence on the road surface friction coefficient μ with the inadequacy flag.

The arithmetic unit 10 includes a CPU, a RAM,
It is composed of a computer having a ROM and the like. Then, the above-described operation is achieved by normally executing the operation program stored in the ROM. On the other hand, it is also preferable to record the operation program in an external recording medium such as the map database 14 so that the program can be installed in the arithmetic unit 10. In this case, the ROM may be rewritable such as EEPROM and the operation program may be recorded therein.

[Brief description of drawings]

FIG. 1 is a block diagram showing an overall configuration of an embodiment.

FIG. 2 is a flowchart showing a processing operation for outputting an alarm.

FIG. 3 is a diagram showing an example of an assumed deceleration pattern.

FIG. 4 is a diagram showing an example of an assumed deceleration pattern.

FIG. 5 is a diagram showing an example of an assumed deceleration pattern.

FIG. 6 is an explanatory diagram of a weighting function.

FIG. 7 is a diagram showing a balance of forces applied to a vehicle.

FIG. 8 is an explanatory diagram of a plurality of control reference values.

FIG. 9 is an explanatory diagram of an example of a weighting function.

FIG. 10 is an explanatory diagram of control reference values.

FIG. 11 is an explanatory diagram showing points on a map.

FIG. 12 is an explanatory diagram showing data interpolation.

[Explanation of symbols]

10 arithmetic processing unit, 12 GPS receiver, 14 map database, 16 wheel speed sensor, 18 improper sensor, 20 alarm output device, 22 speed reducer.

─────────────────────────────────────────────────── ─── Continuation of front page (51) Int.Cl. ⁷ Identification code FI G08G 1/16 G08G 1/16 D // G09B 29/10 G09B 29/10 A (58) Fields investigated (Int.Cl. ⁷ , DB name) G01C 21/00-21/36 G08G 1/09-1/16 B60T 7/12-8/00 B60T 8/32-8/96 B60R 21/00

Claims (4)

(57) [Claims] 1. A vehicle traveling state prediction device for predicting lateral acceleration of a vehicle that occurs when passing a curve that is about to travel, comprising vehicle speed detection means for detecting a vehicle speed of the vehicle, and a point in the road traveling direction. Based on the database having the data about the curve curvature and the data about the road crossing slope as the data related to, the vehicle speed detected by the vehicle speed means, and the curve curvature and the crossing slope in the front of the road read from the database. And a predicting means for predicting lateral acceleration in a curve which is about to enter, and a traveling state predicting device for a vehicle. 2. The apparatus according to claim 1, wherein the predicting means predicts a vehicle speed when traveling ahead in a curve as a time function considering the detected current vehicle speed and an assumed acceleration / deceleration pattern, and makes the prediction. A vehicle running state prediction device, which predicts lateral acceleration as a function of time based on the determined vehicle speed. 3. An alarm device using the device according to claim 1 or 2, wherein the prediction of lateral acceleration in the prediction means is prediction of maximum lateral acceleration in a curve to be entered, and the predicted maximum lateral acceleration. An alarm device, which issues an alarm to a driver when the acceleration exceeds a predetermined reference value. 4. A medium for storing a program for operating a vehicle running state prediction device for predicting a lateral acceleration of a vehicle which occurs when a vehicle is going to travel a curve, the program being a vehicle running vehicle. The vehicle speed detected by the vehicle speed detection means is loaded into the state prediction device, and as a data related to the point in the road traveling direction, a curve in front of the road A vehicle running condition predicting device program is stored, in which the curvature and the cross slope are taken in and the lateral acceleration in the curve to be entered is predicted based on the taken vehicle speed, the curve curvature, and the cross slope. Made medium.