EP1893460A1

EP1893460A1 - Method and device for the detection of a roadway having a low coefficient of friction

Info

Publication number: EP1893460A1
Application number: EP06743384A
Authority: EP
Inventors: Gerald Graf
Original assignee: Robert Bosch GmbH
Current assignee: Robert Bosch GmbH
Priority date: 2005-06-15
Filing date: 2006-04-26
Publication date: 2008-03-05
Also published as: WO2006133994A1; DE102005027647A1; CN101198505A; US20090306853A1

Abstract

The invention relates to a method for detecting the presence of a roadway having a low coefficient of friction. According to said method, a group containing one or several predetermined types of driving situation is predefined, at least two instances of a type of driving situation contained in the group are determined, the type of driving situation not necessarily being identical in the two instances, and the presence of a roadway having a low coefficient of friction is detected in accordance therewith.

Description

Method and device for detecting a low-friction carriageway

State of the art

Known slippery warnings to the driver via the instrument cluster are based on the measured outside temperature. If this falls below a predetermined value, e.g. 4 ° C, then e.g. on a display of the instrument cluster one

Warning message about possible road slipperiness. The actual road condition is not taken into account and the warning is generated even if there is no road slipperiness and only low temperatures prevail.

Advantages of the invention

The invention relates to a method for detecting the presence of a low-friction low-friction roadway, in which a group containing one or more predetermined driving situations is determined, which is determined at least twice occurrences of a Fahrsituationsart included in the group, which is not must necessarily act around the same Fahrsituationsart, and depending on the presence of a Niederreibwertfahrbahn is detected. This results in a more precise and accurate detection of a low-friction roadway than in the case of

Use of an outdoor thermometer possible.

An advantageous embodiment of the invention is characterized in that the group contains at least two different types of driving situations. By the Considering a wider range of driving situations, the reliability of the detection is further improved.

An advantageous embodiment of the invention is characterized in that - for each occurred, predetermined Fahrsituationsart a smoothing size is determined, which represents the probability that a Niederreibwertfahrbahn present and / or a Hochreibwertgröße is determined, which represents the probability that a road with a high coefficient of friction and that - depending on the determined smoothness and / or the determined

Hochreibwertgrößen the presence of a Niederreibwertfahrbahn is detected.

This makes it possible that different driving situations in their occurrence with different weighting in the determination of the presence of a

Enter low-cost roadway.

An advantageous embodiment of the invention is characterized in that

- That for each occurred, predetermined Fahrsituationsart a weighting variable is determined, which depends on how long the occurred, predetermined

Fahrsituationsart present. This takes into account the fact that long-lasting driving situations are more precise

Conclusions on the existence of a Niederreibwertfahrbahn allow only briefly present driving situations.

An advantageous embodiment of the invention is characterized in that according to the relationship

f_low_mue =

Σ / _ low _ mue _ event _ i ^■ weight _ (

Σ f _ low _mue _ event _ i ^■ weight + Σ / _ high _ mue _ event _ i ^■ weight

determining a quantity f_low_mue, which is a measure of the probability that a low-cost roadway exists, and that a Niederreibwertfahrbahn is detected as present when the size f_low_mue exceeds a predetermined limit, wherein in the specified relationship i a running counter for the number of occurred predetermined driving situation types, f_low_mue_event_i and f_high_mue_event_i the determined for the i-th occurred predetermined Fahrsituationsart smoothness and size Hochreibwertgröße Gew_i are the weighting quantity for the i th occurred predetermined Fahrsituationsart.

An advantageous embodiment of the invention is characterized in that at least one predetermined Fahrsituationsart depends on whether a

Wheel slip control system is active.

An advantageous embodiment of the invention is characterized in that at least one predetermined Fahrsituationsart depends on the intensity of the brake pedal operation performed by the driver braking.

An advantageous embodiment of the invention is characterized in that at least one predetermined Fahrsituationsart of the present

Vehicle acceleration depends.

An advantageous embodiment of the invention is characterized in that at least one predetermined Fahrsituationsart of the difference between the vehicle deceleration and at least one wheel deceleration during a

Braking depends.

An advantageous embodiment of the invention is characterized in that at least one predetermined Fahrsituationsart depends on the change in the wheel deceleration per unit time.

The mentioned variables such as status of wheel slip control systems, intensity of a brake pedal operation, vehicle acceleration, wheel deceleration, vehicle deceleration and change of the wheel deceleration per unit time are the same in modern vehicles - A -

existing sensors can be determined without significant additional effort and thus allow an uncomplicated detection of predetermined driving situations.

An advantageous embodiment of the invention is characterized in that in the case of the detection of a Niederreibwertfahrbahn a driver warning. This will be the

Driver advised to adapt his driving style to the road surface.

The device according to the invention for detecting the presence of a low-friction carriageway comprises storage means in which a group containing one or more predetermined

Driving situation types is stored,

Determining means in which the at least two occurrences of a driving situation type contained in the stored group is determined, which need not necessarily be the same driving situation type, and - detection means with which, depending on the ascertained in the determination means, at least twice occurrence of one in the stored Group contained driving condition type the presence of a Niederreibwertfahrbahn is detected.

The advantageous embodiments of the method according to the invention are also expressed as advantageous embodiments of the inventive device and vice versa.

drawing

The drawing consists of Figures 1 to 3.

FIG. 1 shows the basic sequence of the method according to the invention.

Figure 2 shows the basic structure of the inventive device

Figure 3 shows an embodiment of the present invention.

embodiments The invention makes it possible, via the usual brake control functions ABS, ASR and ESP (ESP = "Electronic Stability Program") and commonly used sensors (lateral acceleration, yaw rate, steering wheel angle, wheel speeds) to gain information about the prevailing road conditions and only when detected

Road slippery to indicate a warning to the driver via the instrument cluster.

The invention is based on the fact that with slippery roads at significantly lower accelerations or decelerations to ABS / ASR / ESP interventions than on dry roads would be the case. An additional indication of road smoothness can be obtained from the wheel signals under light braking, even without it comes to an ABS control. Furthermore, occurring high accelerations are an indication of a dry and grippy road. Advantage of the invention is that a warning is issued to the driver only when actually slippery road prevails. A habituation of the driver to a permanently displayed warning, as it takes place in the temperature-triggered approach, is avoided. In vehicles with conventional ESP or ABS system, the driver receives feedback from the pulsation of the brake pedal when it comes to an ABS control. However, this feedback is omitted for vehicles with EHB systems (EHB = "electrohydraulic brake") A warning to the driver according to this invention can replace this missing feedback.

The lane condition estimation algorithm is based on an evaluation of various driving conditions typical of snow lanes or dry asphalt.

Typical driving conditions for snow-slippery roads:

Driving condition Al: There is a slight vehicle acceleration and an ASR or ESP control is active.

Driving condition A2:

There is a weak braking process and an ABS control is active. Driving condition A3:

There is a weak braking action and there is a large difference between at least one wheel deceleration and the determined vehicle deceleration, and there is a restless wheel behavior, recognizable by large values for the time derivatives of the wheel deceleration, i. the jerking of the wheels.

Typical driving conditions for dry asphalt:

Driving state Bl:

There is a weak braking process and

There is a slight difference between at least the wheel delays and the determined vehicle deceleration and - there is a smooth wheel behavior, recognizable by small values for the temporal

Derivatives of the wheel deceleration.

Driving condition B2:

There is at least moderate braking and there is no ABS control active

Driving state B3: There is an at least medium vehicle acceleration without an ASR or ESP control being active.

Driving state B4:

There is a high vehicle acceleration The vehicle acceleration a evaluated in states Al, B3 and B4 is, in particular, the total vehicle acceleration, which may include longitudinal acceleration components and lateral acceleration components. It is determined according to

2 2 a = SQRT (ax + ay), where SQRT is the square root function, ax the e.g. vehicle longitudinal acceleration determined from the wheel speed sensor signals and ay the e.g. is transverse acceleration measured by the lateral acceleration sensor.

The intensity of the braking operation in the states A2, A3, Bl and B2 is e.g. on the basis of the pre-pressure detected by the pre-pressure sensor and / or the e.g. Detected from the wheel speeds detected vehicle longitudinal acceleration or - delay.

Individual estimation probabilities f_low_mue_event and / or f_high_mue_event and a weighting factor Gew are assigned to each of these states.

If one of the states A1, A2, A3, B1,..., B4 is present, a variable f_low_mue_event is calculated from the individual signals associated with the respective situation (eg combination of 4 wheel signals into one variable) via a fuzzy logic method. which indicates the likelihood that the present condition is a smooth lane. Analogously, the size f_high_mue_event indicates the probability that the current state is a handy, paved roadway. For a given state, it is not mandatory that one of the probabilities takes the value 1 and the other probability the value 0. It is also conceivable that for a given

State f_low_mue_event and f_high_mue_event take both nonzero values with f_low_mue_event + f_high_mue_event = 1.

In the determination of the weighting factor Gew is e.g. how long have the conditions for snow-lane or asphalt been met, i. how good the situation is

Evaluation is suitable.

The presence of the abovementioned driving states A1, A2, A3, B1,..., B4 is recognized by means of the invention and is assigned to the respective driving state present Weighting factor determined. To determine the weighting factor, the present driving states are evaluated as long as the driving state continues. Subsequently, for example, a quantity f_low_mue can be determined by means of a fuzzy logic method, which is a measure of whether the evaluated driving situations are indicative of a smooth road surface or rather of a grip roadway. The driver is signaled the presence of a smooth road when the size f_low_mue exceeds a predetermined limit, for example, 0.8.

The size f_low_mue is added to e.g. determined according to the following relationship:

f_low_mue =

Σf_low_mue_ event_i - gew_i (

Σf _ low _ mue _ event _ i ^■ weight _ i + Σf _ high _ mue _ event _ i ^■ weight _

In this case, i denotes the last state that has occurred from the group of the above

Driving conditions Al, A2, A3, Bl,..., B4, f_low_mue_event_i and f_high_mue_event_i indicate the probabilities for slippery roads or dry asphalt and for the last driving conditions i and - Gew_i denotes the weighting factor for the last one that occurred

Driving condition i.

Depending on the size f_low_mue, for example, warning information can be output to the driver or a wheel slip control system or vehicle dynamics control system can be influenced

The sequence of the inventive method is shown in Fig. 1. After the start in block 100, the present driving situation type is detected in block 101. Subsequently, a query is made in block 102 as to whether there is at least two occurrences of a type of driving situation contained in the group, although this is not necessarily the same

Driving style must act. If the answer is "no" (always marked "n" in FIG. 1), then branch back to block 101. Is the answer against it "Yes" (always marked with "y" in FIG. 1), then in block 103 the variable f_low_mue is determined. In block 104 it is subsequently queried whether the variable f_low_mue exceeds a predetermined limit value. If this is not the case, then the input of block 101 is branched back and there the next occurring predetermined Fahrsituationsart detected. However, if the query in block 104 is met, then the presence of a low-friction roadway is detected in block 105 and communicated to the driver, for example. Subsequently, the method ends in block 106 or further corresponding situations are evaluated in order to take into account a possible change in the road condition or to correct misjudgements. Furthermore, it is possible by the use of a hysteresis

Oscillating the warning message to prevent, i. with f_low_mue> 0.6, the low fuel level warning is set and with f_low_mue <0.4 the low fuel level warning is reset. The given numerical values 0.4 and 0.6 are only examples.

The structure of the device according to the invention for detecting the presence of a low-friction roadway is shown in FIG. In this case, block 205 represents storage means in which a group containing one or more predetermined driving situation types is stored. Block 201 contains determination means in which the occurrence of at least two occurrences of one contained in the stored group

Driving situation type, which need not necessarily be the same type of driving situation. To this end, block 201 receives input signals from the sensor means 200, block 200 comprises e.g. Wheel speed sensors and a form pressure sensor for determining the driver's brake wish. With these sensor signals, the current driving situation is determined in block 201 and compared with the driving situation types stored in block 205. Furthermore, FIG. 2 contains detection means 202, with which the presence of a low-friction-value roadway is detected as a function of the occurrence of a driving-situation type contained in the stored group, which is determined at least twice in the determination means 201. If there is a low-cost carriageway, then e.g. either via the driver warning means 203 a

Driver information can be output and / or wheel slip control means 204 can be influenced. FIG. 3 again shows an embodiment of the inventive idea in an alternative representation. In blocks 301, 302 and 303, the instantaneous driving state is detected on the basis of the output signals of the sensors contained in block 300. For example, in block 301, the presence of a partial braking, ie, a weak braking, - in block 302, the current activity of an ABS, ASR or ESP control and in block 303, the presence of a strong vehicle acceleration can be detected.

Depending on the driving condition detected in block 301 and / or 302 and / or 303, it may be classified as indicating a low road friction coefficient in block 304 or as indicating a high road friction coefficient in block 305. In particular, a method based on fuzzy logic can be used for this purpose. This allows the calculation of probabilities for the present driving condition, i. with the probability x is a Niederreibwertfahrbahn and with the probability 1-x is a Hochreib value roadway before. Subsequently, in block 306, for example, the quotient

Number of low-friction drive states / (number of low-friction drive states + number of high-friction drive states)

or a related size like f_low_mue.

Based on this quotient, the presence of a low-cost carriageway is detected in block 307.

Claims

claims

A method for detecting the presence of a low-cost roadway, in which - a group containing one or more predetermined driving situations is specified (205) to detect at least two occurrences of a driving type included in the group, which are not necessarily the same driving type must act (102), and - depending on the presence of a Niederreibwertfahrbahn is detected (105).

2. The method according to claim 1, characterized in that the group (205) contains at least two different driving situations.

3. The method according to claim 1, characterized

- That for each occurred, predetermined Fahrsituationsart (i) a smoothness value (f_low_mue_event_i) is determined, which represents the probability that a Niederreibwertfahrbahn exists and / or a Hochreibwertgröße (f_high_mue_event_i) is determined, which represents the probability that a road with high friction present and

- That the presence of a Niederreibwertfahrbahn is detected (105) depending on the determined smoothness values (f_low_mue_event_i) and / or the determined Hochreibwertgrößen (f_high_mue_event_i).

4. The method according to claim 3, characterized

- That for each occurred, predetermined Fahrsituationsart (i) a weighting variable (Gew_i) is determined, which depends on how long the occurred, predetermined Fahrsituationsart exists.

5. The method according to claim 4, characterized in that according to the relationship

f_low_mue =

Σ / _ low _ mue _ event _ i ^■ weight _ (

Σ / _ low _mue _ event _ i ^■ weight + Σ / _ high _ mue _ event _ i ^■ weight

determining a quantity f_low_mue which is a measure of the likelihood that there is a low-cost track, and that a low-value carriageway is detected as present if the quantity f_low_mue exceeds a predetermined limit, wherein in the given relationship i is a counter for the predetermined driving situations that have occurred , f_low_mue_event_i and f_high_mue_event_i are the smoothness quantity and the high friction value quantity Gew_i determined for the ith predetermined driving type, the weighting quantity for the ith predetermined driving situation type.

6. The method according to claim 1, characterized in that at least one predetermined Fahrsituationsart depends on whether a wheel slip control system is active.

7. The method according to claim 1, characterized in that at least one predetermined Fahrsituationsart depends on the intensity of the brake pedal operation performed by the driver braking.

8. The method according to claim 1, characterized in that at least one predetermined Fahrsituationsart depends on the present vehicle acceleration (a).

9. The method according to claim 1, characterized in that at least one predetermined Fahrsituationsart depends on the difference between the vehicle deceleration and at least one Radverzögerung during a braking operation.

10. The method according to claim 1, characterized in that at least one predetermined Fahrsituationsart depends on the change of the wheel deceleration per unit time.

11. The method according to claim 1, characterized in that in the case of detecting a Niederreibwertfahrbahn a driver warning occurs (203).

12. A device for detecting the presence of a low friction carriageway, comprising storage means (205) in which a group containing one or more predetermined driving situations is stored,

Determining means (201), in which the at least two occurrences of a driving situation type contained in the stored group is determined, which need not necessarily be the same driving situation type, and detection means (202), with which depending on the determined in the determining means, at least twice Occurrence of a Fahrsituationsart contained in the stored group, the presence of a Niederreibwertfahrbahn is detected.