DE102014008588A1 - Detection of short-term irregularities in a road surface - Google Patents

Abstract

The present invention relates to the detection of a short-term irregularity under a vehicle having a first wheel by determining a first sensor signal indicative of time-dependent vibrations on the first wheel using a first sensor, determining a second sensor signal indicating a time-dependent vertical movement of the vehicle chassis Use of a second sensor, and detecting a momentary irregularity of a road surface under the vehicle based on the first sensor signal and the second sensor signal.

Description

TECHNICAL AREA

The present disclosure generally relates to the estimation of the road surface condition under a vehicle and, for example, to systems, methods, and computer program products for estimating the road surface condition under a vehicle.

More particularly, the present disclosure relates to methods, systems and computer program products for estimating the road surface condition under a vehicle.

BACKGROUND OF THE INVENTION

Modern automobiles include electronic control systems or vehicle handling systems such as a traction control system (TCS), an electronic stability program (ESP), an active suspension system, or an anti-lock braking system (ABS). In addition to these active control systems, there are also driver safety information systems such as road friction indicators and sensorless tire pressure monitoring systems, e.g. For example, an indirect tire pressure monitoring system (iTPMS), which present information about the driving condition to the driver.

All of the aforementioned systems benefit from the knowledge of a large set of estimated or measured vehicle characteristic parameters, such as tire air pressure, tire longitudinal stiffness, ambient temperature, tire temperature, wheel resonance frequency, vehicle load, tire radius change during cornering, and speed dependent wheel vibration.

The knowledge of current road surface conditions (also called road quality) is of interest. Road surface condition information, e.g. Certain road sections, for example, may be useful to authorities such as the Department of Transportation for maintenance and travelers planning their route and finding the most comfortable route from point A to point B.

For example, based on road surface condition information, it may be possible to detect road surface anomalies that, if left unchecked, may cause vehicle wear, reduced ride comfort, and reduced vehicle controllability or accident.

The knowledge of road surface conditions can also be used for electronic control systems of vehicles. Modern vehicles include electronic control systems such as anti-lock braking systems (ABS), dynamic stability systems, anti-spin systems and traction control systems. In addition to these active control systems, there are also driver safety information systems, such as road friction indicators and sensorless tire pressure monitoring systems, that present driver information about the driving condition. Such systems may benefit from the knowledge of road surface conditions under the vehicle to account for the current actual surface condition of a road on which a vehicle is currently moving (or will move), system performance (eg, braking force and / or Optimize braking distances). For example, in vehicles having an active damping system, information about the road surface condition may be used to pre-set / adjust the rigidity of the suspension. In this way, driving over short sections of a road deemed uneven by the driver, gravel roads, potholes, speed bumps, bumps or the like may be made more comfortable for the driver / passengers and less damage may be caused to the vehicle in question.

Known approaches to obtaining information about road surface conditions use smartphone-based applications that use GPS information, vehicle-mounted camera images, and a laser sensor scan of the road surface. Such approaches require additional components that are not normally part of a vehicle.

SUMMARY OF THE INVENTION

The object of the present invention is to provide in an improved manner information about road surface conditions obtained by means of components already contained in the vehicle.

Another object of the invention is to provide improved detection of short-term irregularities of a road under a vehicle, such as potholes, speed bumps, or other short sections of the road deemed uneven by the driver.

In view of the above object, the present invention provides methods, systems and computer program products according to the independent claims. Preferred embodiments are defined in the dependent claims.

In general, the goal of methods, systems, and computer program products of the present disclosure is to collect and distribute current road surface condition information, for example to improve traffic safety.

The information collected may be distributed by a vehicle over a communications network to a central server and / or other vehicles. For this purpose, it is possible, for example, to use an auto-to-infrastructure system, a car-to-car system or any other support system that directly communicates information between vehicles and / or between a vehicle and a traffic infrastructure operator via a communication network.

The vehicle may be used as a transducer and the road surface condition information is calculated based on information gathered from sensors in the vehicle. In particular, this means that the vehicle may be able to communicate to other vehicles or road users road surface conditions and the traffic situation based on information that it has collected with its own sensors. Such information can also be supplied to the transport infrastructure.

Embodiments of the invention solve the problem of how to detect road surface anomalies that, if left unchecked, can cause vehicle wear, lower ride comfort, and reduced vehicle controllability or accident. Road surface conditions that may be detected include, but are not limited to, bumpy roads / gravel roads, potholes, bumps, speed bumps, and other portions of a road deemed uneven by the driver.

The methods, systems and computer program product embodiments of the present invention are advantageous in that no additional sensors need to be installed in the vehicle to determine the road surface condition. Further, if the road surface condition is known to the vehicle in advance, the adjustment of any active suspension system may be adjusted accordingly.

Information pertaining to the particular road surface condition may be merged with other road surface condition information at the back end of a cloud-based service system and / or central driver support system, with an auto-to-infrastructure system, car-to-car system, or any other Driver support system is connected, which allows a direct communication of information between vehicles and / or between a vehicle and a traffic infrastructure operator via a communication network to create a map or other description of the current road condition.

Other features are inherent in the disclosed method and system, or will become apparent to those skilled in the art from the following detailed description of the embodiments and the accompanying drawings.

DESCRIPTION OF THE DRAWINGS

Embodiments of the invention will now be described by way of example with reference to the accompanying drawings. It shows:

1A a schematic view of a system according to the embodiments, which includes a vehicle which runs on a road with a surface degradation (unevenness);

1B a schematic view of a system according to embodiments, the one or more vehicles, a communication network and a central system backend unit comprises;

2 a schematic view of an embodiment of a wheel speed sensor;

3 a flowchart of a method according to the embodiments;

4A 4 is a graph showing measurements of how the time difference between two registrations varies by the linear estimated curve for a wheel of a vehicle according to an embodiment;

4B a graphical representation of a variance of the time difference between two registrations of a wheel speed according to an embodiment;

4C a graph showing an example of decision sizes;

5A Fig. 2 is a graph showing exemplary axial height signals obtained by using front and rear axle height sensors when driving over a short-term irregularity;

5B graphs showing the variances of the axis height signals 5A represent.

PRECISE DESCRIPTION

Therefore, the general purpose of the present invention is to provide improved methods and apparatus that make it possible to more accurately determine a ground condition by detecting transient irregularities by combining sensor signals obtained from sensors already in a vehicle.

According to the present invention, transient irregularities in a road under a vehicle are detected using information from one or more sensors indicative of time-dependent vibrations of at least a first wheel of the vehicle and information from one or more sensors indicating a time-dependent vertical movement of the vehicle chassis ,

In general, the detection of transient vehicle irregularities and possibly also a road surface condition under a vehicle may be based on a combination of sensor data representing the time-dependent behavior of wheel vibration signals (eg, vibrations in wheel speed signals) of a vehicle wheel in response to a current road surface and, on the other hand, sensor data indicative of the time-dependent vertical movement of the vehicle chassis (eg, the distance between a vehicle axle and the chassis or a given point on the wheel and chassis).

Such a combination of information can detect short-term irregularities in the road surface. For example, such an information combination allows detection of sensor data of short-term irregularities with smooth edges instead of sharp edges. Furthermore, the present invention also improves the detection of short-term irregularities with sharp edges.

The cause of variations in the time-dependent behavior of vibration signals may be any road feature. Road features may be considered parts of the surface of or on a road, and include e.g. Potholes, asphalt texture, rocks, waves, etc. Such road features cause tire vibration via tire-road contact. Variations that are caused on a particular wheel lead to a specific time-dependent behavior of the respective sensor signal (s). For example, immediate wheel speed signals measured by one or more sensors on a wheel are affected by the road characteristics transmitted to that wheel.

Wheel speed signals may be obtained using one or more wheel speed sensors, for example, ABS systems and / or the vehicle's internal CAN / Flex-Ray bus, and / or any suitable vehicle sensor that is preferably already part of the vehicle.

Information pertaining to a particular road surface condition for a vehicle may be included with other road surface condition information from one or more vehicles and / or from a cloud-based service system in the form of an auto-to-infrastructure system, car-to-car system, or system any other driver support system that enables direct communication of information between vehicles and / or between a vehicle and an infrastructure manager via a communication network. This makes it possible to obtain more accurate road surface condition information about a particular road (or a portion thereof), to obtain an overview of road surface conditions in a geographical area, and / or to create a map of the current road condition. Additionally, such a collection of road surface condition information from various vehicles may be used to determine how a particular road surface condition affects the driving behavior of different types of vehicles.

For collecting road surface condition information from one or more vehicles, the information from the vehicle or vehicles to other vehicles or infrastructure operators may be provided via a backend of a cloud-based service system in the form of an auto-to-infrastructure system, car-to-car system, or any other driver support system that enables communication of information between vehicles and / or between a vehicle and an infrastructure manager via a communication network. In any case, such communication can be direct and / or real-time.

Information concerning the particular road surface condition of a vehicle may be taken alone or merged with other road surface condition information by a cloud-based service system and / or central driver support system in the form of an auto-to-infrastructure system, an auto-to-car system or any other driver support system that enables direct / real-time communication of information between vehicles and / or between a vehicle and an infrastructure manager via a communications network, and / or a processor or evaluation device of the vehicle. For example, the evaluation device of a vehicle, the settings of the vehicle, for. For example, any active suspension settings.

1A shows a schematic view of a system 1 that a vehicle 101 includes, here in the form of a vehicle with four wheels 103 driving on a road with a surface degradation (rub). The vehicle includes a first sensor 100 configured to determine a first sensor signal indicative of time-dependent oscillations on a first wheel of the vehicle and a second sensor 140 configured to determine a second sensor signal indicative of vertical movement of the vehicle chassis. The first and second sensor 100 and 140 are configured to measure and measurement data as sensor signals to a processor or an evaluation device 102 to communicate. The processor or the evaluation device 102 is further configured to receive the first sensor signal and the second sensor signal and to detect, based on the first sensor signal and the second sensor signal, any short-term irregularity present in the road surface under the vehicle.

The evaluation device or the processor 102 may be any type of processing device, such as a general purpose or special purpose processing machine, such as, for example, For example, a microprocessor, a microcontroller or other control logic, or a Field Programmable Gate Array (FPGA) unit that stores code portions stored in a computer-readable storage medium that are immutable to perform particular tasks, but also others includes code portions stored on a computer-readable storage medium that may be changed during use. Such variable sections may include parameters to be used as input for the various tasks, such as, among other things, the setting of active suspension parameters. The evaluation device or the processor 102 is preferably included in a central control device or unit of the vehicle, for. In the form of integrated hardware, firmware and / or additional software.

Since the present invention preferably uses existing sensors of a vehicle, it is possible to add the road surface condition determination according to the invention in the form of additional software or firmware applications or extensions to an already existing control device / unit of a vehicle.

The vehicle may be any wheeled vehicle, such as a passenger car, a truck, a vans, a motorcycle, a bicycle, a train, etc., where at least one wheel with in contact with the ground. Thus, even a vehicle (bicycle, motorcycle) riding on only one wheel can benefit from the present invention.

1B shows a schematic view of a system 1 , one or more vehicles 110 that the vehicle 101 out 1A correspond, and also a communication network 120 and a central system backend unit 130 with an evaluation device or a processor 132 includes.

As indicated by the bidirectional arrows, this is / are the one or more vehicles 110 designed to share information with any other of the one or more vehicles 110 and / or with the central system backend unit 130 over the communication network 120 to communicate. Such information may include, but is not limited to, information about the road surface conditions, such as information about the detection of one or more short-term irregularities, other current road surface condition information to be used to update a current road surface condition description, a map or other description of the road surface condition A control signal that triggers, for example, an alarm that is perceivable to the driver of a vehicle, for example in the form of a graph and / or acoustically perceivable, the alarm refers to a detected short-term irregularity.

The one or more vehicles 110 are preferably used as "transducers". The processor or the evaluation device 102 Each vehicle is configured to calculate the road surface condition information based on information provided by sensors in the vehicle, e.g. B. the sensors 100 and 140 , but may also be collected by other sensors in the vehicle. In particular, this means that each vehicle may be able to communicate road surface conditions and the traffic situation to other vehicles / road users based on information collected with its own sensors. The collected information of a vehicle may be retrieved from any or all of the one or more vehicles via a communications network to a central server located in 1B through the central system backend unit 130 illustrated, and / or other vehicles 110 be distributed. Distribution over the communications network may be facilitated by using a cloud-based service system in the form of an auto-to-infrastructure system, car-to-car system, or any other driver assistance system that facilitates communication between and / or between vehicles Vehicle and a transport infrastructure operator. In any case, such communication can be direct and / or real-time.

The evaluation device or the processor 102 of the vehicle 110 may be configured to create or update a map of the current road surface condition based on information about one or more detected short-term irregularities. The processor 132 the central system backend unit 130 may also be configured to include information about one or more detected short-term irregularities of the vehicle or vehicles 110 over the communication network 120 to recieve. Such information may be used, for example, for data collection purposes. However, such information may also be provided by the central system backend unit 130 to the vehicle or vehicles 110 be communicated. This allows a vehicle 110 To provide information about short-term irregularities caused by one or more other vehicles 110 collected in this case, the evaluation / the processor 102 be configured for the information about short-term irregularities of the vehicle 110 in which he / she is located and / or such information provided by one or more other vehicles 110 used to create or update a map of the current road surface condition.

Additionally or alternatively, the evaluation / the processor 132 the central system backend unit 132 however, be configured to create or update a map of the current road surface condition based on information about one or more detected short term irregularities. For this purpose, the evaluation / the processor 132 the information for one or more vehicles 110 to create / update a map of a current road surface condition for the area (s) where the vehicle (s) are located. The evaluation device / the processor 132 However, information can be obtained from all vehicles 110 to create / update a map of current road surface conditions for the entire area or roads, in / with which the central system backend unit 130 related vehicles 110 are / move.

The evaluation device or the processor 102 and / or the processor 132 the central system backend unit 130 may also be configured to create or update a classification of the road surface based on one or more detected short term irregularities. The evaluation device or the processor 102 and / or the processor 132 the central system backend unit 130 may also be configured to perform the classification update in real time. The evaluation device or the processor 102 may be further configured to adjust the settings of the active suspension of the vehicle based on the updated classification provided by the processor or the evaluation device 102 and / or the processor 132 the central system backend unit 130 calculated and from the central system backend unit 130 Will be received. With regard to the creation / update of a road surface classification, as in the above cases of creation / update of road surface condition maps, information about short-term irregularities of one or more vehicles may be provided 110 be used. The above description applies here accordingly.

The present invention may be used as a driver assistance system that provides current road surface condition information to a driver of a vehicle, and / or as an infrastructure support system that provides organizations responsible for traffic control, infrastructure, or road maintenance with current road surface condition information, just a few non-limiting examples to call.

The sensor used to obtain the first sensor signal may be any type of sensor responsive to time-dependent vibrations of a wheel of the vehicle. For example, the first sensor may be a common wheel speed or wheel acceleration sensor for all wheels of a vehicle, with at least one individual wheel speed or wheel acceleration sensor associated with a single wheel. The first sensor may include two or more types of sensors, such as a wheel speed sensor and a wheel acceleration sensor.

As shown, the first sensor may be a wheel speed sensor 100 be, wherein the first sensor signal is a wheel speed signal, the time-dependent behavior of the speed, or the wheel speed oscillations of the wheel 103 indicates the vehicle. For example, the wheel speed sensors of an anti-lock braking system (ABS) are used. This is advantageous because such ABS sensors are already mounted in all vehicles today. Wheel speed sensors are well known to those skilled in the art.

2 shows a schematic representation of an exemplary wheel speed sensor 100 , the one gear 210 with z. B. includes seven identical teeth. A sensor component 220 is located and arranged so that a sensor signal is always generated when a tooth (wheel tooth) of the gear wheel, the sensor component 220 happens. The sensor component 220 may be an optical sensor, a magnetic sensor (eg, a HALL sensor), or any other conceivable type of sensor. The sensor component 220 generates electrical signals which are transmitted by wires or radio transmission to a downstream processor / evaluation device (eg the evaluation device / processor) for further processing 102 out 1A ). In the example according to 2 There are a total of seven sensor signals that are generated during a complete revolution of the gear.

The processor or the evaluation device 102 The vehicle may be configured to determine time dependent vibrations or wheel speed oscillations using a matched filter, as further described in connection with the method embodiments.

By introducing a second sensor signal indicative of vertical movement of the chassis and combining it with the first sensor signal indicative of wheel speed vibrations (time-dependent vibrations of the wheel), more reliable detection of short-term irregularities in the road surface under a vehicle is achieved. Thus, a sensor fusion approach is used to improve detection performance while minimizing the number of false indications.

As illustrated, the second sensor may be, for example, an axle height sensor configured to determine a distance between the wheel axle of a wheel of the vehicle and the vehicle chassis. The axle sensor may measure the shaft height at various times, for example, at predefined successive time intervals, thereby providing a sensor signal indicative of a time-dependent distance between the wheel axle of the first wheel and the vehicle chassis.

Additionally or alternatively, the second sensor may be an air suspension height sensor and / or an air suspension height sensor associated with each of the one or more wheels of the vehicle that is configured to provide a time-dependent distance between the associated wheel or wheels and the vehicle chassis determine. The air suspension height sensor may perform measurements at various times, e.g. In predefined successive time intervals, thereby providing a sensor signal indicative of a time dependent distance between the associated wheel or wheels and the vehicle chassis.

Additionally or alternatively, the second sensor may be a vertical accelerometer, which may be e.g. B. is located in a suspension system of the vehicle.

The second sensor may include two or more sensor types, e.g. B. at least one Achshöhensensor and / or at least one air suspension height sensor and / or at least one vertical accelerometer.

With regard to wheel acceleration, any one or more sensors capable of determining the acceleration of a vehicle may be used.

The information from the second sensor may include information from one or more axle height sensors, one or more air suspension height sensors, and / or one or more accelerometers that may be combined to generate an enhanced second sensor signal.

Detection of transient irregularities on / on a road surface may be performed using information from sensors coupled to the wheel speed of a vehicle, as well as information from sensors coupled to vertical movement of the chassis of the vehicle, as discussed below.

wobei μ der erwartete Wert und σ² die Varianz von Δt ist.When one of the tires of a vehicle moves over a short-term irregularity on the road or roads, such as short sections of the road deemed uneven by the driver, gravel roads, potholes, speed bumps, bumps or the like, which have more or less pronounced edges , this puts a vertical shock to the tire. Due to the suspension characteristics of the tire and the suspension system, the shock causes a vibration with a pronounced resonance of approximately 15 Hz. The vibration affects the individual wheel speed and can be observed, for example, considering the time difference between two registrations of a wheel speed sensor, as in connection with FIG 2 described. Thus, one way to detect the tire vibrations that occur when a transient irregularity on the road surface is overrun is to maintain the variance of the time difference between two wheel tooth registrations during the duration of a predefined time interval, e.g. 100 ms, but not limited thereto. The variance of the time difference between two wheel tooth registrations can be estimated as follows:

where μ is the expected value and σ ^{2 is} the variance of Δt.

To calculate the variance σ ^{2 of} the time difference between two registrations of a wheel speed sensor for the predefined time interval, the expected value can be estimated. Due to speed changes during the predefined time interval, the expected value of the variance of the time difference between two registrations changes during the time interval. To compensate for this, the expected value of the variance of the time difference between two registrations can be approximated, for example as a linear progression over the time interval, such as by 4A illustrated.

4A shows a graphical representation 400 , the measurements 420 shows how the time difference between two registrations around the linear estimated course 410 for a wheel of the vehicle, which is illustrated here as the right front wheel of a four-wheeled vehicle. In the graphic representation 400 a time interval of 100 ms is emphasized, the oscillations having significantly greater amplitudes than vibrations outside the designated time interval. Such high / high amplitude may cause a momentary irregularity on the road surface of the road under the vehicle and may be compared to a threshold to determine detection of a transient irregularity, as related to 4B discussed in more detail.

The linear course of the variance of the time difference between two registrations may, in embodiments, be written as follows: y _k = φ T / k θ + e _k (Eq 2) where y _{k is} the k ^th measured time difference between two registrations of a wheel speed sensor during the predefined time interval, φ T / k = [k, 1], θ = [a, b] ^{T are} the slope of the linear curve and e _{k is} a noise term.

The least squares solution of Eq. 2 reads:

The estimated slope and offset of the linear gradient can be derived from the following expressions:

After the linear history has been estimated for the current preselected time interval, the variance σ ^{2 of} the time difference between two registrations as in Eq. 1 described.

The variance σ ² may then be compared to a predefined threshold established, for example, in the manufacture of the vehicle or during the calibration of the vehicle data collection and calculation systems.

The threshold value may be set to a level corresponding to a variance σ ^{2 of} the time difference between two registrations indicating a short-term irregularity on the road surface. Proceeding from this, if the variance σ ^{2 is} higher than the predetermined threshold value, this corresponds to an indication of a short-term irregularity under the vehicle and the processor or the evaluation device 102 (and / or the processor 132 ) may be configured to determine the presence of a short-term irregularity under the vehicle, or in other words to detect when the variance σ ^{2 is} above the predefined threshold.

In the in 4B shown graphic representation 430 For example, a variance of the time difference between two registrations of a wheel speed is given by an amplitude value in the y-direction per "set" indicated on the x-axis, where a "set" corresponds to a predefined time interval. In 4B is a threshold 440 indicating the presence of a momentary irregularity indicated by a dashed line. How out 4B As can be seen, there is a distinct peak, with an amplitude n exceeding the threshold followed shortly thereafter by a smaller peak. In this example, this is caused by a front wheel, which first meets the irregularity, and a corresponding rear wheel, which shortly afterwards encounters the same irregularity. The difference in size between the variance of the front and rear wheels in this case is due to the uneven weight distribution of the vehicle assuming that its engine is at the front. The smaller weight on the rear axle does not force the rear wheel to fall on the road irregularity to the same extent as the front wheel, and the impact on the rear wheel is therefore less.

A matched filter may be used to detect the presence of a short-term irregularity under a vehicle. This may include comparing a predefined template signal representative of the wheel speed oscillations, e.g. B. about 15 Hz, which occur when driving over a short-term irregularity on a road surface, with a signal that represents the measured or calculated wheel speed oscillations of a vehicle, and further comprising determining a detection of a transient irregularity when the measured or calculated signal correlates to a high degree (above a predetermined threshold) with the template signal. The matched filter can be written as a convolution, for example: y _MF (t) = (h · x) (t) = Σ _k h (k) x (t - k) (Eq. 6) where h is the searched template signal and x is the (measured / calculated) input signal.

h may be chosen to correspond to the impulse response of a bandpass filter of approximately a frequency representing the energy of a vibration caused by a predefined short-term irregularity.

A decision size for the matched filter signals can be generated by taking the square and low-pass filtering the output: y _LP (t) = LP (y ² (t)) (equation 7)

Examples of such decision variables are in 4C shown a normalized low-pass threshold 450 having. In 4C shows the illustrative graph 440 a signal derived from a wheel speed sensor of the right front wheel of a four-wheeled vehicle. According to this representation, this indicates when the threshold 450 is exceeded, the detection of a short-term irregularity on or the road surface under the vehicle. The detection may trigger an alarm which is perceptible to the driver of the vehicle, e.g. For example, any type of visual / audible / tactile output.

Any custom filter function known in the art and suitable for comparing two signals, not only those exemplified herein, may be used in embodiments of the matched filter.

Further, to supplement the information of the wheel speed signals, information about the vertical movement of the chassis over time can be used, in other words, sensor information concerning time-dependent vibrations of a wheel is fused with a time-dependent vertical movement of the chassis. Driving over an irregularity on the road surface implies energy in the suspension system that can be observed in sensor signals that measure the height between each wheel or wheel axle and the vehicle chassis. These signals may be particularly useful for detecting irregularities that do not have sharp edges that produce strong vibrations in the wheel speed signals.

Furthermore, another advantage of a sensor fusion approach is to minimize the number of false indications. During dynamic driving, for example, with heavy acceleration and gear shifting, the pitch angle of the vehicle could change rapidly, resulting in a possible false indication when only signals indicative of the vertical movement of the chassis are used. In combination with the information from the wheel speed sensor, such false displays can be prevented. In addition, misstatements caused by deterioration caused by the wheel speed signals - which are not associated with short-term road irregularities - can also be prevented by the use of sensor fusion with the sensors measuring the vertical movement of the chassis.

5A shows two graphical representations 500 . 510 exemplary axle height signals obtained using a front and a rear axle height sensor when driving over a short-term irregularity on the road surface under the vehicle.

wobei h_a die Achshöhe der Achse a und

die Bewegungsvarianz von h_a ist.The motion variances for the axis height signals can be calculated to obtain another indicator of short-term irregularities. The variances could be calculated as follows:

where h _{a is} the axis height of the axis a and

the motion variance of h _a is.

5B shows the graphical representations 530 and 540 , which outputs the variances of the axis height signals 5A represent. In method embodiments, the variance of a harmonic signal is compared to a predefined threshold, which in 5B through the dashed lines 550 . 560 3, wherein detection of a short-term irregularity on the road surface under a vehicle is determined when the variance value of the axle height signal exceeds the predetermined threshold.

Axis height signal variance values may be updated if the absolute value of the longitudinal acceleration is within predefined limits. This reduces or eliminates pitch angle variations that occur during high acceleration and sudden braking due to load shifts. As described herein, in one example, the axle height variance information may be provided by a wheel height sensor having wheel speed information, e.g. From a wheel speed sensor or wheel acceleration sensor, in order to obtain improved information (sensor fusion information) on the basis of which short-term irregularities on the road surface under the vehicle can be detected.

3 FIG. 12 is a flowchart of embodiments of a method for detecting a short-term irregularity under a vehicle having at least first and second wheels, the method comprising:
In step S310: determining a first sensor signal indicative of time-dependent oscillations on the first wheel using a first sensor.

• – ein Raddrehzahlsignal, das das zeitabhängige Verhalten der Drehzahl des ersten Rades des Fahrzeugs angibt, zum Beispiel Raddrehzahlschwingungen; und/oder
• – ein Signal von einem Beschleunigungsmesser sein, der sich z. B. in einem Aufhängungssystem des Fahrzeugs befindet.

The first sensor signal can

• A wheel speed signal indicative of the time dependent behavior of the speed of the first wheel of the vehicle, for example wheel speed vibrations; and or
• - Be a signal from an accelerometer, the z. B. is located in a suspension system of the vehicle.

Time dependent oscillations of the first sensor signal may be determined based on at least one of the time variance calculations between two consecutive internal signals of the first sensor, as in connection with FIGS 4A - 4C described, wherein the determining of the time-dependent oscillations comprises the use of a matched filter, as in connection with 4C described.

In a vehicle having at least one pair of wheels including a front and a rear wheel, whereby wheel speed signals obtained at each wheel of the pair of wheels are correlated, a correlation occurs at the time of the vibrations due to the passage of the momentary irregularity on the road surface under the vehicle. Peak up. If the distance between the front and rear axles of the vehicle is known, the wheel correlation can be used to determine the vehicle speed, e.g. As in the related document WO 2011/054363 A1 described.

Any or all of the embodiments according to step S310 may further be combined to obtain even more accurate information about the time-dependent oscillations.

In step S320: determining a second sensor signal indicating a time-dependent vertical movement of the vehicle chassis using a second sensor.

• – Bestimmen eines zeitabhängigen Abstands zwischen der Radachse des ersten Rades und dem Fahrzeugchassis unter Verwendung eines Achshöhensensors, wie in Verbindung mit den 5A und 5B beschrieben,
• – Bestimmen eines zeitabhängigen Abstands jeweils zwischen jedem der wenigstens zwei Räder des Fahrzeugs und dem Fahrzeugchassis unter Verwendung eines jedem der wenigstens zwei Räder zugeordneten jeweiligen Luftaufhängungshöhensensors, und/oder
• – Bestimmen einer Vertikalbeschleunigung unter Verwendung eines Vertikalbeschleunigungsmessers.

Determining a time-dependent vertical movement of the vehicle chassis may include:

• Determining a time dependent distance between the wheel axle of the first wheel and the vehicle chassis using an axle height sensor, as described in connection with FIGS 5A and 5B described,
• Determining a time dependent distance between each of the at least two wheels of the vehicle and the vehicle chassis using a respective air suspension height sensor associated with each of the at least two wheels, and / or
• Determining a vertical acceleration using a vertical accelerometer.

Any or all of the embodiments according to step S320 may be further combined to obtain even more accurate information about the time-dependent vertical movement of the chassis.

In step S330: detecting any short-term irregularity under the vehicle based on the first sensor signal and the second sensor signal.

The sensing step S330 may include comparing a value derived from a combination of the first and second sensor signals with a predefined threshold to determine detection of a short-term irregularity on the road surface under a vehicle.

• – Generieren eines normalisierten ersten Sensorwerts, erster_ensorwert_i, basierend auf einem Sensorsignal, das unter Verwendung des ersten Sensors zum Zeitpunkt t_i erhalten wurde;
• – Generieren eines normalisierten zweiten Sensorwerts, zweiter_Sensorwert_i, basierend auf einem Signal, das unter Verwendung des zweiten Sensors zum Zeitpunkt t_i erhalten wurde;
• – Berechnen eines Gesamtausgangswerts E basierend auf dem normalisierten ersten_Sensorwert_i und dem normalisierten zweiten_Sensorwert_i, und
• – Vergleichen des Gesamtausgangswerts E mit einem vorab festgelegten Schwellenwert, und
• – Bestimmen: o wenn der Gesamtausgangswert Eden vorab festgelegten Schwellenwert übersteigt, dass eine kurzzeitige Unregelmäßigkeit unter dem Fahrzeug vorhanden ist, oder o wenn der Gesamtausgangswert Eden vorab festgelegten Schwellenwert nicht übersteigt, dass keine kurzzeitige Unregelmäßigkeit unter dem Fahrzeug vorhanden ist.

The detection step S330 may include:

• Generating a normalized first sensor value, first sensor value _i , based on a sensor signal obtained using the first sensor at time t _i ;
• Generating a normalized second sensor value, second sensor value _i , based on a signal obtained using the second sensor at time t _i ;
• Calculating a total output value E based on the normalized first sensor value _i and the normalized second sensor value _i , and
• Comparing the total output value E with a predetermined threshold, and
• Determining: o if the total output value E exceeds the predetermined threshold, if there is a short-term irregularity under the vehicle, or o if the total output value E does not exceed the predetermined threshold, that there is no short-term irregularity under the vehicle.

The sensor fusion determination may be performed each time the first and second sensors make measurements as indicated above using the time indication t _i .

Alternatively, the sensor fusion determination may be performed only when it is determined that a measured sensor value from the first or second sensor exceeds a predetermined threshold at a predetermined time t _i , whereby the total output E is calculated and compared to the predetermined threshold only; when the first or second sensor provides an indication that a short term irregularity may be present under the vehicle. In this case, if it is determined that the total output value E does not exceed the predetermined threshold, it corresponds to a "false alarm" because the first or second sensor has registered a value which, taken in isolation, will detect a momentary irregularity indicating on the road surface under the vehicle. In other words, the use of sensor fusion, the fusion of information from two or more sensors, provides a more accurate detection of transient irregularities than the use of information from a single sensor.

The first sensor value can be normalized by multiplication by a first constant K1 and the second sensor value by multiplication by a second constant K2. The values of K1 and K2 may be predetermined and determined during manufacture or calibration and / or in one in a vehicle 1 integrated data storage 104 , as in 1 A shown or a the vehicle 1 accessible data storage, z. B. a data store 134 the central system backend unit 130 , as in 1B be shown, stored and retrieved from this. The processor 102 and / or the processor 132 may be configured to store the first and second constants K1 and K2 from a memory 104 . 132 to normalize the first and second sensor signals using the first and second constants K1 and K2, and to generate an overall output value E by summing the resulting values of the normalized sensor signals according to the following equation: E = K1 · (first sensor value _i ) + K2 · (second sensor value _i ) (equation 9)

The total output value E may correspond to an energy value.

• o wenn der Gesamtausgangswert E den vorab festgelegten Schwellenwert übersteigt, dass eine kurzzeitige Unregelmäßigkeit unter dem Fahrzeug vorhanden ist, oder
• o wenn der Gesamtausgangswert E den vorab festgelegten Schwellenwert nicht übersteigt, dass keine kurzzeitige Unregelmäßigkeit unter dem Fahrzeug vorhanden ist.

The processor 102 and / or the processor 132 may be configured to compare and determine the total output E with a predetermined threshold:

• if the total output E exceeds the pre-established threshold, there is a short-term irregularity under the vehicle, or
• o if the total output value E does not exceed the pre-established threshold, there is no short-term irregularity under the vehicle.

The above rating can be z. For the entire vehicle, for each separate wheel, if the vehicle has more than one wheel, or for each pair of wheels, if the vehicle has two or more pairs of wheels.

The constants K1 and K2 may be at a parameter download in connection with the maintenance of the vehicle or via a download from a communication network, eg. An automatic or user-triggered download at predefined time intervals or in conjunction with a new system version output. Furthermore, the constants K1 and K2 can also be adjusted as a function of the speed of the vehicles, since the induced energy changes as a function of the rotational speed; the higher the speed, the lower the induced energy.

By combining the information obtained from step S310 and step S320, improved detection of short-term irregularities is achieved. For example, step S310 may be sufficient to detect a transient irregularity, e.g. For example, a pothole that has sharp edges and thereby causes large variations in wheel speed vibration, however, a smoother edge irregularity may go unnoticed if, for example, the amplitude of the vibrations does not exceed a predetermined threshold.

By combining the information about variations of the wheel speed vibration with information about chassis vibrations, a more accurate determination as to whether the vibrations of the wheel speed actually indicate the presence of a road irregularity or not can be made.

After step S330, information about each detected short-term irregularity is obtained. This information can be used for several advantageous purposes.

The method may include creating or updating a map of the current road surface condition based on one or more detected short term irregularities.

The method may additionally or alternatively include updating a classification of the road surface based on one or more detected short-term irregularities.

The method may additionally or alternatively include performing the aforementioned creation or update of a map of the current road surface condition and / or updating a classification of the road surface in real time.

The method may further include, additionally or alternatively, adjusting the settings of the active suspension of the vehicle based on the updated classification.

The method may include distributing the updated road surface classification or map using a driver support system that is capable of communicating directly with each other and / or with the traffic infrastructure operators.

All of the method steps and functions described herein may be performed in real time and the calculations and evaluations may be performed by the processor 132 or the evaluation device 102 of the vehicle or by the processor 132 the central system backend unit 130 performed and to the processor or the evaluation 102 be communicated to the vehicle.

The processor or the evaluation device 102 may be configured to determine, in the step relating to the first sensor signal, a sensor signal indicative of time-dependent oscillations on a first wheel, or to determine another sensor signal indicative of time-dependent oscillations on a second wheel, and the first and second sensor signals to correlate to determine a correlation signal of the signals obtained at the first and second wheels. When one or more wheel speed sensors are used to measure the vibrations, the wheel speed signals are preferably measured on a pair consisting of a front and a rear wheel running in a lane so as to sense, with a time delay, the same road characteristics.

The processor or the evaluation device 102 may be configured to perform any one or all of the method steps or functions described herein.

As a possible implementation, a computer program product is provided which, when executed in a computing device, is arranged to control a processor to perform any of the method steps or functions described herein.

The vehicle may include a display device (not shown in the figures), wherein the evaluation device or the processor 102 may be configured to control the display and / or audible and / or noticeable output to output graphics or image or audible or tactile data associated with the road surface condition, such as a map of the current road surface condition, or upcoming obstacles or a visual / audible / noticeable alarm / warning that the vehicle is approaching an obstacle.

Embodiments of computer program products having program code for performing the described methods include any machine-readable medium capable of storing or encoding the program code. The term "machine-readable medium" is therefore to be understood as including, but not limited to, semiconductor memory, optical and magnetic storage media, and carrier wave signals. The program code may be a machine code or other code that may be translated by compilation and / or interpretation into machine code, such as a source code in a high level programming language such as C ++, or any other suitable necessary or functional programming language be virtual machine code. The computer program product may comprise a data medium provided with the program code or other means designed to control or direct a data processing device to carry out the method as described. A data processing apparatus executing the method typically includes a central processing unit, data storage devices and an I / O interface for signals or parameter values.

Fig. 1A

• Rear wheel

  = Rear wheel

  Front wheel

  = Front wheel

Fig. 1B

• Vehicle 1

  = Vehicle 1

  Vehicle 2

  = Vehicle 2

  Vehicle N

  = Vehicle N

Fig. 2

• sensor

  = Sensor

Fig. 3

• ---

Fig. 4A

• Front right wheel

  = Right front wheel

  Oscillations

  = Vibrations

  Oscillations

  = Vibrations

  Estimated trend

  = Estimated History

  Number of tics since last cog

  = Number of tics (i.e., time interval between two tooth detections) since last tooth

  COG [k]

  = TOOTH [k]

Fig. 4B

• Batchwise Variance of Delta-tic

  = set variation of the time interval between two tooth detections

  Front Left

  = Front left

  Front Right

  = Front right

  Rear Left

  = Back left

  Rear Right

  = Back right

  Threshold

  = Threshold

  Batch [nr]

  = Sentence [nr]

Fig. 4C

• Front Right Wheel

  = Right front wheel

Fig. 5A

• Axle height front

  = Achshöhe front

  Axle Hight Rear

  = Achshöhe behind

Fig. 5B

• Axle Hight Variance Front

  = Shaft height variance in front

  Axle Hight Variance Rear

  = Height variance rear

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions.

Cited patent literature

• WO 2011/054363 A1 [0085]

Claims (15)

A method of detecting a transient irregularity of a road surface under a vehicle having at least a first wheel, the method comprising:  a) determining a first sensor signal indicative of time-dependent vibrations at the first wheel using a first sensor,  b) determining a second sensor signal indicative of a time-dependent vertical movement of the vehicle chassis, using a second sensor, and  c) detecting a momentary irregularity of a road surface under the vehicle based on the first sensor signal and the second sensor signal. The method of claim 1, wherein the first sensor signal is a wheel speed signal indicative of the time dependent behavior of the speed of the first wheel of the vehicle. Method according to one of the preceding claims, wherein the first sensor signal is a signal from an accelerometer of the vehicle. Method according to one of the preceding claims, wherein the time-dependent oscillations of the first sensor signal are determined based on calculations of the time variance between two consecutive internal signals of the first sensor. The method of any one of the preceding claims, wherein determining the time dependent vibrations comprises using a matched filter. The method of claim 1, wherein determining a time-dependent vertical movement of the vehicle chassis comprises determining a time-dependent distance between the wheel axle of the first wheel and the vehicle chassis using an axle height sensor. The method of claim 1, wherein determining a time-dependent vertical movement of the vehicle chassis comprises determining a time-dependent distance between the first wheel and the vehicle chassis using an air suspension height sensor associated with the first wheel. The method of claim 1, wherein determining a time-dependent vertical movement of the vehicle chassis comprises determining a vertical acceleration using a vertical accelerometer. The method of any one of the preceding claims, further comprising creating or updating a map of the current road surface condition based on one or more detected short term irregularities. The method of any one of the preceding claims, further comprising updating a classification of the road surface based on one or more detected short-term irregularities. The method of claim 1, further comprising adjusting the settings of the active suspension of the vehicle based on one or more detected short-term irregularities and / or information derived therefrom. The method of claim 9 or 10, further comprising distributing information about one or more detected short-term irregularities and / or information derived therefrom using a driver assistance system. A system for detecting a short-term irregularity of a road surface under a vehicle having a first wheel, the system comprising: a) a first sensor ( 100 ) configured to determine a first sensor signal that detects time-dependent oscillations on the first wheel ( 103 ) indicates b) a second sensor ( 140 ) configured to determine a second sensor signal indicative of a vertical movement of the vehicle chassis, and c) an evaluation device (10); 102 ) configured to: receive the first sensor signal and the second sensor signal, and To detect a momentary irregularity present on a road surface under the vehicle based on the first sensor signal and the second sensor signal. A computer program product configured, when executed in a computing device, to control a processor to detect a momentary irregularity under a vehicle having a first wheel by:  a) determining a first sensor signal indicative of time-dependent vibrations at the first wheel using a first sensor,  b) determining a second sensor signal indicative of a time-dependent vertical movement of the vehicle chassis, using a second sensor, and  c) detecting a momentary irregularity of a road surface under the vehicle based on the first sensor signal and the second sensor signal. The computer program product of claim 14, further configured, when executed in a computing device, to control a processor to perform the method steps of any one of claims 2 to 12.

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