DE102018206956A1 - Method for determining a vehicle position - Google Patents

Abstract

The invention relates to a method for determining the position and / or movement of a vehicle, wherein the vehicle has an electronic processing device (20), a state detector (10), and at least one sensor designed to detect driving dynamic measured values and to output sensor data, wherein
- The electronic processing device (20) determined from the sensor data based on a vehicle dynamics model, a position and / or movement of the vehicle, characterized in that
- The state detector (10) detects a driving condition (1) of the vehicle and
- The processing device (20) depending on the detected driving condition (1) a first or a second vehicle dynamics model (21, 22) used to determine the position and / or movement of the vehicle.

Description

The invention relates to a method for determining the position and / or movement of a vehicle and an associated electronic control device.

For determining the position and / or movement of a vehicle, various approaches are known from the prior art. For example, by means of satellite navigation, also called Global Navigation Satellite System, GNSS for short, a vehicle can be located via a corresponding receiver. Likewise, the odometry of the vehicle can be used. For example, for odometric measurements, the pulses of the wheel angle encoders of all wheels of a vehicle as well as the wheel steering angle can be used and, for example, a longitudinal speed and a rotation angle about the vertical axis can be derived. Acceleration and rotation rate sensors, for example an inertial measurement unit, can be used in a so-called strapdown algorithm for determining location and orientation. A sufficiently precise and reliable determination of the position or movement of the vehicle can often only be achieved by combining or merging a plurality of such and similar measurement information. In this case, a model is used which defines calculation rules according to which the position and / or movement of the vehicle is at least approximately determined from the various input variables.

From the Scriptures WO 2011/098333 A1 It is known to use different sensor sizes in a vehicle to improve existing sensor sizes or to generate new sensor sizes and thus to increase the detectable information.

The model, which is used for the large number of sensor input variables for estimating the vehicle movement or position, is usually adapted as well as possible to the respective vehicle and parameterized. It is assumed that normal driving conditions, possibly taking into account the dynamic driving limit range.

In the meantime, however, there is an increasing number of systems in vehicles that take effect and function after an accident or collision. Typically, then the assumption of the model used is no longer that normal driving conditions exist. Therefore, in the critical phase after an accident, the position or movement information may be deficient.

It is therefore an object of the invention to provide a method which allows a reliable and / or precise determination of position and / or movement of a vehicle, even in critical situations.

This is achieved according to the invention by methods and a control device according to the respective independent claims. Advantageous embodiments can be taken, for example, the respective subclaims. The content of the claims is made by express reference to the content of the description.

• - die elektronische Verarbeitungseinrichtung aus den Sensordaten auf Basis eines Fahrdynamikmodells eine Position und / oder Bewegung des Fahrzeugs ermittelt, dadurch gekennzeichnet, dass
• - der Zustandsdetektor einen Fahrzustand des Fahrzeugs erfasst und
• - die Verarbeitungseinrichtung abhängig von dem erfassten Fahrzustand ein erstes oder ein zweites Fahrdynamikmodell zum Ermitteln der Position und / oder Bewegung des Fahrzeugs verwendet.

According to the invention, for a method for determining the position and / or movement of a vehicle, the vehicle has an electronic processing device, a state detector, and at least one sensor configured to acquire driving dynamic measurements and to output sensor data, the method comprising the steps that

• - The electronic processing device determined from the sensor data based on a vehicle dynamics model, a position and / or movement of the vehicle, characterized in that
• - The state detector detects a driving condition of the vehicle and
• - The processing device depending on the detected driving state, a first or a second vehicle dynamics model used to determine the position and / or movement of the vehicle.

Mentioned steps of the method according to the invention can be carried out in the order given. However, they can also be executed in a different order. In one of its embodiments, for example with a specific set of steps, the method according to the invention can be carried out in such a way that no further steps are carried out. Without prejudice to the said steps of the method, however, further steps can be carried out in principle, even those which are not mentioned in this document.

The term sensor is preferably understood to mean a single sensor or a system of several sensors. The sensor data may preferably include one or more variables, such as position, speed, acceleration, direction, slip angle, ie the angle between the direction of movement of the vehicle in the center of gravity and the vehicle longitudinal axis when cornering, yaw rate and / or offset compensation of sensor sizes.

The vehicle dynamics model preferably designates one or more schedules and / or Arithmetic rules on how certain input data, sensor data or further processed data obtained from sensor data are processed into output data containing information about position and / or movement of the vehicle. The vehicle dynamics model preferably also depends on certain properties, such as dimensions, stiffnesses, masses of the vehicle or its components.

The specified method has the advantage that an adaptation of the position or movement determination to different driving or movement states is made possible by different driving dynamics models, so that the position or movement determination is precise and reliable independently of the current driving or movement state. In the following, for simplicity, only spoken of driving condition.

It is preferable that the state detector distinguishes between an accident-free driving state and a driving state during or after an accident when detecting the driving state, and the processing device uses the first driving dynamics model in an accident-free driving state and the second driving dynamics model in a driving state during or after an accident. By using a driving dynamics model tailored to the driving condition during or after an accident, it is possible that a high level of information quality is available even in this critical phase. This provides, for example, more accurate position information for a satellite-based, preferably permanently installed in the vehicle emergency call system (eCall). In addition, systems that provide, for example, automatic or assisted braking or steering following an accident thus provide better movement information.

Hereinafter, various embodiments are mentioned with regard to the vehicle dynamics models used. It should be noted that these embodiments are arbitrarily combinable, so both alternative to each other and can be used in addition. Accordingly, several retrievable variants can be available in parallel for the second vehicle dynamics model.

Preferably, the second driving dynamics model differs from the first driving dynamics model at least in that parts, in particular specific driving dynamic measured values, of the first driving dynamics model are not taken into account in the second driving dynamics model. According to an advantageous development, adaptive parts of the first driving dynamics model are no longer considered in the second in order to avoid mismatches.

According to an additional development, the second vehicle dynamics model is designed such that, for a certain period of time after the change of the vehicle dynamics model, the determination of the position and / or the movement of the vehicle is suspended, if appropriate under the condition that no plausible sensor data is available. Thus it can be prevented that the driving dynamics model is misaligned.

The condition detector preferably detects the differentiation of the driving conditions on the basis of the measured values of at least one accident sensor. An accident sensor should preferably be understood to be a single or a group of sensors designed to record measured values which in some way make it possible to draw conclusions about an undesired driving situation, for example an imminent, occurring or already occurring collision or a collision between a vehicle-external Object and the vehicle. In addition to the types of accident sensors mentioned below, other known from the prior art accident sensors may be appropriate, as they are often used as a basis for decision for the deployment of an airbag or belt tensioner.

• - einen Kollisionssensor, der ausgebildet ist, eine Berührung mit einem fahrzeugfremden Objekt bzw. eine dadurch hervorgerufene Beschleunigung zu erfassen und / oder
• - einen Überschlagssensor, der ausgebildet ist, eine Drehung um die Fahrzeuglängs- oder Querachse zu erfassen, die ausreichend hoch ist um einen Überschlag des Fahrzeugs zu ermöglichen und / oder
• - einen Beschleunigungssensor, der ausgebildet ist, Beschleunigungen oberhalb eines, insbesondere unfalltypischen, Schwellwertes zu erfassen und / oder
• - einen Umfeld- oder Näherungssensor, der ausgebildet ist, eine bevorstehende Kollision des Fahrzeugs mit einem Objekt zu erfassen. Ein solcher Umfeld- oder Näherungssensor kann beispielsweise als Ultraschallsensor ausgebildet sein.

Zusätzlich oder alternativ zu dem genannten Überschlagssensor kann der Unfallsensor einen bzw. den ohnehin vorhandenen GNSS-Empfänger umfassen, wobei auf Basis der sich schlagartig ändernden Empfangssituation des GNSS-Empfängers ein Überschlag des Fahrzeugs erkannt bzw. die Erfassung durch den Überschlagssensor bestätigt wird.The crash sensor preferably comprises

• a collision sensor, which is designed to detect a contact with a vehicle-foreign object or an acceleration caused thereby and / or
• a rollover sensor adapted to detect a rotation about the vehicle longitudinal or transverse axis which is sufficiently high to allow rollover of the vehicle and / or
• an acceleration sensor which is designed to detect accelerations above a, in particular accident-typical, threshold value and / or
• an environment or proximity sensor configured to detect an imminent collision of the vehicle with an object. Such an environment or proximity sensor may be formed, for example, as an ultrasonic sensor.

In addition or as an alternative to the aforementioned rollover sensor, the accident sensor may comprise one or the already existing GNSS receivers, a rollover of the vehicle being detected or the detection being confirmed by the rollover sensor based on the abruptly changing reception situation of the GNSS receiver.

Preferably, one of the driving dynamics models, in particular the second driving dynamics model, based on vehicle data, in particular axial spacing, axle width, rolling resistance of the wheels, which are dependent on a deformation of the vehicle derived from the measured values of the accident sensor. Thus, a distortion is counteracted in determining the position and / or the movement of the vehicle by vehicle deformation.

An advantageous embodiment of the method according to the invention comprises that one of the driving dynamics models, in particular the second driving dynamics model, is based on kinematic variables which are derived from the measured values of the accident sensor.

For example, a suitably designed collision sensor can provide acceleration values.

It is preferred that one of the driving dynamics models, in particular the second driving dynamics model, comprises equations of motion in which the vehicle is mathematically modeled as point mass. The point mass describes a strong idealization of a real body, in this case the vehicle. The point mass is preferably understood to be a physical model that represents the body solely in terms of its location and mass, and serves to facilitate the description of the movement of the body. External properties such as volume and shape are neglected. The body is considered as a mathematical point, which thus has no extension, but a finite mass. In particular, a spot mass preferably has no rotational degrees of freedom. By disregarding the rotational movement and the distribution of the mass in the body volume of the vehicle with the idealization as point mass, variables which are in any case uncertain or erroneous in a certain driving state, such as after an accident, do not flow into the position / movement determination one.

It is preferred that one of the driving dynamics models, in particular the second driving dynamics model, is based exclusively on driving dynamics variables that map the movement of the vehicle independently of a road contact, in particular wheel speeds ignored. In a driving condition in which it is uncertain whether the wheels touch the ground at all, thus an uncertain size is disregarded in the calculation.

It is preferred that the second vehicle dynamics model differs from the first vehicle dynamics model in that one or more threshold values for error detection, in particular threshold values for error detection in acceleration measurement data, are not taken into account from the first vehicle dynamics model in the second vehicle dynamics model.

A preferred embodiment of the method according to the invention provides that the second vehicle dynamics model differs from the first vehicle dynamics model in that GNSS data as the input variable of the first vehicle dynamics model in the second vehicle dynamics model are not taken into account as an input variable. This is particularly advantageous if it is expected that the GNSS receiver is damaged or the normal assumptions for the propagation of GNSS signals no longer apply.

It is preferred that the second driving dynamics model differs from the first driving dynamics model in that data of an inertial measuring unit as an input variable of the first driving dynamics model in the second driving dynamics model are not taken into account as an input variable. This is particularly advantageous when it is expected that the inertial measuring unit is operated outside its normal working range. Preferably, the term inertial measuring unit is understood to mean an acceleration or yaw rate sensor, particularly preferably a plurality thereof, in particular in the form of a sensory measuring unit of an inertial navigation system.

It is preferred that during the use of the first or second vehicle dynamics model for determining the position and / or the movement of the vehicle, the processing device carries out calculations according to the respective other vehicle dynamics model and makes use of these when changing the vehicle dynamics model. In other words, one or more different from the first vehicle dynamics model driving dynamics models already counted during normal driving. Their output data are thus always available and switching the driving dynamics model used by the processing means only means that the output of another vehicle dynamics model is used. Thus, the vehicle dynamics model can be changed quickly, without settling times for the newly used vehicle dynamics model are necessary.

According to a preferred development of the method according to the invention, the processing device stores the sensor data used in determining the position and / or movement of the vehicle when using the first or second vehicle dynamics model in a data memory and uses the cached sensor data for a certain period of time when the vehicle dynamics model is changed when Input. Thus, the driving dynamics model can be changed quickly.

According to a further aspect of the invention, the object is achieved by an electronic control device which is configured to carry out a method according to one of the preceding claims, wherein the control device preferably has a sensor designed to acquire driving-dynamic measured values and to output sensor data and a state detector for Detecting a driving state of the vehicle includes or is preferably adapted to receive sensor data from the sensor and a driving state of the state detector.

Further features and advantages of the invention, the skilled artisan take the embodiment described below with reference to the accompanying drawings.

1 schematically shows a flowchart for carrying out the method according to the invention according to an embodiment.

It is assumed that a vehicle is an electronic processing device 20 , a state detector 10 and at least one sensor designed to detect driving dynamic measured values and to output sensor data. In the present embodiment, there are several sensors. On the one hand an inertial measuring unit, which is able to detect accelerations and turning rates of the vehicle in all spatial directions. On the other hand, an odometry sensor and a GNSS receiver for receiving satellite signals of a satellite navigation system. The various sensor data originating from these sensors are stored in the processor 20 fused so that the respective merits of the various sensors are used to determine the position or movement of the vehicle.

The processing device 20 receives in the present embodiment, via the GNSS receiver, location data of the vehicle including an absolute position of the vehicle on a roadway. In addition to the absolute position, the location data from the GNSS receiver also includes a speed of the vehicle. The location data from the GNSS receiver is derived in the present embodiment in a manner known to those skilled in the art from a GNSS signal in the GNSS receiver which is received via a GNSS antenna and hence referred to below as GNSS location data. For details, refer to the relevant literature.

By merging with the other sensor data is the processing device 20 able to increase the information content of the GNSS position data derived from the GNSS signal. This is useful because the GNSS signal is not always available. The further sensor data in the present case comprise vehicle dynamics data from an inertial measurement unit in the form of a longitudinal acceleration, a lateral acceleration as well as a vertical acceleration and a roll rate, a pitch rate and a yaw rate of the vehicle.

To further increase the information content of the GNSS position data, an odometry sensor system is used in the present embodiment. This includes wheel speed sensors, which detect the wheel speeds of the individual wheels of the vehicle. It may also include a steering angle signal to further increase the information content of the GNSS location data.

On the one hand, situation data of the vehicle are generated via a strapdown algorithm from the vehicle dynamics data of the inertial measurement unit. The fusion of the sensor data also uses comparative data for the same quantities that are derived from the GNSS position data or the data from the odometry sensors. How the position data or comparison data are calculated may depend on the vehicle dynamics model used.

The filter used for the merger calculates an error budget for the location data and a fault budget for the comparison data based on the location data and the comparison data. The fault households are then supplied according to the strapdown algorithm and the vehicle dynamics model used to correct the position data or the comparison data. This means that the location data and the comparison data are iteratively adjusted for their errors.

The used vehicle dynamics model can depend on a detected driving condition 1 be changed. This is a state detector 10 provided, which is adapted to a change in the driving state 1 to detect via an accident sensor. The driving condition 1 is from the state detector 10 via a corresponding detector signal 2 to the processing device 20 forwarded, the detector signal 2 at least one distinction allows between a driving condition 1 , which corresponds to a normal driving and a driving condition 1 who one driving condition 1 at or after an accident.

The processing device 20 determines the position and / or movement of the vehicle based on the vehicle dynamics model used. Receives a detector signal 2 that a driving condition 1 corresponds to or after an accident, it takes the place of the previously used first vehicle dynamics model 21 on a second driving dynamics model 22 back to make it a position / motion signal 3 to generate, by means of the second driving dynamics model 22 the peculiarities of the changed driving condition 1 considered.

For the second driving dynamics model 22 are different variants conceivable. Accordingly, the detector signal 2 allow in conjunction with the accident sensor or the accident sensors finer distinctions, so that the respectively appropriate variant of the second driving dynamics model 22 can be selected.

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 2011/098333 A1 [0003]

Claims (15)

Method for determining the position and / or movement of a vehicle, wherein the vehicle has an electronic processing device (20), a state detector (10), and at least one sensor designed to acquire driving-dynamic measured values and to output sensor data, wherein - the electronic processing device (20) from the sensor data on the basis of a vehicle dynamics model determines a position and / or movement of the vehicle, characterized in that - the state detector (10) detected a driving condition (1) of the vehicle and - the processing means (20) depending on the detected driving condition (1) uses a first or a second vehicle dynamics model (21, 22) to determine the position and / or movement of the vehicle. Method according to Claim 1 , characterized in that the state detector (10) upon detection of the driving state (1) between an accident-free driving state (1) and a driving state (1) at or after an accident and the processing means (20) in an accident-free driving state (1) the first driving dynamics model (21) and in a driving condition (1) used during or after an accident, the second driving dynamics model (22). Method according to Claim 2 , characterized in that the second driving dynamics model (22) differs from the first driving dynamics model (21) at least in that parts, in particular certain driving dynamic measured values, of the first driving dynamics model (21) are not taken into account in the second driving dynamics model (22). Method according to one of the preceding claims, characterized in that the state detector (10) detects the differentiation of the driving conditions on the basis of the measured values of at least one accident sensor. Method according to Claim 4 characterized in that the crash sensor comprises a collision sensor configured to detect contact with a non-vehicle object and / or comprises a rollover sensor configured to detect rotation about the vehicle longitudinal or lateral axis that is sufficiently high is to allow a rollover of the vehicle and / or - comprises an acceleration sensor which is adapted to detect accelerations above a, in particular accident typical, threshold and / or - includes an environment or proximity sensor, which is an imminent collision of the vehicle to capture with an object. Method according to one of Claims 4 or 5 Characterized in that one of the driving dynamics models, in particular the second dynamics model (22), on the basis of vehicle data, in particular wheelbase, axle width, rolling resistance of the wheels, is modeled, which depend on a variable derived from the measured values of the accident sensor deformation of the vehicle. Method according to one of Claims 4 to 6 , characterized in that one of the driving dynamics models, in particular the second driving dynamics model (22), based on kinematic variables, which are derived from the measured values of the accident sensor. Method according to one of the preceding claims, characterized in that one of the driving dynamics models, in particular the second driving dynamics model (22), comprises equations of motion in which the vehicle is mathematically modeled as a point mass. Method according to one of the preceding claims, characterized in that one of the driving dynamics models, in particular the second driving dynamics model (22), based exclusively on driving dynamics variables that reflect the movement of the vehicle regardless of a road contact, in particular while ignoring wheel speeds. Method according to one of Claims 2 to 9 , characterized in that the second driving dynamics model (22) differs from the first driving dynamics model (21) in that one or more threshold values for error detection from the first driving dynamics model (21) in the second driving dynamics model (22) are not taken into account. Method according to one of Claims 2 to 10 , characterized in that the second driving dynamics model (22) differs from the first driving dynamics model (21) in that GNSS data as the input variable of the first driving dynamics model (21) in the second driving dynamics model (22) are not taken into account as an input variable. Method according to one of Claims 2 to 11 , characterized in that the second driving dynamics model (22) differs from the first driving dynamics model (21) in that data of an inertial measuring unit as an input variable of the first driving dynamics model (21) in the second driving dynamics model (22) are not taken into account as an input variable. Method according to one of the preceding claims, characterized in that the processing device (20) during the use of the first or second driving dynamics model (21, 22) for determining the position and / or movement of the vehicle performs calculations according to the other driving dynamics model and these relies on a change of the vehicle dynamics model. Method according to one of the preceding claims, characterized in that the processing device (20) temporarily stores the sensor data used for determining the position and / or the movement of the vehicle when using the first or second driving dynamics model (21, 22) in a data memory and at a Changing the driving dynamics model uses the cached sensor data as an input variable for a certain period of time. An electronic control device configured to carry out a method according to any one of the preceding claims.

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