Method for providing information on the reliability of parameter estimates of vehicle operating parameters

Abstract

The invention relates to a method for providing information (1, 2) on the parameter estimation reliability of an operating parameter of a vehicle (3), comprising at least the following steps: a) determining an integrity range (1) of the parameter estimation, wherein the integrity range (1) describes a range in which the estimated parameter has a minimum probability; b) determining an effectiveness indicator (2) describing the effectiveness of the integrity range (1) determined in step a); c) providing the integrity range (1) determined in step a) and the effectiveness indicator (2) determined in step b).

Description

Technical Field

[0001] This invention relates to a method for providing information on the reliability of parameter estimates of vehicle operating parameters, a computer program for performing the method, a machine-readable storage medium, and a control device for a vehicle. This invention is particularly suitable for use in conjunction with autonomous driving. Background Technology

[0002] One of the most significant challenges in autonomous driving is determining the self-position of an autonomous vehicle as accurately and reliably as possible. Autonomous vehicles typically possess sensors, such as inertial sensors, wheel sensors, environmental sensors, GNSS sensors, and optical and / or acoustic sensors, which enable the vehicle to estimate its own position. Helpfully in this regard, information about the (expected) accuracy of the determined self-position is also output. For example, the confidence level of the determined self-position can be represented by the so-called "level of protection" ("PL"). Here, PL describes a statistical error bound, which is typically calculated based on statistical considerations and, where necessary, appropriate coordination of the estimation algorithm.

[0003] The concept of protection levels is particularly prevalent in the aviation field. However, solutions developed in this area are not easily transferred to autonomous driving applications. In particular, factors such as houses, canyons, and their impact on satellite signals create problems not present in aviation applications. Therefore, there is a need to improve methods for calculating protection levels that are as reliable as possible, especially those that provide reliable results even in challenging environments such as urban areas. Summary of the Invention

[0004] Hereinafter, according to claim 1, a method for providing information on the reliability of parameter estimates of operating parameters of a (motor) vehicle is described, comprising at least the following steps:

[0005] a) Determine the integrity range of the parameter estimates, where the integrity range describes the range in which the estimated parameters with the minimum probability lie;

[0006] b) Determine the validity metrics, which describe the validity of the integrity scope determined in step a);

[0007] c) Provide the integrity scope determined in step a) and the validity metrics determined in step b).

[0008] Steps a) through c) can be executed at least once or more in the specified order to perform the method. Furthermore, steps a) and b) can be performed at least partially in parallel or even simultaneously.

[0009] Parameters can be safety-related parameters and / or parameters related to or required for at least partially automated and / or autonomous driving operation. Parameters can provide information related to the vehicle's driving operation and / or contribute to or are applicable to describing the vehicle's driving operation. In principle, one or more (different types of) parameters can be estimated. Parameters can be, for example, the vehicle's own position, its own speed, its own acceleration, etc. Parameters are preferably related to the vehicle's own position.

[0010] The parameters can be driving operation parameters of a (motorized) vehicle. Here, driving operation parameters can be understood in particular as parameters that help describe the vehicle's spatial driving operation or its movement in space. Driving operation parameters, in particular, at least help describe the vehicle's own motion and / or its own position. Driving operation parameters can be, for example, the vehicle's (own) position, (own) velocity, (own) acceleration, or orientation (or direction). The driving operation parameter is preferably the vehicle's own position. Therefore, this method can be used, for example, in conjunction with position estimation of the vehicle's position. Here, the integrity range can describe the range in which the estimated (actual) vehicle position (with the minimum probability) lies.

[0011] The information to be provided regarding the reliability of the parameter estimation may include, for example, at least two pieces of information. This information preferably includes at least one integrity range and a validity index for the parameter estimation. Providing at least these two pieces of information can advantageously contribute to improving the reliability of determining (particularly at least partially automated or autonomous driving) the vehicle's own position. Another advantage of this method is that, in addition to integrity information in the form of an integrity range, validity information in the form of a validity index is also provided. This allows the information given by the integrity range to be enriched without changing the integrity range itself. Thus, the design of determining the integrity range used under different conditions can advantageously remain unchanged or independent of the validity information in the form of a validity index. Therefore, the integrity range can continue to be output as mathematically defined statistical error information or error limits. This provides advantageous usability, particularly from the perspective of a unified interface, because the original meaning / definition of the integrity range does not need to be changed. The possibility of modular design is also increased as a result. Furthermore, the provided integrity range can thus be used independently of the validity index when necessary, thereby advantageously improving its applicability.

[0012] In step a), the integrity range of the parameter estimate is determined, where the integrity range describes the range in which the estimated parameter (value) (actual) with the minimum probability lies. Here, the estimated parameter (value) essentially describes the (individual, particularly instantaneous) estimation result of the parameter estimate. In other words, this specifically means that the integrity range describes the range in which the true or actual value of the estimated parameter with the minimum probability lies. Such an integrity range can also be referred to as the so-called "level of protection".

[0013] The minimum probability is usually a predefined minimum probability. Preferably, the minimum probability is 90%, and more preferably 95% or even 99%.

[0014] The integrity range is preferably a protection level. Here, the protection level typically describes the spatial (particularly two- or three-dimensional) range in which the estimated parameter (value) (actual) with the lowest probability resides. The estimated parameter (value) essentially describes the (individual, particularly instantaneous) estimation result of the parameter estimate. In other words, this specifically means that the protection level describes the range in which the true or actual value of the estimated parameter with the lowest probability resides.

[0015] In other words, the protection level specifically describes the confidence interval or (spatial) confidence range in which the true value of the estimated parameter with the minimum probability lies. Here, the estimated value of the parameter is typically located in the middle or center of the confidence interval or confidence range.

[0016] The probability that the estimated true or actual value of the parameter is actually within the protection level is much higher than the "normal" integrity range. Here, the minimum probability is typically greater than 99.99%, particularly preferably greater than 99.999%, or even greater than 99.9999%. For the protection level, the minimum probability may also be expressed not as a percentage, but as the probability of errors occurring within a specific time interval. The protection level can be defined, for example, as the parameter in question exceeding the protection level at most once within a decade. The protection level can also be expressed as a unitless probability or ratio, i.e., the probability of an error occurring within a certain time interval.

[0017] Parameter estimation can essentially include one or more methods for estimating the (same) parameter. Preferably, at least one method is used to estimate the parameter, and it can also provide and / or determine integrity information about the completeness of the estimation or confidence information about the confidence level of the estimation result. For example, parameter estimation can be performed using a Kalman filter. In addition to the (original) estimation result, this typically provides confidence information about the parameter estimation (e.g., the covariance matrix), which can be used here to determine the range of completeness.

[0018] In step b), a validity metric is determined that describes the validity of the integrity range determined in step a). The validity metric can be binary (valid or invalid) or include various “digital intermediate states.” Possible “intermediate states” may, for example, indicate that a certain integrity risk number is currently applicable (e.g., 1e-3 in an urban scenario and 1e-5 on a highway). The validity metric may also include, for example, a (numerical) value describing the validity or reliability of the determined integrity range. This determination may, for example, include a combination of different (input) information, particularly different sensor information and / or status information (e.g., information about vehicle safety-related systems and / or diagnostic equipment from the vehicle). For example, the unavailability of at least one (input) piece of information can also have a (particularly negative) impact on the validity metric.

[0019] For example, an effectiveness index can be determined based on conditions or information, particularly those on the vehicle side and / or conditions or information outside the vehicle and / or information about the range of integrity. For example, vehicle-side conditions and / or vehicle-external conditions can help to more or less trust the determined range of integrity. Vehicle-side conditions or information may be, for example, information about a specific driving situation (e.g., longitudinal and / or lateral acceleration outside defined limits) and / or information about a specific vehicle state and / or the system state of a vehicle system (e.g., at least partial system failure and / or sensor failure). Vehicle-external conditions or information may be, for example, information about environmental influences, such as weather conditions and / or sensor occlusion. For example, (numerical) values ​​can be assigned to the corresponding conditions or information, which can be included in the determination of the effectiveness index if the corresponding conditions are present. If multiple conditions or pieces of information exist, they can be multiplied and / or added or logically connected to each other to calculate the effectiveness index.

[0020] In step c), the integrity range determined in step a) and the validity index determined in step b) are provided. Preferably, the determined integrity range and the determined validity index can be provided together. In this regard, these two pieces of information can be provided, for example, in the form of value pairs. This information can be provided, for example, to a vehicle system configured for self-localization of the vehicle. An example of such a system could be the vehicle's motion and position sensors and / or control devices for at least partially automated or autonomous driving of the vehicle. The system can, for example, determine whether, and if necessary, to use corresponding parameter estimates for position determination based on the determined integrity range and / or the determined validity index, particularly with what weight.

[0021] According to an advantageous design, based on sensor data from at least one of the vehicle's sensors, an integrity range is determined according to step a), and / or an effectiveness index is determined according to step b). The at least one sensor may include, for example, a GNSS sensor, which typically receives GNSS (Global Navigation Satellite System) data (e.g., GNSS correction data and / or GNSS position data) and provides GNSS data after (pre)processing, if necessary. The at least one sensor may alternatively or additionally include at least one environmental sensor. The at least one environmental sensor may be, for example, a camera, radar sensor, lidar sensor, and / or ultrasonic sensor. Furthermore, when determining the integrity range according to step a) and / or the effectiveness index according to step b), other (or alternative) sensor data and / or input data may be considered, such as sensor data regarding vehicle parameters (e.g., speed, acceleration, steering angle, etc.) and / or input data describing the vehicle's state, such as whether there are additional components connected to the vehicle, such as trailers, bicycle racks, etc.

[0022] According to another advantageous design, in step a), the completeness range is determined based on statistical confidence information regarding the parameter estimates. Statistical confidence information can be, for example, the variance and / or residuals of the parameter estimates. Alternatively, confidence information can also be information determined based on the variance and / or residuals and / or (other) indicators of the reliability of the estimates. Residuals, variance, covariance, etc., can be considered in particular as confidence information. Confidence information can be provided, for example, in the form of a covariance matrix or from a covariance matrix.

[0023] In particular, in this regard, the range of completeness can be, for example, a confidence interval. A confidence interval (also called a confidence range or expected range) is a range derived from statistics designed to indicate the accuracy of a location estimate of a parameter (e.g., the mean). A confidence interval represents the range that contains the true location of the parameter when a randomized experiment is repeated indefinitely with a certain probability (confidence level).

[0024] According to another advantageous embodiment, an effectiveness index is determined by using at least one piece of environmental information about the vehicle's surrounding environment. The environmental information may be provided, in particular, in the form of data from vehicle environmental sensors. These environmental sensors may be, for example, cameras, radar sensors, lidar sensors, and / or ultrasonic sensors.

[0025] According to another advantageous embodiment, an effectiveness metric is determined by using at least one state information regarding the state of the vehicle or its components. The state information may include, for example, information about the existence of a specific driving situation, such as longitudinal and / or lateral acceleration, particularly outside defined limits. The state information may also include, for example, information about the existence of a specific vehicle state (safety-related) and / or system state of the vehicle system, such as at least partial system malfunction and / or sensor malfunction.

[0026] According to another advantageous design, the effectiveness index is determined by using the integrity range identified in step a). Thus, the integrity range can, for example, influence the effectiveness index.

[0027] According to another advantageous design, the validity metric is provided as one value from a predetermined set of values. Thus, for example, specific validity levels can be preset, and it can be determined which validity levels currently exist or are present within the corresponding integrity range. This set of values ​​can, for example, be two, thus making the validity metric binary.

[0028] According to another aspect, a computer program for performing the methods described herein is also proposed. In other words, it particularly relates to a computer program (product) comprising instructions that, when a computer runs the program, cause it to perform the methods described herein.

[0029] According to another aspect, a machine-readable storage medium is also proposed, on which the computer program described herein is stored. A machine-readable storage medium is typically a computer-readable data carrier.

[0030] According to another aspect, a control device for a (motorized) vehicle is also proposed, wherein the control device is configured to perform the method described herein. The control device may, for example, be a device (or a computer) for vehicle self-positioning.

[0031] The control device may include, for example, an integrity module for determining the integrity range and an effectiveness module for determining an effectiveness index. These modules can be implemented essentially as physical components of the control device or as part of a computer program. The integrity module may be configured, for example, to determine the integrity range based on at least one confidence level. The confidence level can be estimated, for example, by a Kalman filter. The effectiveness module may be configured, for example, to determine the effectiveness index based on conditions or information, particularly those on the vehicle side and / or conditions or information outside the vehicle and / or the integrity range. For this purpose, the effectiveness module may include, for example, a combiner that can combine or (pre)process various information (e.g., conditions or information on the vehicle side and / or conditions or information outside the vehicle and / or information about the integrity range) into an effectiveness index, and then combine the processed information into an effectiveness index. The various information may include, for example, sensor data, at least one environmental information and / or at least one state information and / or at least one piece of information about the integrity range.

[0032] Furthermore, motor vehicles equipped with the control devices described herein are also proposed. The motor vehicle is essentially a car, preferably a car that is at least partially automated and / or autonomously operated, particularly an autonomous car.

[0033] Therefore, the details, features, and advantageous designs described in this method can also appear in the computer programs, storage media, control devices, and / or vehicles described herein, and vice versa. For this purpose, full reference is made to the explanations herein for a more detailed description of the features. Attached Figure Description

[0034] The solutions and their technical environment described herein are explained in more detail below with the aid of the accompanying drawings. It should be noted that the invention should not be limited to the embodiments shown. In particular, unless explicitly stated otherwise, certain aspects of the facts explained in the drawings may be extracted and combined with other drawings and / or other components and / or findings in this specification.

[0035] in:

[0036] Figure 1 An exemplary flow of the method described herein is illustrated schematically.

[0037] Figure 2 An exemplary structure of the control device described herein is schematically shown, and

[0038] Figure 3 An exemplary illustration of a vehicle having the control equipment described herein is shown schematically. Detailed Implementation

[0039] Figure 1An exemplary flow of the method described herein is illustrated schematically. This method is used to provide information 1, 2 regarding the reliability of parameter estimates of the operating parameters of vehicle 3. The order of method steps a), b), and c) shown by boxes 110, 120, and 130 generally follows the conventional operating flow. Steps a) and b) in particular can be performed at least partially in parallel or even simultaneously.

[0040] In box 110, according to step a), a completeness range 1 for the parameter estimation is determined, wherein completeness range 1 describes the range in which the estimated parameter with the minimum probability lies. In box 120, according to step b), an effectiveness index 2 is determined, which describes the effectiveness of the completeness range 1 determined in step a). In box 130, according to step c), the completeness range 1 determined in step a) and the effectiveness index 2 determined in step b) are provided.

[0041] Figure 2 An exemplary structure of the control device 8 described herein is schematically illustrated. The control device 8 is configured to perform the methods described herein. The control device 8 includes, for example, an integrity module 9 for determining an integrity range 1 (here, a protection level) and a validity module 10 for determining a validity metric 2. Here, these modules can essentially be implemented as physical components of the control device 8 or as part of a computer program.

[0042] Integrity module 9 is exemplarily configured to determine integrity range 1 based on at least one confidence information 5. The confidence information 5 can be estimated, for example, from a Kalman filter. In this regard, the confidence information 5 can be provided, for example, in the form of a covariance matrix or from a covariance matrix. The Kalman filter estimation can be based on sensor data from vehicle sensors. Thus, Figure 2 The following example is also illustrated, which shows how, in step a), based on the statistical confidence information 5 regarding the parameter estimation, the integrity range 1 can be determined, and if necessary, how to determine it.

[0043] The validity module 10 is exemplarily configured to determine a validity index based on conditions or information, particularly those on the vehicle side and / or conditions or information outside the vehicle and / or information regarding the integrity range 1. For this purpose, the validity module 10 may include, for example, a combiner 11, which can combine or (pre-)process various information (e.g., conditions or information on the vehicle side and / or conditions or information outside the vehicle and / or information regarding the integrity range 1) into a validity index 2, and then combine the processed information into the validity index 2. Various information may include, for example, sensor data 4, at least one environmental information 6, and / or at least one state information 7. Of course, other information may also be considered. The information may be generated by sensor 12 (see...). Figure 3 ) and / or Integrity Module 9 are provided.

[0044] thus, Figure 2 The following example is also illustrated: by using at least one piece of environmental information 6 about the surrounding environment of vehicle 3, the effectiveness index 2 can be determined, and if necessary, how to determine it. Furthermore, Figure 2 The following example is also illustrated: by using at least one state information 7 regarding the state of vehicle 3 or its components, the validity index 2 can be determined, and if necessary, how to determine it. Furthermore, Figure 2 The following example is also illustrated, showing how the validity index 2 can be determined, and if necessary, by using the integrity range 1 determined in step a).

[0045] Figure 3 An exemplary illustration of a vehicle 3 having the control device 8 described herein is shown schematically. The vehicle 3 also includes, for example, a plurality of sensors 12 that can provide data or information to the control device 8. This information may, for example, be environmental information 6 about the surrounding environment of the vehicle 3 and / or status information 7 about the state of the vehicle 3. Thus, Figure 3 The following example is also illustrated: based on sensor data 4 from at least one sensor 12 of vehicle 3, the integrity range 1 can be determined, and if necessary, according to step a), and / or the validity index 2 can be determined, and if necessary, according to step b). The validity index 2 can in particular be provided as a value from a predetermined set of values.

Claims

1. A method for providing information on the reliability of parameter estimates of operating parameters of a vehicle (3), comprising at least the following steps: a) Determine the protection level of the parameter estimate, wherein the protection level describes the range in which the estimated parameter with the minimum probability lies; b) Determine an effectiveness index (2) based on at least one condition of the vehicle, the effectiveness index (2) describing the effectiveness of the protection level determined in step a); c) Provide the protection level determined in step a) and the effectiveness index determined in step b) (2); The effectiveness index (2) is determined by means of a combiner (11) based on sensor data (4) from at least one sensor (12) of the vehicle (3) and the protection level. The vehicle is operated based on the parameter estimates, the determined protection level, and the determined effectiveness indicators. The at least one condition of the vehicle includes at least one of the following: the vehicle's longitudinal acceleration and / or lateral acceleration is outside the defined limits; at least part of the vehicle's system malfunctions and / or sensor malfunctions; weather conditions; or the vehicle's sensors are blocked.

2. The method according to claim 1, wherein the protection level is determined in step a) based on statistical confidence information (5) regarding the parameter estimation.

3. The method according to claim 1, wherein the sensor data (4) comprises: At least one piece of environmental information (6) about the surrounding environment of the vehicle (3).

4. The method according to any one of claims 1 to 3, wherein the sensor data (4) comprises: At least one status information (7) regarding the state of the vehicle (3) or its components.

5. The method according to any one of claims 1 to 3, wherein the effectiveness index (2) is provided as one of a predetermined set of values.

6. A computer program product having a computer program for performing the method according to any one of claims 1 to 5.

7. A machine-readable storage medium having a computer program stored thereon, the computer program being used to perform the method according to any one of claims 1 to 5.

8. A control device for a vehicle (3), wherein the control device (8) is configured to perform the method according to any one of claims 1 to 5.

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