DE102022200150A1 - Method for checking the plausibility of data from at least one environment sensor or a GNSS receiver of a vehicle - Google Patents

Abstract

The invention relates to a method for checking the plausibility of data from at least one environment sensor (2) or a GNSS receiver (3) of a vehicle (1) using at least one piece of GNSS-based information and one piece of sensor information, comprising at least the following steps: a) detecting at least one GNSS -based information, which allows conclusions to be drawn about the presence and/or the degree of local impairment of the GNSS reception situation, using at least one GNSS receiver (3) of the vehicle (1),b) detecting at least one piece of sensor information using at least one Environment sensor (2) of the vehicle (1), c) plausibility of data from the at least one environment sensor (2) or the at least one GNSS receiver (3) using the at least one GNSS-based information and the at least one sensor information.

Description

The invention relates to a method for checking the plausibility of data from at least one environment sensor or a GNSS receiver of a vehicle. Furthermore, a computer program, a machine-readable storage medium and a localization device for a vehicle are specified. The invention can be used in particular in connection with at least partially automated or autonomous driving.

State of the art

GNSS (Global Navigation Satellite System) receivers are used today in a variety of technological solutions, including GNSS positioning (for example in combination with maps) and timing applications. Their technology enables the precise calculation of the absolute position, speed, time and orientation using navigation satellite data (e.g. GPS, GLONASS, Beidou, Galileo) and is therefore often used in the automotive industry.

The GNSS systems essentially consist of a space, a ground and a user segment. The space segment includes several GNSS satellites that emit electromagnetic waves that contain a special code that allows these signals to be tracked accurately. This code is received by the GNSS receiver (user segment) and can be used in two ways. First, by tracking the signal, the GNSS receiver can determine the time of flight of the signal. In addition, the broadcast signal contains information about the satellite orbits. This information can be used by the GNSS receiver to determine the position.

GNSS receivers are often used in combination with other sensors (e.g. inertial or wheel speed sensors). The use of the additional sensors improves the navigation system. A combined navigation system with inertial sensors is able to calculate the orientation in three dimensions (yaw, roll and pitch) and, together with the position and speed, provides complete information about the position, speed and attitude (orientation) of the vehicle . This information can be provided with an advantageously high level of precision and reliability, particularly in the case of high-quality, safety-relevant GNSS/INS receivers, such as those intended to be used for autonomous driving, for example.

Self-driving or autonomous vehicles should work reliably under as many conditions as possible (bad weather, optical interference, dirt on the camera, etc.). Since the vehicle view is often based on the vehicle's surroundings sensors, such as LIDAR sensors and/or RADAR sensors, the environmental conditions usually represent a significant factor for the reliability of the measured values of these sensors. In particular, there are a comprehensive introduction of autonomous driving thus high demands on the reliability of corresponding environment sensors.

Proceeding from this, there is an effort to improve the reliability of data from surroundings sensors of vehicles.

Disclosure of Invention

1. a) Erfassen mindestens einer GNSS-basierten Information, welche einen Rückschluss auf das Vorhandensein und/oder den Grad einer lokalen Beeinträchtigung der GNSS-Empfangssituation erlaubt, unter Verwendung mindestens eines GNSS-Empfängers des Fahrzeugs,
2. b) Erfassen mindestens einer Sensorinformation unter Verwendung mindestens eines Umfeldsensors des Fahrzeugs,
3. c) Plausibilisieren von Daten des mindestens einen Umfeldsensors oder des mindestens einen GNSS-Empfängers unter Verwendung der mindestens einen GNSS-basierten Information und der mindestens einen Sensorinformation.

According to claim 1, a method is specified here for checking the plausibility of data from at least one surroundings sensor or a GNSS receiver of a vehicle using at least one piece of GNSS-based information and one piece of sensor information, comprising at least the following steps:

1. a) detecting at least one piece of GNSS-based information, which allows conclusions to be drawn about the presence and/or the degree of a local impairment of the GNSS reception situation, using at least one GNSS receiver of the vehicle,
2. b) detecting at least one item of sensor information using at least one environment sensor of the vehicle,
3. c) Validation of data from the at least one environment sensor or the at least one GNSS receiver using the at least one GNSS-based information item and the at least one sensor information item.

To carry out the method, steps a), b) and c) can be carried out, for example, at least once and/or repeatedly in the order given. Furthermore, steps a), b) and c), in particular steps a) and b), can be carried out at least partially in parallel or simultaneously. The method can be used in particular (specifically) in urban areas, in particular in urban canyons.

The method described serves in particular to increase the reliability of data from surroundings sensors of vehicles. The method can be used, for example, during and in particular to improve a GNSS-based localization of the vehicle. GNSS stands for Global Navigation Satellite System Example GPS (Global Positioning System) or Galileo. In the case of GNSS-based localization, other GNSS-independent sensors of the vehicle, such as environmental sensors and/or inertial sensors, can also be used in order to be able to provide alternative information for the localization of the vehicle in addition or as required (e.g. in the case of GNSS shadowing). In particular, the current (own) position, (own) orientation, (own) speed and/or (own) acceleration of the vehicle can be determined for localization.

The vehicle is preferably a motor vehicle, such as an automobile, which is particularly preferably set up for automated or autonomous (driving) operations. In addition to at least one GNSS receiver, a large number of environment sensors can be used in corresponding vehicles (for example: RADAR sensors, LIDAR sensors, camera sensors, ultrasonic sensors). These environment sensors can be used, for example, to detect objects around the vehicle and to localize them with respect to the vehicle. In addition, environmental sensor data and/or GNSS data can be used, for example, to locate the vehicle on a (highly accurate) digital map. Based on the detected objects or determined vehicle positions, a trajectory can be planned and, if necessary, the vehicle actuators can be controlled accordingly for the execution of (automated or autonomous) driving operations. In this way, the vehicle can advantageously safely navigate through the environment.

In step a), at least one piece of GNSS-based information is recorded, which allows conclusions to be drawn about the presence and/or the degree of a local impairment of the GNSS reception situation, using at least one GNSS receiver of the vehicle. The GNSS receiver can be part of or connected to a GNSS sensor and/or a localization device of the vehicle. In this context, for example, an availability of code and/or Doppler measurements for all or for at least one (specific) GNSS satellite can serve as GNSS-based information. Alternatively or additionally, phase measurements, estimated variances, standard deviations and/or residuals of the GNSS determinations can be used.

In step b), at least one item of sensor information is detected using at least one environment sensor of the vehicle. The environment sensor can be, for example, a LIDAR sensor, RADAR sensor, ultrasonic sensor or an optical sensor such as a camera. The sensor information can contribute, for example, to sensing or recognizing an object in the area surrounding the vehicle. In particular, the distance from the object can be measured. For example, the sensor information can relate to a reflected and re-received sensor signal or can be determined on the basis thereof. The sensor signal can, for example, be emitted by the surroundings sensor and reflected by an object in the surroundings of the vehicle. The object can be, for example, a building, such as a high-rise building or part of a canyon of houses. Furthermore, large vehicles such as trucks or buses can also be sensed or recognized. In particular, the sensor information can allow conclusions to be drawn about the particular local and/or instantaneous shadowing of all or at least one (specific) GNSS satellite. Shadowing describes a state in which a direct line of sight from the vehicle to the relevant satellite is at least partially blocked. Shadowing of all GNSS satellites can be observed in a tunnel, for example. The shadowing of individual GNSS satellites can be observed, for example, when driving through a street canyon or when driving past a truck.

In step c), data from the at least one environment sensor or from the at least one GNSS receiver is checked for plausibility using the at least one piece of GNSS-based information and the at least one piece of sensor information. In this case, for example, the at least one piece of GNSS-based information and the at least one piece of sensor information can be compared. If both (at the same reception position and/or reception time) allow conclusions to be drawn about the presence and/or the degree of local impairment of the GNSS reception situation, this information about the consistency of the two pieces of information can be used to check the plausibility of one or both data sources (environment sensor and GNSS receiver) are used.

According to an advantageous embodiment, it is proposed that the at least one piece of GNSS-based information allows conclusions to be drawn about the presence and/or the degree of local impairment of the visibility of at least one available GNSS satellite. Visibility usually describes (in contrast to shadowing) a state in which there is a direct line of sight from the vehicle to the relevant satellite.

In particular, using the GNSS receiver, a possibly turned on limited satellite visibility of the vehicle's GNSS antenna can be determined or measured as the current GNSS reception situation or the current GNSS reception situation "open sky". The comparison of this information with an environment sensor measurement, such as a lidar/radar measurement, enables a reliability check for all three sensors (in particular lidar/radar) in a particularly advantageous manner and thus advantageously additional safety mechanisms that are advantageously used in particular in self-driving vehicles can.

For example, various mechanisms or algorithms for detecting the current GNSS reception situation, in particular for checking whether an “open sky” or a “restricted view” are present, can be used in the method. Particularly advantageous mechanisms or algorithms are described below. These can particularly advantageously contribute to detecting the at least one GNSS-based information, which allows conclusions to be drawn about the presence and/or the degree of a local impairment of the GNSS reception situation, using the at least one GNSS receiver of the vehicle.

For example, an availability of code and/or Doppler measurements can be determined for all or for at least one (specific) GNSS satellite. A GNSS receiver will typically also receive almanac data (as an example of the satellite position data below). The almanac data usually describes a list of all satellites that are in the sky with an exact position in the absolute coordinate system. This information can be converted into a local coordinate system of the vehicle. In particular, the GNSS receiver can track multiple satellite constellations (e.g., three constellations). Thus, for example, the GNSS receiver can acquire information about the position of more than thirty GNSS satellites distributed over the sky relative to the GNSS antenna. For example, if the GNSS receiver is unable to track one or more of the available GNSS satellites, it may be due to limited satellite visibility in certain parts of the sky due to blocking external objects (buildings, bridges, tunnels, mountains, etc.). This approach can be used advantageously in the case of partial (e.g. urban canyon) and total loss (tunnel, bridge) of satellite visibility.

The information thus gathered that something is obstructing the view of one or more specific satellites (the exact position in the sky relative to the vehicle is known based on GNSS/INS positioning and almanac/ephemeris data) can be used with the Sensor information, such as being compared to lidar/radar readings. Based on this, it can be checked whether these two sources of information are consistent and therefore advantageously reliable. This implementation check can advantageously increase the confidence in, for example, lidar/radar measurements. A positive consistency check can in principle increase both confidence in the environment sensor and confidence in the GNSS positioning.

• - Verfügbarkeit von Phasenmessungen,
• - Geschätzte Standardabweichung der Gesamtlösung,
• - Geschätzte Standardabweichung der GNSS-Messungen, und/oder
• - Residuen aus der GNSS-Positionsberechnung (z. B. für Doppler-, Code- und Phasenmessungen).

Furthermore, for example phase measurements, estimated variances, standard deviations and/or residuals of the GNSS determination/GNSS solution can contribute to the identification of the current GNSS reception situation. In addition to the direct satellite visibility, other or further aspects can also indicate an external object that blocks the line of sight between the antenna and the satellite. These include in particular:

• - availability of phase measurements,
• - Estimated standard deviation of the total solution,
• - Estimated standard deviation of the GNSS measurements, and/or
• - Residuals from the GNSS position calculation (e.g. for Doppler, code and phase measurements).

The aforementioned indicators can advantageously signal that there is an additional or external object that is obstructing a good satellite view. The variances of the observations and the estimated position (e.g. using a Kalman filter) can provide information about the security of the observation and position solution. These can be used as an indicator for a limited satellite visibility scenario. The residuals can indicate the remaining error after calculation for each individual satellite measurement. A high error, especially in Doppler, may indicate an external object blocking direct satellite visibility (for example, signage).

According to a further advantageous embodiment, it is proposed that the at least one piece of GNSS-based information allows conclusions to be drawn about the presence of an external object that is blocking a direct line of sight between the GNSS receiver and at least one available GNSS satellite. A corresponding direct line of sight is generally also described in GNSS technology as a “line of sight” (LOS for short).

The availability of the GNSS satellite can preferably be determined using known satellite position data. The satellite position data are known, for example, because they are communicated to the GNSS receivers or GNSS sensors, in particular at regular time intervals, via data communication channels such as satellite broadcast and/or (mobile) radio. The satellite position data can be provided in the form of almanac data and/or ephemeris data, for example.

According to an advantageous embodiment, it is proposed that the at least one piece of sensor information allows conclusions to be drawn about the presence of an external object in the area around the vehicle. The external object can be, for example, an obstacle such as a building, a truck or a bus.

According to an advantageous embodiment, it is proposed that the surroundings sensor be a LIDAR sensor or RADAR sensor. LIDAR is an abbreviation for the English technical term "light detection and ranging" or "light imaging, detection and ranging". RADAR is an abbreviation for the English technical term "radio detection and ranging".

According to an advantageous embodiment, it is proposed that in step c) a plausibility check of sensor data of the at least one environment sensor is carried out using the at least one GNSS-based information and the at least one sensor information. The method can thus be used particularly advantageously to check the plausibility of LIDAR and/or RADAR sensors.

According to an advantageous embodiment, it is proposed that in step c) it is checked whether both pieces of information, the at least one piece of GNSS-based information and the at least one piece of sensor information, allow a conclusion to be drawn about the presence of an external object in the area surrounding the vehicle. This is usually checked at the same receiving position and/or receiving time.

In a particularly advantageous embodiment, the method thus enables the functionality of a GNSS-based “open sky” detector for the plausibility check of the lidar and/or radar data for autonomous driving in particular. In particular, the method can contribute to the implementation of a GNSS-based "open sky" detector. In this context, the method serves in particular to check the plausibility of lidar/radar measurements or lidar/radar data. The method can use code and/or phase and/or Doppler measurements, for example, in order to recognize the “open sky” state and thus to verify the implementation of the lidar/radar measurements. Since the GNSS receivers work on a different physical principle than lidar/radar, they do not have the same limitations as these two sensors. This allows a particularly advantageous option for checking the plausibility of the lidar/radar measurements.

Furthermore, a computer program for carrying out a method described here can also be specified. In other words, this relates in particular to a computer program (product), comprising instructions which, when the program is executed by a computer, cause the latter to execute a method described here.

A machine-readable storage medium on which the computer program is stored can also be specified. The machine-readable storage medium is usually a computer-readable data carrier.

According to a further aspect, a localization device for a vehicle is proposed, the localization device being set up to carry out a method described here. The localization device can, for example, comprise a computer and/or a control unit (controller) which can execute commands in order to carry out the method. For this purpose, the computer or the control device can, for example, execute the specified computer program. For example, the computer or the control unit can access the specified storage medium in order to be able to run the computer program. The localization device can be, for example, a movement and position sensor that is arranged in particular in or on the vehicle.

The details, features and advantageous configurations discussed in connection with the method can accordingly also occur in the computer program presented here, the storage medium and/or the localization device and vice versa. In this respect, full reference is made to the statements there for a more detailed characterization of the features.

• 1: einen beispielhaften Ablauf eines hier vorgestellten Verfahrens,
• 2: einen beispielhaften Anwendungsfall des hier vorgestellten Verfahrens,
• 3: einen weiteren beispielhaften Anwendungsfall des hier vorgestellten Verfahrens, und
• 4: eine weitere Darstellung des Anwendungsfalls aus 3.

The solution presented here and its technical environment are explained in more detail below with reference to the figures. It should be pointed out that the invention should not be limited by the exemplary embodiments shown. In particular, unless explicitly stated otherwise, it is also possible to use partial aspects of the To extract facts explained figures and to combine them with other components and / or findings from other figures and / or the present description. They show schematically:

• 1 : an example of a procedure presented here,
• 2 : an example application of the method presented here,
• 3 : another exemplary application of the method presented here, and
• 4 : another representation of the use case 3 .

1 shows a schematic of an exemplary sequence of a method presented here. The method is used to validate data from at least one surroundings sensor 2 or one GNSS receiver 3 of a vehicle 1 using at least one piece of GNSS-based information and one piece of sensor information (cf. 2 , 3 and 4 ). The sequence of steps a), b) and c) represented by blocks 110, 120 and 130 is exemplary and can run at least once in the sequence shown in order to carry out the method.

In block 110, according to step a), at least one piece of GNSS-based information is detected, which allows conclusions to be drawn about the presence and/or the degree of local impairment of the GNSS reception situation, using at least one GNSS receiver 3 of the vehicle 1.

In block 120, according to step b), at least one item of sensor information is detected using at least one surroundings sensor 2 of vehicle 1.

In block 130, according to step c), data from the at least one surroundings sensor 2 or from the at least one GNSS receiver 3 is checked for plausibility using the at least one piece of GNSS-based information and the at least one piece of sensor information.

2 shows a schematic of an exemplary application of the method presented here. The situation 2 shows an example of limited satellite visibility of the satellite 4 shown on the right. Its GNSS signal 7 is blocked by the object 5 on the right. In contrast, there is a direct line of sight to the satellites 4 shown in the middle, which lie within the entered elevation angle range 6 .

For example, the GNSS receiver 3 knows from the almanac data that the satellite 4 shown on the right is also in the sky (with a precise position in the absolute coordinate system). If it cannot be located according to code, Doppler and/or phase, it can be concluded that this satellite 4 is blocked by an external object 5.

This represents an example of how the at least one piece of GNSS-based information can allow conclusions to be drawn about the presence and/or the degree of local impairment of the visibility of at least one available GNSS satellite 4 . Furthermore, this also represents an example that and possibly how the at least one piece of GNSS-based information allows a conclusion to be drawn about the presence of an external object 5 that blocks a direct line of sight between the GNSS receiver 3 and at least one available GNSS satellite 4 . In addition, this illustrates by way of example that and possibly how the availability of the GNSS satellite 4 can be determined using known satellite position data, namely almanac data.

Thus, if the GNSS receiver 3 is unable to track one or more of the available GNSS satellites 4, the vehicle 1 may conclude that something is blocking the "visibility" of that satellite 4 from the GNSS receiver 3's view. This information can be used advantageously to check the implementation of lidar/radar measurements (there is a blocking object).

3 shows a schematic of another exemplary application of the method presented here. 4 shows a further representation of the application 3 .

In 3 it can be seen that the GNSS receiver 3 cannot track the satellite 4 due to an object 5 or obstacle along the line of sight 8 (in particular cannot receive its signal, at least not directly). However, the satellite position in the sky is known from almanac data.

Vehicle 1 also has an environment sensor 2, which can be a LIDAR sensor or RADAR sensor, for example. In 4 it is illustrated that the obstacle or object 5 can also be detected by means of lidar/radar. For this purpose, for example, a sensor signal 9 can be reflected on the object 5 and then measured again. This represents an example of how the at least one piece of sensor information can allow conclusions to be drawn about the presence of an external object 5 in the area surrounding vehicle 1 .

If the two pieces of information or measured values from the GNSS receiver and the lidar/radar sensor match, for example, it is possible to conclude that both data are valid.

Tracking information (no maps) from a GNSS receiver 3 can thus advantageously be used in order to enable an advantageous feasibility test for lidar/radar measurements. If the GNSS receiver tracking information and lidar/radar measurements (e.g. clear skies or an obstacle is in the way) are consistent, this can be an indication that both systems are working correctly. In the event of a discrepancy, this can be an indication that at least one of the systems, in particular the surroundings sensor 2, is not working correctly.

This represents an example of the fact that, and if necessary as in step c), it can be checked whether both pieces of information, the at least one piece of GNSS-based information and the at least one piece of sensor information, each allow a conclusion to be drawn about the presence of an external object 5 in the area around the Allow vehicle 1. Furthermore, this also represents an example of the fact that and possibly as in step c), a plausibility check of sensor data of the at least one environment sensor 2 can be carried out using the at least one GNSS-based information and the at least one sensor information.

Furthermore, in the 3 and 4 a localization device 10 for a vehicle 1 is also illustrated. The localization device 10 is set up to carry out the method described here.

Through the plausibility check described, the method advantageously contributes to improving the reliability of data from surroundings sensors of vehicles.

Claims (11)

Method for checking the plausibility of data from at least one environment sensor (2) or a GNSS receiver (3) of a vehicle (1) using at least one piece of GNSS-based information and one piece of sensor information, comprising at least the following steps: a) detecting at least one piece of GNSS-based information which allows conclusions to be drawn about the presence and/or the degree of a local impairment of the GNSS reception situation, using at least one GNSS receiver (3) of the vehicle (1), b) detecting at least one item of sensor information using at least one environment sensor (2) of the vehicle (1), c) plausibility checking of data from the at least one environment sensor (2) or the at least one GNSS receiver (3) using the at least one GNSS-based information item and the at least one sensor information item. procedure after claim 1 , The at least one piece of GNSS-based information allowing a conclusion to be drawn about the presence and/or the degree of a local impairment of the visibility of at least one available GNSS satellite (4). procedure after claim 1 or 2 , The at least one piece of GNSS-based information allowing a conclusion to be drawn about the presence of an external object (5) blocking a direct line of sight between the GNSS receiver (3) and at least one available GNSS satellite (4). procedure after a claims 2 or 3 , wherein the availability of the GNSS satellite (4) is determined using known satellite position data. Method according to one of the preceding claims, wherein the at least one piece of sensor information allows conclusions to be drawn about the presence of an external object (5) in the area surrounding the vehicle (1). Method according to one of the preceding claims, in which the surroundings sensor (2) is a LIDAR sensor or RADAR sensor. Method according to one of the preceding claims, wherein in step c) a plausibility check of sensor data of the at least one surroundings sensor (2) is carried out using the at least one GNSS-based information and the at least one sensor information. Method according to one of the preceding claims, wherein in step c) it is checked whether both pieces of information, the at least one GNSS-based piece of information and the at least one piece of sensor information, each indicate the presence of an external object (5) in the area around the vehicle ( 1) allow. Computer program for carrying out a method according to one of the preceding claims. Machine-readable storage medium on which the computer program claim 9 is saved. Localization device (10) for a vehicle (1), set up to carry out a method according to one of Claims 1 until 8th .

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