WO2017162245A1

WO2017162245A1 - Device and method for assessing characteristic motion for a motor vehicle

Info

Publication number: WO2017162245A1
Application number: PCT/DE2017/200025
Authority: WO
Inventors: Gerrit Wischer; Simon Hachfeld; Tim Kreutzmann; Marc Fischer; Thomas Wichmann; Florian Gross; Emal Sadran
Original assignee: Conti Temic Microelectronic Gmbh
Priority date: 2016-03-21
Filing date: 2017-03-16
Publication date: 2017-09-28
Also published as: CN108885253A; DE102016204654A1; DE112017000482A5

Abstract

The present invention relates to a device (1) for assessing characteristic motion for a motor vehicle (100), said device (1) comprising: a sensor system (10) having at least one first sensor (10-1), a second sensor (10-2) and a vehicle dynamics sensor (10-A), the first sensor (10-1) being designed to generate first sensor data, the second sensor being designed to generate second sensor data and the vehicle dynamics sensor (10-A) being designed to generate initial characteristic motion data; a computer system (20) which is designed to provide a surroundings map (Kn) on the basis of the first sensor data and the second sensor data; and a calibration system (30) which is designed to compensate the initial characteristic motion data on the basis of temporal changes in the surroundings map, and thereby to provide corrected characteristic motion data.

Description

Apparatus and method for proper motion estimation for a

motor vehicle

Technical area

The present invention relates to driver assistance systems for motor vehicles. In particular, the present invention relates

Invention an apparatus and a method for

Eigen motion estimation for a motor vehicle.

Technical background

Currently, the self-motion estimation in motor vehicles is initially derived by driving dynamics, as derived for example from the wheel speed or a steering angle,

certainly .

Try the individual sensors of the motor vehicle

then, based on their own measurements, this

To optimize proper movement of the motor vehicle. One

Collected backflow of data and a central optimization of the measured proper motion does not take place.

Summary of the invention

It is an object of the present invention to provide a

An improved apparatus and method for self-motion estimation for a motor vehicle

provide.

This object is solved by the subject matters of the independent claims. Further developments and embodiments can be found in the dependent claims, the description and the figures of the drawings. A first aspect of the present invention relates to a self-motion estimation apparatus for a

A motor vehicle, the device comprising: a

Sensor device having at least a first sensor, a second sensor and a vehicle dynamics sensor, wherein the first sensor is configured to first

Generate sensor data, wherein the second sensor is configured to generate second sensor data, and wherein the vehicle dynamics sensor is adapted to initial

To generate own movement data; a computer device, which is designed to an environment map based on the first sensor data and based on the second

Provide sensor data; and a calibrator configured to based on temporal

Changes the first environment map and the second environment map to match the initial eigenmigration data and thereby provide corrected eigenmobility data. The present invention advantageously allows a

Optimization of the self-motion estimation. This can

for example, using a grid-based feature fusion or SLAM techniques, or "simulatanous localization and mapping," which involves sensing data from environmental sensors.

The term "feature" can define an environmental element or a detected object, as it can be imaged by an imaging or environmental sensor and can be noted in environment or environment maps These measurements can be generated by all imaginable sensor technologies for assistance systems sensors of the type radar, camera, laser, and ultrasound are used.

The present invention advantageously enables the

Self-motion by matching the data of each

Corresponding to the data of the other sensors to correct and thereby provide an optimized sensor data fusion, so that the data values of the individual

Cumulative sensors are processed in sync.

It can be an optimized and improved corrected

Self-motion or an improved self-localization are provided for the motor vehicle.

The present invention advantageously enables the

Accuracy of self-motion estimation to increase as an optimization of the sensor data and a merger takes place at a central or at least at a single point. For this purpose, the detected environmental elements, also called features, the individual sensors sent to this central point and at this central point these features are then centrally collected and evaluated centrally. The features or topographic objects or environmental elements can either be merged first or entered unfused in a grid, that is in an environment or environment map. Among other things, the performance or type properties of the sensor in the detection range of the respective features can be taken into account.

After all features have been entered into this grid, the grid will be the initial one from the previous measurements Eigenbewegung - for example, determined by the vehicle dynamics sensors - moved and it is assigned to the features from the current grid corresponding features of the previous grid.

In other words, a respective sensor generates sensor data, and based on this sensor data, a map can be continuously created. All or at least a plurality of sensors generate a common map.

The present invention advantageously makes it possible for the resulting feature pairs-corresponding features or corresponding topographic objects or corresponding environmental elements-to subsequently have a

Correction of the proper motion can be made and further driver assistance systems of the motor vehicle this corrected proper motion can be made available. The present invention advantageously allows for the use of the features of all sensors and the

Consider the location of these features in the

respective field of view of the corresponding sensor

Accuracy of self-motion estimation can be increased.

Furthermore, the central optimization of the

Self motion a single proper motion for all other functions or driver assistance systems of the

Motor vehicle used.

According to another, second aspect of the present

The invention provides a method for self-motion estimation for a motor vehicle, wherein the method

the following method steps comprises: generating first Sensor data through a first sensor and second

Sensor data by a second sensor and by initial intrinsic motion data by a vehicle dynamics sensor;

Providing an environment map based on the first sensor data and based on the second sensor data using a computing device; and matching the initials

Eigenmotion data based on temporal changes of the environment map by means of a calibration device and based on providing corrected

Proper motion data.

Advantageous embodiments of the present invention can be found in the dependent claims. In an advantageous embodiment of the present invention

The invention provides that the computer device is designed to map environmental elements on the environment map. This advantageously makes it possible to specifically note features, environmental elements or landmarks on the environment map and to use them for optimizing the self-motion estimation. To self-localization with the help of landmarks will

For example, a landmarks map is provided in which the ego vehicle is positioned.

In a further advantageous embodiment of the

The present invention provides that the

Calibration device is adapted to make the temporal changes of the environment map based on a comparison of at least two temporally successive environment maps. This allows advantageous, temporal

Changes in at least two consecutive

recorded environment maps and advantageous for to use the optimization of the Eigenbewegungsabschätzung, the two consecutively recorded environment maps, for example, a time interval in the form of a

Time span of 20 s or 10 s or before 1 s. In this case, the sensor device is designed to first

Sensor data, second sensor data and initial

Generate proper movement data corresponding to the time interval in the form of the period of 20 s or 10 s or before of 1.

In a further embodiment of the present invention, it is provided that the calibration device to

is formed, the comparison of temporally

successive environment maps by finding corresponding ones of the environmental elements.

This advantageously allows the optimization of

Perform own motion estimation based on identified and correspondingly identified features or features or topographic elements or environment elements. Thereby, the vehicle can advantageously detect a relative movement of the motor vehicle with respect to the environment. In a further advantageous embodiment of the

The present invention provides that the

Computer device is designed to take into account the performance of the first sensor and / or the second sensor when creating the environment map. This

allows advantageous that the environment map on the

technical conditions of the sensor takes into account.

In a further advantageous embodiment of the

The present invention provides that the Computing device is designed to be as to

considering performance of the first sensor and / or the second sensor a range or

Viewing field of the first sensor and / or the second sensor to be considered.

In a further advantageous embodiment of the

The present invention provides that the

Vehicle dynamics sensor is adapted to the initial

Generate self-motion data based on a wheel speed or steering angle or engine speed.

In a further advantageous embodiment of the

The present invention provides that the first sensor and / or the second sensor as an optical camera sensor or as an imaging radar sensor or as a

imaging sound or ultrasonic sensor or as an ultrasonic sensor or as a laser sensor are formed. The described embodiments and developments can be combined with each other as desired.

Other possible embodiments, developments and

Implementations of the present invention also include combinations of features of the present invention described above or below with respect to the embodiments which are not explicitly mentioned.

The accompanying drawings are intended to provide further understanding of the embodiments of the present invention.

The accompanying drawings illustrate

Embodiments and serve in connection with the Description of the explanation of concepts of the present invention.

Other embodiments and many of the stated advantages will become apparent with reference to the figures of the drawings. The illustrated elements of the figures of the drawings are not necessarily shown to scale to each other.

Brief description of the figures

Show it:

Fig. 1: a schematic representation of an apparatus for

Self-motion estimation for a motor vehicle according to an embodiment of the present invention

Invention;

2 shows a schematic representation of a flowchart of a method for self-motion estimation for a motor vehicle according to another

Embodiment of the present invention;

3 shows a schematic representation of a fusion of a first environment map and a second environment map for matching the initial ones

Eigenbewegungsdaten and for finding corresponding topographic elements or environmental elements according to another

Embodiment of the present invention.

Detailed description of the embodiments

In the figures of the drawings denote the same

Reference signs have the same or functionally identical elements, Components, components or method steps, unless stated otherwise.

The motor vehicle or vehicle is

for example, a motor vehicle or a

Hybrid vehicle, for example, a hybrid vehicle with

Sailing function, such as a motorcycle, a bus or a truck or a bicycle. Driver assistance systems are electronic auxiliary devices in motor vehicles to assist the driver in

certain driving situations.

For example, the device is for

Eigenbewegungsschätzung for a motor vehicle with a

Driver assistance system coupled, for example with a parking aid, a lane departure warning, a

Distance control, or a brake assist. Fig. 1 shows a schematic representation of a

Device for self-motion estimation for a motor vehicle 100.

The device 1 comprises a sensor device 10, a computer device 20 and a calibration device 30.

The sensor device 10 includes, for example, a first sensor 10-1, a second sensor 10-2 and a

Driving dynamics sensor 10-A.

The first sensor 10-1 is designed to generate first sensor data. The second sensor 10-2 is designed to generate second sensor data.

The vehicle dynamics sensor 10-A is designed to generate initial eigenmotion data.

The computer device 20 is designed to be a

Environment map Kl, K2, Kn based on the first

To provide sensor data of the first sensor 10-1 and based on the second sensor data of the second sensor 10-2.

The calibration device 30 is designed to adjust the initial eigenmotion data based on temporal changes of the environment map K1, K2, Kn and thereby to provide corrected eigenmobility data.

The first sensor 10-1, the second sensor 10-2 and the

Vehicle dynamics sensor 10-A are designed to continuously generate data, so that changes and temporal changes in the environment map Kl, K2, Kn can be represented, which is designed as an environment map.

In other words, the environment map Kn can also be understood as a temporal map field, so that

For example, in cycles, that is, after expiry of

predetermined periods of time, for example every 20 seconds or every 10 seconds or every second, a new, e.g. updated environment map Kn + 1 is generated, that is, a first

Environment map Kn and an updated second environment map Kn + 1 are generated within two cycles. FIG. 2 shows a schematic representation of a

Flow diagram for self-localization or

Self-motion estimation for a motor vehicle. As a first step of the method, a generation S1 of first sensor data by a first sensor 10-1, generation of second sensor data by a second sensor 10-2 and generation of initial proper movement data by a vehicle dynamics sensor 10-A are performed.

As a second step of the process takes place

Provide S2 from an environment map Kl, K2, Kn based on the first sensor data and based on the second sensor data by means of a computer device 20.

As a third step of the method, an adjustment S3 of the initial eigenmotion data takes place based on temporal changes of the environment map by means of a calibration device 30 and provision of corrected intrinsic motion data based thereon.

The corrected eigenmotion data can be used for more

Driver assistance systems of the motor vehicle such as a lane keeping assistance system or an automatic

Steering system or an automatic parking system can be used.

Fig. 3 shows a schematic representation of a

Fusion of a first environment map K1 and a second environment map K2 for the following, which is subsequently recorded in time

Matching the initial eigenmotion data and the

Finding corresponding topographic elements or environment elements according to another

Embodiment of the present invention. The first environment map K1 comprises, for example, a multiplicity of topographical elements or environmental elements PI, P2, Pn. For example, the first environment map K1 includes, as a neighborhood map, information of all available sensors.

The second environment map K2, temporally recorded, for example, 10 seconds later than the environment map K1

For example, a plurality of topographic elements or environmental elements Rl, R2, Rn.

The second environment map K2 includes, for example, as

Area Map Information from all available sensors. The calibration device 30 is designed to, based on temporal changes of the environment maps Kl, K2 the

initialize eigenmobility data and thereby provide corrected eigenmobility data. This can be done, for example, by finding

corresponding object pairs, PR1, PR2, PRn done.

Thereby, an initial motor vehicle position 100-1 can be corrected to a corrected motor vehicle position 100-K corresponding to the corrected proper motion data provided based on the initial proper motion data.

Although the present invention is based on preferred

Embodiments described above, it is not limited thereto, but modifiable in a variety of ways. In particular, the present invention can be varied in many ways or

modify without departing from the gist of the invention. In addition, it should be noted that "comprising" and "having" does not exclude other elements or steps, and "a" or "an" does not exclude a multitude.

It should also be appreciated that features or steps described with reference to any of the above embodiments may also be used in combination with other features or steps of others described above

Embodiments can be used. Reference signs in the claims are not to be considered as limiting.

Claims

Claims:

A device (1) for self-motion estimation for a motor vehicle (100), the device (1) comprising:

a sensor device (10) which has at least one first sensor (10-1), a second sensor (10-2) and a driving dynamics sensor (10-A), wherein the first one

Sensor (10-1) is adapted to generate first sensor data, wherein the second sensor (10-2) to

is configured to generate second sensor data, and wherein the vehicle dynamics sensor (10-A) is adapted to generate initial eigenmotion data;

- A computer device (20) which is adapted to an environment map (Kn) based on the first sensor data and the second sensor data

provide; and

- A calibration device (30), which

is designed to match based on temporal changes of the environment map (Kn) the initial eigenmigration data and thereby corrected

To provide proper movement data.

2. Device (1) according to claim 1,

wherein the computer device (20) is designed to map environmental elements on the environment map (Kn).

3. Device (1) according to claim 2,

wherein the calibration device (20) is adapted to make the temporal changes of the environment map (Kn) based on a comparison of at least two temporally successive environment maps (K (n), K (n + 1)).

4. Device (1) according to claim 3,

wherein the calibration device (20) is adapted to perform the comparison of the at least two temporally successive environment maps (K (n), K (n + 1)) by finding corresponding ones of the environmental elements.

5. Device (1) according to one of the preceding claims, wherein the computer device (20) is designed to create a performance of the first sensor (10-1) and / or of the second sensor (10-2) when creating the environment map (Kn). to take into account.

6. Device (1) according to claim 5,

wherein the computer means (20) is adapted to be the performance of the first one to be considered

Sensor (10-1) and / or the second sensor (10-2) a

Range or a field of view of the first sensor (10-1) and / or the second sensor (10-2) to be considered.

7. The device according to claim 1, wherein the vehicle dynamics sensor is configured to generate the initial proper motion data based on a wheel speed or a steering angle or an engine speed.

8. Device (1) according to one of the preceding claims, wherein the first sensor (10-1) and / or the second sensor (10- 2) as an optical camera sensor or as an imaging radar sensor or as an imaging sound sensor or as an ultrasonic sensor or formed as a laser sensor.

9. Motor vehicle (100) comprising a device (1) according to one of the preceding claims.

10. A self-motion estimation method for a motor vehicle (100), the method comprising

Process steps include:

Generating (S1) first sensor data by a first sensor (10-1), second sensor data by a second sensor (10-2) and initials

Self-motion data by a vehicle dynamics sensor (10-A);

Providing (S2) from an environment map (Kn)

based on the first sensor data and on the second sensor data by means of a computer device (20); and

- Matching (S3) the initial proper movement data based on temporal changes of the environment map (Kn) by means of a calibration device (30) and providing thereon corrected

Proper motion data.